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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"288",leadTitle:null,fullTitle:"Myocarditis",title:"Myocarditis",subtitle:null,reviewType:"peer-reviewed",abstract:"Myocarditis, the inflammation of the heart muscle, could be in some cases serious and potentially fatal disease. This book is a comprehensive compilation of studies from leading international experts on various aspects of myocarditis. The first section of the book provides a clinical perspective on the disease. It contains comprehensive reviews of the causes of myocarditis, its classification, diagnosis, and treatment. It also includes reviews of Perimyocarditis; Chagas' chronic myocarditis, and myocarditis in HIV-positive patients. The second section of the book focuses on the pathogenesis of myocarditis, discussing pathways and mechanisms activated during viral infection and host immune response during myocarditis. 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Dr. Cihakova was born in the Czech Republic and received her MD and PhD from Charles University, Prague, Czech Republic. Her research focuses on the pathogenesis of autoimmune diseases. In particular, she has concentrated on studying myocarditis and dilated cardiomyopathy using a mouse model of myocarditis called experimental autoimmune myocarditis. With her colleagues, she has recently discovered that Il13 is protective in myocarditis and that IL17A drives the development of dilated cardiomyopathy. She also works on examining the role of monocyte and macrophages during myocarditis pathogenesis. 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She started as Publishing Process Manager and soon became a team supervisor. In 2012, she joined the Marketing Department where her main activities included market research and developing projects aimed at promoting publications. By the end of the same year, she was promoted to Head of Book Publishing, a position that involves coordinating editorial, commissioning, production and logistics departments. Danijela oversees the book department processes while ensuring that all goals are reached. In collaboration with the sales team, she worked on expanding the book distribution markets. Currently she is focusing on the activities and processes of the Commissioning department and working on new initiatives within. 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Metals are constantly released in aquatic systems from natural and anthropic sources such as industrial and domestic sewage discharges, mining, farming, electronic waste, anthropic accidents, navigation traffic as well as climate change events like floods (Figure 1) [1, 2]. Moreover, metals are easily dissolved in water and are subsequently absorbed by aquatic organisms such as fish and invertebrates inducing a wide range of biological effects, from being essential for living organisms to being lethal, respectively. In spite of the fact that some metals are essential at low concentrations for living organisms, such as (i) micronutrients (Cu, Zn, Fe, Mn, Co, Mo, Cr, and Se) and (ii) macronutrients (Ca, Mg, Na, P, and S); at higher concentrations, they could induce toxic effects disturbing organisms’ growth, metabolism, or reproduction with consequences to the entire trophic chain, including on humans [3]. In addition, the non-essential metals such as Pb, Cd, Ni, As, and Hg enhance the overall toxic effect on organisms even at very low concentrations. High levels of metals in the environment could be a hazard for functions of natural ecosystems and human health, due to their toxic effects, long persistence, bioaccumulative proprieties, and biomagnification in the food chain [4, 5]. In this context, metal pollution is a global problem; therefore, the international regulations demanded for water quality compliance with the quality standards both in surface water or groundwater and in biota [6–9]. Currently, in accordance with the European Water Framework Directive (EU-WFD, 2000/60/EC), the ecological status of water bodies is assessed based on five biological indicators such as phytoplankton, macrophytes, phytobenthos, benthic invertebrates, and fish alongside with chemical and hydromorphological quality elements. Due to the fact that biota has the ability to accumulate various chemicals, it has been extensively used to measure the effects of metals on aquatic organisms as an essential indicator of water quality [10]. The mollusks [11–14] and fish [3, 15] are the most used organisms as bioindicators of metal pollution in water or sediment.
\nSources of metal contamination affecting aquatic ecosystems.
The proposed topic of this chapter is based on the assessment of aquatic systems quality linked to persistent metal pollution. The chapter includes an extensive literature review concerning the impact of heavy metals on aquatic systems followed by an experimental part based on metal distribution and toxicity effect on the Romanian surface waters. Due to the European economic and strategic importance of Danube Delta, the final receptor of Danube’s flow, the toxic effect of various metal concentrations (Ni, Zn, Cu, Cd, As, Cr, Pb, Co, Ti, Zr, Fe, Mn, etc.) was analyzed.
\nUnlike organic chemicals, the majority of metals cannot be easily metabolized into less toxic compounds, a characteristic of them being the lack of biodegradability. Once introduced into the aquatic environment, metals are redistributed throughout the water column, accumulated in sediments or consumed by biota [16]. Due to desorption and remobilization processes of metals, the sediments constitute a long-term source of contamination to the food chain. Metal residues in contaminated habitats have the ability to bioaccumulate in aquatic ecosystems—aquatic flora and fauna [17], which, in turn, may enter into human food chain and result in health problems [18]. Metal accumulation in sediments occurs through processes of precipitation of certain compounds, binding fine solid particles, association with organic molecules, co-precipitation with Fe or Mn oxides or species bounded as carbonates—according to the physical and chemical conditions existing between the sediment and the associated water column [19, 20].
\n\nMetal bioavailability is defined as the fraction of the total concentration of metal which has the potential to accumulate in the body. The factors that control the bioavailability of metals (Figure 2) are the following: the organism biology (metals assimilation efficiency, feeding strategies, size or age, reproductive stage); metal geochemistry (distribution in water—sediment, suspended matters, and metal speciation) [21, 22]; physical and chemical factors (temperature, salinity, pH, ionic strength, concentration of dissolved organic carbon, total suspended solids) [23, 24].
\n\nMetal bioavailability controls their accumulation in aquatic organisms. The metals uptaken paths are through the permeable epidermis if metals are in dissolved forms or through the food ingestion if metals are in particulate forms. Metal speciation, the presence of organic or inorganic complexes, pH, temperature, salinity, and redox conditions [24] are the main factors that could modulate metal toxicity. The ingestion uptake depends on similar factors, plus the rate of feeding, intestinal transit time, and the digestion efficiency [25].
\nMany studies have shown that the free hydrated metallic ion is the most bioavailable form for Cu, Cd, Zn [26], and Pb [27], but some exceptions have been reported [28]. Thus, the importance of other chemical forms of dissolved metals and complexes formed with suitable organic ligands with low molecular weight should not be neglected. It has been found that the presence of organic binders increases the bioavailability of Cd in mussels and fish, by facilitating the diffusion of the hydrophobic compound in the lipid membrane. The organic compounds of metals could be more bioavailable than the ionic forms [29]. For instance, the organic mercurial compounds are lipid-soluble and penetrate quickly the lipid membranes, increasing the toxicity compared to mercuric chloride which is not lipid-soluble [30].
\nThe main control factors that influence metal bioavailability.
The adsorption on suspended solids affects the total concentration of metals present in water. The association between solid particles and metals is also critical for the metal uptake into organisms through food ingestion [31]. The suspended solids accumulate the insoluble metal compounds, but under certain conditions, the metal reached the interstitial water being dissolved. Heavy metal concentrations from sediments or suspended solids are much higher than in water, so a small fraction of them could be an important source for bioaccumulation in planktonic and benthic organisms [32]. The dynamics of different forms of metals in the aquatic environment is not fully understood, so new studies are required to analyze the different accumulation/bioaccumulation pathways based on dissolved or suspended metal forms.
\nOther studies highlighted that bioavailability of metals in bivalve mollusks depends on sediment particle size due to their filter feeding behavior. If the particles were coated with bacterial extracellular polymers or fulvic acids, the Cd, Zn, and Ag bioavailability was significantly increased. Overall, the binding of metal decreased the bioavailability of metals from the sediment [28, 33].
\nAfter metal ingestion, this is specifically transported by lipoproteins into different body compartments (organs, blood, or other physiological structures) where they can be specifically oriented to different centers: (i)
The heavy metal overload has inhibitory effects on the development of aquatic organisms (phytoplankton, zooplankton, and fish) [34, 35]. The metallic compounds could disturb the oxygen level and mollusks development, byssus formation, as well as reproductive processes. Several histological changes such as gill necrosis or fatty degeneration of the liver occur in the fish and crustaceans [36, 37]. Assessments at the cellular level enable to understand the action of toxic metals on the enzymatic metabolism and physiology of the aquatic organisms.
\nThe lethal effects of metals in crustaceans were induced by the inhibition of enzymes involved in cellular respiration. The histological changes observed in fish and crustaceans after chronic exposure to metals are the result of antioxidant enzymes inhibition [38–41]. The effects on organisms’ growth and development were triggered by the inhibition of enzymatic systems involved in protein synthesis and cell division. The metal type modulates the bioaccumulation level and enzymatic systems vulnerability generating a multitude of effects, toxic or not [42, 43].
