Sub-normal numbers for floating-point numbers with
\r\n\tThe protection of biodiversity is a major target of the European Union Marine Strategy Framework Directive, requiring an assessment of the status of biodiversity on the level of species, habitats, and ecosystems including genetic diversity and the role of biodiversity in food web structure and functioning. The restoration of marine ecosystems can support the productivity and reliability of goods and services that the ocean provides to humankind, to maintain ecosystem integrity and stability. Some of the goods produced by the marine ecosystem services are fish harvests, wild plant and animal resources, water, some of the services provided recreation, tourism, breeding and nursery habitats, water transport, carbon sequestration, erosion control, and habitat provision.
",isbn:"978-1-83968-460-9",printIsbn:"978-1-83968-459-3",pdfIsbn:"978-1-83968-544-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"727e7eb3d4ba529ec5eb4f150e078523",bookSignature:"Dr. Ana M.M. Marta Gonçalves",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10845.jpg",keywords:"Non-indigenous Species, Dynamics, Ecosystem Maturation, Ecological Succession, Water Quality, Recovery, Biodiversity, Environmental Status, Ecosystem Services, Goods Production, Carbohydrates, Carrageenan",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 14th 2022",dateEndSecondStepPublish:"June 22nd 2022",dateEndThirdStepPublish:"August 21st 2022",dateEndFourthStepPublish:"November 9th 2022",dateEndFifthStepPublish:"January 8th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Ana Marta Gonçalves (h-index 19) holds a Ph.D. in Biology, from the University of Coimbra, Portugal, in collaboration with Ghent University, in 2011. During her research career obtained several grants is highly international competitive calls, including the MARS award for young scientists funded by The Royal Netherlands Institute for Sea Research (NIOZ) and the Foundation for Science and Technology (FCT, Portugal) grants.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"320124",title:"Dr.",name:"Ana M.M.",middleName:"Marta",surname:"Gonçalves",slug:"ana-m.m.-goncalves",fullName:"Ana M.M. Gonçalves",profilePictureURL:"https://mts.intechopen.com/storage/users/320124/images/system/320124.jpg",biography:"Ana Marta Gonçalves obtained a Ph.D. in Biology with a specialization in Ecology from the University of Coimbra, Portugal, in collaboration with Ghent University, Belgium, in 2011. Currently, she is an auxiliary researcher at the Marine and Environmental Sciences Center (MARE), Portugal, where she is also a member of the Directive Board. Since 2016, she has been a member of the Scientific Council of the Institute for Interdisciplinary Research, University of Coimbra (IIIUC). Dr. Gonçalves holds various administrative and management positions in international networks, societies (e.g., Society of Environmental Toxicology and Chemistry, AIL), and associations (e.g., PROAQUA). She is an editorial board member and reviewer for several indexed journals. She has published more than 70 journal articles, 50 book chapters, and 165 communications in international scientific events. She participated as a member and/or coordinator in more than twenty-five national and international projects and is currently the coordinator of four research projects. She has supervised more than ninety-five national and international undergraduate and graduate students. She has experience as a teacher of university courses and in accredited training sessions for teachers. Additionally, she has coordinated several ocean literacy and environmental education activities for kindergarten and school students. During her research career, Dr. Gonçalves obtained several grants and a MARS award for young scientists funded by The Royal Netherlands Institute for Sea Research (NIOZ).\n\nShe has expertise in biosafety, biochemical pathways, and impacts of stressors in aquatic species. Her research focus is on the valorization of marine resources and their applications in the industrial sector, such as the food and pharmaceutical industries. Her studies also highlight the application of biomarker tools for monitoring and managing aquatic systems",institutionString:"University of Coimbra",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Coimbra",institutionURL:null,country:{name:"Portugal"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"12",title:"Environmental Sciences",slug:"environmental-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"278926",firstName:"Ivana",lastName:"Barac",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/278926/images/8058_n.jpg",email:"ivana.b@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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In this chapter, the focus is on the development of quantum algorithms for solving nonlinear differential equations, highlighting key challenges that arise from the non-linearity of the equations to be solved. For this application of quantum computing, progress has so far been relatively limited and in this work, a promising approach to deriving efficient quantum algorithms is proposed. Although the focus is on non-linear equations related to fluid mechanics, the approach put forward here is applicable to a much wider range of problems. Furthermore, in developing the proposed method, efficient quantum circuits involving floating-point arithmetic were created, in contrast to the more commonly used fixed-point arithmetic employed in a range of quantum algorithms. This aspect of the work described here should also be useful for a wider audience. In this work, the development of quantum algorithms for the nonlinear governing equations for fluid mechanics is described with a particular focus on representing the non-linear product terms in the equations. A key aspect of the derived quantum circuits in the present work is the (temporary) representation of the solution in the computational basis, along with the the use of a floating-point data representation in the arithmetic operations. The quantum circuits for obtaining the non-linear product terms are new developments and form the main contribution of this work. In recent years, a small number of works have considered quantum computing applications to fluid mechanics [2, 3, 4, 5, 6, 7, 8]. A brief review of this previous work will be presented in Section 2 and will provide context to the proposed approach. Related work on algorithms with representation in the computational basis is reviewed in this chapter. This chapter is structured as follows. Section 2 describes the background to the current work. Section 3 reviews the key challenges related to treating nonlinear differential equations in a quantum computing context, followed by a discussion of the nonlinear governing equations in fluids dynamics in Section 4. Section 5 then describes how nonlinear terms in governing equations can be evaluated in quantum algorithms using the computational basis. Section 6 and Section 7 discuss the quantum circuits used for computing the square of a floating-point number and the multiplication of two floating-point numbers, respectively. The simulation and verification of the derived quantum circuits is presented in Section 8. The complexity of the circuits is analyzed in Section 9. Finally, conclusions from this work and suggestions for further work are presented in Section 10.
