Anaerobic processing of maize silage—operation parameters of the anaerobic reactor.
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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In order to replace fossil fuels by renewable energy sources, utilization of biofuels and renewable energy sources has been incorporated in the national and international legal standards and the government programs of developed countries. The EU in the Directive 2009
To increase the specific methane production from silage, various methods of physical, chemical, or biological pre-treatment or their combination can be used [15, 16]. However, each pre-treatment method complicates the biogas production technology and increases the operation cost. Therefore, it is necessary to always consider if a higher amount of biogas produced has a relevant effect. Considering its properties and composition, maize silage is often used in co-fermentation with other substrates, for example, with manure, sludge from wastewater plants, various plant substrates, or industrial wastes [17–21].
\nHere, results obtained by anaerobic digestion of maize silage as the single substrate for biogas production in laboratory as well as in full-scale conditions are presented. Start-up of a biogas plant anaerobic reactor for maize silage processing as a single substrate and operation experiences using other co-substrates is presented.
\nWithin the laboratory experiments on anaerobic processing of maize silage, tests of the maize silage biogas potential were carried out, and a long-term operation of a biogas production model was monitored. The aim of these tests was to determine the specific biogas production.
\nIt is necessary to emphasize that the tests of biomethane potential have only an informational character and the specific methane production reached by long-term operation of anaerobic digestion of biologically degradable substrates can differ considerably. Single biomethane potential test results are significantly affected by the anaerobic sludge used as inoculum. Used anaerobic sludge is not usually adapted to the substrate degradation and during batch test the adaptation is not carried out. Therefore, the biomethane potential test provides a value lower than that obtained by long-term anaerobic digestion, when the adaptation of the anaerobic sludge to the used substrate and thus deeper anaerobic digestion of the substrate can take place. If the substrate contains a toxic or inhibitory substance, its influence might not be demonstrated during the biomethane potential test, due to the sufficient dilution of the substrate by the anaerobic sludge used for inoculation, for example, in substrates with high nitrogen or sulfur content. In long-term anaerobic digestion process, when the substrate is repeatedly supplied to the reactor, nitrogen or sulfur can accumulate in the reactor, and ammonia or sulfide inhibition of anaerobic processes can occur gradually. However, the biomethane potential test is a suitable tool for the primary evaluation of anaerobic digestion of a substrate and the possible biogas production.
\nMaize silage produced at the STIFI farm in Hurbanovo was used in the biomethane potential test without particle size adjustment. The particle size was given by the harvesting machine as up to 5 cm in length. Silage was made in the traditional way. Harvesting took place at the TS of the green maize about 30%. After the cropping, green maize was compacted by bulldozer in the silage pit with dimensions of 22 m × 75 m × 5 m. For tests, the silage after two month of ensiling was used. Content of TS of the used silage represented 35% with the VS content of 95.8%. Value of pH of maize silage water leachate (100 g of silage in 400 ml of tap water) was 3.7. Anaerobically stabilized sludge from the municipal wastewater treatment plant in Devínska Nová Ves (total suspended solids— TS of 37.23 g/L and volatile suspended solids—VS of 20.74 g/L) in the volume of 0.5 l and 7 g of fresh silage was used for the tests. The sludge mixture was completed to the total volume of 1 l with tap water. To determine the biogas production from the anaerobically stabilized sludge, a blank test was done. The tests were carried out in the mesophilic temperature regime (35°C) in three repetitions. The biomethane potential results are presented in Figure 1.
\nTest of biomethane potential of maize silage.
From the test results follows that 233 ml of methane per gram of TS (243 ml per gram of VS) respectively 0.206 Nm3/kg of TS (0.215 Nm3/kg of VS) were produced. It is in agreement with results provided by Amon et al. [2].
\nLong-term maize silage processing was carried out in a mixed laboratory anaerobic reactor with the volume of 4 l. The reactor was filled to the half of its volume with the anaerobically stabilized sludge used for biomethane potential tests (TS of 37.2 g/L with VS of 55.7%) and was filled to the total volume of 4 l with tap water. Silage was processed in its raw form without any pre-treatment, that is, as taken from the silage pits in STIFI Hurbanovo, and stored at 4°C. The silage was loaded once a day into the laboratory model operated at 35°C. In the filtered samples of sludge water, parameters as chemical oxygen demand (COD), volatile fatty acids (VFA), ammonia nitrogen (NH4-N), and pH were determined. Also the concentration of suspended solids and biogas production were monitored in the reactor. All analyses were carried out applying standard methods [22]. The analysis of VFA was done employing the method introduced by Kapp [23]. To determine the biogas composition (methane, CO2, H2, and H2S), the apparatus GA 2000 Plus (Geotechnical Instruments, UK) was used.
\nOperation of the laboratory reactor for anaerobic digestion of maize silage started at the organic loading rate (OLR) of 1.68 kg/(m3/d). The course of loading doses and the achieved parameters of the anaerobic reactor are provided in Table 1. Figure 2 shows the course of the specific biogas production per kg of added VS and the cumulative biogas production in the anaerobic reactor with gradual increase of OLR in the reactor. OLR increased from 1.68 to 6.71 kg/(m3/d)—Table 1. Average specific biogas production at individual OLR values was in the range of 0.195–0.655 m3 per kg of VS. Maximum specific biogas production was achieved at the OLR of 5.03 kg/(m3/d). The course of COD and VFA is shown in Figure 3 and that of pH and NH4-N in Figure 4. Instability of the processes was demonstrated by the decrease of pH and the increase of COD and VFA concentration, especially after the increase of OLR in the reactor (Figures 2 and 3).
\nOrganic loading rate (VS) [kg/(m3 d)] | \nDay of operation | \nDose of silage (raw material) [g/d] | \nDose of silage (VS) [g/d] | \nSpecific biogas production (VS) [m3/kg] | \n
---|---|---|---|---|
1.68 | \n0–20 | \n20 | \n6.71 | \n0.195 | \n
2.52 | \n21–40 | \n30 | \n10.06 | \n0.230 | \n
3.36 | \n41–80 | \n40 | \n13.42 | \n0.430 | \n
4.19 | \n81–120 | \n50 | \n16.77 | \n0.530 | \n
5.03 | \n121–220 | \n60 | \n20.12 | \n0.655 | \n
6.71 | \n220–300 | \n80 | \n26.83 | \n0.420 | \n
Anaerobic processing of maize silage—operation parameters of the anaerobic reactor.
Specific and cumulative biogas production in the anaerobic reactor.
COD and VFA in the laboratory anaerobic reactor.
NH4-N and pH in the laboratory anaerobic reactor.
Stabilization of COD and VFA took several days or even weeks depending on the destabilization degree after the silage load increase. At higher loads, the response to increased OLR was stronger and the stabilization period was longer. With the OLR increase, pH decreased below 6.5 (Figure 3) and sodium bicarbonate was used to adjust the pH. The pH value had to be adjusted not only after an OLR increase but throughout the anaerobic reactor operation because pH in neutral range is needed for methanogenic microorganisms. In total, ca. 6000 g of VS silage and 100 g of sodium bicarbonate were loaded into the reactor during its 300 day operation. The average sodium bicarbonate consumption was 0.05 g/g of VS silage. Instability of the anaerobic processing of maize silage is related to it insufficient acid neutralizing capacity (alkalinity) due to the high C/N ratio in this substrate (30–46) [3]. Together with the carbonate buffer system (CO2/CO32−/HCO3−), ammonia buffer system (NH3/NH4+) also has an important role in the anaerobic processes. Results of long-term anaerobic reactor operation indicate that anaerobic digestion of maize silage as the only substrate requires the presence of alkaline reagents. From a practical point of view and that of nutrients demand, loading of a co-substrate with higher content of nitrogen, for example, sewage sludge, or manure, is required. At OLR of 6.71 kg/(m3/d), the COD and VFA values exceeded 18,000 mg/L and 11,000 mg/L, respectively. It is thus clear that at this OLR value, the system was permanently overloaded and the COD and VFA values were stabilized at 6000 mg/L and 2800 mg/L, respectively. Also the specific biogas production was considerably lower (0.420 kg/kg of VS) as that at the load of 5.03 kg/(m3/d) (0.655 kg/kg of VS)(0.655 m3 /kg of VS). Therefore, the optimal value of OLR has been established as 5.03 kg/(m3/d), with the highest specific production of biogas.
\nDuring the stable operation of the reactor (days 121–220), the average concentration of suspended solids in the anaerobic reactor was 79 g/L. Daily amount of the suspended solids of excess sludge was 3.57 g. At the load of 21 g of TS silage (60 g of fresh silage with the TS content of 35%), the production of excess sludge was 0.17 g pre 1 g of TS, which corresponds to the anaerobic silage digestion degree of 83%. The content of individual biogas components is provided in Table 2 and the parameters of anaerobic digestion of maize silage obtained from the laboratory model are summarized in Table 3.
\nComponent | \nValue | \n
---|---|
CH4 [%] | \n54.5 | \n
CO2 [%] | \n45.4 | \n
H2 [ppm] | \n5 | \n
H2S [ppm] | \n215 | \n
Composition of biogas produced from maize grains and maize silage.
Parameter | \nValue | \n
---|---|
OLR (VS) [kg/(m3/d)] | \n5.03 | \n
Suspended solids in reactor [g/L] | \n79 | \n
Specific biogas production (35°C) [m3/kg VS] | \n0.655 | \n
Specific methane production [Nm3/kg VS] | \n0.316 | \n
Specific excess sludge production | \n0.17 | \n
Degradation of TS [%] | \n83.0 | \n
Parameters of maize silage anaerobic digestion.
Considering that from 1 ha of arable land, 30 t of TS silage (VS of 95%) per annum are obtained, methane production is 9006 Nm3/ha. For a biogas plant with produced biogas incineration in a cogeneration unit with the electric power of 1 MW (electric energy production efficiency of 35%), the daily maize silage demand represents the area of 0.77 ha. This means that the annual operation of biogas plants needs 8431.5 t of TS silage, grown on 281 ha of arable land.
\nConclusions of the anaerobic digestion of maize silage in laboratory conditions:
\nBiomethane potential tests provided the measured specific methane production of 0.215 Nm3/kg of VS. For long-term maize silage processing in a mixed laboratory anaerobic reactor, the measured specific methane production was 0.316 Nm3/kg of VSS. The higher value obtained for long-term reactor operation is due to the adaptation of the anaerobic microorganisms to the maize silage substrate.
\nLong-term operation of the anaerobic reactor for maize silage processing as the only substrate showed significant instability caused by the low alkalinity of maize silage (high C:N ratio). To stabilize the anaerobic processes, other alkaline reagents or a co-substrate with higher content of nitrogen (sewage sludge or manure) can be used.
\nDaily operation of a biogas plant with biogas incinerated in a cogeneration unit with the electric power of 1 MW requires the amount of silage from an area of 0.77 ha of arable land.
\nDespite the 17,000 biogas plants in EU [24], many of which use maize silage as the main substrate, only a little information on their start-up and trial operation can be found in literature. Start-up and trial operation of a biogas plant for processing of maize silage as the main substrate are described.
\nTechnology of a biogas plant is depicted in Figure 5. Effective volume of the used anaerobic reactor was 2450 m3. Two high-speed blade mixers with horizontal rotational axis and with the immersion depth and mixing direction regulation were used. Fresh silage was loaded into the reactor by means of a conveyor belt. Silage pits were located next to the anaerobic reactor; an average TS of the silage was used during the start-up, and pilot plant operation was 35%; and the expected biogas production was 4200 m3/d. Biogas was incinerated in a cogeneration unit (ELTECO, Slovakia) with the electric power of 276 kW (electric efficiency of 32%) and the heat power of 479 kW. The reactor was operated at the temperature of 37°C and the volume of the gasholder was 80 m3, which was assumed as sufficient at stabilized production and consumption of biogas. Also a gas boiler enabling biogas as well as a natural gas incineration with the heat power of 470 kW was included in the technology. This boiler plays an important role during the start-up of the anaerobic reactor when biogas is not available and the reactor has to be heated to the operation temperature by natural gas.