\nIn order to understand the interaction mechanism between the toxic metals and the aquatic organisms and how organisms answer to metal contamination, more information on bioavailability is needed [44].
\n\nAt the present, many studies on the assessment of acute and chronic toxicity of metals mentioned the following parameters: survival, growth, development, reproduction, behavior, accumulation, effects on enzyme systems, etc. In Table 1, the values of acute (LC50) and chronic (MATC/NOEC/LOEC) toxic concentration for fish and planktonic crustaceans according to PAN Pesticide Database—Chemical Toxicity Studies on Aquatic Organisms [45] are exemplified. The studies highlighted that the toxic concentration intervals depend on the species, exposure time, age of specimens, type of toxicity test type, and laboratory conditions.
\nMetal | \nFish ( | \nCrustaceans ( | \n|
---|---|---|---|
LC50 (96 h) | \nMATC/NOEC/LOEC | \n||
1.3–10.4 mg/L | \nNOEC 50 µg/L LOEC 3.50; 13 µg/L; 1.97 mg/L | \n1 g/L | \n|
0.45–30 mg/L | \nNOEC 2.60 µg/L; 0.43; 4.20 mg/L | \n0.35–3.29 mg/L | \n|
2–240 µg/L 3–17.05 mg/L | \nNOEC 0.02–37 µg/L LOEC 6.7–440 µg/L | \n24–355.4 µg/L | \n|
0.49 mg/L ( 0.9 mg/L ( | \nLOEC 25 µg/L | \n3.8 mg/L | \n|
14.3–93 mg/L | \nNOEC 0.19–17 µg/L LOEC 25 µg/L | \n22–160 µg/L | \n|
0.44–2 mg/L | \nNOEC 0. 07; 128 µg/L LOEC 0.03–128 µg/L | \n4.4; 5.7 mg/L ( | \n|
6.2–8.3 mg/L ( | \nNOEC 6.2 mg/L | \n>1 g/L | \n|
0.1–15.61 mg/L ( | \n– | \n40 mg/L | \n
Monitoring the toxicity and accumulation of metals into the aquatic biota or sediment is mainly performed for assessing both the surface water quality and ensure food safety, respectively, as well as for the compliance with the directives. The toxicity and accumulation parameters are used for various environment monitoring programs such as wastewater discharges or various risk assessments of natural and anthropogenic events (floods or dredging activities) and also for identifying the source of metal contamination [48, 49].
\nAccording to the European document COM (2011)—876 final—2011/0429 (COD) (2012/C 229/22) amending the Directive 2000/60/EC and 2008/105/EC on priority substances in the field of water policy, new concentration limits of a number of harmful chemical compounds were allowed for the aquatic biota (fish, mollusks, or crustaceans). For instance, diphenyl brominated, fluoranthene, hexachlorobenzene, hexachlorobutadiene, benzene compounds, dicofol, perfluorooctane sulfonic acid and its derivatives, dioxins and dioxin-type compounds, cyclo-hexa-bromo-dodecane, heptachlor epoxide, and heptachlor have a concentration values in the range 6.7 × 10−3 to 167 mg/kg wet weight. The rest of the chemical compounds were not yet amended, which represents a considerable research opportunity to assess their chronic toxicity, bioaccumulation, and subsequently to set their maximum permissible concentration limits in aquatic organisms. Furthermore, the Directive 2008/105/EC of Environmental Quality Standards (EQS) entail values for various chemicals in biota.
\nMore and more studies of various organic and inorganic chemical bioaccumulation/bioconcentration in freshwater organisms revealed induced harmful effects, especially of heavy metals (Hg, As, Cd, Zn, Fe, Pb, Fe, Mn, etc.) [10, 50, 51] and metal nanoparticles [52]. Bioaccumulation remains to be an ongoing highly debated subject. According to United States Geological Survey (USGS) Toxic Substances Hydrology Program, the bioaccumulation represents “
It was observed that the mollusks from the Black Sea have shown a great tendency to accumulate in high concentration Cd and Cu from sediments as well as Cd, Ni, and Cu from water. Data showed that the highest concentrations of heavy metals were found in the digestive tract of fish [56]. Also, the fish
Metal transfer in the aquatic food chain is another interesting environmental topic for many reasons such as the accumulation of metals in aquatic organisms that could transfer up to humans, leading to a potential risk of public health through consumption of contaminated fish [58, 59]. It is known that aquatic organisms can be exposed to high or low concentrations of metals as a result of continuous or accidental release, causing long-term effects. The main uptake pathways of metals in aquatic organisms are direct through the food or sediment particles ingestion and water via epidermis and gills then they are transported inside the cells through biological membranes and ionic channels [60]. Bioconcentration and bioaccumulation of metals into the trophic chain occur if metals are excreted into the water or the contaminated organisms are food for some predator’s organisms [61, 62].
\nThe study named "
Metal concentrations such as Fe, Mn, Cu, Cr, and Pb were not amplified in the food chain (benthic fauna-fish-birds), but they were amplified for Zn and Cd. Concentrations of metals were greater at the end of the trophic chains, as follows: vegetation/detritus—terrestrial invertebrates phytophase/detritophage—terrestrial invertebrates’ predators—amphibians (Cd, Cr, Pb, and Cu in case of detritus chain and Zn in case of vegetation). The fish always accumulate metals, with some exceptions in the case of Cd, for which the transfer coefficient indicates accumulation in muscle and liver. The transfer of metals from benthic invertebrates to omnivorous fish revealed concentration of Zn and Cu in the liver and Zn in muscle. The Mn, Cr, and Cd metals transfer from omnivorous fish (muscle) to predatory fish, more specifically in their muscles and liver. At the end, the birds that are using contaminated fish as food source will accumulate Fe, Mn, Zn, Cu, and Cd in muscle and all metals (except Cr) in the liver [55].
\nSeveral monitoring studies performed by INCD ECOIND Bucharest researchers during 2003–2013 in the Danube Delta—Sfantu Gheorghe Branch (sampling points: Mahmudia, Murighiol, and Uzlina) emphasized some heavy metal concentration patterns in the study area (Table 2). The metal concentrations in water were within the limits of Romanian legislations, for class I and class II quality (according to the EU-WFD and the requirements set by the Romanian Law 310/2004 which amends the Law 17/1996). Cu and Ni showed the highest total concentration (Table 2, marked lines) among the determined metals.
\nMetal | \nMahmudia (2009–2013) | \nMurighiol (2003–2013) | \nUzlina (2003–2013) | \n|||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Min | \nMax | \nAverage | \nSD | \nMin | \nMax | \nAverage | \nSD | \nMin | \nMax | \nAverage | \nSD | \n|
<1.0 | \n24.0 | \n5.79 | \n<1.00 | \n68.1 | \n18.6 | \n<1.00 | \n10.3 | \n2.85 | \n||||
<20 | \n880 | \n270 | \n112 | \n3400 | \n750 | \n80.0 | \n1040 | \n280 | \n||||
<2.0 | \n30.0 | \n10.0 | \n3.00 | \n290 | \n80.0 | \n5.00 | \n50.0 | \n10.0 | \n||||
0.40 | \n0.40 | \n0.00 | \n<0.10 | \n0.50 | \n0.14 | \n<0.10 | \n0.50 | \n0.13 | \n||||
<0.5 | \n6.00 | \n1.74 | \n<0.50 | \n21.0 | \n6.00 | \n<0.50 | \n21.0 | \n5.33 | \n||||
2.50 | \n10.5 | \n2.67 | \n0.012 | \n55.3 | \n17.8 | \n0.03 | \n123 | \n26.7 | \n||||
<2.0 | \n3.20 | \n0.31 | \n<2.00 | \n5.00 | \n1.29 | \n<2.00 | \n5.00 | \n1.27 | \n||||
<2.0 | \n2.20 | \n0.05 | \n<2.00 | \n3.90 | \n0.88 | \n<2.00 | \n2.64 | \n0.59 | \n||||
<0.1 | \n0.24 | \n0.06 | \n<0.10 | \n0. 77 | \n0.20 | \n<0.10 | \n0.14 | \n0.10 | \n||||
<2.0 | \n24.7 | \n7.07 | \n<2.00 | \n56.0 | \n11.4 | \n<2.00 | \n57.0 | \n11.7 | \n||||
<0.5 | \n1.30 | \n0.33 | \n<0.50 | \n5.00 | \n1.65 | \n<0.50 | \n5.00 | \n1.65 | \n
The studies revealed that metals Cu, Pb, Zn, Cr, Ni, Cd, Mn, and Fe were the most abundant in the sediments of the Danube Delta—Sf. Gheorghe Branch sampling sites. The concentrations of these metals ranged with the sampling location and seasonal or natural events, as follows: Cu 4.65–194 mg/kg d.m (dry matter), Pb 4.76–51.3 mg/kg d.m., Zn 17.7–218 mg/kg d.m., Cr 7.5–61.9 mg/kg d.m., Ni 10.8–111 mg/kg d.m., Cd <0.01–1.5 mg/kg d.m. (Figure 3). The average value in the period 2009–2013 for Mn was 614.03 mg/kg d.m. and for Fe, it was 20 987 mg/kg d.m. [64, 65].