For a small number of applications, quantum algorithms have been developed that display a significant speed-up relative to classical methods. Computational quantum chemistry is proving to be one of the key areas of application. Important developments for a wider range of applications include quantum algorithms for linear systems [9, 10] and the Poisson equation [11]. Applications to computational science and engineering problems beyond quantum chemistry have only recently begun to appear [4, 5, 6, 12, 13, 14]. Despite this research effort, progress in defining suitable engineering applications for quantum computers has been limited.
Significant progress has been made in recent years in the development of quantum algorithms for linear ordinary differential equations (ODEs) as well as linear partial differential equations (PDEs) [15, 16, 17, 18, 19]. However, in contract to this progress for linear equations, there has not been similar progress in the development of quantum algorithms for nonlinear ODEs and nonlinear PDEs. An early work by Leyton and Osborne [20] presented an innovative and highly ambitious algorithm. However, the computational complexity of this work involves exponential dependency on the time interval used in the time integration. A small number of more recent works have addressed nonlinear differential equations and typically algorithms for very specific problems were obtained [8]. Therefore, much research work is needed into quantum algorithms for a wider range of nonlinear problems.
Early work in quantum computing relevant to the field of Computational Fluid Dynamics (CFD) mainly involved the work on quantum lattice-gas models by Yepez and co-workers [2, 3]. This work typically used type-II quantum computers, consisting of a large lattice of small quantum computers interconnected in nearest neighbor fashion by classical communication channels. In contrast to these quantum lattice-gas based approaches, the present study focuses on quantum algorithms designed for near-future ‘universal’ quantum computers. The potential of quantum computing in the context of direct numerical simulation of flows was reviewed recently by Griffin et al. [7], showing that a number of further developments are needed to make this approach viable.
Typically, there are two methods of encoding the result of a quantum algorithm: encoding within the computational basis of the quantum state and encoding within the amplitudes of the quantum state. The widely-used Quantum Fourier Transform (QFT) uses the second approach. The QFT with complexity
Here, the two different encoding methods are illustrated using the discrete Fourier Transform (DFT). The QFT performs the DFT in terms of amplitudes as,
The QFT performs a DFT on a list of complex numbers, and the result is stored as amplitudes of a quantum state vector. In order to extract the individual Fourier components, measurements need to be performed on the quantum state vector. Therefore, the QFT is not directly useful for determining the Fourier-transformed coefficients of the input state. However, the QFT is widely used as a subroutine in larger algorithms. In contrast to the amplitude encoding in Eq. (1), Zhou et al. [21] presented a quantum algorithm computing the Fourier transform in the computational basis (termed QFTC). This quantum algorithm encodes Fourier coefficients with fidelity
where
which can be efficiently implemented if
An early work by Leyton and Osborne [20] introduced a quantum algorithm to solve nonlinear differential equations with an unfavorable complexity. Since then, very few works have considered quantum algorithms for nonlinear equations. In contrast, algorithms for linear differential equations have continued to receive significant attention. As an example, advanced quantum spectral methods for differential equations were published recently by Childs and Liu [19].
A key contributing factor to the limited progress in algorithms for non-linear problems is the inherent linearity of quantum mechanics. For quantum algorithms encoding information as amplitudes of a quantum state vector, nonlinear (product) terms cannot be obtained by multiplying these amplitudes by themselves, as a result of the no-cloning theorem that prohibits the copying of an arbitrary quantum state. Furthermore, all quantum-gate operations (with the exception of measurements) in the quantum-circuit model used here need to be unitary and reversible. These requirements add further challenges to representing nonlinear terms when using the amplitude-based encoding approach. Specifically, in a normalized quantum state vector all amplitudes in the vector are
One possible way around these problems associated with nonlinear terms would be a hybrid quantum-classical approach where the nonlinear products are computed on a classical computer. However, due to the complexity introduced by measuring the quantum state (needed before each transfer of information to the classical computer) and the cost of (re-)initialization of the quantum computer with the result of these products, this is not a promising line of development. It is highly unlikely to lead to a quantum speed-up. Recently, Variational Quantum Computing (VQC) was introduced as an effective hybrid classical-quantum approach [22, 23], firstly for applications in quantum chemistry and more recently for a wider range of linear and nonlinear problems [24]. The VQC approach constructs the required solution from a layered network, as illustrated in Figure 1. As shown in Figure 1(a), multiple layers are used (
Illustration of the Variational Quantum computing (VQC) approach (adapted from Lubasch et al. [
The Navier–Stokes equations for an incompressible, Newtonian fluid can be written as,
where
The development of quantum algorithms for fluid dynamics is clearly at a very early stage and therefore it is essential that different approaches are considered.