\nDiagram of biogas plant for anaerobic digestion of the maize silage.
Course of silage dose and biogas production during the start-up of the anaerobic reactor.
The anaerobic reactor was inoculated with aerobically stabilized sewage sludge from a brewery, which is not often used as an inoculation medium for anaerobic reactors. Normally, for the inoculation of the anaerobic reactor the anaerobically stabilized sludge is used, but the distance to the nearest wastewater plant with anaerobically stabilized sludge was 15 km, and the required amount of sludge could not be provided. Aerobically stabilized sludge from brewery wastewater plant was available for only as far as 2 km from the biogas plant. The amount of aerobically stabilized sludge added to the anaerobic reactor for inoculation before its start-up was 1700 m3 with an average concentration of suspended solids (SS) of 30 g/L. After the inoculation, the reactor was heated to 37°C and gradually loaded with maize silage. During the start-up of the anaerobic reactor, biogas production, pH, VFA, NH4-N, PO4-P, and suspended solids concentration were monitored. The course of these parameters was also monitored during the first 200 days of the pilot plant operation (Figures 6–10).
\nConcentration of VFA in filtered sludge water from the anaerobic reactor during the start-up.
Concentration of NH4-N and PO4-P in filtered sludge water from the anaerobic during the start-up.
The silage load was gradually increased (Figure 6), with the starting load of 2 t/d. As it follows from Figures 6 and 7 (biogas production and VFA concentration), anaerobic reactor operation was stable, and the biogas production was proportional to the increasing load approximately until the end of day 100. Maximum load of silage in this period was 20 t/d. This amount was divided into six parts and every 6 hours 3.33 t was dosed. Average specific biogas production between days 50 and 100 of the reactor operation was 0.726 m3/kg of silage TS. Figure 8 presents the course of the NH4-N and PO4-P concentrations.
\n\nIncrease of these concentrations within the first 20 days of operation is related to the degradation of sludge used as the inoculum (similarly as for the VFA concentration—Figure 7). NH4-N concentration gradually decreased to approximately 200 mg/L and that of PO4-P to below 20 mg/L. Low concentrations of ammonia nitrogen were followed by a pH decrease (Figure 9) due to the low alkalinity of the silage. Values of pH below 6.5 led to methanogenesis inhibition which increased the VFA concentration above 7500 mg/L (Figure 7) and decreased the biogas production significantly. From day 120, it was started with dosing of aerobically stabilized sludge (the same one that was used for inoculation) to increase the NH4-N concentration and stabilize pH. The sludge dose was 7–10 m3/d (SS concentration of 30 g/L). As it is evident from Figures 7–9, the NH4-N concentration increased to above 600 mg/L, VFA concentration decreased and pH was stabilized at around 7.2. The silage dose after stabilization of the reactor operation was increased to 24 t/d, specific biogas production reached 0.7 m3/kg of silage TS, and the cogeneration unit worked with its 100% capacity. OLR of the anaerobic reactor was in the range of 2.3–2.7 kg/(m3/d) and the SS concentration in sludge water of the anaerobic reactor after 200 days of operation was 60 g/L (Figure 10).
\nCourse of pH in the anaerobic reactor during the start-up.
During the anaerobic reactor start-up, some interesting phenomena have been observed: after each silage dosing, a temporary increase in biogas production and the resulting increase in the cogeneration unit electrical power output, Figure 11 shows the response of the electrical power output for a silage dose every 3 h (16 t per day, each dose of 2 t), with the total biogas production of 2800 m3 and the cogeneration unit efficiency of 67% (day 140). The period of increased biogas production was ca. 1 h; the increase in biogas production showed in Figure 11 represents 5.13% of the total biogas production per silage dose. Such an increase is related to the content of readily biodegradable organic matter in maize silage (VFA, alcohols, lower saccharides, etc.), which can vary in the range of 2.1–11.1% (Table 4).
\nConcentration of suspended solids in the anaerobic reactor during the start-up.
Increase of power output of the cogeneration unit (biogas production) after silage dosing.
TS [%] | \nAcid | \nEthanol | \nGlucose | \nFructose | \nReference | \n|||
---|---|---|---|---|---|---|---|---|
Lactic | \nAcetic | \nPropionic | \nButyric | \n|||||
39.2 | \n6.2 | \n2.6 | \n0.2 | \n<1 | \n1.1 | \n– | \n– | \n[25] | \n
36.0 | \n4.2 | \n1.5 | \n0.32 | \n1.04 | \n1.5 | \n– | \n– | \n[26] | \n
31.0 | \n5.21 | \n1.28 | \n– | \n– | \n– | \n0.29 | \n0.47 | \n[27] | \n
41.0 | \n2.12 | \n0.86 | \n0.05 | \n0.24 | \n0.17 | \n– | \n– | \n[28] | \n
28.5 | \n0.56 | \n0.47 | \n0.01 | \n0.01 | \n0.27 | \n– | \n– | \n[29] | \n
Concentration of volatile and readily biodegradable matter in maize silage (% of TS).
Between two doses, also the quality of the biogas produced changed; average methane concentration in biogas was 54.5% and that of hydrogen sulfide was 160 ppm. In the first two hours after the loading, the methane concentration decreased by ca. 2% (from 55 to 53%), which can be explained by higher CO2 production due to the degradation of readily biodegradable matter. More significant changes in the biogas composition were observed for a five day silage loading interruption, when the methane concentration in biogas increased from 52.8 to 65%.
\nIn the steady state, when the full capacity of the cogeneration unit was achieved, the biogas production of 4200 m3/d, electric energy production of ca. 6600 kWh/d and the heat production of ca. 11,500 kWh/d were provided at the daily maize silage dose of 6–7 t of TS. Electric energy was sold to the electric grid, produced heat was employed for the anaerobic reactor heating (12–13% of the produced heat), for greenhouses heating and also for drying maize grains between September and December produced on the premises as well as that produced by neighboring farmers. The digestate was stored and used if necessary as a fertilizer on the arable lands of the farm.
\nConclusions from the start-up and trial operation of a biogas plant for anaerobic digestion of maize silage:
\nResults of the start-up of the anaerobic reactor have proved the suitability of aerobically stabilized sludge for the anaerobic reactor inoculation despite the substrate not being used for this purpose usually.
\nStart-up of the anaerobic reactor took approximately 100 days.
\nResults of the laboratory experiments were confirmed – the low alkalinity of maize silage and the need for additional substrates with higher nitrogen content to stabilize the reactor operation. In the present case, aerobically stabilized sludge from a brewery wastewater plant was used.
\nAfter ca. 150 days of the biogas plant operation, the designed parameters were stabilized. At the full capacity of the cogeneration unit, the biogas production of 4200 m3/d, electric energy production of ca. 6600 kWh/d and heat production of ca. 11,500 kWh/d were achieved. Daily dose of silage was 24 t/d, divided into six portions every 4 hours.
\nRaw materials used for the biogas plant differ not only in their physical properties but also in their composition. From the anaerobic digestion point of view, organic carbon and its proportion to nitrogen are more appreciated. If the organic carbon is in the form of hardly degradable matter and hydrolysis or acidification is required, the effect of substrate dosing will differ from that observed for readily biodegradable matter. If the dosing effect of readily biodegradable substrate on the anaerobic processes is strong and the biogas production increases sharply immediately after the loading, together with other changes in the reaction mixture (pH change, VFA increase, etc.), it is recommended to divide the loadings to as many as possible during the day. Dosing optimization has a positive influence on the processes not only considering the degradation but also concerning the presence of toxic or inhibitory substances.
\nFor efficient anaerobic processes, the balanced substrates composition, especially when considering the macronutrients (nitrogen and phosphorus) content, is also an important factor. Inhibition of ongoing processes can be caused by low nitrogen or phosphorus content, or by high nitrogen content. Optimum COD/N/P ratio for the anaerobic microorganisms growth is in the range of 1000:5:1 for acidified substrate (with low biomass production), and up to 350:5:1 for unacidified substrates (with high biomass production) [29]. For materials processed in biogas plants, COD determination is quite a complex problem; therefore, the ratio of organic carbon to nitrogen (C:N ratio) is usually applied. Generally, it can be stated that for materials with high nitrogen content (blood, meat and bone meal, rapeseed meal, chicken droppings), this ratio is up to 10–15, for materials with medium nitrogen content (maize silage, cereal straw) it is up to approx. 50, and for materials with low nitrogen content (e.g. wood biomass), the C:N ratio is above 50 [30].
\nAt very high C:N ratios, methanogenic microorganisms are not sufficiently supplied with nitrogen to assimilate (growth and propagation) and conditions for organic carbon degradation are not achieved. Or, as in case of maize silage, at low alkalinity of the substrate, pH in the reactor decreases and the process becomes instable. At low values of pH (below 6.5) growth of methanogenic microorganisms is strongly inhibited, because optimal pH for their growth is in the neutral range. However, at very low C/N ratios, nitrogen accumulates in the sludge water in its ammonia form, which can result in a pH increase and anaerobic processes inhibition by undissociated ammonia.
\nConsidering the biomass composition, the presence of sulfur is also important; sulfur in its organic as well as inorganic form is transformed to its reduced forms, mainly to sulfides and hydrogen sulfide, by anaerobic processes. Sulfides present in the anaerobic sludge water are toxic to the methanogenic microorganisms, and hydrogen sulfide causes problems with the biogas incineration in heaters of cogeneration units.
\nAs an example of influent of different substrates dosing on a biogas plant operation, long-term monitoring of the biogas plant in Hurbanovo using maize silage as the main substrate can be provided. Its start-up and trial operation were described above.
\nFrom the beginning of the biogas plant operation, maize silage was used as the main and often the only substrate. Maize silage composition has changed depending on different factors, for example, the maize variety used. One of the most important factors is the ripeness season when maize is harvested for ensiling [3, 8]. In Table 5, selected parameters of substrates significantly influencing the biogas plant operation are provided. Except for the maize silage, also meat and bone meal, molasses stillage from bioethanol production—vinasse and a by-product of biodiesel production—crude glycerol characteristics are presented.
\nParameter | \nMaize silage | \nMeat and bone meal | \nVinasse | \nCrude glycerol | \n
---|---|---|---|---|
pH | \n– | \n– | \n6.15 | \n9.03 | \n
Chemical oxygen demand [g/g of TS] | \n1.22 | \n1.32 | \n– | \n– | \n
Chemical oxygen demand [mg/L] | \n– | \n– | \n332,930 | \n1,870,000 | \n
Total Kjeldahl nitrogen [% of TS] | \n0.88 | \n7.90 | \n– | \n– | \n
Total Kjeldahl nitrogen [mg/L] | \n– | \n– | \n19,254 | \n– | \n
NH4-N [mg/L] | \n– | \n– | \n3390 | \n– | \n
Total nitrogen [% of TS] | \n2.69 | \n8.85 | \n– | \n– | \n
Total nitrogen [mg/L] | \n– | \n– | \n– | \n1690 | \n
Total phosphorus [mg/L] | \n– | \n– | \n– | \n192 | \n
PO4-P [mg/L] | \n– | \n– | \n835 | \n– | \n
C:N | \n17.6 | \n4.42 | \n– | \n– | \n
Dissolved anorganic salts [mg/L] | \n– | \n– | \n– | \n5150 | \n
Density [g/L] | \n– | \n– | \n– | \n1080 | \n
Lactic acid [%] | \n1.85 | \n– | \n– | \n– | \n
Acetic acid [%] | \n1.77 | \n– | \n– | \n– | \n
TS [%] | \n30.8 | \n72.5 | \n45.9 | \n– | \n
VS of TS [%] | \n94.1 | \n79.9 | \n71.8 | \n– | \n
Characteristics of the used substrates.
During the biogas plant operation, other substrates were also processed, for example, rye silage and a mixture of oat and peas, which however did not significantly affect the reactor operation.
\nCo-substrate loading in the biogas plant had two main reasons: insufficient amount of the main substrate—maize silage, especially in spring; and stabilization of the anaerobic reactor operation, for example, in case of the brewery wastewater plant sludge. The course of various substrates loading is presented in Figure 12.