\nAlongside metal concentration, several chemical (nutrients, oxygen and pH regime, pesticides, petroleum products, polychlorinated biphenyls) and biological (phytoplankton, zooplankton, and benthic macroinvertebrates) elements were investigated, showing that the organochlorine pesticides and petroleum products exceeded the maximum allowed limits [63, 66].
\nIn addition, other studies performed along Romanian rivers showed that the mining activities had a great impact on sediment ecosystems due to metal pollution. For instance, a study performed during 2003 in Baia Mare (in North Vest of Romania) mining area after a pollution accident showed a high content of heavy metals in Somes River sediment (Cu 104–339 mg/kg, Pb 59–465 mg/kg, Zn 56–2060 mg/kg, Cd 0.05–14.14 mg/kg, CN 0.33–15.86 mg/kg). The detected concentration affected the aquatic ecosystem where the microalgae species disappeared and the number of fish species decreased dramatically compared to the period before the incident. Also many species of mollusks disappeared because their capacity to accumulate large amount of heavy metals was exceeded [67]. In addition, in Rosia Montana area (in the West part of Romania), significant water contamination with heavy metals occurred due to the mining acidic waters from area on two water courses: Rosia and Corna stream. The results showed exceedances of Cu, Cd, Fe, Ni, and Cr, in particular in the Rosia Montana water stream [68]. Along Jiu River (in south of Romania) sediments, heavy metal pollution in most sampling points was recorded according to the pollution load index (PLI) [69].
\nOccurrence of metals in sediments of Danube Delta—Sf. Gheorghe (2003–2013) (average values). S1—Mahmudia, S2—Murighiol, and S3—Uzlina [
In the above context, in the following sections will be presented some data concerning the metals effects on freshwater organisms (fish, planktonic crustacean, and mollusks), obtained through laboratory testing or by biological samples collected from contaminated fields.
\nThe assessment of metals acute and chronic effects was based on fish (
For stock solution preparation, a known quantity of metals test as NiSO4, ZnSO4, CuSO4, CdCl2/CdSO4, As2O3, K2Cr2O7, Pb(NO3)2, SbCl5, MnCl2x4H2O, TiO2, ZrCl4 was dissolved into the specified volume of dilution water or growth medium. No added solvents have been used, and all substances have been tested under their maximum solubility. The solutions were stirred for 24 h, in the dark at 25°C. The testing solutions were prepared by mixing the appropriate volumes of stock solution with dilution water or growth medium in order to obtain the final concentrations used for testing. Finally, the pH values of tested solutions were situated between 6.5 and 8.5 units.
\nUsing OECD methodologies for acute toxicity, the lethal concentrations for 50% of tested organisms were estimated. Metals’ long-term toxicities on fish were conducted using an in-house methodology based on the changes in some physiological indicators such as growth rate, mortality, biomass, production, food use and biochemical indicators, hepatic enzyme activity, respectively. Table 3 presents the technical parameters of fish toxicity tests.
\nThe toxicity test determined the metal concentration that immobilizes or kills 50% (LC50) of
The acute effect concentration values in the fish and crustacean tests were calculated using probity analysis method, based on exponential regression relationship between cumulative percentages of mortality (expressed as probity units) for each exposure period against logarithmic concentrations of test substance. For each result, standard deviations were calculated.
\nAcute toxicity tests provide a measure of toxicity for a target species under specific environmental situations and could suggest a rapid and severe effect of contaminants. Acute and chronic toxicity test mimicked the metals accidental release or long-term accumulation in sediment [67–70]. The carp fish LC50-96h values showed different responses in direct correlation with the metals type and concentration. The LC50-96h values were 0.16, 0.28, 0.31, and 0.40 mg/L for Cd, Ti, Zr, and As (Figure 4), 2.17, 12.2, 30.10, and 65.8 mg/L for Cu, Zn, Pb, and Ni (Figure 5), 120, and 758 mg/L for Cr and Sb, obtained from two replicates for each metal (Table 4).
\nTest conditions | \nOECD 203 (acute tests) | \nIn-house procedure (chronic tests) | \n
---|---|---|
Acclimatization of fish in laboratory tanks for 3 weeks | \n||
One concentration selected according to scientific literature | \nMATC estimated = LC50-96 h × 0.1 | \n|
Five concentrations in a geometric series | \nTwo concentrations (under or over the estimated MATC) | \n|
Static | \nDiscontinuous (renewal solutions at 24 h) | \n|
96 h | \n60 days | \n|
10 exemplars/test solution, 5–7 cm, 10–15 g/exemplary | \n20–30 exemplars/test solution, 12–14 cm, 25–30 g/exemplary | \n|
Romanian specialized fish farm | \n||
10 L | \n100 L | \n|
18–25°C, ≥4 mgO2/L, pH 6.5–8.5 (daily measuring), 12- to 16-h photoperiod daily. Mean of water total hardness 13 mg/L CaCO3 | \n||
Not food | \n2% from the surviving lot weight/day | \n|
All toxicity tests were carried out in the same time with a control test | \n||
Two replicates/test/metal | \n||
Inductively coupled plasma atomic emission spectrometry (ICP-OES) | \n||
Organisms mortalities and visible abnormalities (at 24, 48, 72, and 96 h) | \nGrowth instant rate, mortality rate, biomass mean, production, used food rate, and biochemical indicators—hepatic enzymes activity—GOT and GPT | \n|
Probity analysis method based on the exponential regression model between the mortality (probity units) and the log of concentrations of the metal | \nComparative analyses with the controls | \n|
Lethal concentrations for 50% of tested fish after 96 h of exposure (LC50-96 h) | \nMaximum acceptable toxicant concentration in aquatic systems (MATC) | \n
Test conditions of acute and chronic toxicity tests.
Acute and chronic toxicity of Ti, Zr, Cd, and As classified in very toxic class for
Acute and chronic toxicity of Zn, Cu, Pb, and Ni classified in toxic class for
According to Global Harmonization System for chemical classification and labeling, Cd, Ti, Zr, and As were the most toxic metals for fish. Cd, Ti, Zr, and As showed to be very toxic compared with the other analyzed metals. Research studies revealed similar acute toxicity intervals: 6.16–47.58 mg/L for Ni, 0.15–21.4 mg/L for Zn, 0.28–34.5 mg/L for Cu, 0.005–7.92 mg/L for Cd and 90 to >139 mg/L for Cr [71]. The maximum acceptable toxicant concentration (MATC) is a value calculated from chronic toxicity tests [72] in order to set water quality norms for aquatic life protection.
\nMetals | \nG.D. 351/2005a (µg/L) | \nDirective 105b (µg/L) | \nNational planc (µg/L) | \nToxicity classd | \n|||
---|---|---|---|---|---|---|---|
LC50-96h (mg/L) | \nMATC (mg/L) | \nLC50-48h (mg/L) | \n|||||
Ti (TiO2) | \n0.28 ± 0.01 | \n0.005 ± 0.001 | \n5.56 ± 0.8 | \n– | \n– | \n– | \nVery toxic—fish | \n
Zr (ZrCl4) | \n0.31 ± 0.01 | \n0.005 ± 0.002 | \n91.20 ± 10 | \n– | \n– | \n– | \nVery toxic—fish | \n
Ni (NiSO4) | \n65.8 ± 20.0 | \n0.10 ± 0.02 | \n– | \n20 | \n20 | \n4–34 | \nToxic—fish | \n
Zn (ZnSO4) | \n12.2 ± 5.0 | \n0.60 ± 0.01 | \n– | \n5 | \n– | \n11.80–73 | \nToxic—fish | \n
Cu (CuSO4) | \n2.17 ± 0.50 | \n0.05 ± 0.01 | \n– | \n100 | \n– | \n1.22–10 | \nToxic—fish | \n
Cd (CdCl2/ CdSO4) | \n0.16 ± 0.001 | \n0.001 ± 0.0005 | \n0.14 ± 0.01 | \n5 | \n0.2 | \n– | \nVery toxic—fish and daphnia | \n
As (As2O3) | \n0.40 ± 0.02 | \n0.005 ± 0.001 | \n– | \n10 | \n– | \n49 | \nVery toxic—fish | \n
Cr (K2Cr2O7) | \n120 ± 22 | \n1.00 ± 0.01 | \n0.81 ± 0.02 | \n50 | \n– | \n8.8 | \nVery toxic—daphnia | \n
Pb (Pb(NO3)2) | \n30.1 ± 5.0 | \n1.00 ± 0.02 | \n– | \n10 | \n7.2 | \n– | \nToxic—fish | \n
Sb (SbCl5) | \n758 ± 24 | \n0.060 ± 0.001 | \n148 ± 21 | \n5 | \n– | \n– | \nNon-toxic—fish and daphnia | \n
Mn (MnCl2×4H2O) | \n>53 ± 8 | \n– | \n– | \n– | \n– | \n– | \nNon-toxic—fish | \n
In-house toxicity data of metals for fish and crustacean in relation with the national and international norms for metals limits in surface water.