In the present work, an alternative approach to introducing the nonlinear terms of nonlinear differential equations into a quantum algorithm is investigated. Specifically, the assumption is made that in a large-scale quantum algorithm for the solution of the nonlinear (partial) differential equations, the solution is encoded in terms of amplitude in the quantum state vector, i.e. the approach used in a wide range of algorithms including the QFT. Then, for the nonlinear terms of the equations, the following steps are suggested. First, within the larger quantum algorithm, a quantum algorithm is embedded that converts the solution from the quantum-amplitude representation to a representation in the computational basis. Recently, quantum algorithms for this ‘analog-to-digital conversion’ were published by Mitarai et al. [25]. Using the representation of the solution in the computational basis, the required nonlinear terms are then efficiently evaluated using quantum circuits presented later in this chapter. Once computed, a conversion back to quantum-amplitude representation is to be used, enabling the rest of the quantum algorithm to proceed. For this ‘digital-to-analog’ conversion, quantum algorithms were recently studied and published by SaiToh [26]. For the representation in the computational basis, a fixed-point approach is typically employed to represent real or complex numbers in quantum algorithms. The number of additional qubits required when using computational-basis encoding depends directly on the number of qubits required to represent the real and complex numbers needed in the algorithm. In the present work, a different approach is put forward: instead of using fixed-point arithmetic, a floating-point representation is used.
In the literature, quantum arithmetic using floating-point numbers has received very little attention so far. Haener et al. [27] described an investigation into quantum circuits for floating-point addition and multiplications and compared automatically generated circuits from Verilog implementations with hand-crafted optimized circuits. Their study provides evidence that floating-point arithmetic is a viable candidate for use in quantum computing, at least for typical scientific applications, where addition operations usually do not dominate the computation. Following on from these conclusions, the present work investigates the use of floating-point arithmetic as part of evaluating nonlinear terms in the computational basis.
Quantum arithmetic in the computational basis constitutes an important component of many quantum algorithms, and as a result reversible implementations of algebraic functions (addition, multiplication, inverse, square root, etc.) have been widely studied. In contrast, there is relatively little work on quantum algorithm implementation of higher-level transcendental functions, such as logarithmic, exponential, trigonometric and inverse trigonometric functions. Examples of applications of trigonometric and inverse trigonometric functions in the computational basis can be found in the famous HHL algorithm [9] and in the state preparation algorithm introduced by Grover and Rudolph [28]. More recently, a quantum algorithm for approximating the QR decomposition of a
A fixed-point number held in an
where
where the numbers
Here, it is important to note that always
Based on the floating point representation defined in the IEEE standard, the present work introduces a floating-point system with fewer bits (i.e. qubits in this case) than the 32 used for single format numbers. This is the direct result of the limited number of qubits available on current and near-term quantum computers. To optimize the range of floating-point numbers that can be represented with the approach used here, the following key aspects of the IEEE standard were adopted:
For the mantissa only the fractional part is stored,
Exponent bit strings
The remaining range of exponent bit strings is used for a range of exponential centred around
Sub-normal numbers are used to extend the range of small numbers,
Rounding down to nearest is used as rounding mode,
Only unsigned numbers are considered for simplicity. Signed numbers can easily be obtained by adding a further ‘sign’ qubit.
In this work, a floating-point number is represented as an
Sub-normal numbers for floating-point numbers with
Similarly, using
Sub-normal numbers for floating-point numbers with
In line with the IEEE 754 standard, exponent state
For a floating-point number defined by
For
Quantum circuit used to compute square of mantissa (for
Quantum circuit used to obtain exponent for squaring operation (
For certain normalized input numbers the squaring operation leads to outputs truncated to
Quantum circuits used in obtaining output mantissa for squaring operation, including sub-normal numbers and underflow/overflow protection (
Quantum circuit used to obtain exponent for squaring operation, including sub-normal numbers and under/overflow protection (
For a fixed value of
Quantum circuit used to set output mantissa for squaring operation, including sub-normal numbers and underflow/overflow protection (
In the interest of brevity, only the main features of the quantum circuits used for multiplication of two quantum floating-point numbers are summarized here. Figure 7 illustrates the quantum circuit used to compute the product of the mantissas of two inputs. Compared to the circuit shown in Figure 2 the main difference is that ancilla qubit
Quantum circuit used in multiplying the mantissa of two input numbers (
The proposed quantum circuits for squaring and multiplying floating-point numbers as part of the computational-basis representation, were systematically verified by gate-level simulation of the circuits for a wide range of cases with and without sub-normal numbers as well as cases with overflow results. The C++ quantum computer simulator detailed in previous work [4] was used for this purpose. To illustrate the process, the quantum algorithm used to square numbers with
where
Input | Initial state | Output state |
---|---|---|
Results from quantum circuit simulation for representative range of inputs (squaring
Before analyzing the quantum circuits introduced here in terms of complexity, first the choice of
In a two-dimensional flow field, the non-linear terms appearing in the Navier–Stokes equations, shown in Eq. (4), involve the square of the velocity components in
Considering a
Rounding down - using sub-normal numbers | |||||
3 | 3 | ||||
4 | 3 | ||||
5 | 3 | ||||
6 | 3 | ||||
7 | 3 | ||||
8 | 3 | ||||
4 | 4 | ||||
5 | 4 | ||||
6 | 4 | ||||
7 | 4 | ||||
8 | 4 | ||||
Rounding down - without sub-normal numbers | |||||
3 | 3 | ||||
4 | 3 | ||||
5 | 3 | ||||
6 | 3 | ||||
7 | 3 | ||||
8 | 3 | ||||
4 | 4 | ||||
5 | 4 | ||||
6 | 4 | ||||
7 | 4 | ||||
8 | 4 |
Approximation errors in Taylor-green vortex flow field due to reduced-precision floating-point representation.
