Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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1. Introduction
Hydrocarbon steam cracking is the most important process for producing industrial chemicals such as olefin and aromatics. Mathematical models for steam cracking simulation have been studied for several decades and various models have been developed such as SPYRO [1] and COILSIM [2]. Meanwhile, the steam cracking model can be applied to the steam furnace design and optimization [3]. As various feedstock and furnaces are used in steam cracking, a more accurate and robust model is needed.
A mathematical model is a collection of relations among variables representing certain properties of a system, using equations and inequalities. By solving a model, one can predict the values of some properties of the system, given the values of some other properties, or predict the distributions of the values of some properties in particular domains, given certain boundary conditions. To meet the scientific and engineering demands in terms of revealing the characteristics of a system in-depth, a mathematical model may involve relations of properties at different scales of the system [4], referred to as a multi-scale model. The multi-scale model often consists of nonlinear equations and differential equations, and is not easy to solve. The information communication between scales is the key factor in multi-scale models [5]. In recent years, multi-scale modelling has been applied in all fields of chemical engineering such as thermodynamics, reaction engineering, polymer materials and CFD (computational fluid dynamics), among others. Multi-scale modelling is used in steam cracking models to reveal the nature of steam cracking and to establish a more accurate and robust model.
The kernel part of the steam cracking model is the reaction network. Researchers have developed various reaction models to describe the steam cracking process. There are three different types of reaction models: empirical models, molecular models and elementary reaction models. Empirical models use a large database of experimental results to regress a number of empirical correlations for the yields of the main products as a function of a number of easily measurable process variables [6]. Empirical reaction models need a large number of experiment data to render a regression. Once the feedstock or the furnaces change, the reaction model has to be re-established to obtain accurate simulation results. On the basis of empirical reaction models, molecular reaction models have been developed and frequently used [7-9], e.g., the Kumar reaction model [10]; 22 molecular reactions are involved in Kumar’s reaction model: one primary reaction and 21 secondary reactions. The primary reaction is shown as eq. (1). The selective coefficients of the primary reaction (a1~a10) have been regressed from experimental data. If the feedstock or operating conditions change, the selective coefficients of the primary reaction should be regressed again.
Nowadays, elementary reaction models have been widely used to develop a more reliable and robust mathematical model. Since the pioneering work of Rice [11-13] there has been a general consensus about the elementary reaction mechanism. As the mathematical difficulties encountered for solving the detailed kinetic models can be overcome by the development of stiff solvers [14], detailed elementary reaction networks are widely used to accurately describe chemical processes in a wide range of process conditions and feedstock. Sundaram et al. [15] established a radical reaction model for the pyrolysis of simple paraffins, olefins and their mixtures. Scharfe et al. [16] established a radical reaction model for n-hexane pyrolysis. Joo et al. [17] established a radical reaction model for industrial naphtha cracking furnaces.
However, it has remained problematic to generate thousands of elementary reactions and to determine the reaction rate constants of these reactions until an automatic reaction network generation technique was studied. Today, computers are used not only to solve the simulation numerically, but also to generate the elementary reaction network, construct the model and calculate the kinetic parameters [2]. Many research groups have developed computer tools for automatically generating these mechanisms [18-23] such as RMG [24] and CRACKSIM [25]. The elementary reaction model is expected to be used in furnace design and operating condition optimization. However, the huge number of reactions in the elementary reaction network usually requires significant CPU time during simulation. Thus, the steam cracking simulation model has to be reduced before it can be used in operating condition optimization, in order to make real-time optimization (RTO) realistic.
There are multiple methods for creating model reduction. In terms of chemistry, quasi-steady-state approximation (QSSA) [26], reaction rate analysis [27] and reaction path analysis [28], among others, can be used to reduce a reaction model. In terms of mathematics, principle component analysis [29] and sensitivity analysis [30] can also be used. On the other hand, data driven methods can also be used in model reduction, for example, the black box model, a neural network [31] and PCA based ROMs [32]. Several assumptions can also be applied to help retain the mechanism at a manageable size. The most important assumption is the μ radical hypothesis, which assumes that bimolecular reactions can be neglected for radicals with more than five carbon atoms [33]. The latter are also referred to as μ radicals. Thus, the QSSA method can be applied to remove μ radicals from the reaction network.
A multi-scale model for the steam cracking process is established in this chapter. The multi-period steam cracking process is also studied in the context of the established multi-scale model. Coking is an unavoidable factor during the multi-period steam cracking process. Coking increases pressure drops in the reaction tube, decreases the coefficient of heat transfer between the furnace and tube, and most importantly, increases the outer-wall temperature of the tubes. If one of the tubes in the furnace reaches the maximum allowance temperature of the tube material, the furnace must be shut down to execute a decoking process, otherwise the tube will be destroyed. The operation conditions are generally maintained constant during the long-term steam cracking process. Thus, dynamic operating conditions need to be optimized using a detailed steam cracking model in order to achieve a higher profit. Abel et al. [34] used the SQP method to solve a real-time optimization problem in the olefins production process. Tarafder et al. [35] proposed a multi-objective optimization problem in the operation and design of a styrene manufacturing process. Li et al. [36] applied an artificial neural network (ANN) hybrid model in the operation optimization of a naphtha industrial cracking furnace. Gao et al. [3] used a new parallel hybrid algorithm combining NSGA-II with SQP on multi-objective optimization for the periodic operation of the naphtha pyrolysis process. However, due to the complexity of the elementary reaction model, the researchers did not use this reaction model in the optimization problem. In this chapter, an elementary reaction model is applied to the operating condition optimization problem to obtain a more reliable optimization result. Based on this, a surrogate coke thickness model is proposed to make multi-period optimization with parallel simulation possible.
The general idea of this chapter is outlined in Figure 1. The first step in the conceptual development of a detailed molecule-based model for a complex feedstock is to determine an accurate molecular representation of the feedstock. Then, a multi-scale steam cracking model is established following the feedstock prediction. Finally, operating condition optimization of multi-period steam cracking is carried out using the established multi-scale model.
Figure 1.
Diagram of simulation and optimization of the steam cracking process methodology
This chapter is structured as follows. Section 2 offers a detailed discussion of the establishment of the multi-scale steam cracking model; a case study for naphtha steam cracking simulation is presented. Section 3 provides the operating condition optimization model; surrogate coke thickness model and parallel simulation are used to accelerate the computing of the optimization model. A case study of operating condition optimization is presented and the results are presented and discussed. Finally, section 4 offers conclusions from this study.
2. Steam cracking model
2.1. Multi-scale model for steam cracking
A multi-scale model is proposed in this chapter to reveal the nature of the steam cracking process and to generate a reliable and robust model for accurately predicting the yields of products. The multi-scale model is built up from the molecular level, to the reaction level to the process level. The establishment of the multi-scale model is discussed in detail in the following sections.
Feedstock composition prediction
Conventional analytical techniques are generally incapable of directly measuring the identities of all the molecules in complex feedstock, especially for the high carbon number range; however, this applies only to indirect characteristics [37]. Here, the Shannon entropy method [38] and probability density function were used to predict detailed feedstock composition, based on the analytical data. A detailed model for feedstock composition prediction can be found in [39]. The objective function of this NLP (non-linear programming) problem is shown in eq. (2), where S(x) is Shannon entropy and xi is the mole fraction of component i.
maxS(x)=−∑i=1nxilnxiE2
\n\t\t\t\t
Figure 2 shows the predicted feedstock composition using Shannon entropy, compared with the experimental data. The predicted results show the effectiveness of the Shannon entropy theory in obtaining the missing information for models of the steam cracking process.
Figure 2.
Comparison of experimental and calculated feedstock component mole fractions [39].
Process-level model
A process-level model consists of mass balance equations, momentum balance equation and energy balance equation (eqs. (3-5)) [40, 41]. For the simulation of smooth tubular reactor types, the use of a one-dimensional reactor plug-flow model is generally recognized as providing a sufficient degree of accuracy, as all radical profiles are wiped out due to the high turbulence corresponding to Reynolds numbers of over 250 000. The plug-flow reactor model implicitly assumes that there is no mixing in the axial direction, but rather, perfect mixing in the transverse direction [2].
dNmdL=SV∑iνi,mri=fN(T,P,Nm)E3
\n\t\t\t\t
dPdL=−f⋅E(L)⋅G25.07×ρ⋅Di×104=fP(T,P,Nm)E4
\n\t\t\t\t
dTdL=kπDo(Tw−T)−∑mΔHfm0⋅dNmdL∑mcpmNm=fT(T,P,Nm)E5
\n\t\t\t\t
In eq. (3), Nm is the concentration of species m and L is the length of the reactor tube. S is the flow area, V is the volume flow rate, μim is the stoichiometric coefficient of reaction i and ri is the reaction rate of reaction i. In eq. (4), P is the pressure of the mass flow, f is the Fanning friction factor, E(L)=Le/L, Le is the equivalent length of the reactor tube, G is the mass flow rate, Di is the internal diameter of the tube and ρ is the density of the gas mixture. In eq. (5), T is the temperature of the mass flow, Do is the outer diameter of the tube, k is the overall heat transfer coefficient, Tw is the outer wall temperature of the tube, ΔHfm0 is the standard heat of formation of species m and cpm is the specific heat of species m.
It should be noted that the measuring point of the COT (coil-outlet temperature) of an industrial furnace is usually on the outer wall of the tube. Thus, the measured COT has a temperature difference from the outlet temperature of the gas mixture. Eq. (6) has been derived from heat balance equations in order to adjust to the temperature difference; the results show that there exists a 15-20K temperature difference, which agrees well with what has previously been reported.
In eq. (6), λisolation is the heat transfer coefficient of the isolation layer. Tisolation_o is the outer wall temperature of the isolation layer, ro is the external diameter of the tube, ri is the interior diameter of the tube, disolation is the thickness of isolation layer, dcoke is the thickness of coke and αmixture is the heat transfer coefficient of the gas mixture in the tube.
Reaction-level model
The reaction model is the most important part of the steam cracking model. Many researchers have conducted in-depth studies on the elementary reaction model. An elementary reaction model can contain thousands of reactions and hundreds of species. The reaction model can be extremely hard to solve due to its stiffness. An accurate and robust elementary reaction model is developed in this chapter, and a Gear algorithm is used to solve the stiff ODEs. Generally, a detailed reaction network is generated by allowing the feedstock components to react according to different reaction families. The reaction families can be summarized as follows: (1) initiation reaction and termination reaction: R1—R2\n\t\t\t\t\t↔\n\t\t\t\t\tR1∙+R2∙; (2) hydrogen abstraction reaction: R1—H+R2\n\t\t\t\t\t↔\n\t\t\t\t\tR1∙+R2—H; (3) radical addition and β-scission reaction: R1∙+R2=R3\n\t\t\t\t\t↔\n\t\t\t\t\tR1—R2—R3∙.
Figure 3.
Sub-models in the generation of hydrocarbon steam cracking reaction networks.
The hydrocarbon steam cracking elementary reaction network can be separated into several sub-models. based on the composition of feedstock as shown in Figure 3. The sub-models are generated separately, based on the reaction families described above.
An elementary reaction model for light hydrocarbon can be found in much of the literature and databases, and it is more accurate than the automatic generated elementary reaction model. Thus, the elementary model for steam cracking is separated into two parts: a light hydrocarbon and heavy hydrocarbon reaction model (carbon number greater than five). The light hydrocarbon reaction model is generated using RMG [24]. RMG considers each species as unique and comprising a set of molecular structural isomers. When a reaction network is generated using RMG, it need not consider all the isomers in the real steam cracking process; instead, only a set of representative species are considered during the generation of a reaction network. The heavy reaction model is combined using different reaction models of pure compound feedstock and each reaction model is generated from the reaction families. The reaction coefficients can be obtained from the summary of experimental data (Table 1) in the work of Dente et al. [26]. The heavy hydrocarbon reaction model was generated using our own code.