\nLoading of various substrates is discussed in relationship with the biogas production and pH changes. The course of biogas production in a biogas plant from the start of its operation is presented in Figure 13 and the pH values are shown in Figure 14.
\nCourse of dosing of various substrates in the biogas plant.
Biogas production in the biogas plant.
Course of pH values in the anaerobic reactor of the biogas plant.
Start-up and trial operation were discussed earlier. At this period of the anaerobic reactor operation, the disadvantage of the low alkalinity of maize silage processed as the only substrate was demonstrated. This disadvantage was suppressed by brewery sludge loading to the reactor. The main effect of sludge dosing was the increase of N in the system. It is possible, that the other effects of sludge dosing was introducing micronutrients and minerals, but from Figures 8 and 9 it is obvious that main effect to pH stabilization is the increase of NH4-N concentration.
\nFrom day 203 of the operation, meat and bone meal was dosed to the reactor, first to increase nitrogen concentration, then also to compensate the lack of maize silage. When the maize silage was not available and only low quality rye silage could be used, the average dose of this silage was 2 t and up to 3.2 t of meat and bone meal. Between days 180 and 250 of the operation, the biogas production achieved its maximum (designed) values. Long-term high loads of meat and bone meal (between days 203–255) had, however, a negative impact on the anaerobic reactor operation; therefore, dosing of this substrate was in day 255 stopped. Meat and bone meal is a substrate with low C:N ratio, of 4.42 (Table 5), and thus with high nitrogen content, which resulted in the increase in ammonia nitrogen concentration in the sludge water to above 2800 mg/L and that of pH to above 7.5; the process was probably inhibited by undissociated ammonia in the sludge water. Volatile fatty acids concentration was higher than 7500 mg/L (Figure 15) and the biogas production decreased (Figure 13). Also the biogas quality was lower, H2S concentration increased from values below 200 ppm to values above 1800 ppm. Loading to the anaerobic reactor was interrupted for two weeks and after the volatile fatty acids concentration decreased below 6000 mg/L, rye silage and maize splits loadings were slowly resumed. Following the initiation of maize silage dosing from the new harvest in about day 300, the reactor operation gradually stabilized and the biogas production almost reached its maximum values. Although the following reactor operation was not quite stable, such severe conditions as after meat and bone meal dosing did not occur.
\nConcentration of VFA in filtrated sludge water from the anaerobic reactor in the biogas plant.
Another interesting substrate used in the biogas plant was molasses stillage from ethanol production, also called vinasse. At COD of 333,000 mg/L, the TKN concentration was 19,250 mg/L (Table 5), which is quite high. After the meat and bone meal dosing was stopped, the NH4-N concentration in sludge water decreased below 1600 mg/L; however, it increased to almost 4500 mg/L after ca. 200 days of molasses residue loading (between days 500 and 700). Also the volatile fatty acids concentration increased significantly (Figure 15) and pH reached values of above eight (Figure 14). These changes were not abrupt but gradual and the anaerobic biomass adapted to these new conditions; therefore, the changes had no significant effect on the biogas production. Lower biogas production in this time period was caused by the lack of maize silage, as only one third or one half of the designed amount was loaded. After the molasses stillage loadings were stopped, the volatile fatty acids concentration decreased again (Figure 15). In the following season when maize silage was lacking, rye silage or a mixture of oat and peas was used.
\nConsidering the anaerobic reactor operation stability, crude glycerol seems to be a promising co-substrate; it was used for more than two years in the biogas plant. It is a by-product of biofuel production; some of its characteristics are listed in Table 5. As it can be seen from the biogas production (Figure 13), pH (Figure 14), and volatile fatty acids concentration (Figure 15), the use of crude glycerol as a co-substrate with maize silage resulted in the anaerobic reactor stabilization.
\nTo evaluate the specific biogas production from crude glycerol and its contribution to the total biogas production, a stable biogas plant operation period of 141 days was chosen, when only maize silage and crude glycerol were loaded to the anaerobic reactor. The average daily biogas production achieved was 4091.4 m3, at the daily silage loading of 5280.4 kg TS (TS in the silage used was 42.47%) and the daily crude glycerol loading of 683.7 kg. To determine the specific biogas production from crude glycerol, the value of the specific biogas production from maize silage (0.66 m3 per 1 kg of the maize silage TS, obtained when maize silage was the only substrate) was employed. The average daily amount of biogas produced from maize silage was calculated as 3485 m3 and the average daily amount of biogas produced from crude glycerol was 606.4 m3. The specific biogas production per 1 kg of crude glycerol was 0.887 m3, which corresponds to the specific biogas production of 0.512 m3/kg of COD and is in agreement with the results presented in [31].
\nBiogas produced from crude glycerol represented 14.82% of the total biogas production, while 11.46% of the total TS, 12.1% of VS and only 5.21% of the total mass of the raw materials loaded. At the electrical power output of the cogeneration unit of 300 kW (electrical power output of the cogeneration unit was increased from 276 kW to 300 kW after an agreement with the producer considering the operation experiences), the daily electric energy production from crude glycerol was 1067 kWh and almost 15% of silage were saved.
\nAmon et al. [32] studied the influence of various loading doses of crude glycerol on the anaerobic digestion of pig manure, maize silage and maize corns. Co-fermentation effect was observed. It means that methane yield of the basic mixture supplemented with glycerol was higher than the combined methane yields of both substrates if digested separately. The co-fermentation effect was especially high with glycerin additions of 3–6%. They recommend the glycerol content of maximum 6% for a stable reactor operation.
\nTo complete the biogas plant monitoring results obtained for various co-substrates, the course of suspended solids concentration in the anaerobic reactor is provided in Figure 16, which shows a gradual increase of this concentration in the period of more than two years. After crude glycerol started to be added to the reactor, the concentration of suspended solids slightly decreased, which had a positive effect on the reactor mixing.
\nIn our case of long-term crude glycerol loading in the biogas plant, the average glycerol VS addition was 12.1% and the anaerobic digestion process was stable. However, no co-fermentation effect was observed.
\nConclusions of the study of various substrates loading on the biogas plant operation:
\nCo-substrates used in anaerobic digestion of maize silage as the main substrate can have a positive as well as a negative effect on the biogas plant operation.
\nUncontrolled meat and bone meal loading resulted in a failure of the anaerobic reactor due to the high nitrogen content in this substrate. Its processing together with the maize silage is possible; however, the loading dose has to be regulated considering the ammonia nitrogen concentration and the pH in the anaerobic reactor.
\nIt has been proved that the inhibitory effect of ammonia nitrogen depends on also the course of its increase. While an abrupt increase of the NH4-N concentration to approximately 2800 mg/L (loading of meat and bone meal) resulted in an inhibition of the anaerobic processes, gradual increase to almost 4500 mg/L (in case of vinasse loading) showed no negative effect on the process.
\nConcentration of undissolved substances in the anaerobic reactor in the biogas plant.
Crude glycerol loading of 12.1% of the total loaded VS had a positive and stabilizing effect on the biogas plant operation.
\nThe obtained laboratory and full scale results showed that maize silage is a suitable substrate for anaerobic digestion and biogas production. This is confirmed also by thousands of biogas plants in Europe, which use maize silage as the main substrate. Thus, it can be concluded that maize silage as the most widely used substrate for biogas production is a fact of presence. However, biogas production from this substrate is not sustainable nor is the production of the first generation biofuels produced from food commodities (e.g. biodiesel from edible oils, or bioethanol from cereals).
\nThe advantage of using maize silage for biogas production is because of its high yield per hectare and high specific biogas production. The main disadvantage is that maize used for biogas production cannot be used as designed in human or animal nutrition. Such competition deforms also its price and maize silage becomes a scarce commodity. Moreover, mass growing of maize as a monoculture occupies arable land for growing other crops and increases the need for fertilization and plant protection. These negative effects were also presented by the authors from the Karlsruhe Institute of Technology, Germany [33]. The main aims of their project were “Landscaping instead of monoculture” and “Grass is an alternative to silage maize in biogas production.” It is evident that grass hectare yields or specific biogas production cannot compete with maize silage; however, it is a sustainable alternative to maize silage and makes biogas a surplus value of landscaping.
\nAnother alternative is growing energetic crops which are not part of the food chain of humans or animals, for example, sorghum provides interesting hectare yields as well as specific biogas production values [34]. Other such crops include hemp (
Also biologically degradable waste from agriculture and industry as well as municipal waste are suitable substrates for biogas production and are an alternative to maize silage, which has been confirmed by the estimated biogas potential of these substrates in Germany [37]. While the energetic crops biogas potential was estimated to be 46.2% of the total biogas potential, the rest is obtained from various waste materials such as livestock excrements, harvesting residues and by-products of crops processing, municipal waste, sewage sludge, landscaping and industrial wastes.
\nAlthough a structure of the substrate mixture used in biogas plants is not sustainable even though its change is inevitable a long-time will pass before maize silage loses its position as the main substrate for biogas production.
\nThis contribution is the result of the project implementation: Finalizing of the National Centre for Research and Application of Renewable Energy Sources, ITMS 26240120028, supported by the Research & Development Operational Programme funded by the ERDF.
\nIn recent years, major ports around the world have been implementing new technologies to realize “Smart Ports,” in order to enhance international competitiveness, reduce environmental impact, and improve the workplace environment. In addition to the automation and labor-saving measures that have been actively pursued so far, smart ports are nowadays expected to benefit from the Internet of Things (IoT), Artificial Intelligence (AI), and Big Data2, as well as more focused initiatives, in specific the Physical Internet (PI), based on the development of high-speed communication infrastructures, such as the fifth generation mobile communication system (5G). The robust use of the numerous digital technologies, such as the ones above-mentioned, offers substantial business innovation opportunities and requires numerous organizational adjustments [1].
In specific, the digitalization of ports is enabled by 5G networks that provide low latency, high capacity, and increased bandwidth, hence allowing the collection and intelligent processing of vast amounts of data shared over an IoT information network infrastructure. 5G is foremost supporting the PI objectives, namely the widespread adoption of interconnected, sustainable logistics systems and applications.
A smart port is realized by means of wireless devices, smart sensors, actuators, data centers, and other IoT-based systems being connected and exchanging information. The seamless communication of ships, cargoes, and waterway and shore-based facilities, based on 5G and IoT technologies, constitutes the infrastructure of the smart port and shapes the innovation potential of the emergent maritime logistics services and applications. The efficiency, security, and safety of port operations and the achievement of the highly prioritized sustainable development goals are substantially improved by automating port operations, such as vessel management, container terminal operations, and yard automation.
Competitiveness and henceforth the competitive positioning of ports being nodes of multiple, global supply chain networks are of paramount importance and are directly determined by the adopted digital strategy and infrastructures implemented in each port.
This chapter outlines the main technologies’ capabilities, as well as the current status of policies and initiatives for the development and deployment of various technologies, primarily for automated terminals and automated ships in ports, as innovations for ships and various automated machinery, mainly for cargo handling, toward the realization of smart ports. Moreover, the chapter introduces a particular technological framework for creating a sustainable next-generation maritime logistics system, by applying PI to digitize maritime logistics networks and BC technology for secure information exchange to improve the overall efficiency of maritime logistics, at ports.
How does modern maritime logistics look like in the era of Industry 4.0? The concept of Industry 4.0, first formulated by the German government, mainly refers to the automation and digitization of manufacturing processes. Industry 4.0 encompasses cyber-physical systems3, AI4, IoT5, cloud computing6, cognitive computing7, smart factories8, and digital twin9. Industry 4.0 has been implemented in many countries besides Germany, including the US, France, the UK, China, Japan, Korea, and Thailand. Particularly in the supply chain area, digitalization, integration of AI and IoT, sharing economy10, and BC are playing an important role in addition to these core technologies. Logistics has not been associated with high technology for a long time since it was recognized as an industry in the mid of nineteenth century. The situation is changing with the increase of Logistics 4.0 efforts, where innovative technologies such as AI, IoT, and BC are increasingly being implemented in the logistics industry, in parallel with similar efforts to many other industries, presenting even more efficient sustainability and human-centric approaches. However, despite the numerous regional initiatives, there are no adequate frameworks existing for companies in the logistics industry to embrace those technologies to the largest extent. There is a need for guidelines to implement new technologies in the logistics industry for the common good of the entire industry and eventually society as a whole.