For
Rounding down - using sub-normal numbers | |||||
4 | 4 | ||||
5 | 4 | ||||
6 | 4 | ||||
7 | 4 | ||||
8 | 4 | ||||
Rounding down - without sub-normal numbers | |||||
4 | 4 | ||||
5 | 4 | ||||
6 | 4 | ||||
7 | 4 | ||||
8 | 4 |
Approximation errors of velocity products in Taylor-green vortex flow field due to reduced-precision floating-point representation.
9 | 27 | ||
14 | 66 | ||
20 | 130 |
Number of controlled-phase gates (
6 | 9 | ||||
10 | 14 | ||||
15 | 20 | ||||
21 |
Number of controlled-phase gates (CPHASE) in phase-addition step for modulo adder (
The quantum circuits presented here for squaring two floating-point numbers in the format proposed show that by accounting for sub-normal numbers and under/overflow an additional number of multi-qubit controlled-NOT gates is needed. However, for the examples analyzed a polynomial dependence on
The challenges associated with representing non-linear differential equations in terms of quantum circuits were discussed in this chapter. In this work, a new approach for representing product-terms in nonlinear equations suitable for near-term (e.g. NISQ generation) quantum computers was proposed. A key aspect discussed is the (temporary) representation of the variables in the computational basis. Furthermore, the use of a suitably-chosen floating-point format was detailed. The importance of including sub-normal numbers, such as defined in the IEEE 758 standard for floating-point arithmetic on classical computers, was demonstrated. Based on the current findings, a number of suggestions for further work can be put forward. The presented circuits performed arithmetic for a single set of input data, i.e. equivalent to data for a single point in a computational domain. Extending the approach to a multi-dimensional computational mesh is a first step to consider. A complexity analysis will be needed to assess the potential speed-up relative to classical discretization approaches for the considered equations. A further step involves investigating how the proposed approach can be made part of a larger quantum algorithm, where a mix of amplitude-based encoding and computational-basis encoding occurs. A key aspect is therefore the development of efficient quantum circuits to perform the required conversions between the two different encoding approaches. Finally, further work is needed to establish how the approach presented here can be used in a wider range of quantum computing applications.
In this chapter, we present the analysis and design of cyber-physical systems using graph-theoretic ideas. We are motivated by the energy-efficient control of buildings.
Our fundamental view of a building is of overlapping, interacting networks, as shown in Figure 1. This diagram depicts the dominant phenomenon that contributes to building as a network (or graphs). These networks consist of nodes that constitute distinct sub-systems. For example, in heat-sensing or networks of humans, the nodes may refer to specific rooms in a house or office building. In contrast, nodes might represent a particular sensor, actuator, or perhaps a computational unit in a control network. The links between nodes denote communication of fluctuating or sharing variables in a system, such as the passage of people in a human network between rooms through hallways, or the heat flow between rooms in the thermal network through walls and doors. Smaller circles in Figure 1 indicate links between networks. Note that typical graph-based networks assume links that are in some way constant, but as we will see, in some networks, such as the building thermal network, links between nodes may be dynamic.
A building as a collection of interacting networks.
Control of distributed systems, such as shown in Figure 1 is a currently active area of research within the field of control systems. By a distributed system, we mean one with many inputs and outputs, possibly spatially distributed dynamics, and a decentralized decision and control architecture, with restrictions on communication between computational nodes. Many researchers have focused basically on homogeneous systems. However, a building may be viewed as a hybrid system where a physical process (the structure itself) has been augmented with a hardware infrastructure (sensors and actuators) and a cyber-infrastructure (communication and decision nodes). Such overlaid heterogeneous systems with constrained connectivity and interaction between the different layers present challenges and system optimization and control opportunities. What is needed are ways to reason about discrete, multi-attribute heterogeneous entities (such as cyber-systems) and continuous, heterogeneous processes (such as physical phenomena) operating on a hierarchy of layered graphs related to each other through a set of mappings or transformations.
In this chapter, we consider methods for studying distributed systems that are heterogeneous and possibly spatially varying. Though a building can be seen as a set of interconnected networks, we consider only the thermal network. We begin by showing how a building’s thermal processes can be modeled as a graph whose node variables are temperature and heat flows and whose interconnections are walls, doors, windows, etc. In our graphical representation of a building, both the nodes and the interconnections can be (heterogeneous) dynamic systems. We call this a
The consensus protocols in networking in engineering have received significant academic and corporate attention because of their vast array of potential applications in various fields. Robotics, transportation, sensor networking, communication networking, biology, and physics are only some potential fields that networking consensus could benefit. This section aims to analyze a generalization of consensus problems whereby the weights of network edges are no longer static gains. Instead, they are dynamic systems, which lead towards
Network topology is static for the consensus networks, meaning that there are no dynamics in the interconnections between the nodes
The consensus protocol (Eq. (1)) can be written in matrix form as:
where
For the multi-agent consensus problem, suppose that
There have been many engineering scientists in the past years involved in the controllability of dynamic consensus networks. The focus was on controlling dynamic consensus networks under the leader-follower approach, where some nodes are considered leaders and other nodes are followers. This approach aims to transfer followers’ trajectories from an initial position to the desired position (set-point) by adequately selecting the leaders’ trajectory. Many authors [2, 3, 4, 5] have considered this framework by using some algebraic methods and the eigenvalues and eigenvectors of the dynamic Laplacian matrix. Other researchers also investigated the controllability using graphic tools such as the graph’s equitable partition [4] and symmetry properties [3]. These graphical tools are built based on the graph’s configuration and topology associated with the consensus network. The controllability investigation using the minimum energy for static consensus networks using the first-order system formulated and proposed in [6, 7]. This Chapter will investigate the controllability for dynamic consensus networks with edges (links) of rational dynamical systems.