The automatic generated reaction network may contain a large number of unimportant reactions and species. These reactions can increase the complexity of the model and make the model hard to solve. Thus, reaction model reduction is needed following the automatic model generation. The QSSA method is introduced first to remove the μ radicals in the reaction network [33]. As eq. (6) shows, the reaction rate of μ radicals can be treated as zero, based on the assumption.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tInitiation reactions: unimolecular decomposition of C-C bonds\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tCH3-Csec\n\t\t\t
\n\t\t\t
\n\t\t\t\tCsec-Csec\n\t\t\t
\n\t\t\t
\n\t\t\t\tCsec-Cter\n\t\t\t
\n\t\t\t
\n\t\t\t\tCsec-Cquat\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
5×1016exp(-83,500/RT)
\n\t\t\t
5×1016exp(-81,000/RT)
\n\t\t\t
5×1016exp(-80,000/RT)
\n\t\t\t
5×1016exp(-78,000/RT)
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tH-abstraction reactions of alkyl radicals\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
Primary H-atom
\n\t\t\t
Secondary H-atom
\n\t\t\t
Tertiary H-atom
\n\t\t
\n\t\t
\n\t\t\t
Primary radical
\n\t\t\t
108exp(-13,500/RT)
\n\t\t\t
108exp(-11,200/RT)
\n\t\t\t
108exp(-9,000/RT)
\n\t\t
\n\t\t
\n\t\t\t
Secondary radical
\n\t\t\t
108exp(-14,500/RT)
\n\t\t\t
108exp(-12,200/RT)
\n\t\t\t
108exp(-10,000/RT)
\n\t\t
\n\t\t
\n\t\t\t
Tertiary radical
\n\t\t\t
108exp(-15,000/RT)
\n\t\t\t
108exp(-12,700/RT)
\n\t\t\t
108exp(-10,500/RT)
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tIsomerization reactions (Transfer of a primary H-atom)\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
1-4 H-transfer
\n\t\t\t
1-5 H-transfer
\n\t\t\t
1-6 H-transfer
\n\t\t
\n\t\t
\n\t\t\t
Primary radical
\n\t\t\t
1011exp(-20,600/RT)
\n\t\t\t
1.58×1010exp(-14,500/RT)
\n\t\t\t
3.16×109exp(-19,500/RT)
\n\t\t
\n\t\t
\n\t\t\t
Secondary radical
\n\t\t\t
1011exp(-21,600/RT)
\n\t\t\t
1.58×1010exp(-15,500/RT)
\n\t\t\t
3.16×109exp(-20,500/RT)
\n\t\t
\n\t\t
\n\t\t\t
Tertiary radical
\n\t\t\t
1011exp(-22,100/RT)
\n\t\t\t
1.58×1010exp(-16,000/RT)
\n\t\t\t
3.16×109exp(-21,000/RT)
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tAlkyl radical decomposition reactions (to form primary radicals)\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
Primary radical
\n\t\t\t
Secondary radical
\n\t\t\t
Tertiary radical
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
1014exp(-30,000/RT)
\n\t\t\t
1014exp(-31,000/RT)
\n\t\t\t
1014exp(-31,500/RT)
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tCorrections of decomposition rates to form\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Methyl radical
\n\t\t\t
Secondary radical
\n\t\t\t
Tertiary radical
\n\t\t\t
Alkyl radical
\n\t\t
\n\t\t
\n\t\t\t
exp(-2,500/RT)
\n\t\t\t
exp(1,500/RT)
\n\t\t\t
exp(2,500/RT)
\n\t\t\t
0.316×exp(8,000/RT)
\n\t\t
\n\t
Table 1.
Reference kinetic parameters of pyrolysis reactions [26].
Figure 4.
Flowchart of automatic generation and reduction of reaction network.
In eq. (8), rj is the rate of direct formation of j-radical, ki,j is the rate constant for the isomerization reaction (Ri\n\t\t\t\t\t→\n\t\t\t\t\tRj) and kdj is the total rate constant for the decomposition reactions of Rj; μ radicals are reduced using eq. (8). The number of species included in the model is decreased.
Reaction rate analysis is used to reduce the unimportant reactions in the reaction network. The average reaction rate in the reaction network reflects the importance of the reaction in the network. Thus, we can rank the reactions based on the average reaction rate and reduce the reactions where the reaction rate is less than Rmin [44].
The flowchart of the automatic generation and reduction of the reaction network is shown in Figure 4.
Molecular-level model
The physical properties of some species (radical, non-common substances, etc.) involved in the model are difficult to obtain from databases. The physical properties of these species can be calculated using the group contribution method [42]. RMG also supplies a thermochemistry estimates utility using the group contribution method and was used in our model to automatically calculate the physical properties of these species.
Elementary reaction network for light hydrocarbon steam cracking.
2.2. Case study: Naphtha steam cracking model simulation
A light hydrocarbon reaction model was generated using RMG, which contained 91 reactions and 26 species (Table 2). A naphtha steam cracking reaction network was generated based on the light hydrocarbon network. The naphtha reaction network contained 2424 reactions and 125 species.
Thirteen sets of industrial data (Table 3) were used here to verify the established multi-scale steam cracking model. The industrial data were taken from a steam cracking furnace designed by KBR (Kellogg Brown & Root). The data were collected twice a day and each set of data was the average value of these two parallel experiments as a means for preventing any errors. The multi-scale steam cracking simulation took roughly 70s CPU time. The simulation results and the industrial data of the mass fraction of the main products are shown in Figure 5, where the x-axis represents the industrial data and y-axis represents the simulation results. All points in Figure 5 are around the 1:1 diagonal line, which shows that the error of most results were small. Thus, the established multi-scale model was defined as accurate and robust; it satisfies industrial needs and can be applied further in our study of operating conditions optimization.
3. Multi-period steam cracking optimization
3.1. Multi-period optimization model for steam cracking
Coking is an unavoidable factor in the long-term steam cracking process. During the steam cracking process, coke forms on the inner walls of the tube. With coke formation, the internal diameter of the tube decreases, pressure drops increase and outer wall temperature increases. It is generally accepted that coke forms from unsaturated hydrocarbons and aromatics [43]; on this basis, an empirical model for coke formation rate is proposed, as shown in eq. (9).
Steam cracking is a dynamic process, as coke grows inside the tube. However, coke formation is slow enough that we can divide the entire cracking period into a series of virtual steady state periods. Thus, the established multi-scale model can be used in each steady state period, with coke thickness updated between periods.
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t\t
\n\t\t\tNo.\n\t\t
\n\t\t
\n\t\t
\n\t\t\t1\n\t\t
\n\t\t
\n\t\t\t2\n\t\t
\n\t\t
\n\t\t\t3\n\t\t
\n\t\t
\n\t\t\t4\n\t\t
\n\t\t
\n\t\t\t5\n\t\t
\n\t\t
\n\t\t\t6\n\t\t
\n\t\t
\n\t\t\t7\n\t\t
\n\t\t
\n\t\t\t8\n\t\t
\n\t\t
\n\t\t\t9\n\t\t
\n\t\t
\n\t\t\t10\n\t\t
\n\t\t
\n\t\t\t11\n\t\t
\n\t\t
\n\t\t\t12\n\t\t
\n\t\t
\n\t\t\t13\n\t\t
\n\t
\n\t
\n\t\t
\n\t\t\tFeed\n\t\t
\n\t
\n\t
\n\t\t
D15
\n\t\t
\n\t\t
0.7091
\n\t\t
0.7106
\n\t\t
0.7109
\n\t\t
0.7099
\n\t\t
0.7122
\n\t\t
0.694
\n\t\t
0.7099
\n\t\t
0.6981
\n\t\t
0.7109
\n\t\t
0.6796
\n\t\t
0.7121
\n\t\t
0.7115
\n\t\t
0.7109
\n\t
\n\t
\n\t\t
M
\n\t\t
\n\t\t
94.1
\n\t\t
94.76
\n\t\t
94.68
\n\t\t
94.29
\n\t\t
94.31
\n\t\t
94.43
\n\t\t
94.6
\n\t\t
93.67
\n\t\t
94.74
\n\t\t
95.26
\n\t\t
95.26
\n\t\t
95.41
\n\t\t
94.83
\n\t
\n\t
\n\t\t
T
\n\t\t
°C
\n\t\t
99.3
\n\t\t
101.7
\n\t\t
101.6
\n\t\t
103.38
\n\t\t
101.7
\n\t\t
99.6
\n\t\t
96.4
\n\t\t
99
\n\t\t
100.9
\n\t\t
101.2
\n\t\t
103.3
\n\t\t
98.2
\n\t\t
97
\n\t
\n\t
\n\t\t
K
\n\t\t
\n\t\t
12.45
\n\t\t
12.45
\n\t\t
12.45
\n\t\t
12.48
\n\t\t
12.41
\n\t\t
12.71
\n\t\t
11.17
\n\t\t
12.64
\n\t\t
12.44
\n\t\t
13.02
\n\t\t
12.44
\n\t\t
12.4
\n\t\t
12.39
\n\t
\n\t
\n\t\t
\n\t\t\tOperating conditions\n\t\t
\n\t
\n\t
\n\t\t
F
\n\t\t
t/h
\n\t\t
6.3686
\n\t\t
5.413
\n\t\t
5.4166
\n\t\t
6.0792
\n\t\t
5.1948
\n\t\t
5.2302
\n\t\t
4.9632
\n\t\t
4.9812
\n\t\t
5.3286
\n\t\t
5.397
\n\t\t
5.3726
\n\t\t
5.431
\n\t\t
5.5722
\n\t
\n\t
\n\t\t
W/O
\n\t\t
t/t
\n\t\t
0.5
\n\t\t
0.53
\n\t\t
0.53
\n\t\t
0.5
\n\t\t
0.53
\n\t\t
0.53
\n\t\t
0.54
\n\t\t
0.53
\n\t\t
0.52
\n\t\t
0.54
\n\t\t
0.53
\n\t\t
0.52
\n\t\t
0.53
\n\t
\n\t
\n\t\t
CIT
\n\t\t
°C
\n\t\t
639.6
\n\t\t
639.4
\n\t\t
639.5
\n\t\t
633.4
\n\t\t
640.9
\n\t\t
639.8
\n\t\t
642.5
\n\t\t
641.4
\n\t\t
636.5
\n\t\t
634.8
\n\t\t
638.8
\n\t\t
640.8
\n\t\t
639.1
\n\t
\n\t
\n\t\t
COT
\n\t\t
°C
\n\t\t
871.6
\n\t\t
867.6
\n\t\t
867.2
\n\t\t
872.6
\n\t\t
865.6
\n\t\t
869.2
\n\t\t
865.8
\n\t\t
861.6
\n\t\t
865.4
\n\t\t
863.4
\n\t\t
868.4
\n\t\t
865.8
\n\t\t
867
\n\t
\n\t
\n\t\t
CIP
\n\t\t
Mpa
\n\t\t
0.366
\n\t\t
0.314
\n\t\t
0.312
\n\t\t
0.345
\n\t\t
0.641
\n\t\t
0.303
\n\t\t
0.292
\n\t\t
0.289
\n\t\t
0.302
\n\t\t
0.312
\n\t\t
0.311
\n\t\t
0.313
\n\t\t
0.326
\n\t
\n\t
\n\t\t
COP
\n\t\t
Mpa
\n\t\t
0.044
\n\t\t
0.043
\n\t\t
0.042
\n\t\t
0.039
\n\t\t
0.043
\n\t\t
0.048
\n\t\t
0.044
\n\t\t
0.04
\n\t\t
0.044
\n\t\t
0.044
\n\t\t
0.043
\n\t\t
0.042
\n\t\t
0.045
\n\t
\n\t
\n\t\t
\n\t\t\tYields of major products\n\t\t
\n\t
\n\t
\n\t\t
H2\n\t\t
\n\t\t
wt%
\n\t\t
1.07
\n\t\t
0.99
\n\t\t
1.09
\n\t\t
1.10
\n\t\t
0.99
\n\t\t
1.07
\n\t\t
0.87
\n\t\t
1.01
\n\t\t
0.93
\n\t\t
1.15
\n\t\t
1.19
\n\t\t
1.06
\n\t\t
1.15
\n\t
\n\t
\n\t\t
CH4\n\t\t
\n\t\t
wt%
\n\t\t
16.55
\n\t\t
15.62
\n\t\t
16.73
\n\t\t
16.83
\n\t\t
15.39
\n\t\t
16.73
\n\t\t
13.90
\n\t\t
15.76
\n\t\t
15.15
\n\t\t
18.09
\n\t\t
18.80
\n\t\t
16.98
\n\t\t
17.64
\n\t
\n\t
\n\t\t
C2H4\n\t\t
\n\t\t
wt%
\n\t\t
30.65
\n\t\t
28.62
\n\t\t
29.59
\n\t\t
30.03
\n\t\t
28.57
\n\t\t
30.52
\n\t\t
29.23
\n\t\t
28.45
\n\t\t
30.91
\n\t\t
30.64
\n\t\t
30.82
\n\t\t
30.55
\n\t\t
29.56
\n\t
\n\t
\n\t\t
C2H6\n\t\t
\n\t\t
wt%
\n\t\t
3.79
\n\t\t
3.44
\n\t\t
3.54
\n\t\t
3.56
\n\t\t
3.34
\n\t\t
3.64
\n\t\t
3.49
\n\t\t
3.69
\n\t\t
3.61
\n\t\t
3.63
\n\t\t
3.65
\n\t\t
3.68
\n\t\t
3.60
\n\t
\n\t
\n\t\t
C3H6\n\t\t
\n\t\t
wt%
\n\t\t
16.13
\n\t\t
17.38
\n\t\t
16.51
\n\t\t
16.09
\n\t\t
14.88
\n\t\t
14.95
\n\t\t
15.72
\n\t\t
16.95
\n\t\t
17.22
\n\t\t
15.89
\n\t\t
16.50
\n\t\t
17.08
\n\t\t
16.72
\n\t
\n\t
\n\t\t
C3H8\n\t\t
\n\t\t
wt%
\n\t\t
0.90
\n\t\t
1.74
\n\t\t
0.87
\n\t\t
0.82
\n\t\t
0.83
\n\t\t
0.69
\n\t\t
0.99
\n\t\t
0.88
\n\t\t
1.53
\n\t\t
0.96
\n\t\t
1.05
\n\t\t
1.21
\n\t\t
1.17
\n\t
\n\t
\n\t\t
C4H6\n\t\t
\n\t\t
wt%
\n\t\t
6.02
\n\t\t
6.13
\n\t\t
6.09
\n\t\t
6.03
\n\t\t
5.74
\n\t\t
5.76
\n\t\t
5.51
\n\t\t
6.06
\n\t\t
5.63
\n\t\t
5.62
\n\t\t
5.80
\n\t\t
5.57
\n\t\t
5.48
\n\t
\n\t
\n\t\t
N-C4H8\n\t\t
\n\t\t
wt%
\n\t\t
1.41
\n\t\t
1.59
\n\t\t
1.70
\n\t\t
1.54
\n\t\t
1.40
\n\t\t
1.31
\n\t\t
1.46
\n\t\t
2.07
\n\t\t
1.38
\n\t\t
1.37
\n\t\t
1.43
\n\t\t
1.58
\n\t\t
1.57
\n\t
\n\t
\n\t\t
I-C4H8\n\t\t
\n\t\t
wt%
\n\t\t
2.66
\n\t\t
2.83
\n\t\t
2.98
\n\t\t
2.70
\n\t\t
2.38
\n\t\t
2.32
\n\t\t
2.57
\n\t\t
3.18
\n\t\t
2.79
\n\t\t
2.67
\n\t\t
2.88
\n\t\t
3.09
\n\t\t
3.09
\n\t
\n\t
\n\t\t
others
\n\t\t
wt%
\n\t\t
20.82
\n\t\t
21.66
\n\t\t
20.9
\n\t\t
21.3
\n\t\t
26.48
\n\t\t
23.01
\n\t\t
26.26
\n\t\t
21.95
\n\t\t
20.85
\n\t\t
19.98
\n\t\t
17.88
\n\t\t
19.2
\n\t\t
20.02
\n\t
\n
Table 3.
