Pretreatment of rice straw had the crystallinity and the rate of saccharification
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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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\r\n\tToday, in the fields of psychology, medicine, biology, sociology, and anthropology, there is a great deal of research on the factors that are related to happiness and the effects of happiness on people's mental and physical health.
\r\n\r\n\tThis book aims to provide a comprehensive overview of this topic by exploring research, theories, biopsychosocial perspectives, and cross-cultural studies about happiness. The objectives of the project are: to analyze in-depth updates from research and clinic on how specific biological, psychological, and social factors are related to happiness, and how they develop in different contemporary cultural and anthropological contexts to further analyze their associations with mental health and, to investigate the interaction of demographic variables along different psychological and social trajectories, and thus obtain detailed information on the factors that influence the development of happiness.
\r\n\r\n\tFinally, this book aims to provide an overview to promote happiness and psychological well-being in the general population.
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The main sources of cellulose are woods, agricultural residues, hydrophytes and straws (Dieter and Thomas et al. 2003; Hon, 1996). Rice straw is a frequently abandoned crop straw in Asia and is often burned. This wastes cellulose and pollutes the air. Thus, utilizing rice straw to produce biofuel has promise. Generally, the procedure of converting rice straw into fuels is removal of the protective lignin first, followed by transformation of cellulose into glucose and at last, converting these sugars to biofuel by fermentation.
Removing lignin is critical to utilizing cellulose (Reith et al. 2003). Lignin content, crystallinity and particle size, limit the digestibility of cellulose (Hendriks and Zeeman, 2009). Therefore, various pretreatments remove or alter the hemicellulose or lignin and decrease the crystallinity of cellulose to enhance enzymatic hydrolysis efficiency (Goering, et al., 1970; Mosier et al., 2005; Zhao et al., 2009). The major methods include pretreatment by milling (Sato et al., 2009; Delgenés et al., 2002; Chang and Holtzapple, 2000; Palmowski and Muller, 1999), acid (Keikhosro K, 2006; Nguyen, Q, 2004; Ye and Jay, 2005; Taherzadeh and Karimi, 2007; Iranmahboob, F, 2002), steam explosion (Mukhopadhyay and Fangueiro, 2009; Brownell et al., 1986; Negro et al., 1992), liquid hot water (Liu and Wyman, 2005), alkali (Das and Chakraborty, 2009; Goswami et al., 2009; Fengel and Wegener, 1984; Laser et al., 2002), wet oxidation (Palonen and Thomsen, 2004; Kumar and Wyman, 2009), ammonia fiber explosion (AFEX) (Taherzadeh and Karimi, 2008; Li et al., 2009; Zheng et al., 1998; Wu et al., 1999), SO2 catalyzed steam explosion (Balint and Emma, 2010) etc. Although these common pretreatments have made great successes in recycling cellulose from lignocellulosic biomass, they are not appropriate enough for biofuel production by industrialization if considering the disadvantages of them such as low efficient, huge energy consumption, high requirements for conditions of operations, environment pollution and so on.
Recently, rice straw has been pretreated with, ionic liquid (Vitz, J. and Erdmenger, 2009), low-temperature plasma (Li and Yao, 2012), microwave-assisted dilute lye (Li and Yao, 2012). In this chapter, we concentrate upon the novel pretreatment method of rice straw based on sulfur trioxide micro-thermal explosion (STEX), the moderate conditions for the operation of this pretreatment method make it a promising technology to reduce costs and increase the utilization of lignocellulosic cellulose.
The principles of STEX can be described by the model diagram shown in Fig.1. sulfur trioxide (SO3) gas diffuses into the interior of rice straw through its capillary channels, reacts with the water in the tissue space and surface. As a result of violent exothermic process of the reaction, the gas in the limited tissue space expands and an in-situ detachment between the cellulose and the lignin will occur, moreover, lignin will be sulphonated partly during this process which may increase the solubility of the lignin in dilute lye. The operation can be performed under atmospheric pressure at about 50℃, it makes the subsequent treatment of stripping off lignin by dilute alkali solution more effectively as compared to the procedure by dilute alkali only (Yao and Hu etc. 2011).