Several researchers have already studied controllability analysis for consensus networks with static topology. The vast majority of these published academic studies have investigated the impact of the static topology on the controllability of their respective consensus networks. Those studies have [8] introduced a graph-theoretic characterization of static networks’ structural controllability with only a single leader. In their research, many illustrate that a static network with variable topology is structurally controllable if the union graph of the underlying static topologies is connected. For example, in [9], the controllability of the network was investigated using the size of the graph as well as its connectivity. Meanwhile, controllability for leader-based, multi-agent systems has been analyzed by [7, 10] based on connectivity and the null space of the leader and followers’ incidence matrices. Controllability using graph symmetry and equitable partition properties has been addressed in [11, 12]. The paper [13] formulated an equivalent data-driven Hautus-type test for a general input/output system that assumes no knowledge of the system’s state. The authors’ work proposed in this Chapter also provided an algorithm for data-driven verification of controllability of the system. They used the singular value decomposition of the Hankel matrix. A multi-vehicle system’s consensus problem was proposed and analyzed by [14, 15] with a time- varying reference state. Under the condition, only a portion of the vehicles can access the reference state in this problem. Those vehicles might not have the ability to share the information with the other cars in the team. Although their paper focused on developing an algorithm for investigating the consensus conditions for a directed fixed information exchange topology, so it is helpful to extend this algorithm to directed switching information-exchange typologies. In our article, the topology (edges) that describes the interconnections between nodes is considered time-varying rational transfer functions. Investigating the consensus conditions and the controllability for a multi-vehicle system might be one of the motivating applications of this work.
The consensus protocol, such as outlined in (Eq. (1)) and its variants, have been studied extensively in previously published academic studies. The findings from these studies have been applied in many domains, such as for formation motion control during time agents are mobile. However, the common intellectual idea of the consensus paradigm can be restrictive for researchers and engineers alike in several ways. For example, notice that we have interpreted the consensus problem as having integrating nodes and static weights. In the next section, will we extend this idea to networks with weights, which were transfer functions or nodes are more than just integrators. We will explore this dilemma by modeling heat transfer in buildings [16, 17, 18, 19]. By the notation “dynamic systems,” we mean that linear ordinary differential equations (LODEs) are described as relationships between the system variables. We call such networks
The Chapter is organized as follows: In Section 2, we present a general framework for a dynamic consensus network. We present a detailed study of modeling thermal processes in buildings as directed, dynamic graphs, beginning with a simple two-room model and transitioning to multiple interconnected rooms. Section 3 outlines a theoretical framework dedicated to these dynamic graphs and dynamic consensus networks. This framework will introduce the notion of a degree of dynamics, adjacency, incident, and Laplacian matrices in a way that naturally extends these concepts from a static case. By modeling this, one can easily define equivalent concepts of dynamic interconnection matrices and dynamic consensus networks.
This Section first presents examples showing how a dynamic graph can arise in applications and then give a general framework for a dynamic consensus network. We present a detailed study of modeling thermal processes in buildings as directed, dynamic graphs, beginning with a simple two-room model and transitioning to a model with multiple interconnected rooms. Motivated by this example, we then propose a mathematical framework in service of dynamic graphs and dynamic consensus networks.
Historically, there has always been a recognized need to model the energy processes within buildings. Typical examples of this modeling application are sizing HVAC equipment, determining energy usage performance, and optimizing energy management in a building through persistent control. Current state- of-the-art methods include modeling packages, such as Energy Plus [20], that allows users to specify a building’s geometry, equipment, orientation, materials, and usage patterns, simulated using first principles models and simulated weather data. Though undoubtedly useful for design, these computationally complex systems may suffer from certain limitations once a building has been constructed due to significant deviations in construction, occupant use, and other specifications that cause the actual building’s behavior to be quite different the model.
At the opposite extreme, so-called black box models have been developed from observational data. Though we can utilize these models to predict future values of particular variables, they do not incorporate any structural information about the system when gathering data, resulting in the need for large amounts of data to train and suffering from the difficulty of extracting relevant information about internal physical parameters that may be of interest.