Industrial data for feedstock, operating conditions and yields of major products.
Operation condition optimization is carried out based on the multi-period process model. Coil outlet temperature (COT) is selected as the variable to be optimized. Thus, the COT of all time periods of the multi-period model is discretized as [COT1, COT2,..., COTn].
In objective function (10), M is the number of considered species, N is the period number, ωt (t=1, 2,..., M) are weighted fractions based on the price of each species and yoj,t is the mass fraction of selected species j in products of period t. Eqs. (11-13) describes mass balance, momentum balance and energy balance equations in period t (t=1, 2,..., N). In eq. (14), the internal diameter of period t+1 Di,t+1 equals the internal diameter of the previous period Di,t minus the coke layer thickness. In eq. (16), peak outer-wall temperature should not exceed the maximum temperature of the tube material. Eq. (17) shows that the adjacent COT difference is restricted to a certain region to keep the operation stable. Eq. (18) shows the upper and lower boundaries of optimization variables.
The most time-consuming part of the optimization is the simulation of the multi-period model. As Figure 6 shows, the only connection between adjacent periods is the coke thickness. Coke thickness is related to the feedstock component, furnace running time and operating conditions. As it has been assumed that the feedstock component is fixed between periods and only COT changes in operating conditions, as eq. (19) shows, then dt is the coke thickness in period t.
dt=f(feed,period number,COT1,COT2,⋯,COTt)E19
\n\t\t\t\t
The accumulated coke thickness within a certain period δdt is assumed to only be related to the furnace running time and COTt (t=1, 2,..., N-1), shown as eqs. (20) and (21).
Optimization procedure with multi-period steam cracking simulation.
Thus, δdt in period t can be regressed using the polynomial function shown as eq. (20). Here, the coke thickness data is generated using the original multi-period simulation model and based on this, a surrogate coke thickness model is obtained through regression. The coke thickness using the surrogate model and original multi-period simulation model are shown in Figure 7. Dots in Figure 7 are coke thickness from the original multi-period simulation model and the surface is from surrogate model.
The coke thickness from the surrogate model fits well with the original model; thus, the decoupled multi-period cracking model, combined with the surrogate coke thickness model was used in the multi-period simulation. The initial coke distribution along the serial operation periods was carried out using the surrogate model. Thus, the multi-period simulation problem was decoupled into N sub-problems and simulated, respectively, in parallel, as shown in Figure 8.
3.3. Optimization with parallel simulation
Figure 8 shows optimization with a parallel simulation procedure using the surrogate coke thickness model.
Figure 7.
Coke thickness from the surrogate model and original multi-period model.
Figure 8.
Optimization using a parallel simulation procedure.
In Figure 8, a surrogate coke thickness model is regressed from the results of the original multi-period model and the surrogate coke thickness model generates the coke thickness distribution for each period prior to the simulation. Once the surrogate model is regressed, the process for each period can be simulated in parallel. The simulation results are sent to the optimization model. If the criteria are satisfied, the optimization stops; if not, the optimization model generates a new set of COT and returns it to the simulation model.
There are several common types of parallel computing methods: phase parallel, divide and conquer parallel, pipeline parallel, master-slave parallel and work pool parallel methods. In this instance, the work pool parallel job partitioning method was used in the optimization. Simulation for one period can be treated as one job in the parallel simulation. All the jobs are stored in the work pool; processors fetch jobs from the work pool as long as the work pool is not empty. A detailed scheme for parallel simulation is shown in Figure 9.
Figure 9.
Detailed scheme for parallel simulation.
In Figure 9, NP is the resources that can be used in a parallel simulation (NP=computer number×processor number for each computer) and NJ is the period number in the multi-period simulation. If NP≥NJ, that means all jobs can be calculated in one iteration. Otherwise, NP jobs must be fetched from the work pool and be postponed until all processors are idle before the next iteration. Simulation will continue until the work pool is empty.
Another benefit of using parallel simulation is a warm start. To accelerate the steam cracking simulation, iteration information is stored after the first simulation, which is called a warm start. If the iteration information is recorded, it can be used as an initial value in the next simulation for reducing CPU time. A comparison between a warm start for serial and parallel simulation is shown in Figure 10.
Figure 10.
Comparison between a warm start for serial and parallel simulation, based on the multi-period steam cracking model.
Iteration information for the most recent period is stored in serial simulation. The iteration information for each period is not entirely the same. Inconsistency of iteration information makes the simulation slow. In a parallel simulation, however, iteration information for each period can be stored. This delivers a faster simulation for each period.
3.4. Case study: Naphtha steam cracking model optimization
An industrial multi-period steam cracking instance was used as a case study. Input data is shown in Table 4. The detailed feedstock composition was calculated using the Shannon entropy method [39]. An elementary reaction model and optimization with parallel simulation was used in this case study. The computer used in this optimization had eight cores of i7-2600 CPU and 4GB memory.
The optimization results show a 0.62% ethylene increase compared to the invariant operating condition that was implemented in the practice. The comparison of the serial optimization results and optimization with parallel simulation results are shown in Figure 11 and Figure 12. It can be seen that the tendency of serial and parallel optimization results were the same. There was a high outlet temperature and high conversion of the major products in the beginning and intermediate periods, and the outlet temperature of final periods were rather low for reducing the coke formation and for avoiding a high outer-wall temperature.
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t\t
\n\t\t\tFeed\n\t\t
\n\t
\n\t
\n\t\t
Molecular weight
\n\t\t
95.26
\n\t
\n\t
\n\t\t
H/C
\n\t\t
2.11
\n\t
\n\t
\n\t\t
\n\t\t
P
\n\t\t
I
\n\t\t
N
\n\t\t
A
\n\t
\n\t
\n\t\t
PINA
\n\t\t
0.3096
\n\t\t
0.3223
\n\t\t
0.2856
\n\t\t
0.0825
\n\t
\n\t
\n\t\t
\n\t\t
IBP
\n\t\t
10%
\n\t\t
30%
\n\t\t
50%
\n\t\t
70%
\n\t\t
90%
\n\t\t
EBP
\n\t
\n\t
\n\t\t
ASTM (°C)
\n\t\t
41.2
\n\t\t
58.2
\n\t\t
80.1
\n\t\t
99.0
\n\t\t
119.6
\n\t\t
148.9
\n\t\t
175.9
\n\t
\n\t
\n\t\t
\n\t\t\tOperating condition\n\t\t
\n\t
\n\t
\n\t\t
Feed rate (t/h)
\n\t\t
5.4
\n\t
\n\t
\n\t\t
Water/Oil (t/t)
\n\t\t
0.54
\n\t
\n\t
\n\t\t
Coil inlet temperature (°C)
\n\t\t
636.5
\n\t
\n\t
\n\t\t
Coil inlet pressure (Mpa)
\n\t\t
0.31
\n\t
\n\t
\n\t\t
Coil outlet pressure (Mpa)
\n\t\t
0.04
\n\t
\n\t
\n\t\t
\n\t\t\tOptimization variables\n\t\t
\n\t
\n\t
\n\t\t
Objective function
\n\t\t
max110(0.52∑t=110yC2H4,to+0.48∑t=110yC3H6,to)
\n
\n
\n\t
Furnace runtime (day)
\n\t
50
\n
\n
\n\t
\n\t\tNP\n\t
\n\t
8
\n
\n
\n\t
\n\t\tTM\n\t\t (°C)
\n\t
1000.0
\n
\n
\n\t
\n\t\tδ (°C)
\n\t
5.0
\n
\n
\n\t
\n\t\tLB (°C)
\n\t
855.0
\n
\n
\n\t
\n\t\tUB (°C)
\n\t
872.0
\n
\n
Table 4.
Supporting information for the steam cracking optimization model.
The error of parallel simulation compared to serial simulation is shown in Table 5.
The CPU time of serial optimization was 17.78hr, while the CPU time of parallel optimization was 2.08hr. There was a 8.55 x speedup compared with serial optimization, because parallel calculation and a warm start strategy were used. Thus, the operating conditions could be dynamically optimized to track the changing market conditions.
The error in optimization with the parallel simulation model was caused by the surrogate coke thickness model. In eq. (22),
δdt=dt+1−dt=f(t,COTt)∀t∈{1,2,⋯,N−1}E22
\n\t\t\t\t
Figure 11.
COT optimization results for serial and parallel simulation.
Figure 12.
C2H4 and C3H6 optimization results for serial and parallel calculation.
The feedstock composition and operating conditions, except COT, were fixed. However,
Accumulate coke thickness in each period was related to the operating conditions of all previous periods. Eq. (23) is simplified as eq. (22) to make the model easier to regress and the error caused by the simplification is acceptable according to the error shown in Table 5.
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t
\n\t\t
\n\t\t
\n\t\t\tCOT\n\t\t
\n\t\t
\n\t\t\tC2H4\n\t\t\t\n\t\t
\n\t\t
\n\t\t\tC3H6\n\t\t\t\n\t\t
\n\t
\n\t
\n\t\t
\n\t\t\tPeriod\n\t\t
\n\t\t
\n\t\t\tSerial (°C)\n\t\t
\n\t\t
\n\t\t\tParallel (°C)\n\t\t
\n\t\t
\n\t\t\tError (%)\n\t\t
\n\t\t
\n\t\t\tSerial (wt%)\n\t\t
\n\t\t
\n\t\t\tParallel (wt%)\n\t\t
\n\t\t
\n\t\t\tError (%)\n\t\t
\n\t\t
\n\t\t\tSerial (wt%)\n\t\t
\n\t\t
\n\t\t\tParallel (wt%)\n\t\t
\n\t\t
\n\t\t\tError (%)\n\t\t
\n\t
\n\t
\n\t\t
1
\n\t\t
872.00
\n\t\t
872.00
\n\t\t
0.00
\n\t\t
32.13
\n\t\t
32.13
\n\t\t
0.01
\n\t\t
16.54
\n\t\t
16.54
\n\t\t
0.00
\n\t
\n\t
\n\t\t
2
\n\t\t
872.00
\n\t\t
872.00
\n\t\t
0.00
\n\t\t
32.22
\n\t\t
32.24
\n\t\t
0.05
\n\t\t
16.55
\n\t\t
16.55
\n\t\t
0.00
\n\t
\n\t
\n\t\t
3
\n\t\t
872.00
\n\t\t
872.00
\n\t\t
0.00
\n\t\t
32.31
\n\t\t
32.36
\n\t\t
0.14
\n\t\t
16.57
\n\t\t
16.57
\n\t\t
0.01
\n\t
\n\t
\n\t\t
4
\n\t\t
872.00
\n\t\t
872.00
\n\t\t
0.00
\n\t\t
32.42
\n\t\t
32.48
\n\t\t
0.21
\n\t\t
16.59
\n\t\t
16.59
\n\t\t
0.02
\n\t
\n\t
\n\t\t
5
\n\t\t
872.00
\n\t\t
872.00
\n\t\t
0.00
\n\t\t
32.56
\n\t\t
32.65
\n\t\t
0.27
\n\t\t
16.58
\n\t\t
16.56
\n\t\t
0.14
\n\t
\n\t
\n\t\t
6
\n\t\t
872.00
\n\t\t
872.00
\n\t\t
0.00
\n\t\t
32.70
\n\t\t
32.84
\n\t\t
0.44
\n\t\t
16.55
\n\t\t
16.49
\n\t\t
0.34
\n\t
\n\t
\n\t\t
7
\n\t\t
870.58
\n\t\t
871.38
\n\t\t
0.09
\n\t\t
32.84
\n\t\t
33.02
\n\t\t
0.54
\n\t\t
16.46
\n\t\t
16.40
\n\t\t
0.34
\n\t
\n\t
\n\t\t
8
\n\t\t
865.58
\n\t\t
866.38
\n\t\t
0.09
\n\t\t
32.89
\n\t\t
33.07
\n\t\t
0.54
\n\t\t
16.31
\n\t\t
16.22
\n\t\t
0.52
\n\t
\n\t
\n\t\t
9
\n\t\t
860.58
\n\t\t
861.38
\n\t\t
0.09
\n\t\t
32.98
\n\t\t
33.09
\n\t\t
0.35
\n\t\t
16.11
\n\t\t
16.04
\n\t\t
0.39
\n\t
\n\t
\n\t\t
10
\n\t\t
855.58
\n\t\t
856.38
\n\t\t
0.09
\n\t\t
33.11
\n\t\t
33.09
\n\t\t
0.04
\n\t\t
15.87
\n\t\t
15.88
\n\t\t
0.07
\n\t
\n\t
\n\t\t
Average error
\n\t\t
-
\n\t\t
-
\n\t\t
0.04
\n\t\t
-
\n\t\t
-
\n\t\t
0.26
\n\t\t
-
\n\t\t
-
\n\t\t
0.18
\n\t
\n
Table 5.