STEX collaborative dilute alkali model diagram
Comparing to liquid, gas diffuses more quickly and deeply into interior of rice straw through its capillary channels. When SO3 gas accesses to the interior of rice straw, micro-thermo explosions take place as a result of reaction between SO3 and water remaining in the pores of the rice straw, which make great changes of the interior structure of the rice straw.
The capillary channels presence in the original straw are arranged irregularly and some of its opening have been blocked (Fig.2A). The blocked openings are not conductive to the entry of cellulose hydrolysis enzyme. After straw is treated by SO3 gas, the channels in the straw increase and are bundled, as if the internal structure of the straw are "hollowed out" (Fig.2B), which will promote the access of the substances during the subsequent handling. With increase of the STEX time, the channel structure becomes more obvious (Fig.2C). However, when the STEX time is more than 60 min, channels aggregate together and become not so obvious (Fig.2D and\n\t\t\t\t\tFig.2E). The elongated STEX time may cause the internal environment of the straw more acidic, and induces acid hydrolysis, thereby major components of the rice straw degrade and the structure of the rice straw is damaged.
The STEX for rice straw is convenient and can be performed under atmospheric pressure at about 50℃. A typical procedure of this method in the laboratory can be divided into two steps: First, 1g rice straw is cut into small pieces of about 2-3 cm in length, and hung over the upper portion of a test tube with 1mL oleum (Sulfur trioxide 50%) loading in the bottom, after raising the temperature of the system to 50℃ SO3 gas is generated and reacts with the upper straw for 5~120min. Second, the as-prepared rice straw is soaked in NaOH solution (1%, w/v) with the solid-liquid ratio of 1:10, the mixture is stirred at 90rpm with placing the reaction flask in a water bath at 50℃ for 2h, then the solids are washed with 800 mL of deionized water before the subsequent enzymatic hydrolysis procedure.
STEX undermines the structure of straw at a microscopic level that makes it conducive to the subsequent alkali stripping. In this section, the results of scanning electron microscope (SEM), X-ray diffraction (XRD), and fourier transform infrared (FTIR) spectroscopy will reveal the effects of STEX on rice straw.
The microscopic morphologies of pretreated-straws are shown in Fig.3. Regarding the untreated straw, a compact structure comprised of plant cell wall compositions such as epidermis, vascular bundles, lumens, dents and parenchyma still remains. To the rice straw treated by sulfur trioxide, the flaking traces and some holes can be observed on the straw surface (Fig.3B). As mentioned previously, gaseous sulfur trioxide can react with water in straw and release great heat in-situ at the same time. As a result, the air and water vapor in the limited interior spaces of the straw expand sharply to make a hot explosion from the interior and cause effective detachment between cellulose and lignin; it makes the subsequent removal of lignin with dilute lye more efficient. As shown in Fig.3C, vesicle shaped particles were stripped away effectively and exposures of cellulose filaments were significant after treatment of STEX treated-straw with 1% w/v NaOH for 2 hours at 50℃.
SEM of rice straw cross-sectional with the STEX, A-original straw, B-STEX 15min, C-STEX 30min, D-STEX 60min, E-STEX 120min.
SEM imagines of straw samples with different treatment. A-original straw, B-STEX treated-straw, C-STEX collaborative dilute lye treated-straw
The disruption of the vesicle structure increases with reaction time between rice straw and SO3 (Fig.4). In our experiments, when the reaction time was prolonged to 120 min, the structure of rice straw was almost completely ruptured.
The SEM images of straw with different STEX time, A-untreated, B-STEX 15min, C-STEX 30min, D-STEX 60min, and E-STEX 120min
Crystallinity of cellulose is one of the main obstacles for enzymatic hydrolysis. STEX can reduce the crystallinity of rice straw effectively especially after the assistance of subsequent dilute lye. As shown in Tab.1, the effects of sulfur trioxide collaborative dilute alkali method are remarkable on the crystallinity and saccharification rate of the rice straw comparing with the ones of untreated, sulfur trioxide-treated only, alkali-treated only methods. Although sulfur trioxide-treated method decreases the crystallinity of cellulose, it doesn\'t significantly improve cellulose hydrolysis without the collaboration of dilute alkali. This result may imply that there are more profound changes occurring on contents and chemical structures of the straw during the process of the pretreatment.