a Governmental Decision no. 351/2005 concerning the hazard chemical discharge.
b Directive 2008/105/EC on environmental quality standards in the field of water policy.
c National Plan of River Basin Management (2016-2021)—Annex 6.1.3B.
d According to REACH 1907/2006; Regulation (EC) 1272/2008; Regulation (EU) 286/2011; Global Harmonization System for chemical classification and labeling (GHS) Revision 2011. The toxicity class was decided on the highest toxicity of target organisms.
Experimental exposure of fish for 60 days to different concentrations of metals revealed different long-term effects. The final results showed no effects concentrations on target organisms, assessment of environmentally safe concentrations, respectively. The calculation of MATC values started by multiplication of the LC50-96h of each metal with an application factor of 0.1 (Table 2). The monitored physiological parameters from chronic test revealed that Cd is non-toxic at 0.001 mg/L, Ti, Zr, and As were safety to 0.005 mg/L, Cu at 0.05 mg/L, Sb at 0.06 mg/L, Ni at 0.10 mg/L, Zn at 0.60 mg/L, Cr and Pb at 1.00 mg/L, comparative with the controls (Figures 4 and 5, Table 4). Similar values for Cu (0.012 mg/L) and Zn (0.5 mg/L) were also obtained in other studies [73].
\nToxicity tests on
Acute toxicity of Ti, Zr, Cd, Cr, and Sb for
The surface water quality norms require specific limits only for few very toxic and toxic metals. For example, Ti, Zr, Cd, and Pb norms are not established by the National Plan of River Basin Management—Annex 6.1.3B, despite of their acute toxic effects at very low concentrations (Table 4). Also the Directive 2008/105/EC on environmental quality standards in the field of water policy sets limits only for Ni, Cd, and Pb. The present limits assure the protection of aquatic organisms, especially for fish and planktonic crustaceans.
\nIn order to assess the impact of metals in the field, the following sections present some preliminary data concerning the metal bioaccumulation into benthic invertebrates (mollusks).
\nThe studied area was focused on a highly sinuous channel, located on the southeast area of the Danube Delta (Sf. Gheorghe Branch) receiving 22% of Danube’s water flow. The Sf. Gheorghe Branch has a width varying between 150 and 550 m, and the water depth varies between 3 and 27 m. The sampling sites location was selected taking into consideration the changes in the Sf. Gheorghe Branch morphology as a result of the pressure from anthropic and environmental factors. Iron Gates I dam construction on Danube River led to a 10% decrease in the suspended sediment amount at Isaccea station. Moreover, the Iron Gates II dam building induced a 50% decrease in suspended sediment at Isaccea. These constructions alongside meander modification (during the years 1984–1988) have produced major changes in sediment distribution. The establishing of space location was performed using GPS type system map 60CSx—Garmin [74].
\nIn addition, the anthropic activities undertaken to strength the banks against coastal erosion led to meanders cutoff, which in turn caused continuous biotope degradation. These changes negatively impacted the ecosystem functions by reducing the structure of the main and constant ecological communities, the benthic invertebrates. So that, to characterize metal bioaccumulation (in benthic invertebrates), two representative sampling sites were selected considering the pressure resulted from anthropic and environmental factors (Murighiol and Uzlina)—Figure 7. At temporal scale, this study \nwas conducted during summer and autumn of 2013.
\nLocation of sampling sites in Danube Delta (Sfantu Gheorghe Branch) (St 1—Murighiol; St 2—Uzlina).
The sediment samples for both benthic invertebrates and metal analysis were collected in two replicates using a Van Veen grab, according to the following methodologies: EN ISO 5667-1:2008, ISO SR 5667-6:2009, SR ISO 5667-12:2001 and EN ISO 9391:2000. Surface sample unit was of 255 cm2, and the sampling depth was of 10 cm. The analysis of benthic invertebrates was performed according to SR EN ISO 8689-1:2003. The species identification was performed using a Motic stereomicroscope. The results were calculated taking into consideration the wet biomass.
\nThe biota samples were dried at 40°C (24 h) and crushed then about three grams of biological sample were dissolved in aqua regia (a mixture of suprapure acids HCl 30 and 65% HNO3 in the report 21–7 mL). The mixture was mineralized using a sand bath until complete dissolution. After cooling, the samples were filtered on paper filter (porosity <45 μm) in a 50-mL volumetric flask and filled with ultrapure water. The metal content in the samples was determined by inductively coupled plasma optical emission spectrometry. A calibration curve in the range of 0.1–0.5 mg/L (As, Se, Sb, Cd, Cr, Cu, Co, Fe, Mn, Mg, Ni, Pb, Zn) was performed using a Certified Reference Material solution (100 mg/L Multi Element Standard Solution, Certipur, Merck). The quality control of the data was carried out according to Quality Control Standards 21A, 100 mg/L, produced by PerkinElmer. A reagent blank in order to estimate the metal contents from acids was prepared.
\n\nThe mollusks (two bivalves’ species:
The analyzed benthic macroinvertebrates species.
This study included metal analysis results in the bivalves and gastropod shells from Murighiol and Uzlina sampling site. Other researchers [76–79] performed their studies as well using the same biological model, mollusk shells, for the metal accumulation analysis.
\nThe mollusks have the largest representation and are the most valuable groups among the benthic invertebrates’ communities due to the fact they are dominant in the total benthic community biomass and represent a basic food for the next trophic level (e.g., fish).
\nTwo types of bivalve species identified at Uzlina and Murighiol were selected for metal analysis, respectively:
Sampling point/month | \nSpecies | \nWet biomass (g) | \nDry biomass (g) | \n
---|---|---|---|
25.38 | \n24.49 | \n||
10.96 | \n0.88 | \n||
39.64 | \n35.44 | \n||
32.73 | \n30.16 | \n||
19.68 | \n18.58 | \n
Dry and wet biomass values of the selected species.
The Biota Sediment Accumulation Factor (BSAFsed) was calculated using the equation:
At Murighiol sampling site, in the
Metal | \nCb* | \nCsed* | \nCsed* | \nBSAFsed 2009–2013** | \n
---|---|---|---|---|
<0.05 | \n12.2 | \n9.61 | \n0.004 | \n|
<0.01 | \n– | \n0.50 | \n– | \n|
1.97 | \n47.0 | \n35.1 | \n0.04 | \n|
0.12 | \n27.6 | \n31.6 | \n0.004 | \n|
0.05 | \n9.41 | \n8.37 | \n0.005 | \n|
73.2 | \n– | \n14,895 | \n– | \n|
230 | \n– | \n464 | \n– | \n|
0.60 | \n35.0 | \n30.8 | \n0.02 | \n|
<0.05 | \n25.6 | \n22.3 | \n0.002 | \n|
0.44 | \n– | \n– | \n– | \n|
<0.05 | \n– | \n– | \n– | \n|
1.17 | \n91.7 | \n88.5 | \n0.01 | \n|
62.5 | \n– | \n– | \n– | \n
Metal | \nCb* | \nBSAFsed | \nCb* | \nBSAFsed | \nCsed* | \nCsed* 2009–2013** | \n
---|---|---|---|---|---|---|
<0.05 | \n0.006 | \n<0.05 | \n0.006 | \n7.75 | \n9.30 | \n|
<0.01 | \n– | \n<0.01 | \n– | \n– | \n0.51 | \n|
2.61 | \n0.05 | \n2.60 | \n0.05 | \n54.7 | \n47.0 | \n|
<0.01 | \n0.0003 | \n0.42 | \n0.01 | \n29.6 | \n29.2 | \n|
0.11 | \n0.01 | \n0.19 | \n0.02 | \n10.8 | \n9.84 | \n|
140 | \n– | \n279 | \n– | \n– | \n20987 | \n|
58.7 | \n– | \n30.0 | \n– | \n– | \n614 | \n|
0.34 | \n0.0085 | \n0.58 | \n0.015 | \n40.0 | \n39.3 | \n|
<0.05 | \n0.002 | \n0.15 | \n0.006 | \n26.7 | \n21.3 | \n|
<0.09 | \n– | \n<0.09 | \n– | \n– | \n– | \n|
<0.05 | \n– | \n<0.05 | \n– | \n– | \n– | \n|
0.90 | \n0.006 | \n3.87 | \n0.02 | \n158 | \n96.9 | \n|
154 | \n– | \n211 | \n– | \n– | \n– | \n
Concentrations of As, Cd, Cr, Fe, Pb, Se, Sb, Mg did not showed significant values in shells of analyzed benthic organisms. The metals Cu, Ni, and Zn were present in sediment over the set limits of national norms inducing their accumulation in shells. The highest values of Cu and Zn were both in
Metal concentrations showed a lower magnitude in mollusk shells than in their bodies, and this result could be explained by the fact that metals were accumulated in shell only after they were absorbed by the body. The bioaccumulation selectivity of metals in gastropod shells follows the next order: Fe > Mn > Zn > Cu > Pb > Co > Cd. Thus, the quantitative distribution of metals in mollusk shells is considered by the level of biochemical involvement, metabolic processes, their toxicity degree as well as the bioavailability to aquatic organisms [81].