Summarized optimization results for serial and parallel calculation.
4. Conclusion
A multi-scale steam cracking model was established in this chapter. An elementary reaction network was generated to obtain a more accurate and robust model. The results showed that the established multi-scale model agrees well with the industrial data. A surrogate coke thickness model is thus proposed to make multi-period optimization with parallel simulation possible. A case study showed that multi-period optimization with parallel computing possesses an 8.55 x speedup compared to optimization with serial simulation. Parallel computing makes real-time optimization (RTO) possible in multi-period optimization. The average error of optimization using a parallel simulation model was 0.04% compared to optimization using a serial model. The error was deemed acceptable for the optimization of large-scale industrial steam cracking processes.
Optimization using the parallel computing method can also be used in other aspects of chemical processes. Due to the complexity of chemical processes, it is always difficult to conduct a simulation or optimization using a multi-scale model. The connections of different levels in a multi-scale model or different equipment in chemical process can be decoupled and transferred to a multiple sub-system model, which can be simulated in parallel. This method can bring powerful computing performance into play in chemical engineering.
Acknowledgments
The authors gratefully acknowledge the financial support of the National Basic Research Programme (No. 2012CB720500) and the NSFC (No. 21306100).
\n',keywords:"Steam cracking, multi-scale modelling, elementary reaction network, parallel simulation, surrogate model",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/48583.pdf",chapterXML:"https://mts.intechopen.com/source/xml/48583.xml",downloadPdfUrl:"/chapter/pdf-download/48583",previewPdfUrl:"/chapter/pdf-preview/48583",totalDownloads:2108,totalViews:530,totalCrossrefCites:2,totalDimensionsCites:2,totalAltmetricsMentions:3,impactScore:1,impactScorePercentile:72,impactScoreQuartile:3,hasAltmetrics:1,dateSubmitted:"October 18th 2014",dateReviewed:"March 24th 2015",datePrePublished:null,datePublished:"September 30th 2015",dateFinished:"June 19th 2015",readingETA:"0",abstract:"Hydrocarbon steam cracking is the most important process for producing industrial chemicals such as olefin and aromatics. Steam cracking modelling and optimization is an effective way for increasing production and saving energy. In this chapter, multi-scale modelling and elementary reaction networks are established and used in the modelling and optimization of steam cracking. However, the large scale of the optimization model makes it difficult to obtain a solution. Thus, a surrogate coke thickness model for long-term steam cracking is proposed in this chapter to remove the connection between different periods of steam cracking process. By so doing, a parallel simulation can be used to accelerate optimization. An industrial case study showed optimization time to be significantly reduced from 17.78 hours to 2.08 hours using multi-period optimization with parallel simulation and the surrogate coke thickness model. It has been shown that a 0.62% increase in ethylene yield can be obtained via operating condition optimization, which demonstrates the effectiveness of the multi-scale steam cracking model and multi-period optimization with parallel simulation.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/48583",risUrl:"/chapter/ris/48583",book:{id:"4600",slug:"advances-in-petrochemicals"},signatures:"Lei Zhang, Hangzhou Wang, Tong Qiu and Bingzhen Chen",authors:[{id:"173775",title:"Dr.",name:"Lei",middleName:null,surname:"Zhang",fullName:"Lei Zhang",slug:"lei-zhang",email:"delphithu@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Tsinghua University",institutionURL:null,country:{name:"China"}}},{id:"173776",title:"Dr.",name:"Hangzhou",middleName:null,surname:"Wang",fullName:"Hangzhou Wang",slug:"hangzhou-wang",email:"whz@mails.tsinghua.edu.cn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"173777",title:"Prof.",name:"Tong",middleName:null,surname:"Qiu",fullName:"Tong Qiu",slug:"tong-qiu",email:"qiutong@mail.tsinghua.edu.cn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"173778",title:"Prof.",name:"Bingzhen",middleName:null,surname:"Chen",fullName:"Bingzhen Chen",slug:"bingzhen-chen",email:"dcecbz@mail.tsinghua.edu.cn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Steam cracking model",level:"1"},{id:"sec_2_2",title:"2.1. Multi-scale model for steam cracking",level:"2"},{id:"sec_3_2",title:"2.2. Case study: Naphtha steam cracking model simulation",level:"2"},{id:"sec_5",title:"3. Multi-period steam cracking optimization",level:"1"},{id:"sec_5_2",title:"3.1. Multi-period optimization model for steam cracking",level:"2"},{id:"sec_6_2",title:"3.2. Surrogate coke thickness model",level:"2"},{id:"sec_7_2",title:"3.3. Optimization with parallel simulation",level:"2"},{id:"sec_8_2",title:"3.4. Case study: Naphtha steam cracking model optimization",level:"2"},{id:"sec_10",title:"4. Conclusion",level:"1"},{id:"sec_11",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Van Goethem, Marco et al. Equation-based SPYRO model and solver for the simulation of the steam cracking process. Computers & Chemical Engineering. 2001; 25(4): 905-911.'},{id:"B2",body:'Van Geem, K. 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Model order reduction using neural network principal component analysis and generalized dimensional analysis. Engineering Computations. 2008; 25(5): 443-463.'},{id:"B32",body:'Lang, Y. D., Malacina, A., Biegler, L. T., Munteanu, S., Madsen, J. I., Zitney, S. E. Reduced Order Model Based on Principal Component Analysis for Process Simulation and Optimization. Energy & Fuels. 2009; 23(3): 1695-1706.'},{id:"B33",body:'Ranzi, E., Dente, M., Pierucci, S., Biardi, G. Initial product distributions from pyrolysis of normal and branched paraffins. Industrial & Engineering Chemistry Fundamentals. 1983; 22(1): 132-139.'},{id:"B34",body:'Abel, O., Birk, J. Real Time Optimization of Chemical Processes with Application to Olefins Production. AUTOMATISIERUNGSTECHNIK. 2002; 50(12): 586-596.'},{id:"B35",body:'Tarafder, A., Rangaiah, G. P., Ray, A. K. Multiobjective optimization of an industrial styrene monomer manufacturing process. Chemical Engineering Science. 2005; 60(2): 347-363.'},{id:"B36",body:'Li, C., Zhu, Q., Geng, Z. Multi-objective particle swarm optimization hybrid algorithm: An application on industrial cracking furnace. Industrial & engineering chemistry research. 2007; 46(11): 3602-3609.'},{id:"B37",body:'Klein, M. T., Hou, G., Bertolacini, R., Broadbelt, L. J., Kumar, A. Molecular modeling in heavy hydrocarbon conversions. CRC Press; 2010.'},{id:"B38",body:'Shannon, C. E. A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review. 2011; 5(1): 3-55.'},{id:"B39",body:'Zhang, L., Chen, B. Applications of Shannon\'s entropy theory to naphtha pyrolysis simulation. Chemical Engineering & Technology. 2012; 35(2): 281-286.'},{id:"B40",body:'Jae Lee, W., Froment, G. F. Ethylbenzene dehydrogenation into styrene: kinetic modeling and reactor simulation. Industrial & Engineering Chemistry Research. 2008; 47(23): 9183-9194.'},{id:"B41",body:'Xu Q., Chen, B., He, X. A fast simulation algorithm for industrial cracking furnaces. Hydrocarbon processing. 2002; 81: 65-68.'},{id:"B42",body:'Constantinou, L., Gani, R. New group contribution method for estimating properties of pure compounds. AIChE Journal. 1994; 40(10): 1697-1710.'},{id:"B43",body:'Kumar, P., Kunzru, D. Coke formation during naphtha pyrolysis in a tubular reactor. The Canadian Journal of Chemical Engineering. 1987; 65(2): 280-285.'},{id:"B44",body:'Zhang, L. Radical Reaction Model Based Simulation and Optimization Method for Steam Cracking Process. Ph.D. thesis. Tsinghua University; 2014.'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Lei Zhang",address:null,affiliation:'
Department of Chemical Engineering, Tsinghua University, Beijing, China
Department of Chemical Engineering, Tsinghua University, Beijing, China
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1. Introduction
COVID-19 outbreak reminds us of nationwide lockdowns, home-confinement, overburdened hospitals, country wide curfews, violent and chaotic health-facilities and domestic scenario and gradual but steady rise of stigmatizing factors like fear of isolation, racism, discrimination and marginalization cumulatively intensifying the unavoidable stress, fear, anxiety, depression, poor life quality, substance abuse resulting in enhanced mortality risk particularly among the health-compromised population [1, 2, 3] . Survival through this turmoil highlighted the elemental role of mental health organizations, individual healthcare and research, social media, awareness programs at both personal and community levels in significantly combating the world’s psychosocial distress [4, 5, 6]. Although, COVID-19 bears the brunt of rising mental illness, a clear understanding of world’s disease response would certainly aid in improving our medical emergencies and coping skills around the world.
Psychosocial impact of COVID-19 has been widely discussed in literature but what remains untouched as with all other parts of psychiatry is that the cause of impact has not been discussed [2, 3, 4, 7]. It is often easy to label each and every disorder that a psychiatrist is seeing in COVID-19 patients or in patients or healthy beings having the effects somehow related to the pandemic to label as evidence. It thus becomes imperative to discuss the impact that a society is having through a unique lens that widens the perspective relating to the cause and consequence of each and every response that happens to the disease process. To help with this perspective, we shall use the model described by Kunal in his paper on hypothesis spanning the diversities of psychiatry and normalcy, in the section on pathophysiology [8]. But before we shall delve into this new perspective, we shall see what evidence has to say for the psychosocial impact of the pandemic.
2. Methodology
2.1 Objectives
To analyze the psychosocial impact of COVID19.
To delineate the process of impact, by looking into its pathophysiology.
2.2 Data acquisition
Literature was reviewed from PubMed and Google Scholar to find out articles describing the psychosocial impact of COVID19. A search was also carried out to find the explanations pertaining to different behavior of an individual to a given stress in order to justify the impact and explore management options.
2.3 Data analysis
The compilation of effects was studied and a way was formulated to better understand the psychosocial impact (Figure 1).
Figure 1.
Algorithm to show mapping of psychosocial impact of COVID19 based on literature.
3. Results and discussion
3.1 Social impact
When talking about social impact one needs to understand how a society is formed and functions. Society is like a big web of individuals who are inter-related because of friendship, families or workplace. There are visible and some invisible connections where a person relates to another person or set of person based on ideologies, principles or practice like in name of color, caste, creed or nationality. Invisible connections that often turn into sentiments of positivity or negativity. Stigmatization based on religion, social status and nationality has been a core of social discrimination in this pandemic [2, 9].
A revolution this pandemic brought was the strengthening of visible connections. Spending more time with families had both positive and negative impact. The bonding of families increased however spending too much of time together also had reportedly increased rates of divorce among couples [2, 10]. Veliyannoor coined this as ‘return of the repressed’ where old conflicts re-emerged during the lockdown due to prolonged forced togetherness between couples [10].
Joshi noticed in her review of psycho-social impact of COVID19 in India that adolescents and young people found it restricting and frustrating to be monitored by parents. Also, she pointed out how the conventional gender role expectations in an Indian society resulted in their overburdening leading to frustration and anger bursts. Family dynamics were also influenced by forced togetherness or separation [2].
Based on age, Dubey et al. showed various psychological issues that can happen in different groups and suggested intervention accordingly [7]. Authors showed that children are more prone to boredom, anxiety related to educational development, irritability and fear of infection. Indeed these fears might have been cultivated in them by their parents or guardians to prevent them from going outside. Though the psychological treatment should aim to control extreme fear, casual fear is indeed protective. Proper parenting, online education, and inculcation of healthy habits can provide a feasible solution but this can result in obsession for cleanliness sometimes which if not controlled earlier can get incorporated in psyche and lead to development of OCD (see section on pathophysiology). Young adults developed more anxiety due to low experience in coping with facing distress. Elderlies had irritability, anger issues, fear, anxiety and cognitive decline. Deprivation from pre-scheduled checkup or follow-up can lead to aggravation of their current conditions thus exacerbating the impact. Telepsychology or sessions via telephone or online consultations proved to be useful in all these cases [11]. Telemedicine has gained a lot of popularity during last 2 years and has almost replaced for physical visits except for emergencies at least at some point of time. Though it is not a true alternative to physical consultations it can have advantages in times of distress where risk–benefit ratio might be high for the physical visits for simple follow-ups or chronic illnesses.
Education builds society into a framework as we see and want to see. Conventional education has long been debated but has never been challenged at this scale. Pandemic showed the world a new perspective towards education in terms of online education system. The cellphones which were till an year back not allowed in many schools have become an integral part of education system and has also given food for thought as whether our thought process of keeping these at bay mattered? Long term effects are yet to be seen and short term reports have shown that not going to school may have psychologically affected children but again what impact it shall have on overall growth of a child is yet to be found out. Educational impact can be understood in three different ways- one on parents, one on children and one on teachers. While parents are still doubtful of new education system, it may be difficult for teachers too as maintaining the sanctity and discipline of class could not be strictly possible in addition to the fact that it is not possible to look after every student in classroom now. Also, teachers may face a constant struggle for validation as this technique of teaching is new for many and they might be under supervision of hundreds of parents who might be listening to what they speak. For students the learning experience has changed, as the way they interact with teachers and fellows have been changed. But not only the schools, even the crucial education deliveries have changed like that of medical training program even though examination patterns have remained nearly same. How this will change the social dynamics is yet to be seen in future [12, 13, 14].