Semi-physical models resulting in an intermediate level of modeling are known as gray-box modeling. Simple modeling elements containing parameters identified using observational data are chosen and connected based upon physical insight to represent the system’s actual configuration. This is commonly the modeling technique used for thermal networks, which have been used to study load-shifting and peak-reducing control in buildings [21, 22]. A typical thermal network model for a single room is shown in Figure 2, which was adapted from [22]. These networks of (analogous) thermal resistors and capacitors model different building elements. To date, this has typically been performed at a very coarse level, sometimes by combining multiple rooms into one practical room per zone. In [22], a gray-box model for an experimental building was created by utilizing measurements of weather, room temperature, and room air supply and flow. This model was used to predict the effects of a demand-limiting control strategy that we later validated experimentally.
Thermal model of a room.
This section uses a single-room model as shown in Figure 2 from [22] as the basis for a node and its interconnections to other nodes to build up a dynamic graph representation of a building’s thermal processes. First, we consider two rooms connected by a wall. We then illustrate how several such nodes may be interconnected, using the example of a hypothetical four-room building, with analysis provided of the resulting model that motivates the generalization in the next section.
Before proceeding, we note that the initial interest in modeling thermal processes in a building comes from viewing a building as a group of overlapping, interacting networks. In thermal networks, these nodes may denote rooms in an office or school, while in the control network, they may represent a sensor, actuator, or a unit of computation. The connections in the middle of nodes will represent varibles that share information, such as the flow of air-conditioned air between rooms through walls, windows, and doors in a thermal network. While some typical graph-based networks consist of links that are in some way constant gains; some networks, such as a building’s thermal network, may have dynamic links between nodes, as we will explore in the next section.
Figure 3 depicts what is called a 3R2C model in the literature [23]. We identify a room
Two rooms connected by a wall using the 3R2C model.
The interconnection between the two rooms is a wall represented analogously by an electrical circuit with three resistors and two capacitors, simplifying the model in Figure 3. The capacitors
As shown in [23], the heat flows in Figure 3 can be written as:
where
and
Here, s is the independent variable of the Laplace transform, which can be interpreted as
From (3), the nodal equation can be written as:
Combining (Eqs. (4) and (5)) gives:
To motivate later analysis, notice that in the absence of any external heat inputs (i.e.,
which defines the relationship between the temperatures in two rooms using the 3R2C model.
It is useful to separate (Eq. (7)) as
where
This subsection uses the previous subsection’s expressions to develop a building model with several interconnected rooms with different possible pathways between each room and the outside environment.Ideas are developed for a specific theoretical four-room building shown in Figure 4 with each room having neighboring rooms with which heat can travel through-and-from. One such neighbor is always the external environment (which does not include the rooms), whose variable is denoted
A hypothetical four-room example.
Heat flow network corresponding to the four-room example.
In developing a model for this system, we modify (Eq. (5)) to sum the energy losses through all pathways connected to a node, resulting in:
where
For building thermal analysis, there may be several different types of interconnection elements, though they will all have the basic format of (Eq. (4)). Because there is negligible energy storage in doorways and windows, when these are the sole interconnection elements between rooms, we use a single R model, so that (Eq. (4)) is expressed with
where the primed variables represent the 3R2C model, and the unprimed variables represent the resulting parallel connection. In the expressions below, we assume that this computation has been done and the resulting unprimed coefficients can be easily calculated and are thus omitted here. Note that in the case of a door or window that is parallel to a wall, the coefficients
Table 1 summarizes the neighbors for each node and the pathways between each node and each of its neighbors for this example. The table also identifies the coefficients used in the transfer matrix describing the interconnection between each pair of neighbors where the various polynomials
Node | Neighbors | Paths | Coefficients |
---|---|---|---|
1 | 2 | 1-wall | |
a | 2-wall | ||
1-window | |||
3 | 1-wall | ||
4 | 1-door | ||
2 | 1 | 1-wall | |
a | 2-wall | ||
1-window | |||
4 | 2-wall | ||
1-door | |||
3 | 1 | 1-wall | |
a | 2-wall | ||
1-window | |||
4 | 2-wall | ||
1-door | |||
4 | 1 | 1-door | |
a | 1-wall | ||
2 | 2-wall | ||
1-door | |||
3 | 2-wall | ||
1-door |
Hypothetical four room example.
Combining (Eqs. (4) and (9)) for the configuration shown in Figure 5 with the parameters shown in Table 1 and defining the vectors
we can easily show that:
where the matrix
or
a
Notice that we can redraw Figure 5 as shown in Figure 6, where
A hypothetical four-room example as a dynamic consensus network.
The graph shown in Figure 6 will be referred to as a
Laplacian (12) for the dynamic graph Figure 6 we get
which reduces to (Eq. (13)) if we insert the full expressions for
Figure 7 shows a simple simulation of (Eq. (9)) for the case when
Example simulation.
We also [24] consider another example that motivated a generalization of the static consensus problem (Eq. (1)), modeling the load frequency control (LFC) network of an electrical power grid as a dynamic consensus network. We consider the following network:
Based on the dynamics of a network’s nodes and their topology, several consensus problems can be specified. This Chapter focuses on two types of dynamic consensus networks: directed and undirected. The dynamic consensus networks studied are:
or,
or,
or,
The node and edge processing in the proposed dynamic networks (Eqs. (19)–(25)) are linear, time-invariant LTI.
The dynamic topology consists of dynamic edges
The topology of a network can be directed or undirected. The first dynamic network (Eq. (19)) uses a directed topology, whereas the second dynamic network (Eq. (21)) uses an undirected topology.