\nSome studies [82] revealed that Fe belongs to metals which play an important role in body metabolism and is not toxic. The Mn, Mg, Co, Cu, Zn, and Ni are involved in growth, development, and reproduction process, but in high concentrations can show toxic effects (see the above section “
Metal | \nCb* | \nBSAFsed | \nCb* | \nBSAFsed | \nCsed* | \nCsed* 2009–2013** | \n
---|---|---|---|---|---|---|
<0.05 | \n0.007 | \n\n | 0.008 | \n6.60 | \n9.30 | \n|
<0.01 | \n– | \n<0.01 | \n– | \n– | \n0.51 | \n|
2.57 | \n0.05 | \n4.63 | \n0.09 | \n48.9 | \n47.0 | \n|
<0.01 | \n0.0004 | \n0.14 | \n0.005 | \n28.2 | \n29.2 | \n|
0.13 | \n0.01 | \n<0.01 | \n0.001 | \n9.47 | \n9.84 | \n|
153 | \n– | \n97.8 | \n– | \n– | \n20,987 | \n|
248 | \n– | \n157 | \n– | \n– | \n614 | \n|
0.29 | \n0.008 | \n0.24 | \n0.007 | \n35.6 | \n39.3 | \n|
<0.05 | \n0.002 | \n<0.05 | \n0.001 | \n30.2 | \n21.3 | \n|
<0.09 | \n– | \n<0.09 | \n– | \n– | \n– | \n|
<0.05 | \n– | \n<0.05 | \n– | \n– | \n– | \n|
0.59 | \n0.006 | \n1.27 | \n0.01 | \n91.2 | \n96.9 | \n|
42.8 | \n– | \n79.6 | \n– | \n– | \n– | \n
In this case, the highest metal concentration was recorded for Cu, Ni, and Zn. The Cu and Ni concentrations from sediment exceed the allowed limit values both in September 2013 and as well as during 2009–2013 monitoring period. As shown in Table 8, the
The bioaccumulation level varied depending on species, metals type, and sampling sites. No significant differences were observed between bioaccumulation factors of Cu, Zn, and Ni calculated for
This preliminary study for the metal bioaccumulation capacity in the shell mollusks from Danube Delta aquatic system showed that essential metals involved in metabolic processes (such as Fe, Mn, Zn, Cu, and Mg) have a greater storage capacity than those toxic (such as Pb and Cd). The statement was also confirmed in other studies [83–85].
\nAll the biota sediment bioaccumulation factors were subunitary, which indicated a slowly bioaccumulation process occurred in the studied aquatic ecosystems.
\n\nRisk characterization is required for all chemicals as an estimation of their exposure and adverse effects on the environmental compartment. Generally, this is based on Predicted Environmental Concentration (PEC) and Predicted No Effect Concentration (PNEC) calculation, in terms of exposure and assessment of effects [86].
\nIn order to estimate the current contamination of Danube surface water and sediment with metals, we use the average of the measured environmental concentrations (MEC) as PEC values, for the period 2009–2013 at Murighiol and Uzlina. The PNEC value calculation was made using an assessment factor (AF) of 1000 applied for acute toxicity values—LC50 (96 h) or 10 applied for chronic toxicity values—MATC for
Metal | \nMEC (µg/L)* | \nPNEC (µg/L) | \nRQs acute | \nRisk level | \nRQs chronic | \nRisk level | \n||||
---|---|---|---|---|---|---|---|---|---|---|
S7 | \nS8 | \nAcute (AF = 1000) | \nChronic (AF = 10) | \nS7 | \nS8 | \nS7 | \nS8 | \n|||
12.4 | \n2.60 | \n65.8 | \n10.0 | \n0.18 | \n0.03 | \nL/I | \n1.24 | \n0.26 | \nL | \n|
0.36 | \n0.37 | \n0.16 | \n0.10 | \n2.25 | \n2.31 | \nM | \n3.60 | \n3.70 | \nM | \n|
5.38 | \n3.52 | \n120 | \n100 | \n0.04 | \n0.02 | \nI | \n0.05 | \n0.04 | \nI | \n|
12.9 | \n14.5 | \n2.17 | \n5.00 | \n5.94 | \n6.68 | \nM | \n2.58 | \n2.90 | \nM | \n|
2.15 | \n2.17 | \n30.1 | \n100 | \n0.07 | \n0.07 | \nI | \n0.02 | \n0.02 | \nI | \n|
1.82 | \n1.73 | \n0.40 | \n0.50 | \n4.55 | \n4.32 | \nM | \n3.64 | \n3.46 | \nM | \n|
9.58 | \n8.15 | \n12.2 | \n60.0 | \n0.78 | \n0.66 | \nL | \n0.16 | \n0.14 | \nL | \n|
30.8 | \n39.3 | \n65.8 | \n10.0 | \n0.46 | \n0.59 | \nL | \n3.08 | \n3.93 | \nM | \n|
0.50 | \n0.51 | \n0.16 | \n0.10 | \n3.12 | \n3.18 | \nM | \n5.00 | \n5.10 | \nM | \n|
31.6 | \n29.2 | \n120 | \n100 | \n0.26 | \n0.24 | \nL | \n0.32 | \n0.29 | \nL | \n|
35.1 | \n47.0 | \n2.17 | \n5.00 | \n16.2 | \n21.7 | \nH | \n7.01 | \n9.41 | \nM | \n|
22.3 | \n21.3 | \n30.1 | \n100 | \n0.74 | \n0.70 | \nL | \n0.22 | \n0.21 | \nL | \n|
9.61 | \n9.30 | \n0.40 | \n0.50 | \n24.0 | \n23.3 | \nH | \n19.2 | \n18.6 | \nH | \n|
88.5 | \n96.9 | \n12.23 | \n60.0 | \n7.23 | \n7.92 | \nM | \n1.48 | \n1.62 | \nM | \n
Estimated acute and chronic RQs at Murighiol (S7) and Uzlina (S8) for
* Average of concentrations in period of 2009–2013; I—insignificant risk; L—low risk; M—moderate risk; H—high risk.