The increasing role of social media cannot be overlooked in context of COVID19. The major role it played in pandemic has both positive and negative sides. Positive side includes spreading awareness, helping out friends and locals in times of need like shortage of supplies, finding hospitals etc. seeking help in times of distress (which inculcated a sense of hope in lockdown and quarantines) and enhance bonding among people. But nothing comes without a cost, like enhanced bonding promoted stigmatization of particular community or nationality, outbursts of racism and therapeutic misadventures tried by lay people misleading the general public about treatment or prophylaxis. Coronavirus ‘infodemic’ is another concern that was created on social media in which panic was created by laying out unchecked mind-boggling rumors [15]. Also it helped to promote the disobedience attitude among people who failed to recognize the disease as pandemic and labeled it as hoax created by world governments to divert the commoners from daily problems.
3.2 Socio-economic impact
Economic profiles can lead to formation of two groups in society- one whose livelihood has been greatly affected like those of laborers or small businessmen and another those whose work were less affected like those of HCPs, government servants, big businessmen and those working in private sector companies that still ran work-from home. The latter group had lesser financial implications, while former group went nearly bankrupt. Financial implications along with separation from families led migrant workers into great despair. Daily wage earners could not get enough wages to support family. Movement in groups and living in poor conditions predisposed them to infection and stigmatization of being carriers. The ill planned distribution of health services and expense of medical treatment led to hoarding of supplies, black marketing and other health crimes [9].
3.3 Socio-political impact
This section shall be incomplete without the mention of social and political revolutions. Revolution does not see the face of pandemic to break out. A very crucial aspect of any society is opposition to the laid rules. Protest is common in democracy as problems do not cease to exist in democracy. These people are marginalized and unheard, complicated by existence of pandemic, media often ignore either their plea or glorify their ignorance towards safety guidelines like wearing of masks, grouping together or following proper guidelines. The protestors may also have a feeling of vulnerability and learned helplessness as described for those people who have patients admitted in hospitals and must break social protocols to be able to provide proper care.
Social inequities like belonging to marginalized sections with poor health facilities often expose to chronic diseases leading to higher mortality when contracting COVID19 which has been reported by Osofsky et al. They also reported how poorer connectivity can affect seeking help in times of distress [16]. The solution to this cannot be made in a day but it points towards a poor preparedness for any such catastrophic event.
3.4 Social impact on health care
Based on health care the society was clearly divided into two strata during the pandemic- one providing health service and the other at receiving end. Patients developed anxiety, depression, panic, irritability, while the attendants developed a sense of uncertainty, helplessness, worthlessness and a fear of infection [1, 7, 17]. The kin of those who died developed prolonged grief, depression, substance abuse, and stigma related to spread of infection [7]. Inability to do a proper funeral further accentuated the problem. The visuals of ill treatment of dead bodies or mass funerals can further develop a sense of despair in individuals who could not say a proper good-bye to family and same could be for the families too. Another perspective could be for those persons who have their patients admitted in hospitals. They might develop fear of contracting the infection on one hand and on other might feel helpless in not being able to maintain social restrictions thus depicting learned helplessness [7].
Another special set of patients that needs special mention is psychiatric patients. Violence, addiction and disturbed routine follow-up were common issues faced by them. Xiao proposed novel approach of structure letter therapy while Saladino et al. and Zhou et al. emphasized the use of telepsychology and telehealth [11, 18, 19]. Another aspect for proper health care delivery to these patients would be to ensure that supply of prescribed medicines should be monitored and checked to prevent any lapse and family members or caretakers should also be looked for as they might develop their own set of problems.
On the other hand, psychological impact on HCWs could be very different. They felt overworked, unable to attend to family duties and guilt of not being able to save the patients. Those not involved in direct care of patients could have felt worthlessness for not being able to help [7]. Overwork can lead to burnouts, depression and anxiety [5]. Lack of facilities can also produce secondary traumatic stress disorder where HCWs have to decide who can access and who cannot access the facilities [20]. Lai et al. reported that nearly half of HCWs working in COVID wards had depression followed by anxiety and insomnia and nearly three-fourth had distress [21]. The problems faced by HCWs can be broadly labeled into three categories: those faced by them related to work and family needs, those faced by problems related to patient care and those faced by colleagues distress created by news of violence against doctors, work under poor safety guidelines, eviction of doctors from their rented house in various resident communities and death while providing services to patients. Though all three creates a similar type of stress pattern, psychotherapy shall aim at different roots when going for consultations. In most cases, these HCWs would not seek professional opinion and these distresses would be transient though theoretically affecting the patient care sometimes by reducing efficiency or indirectly affecting other colleagues or family member who might feel helpless in saving him or her.
3.5 Professional impact on training
Trainee doctors and medical graduates were also affected in their training. Reduced patient contact led to decrement in development of skills [22, 23]. Surgeons faced redeployment and decreased operation theater postings which in turn affected their surgical skill development [24]. Adaptation to online learning and problems with submission of dissertation was also a challenge and all these stress added to psychological impact on them [24, 25, 26]. A positive statement was that with online classes and posting in backup teams, these trainees got time to let the steam off and de-stress them. The training of not only health care workers but also every sector suffered tremendously thus also creating a question mark for not only training modules in past but also in future of the trainees trained during COVID19. Although, detailed discussion is out of scope of this chapter.
3.6 Risk factors for psychosocial impact
Romm et al. reported that females and sexual minorities were at risk for increased depression while males were at greater risk for decreased physical activity. Whites when compared to Blacks were at greater risk for increase in mental health impacts while Asians had greater chances of alcohol abuse. Hispanics were at greater risk for decreased relationship quality, physical activity, and increased sedentary activity [27]. Fteropoulli et al. found that factors associated with poorer outcomes for psychosocial impact include medical profession, female gender, frontline work and use of avoidance as coping skill [6]. They also reported depression and burnout to be strongest predictors of poor quality of life parameters, similar to findings reported by Suryavanshi et al. in Indian HCWs [28].
3.7 Pathophysiology- a fresh perspective
So what caused this impact? This is not a direct impact of the virus. Let us consider COVID-19 as a stress- a newly found one (Figure 2), according the “third-eye model’ [8]. It is a new experience and in some way have affected every person even the dead who could not get proper funerals and good-byes. And indeed that too has affected the living. Figure 3 shows normal response to stress. Whenever a stress strikes, it tends to push the brain cycle into NREM phase. A person always tries to end it and mount a REM response based on conditionings in brain. Conditionings are the coping skills that a person had learned during lifetime, so technically children will have lesser conditioning than adults and young will have lesser conditioning than elders. Thus problems with children will focus on what they do as in difficulty in concentrating, boredom, irritability, restlessness, nervousness, sense of loneliness, uneasiness, and worries, while adults would have anxiety, depression, burnouts, loneliness, panic, and substance use disorders.
Figure 2.
Algorithm showing basic response to any stress (further algorithm is given in Figures 3–5).
Figure 3.
Algorithm showing response when a patient can control the thoughts provoking mental stress and possible responses.
But not all people suffer from psychological impact at a given time. If one believes that the stress shall be controlled and it is indeed controlled then the behavior is more towards normalcy like with those whose income was not affected- pensioners, HCPs and government employees. Even though many times they worked under the fear of getting infected sometimes this fear was casual but at times where situation was not under control like working with limited supplies or exposure to large number of COVID patients or working long shifts, this could turn into anxiety or panic.
Whenever the stress is identified as stress like a person believes that abnormal response to COVID19 is validated, a justification happens for stress. If this justification is for a process that just a mirror image of what a person usually saw this could lead to adjustment disorders giving sense of irritability or loneliness to the person but if it backed by emotional turmoil or magnification where COVID19 is seen to impact the lives of people like never before killing thousands, breaking families, blowing the finances of families or simply loss of very close one who had no disease otherwise can lead to PTSD. It is often the effect of COVID19 that tends to cause adjustment disorder and PTSD than itself. Multiplied by isolation and long stays at home it is not difficult to imagine that bereavement reaction can also be prolonged.
Now all of this may comprise a normal response to a pandemic because the person still has some control over thoughts of stress and often the problem would lay on impact of stress as in death of a person, inability to help others, financial breakdowns and social cut-offs rather than COVID19 itself. Once the stress is incorporated in psyche of an individual, the principle of inertia decides as to whether the psyche can overcome the persistence of thoughts. If it tries to overcome it, it searches for a manipulation (remember here the thoughts have persisted and cannot be simply overthrown by mounting a response as explained in above text). From Figure 4, we can see if the manipulation is specific to stress it can be lead to anxiety if the manipulation is feasible for psyche but patient cannot do that. Another common way to mount a response is to mount a response which is very feasible to psyche like washing hands repeatedly as in OCD or shifting to over smoking or over drinking for stress relief. Sometimes this substance abuse can be an excuse for stress where the patient may be trying to gain sympathy or needs a leave from workplace and do not want to malinger which indeed can be very common due to non-specific and objective complaints of COVID-19 which can be practically anything from myalgia to loose stools. If the patient is already not ill can present with a spectrum of somatization and this could be for same reason except for the fact that malingering or claiming false symptoms is not feasible to psyche, i.e. the person does not want to malinger or do substance abuse which can be due to ethics, emotions or rationality.
Figure 4.
Algorithm showing response when a patient cannot control the thoughts provoking mental stress and still tries to find possible ways to control its inception in thought process.
Although, the above pathologies are not uncommon but another common response pattern is where the NREM state induced by stress is only controlled to some extent or cannot be controlled at all (Figures 2 and 5). In any of these cases, giving up to brain cycle is difficult as these people would have otherwise stronger will to control the brain. COVID19 is a pandemic and has affected everyone in some extent and thus does not target any specific group and is a boon for others. This feeling helps the person to control rather than be controlled by brain. Dysthymia has a definition to fulfill and can be underreported or can be diagnosed as depression by many. Low mood is not uncommon as it does not require any specific action from the person, it is like ‘going with the flow’.
Figure 5.
Algorithm showing response when a patient cannot control the thoughts provoking mental stress and cannot find possible ways to control its inception in thought process.
Each and every response can be mapped and the therapy oriented at that, however it is beyond the scope of this chapter to discuss every disease and intervention in detail [8].
3.8 Future prospects
Studying the impact can help us delineate the stress parameters and try to streamline treatment modalities. Saladino et al. recommended the same as primary prevention modality [11]. Under secondary prophylaxis, they recommended sensitizing the general populace on telepsychology, training next generation of psychotherapists in managing online devices and developing new tools of support and psychological treatment. However they mostly related to psychological issues needing treatment often the part unlooked is the iceberg below the tip. Those unreported psychological impact can be overcome by better preparedness for next pandemic by government, people, and society in general. A change is inevitable so rather than resisting the change, we shall look at its brighter side: incorporate healthy habits, give time to family and friends, look at education in terms of learning and prepare for medical emergency.
4. Conclusions
The visuals of people dying despite best health facilities puts the question forward for us as to what are we in front of nature? How much have we learned and how much we are we prepared for catastrophe? The rapid response and adaptability of general population cannot be overlooked. But it has left a deep impact with long term unforeseen effects. We shall not only study the effects in its past form but also anticipate further damage it can cause in late future. Other than teaching us the fact that we need a lot of medical preparedness, it also taught us that healthy individuals can also become transiently stressed and show symptoms which may not be deemed as psychologically fit. This blemish had to be erased to bring people to talk about psychological issues with even non-medico or non-psychiatrist friends and colleagues. Ignorance had been a bliss for ignorant but not for those who suffered in silence. It is the awareness that has brought us together in the face of crisis.
COVID19 came as wave and swayed the humanity. Different states of individual showed different responses to the same stress creating a gamut of responses which led to different socio-economic, socio-political, professional and psychosocial impact. Identification of stress, mapping of response and a better preparedness from experience can all help us in preventing and controlling it next time.
Conflict of interest
The authors declare no conflict of interest.