Against this background, a closely related development, namely the Physical Internet (PI), has drawn attention from various parties as one of the most effective measures to improve logistics efficiency and reduce greenhouse gas emissions. The features of PI include interoperability, modularity, and standard interfaces and protocols. In order to take advantage of these features, technology to share data while maintaining confidentiality, such as Blockchain (BC) technology, is essential. This technology, also known as a distributed ledger, is difficult to tamper with, requires no administrator, and allows execution of smart contracts. The use of BC technology in PI is expected to dramatically accelerate the construction of a sustainable logistics network. In the following sections, we will present, in more detail, the potential of applying BC technology in the PI network context.
Artificial Intelligence (AI) is a field of computer science that uses the concept of “computation” and the tool of “computers” to study and implement “intelligence.”
AI can be classified into general-purpose AI and specialized AI. General-purpose AI is also referred to as strong AI. It is an AI that is not limited to a specific task but is capable of general-purpose processing; that is, it has the same intelligence as humans. Some examples of general-purpose AI are Doraemon and Astro Boy. None of them exist in the real world yet. Specialized AI is also called weak AI. It is an AI that specializes in performing a specific task. Image recognition, chess, Go, automated driving, human conversation, etc., are all examples of specialized AI.
In a broader sense, AI includes rule-based AI and machine-learning AI. Rule-based AI refers to making decisions according to rules described by humans. It also automates tasks that require hardware and human judgment. It can be described as an office robot. In contrast, machine-learning AI generally does not require a human to write the rules. It has algorithms for self-learning in machine-learning models, and it behaves intelligently based on those algorithms, building the models automatically. Compared with machine-learning AI, rule-based AI has advantages such as faster to automate tasks, a human can train AI, and lower cost. On the other hand, it also has disadvantages such as unable to learn independently, unable to train AI unless it is explicit knowledge, and unable to make decisions on matters it has not been trained on.
Machine learning can be divided into supervised learning, unsupervised learning, and reinforcement learning in general (Figure 1).
AI and machine learning relationship diagram.
Supervised learning is the process of preparing training data with a set of inputs and correct outputs in advance, and having the computer learn to produce correct outputs when given a certain input. Supervised learning methods are mainly used for prediction and classification (labeling). Examples include image classification. Supervised learning can be applied to forecasting sales and predicting the tendency of customers’ churns, etc.
Unsupervised learning is often referred to as self-supervised learning these days. It is used to grasp the inherent structure of data from the input data supplied Unsupervised learning mainly uses clustering techniques to classify data. Examples of applications include product recommendation, customer segmentation, target marketing, etc., based on customer purchase history.
Reinforcement learning is a model that learns to maximize future value instead of giving the correct answer. In other words, it learns to act in a way that maximizes value through trial and error. The problem setting is similar to that of supervised learning, but it is not enough to learn the output of the given correct answer as it is, but it is necessary to learn the behavior that maximizes value in a broader sense.
Tetris game is a good example to understand the scheme of reinforcement learning. When playing a game of Tetris, the problem of getting the highest possible score can be considered in the framework of reinforcement learning. The best way to score at that point is to play in such a way that even a single row can be eliminated immediately, but in the longer term, the score will be higher if you accumulate as much as possible and then eliminate many rows at once.
AlphaGo, which defeated a human player, also incorporates reinforcement learning in some parts of its games. As in the case of Go, it can learn even when humans do not necessarily know the correct answer, so it is expected to acquire the ability to surpass humans.
A neural network is a mathematical model inspired by the function of nerve cells (neurons) and their connections, or neural networks in the human brain, called artificial neurons. When the neural network model is properly constructed according to the problem to be solved, it can make a variety of decisions (i.e., outputs), such as the following:
First, image recognition and binary classification. For example, it answers questions such as: Is the object in front of me a ship or a train?
Second, natural language processing, multi-level classification. For example: which is “Emma Maersk” among various images of vessels online?
Deep Learning is a method of machine learning in which neural networks are combined in multiple layers to enhance their representation and learning capabilities. Currently, it is the most commonly used algorithm for AI.
Deep learning, on the other hand, is often used when complex unstructured data is available and is applied in fields such as speech recognition, image recognition, and natural language processing.
There are many cases where conventional machine-learning methods do not work well for classification and regression without complex function approximation, and deep-learning methods are increasingly being used for such problems. In some cases, deep-learning methods have dramatically improved recognition accuracy compared with conventional methods, and deep learning is currently attracting a great deal of attention in the world. Recently, it has been used in a wide range of fields such as recommendation and automated driving.
BC is an open distributed ledger technology (DLT) based on a peer-to-peer (P2P) approach that allows transactions to be recorded on thousands of servers simultaneously. On the efficient, verifiable, and immutable BC platform, anyone can see the transactions of others in near real time, making it difficult for one user to manipulate the records and control the network [2]. Applying these features, BC facilitates the digitization of traditional economic, legal, and political systems.
In BC, cryptography is used to store records (hash values11) of transactions that occur in the network in blocks of records called blocks. In each block, it contains three values, the first is the hash value of the previously generated block, the second is the record of the transaction in the current block, and the third is a new hash value generated by a disposable random value called a nonce. The three values are passed to the next block and the accumulated blocks form a chain of blocks in time series. The name BC comes from this data structure.
BC can be divided into public BC, which allows anonymous participation, and permitted BC, which requires permission to participate. Public BC is mainly applied to cryptocurrencies. Since the permitted type of BC is faster than the public type in handling transactions, it has been applied to various business fields such as supply chain and intellectual property management [3].
There have been five main types of algorithms for consensus building in BC (Table 1). In public BC, PoW and PoS are mainstream; in the PoW consensus, rewards are evaluated by the amount of work done. In PoW consensus, the reward is evaluated by the amount of work done; in other words, the network participant who performs the appropriate computation the fastest receives the reward. In the PoS consensus, rewards are based on both the amount of work and the amount of cryptocurrencies held. In PoS consensus, rewards are based on both the amount of work done and the amount of cryptocurrencies held, easing the fierce competition in PoWs and saving electricity consumption, it suffers the problem that the rich get richer. On the other hand, in permitted BC, PBFT is the mainstream method. PBFT is faster than other consensus methods but has the disadvantage that blocks will not be created if two-thirds or more of the consensus is not obtained.
Consensus | PoW (Proof of Work) | PoS (Proof of Stake) | PoI (Proof of Importance) | PoC (Proof of Consensus) | PBFT (Practical Byzantine Fault Tolerance) |
---|---|---|---|---|---|
Evaluation method | (one’s) workload | Workload and coin holdings | Overall evaluation of coin holdings, transaction volume, transaction frequency, etc. | Designated agency | Consensus of two-thirds or more |
Benefits | Resistant to transaction tampering | No wasted power consumption | Low power consumption | Fast remittance speed | High speed compared to other methods |
Weakness | High-power consumption | How the rich get richer. | Participation is impossible without a certain amount of coins. | centralized | A block will not be created unless a two-thirds majority is agreed. |
Representative example | Bitcoin (BTC) | Ethereum (ETH) | Nem (NEM) | Ripple (XRP) | Permitted type consortium type |
Typical consensus algorithms.
In the maritime industry, many players from different industries, usually in several countries, are involved in currently operating blockchain platforms. This complexity leads to a lack of transparency in the entire supply chain. In addition, the industry has the disadvantage of high transaction costs for information exchange, the possibility of fraud and theft, and vulnerability to the risk of cyber-attacks. BC offers the possibility to solve these problems [3]. To maximize the capacity and productivity of the digital information space, traditional authentication methods and data structures need to be reformed and modern technologies such as BC need to be actively applied.
PI was initially proposed by Montreuil in 2010 [4]. He defined PI as an open, global logistics network that efficiently and sustainably interconnects all elements of the logistics process. The PI includes the complete supply chain including storage, movement, supply, and delivery of goods, and the PI network is composed of various logistic providers. The goal of PI is to create a global logistics system based on the interconnection of existing logistic networks. To achieve this, a standardized set of protocols, modular containers, and smart interfaces are combined modular containers, called PI containers (Figure 2), which come in various sizes and can be combined and loaded to reduce waste. In addition to modular containers, PI-stores, PI-movers, PI-conveyors, and PI-gateways have also been proposed.
An example of PI container combination. Source: Montreuil et al., 2010 [
The characteristics of PI include interoperability, modularity, and standard interfaces and protocols. In order to take advantage of these features, technologies to share data while protecting confidentiality, such as BC technology, are essential.
Although it is not difficult to understand the usefulness of PI and BC, specific application measures have not been fully studied. In this chapter, we make a proposal for planning measures to build a BC network in PI, and discuss issues and measures for practical application. Specifically, the next sections also aim to clarify the following two points. First, to clarify the scope of application of BC in PI. Second, we propose a framework for implementing PI and BC technologies.
Various information systems have been introduced in maritime and port-related operations, such as Terminal Operating System (TOS) for internal terminal operations, Port Community System (PCS) for port logistics, Automatic Identification System (AIS), and the Transport Management System (TMS) for land-side operations such as trucking [5]. A smart port is an initiative that aims to improve the efficiency and safety of the port as a whole and to reduce the environmental impact of the port by integrating these systems through innovations in automation and new digital technologies such as IoT, AI, and 5G. Currently, the Port of Rotterdam (Smart Port Initiative) and the Port of Hamburg (smart port) in Europe, Japan (PORT2030), Korea (Smart Maritime Logistics) and Singapore (Sense-making Analytics For maritime Event Recognition: SAFER) and other major ports around the world are working on various initiatives.
The Port of Rotterdam in the Netherlands has a vision of being the “smartest port in the world” and is working on digitalization, energy transformation, and innovation to become carbon neutral. They have identified four levels of “digital maturity” for a port cargo community as shown in Table 2 [8]. The Smart Port Initiative is a roadmap that includes projects in energy and industry like recycling, electrification, renewable energy, logistics like BD, automated driving and BC, port infrastructure like quays, dredging, maritime traffic management, and innovation. The Port Call Optimization (PMO) project is underway as part of Port Collaborative Decision Making (PortCDM), an initiative aimed at optimizing the timing of vessel arrival and departure [9]. PortXChange (formerly Pronto), a real-time information sharing platform for PMO between shipping companies, shipping agents, terminals, and other stakeholders, has been in operation since 2018. In the past, about 75% of shipping companies, including major operators such as Maersk and ONE, have participated in the experiment, and the results have shown that PortXChange is effective in reducing the waiting time of ships, especially for departures.
Level | Name | Overview |
---|---|---|
1 | Digitization of individual activities in the port | The individual organizations operating in the port digitize their processes so that they work more efficiently. |
2 | Integrated systems in a port community | The digital exchange of information within the port community leads to reliable, efficient, and paperless dataflows, resulting in more efficient port operations. The focus at this level is related to securely sharing data. Cybersecurity and cyber resilience are key. |
3 | Logistics chain integrated with hinterland | The hinterland four players (importers, exporters, logistics hubs, and domestic transporters) are involved in digital communication with the port community. This integration promotes sharing of real-time information on freight and vessel movements, facilitating better planning. |
4 | Connected ports in the global logistics chain | The port and its hinterland connections are extended to other ports around the world, forming a global network of interconnected ports. This network will allow further reductions of inefficiencies in the global logistics chains by optimizing the use of port capacities and achieving shorter, more reliable transit times. |
In Japan, one of the main measures in the mid-to long-term port policy “PORT2030” announced in July 2018 is to make ports smarter and more resilient by using information and communication technologies. In addition to the complete computerization of ports, which will be called “Cyber Port” through the construction of a port-related data linkage infrastructure, the policy aims to create container terminals with the world’s highest level of productivity and a good working environment (AI terminals) by combining AI, IoT, and automation technologies. In the container terminal field, the introduction of remote-controlled cargo handling machinery and automated gate handling is being promoted, terminal operations are being streamlined and optimized using AI and other technologies, automated vessels, and remote-controlled tugboats are being operated, automated guided vehicles are being introduced, and automated trucks are being driven in convoys. In addition, the next generation high standard unit load terminal will be developed. Furthermore, in the next generation of high standard unit load terminals, the use of automatic driving technology for cross-carriage transport and the linkage with automatic navigation and navigation support technology for ships are mentioned.