Depending on the application, the flow is modeled differently. For instance,
The nodes’ dynamics can be integrators (Eqs. (19) and (21)) or more general dynamics Eqs. (23) and (25).
The nodes’ dynamics and the edges can be identical Eqs. (23) or heterogeneous Eqs. (25).
These models are often autonomous, meaning no input flows into the dynamic consensus networks. However, we add inputs and disturbances to the proposed dynamic consensus networks’ general forms in some problems.
Consider the example in Figure 8. These graphical depictions are outlined as a set of nodes (or vertices)
Directed-dynamic graph.
Later, we also view a node as implementing a transfer function that produces the node variable (
As in the static case, we ordered the edges
Each node
The dynamic in-degree matrix
The dynamic out-degree matrix
The dynamic degree matrix
Notice that
If a dynamic edge
1. The incoming dynamic adjacency matrix
2. The dynamic outgoing adjacency matrix
3. The dynamic adjacency matrix
Notice that
Another type of matrix is the dynamic incident matrix. For that matrix, we outline two incident matrices: one that indicates the direction of the edges connected to a node, where for node
To illustrate, for the example shown in Figure 8 these matrices are:
Similarly, we can define a dynamic and static outgoing incident matrices for a dynamic graph by,
To illustrate, for the example shown in Figure 8, these matrices are
Also, we can define the dynamic and static incident matrices for a directed dynamic graph as
Notice that
We can now give the definition of dynamic Laplacian matrix equivalent with the derived dynamic degree, adjacency, and incident matrices. This matrix mentioned above has spectral properties that indicate many conditions of a graph. An undirected dynamic graph has a corresponding dynamic Laplacian matrix defined by
Here, we also outline the aforementioned matrix of an undirected dynamic graph as
where
We define the dynamic Laplacian matrix through the implementation of the the dynamic degree and dynamic adjacency matrices which distinguish between incoming and outgoing conventions. Examples include:
where
By combining (Eqs. (34) and (35)), the outgoing, dynamic Laplacian matrix
A similar definition can be given for
To illustrate, regarding the example noted in Figure 8, the associated dynamic degree, adjacency, and Laplacian matrices are given by (Eq. (32)). Notice that
Block diagram of the dynamic graph.
Now, the dynamic of each node can be represented in time domain for
where,
The overall system of the dynamic graph 8 can be written in frequency domain as
where,
The block diagram for the overall system (38) can be depicted as shown in 9.
The dynamic graphs presented here are governed by dynamic consensus protocols as discussed in the previous sections.
This Chapter studied a generalization of consensus network problems whereby the network edges’ weights are no longer modeled as static gains. Instead, they are represented as dynamic systems coupling the nodes. We call such networks dynamic consensus networks because, under some conditions, all node variables converge to a common value called a consensus. We presented examples of how dynamic graphs can arise in applications. Detailed studies of modeling thermal processes in buildings as directed dynamic graphs were presented. Motivated by these examples, a framework was proposed for dynamic graphs and dynamic consensus networks. This framework introduced the idea of dynamic degree, adjacency, incident, and Laplacian matrices in a way that naturally extends these concepts from the static case. The dynamic consensus networks addressed herein considered various dynamics of nodes and interconnection topology, including (1) directed dynamic networks with integrator nodes and real-rational transfer function edges; (2) undirected dynamic networks with integrator nodes and strictly-positive-real transfer function edges; and (3) undirected dynamic networks with identical linear time-invariant nodes and dynamic edges. We used the established aspects and properties of the defined dynamic graph theory in conjunction with the behavioral approach to developing a controllability-analysis methodology for dynamic networks.
The authors would like to thank Professor Kevin L. Moore and Professor Tyrone L. Vincent at the Colorado School of Mines for their help and advice.
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Even though the adoption of these chemicals has no doubt brought relief to the farmers and has resulted in increased yam production over the years, it has also brought in its wake, negative externalities of environmental pollution, human health effects, and food quality issues. The study was thus designed to investigate how yam is produced, the human and environmental health effects of how yam is produced, and food quality effects of how yam is produced. This was done through literature review, and field and laboratory experiments. It was revealed that, in recent years, new innovations have been introduced in yam production, the manner in which farmers handle herbicides in their yam production process exposes them to high doses of pesticides, thereby endangering their lives. 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We used secondary data for the study of the daily milk production of cows at Andassa dairy farm. The specific objectives of the study were—to identify whether the milk production is time-dependent or not; to predict in which season the milk production is high or low; to examine the daily trend analysis of milk production; to fit the appropriate model; and to forecast the milk production for the future. The study was conducted based on quantitative variables. So, the dependent variable is the average daily milk, and the independent variable is the time measure at which milk production is measured each day. The study used both descriptive and inferential statistics to analyze the data that were collected from the dairy farms in the sector. This study covered a total of 179 days of milk production. 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He completed a one-year Post-Doctoral Fellowship awarded by the DFAIT (Foreign Affairs and International Trade Canada) at the Institute of Biomedical Engineering of the University of New Brunswick (Canada) in 2010. Currently, he is Professor in the Faculty of Electrical Engineering (UFU). He has authored and co-authored more than 200 peer-reviewed publications in Biomedical Engineering. He has been a researcher of The National Council for Scientific and Technological Development (CNPq-Brazil) since 2009. He has served as an ad-hoc consultant for CNPq, CAPES (Coordination for the Improvement of Higher Education Personnel), FINEP (Brazilian Innovation Agency), and other funding bodies on several occasions. He was the Secretary of the Brazilian Society of Biomedical Engineering (SBEB) from 2015 to 2016, President of SBEB (2017-2018) and Vice-President of SBEB (2019-2020). He was the head of the undergraduate program in Biomedical Engineering of the Federal University of Uberlândia (2015 - June/2019) and the head of the Centre for Innovation and Technology Assessment in Health (NIATS/UFU) since 2010. He is the head of the Postgraduate Program in Biomedical Engineering (UFU, July/2019 - to date). He was the secretary of the Parkinson's Disease Association of Uberlândia (2018-2019). Dr. Andrade's primary area of research is focused towards getting information from the neuromuscular system to understand its strategies of organization, adaptation and controlling in the context of motor neuron diseases. 