\n',keywords:"COVID-19, psychosocial, social, impact, risk factors, HCWs",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/81991.pdf",chapterXML:"https://mts.intechopen.com/source/xml/81991.xml",downloadPdfUrl:"/chapter/pdf-download/81991",previewPdfUrl:"/chapter/pdf-preview/81991",totalDownloads:0,totalViews:0,totalCrossrefCites:null,dateSubmitted:"September 12th 2021",dateReviewed:"April 19th 2022",datePrePublished:"May 28th 2022",datePublished:null,dateFinished:"May 28th 2022",readingETA:"0",abstract:"COVID-19 outbreak reminds us of nationwide lockdowns, home-confinement, overburdened hospitals, country wide curfews, violent and chaotic health-facilities and domestic scenario and gradual but steady rise of stigmatizing factors like fear of isolation, racism, discrimination and marginalization cumulatively intensifying the unavoidable stress, fear, anxiety, depression, poor life quality, substance abuse resulting in enhanced mortality risk particularly among the health-compromised population. With objectives to analyze the psychosocial impact of COVID19 and to delineate the process of impact, by looking into its pathophysiology a literature review was carried on. Various impacts and adaptations were found. With a proper mapping algorithm, their responses can be understood. Different states of individual showed different responses to the same stress creating a gamut of responses which led to different socio-economic, socio-political, professional and psychosocial impact. Identification of stress, mapping of response and a better preparedness from experience can all help us in preventing and controlling it next time.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/81991",risUrl:"/chapter/ris/81991",signatures:"Kishor Kunal, Priyanka Choudhary, Jiwesh Kumar, Ravi Prakash, Anita Singh and Kirti Kanchan",book:{id:"10912",type:"book",title:"Psychosocial, Educational, and Economic Impacts of COVID-19",subtitle:null,fullTitle:"Psychosocial, Educational, and Economic Impacts of COVID-19",slug:null,publishedDate:null,bookSignature:"Dr. Jose C. Sánchez-García, Dr. Brizeida Hernandez-Sanchez, Dr. António Carrizo Moreira and Associate Prof. Alcides Monteiro",coverURL:"https://cdn.intechopen.com/books/images_new/10912.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80355-040-4",printIsbn:"978-1-80355-039-8",pdfIsbn:"978-1-80355-041-1",isAvailableForWebshopOrdering:!0,editors:[{id:"105695",title:"Dr.",name:"Jose C.",middleName:null,surname:"Sánchez-García",slug:"jose-c.-sanchez-garcia",fullName:"Jose C. Sánchez-García"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Methodology",level:"1"},{id:"sec_2_2",title:"2.1 Objectives",level:"2"},{id:"sec_3_2",title:"2.2 Data acquisition",level:"2"},{id:"sec_4_2",title:"2.3 Data analysis",level:"2"},{id:"sec_6",title:"3. Results and discussion",level:"1"},{id:"sec_6_2",title:"3.1 Social impact",level:"2"},{id:"sec_7_2",title:"3.2 Socio-economic impact",level:"2"},{id:"sec_8_2",title:"3.3 Socio-political impact",level:"2"},{id:"sec_9_2",title:"3.4 Social impact on health care",level:"2"},{id:"sec_10_2",title:"3.5 Professional impact on training",level:"2"},{id:"sec_11_2",title:"3.6 Risk factors for psychosocial impact",level:"2"},{id:"sec_12_2",title:"3.7 Pathophysiology- a fresh perspective",level:"2"},{id:"sec_13_2",title:"3.8 Future prospects",level:"2"},{id:"sec_15",title:"4. Conclusions",level:"1"},{id:"sec_19",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Serafini G, Parmigiani B, Amerio A, Aguglia A, Sher L, Amore M. The psychological impact of COVID-19 on the mental health in the general population. QJM. 22 Jun 2020;113(8):531-537. DOI: 10.1093/qjmed/hcaa201. Epub ahead of print. PMID: 32569360; PMCID: PMC7337855'},{id:"B2",body:'Joshi A. COVID-19 pandemic in India: Through psycho-social lens. Journal of Social and Economic Development. Sep 2021;23(2):414-437'},{id:"B3",body:'Chawla N, Tom A, Sen MS, Sagar R. Psychological impact of COVID-19 on children and adolescents: A systematic review. Indian Journal of Psychological Medicine. 2021;43:294-299'},{id:"B4",body:'Dong F, Liu H, Yang M, Lu C, Dai N, Zhang Y, et al. Immediate psychosocial impact on healthcare workers during COVID-19 pandemic in China: A systematic review and Meta-analysis. Frontiers in Psychology. 2021;12:645460'},{id:"B5",body:'Sheraton M, Deo N, Dutt T, Surani S, Hall-Flavin D, Kashyap R. Psychological effects of the COVID 19 pandemic on healthcare workers globally: A systematic review. Psychiatry Research. 2020;292:113360'},{id:"B6",body:'Fteropoulli T, Kalavana TV, Yiallourou A, Karaiskakis M, Koliou Mazeri M, Vryonides S, et al. Beyond the physical risk: Psychosocial impact and coping in healthcare professionals during the COVID-19 pandemic. Journal of Clinical Nursing. 6 Jul 2021. DOI: 10.1111/jocn.15938. Epub ahead of print. PMID: 34231263; PMCID: PMC8447326'},{id:"B7",body:'Dubey S, Biswas P, Ghosh R, Chatterjee S, Dubey MJ, Chatterjee S, et al. Psychosocial impact of COVID-19. Diabetes & Metabolic Syndrome: Clinical Research and Reviews. 2020;14:779-788'},{id:"B8",body:'Kunal K. Third eye model: A hypothesis to span the diversities of psychiatry and normalcy. Neuropsychiatry (London). 2019;9:2397-2418'},{id:"B9",body:'Caki N, Krupić D, Corr P ). Pyschosocial effects of the COVID-19 pandemic. In: Bozkurt V, Dawes G, Gulerce H, Westenbroek P, editors. The societal impacts of COVID-19: A transnational perspective. Istanbul, Turkey: Istanbul University Press. 2021. pp. 63-78. DOI: 10.26650/B/SS49.2021.006.05'},{id:"B10",body:'Veliyannoor P. The return of the repressed. COVID-19: The need for intervention at socio-cultural inscape. In: COVID-19 Pandemic: Challenges and Responses of Psychologists from India. Manickam LSS ed. Thiruvananthapuram: The Editor; 2020. pp. 108-129'},{id:"B11",body:'Saladino V, Algeri D, Auriemma V. The psychological and social impact of Covid-19: New perspectives of well-being. Frontiers in Psychology. 2020;11:577684'},{id:"B12",body:'Chick RC, Clifton GT, Peace KM, Propper BW, Hale DF, Alseidi AA, et al. Using technology to maintain the education of residents during the COVID-19 pandemic. Journal of Surgical Education. 2020;77:729-732'},{id:"B13",body:'Ahmed H, Allaf M, Elghazaly H. COVID-19 and medical education. The Lancet Infectious Diseases. 2020;20:777-778'},{id:"B14",body:'Daniel J. Education and the COVID-19 pandemic. Prospects. 2020;49:91-96'},{id:"B15",body:'Eysenbach G. How to fight an infodemic: The four pillars of infodemic management. Journal of Medical Internet Research. 2020;22:e21820'},{id:"B16",body:'Osofsky JD, Osofsky HJ, Mamon LY. Psychological and social impact of COVID-19. Psychological Trauma: Theory, Research, Practice, and Policy. 2020;12:468'},{id:"B17",body:'Saha K, Torous J, Caine ED, De Choudhury M. Psychosocial effects of the COVID-19 pandemic: Large-scale quasi-experimental study on social media. Journal of Medical Internet Research. 2020;22:e22600'},{id:"B18",body:'Xiao H, Zhang Y, Kong D, Li S, Yang N. The effects of social support on sleep quality of medical staff treating patients with coronavirus disease 2019 (COVID-19) in January and February 2020 in China. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2020;26:e923549-e923541'},{id:"B19",body:'Zhou X, Snoswell CL, Harding LE, Bambling M, Edirippulige S, Bai X, et al. The role of telehealth in reducing the mental health burden from COVID-19. Telemedicine and e-Health. 2020;26:377-379'},{id:"B20",body:'Orrù G, Marzetti F, Conversano C, Vagheggini G, Miccoli M, Ciacchini R, et al. Secondary traumatic stress and burnout in healthcare workers during COVID-19 outbreak. International Journal of Environmental Research and Public Health. 2021;18:337'},{id:"B21",body:'Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Network Open. 2020;3:e203976-e203976'},{id:"B22",body:'Edigin E, Eseaton PO, Shaka H, Ojemolon PE, Asemota IR, Akuna E. Impact of COVID-19 pandemic on medical postgraduate training in the United States. Medical Education Online. 2020;25:1774318'},{id:"B23",body:'Liang ZC, Ooi SBS, Wang W. Pandemics and their impact on medical training: Lessons from Singapore. Academic Medicine. 2020;95:1359-1361'},{id:"B24",body:'Upadhyaya GK, Jain VK, Iyengar KP, Patralekh MK, Vaish A. Impact of COVID-19 on post-graduate orthopaedic training in Delhi-NCR. Journal of Clinical Orthopaedics and Trauma. 2020;11:S687-S695'},{id:"B25",body:'Yuen J, Xie F. Medical education during the COVID-19 pandemic: Perspectives from UK trainees. Postgraduate Medical Journal. 2020;96:432-433'},{id:"B26",body:'Crosby DL, Sharma A. Insights on otolaryngology residency training during the COVID-19 pandemic. Otolaryngology and Head and Neck Surgery. 2020;163:38-41'},{id:"B27",body:'Romm KF, Patterson B, Wysota CN, Wang Y, Berg CJ. Predictors of negative psychosocial and health behavior impact of COVID-19 among young adults. Health Education Research. 2022;36(4):385-397. DOI: 10.1093/her/cyab026'},{id:"B28",body:'Suryavanshi N, Kadam A, Dhumal G, Nimkar S, Mave V, Gupta A, et al. Mental health and quality of life among healthcare professionals during the COVID-19 pandemic in India. Brain and Behavior. 2020;10:e01837'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Kishor Kunal",address:null,affiliation:'
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The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.
",metaTitle:"Our story",metaDescription:"The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.",metaKeywords:null,canonicalURL:"/page/our-story",contentRaw:'[{"type":"htmlEditorComponent","content":"
We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
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In the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
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The IntechOpen timeline
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2004
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Intech Open is founded in Vienna, Austria, by Alex Lazinica and Vedran Kordic, two PhD students, and their first Open Access journals and books are published.
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Alex and Vedran launch the first Open Access, peer-reviewed robotics journal and IntechOpen’s flagship publication, the International Journal of Advanced Robotic Systems (IJARS).
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2005
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IntechOpen publishes its first Open Access book: Cutting Edge Robotics.
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2006
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IntechOpen publishes a special issue of IJARS, featuring contributions from NASA scientists regarding the Mars Exploration Rover missions.
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2008
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Downloads milestone: 200,000 downloads reached
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2009
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Publishing milestone: the first 100 Open Access STM books are published
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2010
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Downloads milestone: one million downloads reached
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IntechOpen expands its book publishing into a new field: medicine.
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2011
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Publishing milestone: More than five million downloads reached
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IntechOpen publishes 1996 Nobel Prize in Chemistry winner Harold W. Kroto’s “Strategies to Successfully Cross-Link Carbon Nanotubes”. Find it here.
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IntechOpen and TBI collaborate on a project to explore the changing needs of researchers and the evolving ways that they discover, publish and exchange information. The result is the survey “Author Attitudes Towards Open Access Publishing: A Market Research Program”.
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IntechOpen hosts SHOW - Share Open Access Worldwide; a series of lectures, debates, round-tables and events to bring people together in discussion of open source principles, intellectual property, content licensing innovations, remixed and shared culture and free knowledge.
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2012
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Publishing milestone: 10 million downloads reached
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IntechOpen holds Interact2012, a free series of workshops held by figureheads of the scientific community including Professor Hiroshi Ishiguro, director of the Intelligent Robotics Laboratory, who took the audience through some of the most impressive human-robot interactions observed in his lab.
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2013
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IntechOpen joins the Committee on Publication Ethics (COPE) as part of a commitment to guaranteeing the highest standards of publishing.
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2014
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IntechOpen turns 10, with more than 30 million downloads to date.
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IntechOpen appoints its first Regional Representatives - members of the team situated around the world dedicated to increasing the visibility of our authors’ published work within their local scientific communities.
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2015
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Downloads milestone: More than 70 million downloads reached, more than doubling since the previous year.
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Publishing milestone: IntechOpen publishes its 2,500th book and 40,000th Open Access chapter, reaching 20,000 citations in Thomson Reuters ISI Web of Science.
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40 IntechOpen authors are included in the top one per cent of the world’s most-cited researchers.
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Thomson Reuters’ ISI Web of Science Book Citation Index begins indexing IntechOpen’s books in its database.
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2016
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IntechOpen is identified as a world leader in Simba Information’s Open Access Book Publishing 2016-2020 report and forecast. IntechOpen came in as the world’s largest Open Access book publisher by title count.
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2017
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Downloads milestone: IntechOpen reaches more than 100 million downloads
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Publishing milestone: IntechOpen publishes its 3,000th Open Access book, making it the largest Open Access book collection in the world
We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
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In the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
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The IntechOpen timeline
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2004
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Intech Open is founded in Vienna, Austria, by Alex Lazinica and Vedran Kordic, two PhD students, and their first Open Access journals and books are published.
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Alex and Vedran launch the first Open Access, peer-reviewed robotics journal and IntechOpen’s flagship publication, the International Journal of Advanced Robotic Systems (IJARS).
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2005
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IntechOpen publishes its first Open Access book: Cutting Edge Robotics.
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2006
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IntechOpen publishes a special issue of IJARS, featuring contributions from NASA scientists regarding the Mars Exploration Rover missions.
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2008
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Downloads milestone: 200,000 downloads reached
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2009
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Publishing milestone: the first 100 Open Access STM books are published
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2010
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Downloads milestone: one million downloads reached
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IntechOpen expands its book publishing into a new field: medicine.
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2011
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Publishing milestone: More than five million downloads reached
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IntechOpen publishes 1996 Nobel Prize in Chemistry winner Harold W. Kroto’s “Strategies to Successfully Cross-Link Carbon Nanotubes”. Find it here.
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IntechOpen and TBI collaborate on a project to explore the changing needs of researchers and the evolving ways that they discover, publish and exchange information. The result is the survey “Author Attitudes Towards Open Access Publishing: A Market Research Program”.
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IntechOpen hosts SHOW - Share Open Access Worldwide; a series of lectures, debates, round-tables and events to bring people together in discussion of open source principles, intellectual property, content licensing innovations, remixed and shared culture and free knowledge.
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2012
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Publishing milestone: 10 million downloads reached
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IntechOpen holds Interact2012, a free series of workshops held by figureheads of the scientific community including Professor Hiroshi Ishiguro, director of the Intelligent Robotics Laboratory, who took the audience through some of the most impressive human-robot interactions observed in his lab.