Various efforts have been made by shipping companies to develop navigation support technologies to improve the safety and efficiency of ship operations using IoT and big data. In this context, Maritime Autonomous Surface Ships (MASS) have been attracting attention rapidly in recent years. The term MASS generally describes a ship that is highly automated or remotely controlled to perform some or all of the following shipboard tasks: external situational awareness (watchkeeping), monitoring of equipment status, ship operation, engine control, cargo management, and loading/unloading, take-off and landing, and other shipboard tasks by using the latest technologies such as IoT, ICT, and data analysis technologies, various sensors, and land-based monitoring and control centers connected by broadband communications.
A number of projects are underway, mainly in Europe, with the aim of realizing MASS. In December 2018, Rolls-Royce and FinnFerry successfully demonstrated the world’s first fully automated ferry. As an example of an international project, One Sea, a consortium launched in Finland in 2016, is developing a roadmap for practical application and discussing the necessary safety standards and international standardization in order to create an environment for MASS operation by 2025.
There is an ongoing international discussion on the legislative framework for safety standards for MASS. With regard to classification societies’ certification systems, in February 2017, the British classification society Lloyd’s Register published the LR Unmanned Marine Systems Code, which sets out the performance requirements for automated ships. The International Maritime Organization (IMO) has been considering the regulatory aspects of automated ships since May 2018 and has presented a provisional proposal, as shown in Table 3, and is discussing the necessary amendments to IMO rules and new developments. For demonstration tests, the provisional guidelines for safe and efficient demonstration tests of automated ships, jointly proposed by Japan and Norway, have been approved in June 2019. In May 2021, IMO has completed a regulatory scoping exercise on MASS that was designed to assess existing IMO instruments to see how they might apply to ships with varying degrees of automation.
Level | Name | Overview |
---|---|---|
1 | Ship with automated processes and decision support | Seafarers are on board to operate and control shipboard systems and functions. Some operations may be automated and at times be unsupervised but with seafarers on board ready to take control. |
2 | Remotely controlled ship with seafarers on board | The ship is controlled and operated from another location. Seafarers are available onboard to take control and to operate the shipboard systems and functions. |
3 | Remotely controlled ship without seafarers on board | The ship is controlled and operated from another location. There are no seafarers on board. |
4 | Fully autonomous ship | The operating system of the ship is able to make decisions and determine actions by itself. |
In Japan, industry, government, and academia have been collaborating since FY2017 to develop technologies, develop infrastructure and systems, and study business models for the realization of MASS through demonstration projects of automatic ship operation, remote ship operation, and automatic docking and unloading functions in order to improve the environment, including the formulation of safety requirements. The ClassNK has been working on the development of the technology through demonstration projects. In January 2020, the ClassNK established requirements and procedures for the functional verification of automation and remote-control systems used on ships and remote-control facilities, from the perspective of ensuring safety at each stage of development and design, ship installation, and operation [11]. The Ship Data Centre was established in December 2015 as a platform for the use of ship big data, with the participation of shipping companies, shipbuilders, marine industry operators, and meteorological information companies. The Ship Data Center was established in December 2015 as a foundation for the use of ship big data, with the participation of shipping companies, shipbuilders, marine industry companies, meteorological information companies, etc. Rules for fair and equitable data use have been established to promote the distribution and use of ship big data, and the effective use of accumulated big data is being promoted.
Based on the results of the economic evaluation of the MASS operation system, efforts are being made to commercialize a manned automated ship operation system (corresponding to automation level 1 in Table 3), which is more feasible in the short term. In NYK line, research has been conducted on an action planning system for the decision-making required to execute ship operations, and the world’s first demonstration of a manned automated ship based on the provisional guidelines set by the IMO was conducted in September 2019 [12]. Future projections for unmanned automated ships (corresponding to automation level 3 or higher in Table 3) for domestic ships suggest that if 50% of ships are replaced by unmanned automated ships in 2040, the annual economic impact will be approximately 1 trillion yen [13]. In June 2020, the Foundation selected five projects for MEGURI 2040, which aims to realize unmanned automated ships by 2025, by conducting the world’s first demonstrations in waters with high vessel traffic, long-distance navigation, and using large vessels.
The unmanned and automated handling of cargo at container terminals is expected to increase productivity per worker, improve the working environment and safety, and reduce the effects of weather conditions such as fog and wind. On the other hand, the introduction of the system is not without its challenges, such as high initial investment costs, maintenance costs (e.g., power consumption), and coordination with trade unions. At the ECT Delta Terminal in the Port of Rotterdam, the world’s first automated terminal, an Automated Guided Vehicle (AGV) and an Automated Stacking Crane (ASC) were introduced in 1993. However, the introduction of these systems did not proceed due to technical and economic problems and difficulties in coordinating with labor unions, and there were only a few cases until the mid-2000s. However, since the mid-2000s, and especially since the 2010s, the number of automated terminals has been increasing rapidly, with nearly 60 terminals worldwide having installed the system so far. The number of automated terminals has increased rapidly since the mid-2000s, especially in the last decade. Table 4 summarizes the status of the introduction of automated terminals, focusing on the level of automation. The symbols in the table indicate: ◎: mainstream status with many cases of introduction, ○: diffusion stage with several cases of introduction, and △: early stage with limited cases of introduction. In the case of marshaling yards and land-side container handling, remote control and automation are the basic systems. On the other hand, the manned operation is the mainstream for quay cranes, and full automation has been introduced only recently in a limited number of cases. In the case of horizontal transport within the premises, although there is a high degree of automation, various types of cargo handling machines have been introduced, and the level of automation differs greatly between ports.
Type | Activities | Typical cargo handling machine | Manned | Unmanned | |
---|---|---|---|---|---|
Remote control | Automation | ||||
Waterside transport | Moving containers from ship to shore | STS (Ship To Shore Container Crane)/ QC (Quayside Conatiner Crane) | ◎ | ○ | △ |
Horizontal transport | Moving containers between the quayside and yard storage blocks | AGV (Automated Guided Vehicle), SC (Straddle Carrier), ShC (Shuttle Carrier), Chassis | ◎ | — | ○ |
Marshaling yard | Moving containers at yard storage blocks | ASC (Automated Stacking Crane), ShC | — | ○ | ◎ |
Landside transport | Moving containers from the terminal truck gate or intermodal railhead to the marshaling yard | ASC, ShC | — | ◎ | ○ |
In Japan, AGVs and remote-controlled ASCs were introduced at the south side container terminal of Tobishima Pier in the port of Nagoya in December 2005, which is a relatively early stage in international perspective, but it is the only automated terminal in Japan at present. Currently, efforts are being made to promote the introduction of remote-controlled ASCs, mainly at strategic international container ports, and to improve the efficiency and optimization of terminal operations by using AI-based on container cargo information.
In the following, a specific case study of a blockchain technology application, in a Logistics 4.0 Physical Internet environment, is explicated, as a representative system implementation for innovative, digital maritime logistics environments, with automated ships and terminals constituting flagship applications of Industry 4.0.
Three recent representative studies on the application of PI and BC in the supply chain are available [16, 17, 18]. Meyer et al. [16] proposed a conceptual framework for the exchange of value and physical assets in logistics networks that proposed a BC-based conceptual framework and provides a solution to the fundamental barrier of PI. As the main contribution, they identified barriers to transforming current logistics systems into PI networks through case studies. The key barriers included the creation of a network with equal participation, robustness of the framework, assurance of integrity and resilience, rewards in the operational process, and reliable data exchange. By further describing the key features of the technology, they discussed how the BC would address the barriers to PI adoption. They proposed Ethereum BC, implemented smart contracts based on the ERC721 standards12, and evaluated the transport process in PIs. The authors conclude that BC technology can solve the barriers in PI because it enables a reliable and secure exchange of value in an untrustworthy environment. The authors propose a PoS based BC environment in order to save computational resources. In the case of small-scale PIs, the proposed solution already works, but the scalability13 problem as a whole needs to be solved before PIs can be widely adopted.
Hassan et al. [17] presented a permitted BC architecture suitable for the integration of BC technology with PI. They discussed how to take advantage of the interoperability14 between two permitted BCs. They demonstrated the applicability and practicality of the PI architecture to be built on top of a permitted BC and presented a case study of its application. The authors pointed out the scalability of both BC and PI networks as an issue to be solved.
Tan et al. [18] presented a framework of green logistics based on BC to realize sustainable logistics by integrating IoT and big data. The authors propose a framework with seven layers: physical layer, perception layer, network layer, blockchain layer, management layer, application layer, and user layer. The authors pointed out three issues: data storage and transmission, implementation cost, and risk. Then, for future research, the authors suggested to focus on the following: (1) developing a way to effectively connect the physical and perceptual layers to collect logistics data, and (2) designing an incentive mechanism to encourage logistics companies to participate in the BC platform.
In contrast to the various advantages of BC, this technology requires a transformation of digital systems. First, existing processes need to be digitized. Currently, there are many tasks in logistic operations that are done by hand on paper or on computers that are not connected to a network. In order to effectively accumulate and utilize data in these tasks, it is necessary to digitize the tasks themselves or use AI (e.g., Optical Character Reader) services to digitize them.
Next, in order to work with platforms such as BC, existing systems need to have a mechanism to use APIs15. In the logistics field, many existing systems are still based on EDI16, which supports only batch sending and receiving, while APIs support real-time sending and receiving. In the logistics sector, there are still many existing EDI-based systems; EDI supports only batch sending and receiving, while APIs support real-time sending and receiving, and the development cost is higher than APIs [3]. Making EDI-based core systems API compatible is an important task. The issue of standardization is important in the diffusion of APIs. At present, there is a bunch of standards at the level of international organizations, governments, and industries. Some of the standards conflict with each other. These standards need to be unified. Organizations like Digital Container Shipping Association (DCSA) help to expedite the process. DCSA aims to develop digital standards for the containership industry and has compiled and published electronic standards such as vessel schedules, port operations, and electronic B/Ls. The PoV should follow the standards and protocols published by DCSA. In addition, the API is an architectural style that can be easily manipulated and can flexibly respond to the unique standards of countries and industries, for example, 10-ft container, low floor chassis.
Munim et al. [19] identified the main challenges in the practical application of BC in the maritime sector as lack of standardization of data elements, lack of interoperability and scalability between systems, delay in legislation, lack of understanding of the technology, and lack of training facilities and materials. PiChain is facing the same challenges as it uses BC technology. In addition, it is necessary to solve the issues of attracting participating logistics companies and infrastructure development in the implementation of PI. The search for solutions to these issues remains a future task.
These previous studies pointed out the issues of scalability after conducting small-scale demonstrations. In this study, we propose a framework for building innovative Logistics 4.0 systems and applications to solve these issues.
We propose the following scope of application of BC technology in PI. PI contains three flows, namely physical (logistics) flow, information flow, and financial flow. BC technology is indispensable for two of the three flows: information flow and financial flow (Figure 3).
The scope of BC technology application in PI.
For implementation, this chapter proposes a new framework called PiChain, which consists of five components (Figure 4).
Overview of the proposed framework “PiChain.”
The first component is the PI that interconnects the maritime logistics networks. The second component includes networks such as LPWA that supports various types of IoT devices, and 5G and 6G that support cloud computing and edge computing. The third component consists of sensors, IoT devices, Internet of Robotic Things (IoRT), and drones. The fourth component includes big data for optimization with AI and visualization with business intelligence (BI). The top layer is the component that refers to the space optimization of business and operational processes implemented goals of logistics and sustainability goals (SDGs). All these components function on a decentralized platform that uses BCs to prevent data modification, which also support traceability and various types of payments.