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For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. 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His fields of interest are anterior segment disease, keratoconus, glaucoma, corneal dystrophies, and cataracts. His research topics include\nintraocular lens power calculation, eye modification induced by refractive surgery, glaucoma progression, and validation of new diagnostic devices in ophthalmology. \nHe has published more than 100 papers in international and Italian scientific journals, more than 60 in journals with impact factors, and chapters in international and Italian books. He has also edited two international books and authored more than 150 communications or posters for the most important international and Italian ophthalmology conferences.",institutionString:'University of Campania "Luigi Vanvitelli"',institution:{name:'University of Campania "Luigi Vanvitelli"',institutionURL:null,country:{name:"Italy"}}}]},{type:"book",id:"7560",title:"Non-Invasive Diagnostic Methods",subtitle:"Image Processing",coverURL:"https://cdn.intechopen.com/books/images_new/7560.jpg",slug:"non-invasive-diagnostic-methods-image-processing",publishedDate:"December 19th 2018",editedByType:"Edited by",bookSignature:"Mariusz Marzec and Robert Koprowski",hash:"d92fd8cf5a90a47f2b8a310837a5600e",volumeInSeries:3,fullTitle:"Non-Invasive Diagnostic Methods - Image Processing",editors:[{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",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. 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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. 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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:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/267434/images/system/267434.jpg",biography:"Dr. Rohit Raja received Ph.D. in Computer Science and Engineering from Dr. CVRAMAN University in 2016. His main research interest includes Face recognition and Identification, Digital Image Processing, Signal Processing, and Networking. Presently he is working as Associate Professor in IT Department, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur (CG), India. He has authored several Journal and Conference Papers. He has good Academics & Research experience in various areas of CSE and IT. He has filed and successfully published 27 Patents. He has received many time invitations to be a Guest at IEEE Conferences. He has published 100 research papers in various International/National Journals (including IEEE, Springer, etc.) and Proceedings of the reputed International/ National Conferences (including Springer and IEEE). He has been nominated to the board of editors/reviewers of many peer-reviewed and refereed Journals (including IEEE, Springer).",institutionString:"Guru Ghasidas Vishwavidyalaya",institution:{name:"Guru Ghasidas Vishwavidyalaya",country:{name:"India"}}},{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:{name:"University of Silesia",country:{name:"Poland"}}},{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:null,institution:{name:"Beijing University of Technology",country:{name:"China"}}},{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:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:{name:"Medical University Plovdiv",country:{name:"Bulgaria"}}},{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:"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:"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:"Igor Victorovich Lakhno 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.\nPh.D. – 1999, Kharkiv National Medical Univesity.\nDSC – 2019, PL Shupik National Academy of Postgraduate Education \nProfessor – 2021, Department of Obstetrics and Gynecology of VN Karazin Kharkiv National University\nHead of Department – 2021, Department of Perinatology, Obstetrics and gynecology of Kharkiv Medical Academy of Postgraduate Education\nIgor Lakhno has been graduated from international training courses on reproductive medicine and family planning held at Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor in 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 been a professor in the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics, and gynecology department. He’s affiliated with Kharkiv Medical Academy of Postgraduate Education as a Head of Department from November 2021. Igor Lakhno has participated in several international projects on fetal non-invasive electrocardiography (with Dr. J. A. Behar (Technion), Prof. D. Hoyer (Jena University), and José Alejandro Díaz Méndez (National Institute of Astrophysics, Optics, and Electronics, Mexico). He’s an author of about 200 printed works and there are 31 of them in Scopus or Web of Science databases. Igor Lakhno is a member of the Editorial Board of Reproductive Health of Woman, Emergency Medicine, and Technology Transfer Innovative Solutions in Medicine (Estonia). He is a medical Editor of “Z turbotoyu pro zhinku”. Igor Lakhno is a reviewer of the Journal of Obstetrics and Gynaecology (Taylor and Francis), British Journal of Obstetrics and Gynecology (Wiley), 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 a DSc degree “Pre-eclampsia: prediction, prevention, and treatment”. Three years ago Igor Lakhno has participated in a training course on innovative technologies in medical education at Lublin Medical University (Poland). 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: are obstetrics, women’s health, fetal medicine, and cardiovascular medicine. \nIgor Lakhno is a consultant at Kharkiv municipal perinatal center. He’s graduated from training courses on endoscopy in gynecology. He has 28 years of practical experience in the field.",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. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"243698",title:"Dr.",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. 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\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
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