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2013
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IntechOpen joins the Committee on Publication Ethics (COPE) as part of a commitment to guaranteeing the highest standards of publishing.
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2014
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IntechOpen turns 10, with more than 30 million downloads to date.
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IntechOpen appoints its first Regional Representatives - members of the team situated around the world dedicated to increasing the visibility of our authors’ published work within their local scientific communities.
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2015
\n\n
\n\t
Downloads milestone: More than 70 million downloads reached, more than doubling since the previous year.
\n\t
Publishing milestone: IntechOpen publishes its 2,500th book and 40,000th Open Access chapter, reaching 20,000 citations in Thomson Reuters ISI Web of Science.
\n\t
40 IntechOpen authors are included in the top one per cent of the world’s most-cited researchers.
\n\t
Thomson Reuters’ ISI Web of Science Book Citation Index begins indexing IntechOpen’s books in its database.
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\n\n
2016
\n\n
\n\t
IntechOpen is identified as a world leader in Simba Information’s Open Access Book Publishing 2016-2020 report and forecast. IntechOpen came in as the world’s largest Open Access book publisher by title count.
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\n\n
2017
\n\n
\n\t
Downloads milestone: IntechOpen reaches more than 100 million downloads
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Publishing milestone: IntechOpen publishes its 3,000th Open Access book, making it the largest Open Access book collection in the world
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Carbonell Barrachina and Pilar Legua Murcia",authors:[{id:"178432",title:"Dr.",name:"David",middleName:null,surname:"Lopez Lluch",slug:"david-lopez-lluch",fullName:"David Lopez Lluch"},{id:"317122",title:"Dr.",name:"Francisca",middleName:null,surname:"Hernández García",slug:"francisca-hernandez-garcia",fullName:"Francisca Hernández García"},{id:"317205",title:"Ms.",name:"Lucia",middleName:null,surname:"Andreu Coll",slug:"lucia-andreu-coll",fullName:"Lucia Andreu Coll"},{id:"317206",title:"Ms.",name:"Marina",middleName:null,surname:"Cano-Lamadrid",slug:"marina-cano-lamadrid",fullName:"Marina Cano-Lamadrid"},{id:"317207",title:"Dr.",name:"Ángel",middleName:null,surname:"Carbonell Barrachina",slug:"angel-carbonell-barrachina",fullName:"Ángel Carbonell Barrachina"},{id:"317208",title:"Dr.",name:"Pilar",middleName:null,surname:"Legua Murcia",slug:"pilar-legua-murcia",fullName:"Pilar Legua Murcia"}]},{id:"25357",doi:"10.5772/29589",title:"Connection Between Structural Changes and Electrical Parameters of Pea Root Tissue Under Anoxia",slug:"connection-between-structural-changes-and-electrical-parameters-of-pea-root-tissue-under-anoxia",totalDownloads:1610,totalCrossrefCites:3,totalDimensionsCites:8,abstract:null,book:{id:"1051",slug:"anoxia",title:"Anoxia",fullTitle:"Anoxia"},signatures:"Eszter Vozáry, Ildikó Jócsák, Magdolna Droppa and Károly Bóka",authors:[{id:"78464",title:"Dr.",name:"Eszter",middleName:null,surname:"Vozary",slug:"eszter-vozary",fullName:"Eszter Vozary"},{id:"78515",title:"MSc.",name:"Ildikó",middleName:null,surname:"Jócsák",slug:"ildiko-jocsak",fullName:"Ildikó Jócsák"},{id:"78516",title:"Dr.",name:"Károly",middleName:null,surname:"Bóka",slug:"karoly-boka",fullName:"Károly Bóka"},{id:"78526",title:"Prof.",name:"Magdolna",middleName:null,surname:"Droppa",slug:"magdolna-droppa",fullName:"Magdolna Droppa"}]},{id:"65961",doi:"10.5772/intechopen.84872",title:"The Disturbed Habitat and Its Effects on the Animal Population",slug:"the-disturbed-habitat-and-its-effects-on-the-animal-population",totalDownloads:1528,totalCrossrefCites:1,totalDimensionsCites:7,abstract:"Changes in the “habitat” may interfere with the normal functioning of all biological systems. The existence of relationships between environmental changes and health in humans and animal species is well known and it has become generally accepted that poor health affects the animal’s natural behaviors and animal welfare and, consequently, food safety and animal production quality. Microclimate alterations, husbandry-management conditions, quality of human-animal interactions, feeding systems, and rearing environment represent the main factors that could negatively affect animal welfare and may produce behavioral, biochemical, endocrine, and pathological modifications in domestic and wild animals. Particularly, high stress levels can reduce the immune system response and promote infectious diseases. Adverse socio-environmental factors can represent a major stimulus to the development of different pathologies. This chapter will discuss the main pathological modifications described in domestic and wild animals due to “disturbed habitat” paying more attention to critical points detected in standard breeding systems.",book:{id:"8833",slug:"habitats-of-the-world-biodiversity-and-threats",title:"Habitats of the World",fullTitle:"Habitats of the World - Biodiversity and Threats"},signatures:"Maria Teresa Capucchio, Elena Colombino, Martina Tarantola, Davide Biagini, Loris Giovanni Alborali, Antonio Marco Maisano, Federico Scali, Federica Raspa, Emanuela Valle, Ilaria Biasato, Achille Schiavone, Cristian Salogni, Valentina Bar, Claudia Gili and Franco Guarda",authors:[{id:"57235",title:"Dr.",name:"Maria Teresa",middleName:null,surname:"Capucchio",slug:"maria-teresa-capucchio",fullName:"Maria Teresa Capucchio"},{id:"291161",title:"Dr.",name:"Elena",middleName:null,surname:"Colombino",slug:"elena-colombino",fullName:"Elena Colombino"},{id:"291162",title:"Dr.",name:"Martina",middleName:null,surname:"Tarantola",slug:"martina-tarantola",fullName:"Martina Tarantola"},{id:"291163",title:"Dr.",name:"Davide",middleName:null,surname:"Biagini",slug:"davide-biagini",fullName:"Davide Biagini"},{id:"291164",title:"Dr.",name:"Loris Giovanni",middleName:null,surname:"Alborali",slug:"loris-giovanni-alborali",fullName:"Loris Giovanni Alborali"},{id:"291165",title:"Dr.",name:"Antonio Marco",middleName:null,surname:"Maisano",slug:"antonio-marco-maisano",fullName:"Antonio Marco Maisano"},{id:"291166",title:"Dr.",name:"Federico",middleName:null,surname:"Scali",slug:"federico-scali",fullName:"Federico Scali"},{id:"291167",title:"Dr.",name:"Federica",middleName:null,surname:"Raspa",slug:"federica-raspa",fullName:"Federica Raspa"},{id:"291168",title:"Dr.",name:"Emanuela",middleName:null,surname:"Valle",slug:"emanuela-valle",fullName:"Emanuela Valle"},{id:"291169",title:"Dr.",name:"Ilaria",middleName:null,surname:"Biasato",slug:"ilaria-biasato",fullName:"Ilaria Biasato"},{id:"291170",title:"Prof.",name:"Achille",middleName:null,surname:"Schiavone",slug:"achille-schiavone",fullName:"Achille Schiavone"},{id:"291171",title:"Dr.",name:"Cristian",middleName:null,surname:"Salogni",slug:"cristian-salogni",fullName:"Cristian Salogni"},{id:"291172",title:"Dr.",name:"Valentina",middleName:null,surname:"Bar",slug:"valentina-bar",fullName:"Valentina Bar"},{id:"291173",title:"Dr.",name:"Claudia",middleName:null,surname:"Gili",slug:"claudia-gili",fullName:"Claudia Gili"},{id:"291174",title:"Prof.",name:"Franco",middleName:null,surname:"Guarda",slug:"franco-guarda",fullName:"Franco Guarda"}]}],mostDownloadedChaptersLast30Days:[{id:"65961",title:"The Disturbed Habitat and Its Effects on the Animal Population",slug:"the-disturbed-habitat-and-its-effects-on-the-animal-population",totalDownloads:1528,totalCrossrefCites:1,totalDimensionsCites:7,abstract:"Changes in the “habitat” may interfere with the normal functioning of all biological systems. The existence of relationships between environmental changes and health in humans and animal species is well known and it has become generally accepted that poor health affects the animal’s natural behaviors and animal welfare and, consequently, food safety and animal production quality. Microclimate alterations, husbandry-management conditions, quality of human-animal interactions, feeding systems, and rearing environment represent the main factors that could negatively affect animal welfare and may produce behavioral, biochemical, endocrine, and pathological modifications in domestic and wild animals. Particularly, high stress levels can reduce the immune system response and promote infectious diseases. Adverse socio-environmental factors can represent a major stimulus to the development of different pathologies. This chapter will discuss the main pathological modifications described in domestic and wild animals due to “disturbed habitat” paying more attention to critical points detected in standard breeding systems.",book:{id:"8833",slug:"habitats-of-the-world-biodiversity-and-threats",title:"Habitats of the World",fullTitle:"Habitats of the World - Biodiversity and Threats"},signatures:"Maria Teresa Capucchio, Elena Colombino, Martina Tarantola, Davide Biagini, Loris Giovanni Alborali, Antonio Marco Maisano, Federico Scali, Federica Raspa, Emanuela Valle, Ilaria Biasato, Achille Schiavone, Cristian Salogni, Valentina Bar, Claudia Gili and Franco Guarda",authors:[{id:"57235",title:"Dr.",name:"Maria Teresa",middleName:null,surname:"Capucchio",slug:"maria-teresa-capucchio",fullName:"Maria Teresa Capucchio"},{id:"291161",title:"Dr.",name:"Elena",middleName:null,surname:"Colombino",slug:"elena-colombino",fullName:"Elena Colombino"},{id:"291162",title:"Dr.",name:"Martina",middleName:null,surname:"Tarantola",slug:"martina-tarantola",fullName:"Martina Tarantola"},{id:"291163",title:"Dr.",name:"Davide",middleName:null,surname:"Biagini",slug:"davide-biagini",fullName:"Davide Biagini"},{id:"291164",title:"Dr.",name:"Loris Giovanni",middleName:null,surname:"Alborali",slug:"loris-giovanni-alborali",fullName:"Loris Giovanni Alborali"},{id:"291165",title:"Dr.",name:"Antonio Marco",middleName:null,surname:"Maisano",slug:"antonio-marco-maisano",fullName:"Antonio Marco Maisano"},{id:"291166",title:"Dr.",name:"Federico",middleName:null,surname:"Scali",slug:"federico-scali",fullName:"Federico Scali"},{id:"291167",title:"Dr.",name:"Federica",middleName:null,surname:"Raspa",slug:"federica-raspa",fullName:"Federica Raspa"},{id:"291168",title:"Dr.",name:"Emanuela",middleName:null,surname:"Valle",slug:"emanuela-valle",fullName:"Emanuela Valle"},{id:"291169",title:"Dr.",name:"Ilaria",middleName:null,surname:"Biasato",slug:"ilaria-biasato",fullName:"Ilaria Biasato"},{id:"291170",title:"Prof.",name:"Achille",middleName:null,surname:"Schiavone",slug:"achille-schiavone",fullName:"Achille Schiavone"},{id:"291171",title:"Dr.",name:"Cristian",middleName:null,surname:"Salogni",slug:"cristian-salogni",fullName:"Cristian Salogni"},{id:"291172",title:"Dr.",name:"Valentina",middleName:null,surname:"Bar",slug:"valentina-bar",fullName:"Valentina Bar"},{id:"291173",title:"Dr.",name:"Claudia",middleName:null,surname:"Gili",slug:"claudia-gili",fullName:"Claudia Gili"},{id:"291174",title:"Prof.",name:"Franco",middleName:null,surname:"Guarda",slug:"franco-guarda",fullName:"Franco Guarda"}]},{id:"73021",title:"Red Palm Weevil Rhynchophorus ferrugineus (Coleoptera: Curculionidae): Global Invasion, Current Management Options, Challenges and Future Prospects",slug:"red-palm-weevil-em-rhynchophorus-ferrugineus-em-coleoptera-curculionidae-global-invasion-current-man",totalDownloads:808,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The red palm weevil (RPW) Rhynchophorus ferrugineus (Coleoptera: Curculionidae) also known as the Asian palm weevil is a key pest of palms (Arecaceae) in diverse agro-ecosystems the world over. During March 2017, the Food and Agricultural Organization of the UN through its ‘Rome Declaration’ called for the urgent need to combat RPW by collaborative efforts and commitments at the country, regional and global levels to stop the spread of this devastating pest. There exist gaps and challenges in almost all the components of the current RPW-IPM strategy, particularly with regard to early detection, developing and implementing phytosanitary measures, lack of effective biological control agents in the field and poor farmer participation in the control programmes, which have made RPW control and eradication extremely difficult. This chapter gives an overview of the global invasion, current management options, challenges and future prospects for its effective control.",book:{id:"9698",slug:"invasive-species-introduction-pathways-economic-impact-and-possible-management-options",title:"Invasive Species",fullTitle:"Invasive Species - Introduction Pathways, Economic Impact, and Possible Management Options"},signatures:"Hamadttu Abdel Farag El-Shafie and Jose Romeno Faleiro",authors:[{id:"192142",title:"Dr.",name:"Hamadttu",middleName:null,surname:"El-Shafie",slug:"hamadttu-el-shafie",fullName:"Hamadttu El-Shafie"},{id:"320867",title:"Dr.",name:"Jose",middleName:null,surname:"Romeno Faleiro",slug:"jose-romeno-faleiro",fullName:"Jose Romeno Faleiro"}]},{id:"72961",title:"Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae): An Invasive Insect Pest Threatening the World Tomato Production",slug:"-em-tuta-absoluta-em-meyrick-lepidoptera-gelechiidae-an-invasive-insect-pest-threatening-the-world-t",totalDownloads:618,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"The South American tomato pinworm or tomato leaf miner (TLM), Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae), is a serious invasive and destructive insect pest of tomato (Solanum lycopersicum L.) worldwide. The moth can cause 100% damage in tomato crop in both greenhouses and open fields if control measures are not carried out. Due to the high reproduction potential, dispersal ability, and tolerance to environmental conditions, the TLM invaded most tomato-producing countries in Europe, Africa, and Asia. The tomato leaf miner originated in South America and was first introduced in Spain in 2006 and from where it spread to other part of the world. This chapter consolidates the rich literature on the pest with emphasis on invasion history, economic significance, and possible management options adopted worldwide.",book:{id:"9698",slug:"invasive-species-introduction-pathways-economic-impact-and-possible-management-options",title:"Invasive Species",fullTitle:"Invasive Species - Introduction Pathways, Economic Impact, and Possible Management Options"},signatures:"Hamadttu Abdel Farag El-Shafie",authors:[{id:"192142",title:"Dr.",name:"Hamadttu",middleName:null,surname:"El-Shafie",slug:"hamadttu-el-shafie",fullName:"Hamadttu El-Shafie"}]},{id:"72034",title:"Invasive Insects in India",slug:"invasive-insects-in-india",totalDownloads:898,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Invasive