Pretreatment | Crystallinity(%) | Sugar conversion rate (%) |
(A) | 64.7±0.6 | 22.2±0.8 |
(B) | 58.5±0.3 | 41.8±0.4 |
(C) | 55.8±0.7 | 64.3±0.6 |
(D) | 51.3±0.4 | 91.7±0.4 |
Pretreatment of rice straw had the crystallinity and the rate of saccharification
Sugar conversion rate from pretreated rice straw was calculated as follows: (EQ1)
where RG is the dry-weight of reducing sugars in enzyme hydrolysis supernatant, RS is the dry-weight rice straw in pretreated solids.
Differences between the IR spectra of the untreated, sulfur trioxide-treated and sulfur trioxide collaborative dilute alkali-treated rice straws confirm changes of the rice straw occurring on the chemical level during STEX. As shown in Fig.6, the absorption bands at 3317cm-1 (O-H stretch vibration), 2919 and 2850cm-1 (C-H stretch vibration), 1630cm-1 (C=C stretch vibration) and 1037cm-1 (C=O stretch vibration) are characteristics of the original rice straw. After rice straw is treated by sulfur trioxide, new peaks at 1147cm-1 (S=O stretch vibration) and 876 cm-1(C-SO stretch vibration) appear. To the rice straw treated with sulfur trioxide collaborative dilute alkali, the peaks about 1147cm-1(S=O stretch vibration) and 876 cm-1(C-SO stretch vibration) disappear. These results indicate that lignin is sulphonated partly, then this part is been stripped on the processing with dilute lye. We suggest that not only the detachment between lignin and cellulose but also sulphonation of lignin during STEX may play an important role to the final lignin removal, which means the collaboration of dilute alkali is necessary.
X-ray diffract diagram: (A) untreated rice straw; (B), rice straw was treated for 30min at 50℃ by sulfur trioxide; (C), rice straw was treated for 7 hours at 50℃ by 1% w/v NaOH. (D), straw was treated with sulfur trioxide for 30min following 1% w/v NaOH treatment for 7 hours at 50℃
The quantities of the components of rice straw change a lot after being treated with STEX collaborative dilute alkali. Results from our work are shown in Table 2. The composition was calculated based on the dry weight of the samples and we found that water-soluble content of the STEX-treated rice straw increased. It indicates water soluble molecules such as oleoresin, lignin/hemicellulose fragments and sulphonated matter have more chances to contact water after STEX-treated. Moreover, the lignin and hemicellulose of the rice straw pretreated by STEX collaborative dilute lye decreased from 19.6% to 6.9% and 21.4% to 13.5%, respectively.
FTIR spectra: A-Untreated-straw, B-STEX treated-straw, C-STEX collaborative dilute alkali treated-straw.
Composition (%) | Untreated straw (100.0 g) | STEX treated straw (100.8 g) | STEX assist lye treated straw (73.6 g) |
Water-Soluble | 14.1 ± 0.2 | 15.9±0.4 | 8.6 ± 0.5 |
Cellulose | 39.2 ± 0.7 | 39.8±0.5 | 65.8 ± 1.0 |
Hemicellulose | 21.4 ± 0.4 | 20.4±0.6 | 13.5 ± 0.3 |
Lignin | 19.6 ± 0.8 | 18.4±0.3 | 6.9 ± 0.6 |
Ash | 5.7 ± 0.1 | 5.5±0.4 | 5.2 ± 0.3 |
Chemical composition (percent by dry weight) of rice straw
The cellulose content increased from 39.2% to 65.8%, that is predominantly attributed to the decrease of lignin and hemicellulose. Removal of lignin can reduce the binding of lignin to hemicellulose/cellulose (Han et al. 1997; Lu et al. 2002; Ahola et al. 2008; Ma et al. 2008), and more removal of hemicellulose implies that the connections between the hemicellulose and cellulose are broken and more cellulose is exposed. In summary, STEX collaborative diluted lye pretreatment will partly break the lignocellulose structure, enhance enzymatic biocatalysis, increase the desired products yield and recycle more cellulose.
Producing ethanol from lignocellulosic materials need a series of chemical and biological procedures, namely opening the bundles of lignocelluloses in order to access the polymer chains of cellulose and hemicellulose, polymers hydrolysis to achieve monomer sugar solutions, fermentation of the sugars to obtain ethanol solution (mash) by microorganisms, purification of ethanol from mash by distillation and dehydration. Figure 7 is a flow figure designed for applying the technology of STEX for producing bioethanol.