The results showed different levels of risk in accordance with detected environmental concentration of metals, the acute and chronic toxicity and the environmental compartment (water or sediment). In water, Cr and Pb showed insignificant risk; Ni and Zn showed a low risk; and Cd, Cu, and As highlight a moderate risk considering both acute and chronic effects on
As we expected, the risk level increases within the sediment compartment. The sediment contamination revealed low-to-moderate risk, exception for As and Cu. Therefore, Cr and Pb showed low risk; Ni, Cd, Zn and Cu highlighted moderate risk; and As and Cu could express a high risk on fish
The results highlighted a pessimistic view concerning the quality of aquatic ecosystem needed to support the carp fish survival. The concern is related to the constantly presence of metal concentrations especially in sediments (the food provider compartment) which could determinate the bioaccumulation. The same statement was made in a Romanian study named “
The topic of this chapter was based on the assessment of aquatic systems quality related to persistent metal pollution. The toxic metals are the most frequently detected pollutants in the aquatic environmental, and their effects identification are essential to protect the ecosystems integrity as well as human health. Metal pollution is a global problem; thus, the international regulations with regard to the water quality demand compliance with the quality standards in surface water, groundwater, and biota. The use of organisms (such as fish, crustacean, and mollusks) as bioindicators of metal pollution allowed us to obtain valuable information about the effects on the Romanian common species and to estimate the quality of their environment. The results from laboratory toxicity tests showed the highest concentration values that are not relevant for the detected metal concentrations into surface water, but the metals accidentally released and long-term accumulation could create similar conditions to the results of applied tests. Cd, As, Cu, Zn, Pb, Ni, Zr, and Ti have a very toxic and toxic effects for
Cd – cadmium
As – arsenium
Cu – copper
Pb – lead
Ni – nickel
Zr – zirconium
Ti – titanium
Fe – iron
Zn – zinc
Mn – manganese
Mg – magnesium
Cd – cadmium
Co – cobalt
Cr – chromium
Mo – molybdenum
Se – selenium
Na – sodium
P – phosphorus
S – sulfur
Hg – mercury
CN – cyanide
LC (EC) 50 – lethal concentrations for 50% of tested organisms after 96 or 48 h
MATC – maximum acceptable toxicant concentration in aquatic systems
NOEC – no observed effect concentration
LOEC – low observed effect concentration
GOT – glutamic oxaloacetic transaminase
GPT – glutamic pyruvic transaminase
OECD – Organization for Economic Co-operation and Development
PNEC – predicted no-effect concentration
PEC – predicted exposure concentration
MEC – measured environmental concentration
RQ – risk quotient
Cd | \ncadmium | \n
As | \narsenium | \n
Cu | \ncopper | \n
Pb | \nlead | \n
Ni | \nnickel | \n
Zr | \nzirconium | \n
Ti | \ntitanium | \n
Fe | \niron | \n
Zn | \nzinc | \n
Mn | \nmanganese | \n
Mg | \nmagnesium | \n
Cd | \ncadmium | \n
Co | \ncobalt | \n
Cr | \nchromium | \n
Mo | \nmolybdenum | \n
Se | \nselenium | \n
Na | \nsodium | \n
P | \nphosphorus | \n
S | \nsulfur | \n
Hg | \nmercury | \n
CN | \ncyanide | \n
LC (EC) 50 | \nlethal concentrations for 50% of tested organisms after 96 or 48 h | \n
MATC | \nmaximum acceptable toxicant concentration in aquatic systems | \n
NOEC | \nno observed effect concentration | \n
LOEC | \nlow observed effect concentration | \n
GOT | \nglutamic oxaloacetic transaminase | \n
GPT | \nglutamic pyruvic transaminase | \n
OECD | \nOrganization for Economic Co-operation and Development | \n
PNEC | \npredicted no-effect concentration | \n
PEC | \npredicted exposure concentration | \n
MEC | \nmeasured environmental concentration | \n
RQ | \nrisk quotient | \n
Seven century’s
These days, there are number of software have been developed to generate 3D predictive modelling (e.g., [4]), visualisation, and digital conservation through virtual reality (VR) (e.g. [5]). It can be considered as a known to unknown journey of cultural heritage. Following the London Charter of 2006 and Seville Principles of 2011 are followed to generate the 3D predictive modelling and VR for visualisation and digitally preserve the world’s cultural heritage of the Buddhist Vihara of Paharpur. The norms of digitalisation of cultural heritage have not been officially initiated by UNESCO, and ICOMOS did not ratified it by the general assembly [5]. Therefore, the London Charter of 2006 and the Seville Principle of 2011 are widely accepted to digitalise the cultural heritage, which also been followed to systematise this research.
The essence of this initiative, particularly for generating predictive 3D modelling of Paharpur Vihara or
Paharpur has been archaeologically identified as
Geodetic position of Paharpur [
The square-shaped Mahavihara can be seen in Figure 2, where every wing is 281 m in length. The Pala dynasty, notably, Dharmapala (781–821 AD), the second Pala ruler, established this
A bird’s eye view of the Paharpur (Google earth, January 2018).
The central courtyard contains various small-scale and different structures such as, at the southeast corner structures, a group of five votive stupas or
The fragments of sculptures, potsherds, ornaments, coins, seals, sealings, votive stupas salvaged are a fair number from these cultural heritage sites. From 1807, 1812, and 1879, under the reign of the British Empire, there were a couple of field explorations, and archaeological excavations were carried out by the high professional British officers, e.g., Buchanon Hamilton, Westmacott, and Sir Alexander Cunnigham [2]. They have collected so many artefacts and preserved those in Kolkata Museum in India. In addition, the Varendra Research Museum of Rajshahi preserved a couple of artefacts by Saratkumar Ray,
In 1923, a joint excavation was started by the Archaeological Survey of India, Varendra Research Society of Rajshahi, and University of Kolkata. The excavation initiated under Professor Dr. Bhandarkar of ancient history and ex-superintendent of Archaeological Survey of India. He conducted the excavation from 1925 to 1926 in the northern part of the central mound. After his archaeological activities, KN Dikshit commenced the next session from 1926 to 1927 and 1930–1932. GC Chandra conducted excavations from 1932 to 1934. After that time frame, Paharpur became a part of Pakistan, and Rafique Mughal excavated the monastic cells of the east wings. As an independent state of Bangladesh, after 1971, the Department of Archaeology began excavations in different phases, within 1981–1982, 1984–1985, 1988–1989, 1990–1991, and 2007–2008 [2].
The clay seals revealed the historical connections among Shri-Somapure-Shri-Dharmapaladeva-Mahavihariyarya-bhiksu-sangghasya. Taranatha and other Tibetan sources state that it was built by Devapala. As the Pala rulers were devout Buddhists, an inscription on the pillar found in the central shrine was inscribed with the name of Bhiksu Ajayagrabha, who was identified with the Pala Dynasty. He was a worthy successor of Devapala. The data was crosschecked with the Jagjivanpur copperplate, where the same name was found inscribed. This can be taken as proof that the monastery received continuous patronage from the Mahendrapala. Tibetan writings, especially,
The Nalanda inscription of Vipulashrimitra showed that the
In statistical analysis, predictive modelling is related to data mining, and it forecasts the probability of outcomes. This forecasting always depends on several predictors to understand the future move. It is a futuristic prediction format despite the archaeologist’s motto, which is to predict the past. Usually, an archaeological predictive model is a map, that indicates the relative potential of encountering an archaeological site. Primarily, predictive location models were attempted to locate and identify the pattern of distribution of archaeological records. In this research, the ruins of
Specific initiatives were made under this study, to save the world heritage, predict the 3D modelling, and represent the world cultural heritage by VR. It is argued that digital technology is essential to visualise the unknown past for it to be known. Technologies and techniques are getting updated daily, and archaeologists may quickly grasp these valuable techniques and tools to establish their hypothesis. It is very unusual to find in situ archaeological records. In most cases, fragmented and ruined archaeological records have been dug out. In this case, typo-technology and spatiotemporal reality have only been imagined hypothetically. The 3D modelling tools help to make this virtually real. It is virtual reality that was used to visualise the predictive 3D models of ruins of the vihara at Paharpur. This structure is well preserved and renovated by the Department of Archaeology, Ministry of Cultural Affairs, People’s Republic of Bangladesh.
The 3D models of the present can feature architectures, monuments, and artefacts, making it possible, to generate the predictive 3D models to aid in understanding the future-past. This paper has presented a proposal for arranging some 3D presentations of the structures of the cultural heritage. 3D modelling in archaeology is not a recent phenomenon. In fact, it has been practised for digital conservation systems and predictive modelling of archaeological objects and architectures in the last three decades. Some papers have been published in this regard. As author, we published a couple of research papers [4, 5] in this regard. It is submitted that this paper can be considered as one of the in-depth introductory research where a digital initiative has been made. A chapter of PhD dissertation has been completed on 3D conservation of cultural heritage site [3].
Generating 3D modelling of this paper is not the first attempt. Previously P.R. Myer in 1961 and M.A. Naqi et al. in 1999 published two papers where they tried generating 3D modelling of the central temple of Paharpur Vihar. Myer and Naqi both have imagined the ruined structure central structure as a stupa. Developed the idea by following Nalanda and Pagan stupa architecture, and Naqi et al. characterised the structure based on the Hindu temples of Eastern India and Ananda Temple of Pagan. They failed to be philosophising the structure. They tried to follow the ground plane to erect the rest of the ruins and tried to compare the style with the nearby references of the stupa.