alien species (IAS) is an exotic species that becomes established in natural or seminatural ecosystems or habitats. It is an agent of change and threatens native biological diversity. Invasive insects in India have been a major threat to household commodities, human health, agricultural produce and environment. India is highly diversified in its weather and climate, which supports the establishment of various introduced insects from other parts of the world. Furthermore, globalisation has facilitated numerous introductions of invasive insect pests. There have been 23 invasive alien insects reported from India to date. This chapter exclusively deals with the characteristics of insects that make them invasive, the common pathways of entry of the invasive insects, the steps through which the introduced insect has established itself in the foreign land and finally the ways to manage them.",book:{id:"9698",slug:"invasive-species-introduction-pathways-economic-impact-and-possible-management-options",title:"Invasive Species",fullTitle:"Invasive Species - Introduction Pathways, Economic Impact, and Possible Management Options"},signatures:"Swoyam Singh, Jai Hind Sharma, Avinash Udikeri and Hashib Ansari",authors:[{id:"315507",title:"Dr.",name:"Swoyam",middleName:null,surname:"Singh",slug:"swoyam-singh",fullName:"Swoyam Singh"},{id:"317139",title:"MSc.",name:"Hashib",middleName:null,surname:"Ansari",slug:"hashib-ansari",fullName:"Hashib Ansari"},{id:"318716",title:"Mr.",name:"Jai Hind",middleName:null,surname:"Sharma",slug:"jai-hind-sharma",fullName:"Jai Hind Sharma"},{id:"318717",title:"Mr.",name:"Avinash",middleName:null,surname:"Udiker",slug:"avinash-udiker",fullName:"Avinash Udiker"}]},{id:"25356",title:"Increase in Anoxia in Lake Victoria and Its Effects on the Fishery",slug:"increase-in-anoxia-in-lake-victoria-and-its-effects-on-the-fishery",totalDownloads:3130,totalCrossrefCites:9,totalDimensionsCites:18,abstract:null,book:{id:"1051",slug:"anoxia",title:"Anoxia",fullTitle:"Anoxia"},signatures:"Murithi Njiru, Chrisphine Nyamweya, John Gichuki, Rose Mugidde, Oliva Mkumbo and Frans Witte",authors:[{id:"70254",title:"Dr.",name:"James",middleName:"Murithi",surname:"Njiru",slug:"james-njiru",fullName:"James Njiru"}]}],onlineFirstChaptersFilter:{topicId:"330",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:290,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. 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Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,annualVolume:11419,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,annualVolume:11420,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:249,paginationItems:[{id:"274452",title:"Dr.",name:"Yousif",middleName:"Mohamed",surname:"Abdallah",slug:"yousif-abdallah",fullName:"Yousif Abdallah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274452/images/8324_n.jpg",biography:"I certainly enjoyed my experience in Radiotherapy and Nuclear Medicine, particularly it has been in different institutions and hospitals with different Medical Cultures and allocated resources. Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. 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The motor of the society is the industry and the research of this topic has to be empowered in order to increase and improve the quality of our lives.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",keywords:"Machine Learning, Intelligence Algorithms, Data Science, Artificial Intelligence, Applications on Applied Intelligence"},{id:"23",title:"Computational Neuroscience",scope:"Computational neuroscience focuses on biologically realistic abstractions and models validated and solved through computational simulations to understand principles for the development, structure, physiology, and ability of the nervous system. This topic is dedicated to biologically plausible descriptions and computational models - at various abstraction levels - of neurons and neural systems. This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. 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Novel computational algorithms for image analysis, scene understanding, biometrics, deep learning and their software or hardware implementations for natural and medical images, robotics, VR/AR, applications are some research directions relevant to this topic.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",keywords:"Image Analysis, Scene Understanding, Biometrics, Deep Learning, Software Implementation, Hardware Implementation, Natural Images, Medical Images, Robotics, VR/AR"},{id:"25",title:"Evolutionary Computation",scope:"Evolutionary computing is a paradigm that has grown dramatically in recent years. This group of bio-inspired metaheuristics solves multiple optimization problems by applying the metaphor of natural selection. It so far has solved problems such as resource allocation, routing, schedule planning, and engineering design. Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"25",title:"Environmental Sciences",doi:"10.5772/intechopen.100362",issn:"2754-6713",scope:"
\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems. \r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
",coverUrl:"https://cdn.intechopen.com/series/covers/25.jpg",latestPublicationDate:"April 13th, 2022",hasOnlineFirst:!1,numberOfOpenTopics:4,numberOfPublishedChapters:9,numberOfPublishedBooks:1,editor:{id:"197485",title:"Dr.",name:"J. Kevin",middleName:null,surname:"Summers",fullName:"J. Kevin Summers",profilePictureURL:"https://mts.intechopen.com/storage/users/197485/images/system/197485.jpg",biography:"J. Kevin Summers is a Senior Research Ecologist at the Environmental Protection Agency’s (EPA) Gulf Ecosystem Measurement and Modeling Division. He is currently working with colleagues in the Sustainable and Healthy Communities Program to develop an index of community resilience to natural hazards, an index of human well-being that can be linked to changes in the ecosystem, social and economic services, and a community sustainability tool for communities with populations under 40,000. He leads research efforts for indicator and indices development. Dr. Summers is a systems ecologist and began his career at the EPA in 1989 and has worked in various programs and capacities. This includes leading the National Coastal Assessment in collaboration with the Office of Water which culminated in the award-winning National Coastal Condition Report series (four volumes between 2001 and 2012), and which integrates water quality, sediment quality, habitat, and biological data to assess the ecosystem condition of the United States estuaries. He was acting National Program Director for Ecology for the EPA between 2004 and 2006. He has authored approximately 150 peer-reviewed journal articles, book chapters, and reports and has received many awards for technical accomplishments from the EPA and from outside of the agency. Dr. Summers holds a BA in Zoology and Psychology, an MA in Ecology, and Ph.D. in Systems Ecology/Biology.",institutionString:null,institution:{name:"Environmental Protection Agency",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"38",title:"Pollution",keywords:"Human activity, Pollutants, Reduced risks, Population growth, Waste disposal, Remediation, Clean environment",scope:"
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",annualVolume:11966,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null,editorialBoard:[{id:"252368",title:"Dr.",name:"Meng-Chuan",middleName:null,surname:"Ong",fullName:"Meng-Chuan Ong",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRVotQAG/Profile_Picture_2022-05-20T12:04:28.jpg",institutionString:null,institution:{name:"Universiti Malaysia Terengganu",institutionURL:null,country:{name:"Malaysia"}}},{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",institutionString:null,institution:{name:"Aswan University",institutionURL:null,country:{name:"Egypt"}}},{id:"187907",title:"Dr.",name:"Olga",middleName:null,surname:"Anne",fullName:"Olga Anne",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBE5QAO/Profile_Picture_2022-04-07T09:42:13.png",institutionString:null,institution:{name:"Klaipeda State University of Applied Sciences",institutionURL:null,country:{name:"Lithuania"}}}]},{id:"39",title:"Environmental Resilience and Management",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices",scope:"
\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
",annualVolume:11967,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",institutionString:"Miguel Hernández University of Elche, Spain",institution:null},editorTwo:null,editorThree:null,editorialBoard:[{id:"177015",title:"Prof.",name:"Elke Jurandy",middleName:null,surname:"Bran Nogueira Cardoso",fullName:"Elke Jurandy Bran Nogueira Cardoso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGxzQAG/Profile_Picture_2022-03-25T08:32:33.jpg",institutionString:"Universidade de São Paulo, Brazil",institution:null},{id:"211260",title:"Dr.",name:"Sandra",middleName:null,surname:"Ricart",fullName:"Sandra Ricart",profilePictureURL:"https://mts.intechopen.com/storage/users/211260/images/system/211260.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}}]},{id:"40",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"
\r\n\tIn general, the harsher the environmental conditions in an ecosystem, the lower the biodiversity. Changes in the environment caused by human activity accelerate the impoverishment of biodiversity.
\r\n
\r\n\tBiodiversity refers to “the variability of living organisms from any source, including terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; it includes diversity within each species, between species, and that of ecosystems”.
\r\n
\r\n\tBiodiversity provides food security and constitutes a gene pool for biotechnology, especially in the field of agriculture and medicine, and promotes the development of ecotourism.
\r\n
\r\n\tCurrently, biologists admit that we are witnessing the first phases of the seventh mass extinction caused by human intervention. It is estimated that the current rate of extinction is between a hundred and a thousand times faster than it was when man first appeared. The disappearance of species is caused not only by an accelerated rate of extinction, but also by a decrease in the rate of emergence of new species as human activities degrade the natural environment. The conservation of biological diversity is "a common concern of humanity" and an integral part of the development process. Its objectives are “the conservation of biological diversity, the sustainable use of its components, and the fair and equitable sharing of the benefits resulting from the use of genetic resources”.
\r\n
\r\n\tThe following are the main causes of biodiversity loss:
\r\n
\r\n\t• The destruction of natural habitats to expand urban and agricultural areas and to obtain timber, minerals and other natural resources.
\r\n
\r\n\t• The introduction of alien species into a habitat, whether intentionally or unintentionally which has an impact on the fauna and flora of the area, and as a result, they are reduced or become extinct.
\r\n
\r\n\t• Pollution from industrial and agricultural products, which devastate the fauna and flora, especially those in fresh water.
\r\n
\r\n\t• Global warming, which is seen as a threat to biological diversity, and will become increasingly important in the future.
",annualVolume:11968,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/40.jpg",editor:{id:"209149",title:"Prof.",name:"Salustiano",middleName:null,surname:"Mato",fullName:"Salustiano Mato",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLREQA4/Profile_Picture_2022-03-31T10:23:50.png",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorTwo:{id:"60498",title:"Prof.",name:"Josefina",middleName:null,surname:"Garrido",fullName:"Josefina Garrido",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRj1VQAS/Profile_Picture_2022-03-31T10:06:51.jpg",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorThree:{id:"464288",title:"Dr.",name:"Francisco",middleName:null,surname:"Ramil",fullName:"Francisco Ramil",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003RI7lHQAT/Profile_Picture_2022-03-31T10:15:35.png",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorialBoard:[{id:"220987",title:"Dr.",name:"António",middleName:"Onofre",surname:"Soares",fullName:"António Soares",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNtzQAG/Profile_Picture_1644499672340",institutionString:null,institution:{name:"University of the Azores",institutionURL:null,country:{name:"Portugal"}}}]},{id:"41",title:"Water Science",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection",scope:"
\r\n\tWater is not only a crucial substance needed for biological life on Earth, but it is also a basic requirement for the existence and development of the human society. Owing to the importance of water to life on Earth, early researchers conducted numerous studies and analyses on the liquid form of water from the perspectives of chemistry, physics, earth science, and biology, and concluded that Earth is a "water polo". Water covers approximately 71% of Earth's surface. However, 97.2% of this water is seawater, 21.5% is icebergs and glaciers, and only 0.65% is freshwater that can be used directly by humans. As a result, the amount of water reserves available for human consumption is limited. The development, utilization, and protection of freshwater resources has become the focus of water science research for the continued improvement of human livelihoods and society.
\r\n
\r\n\tWater exists as solid, liquid, and gas within Earth’s atmosphere, lithosphere, and biosphere. Liquid water is used for a variety of purposes besides drinking, including power generation, ecology, landscaping, and shipping. Because water is involved in various environmental hydrological processes as well as numerous aspects of the economy and human society, the study of various phenomena in the hydrosphere, the laws governing their occurrence and development, the relationship between the hydrosphere and other spheres of Earth, and the relationship between water and social development, are all part of water science. Knowledge systems for water science are improving continuously. Water science has become a specialized field concerned with the identification of its physical, chemical, and biological properties. In addition, it reveals the laws of water distribution, movement, and circulation, and proposes methods and tools for water development, utilization, planning, management, and protection. Currently, the field of water science covers research related to topics such as hydrology, water resources and water environment. It also includes research on water related issues such as safety, engineering, economy, law, culture, information, and education.
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