Flow diagram for bioethanol production from rice straw
The structure of untreated rice straw is nonporous and tight. The compact structure makes it difficult to moisturize the interior of rice straw and prevents from entering of the cellulase dissolved in water, which will decrease the efficiency of the enzyme hydrolysis. Hence, water retention value (WRV) of cellulose is often used to evaluate accessibility of cellulose for enzyme and we used it to evaluate the effects of the SO3 micro-thermal explosion. The straw water retention values were determined by centrifugation method. The straw was soaked in water at 25℃ for 30 min, then centrifuged at 3000rpm for 15 min. The wet straw was weighed after centrifuging and then reweighed after being dried at 90℃ for 2h, The WRV was calculated as the amount of water which retained in the rice straw after centrifuging comparing with dried weight of straw (Eq2)
The impacts of pretreatment manners to WRV and saccharification rate are shown in Fig.8. To STEX treated rice straw, WRV and saccharification rate increased with the treating time during the initial 120min, when the treatment with sulfur trioxide duration was elongated the WRV began to decline rapidly and the saccharification rate just decreased slightly (Fig.8A), we suggest that a little of carbide might form in the rice straw when time of STEX was too long and cellulose became more hydrophobic. To dilute alkali-treated method, the WRV increased during the initial 120 min and then became stable, the saccharification rate increased within initial 180min (Fig.8B). The dilute alkali-treated method removed the lignin in lignocellulosic slowly, slightly destructed the internal structure of cellulose and the off lignin lignocellulosic structure will be opened gradually so that the WRV and the saccharification rate increased. The change of the saccharification rate and WRV of the sulfur trioxide followed by alkali-treated rice straw are shown in Fig.8C, the WRV increased within initial 60min but decreased after 60min and the saccharification rate increased and became stable after 120min.
The impacts of WRV on saccharification rate by pretreatment. -▲-, saccharification rate; -●-, WRV; (A) rice straw was treated for 4 hours at 50℃ by sulfur trioxide; (B) rice straw was treated for 4 hours at 50℃ by 1% w/v NaOH; (C) straw was treated with sulfur trioxide for 4 hours followed by 1% w/v NaOH treatment for 2 hours at 50℃.
STEX for the pretreatments of cornstalk, rape straw, wheat straw had also been researched in our lab, and the STEX method exibited significant effects on the enhancement of enzyme hydrolysis of these herbs, that means STEX can act as a universal method for lignocellulosic pretreatment, and mdoderate requirements for performing STEX may improve competitiveness of the renewable energy from biomass. While there are also several aspects, which need to be researched for applying the STEX into commercial-scale application (industry), such as pretreatment equipment, clean technology in lower cost, and how to attain the utter utilization of lignocelluloses in order to manufacture high-purity cellulose. Meanwhile, the optimization of the STEX pretreatment process, clean and low-cost application of lignin black liquor and the research of high-efficiency pretreatment technology in the farmland are imminent. Commercial-scale application approach of rice straw with the STEX in the future is showed in Fig.9.
A platform of SO3/alkali processing technology to achieve each component of straw and utter utilization of biomass
Family planning is indispensable in facilitating the prosperity and autonomy of women, their families, and their communities. Contraceptive choices, maternal and newborn health care, sexually transmitted infections, and sexual health are the main concepts of reproductive health [1]. The states agreed in 2001 that among the Millennium Development Goals (MDGs), target 5b was called for by 2015 for universal access to reproductive health. Global contraceptive prevalence is 64% (41% in low-income countries) and the global unmet need for family planning is 12% (22% in low-income countries) as reported at the end of the MDGs period. Sustainable Development Goals (SDGs) targets 3.7 and 5.6 call for universal access to sexual and reproductive health care services and sexual and sexual and reproductive health and reproductive rights, respectively [2, 3].
It has been calculated that maternal mortality has been reduced globally by 30% by the increase in contraceptive use [4]. Unintended pregnancies, pregnancy spacing, and reducing high-risk pregnancies are the consequences of contraceptive use [5, 6, 7]. Current studies show that every year, contraceptive use could reduce nearly 230 million births by stopping unwanted pregnancies [8]. As a result, the use of contraception improves the health of women and their children [6, 9]. However, the prevalence of contraceptive practice varied between 11.3% and 72.1% in different countries, namely Mozambique, 11.3%, Ghana, 21.5%, Bangladesh (modern method), 54.0%, and Sweden, 72.1% [9, 10, 11, 12].