To give a better idea of how PiChain works, let us look at a few scenarios. In the future cargo transportation, upon booking information received, AI will automatically calculate the optimal transportation route and method constraints such as cargo destination, size, and weight using PI containers that match the size of the cargo. As soon as this information is finalized or updated, it is automatically sent to the shipper. In the shipper’s internal system, AI uses the latest transportation information to optimize ordering, warehouse storage, and production planning. As soon as the consignee receives the shipment, the payment managed by BC’s smart contract will be automatically executed.
To overcome the lack of scalability of BCs, as pointed out in previous studies, this study recommends the adoption of the Avalanche protocol (Table 5) proposed by Rocket 2019 [20].
Comparison of BC protocols.
1Finality means that the amount of money is certain to be obtained as expected. The Bank of Japan lists the following specific conditions for a finalized settlement: (1) The money received will not later be turned into scrap paper or disappear, and (2) the settlement made will never be reversed later.
2A 51% attack is the control of 51% (more than 50%) of the hash rate of the entire network by a malicious group or individual to perform fraudulent transactions.
Source: Prepared by the author based on Sirer 2020 [13].
The Avalanche protocol is one of the most promising platforms for BCs because of its scalability, ease of use, flexibility, and proper governance. Avalanche was initially built to serve the financial markets (cryptocurrency AVAX), but it is interoperable with both public and permitted BC. Therefore, it can be adopted by other industries in addition to finance. Avalanche is also capable of combining public and private BCs. Compared with the existing Classical and Nakamoto protocols, the BFT-based Avalanche protocol is very efficient and robust, and can also achieve high productivity and fast finality. While traditional protocols require any given node to communicate with all other nodes, the Avalanche protocol communicates with a small subset (validators), which dramatically reduces the latency to 1/3600 compared with Bitcoin (Table 6). As a result, Avalanche is able to achieve a performance of 7100 transactions per second, compared with 5 transactions per second for Bitcoin, the Nakamoto protocol equivalent.
Performance comparison | Bitcoin | AVAX |
---|---|---|
Latency | 1 | 1/3600 |
Speed (transactions per second) | 5 | 7100 |
Finality | Accomplished in 1 hour. | Accomplished in 1 second. |
Number of simultaneous participants | About 20 people | millions of people |
We recommend a small-scale Proof of Value (PoV) to be executed. In the PoV, a small-scale PI network will be constructed by implementing the Avalanche protocol, which is small scale and scalable, in order to connect with the existing logistics network and using BC technology, the collected big data will be analyzed for optimization, etc., using AI while ensuring its confidentiality. The results will be used for management decisions and environmental protection measures. This positive cycle will dramatically improve the efficiency of logistics and promote sustainable development. It will also be possible to measure and optimize the contribution of innovative technologies to the sustainable development of logistics and the SDGs. For example, it will be possible to quantify how much waste in loading and waiting for pickup is eliminated by the use of PI-containers, and how much congestion is eliminated by optimization at ports. Or how much truck driver time was saved by reducing waiting time, or how much CO2 emissions were reduced, such measurements could be automatically recorded and measured on a reliable BC. The combination of Avalanche and PI in the logistic industry will drive logistics digitalization to a global scale.
In this chapter, we have overviewed the international efforts for innovation in automation and digitalization for the realization of the Smart Port, including the development of technologies and demonstration experiments for their diffusion. It is necessary not only to automate cargo handling at the terminal, but also to share information in real time regarding pre-and post-processes, such as the arrival and departure of ships and the waiting status of vehicles, in cooperation with various IoT devices, and to prepare in advance based on predictive information using AI. It is expected to establish a de facto standard on a global scale by promoting the packaging of port handling machinery combining hardware and software. On the other hand, the international standardization for automated ships is being discussed internationally mainly by initiated by IMO as de jure standard. In addition, it will be necessary to share real-time information on the movements of ships using AIS and IoT and to make comprehensive efforts in cooperation with port infrastructures, such as coordinated operation with work vessels such as tugboats and refueling vessels, and automatic mooring at the wharf. In August 2020, MASSPorts, a framework for international collaboration on the operation of Maritime Autonomous Surface Ships (MASS) in ports, will be launched to establish guidelines for demonstration operations and to study interoperability in multiple ports around the world.
From the research and development stage to the full-scale deployment of new technologies, it is necessary to consider not only the individual optimization of ports and ships but also the overall optimization involving the ocean, ports, and the inland hinterland. As the need for mutual cooperation between ports and ships increases, new infrastructures, systems, laws and regulations, and international standardization need to be discussed. In addition, it is necessary to address not only the safety and cost aspects of installation and operation, but also cyber security, environmental aspects including renewable energy and electrification, and social acceptability. In order to enhance social acceptability, it is important to build a relationship of trust so that not only the port and maritime industries but also the general public can feel secure.
Furthermore, in this chapter, we have proposed PiChain, a framework for creating a sustainable, next-generation maritime logistics system, by applying PI to digitize maritime logistics networks and BC technology for secure information exchange to improve the overall efficiency of maritime logistics, at ports. The following three effects can be expected from the adoption of PiChain.
Recently, there have been many disruptions in the supply chain due to unexpected circumstances such as bad weather, cyber-attacks, and port congestion. In particular, the covid-19 pandemic that began in early 2020 led to travel restrictions and border closures in some countries, which in turn caused disruptions in sea, land, and air logistics. The disruption of logistics also resulted in stagnant production in many countries. The framework proposed in this chapter, PiChain, is useful for supply chain management during emergencies and early recovery from disasters, as the BC-based platform provides real-time information and visualization of the entire delivery process, which in return enables quick response to unexpected delays. In addition, since PI containers can be freely combined or split, switching parts of cargo to alternative modes of transportation can be done flexibly when needed. Furthermore, the application of automated delivery methods, such as drones, will make it possible to deliver even in the middle of the night or in hazardous environments. In conclusion, PiChain can strengthen the resilience of the supply chain while managing a wide range of unknown risks.
In addition, cyber-attacks in the supply chain have been dramatically increasing in recent years. With risks increasing day by day, a high level of cybersecurity is vital for supply chain resilience. The PiChain framework uses BC technology to make the entire network highly resistant to cyber-attacks. Even in the event of being attacked, the stolen data are a hash value generated by BC, so it is difficult to recover the original data from the hash value, which significantly reduces the risk of information leakage. In addition, since the data are stored in a distributed manner in the cloud, it can be recovered quickly after an attack.
Regarding the establishment of a sustainable supply chain within the framework of PiChain, the following three points can be summarized.
First, realizing the SDG Goals. Visualizing, measuring, and optimizing GHG emissions will help to minimize their negative impact on the environment. This will contribute to the realization of SDG Goal 13: Take urgent action to combat climate change and its impacts.
Second, improvement of working conditions. In the framework of PiChain, it is expected to improve the working conditions of workers. For example, AI-guided optimal delivery routes will shorten waiting time hence reducing stress for drivers. In addition, logistics workers will be able to enjoy the benefits of advanced visibility and perform their daily work in a more independent way. This will contribute to SDG Goal 8: Promote sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all.
Third, improvement of service quality. Visible logistics management with PiChain will make just-in-time delivery easier. The deployment of drones will also make nighttime delivery possible. This will help improve the quality of logistic operations by enabling a quick response to any unforeseen circumstances that may arise.
With the spread of innovative technologies, new business models will emerge. For example, the inspection at the yard when returning empty containers used to be done by human eyes. Now, using AI image recognition technology, AI can quickly analyze photos of containers automatically taken by surveillance cameras at the gate, and determine if the container is dirty or damaged with an accuracy of over 98%. This kind of service is already being offered in countries like China.
AI will be able to analyze the big data collected and accumulated from the IoT and other sources to realize end-to-end optimization and real-time visibility of the supply chain. New business models that provide niche services in the supply chain emerge continuously, benefiting from innovative technologies.
In addition, there will be businesses that provide training on technologies such as BC and AI. Not only corporate management but also frontline workers will acquire basic knowledge of the new technologies to work more comfortably and efficiently. Since such services are still few, demand will increase further and new businesses in this field are expected to grow considerably. With the digitization of operations and the creation of new business models, maritime logistics, and its various systems, including smart ports will evolve into the next generation, Industry 4.0 modus operandi.
As data-centric processes gain more momentum, shipping and port operations are transformed by meticulously embracing innovative business models and Industry 4.0 technologies. Reliable, secure, and efficient cross-collaboration maritime logistic processes are of paramount importance for the promotion of automated ports, as critical nodes in sustainable, digital supply chains.
A decentralized maritime logistics management system, such as a blockchain-based and IoT-aware system that is deployed over a Physical Internet reference architecture, can support and further advance the development of shipping digitalization and ports’ automation. AI techniques and respective platforms can exploit real-time information on the movements of ships using AIS and IoT, also port infrastructures and machinery information, and data from vehicles and objects supporting the overall logistics flow, in road or air transport segments, respectively. In this chapter, we outline the technologies and provide a blueprint for building efficient, decentralized, scalable Logistics 4.0 systems, offering a prototype infrastructure model and immediate practice guidance to the next-generation shipping and port community.