The purpose of the 3D modelling of
The ground plan of Somapura Mahavihara, Paharpur [
2D model of
Ground plan of the central shrine of
In
Garbhadhatu mandala (
As a Structural Principles for Generating the 3D Model of Mahavihara, here the basic principles of Vastu Shastra are applied in constructing buildings, i.e., residential buildings, commercial complexes, industry layouts, towns, temples. The Vastu Mandala always follow five basic principles, which are:
As an archaeological structural reference for generating the 3D model of the central shrine of
Bronze votive stupa, Ashrafpur [
Bronze votive stupa, Shallban Vihara [
Votive stupa from Saranth [
Votive stupa from Bodhgaya [
Philosophising the Bangla regions’ Buddhism and understanding the existing vihara structure to negotiate the prediction of
To generate the Predictive 3D modelling and VR of
3D model of the front view of the resent structure of
Ware frame for generating the 3D model of the central shrine of
Long view of the 3D model of existing
Close view of the 3D model of
Mid shot of the central shrine of the
Partial close view of the central shrine of the
Top view of the 3D model of the
Going with the aforesaid logical background, the following predictive 3D model has been developed. Shown here is the ground plan to develop the structure morphologically using the
Design of corbel arch.
Partial view of predictive 3D model of the central structure of the
Partial top view of the predictive 3D model of the
Front view of the predictive 3D model of the central shrine of the
Ware frame of the central gateway of the predictive 3D model of the
Ware frame of partial view of predictive 3D model of the central shrine of the
Ware frame of the horizontal view of the predictive 3D model of the
Ware frame of the vertical view of the predictive 3D model of the
Top view of the predictive 3D model of the
Vajrayana Buddhism philosophised the yantra mandala style of vihara of Paharapur in this paper, and structurally Votive Stupas, notably, Shallbanvihar, Ashrafpur, Saranath, and Bodhgaya phenomenally characterised the superstructure of this vihara. The discovered Votive stupa belongs to the Vajrayana Buddhism. The Figures 19–26 are the logical interpretation of the Vajrayana style. Meanwhile, a question has been raised inquiring into the real necessity to regenerate these structures virtually. The answer is: yes, it is vital for a better understanding of accuracy and preservation capability. A case in point is the predictive 3D modelling of Paharpur Vihara has been generated on the idea of Yantra Mandala and the central shrine predicted on the notion of Vajrayana. Heritage sites are continuously exposed to threats such as weathering erosion and anthropogenic erosion, and especially, the problematic safeguarding mechanism [15]. Therefore, it is necessary to conserve the Paharpur Vihara or
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This has compromised the ability of the environment to foster life and render its intrinsic values. Heavy metals are known to be naturally occurring compounds, but anthropogenic activities introduce them in large quantities in different environmental compartments. This leads to the environment’s ability to foster life being reduced as human, animal, and plant health become threatened. This occurs due to bioaccumulation in the food chains as a result of the nondegradable state of the heavy metals. Remediation of heavy metals requires special attention to protect soil quality, air quality, water quality, human health, animal health, and all spheres as a collection. Developed physical and chemical heavy metal remediation technologies are demanding costs which are not feasible, time-consuming, and release additional waste to the environment. This chapter summarises the problems related to heavy metal pollution and various remediation technologies. 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Historically, species have been described and characterized on the basis of morphological criteria, which are closely linked by environmental conditions or which find their limits especially in groups where they are difficult to access, as is the case for many species of microorganisms. The need to understand the molecular mechanisms in species has made the PCR an indispensable tool for understanding the functioning of these biological systems. A number of markers are now available to detect nuclear DNA polymorphisms. In genetic diversity studies, the most frequently used markers are microsatellites. 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Primary HVAC equipment includes heating equipment, ventilation equipment, and cooling or air-conditioning equipment. Central HVAC systems locate away from buildings in a central equipment room and deliver the conditioned air by a delivery ductwork system. Central HVAC systems contain all-air, air-water, all-water systems. Two systems should be considered as central such as heating and cooling panels and water-source heat pumps. Local HVAC systems can be located inside a conditioned zone or adjacent to it and no requirement for ductwork. Local systems include local heating, local air-conditioning, local ventilation, and split systems.",book:{id:"6807",slug:"hvac-system",title:"HVAC System",fullTitle:"HVAC System"},signatures:"Shaimaa Seyam",authors:[{id:"247650",title:"M.Sc.",name:"Shaimaa",middleName:null,surname:"Seyam",slug:"shaimaa-seyam",fullName:"Shaimaa Seyam"},{id:"257733",title:"MSc.",name:"Shaimaa",middleName:null,surname:"Seyam",slug:"shaimaa-seyam",fullName:"Shaimaa Seyam"},{id:"395618",title:"Dr.",name:"Shaimaa",middleName:null,surname:"Seyam",slug:"shaimaa-seyam",fullName:"Shaimaa Seyam"}]},{id:"70315",title:"Some Basic and Key Issues of Switched-Reluctance Machine Systems",slug:"some-basic-and-key-issues-of-switched-reluctance-machine-systems",totalDownloads:1264,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Although switched-reluctance machine (SRM) possesses many structural advantages and application potential, it is rather difficult to successfully control with high performance being comparable to other machines. Many critical affairs must be properly treated to obtain the improved operating characteristics. This chapter presents the basic and key technologies of switched-reluctance machine in motor and generator operations. The contents in this chapter include: (1) structures and governing equations of SRM; (2) some commonly used SRM converters; (3) estimation of key parameters and performance evaluation of SRM drive; (4) commutation scheme, current control scheme, and speed control scheme of SRM drive; (5) some commonly used front-end converters and their operation controls for SRM drive; (6) reversible and regenerative braking operation controls for SRM drive; (7) some tuning issues for SRM drive; (8) operation control and some tuning issues of switched-reluctance generators; and (9) experimental application exploration for SRM systems—(a) wind generator and microgrid and (b) EV SRM drive.",book:{id:"8899",slug:"modelling-and-control-of-switched-reluctance-machines",title:"Modelling and Control of Switched Reluctance Machines",fullTitle:"Modelling and Control of Switched Reluctance Machines"},signatures:"Chang-Ming Liaw, Min-Ze Lu, Ping-Hong Jhou and Kuan-Yu Chou",authors:[{id:"37616",title:"Prof.",name:"Chang-Ming",middleName:null,surname:"Liaw",slug:"chang-ming-liaw",fullName:"Chang-Ming Liaw"},{id:"306461",title:"Mr.",name:"Min-Ze",middleName:null,surname:"Lu",slug:"min-ze-lu",fullName:"Min-Ze Lu"},{id:"306463",title:"Mr.",name:"Ping-Hong",middleName:null,surname:"Jhou",slug:"ping-hong-jhou",fullName:"Ping-Hong Jhou"},{id:"306464",title:"Mr.",name:"Kuan-Yu",middleName:null,surname:"Chou",slug:"kuan-yu-chou",fullName:"Kuan-Yu Chou"}]}],onlineFirstChaptersFilter:{topicId:"1",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"83066",title:"Carbon Nanomaterials Based Supercapacitors: Recent Trends",slug:"carbon-nanomaterials-based-supercapacitors-recent-trends",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.106730",abstract:"The increasing demand for renewable energy sources worldwide and the predicted depletion of current fossil fuel sources need continuous energy storage and conversion technology development. The use of supercapacitors (SC) as electrical energy storage devices in consumer electronics items and alternative power sources is an interesting and potentially lucrative area of application. Therefore, continuous developments are conducted to improve SC performance using different composites and nanocomposites. Carbon materials in SC are among the most important uses of this material. This chapter provides a short communication on recent progress in supercapacitor-based carbon materials. Various fundamental carbon allotropes were presented and debated, including fullerene, carbon nanotubes, and graphene-based supercapacitors.",book:{id:"11538",title:"Updates on Supercapacitors",coverURL:"https://cdn.intechopen.com/books/images_new/11538.jpg"},signatures:"Mohamed M. Atta and Rania M. Ahmed"},{id:"82713",title:"Fouling and Mechanism",slug:"fouling-and-mechanism",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.105878",abstract:"Fouling is the deposition of material on the heat transfer surface which reduces the film heat transfer coefficient. The impact of fouling on the heat exchanger is manifested as the reduction of thermal and hydraulic performance, in which the latter has a minor effect. This factor needs to be considered when calculating the effectiveness of the heat exchanger. During the design of heat exchangers, the fouling factor increases the required heat transfer area, which adds extra manufacturing costs. With less efficient heat exchangers, the economic cost of fouling is related to excess fuel consumption, loss of production, and maintenance or cleaning. The extra fuel consumption also damages the environment by increasing greenhouse gas production. Although much of the research work has been done on modeling and predicting fouling, it is still a poorly understood phenomenon representing the complexity of its mechanism. The common fouling mitigation action after the onset of fouling is to optimize the operating condition, e.g., increase the bulk flow velocity or decrease surface temperature. However, many quantitative and semi-empirical