This work was supported by JSPS KAKENHI Grant Number 21H01564.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
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\\n\\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
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The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
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\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
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\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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Chun",coverURL:"https://cdn.intechopen.com/books/images_new/3476.jpg",editedByType:"Edited by",editors:[{id:"164636",title:"Prof.",name:"Jang Ho",middleName:null,surname:"Chun",slug:"jang-ho-chun",fullName:"Jang Ho Chun"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2549",title:"Ion Exchange Technologies",subtitle:null,isOpenForSubmission:!1,hash:"d5d70a346ca433c501e5968f54286740",slug:"ion-exchange-technologies",bookSignature:"Ayben Kilislioğlu",coverURL:"https://cdn.intechopen.com/books/images_new/2549.jpg",editedByType:"Edited by",editors:[{id:"139903",title:"Prof.",name:"Ayben",middleName:null,surname:"Kilislioglu",slug:"ayben-kilislioglu",fullName:"Ayben Kilislioglu"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:21,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"40697",doi:"10.5772/51040",title:"Selective Removal of Heavy Metal Ions from Waters and Waste Waters Using Ion Exchange Methods",slug:"selective-removal-of-heavy-metal-ions-from-waters-and-waste-waters-using-ion-exchange-methods",totalDownloads:19357,totalCrossrefCites:37,totalDimensionsCites:95,abstract:null,book:{id:"2549",slug:"ion-exchange-technologies",title:"Ion Exchange Technologies",fullTitle:"Ion Exchange Technologies"},signatures:"Zbigniew Hubicki and Dorota Kołodyńska",authors:[{id:"42116",title:"Dr.",name:"Dorota",middleName:null,surname:"Kołodyńska",slug:"dorota-kolodynska",fullName:"Dorota Kołodyńska"},{id:"141883",title:"Prof.",name:"Zbigniew",middleName:null,surname:"Hubicki",slug:"zbigniew-hubicki",fullName:"Zbigniew Hubicki"}]},{id:"33450",doi:"10.5772/37583",title:"Measurement of the Nanoscale Roughness by Atomic Force Microscopy: Basic Principles and Applications",slug:"measurement-of-the-nanoscale-roughness-by-atomic-force-microscopy-basic-principles-and-applications",totalDownloads:21310,totalCrossrefCites:20,totalDimensionsCites:89,abstract:null,book:{id:"2282",slug:"atomic-force-microscopy-imaging-measuring-and-manipulating-surfaces-at-the-atomic-scale",title:"Atomic Force Microscopy",fullTitle:"Atomic Force Microscopy - Imaging, Measuring and Manipulating Surfaces at the Atomic Scale"},signatures:"R.R.L. De Oliveira, D.A.C. Albuquerque, T.G.S. Cruz, F.M. Yamaji and F.L. Leite",authors:[{id:"1164",title:"Dr.",name:"Fabio",middleName:"Lima",surname:"Leite",slug:"fabio-leite",fullName:"Fabio Leite"},{id:"136651",title:"MSc.",name:"Ricardo",middleName:null,surname:"De Oliveira",slug:"ricardo-de-oliveira",fullName:"Ricardo De Oliveira"},{id:"136652",title:"M.Sc.",name:"Diego",middleName:"Aparecido Carvalho",surname:"Albuquerque",slug:"diego-albuquerque",fullName:"Diego Albuquerque"},{id:"136653",title:"Prof.",name:"Tersio",middleName:null,surname:"Cruz",slug:"tersio-cruz",fullName:"Tersio Cruz"},{id:"136657",title:"Prof.",name:"Fabio",middleName:null,surname:"Yamaji",slug:"fabio-yamaji",fullName:"Fabio Yamaji"}]},{id:"49054",doi:"10.5772/60952",title:"Anion Exchange Resins as Effective Sorbents for Removal of Acid, Reactive, and Direct Dyes from Textile Wastewaters",slug:"anion-exchange-resins-as-effective-sorbents-for-removal-of-acid-reactive-and-direct-dyes-from-textil",totalDownloads:3188,totalCrossrefCites:24,totalDimensionsCites:47,abstract:"Coloured wastewaters are a consequence of batch processes in both dye-manufacturing and dye-consuming industries. Dyes are widely used in a number of industries, such as textile and leather dyeing, food, cosmetics, paper printing, gasoline, with the textile industry as the largest consumer. Dyeing as a fundamental operation during textile fibre processing causes the production of more or less coloured wastewaters, depending on the degree of fixation of dyes on substrates, which varies with the nature of substances, desired intensity of coloration, and application method. Dye bearing effluents are considered to be a very complex and inconsistent mixture of many pollutants ranging from dyes, dressing substances, alkalis, oils, detergents, salts of organic and inorganic acids to heavy metals.Thus after dyeing wastewaters are characterized not only by intensive and difficult for removal colour but also by high pH, suspended and dissolved solids, chemical and biochemical oxygen demands. Ion exchange is a very versatile and effective tool for treatment of aqueous hazardous wastes including dyes. The role of ion exchange in dye effluents treatment is to reduce the magnitude of hazardous load by converting them into a form in which they can be reused, leaving behind less toxic substances in their places or to facilitate ultimate disposal by reducing the hydraulic flow of the stream bearing toxic substances. Another significant feature of the ion exchange process is that it has the ability to separate as well as to concentrate pollutants. Taking into account high capacity and selectivity of ion exchange resins for different dyes, they seem to be proper materials for dyes sorption from textile effluents. The aim of the paper is to study the removal of the acid, reactive and direct textile dyes such as C.I. Acid Orange 7, C.I. Reactive Black 5 and C.I. Direct Blue 71 on the commercially available anion exchangers (Lewatit MonoPlus MP 62, Lewatit MonoPlus MP 64, Lewatit MonoPlus MP 500, Lewatit MonoPlus M 500, Amberlite IRA 67, Amberlite IRA 478RF, Amberlite IRA 458 and Amberlite IRA 958) differing not only in basicity of the functional groups but also in composition and structure of the matrix. Comparison of the sorption parameters obtained by the batch method taking into account influence of phase contact time, dyes initial concentration and solution pH were discussed in detail. Desorption conditions depending on the dyes sorption mechanism were also presented. Influence of the auxiliaries typically present in textile effluents such as inorganic electrolytes and different surfactants on the amounts of dyes retained by the anion exchangers was presented. The adsorption behaviour of the polyacrylic Amberlite IRA 958 demonstrates that it can be a promising adsorbent for the textile wastewater treatment. The results obtained with raw textile wastewaters purification confirmed this statement.",book:{id:"4599",slug:"ion-exchange-studies-and-applications",title:"Ion Exchange",fullTitle:"Ion Exchange - Studies and Applications"},signatures:"Monika Wawrzkiewicz and Zbigniew Hubicki",authors:[{id:"141883",title:"Prof.",name:"Zbigniew",middleName:null,surname:"Hubicki",slug:"zbigniew-hubicki",fullName:"Zbigniew Hubicki"},{id:"173310",title:"Dr.",name:"Monika",middleName:null,surname:"Wawrzkiewicz",slug:"monika-wawrzkiewicz",fullName:"Monika Wawrzkiewicz"}]},{id:"52110",doi:"10.5772/64935",title:"Electrodeposition from Deep Eutectic Solvents",slug:"electrodeposition-from-deep-eutectic-solvents",totalDownloads:3488,totalCrossrefCites:7,totalDimensionsCites:29,abstract:"Deep eutectic solvents constitute a class of compounds sharing many similarities with properly named ionic liquids. The accepted definition of ionic liquid is a fluid (liquid for T<100 °C) consisting of ions, while DES are eutectic mixtures of Lewis or Brønsted acids and bases. Their most attractive properties are the wide potential windows and the chemical properties largely different from aqueous solutions. In the last few decades, the possibility to electrodeposit decorative and functional coatings employing deep eutectic solvents as electrolytes has been widely investigated. A large number of the deposition procedures described in literature, however, cannot find application in the industrial practice due to competition with existing processes, cost or difficult scalability. From one side, there is the real potential to replace existing plating protocols and to find niche applications for high added-value productions; to the other one, this paves the path towards the electrodeposition of metals and alloys thermodynamically impossible to be obtained via usual aqueous solution processes. The main aim of this chapter is therefore the critical discussion of the applicability of deep eutectic solvents to the electrodeposition of metals and alloys, with a particular attention to the industrial and applicative point of view.",book:{id:"5381",slug:"progress-and-developments-in-ionic-liquids",title:"Ionic Liquids",fullTitle:"Progress and Developments in Ionic Liquids"},signatures:"R. Bernasconi, G. Panzeri, A. Accogli, F. Liberale, L. Nobili and L.\nMagagnin",authors:[{id:"188210",title:"Associate Prof.",name:"Luca",middleName:null,surname:"Magagnin",slug:"luca-magagnin",fullName:"Luca Magagnin"},{id:"194387",title:"MSc.",name:"Roberto",middleName:null,surname:"Bernasconi",slug:"roberto-bernasconi",fullName:"Roberto Bernasconi"},{id:"194388",title:"MSc.",name:"Gabriele",middleName:null,surname:"Panzeri",slug:"gabriele-panzeri",fullName:"Gabriele Panzeri"},{id:"194389",title:"MSc.",name:"Alessandra",middleName:null,surname:"Accogli",slug:"alessandra-accogli",fullName:"Alessandra Accogli"},{id:"194390",title:"MSc.",name:"Francesco",middleName:null,surname:"Liberale",slug:"francesco-liberale",fullName:"Francesco Liberale"},{id:"194391",title:"Prof.",name:"Luca",middleName:null,surname:"Nobili",slug:"luca-nobili",fullName:"Luca Nobili"}]},{id:"25422",doi:"10.5772/28293",title:"Electrochemical Polymerization of Aniline",slug:"electrochemical-polymerization-of-aniline",totalDownloads:11463,totalCrossrefCites:3,totalDimensionsCites:29,abstract:null,book:{id:"607",slug:"electropolymerization",title:"Electropolymerization",fullTitle:"Electropolymerization"},signatures:"Milica M. Gvozdenović, Branimir Z. Jugović, Jasmina S. Stevanović, Tomislav Lj. Trišović and Branimir N. Grgur",authors:[{id:"73400",title:"Dr.",name:"Milica",middleName:null,surname:"Gvozdenović",slug:"milica-gvozdenovic",fullName:"Milica Gvozdenović"},{id:"78801",title:"Dr.",name:"Branimir",middleName:null,surname:"Jugović",slug:"branimir-jugovic",fullName:"Branimir Jugović"},{id:"78807",title:"Dr.",name:"Jasmina",middleName:null,surname:"Stevanović",slug:"jasmina-stevanovic",fullName:"Jasmina Stevanović"},{id:"120374",title:"Dr.",name:"Tomislav",middleName:null,surname:"Trišović",slug:"tomislav-trisovic",fullName:"Tomislav Trišović"},{id:"120376",title:"Prof.",name:"Branimir",middleName:null,surname:"Grgur",slug:"branimir-grgur",fullName:"Branimir Grgur"}]}],mostDownloadedChaptersLast30Days:[{id:"52110",title:"Electrodeposition from Deep Eutectic Solvents",slug:"electrodeposition-from-deep-eutectic-solvents",totalDownloads:3487,totalCrossrefCites:7,totalDimensionsCites:29,abstract:"Deep eutectic solvents constitute a class of compounds sharing many similarities with properly named ionic liquids. The accepted definition of ionic liquid is a fluid (liquid for T<100 °C) consisting of ions, while DES are eutectic mixtures of Lewis or Brønsted acids and bases. Their most attractive properties are the wide potential windows and the chemical properties largely different from aqueous solutions. In the last few decades, the possibility to electrodeposit decorative and functional coatings employing deep eutectic solvents as electrolytes has been widely investigated. A large number of the deposition procedures described in literature, however, cannot find application in the industrial practice due to competition with existing processes, cost or difficult scalability. From one side, there is the real potential to replace existing plating protocols and to find niche applications for high added-value productions; to the other one, this paves the path towards the electrodeposition of metals and alloys thermodynamically impossible to be obtained via usual aqueous solution processes. The main aim of this chapter is therefore the critical discussion of the applicability of deep eutectic solvents to the electrodeposition of metals and alloys, with a particular attention to the industrial and applicative point of view.",book:{id:"5381",slug:"progress-and-developments-in-ionic-liquids",title:"Ionic Liquids",fullTitle:"Progress and Developments in Ionic Liquids"},signatures:"R. Bernasconi, G. Panzeri, A. Accogli, F. Liberale, L. Nobili and L.\nMagagnin",authors:[{id:"188210",title:"Associate Prof.",name:"Luca",middleName:null,surname:"Magagnin",slug:"luca-magagnin",fullName:"Luca Magagnin"},{id:"194387",title:"MSc.",name:"Roberto",middleName:null,surname:"Bernasconi",slug:"roberto-bernasconi",fullName:"Roberto Bernasconi"},{id:"194388",title:"MSc.",name:"Gabriele",middleName:null,surname:"Panzeri",slug:"gabriele-panzeri",fullName:"Gabriele Panzeri"},{id:"194389",title:"MSc.",name:"Alessandra",middleName:null,surname:"Accogli",slug:"alessandra-accogli",fullName:"Alessandra Accogli"},{id:"194390",title:"MSc.",name:"Francesco",middleName:null,surname:"Liberale",slug:"francesco-liberale",fullName:"Francesco Liberale"},{id:"194391",title:"Prof.",name:"Luca",middleName:null,surname:"Nobili",slug:"luca-nobili",fullName:"Luca Nobili"}]},{id:"74147",title:"Electrochemical Impedance Spectroscopy (EIS): A Review Study of Basic Aspects of the Corrosion Mechanism Applied to Steels",slug:"electrochemical-impedance-spectroscopy-eis-a-review-study-of-basic-aspects-of-the-corrosion-mechanis",totalDownloads:2662,totalCrossrefCites:11,totalDimensionsCites:21,abstract:"AC impedance measurements have been applied for over twenty years in electrochemistry and physics to investigate the electrical properties of conductive materials and their interfaces using an external electrical impulse (VOLTAGE, V or CURRENT, I) as driving force. Furthermore, its application has recently appeared to be destined in the Biotechnology field as an effective tool for rapid microbiologic diagnosis of living organism in situ. However, there is no doubt that the electrochemical impedance spectroscopy (EIS) is still one of the most useful techniques around the world for metal corrosion control and its monitoring. Corrosion has long been recognized as one of the most expensive stumbling blocks that concern many industries and government agencies, because it is a steel destructive phenomenon that occurs due to the chemical interaction with aqueous environments and takes place at the interface between metal and electrolyte producing an electrical charge transfer or ion diffusion process. Consequently, it is experimentally possible to determine through the EIS technique the mechanism and control that kinectics of corrosion reactions encounter. First, EIS data is collected through a potentiostat/galvanostat apparatus. After, it is fitted to a mathematical model (i.e. an equivalent electrical circuit, EEC) for its interpretation and analysis, fundamentally seeking a meaningful physical interpretation. Finally, this review reports some basic aspects of the corrosion mechanism applied to steels through the experimental EIS response using Nyquist or Bode plots. Examples are given for different applied electrochemical impedance cases in which steel is under study intentionally exposed to a corrosive aqueous solution by applying a sinusoidal potential at various test conditions.",book:{id:"10054",slug:"electrochemical-impedance-spectroscopy",title:"Electrochemical Impedance Spectroscopy",fullTitle:"Electrochemical Impedance Spectroscopy"},signatures:"Héctor Herrera Hernández, Adriana M. Ruiz Reynoso, Juan C. Trinidad González, Carlos O. González Morán, José G. Miranda Hernández, Araceli Mandujano Ruiz, Jorge Morales Hernández and Ricardo Orozco Cruz",authors:[{id:"114381",title:"Dr.",name:"Jorge",middleName:null,surname:"Morales-Hernandez",slug:"jorge-morales-hernandez",fullName:"Jorge Morales-Hernandez"},{id:"215540",title:"Dr.",name:"Araceli",middleName:null,surname:"Mandujano Ruiz",slug:"araceli-mandujano-ruiz",fullName:"Araceli Mandujano Ruiz"},{id:"268773",title:"Dr.",name:"Hector",middleName:null,surname:"Herrera Hernandez",slug:"hector-herrera-hernandez",fullName:"Hector Herrera Hernandez"},{id:"268774",title:"Dr.",name:"Carlos O.",middleName:null,surname:"Gonzalez Moran",slug:"carlos-o.-gonzalez-moran",fullName:"Carlos O. Gonzalez Moran"},{id:"314695",title:"Dr.",name:"Adriana Mercedes",middleName:null,surname:"Ruiz Reynoso",slug:"adriana-mercedes-ruiz-reynoso",fullName:"Adriana Mercedes Ruiz Reynoso"}]},{id:"62242",title:"Oxygen Reduction Reaction",slug:"oxygen-reduction-reaction",totalDownloads:4028,totalCrossrefCites:8,totalDimensionsCites:18,abstract:"In this chapter, the oxygen reduction reaction (ORR), which is one of the most important reactions in energy conversion systems such as fuel cells, including its reaction kinetics, is presented. Recent developments in electrocatalysts for ORR in fuel cells, including low and non-Pt electrocatalysts, metal oxides, transition metal macrocycles and chalgogenides, are discussed. Understanding of the interdependence of size, shape and activity of the electrocatalysts is evaluated. The recent development of ORR electrocatalysts with novel nanostructures is also reported. The mechanism catalysed by these electrocatalysts is presented. Finally, the perspectives of future trends for ORR are discussed.",book:{id:"6778",slug:"electrocatalysts-for-fuel-cells-and-hydrogen-evolution-theory-to-design",title:"Electrocatalysts for Fuel Cells and Hydrogen Evolution",fullTitle:"Electrocatalysts for Fuel Cells and Hydrogen Evolution - Theory to Design"},signatures:"Lindiwe Khotseng",authors:[{id:"236596",title:"Dr.",name:"Lindiwe Eudora",middleName:null,surname:"Khotseng",slug:"lindiwe-eudora-khotseng",fullName:"Lindiwe Eudora Khotseng"}]},{id:"40709",title:"The Role of Ion Exchange Chromatography in Purification and Characterization of Molecules",slug:"the-role-of-ion-exchange-chromatography-in-purification-and-characterization-of-molecules",totalDownloads:12954,totalCrossrefCites:2,totalDimensionsCites:9,abstract:null,book:{id:"2549",slug:"ion-exchange-technologies",title:"Ion Exchange Technologies",fullTitle:"Ion Exchange Technologies"},signatures:"Hidayat Ullah Khan",authors:[{id:"140538",title:"Dr.",name:"Hidayat",middleName:null,surname:"Khan",slug:"hidayat-khan",fullName:"Hidayat Khan"}]},{id:"49055",title:"Ion Exchange Method for Removal and Separation of Noble Metal Ions",slug:"ion-exchange-method-for-removal-and-separation-of-noble-metal-ions",totalDownloads:3029,totalCrossrefCites:6,totalDimensionsCites:12,abstract:"Ion exchange has been widely applied in technology of chemical separation of noble metal ions. This is associated with dissemination of methods using various ion exchange resins which are indispensable in many fields of chemical industry. Due to small amounts of noble elements in nature and constant impoverishment of their natural raw materials, of particular importance are physicochemical methods of their recovery from the second sources e.g. worn out converters of exhausted gases, chemical catalysts, dental alloys, anodic sludges from cooper and nickiel electrorefining as well as waste waters and running off waters from refineries containing trace amount of noble metals. It should be stated that these waste materials are usually pyro- and hydrometallurgically processed. Recovery of noble metals, from such raw materials requires individual approach to each material and application of selective methods for their removal. Moreover, separation of noble metals, particularly platinum metals and gold from geological samples, industrial products, synthetic mixtures along with other elements is a problem of significant importance nowadays. In the paper the research on the applicability of different types of ion exchangers for the separation of noble metals will be presented. The effect of the different parameters on their separation will be also discussed. The examples of the removal of noble metals chlorocomplexes will also be presented in detail.",book:{id:"4599",slug:"ion-exchange-studies-and-applications",title:"Ion Exchange",fullTitle:"Ion Exchange - Studies and Applications"},signatures:"Zbigniew Hubicki, Monika Wawrzkiewicz, Grzegorz Wójcik, Dorota\nKołodyńska and Anna Wołowicz",authors:[{id:"141883",title:"Prof.",name:"Zbigniew",middleName:null,surname:"Hubicki",slug:"zbigniew-hubicki",fullName:"Zbigniew Hubicki"},{id:"173610",title:"Dr.",name:"Dorota",middleName:null,surname:"Kołodyńska",slug:"dorota-kolodynska",fullName:"Dorota Kołodyńska"}]}],onlineFirstChaptersFilter:{topicId:"505",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:140,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,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:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",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. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"July 5th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. 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). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. 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,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,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. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:20,paginationItems:[{id:"82526",title:"Deep Multiagent Reinforcement Learning Methods Addressing the Scalability Challenge",doi:"10.5772/intechopen.105627",signatures:"Theocharis Kravaris and George A. Vouros",slug:"deep-multiagent-reinforcement-learning-methods-addressing-the-scalability-challenge",totalDownloads:19,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Multi-Agent Technologies and Machine Learning",coverURL:"https://cdn.intechopen.com/books/images_new/11445.jpg",subseries:{id:"27",title:"Multi-Agent Systems"}}},{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:14,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:59,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"94311",title:"Prof.",name:"Martins",middleName:"Ochubiojo",surname:"Ochubiojo Emeje",slug:"martins-ochubiojo-emeje",fullName:"Martins Ochubiojo Emeje",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94311/images/system/94311.jpeg",biography:"Martins Emeje obtained a BPharm with distinction from Ahmadu Bello University, Nigeria, and an MPharm and Ph.D. from the University of Nigeria (UNN), where he received the best Ph.D. award and was enlisted as UNN’s “Face of Research.” He established the first nanomedicine center in Nigeria and was the pioneer head of the intellectual property and technology transfer as well as the technology innovation and support center. Prof. Emeje’s several international fellowships include the prestigious Raman fellowship. He has published more than 150 articles and patents. He is also the head of R&D at NIPRD and holds a visiting professor position at Nnamdi Azikiwe University, Nigeria. He has a postgraduate certificate in Project Management from Walden University, Minnesota, as well as a professional teaching certificate and a World Bank certification in Public Procurement. Prof. Emeje was a national chairman of academic pharmacists in Nigeria and the 2021 winner of the May & Baker Nigeria Plc–sponsored prize for professional service in research and innovation.",institutionString:"National Institute for Pharmaceutical Research and Development",institution:{name:"National Institute for Pharmaceutical Research and Development",country:{name:"Nigeria"}}},{id:"436430",title:"Associate Prof.",name:"Mesut",middleName:null,surname:"Işık",slug:"mesut-isik",fullName:"Mesut Işık",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/436430/images/19686_n.jpg",biography:null,institutionString:null,institution:{name:"Bilecik University",country:{name:"Turkey"}}},{id:"268659",title:"Ms.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/268659/images/8143_n.jpg",biography:"Dr. Zhan received his undergraduate and graduate training in the fields of preventive medicine and epidemiology and statistics at the West China University of Medical Sciences in China during 1989 to 1999. He received his post-doctoral training in oncology and cancer proteomics for two years at the Cancer Research Institute of Human Medical University in China. In 2001, he went to the University of Tennessee Health Science Center (UTHSC) in USA, where he was a post-doctoral researcher and focused on mass spectrometry and cancer proteomics. Then, he was appointed as an Assistant Professor of Neurology, UTHSC in 2005. He moved to the Cleveland Clinic in USA as a Project Scientist/Staff in 2006 where he focused on the studies of eye disease proteomics and biomarkers. He returned to UTHSC as an Assistant Professor of Neurology in the end of 2007, engaging in proteomics and biomarker studies of lung diseases and brain tumors, and initiating the studies of predictive, preventive, and personalized medicine (PPPM) in cancer. In 2010, he was promoted to Associate Professor of Neurology, UTHSC. Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. His current main research interest focuses on the studies of cancer proteomics and biomarkers, and the use of modern omics techniques and systems biology for PPPM in cancer, and on the development and use of 2DE-LC/MS for the large-scale study of human proteoforms.",institutionString:null,institution:{name:"Xiangya Hospital Central South University",country:{name:"China"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"354817",title:"Dr.",name:"Anubhab",middleName:null,surname:"Mukherjee",slug:"anubhab-mukherjee",fullName:"Anubhab Mukherjee",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y0000365PbRQAU/ProfilePicture%202022-04-15%2005%3A11%3A18.480",biography:"A former member of Laboratory of Nanomedicine, Brigham and Women’s Hospital, Harvard University, Boston, USA, Dr. Anubhab Mukherjee is an ardent votary of science who strives to make an impact in the lives of those afflicted with cancer and other chronic/acute ailments. He completed his Ph.D. from CSIR-Indian Institute of Chemical Technology, Hyderabad, India, having been skilled with RNAi, liposomal drug delivery, preclinical cell and animal studies. He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. Ltd. and heads the Hyderabad R&D center of the organization.",institutionString:"Esperer Onco Nutrition Pvt Ltd.",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a Principal Investigator and Scientist at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via machine-learning-based analyses of exosomal signatures. Dr. Paul has published in more than fifty peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals. He is currently working on the protective activity of phenolic compounds in disorders associated with oxidative stress and inflammation.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Dr.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329248",title:"Dr.",name:"Md. Faheem",middleName:null,surname:"Haider",slug:"md.-faheem-haider",fullName:"Md. Faheem Haider",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329248/images/system/329248.jpg",biography:"Dr. Md. Faheem Haider completed his BPharm in 2012 at Integral University, Lucknow, India. In 2014, he completed his MPharm with specialization in Pharmaceutics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. He received his Ph.D. degree from Jamia Hamdard University, New Delhi, India, in 2018. He was selected for the GPAT six times and his best All India Rank was 34. Currently, he is an assistant professor at Integral University. Previously he was an assistant professor at IIMT University, Meerut, India. He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/system/329795.png",biography:"Dr. Mohd Aftab Siddiqui is an assistant professor in the Faculty of Pharmacy, Integral University, Lucknow, India, where he obtained a Ph.D. in Pharmacology in 2020. He also obtained a BPharm and MPharm from the same university in 2013 and 2015, respectively. His area of research is the pharmacological screening of herbal drugs/natural products in liver cancer and cardiac diseases. He is a member of many professional bodies and has guided many MPharm and PharmD research projects. Dr. Siddiqui has many national and international publications and one German patent to his credit.",institutionString:"Integral University",institution:null}]}},subseries:{item:{id:"22",type:"subseries",title:"Applied Intelligence",keywords:"Machine Learning, Intelligence Algorithms, Data Science, Artificial Intelligence, Applications on Applied Intelligence",scope:"This field is the key in the current industrial revolution (Industry 4.0), where the new models and developments are based on the knowledge generation on applied intelligence. 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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. 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Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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