models have been developed to predict the fouling rate for preventive actions and optimizing cleaning schedules.",book:{id:"11161",title:"Heat Transfer",coverURL:"https://cdn.intechopen.com/books/images_new/11161.jpg"},signatures:"Obaid ur Rehman, Nor Erniza Mohammad Rozali and Marappa Gounder Ramasamy"},{id:"83057",title:"Communication Technologies and Their Contribution to Sustainable Smart Cities",slug:"communication-technologies-and-their-contribution-to-sustainable-smart-cities",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.106223",abstract:"Sustainable smart cities (SSC) are becoming a reality as many develop their unique model of smart cities based on vast communication infrastructure. New technologies led to innovative ecosystems where transportation, logistics, maintenance, etc., are automated and accessed remotely. Information and communication coordinate their overall activities. Sensors embedded in these devices sense the environment to provide the required input. Together with artificial intelligence, machine learning, and deep learning, it enables them to facilitate effective decision-making. This chapter discusses the role of integrating technologies in smart cities, focusing on the information and communication aspects, challenges, limitations, and mitigation strategies related to the infrastructure, implementations, and best practices for attaining SSC. We propose a four-layered model covering the main aspects of incorporating communication technology within sustainable smart cities. It covers the basic physical level, providing guidelines for designing a smart city that supports the requirements of a proper communications infrastructure. The level above is the network level where we describe current communication networks and technologies. The rest two upper layers represent the software with integrated and embedded communication components. In summary, we conclude that communication technology is the key enabler of most of the activities performed in smart cities.",book:{id:"11507",title:"New Generation of Sustainable Smart Cities",coverURL:"https://cdn.intechopen.com/books/images_new/11507.jpg"},signatures:"Menachem Domb"},{id:"83055",title:"Boron Clusters in Biomedical Applications: A Theoretical Viewpoint",slug:"boron-clusters-in-biomedical-applications-a-theoretical-viewpoint",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.106215",abstract:"In this chapter, we presented an analysis of the recent advances in the applications of boron clusters in biomedical fields such as the development of biosensors and drug delivery systems on the basis of quantum chemical calculations. Biosensors play an essential role in many sectors, e.g., law enforcement agencies for sensing illicit drugs, medical communities for detecting overdosed medications from human and animal bodies, etc. The drug delivery systems have theoretically been proposed for many years and subsequently implemented by experiments to deliver the drug to the targeted sites by reducing the harmful side effects significantly. Boron clusters form a rich and colorful family of atomic clusters due to their unconventional structures and bonding phenomena. Boron clusters and their complexes have various biological activities such as the drug delivery, imaging for diagnosis, treatment of cancer, and probe of protein-biomolecular interactions. For all of these reactivities, the interaction mechanisms and the corresponding energetics between biomaterials and boron clusters are of essential importance as a basic step in the understanding, and thereby design of relevant materials. During the past few years, attempts have been made to probe the nature of these interactions using quantum chemical calculations mainly with density functional theory (DFT) methods. This chapter provides a summary of the theoretical viewpoint on this issue.",book:{id:"11762",title:"Characteristics and Applications of Boron",coverURL:"https://cdn.intechopen.com/books/images_new/11762.jpg"},signatures:"Ehsan Shakerzadeh, Elham Tahmasebi, Long Van Duong and Minh Tho Nguyen"},{id:"83061",title:"Dipole Solitons in a Nonlocal Nonlinear Medium with Self-Focusing and Self-Defocusing Quintic Nonlinear Responses",slug:"dipole-solitons-in-a-nonlocal-nonlinear-medium-with-self-focusing-and-self-defocusing-quintic-nonlin",totalDownloads:0,totalDimensionsCites:0,doi:"10.5772/intechopen.106207",abstract:"Stability dynamics of dipole solitons have been numerically investigated in a nonlocal nonlinear medium with self-focusing and self-defocusing quintic nonlinearity by the squared-operator method. It has been demonstrated that solitons can stay nonlinearly stable for a wide range of each parameter, and two nonlinearly stable regions have been found for dipole solitons in the gap domain. Moreover, it has been observed that instability of dipole solitons can be improved or suppressed by modification of the potential depth and strong anisotropy coefficient.",book:{id:"10958",title:"Vortex Dynamics - From Physical to Mathematical Aspects",coverURL:"https://cdn.intechopen.com/books/images_new/10958.jpg"},signatures:"Mahmut Bağcı, Melis Turgut, Nalan Antar and İlkay Bakırtaş"},{id:"82984",title:"Feedback Linearization Control of Interleaved Boost Converter Fed by PV Array",slug:"feedback-linearization-control-of-interleaved-boost-converter-fed-by-pv-array",totalDownloads:0,totalDimensionsCites:0,doi:"10.5772/intechopen.106355",abstract:"One of the powerful methods of nonlinear control is the feedback linearization technique. This technique consists of input state and input-output linearization methods. In this chapter, the feedback linearization technique, including input state and input-output linearization methods, is described. Then, input-output linearization method is used for output voltage control of interleaved boost converter. Firstly, mathematical model of the interleaved boost converter is derived after that the method is applied. Besides, the interleaved boost converter is fed by a PV array under irradiation level and ambient temperature change. As a result of the simulation study, output voltage control of interleaved boost converter under reference voltage change is realized as desired.",book:{id:"11499",title:"Nonlinear Systems - Recent Developments and Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11499.jpg"},signatures:"Erdal Şehirli"}],onlineFirstChaptersTotal:813},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:139,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:21,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:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517",scope:"Paralleling similar advances in the medical field, astounding advances occurred in Veterinary Medicine and Science in recent decades. These advances have helped foster better support for animal health, more humane animal production, and a better understanding of the physiology of endangered species to improve the assisted reproductive technologies or the pathogenesis of certain diseases, where animals can be used as models for human diseases (like cancer, degenerative diseases or fertility), and even as a guarantee of public health. Bridging Human, Animal, and Environmental health, the holistic and integrative “One Health” concept intimately associates the developments within those fields, projecting its advancements into practice. This book series aims to tackle various animal-related medicine and sciences fields, providing thematic volumes consisting of high-quality significant research directed to researchers and postgraduates. It aims to give us a glimpse into the new accomplishments in the Veterinary Medicine and Science field. By addressing hot topics in veterinary sciences, we aim to gather authoritative texts within each issue of this series, providing in-depth overviews and analysis for graduates, academics, and practitioners and foreseeing a deeper understanding of the subject. Forthcoming texts, written and edited by experienced researchers from both industry and academia, will also discuss scientific challenges faced today in Veterinary Medicine and Science. In brief, we hope that books in this series will provide accessible references for those interested or working in this field and encourage learning in a range of different topics.",coverUrl:"https://cdn.intechopen.com/series/covers/13.jpg",latestPublicationDate:"August 7th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:11,editor:{id:"38652",title:"Prof.",name:"Rita",middleName:null,surname:"Payan-Carreira",slug:"rita-payan-carreira",fullName:"Rita Payan-Carreira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRiFPQA0/Profile_Picture_1614601496313",biography:"Rita Payan Carreira earned her Veterinary Degree from the Faculty of Veterinary Medicine in Lisbon, Portugal, in 1985. She obtained her Ph.D. in Veterinary Sciences from the University of Trás-os-Montes e Alto Douro, Portugal. After almost 32 years of teaching at the University of Trás-os-Montes and Alto Douro, she recently moved to the University of Évora, Department of Veterinary Medicine, where she teaches in the field of Animal Reproduction and Clinics. Her primary research areas include the molecular markers of the endometrial cycle and the embryo–maternal interaction, including oxidative stress and the reproductive physiology and disorders of sexual development, besides the molecular determinants of male and female fertility. She often supervises students preparing their master's or doctoral theses. She is also a frequent referee for various journals.",institutionString:null,institution:{name:"University of Évora",institutionURL:null,country:{name:"Portugal"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:7,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",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). 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Isler",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",institutionURL:null,country:{name:"Turkey"}}}]},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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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,editorialBoard:[{id:"111683",title:"Prof.",name:"Elmer P.",middleName:"P.",surname:"Dadios",slug:"elmer-p.-dadios",fullName:"Elmer P. 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