Previous research has shown that various variables are significantly associated with contraceptive use, such as maternal age, maternal and husband’s educational level, wealth status, maternal age at first marriage, and so on [11, 13]. Through the promotion of family planning, appropriate diagnostics, and interventions, the prevalence of contraceptive use is increasing. Popular statistical methods (binary logistic regression) have been applied to determine important indicators of contraceptive use among women. But the main goal is to predict contraceptive practice among women aged between 15 and 49 in Bangladesh. Machine learning is a scientific method that can build models for prediction purposes. According to the research, traditional statistical procedures were shown to be ineffective in this form of modeling. Machine learning approaches have long been shown to be more successful and promising in handling a variety of complicated and nonlinear issues [14, 15, 16].
However, not many studies have explored machine learning methods to develop predictive models for studying contraceptive methods. Therefore, various well-known machine learning algorithms were applied to predict contraceptive practices among 15–49-year-old women in Bangladesh in this study. Before prediction, we applied a Hierarchical Logistic Regression classifier in machine learning approaches that were used to select potential risk factors associated with the contraceptive practice of women. To our best knowledge, the originality of the study is that it is almost new in the field of machine learning classifier approach in the contraceptive practice of Bangladesh context, for the first time using such methods, which will assist future data scientists.
In this study, the necessary information has been extracted from a representative secondary national data set, the Bangladesh Demographic and Health Survey (BDHS), 2014. This survey was carried out through a joint effort of the National Institute of Population Research and Training (Bangladesh), Mitra Associates (Bangladesh), and ICF International (USA).
The entire list of enumeration areas (EAs) that encompasses the entire country, provided by the Bangladesh Bureau of Statistics (BBS) for the 2011 population and housing census of the People’s Republic of Bangladesh, served as the sampling frame for the 2014 BDHS. An EA was a geographical zone with an average of 120 households. The survey uses a two-stage stratified sampling process that includes information on the EA region, residence (urban or rural), and the number of residential households counted. Viable interviews were conducted in 98% of the selected households (out of 17,989 total). For this study, 17,863 ever-married women aged 15–49 years were included in the final analysis. Note that to learn more about the detailed sampling procedure of the 2014 BDHS, see the final published report of the survey [17].
Since the main purpose of this study was to predict contraception practice among women aged 15–49 years, the response variable was “current contraception use”, which was classified as “Yes or No”. If the respondent currently utilizes a contraceptive method, she falls into the “Yes” group, otherwise, she falls into the “No” group.
Besides the response variable, a set of 21 demographic and socioeconomic risk factors were included in the analysis, which was associated with contraceptive practice and considered predictor variables. Several studies found that demographic and socioeconomic characteristics such as current age, division, religion, residence, respondent’s working status, FP media exposure, age at first marriage, currently breastfeeding, wealth status, women’s education, husband’s education, child ever born, number of living children, ideal number of children, fertility preference, marital status, and decision making for using contraception are potential risk factors that determine contraception practice among women [10, 11, 18, 19, 20, 21, 22, 23, 24]. The list of independent variables and their measures are presented in Table 1.
No. | Variables | Measures |
---|---|---|
1 | Women current age (years) | 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49 |
2 | Division | Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, Sylhet |
3 | Religion | Islam, other |
4 | Sex of household head | Male, female |
5 | Residence | Urban, rural |
6 | Respondent working status | No, yes |
7 | Family planning (FP) media exposure | No, yes |
8 | Age at first marriage | <18, 18+ |
9 | Currently breastfeeding | No, yes |
10 | Currently amenorrhoeic | No, yes |
11 | Currently abstaining | No, yes |
12 | Wealth status | Poor, middle, rich |
13 | Women education | No education, primary education, secondary+ |
14 | Husband education | No education, primary education, secondary+ |
15 | Sexually transmitted infection (STI) | No, yes |
16 | Children ever born | 0–1, 2–3, 4+ |
17 | Number of living children | None, 1–2, 3+ |
18 | Ideal number of children | 0–1, 2–3, 4+ |
19 | Fertility preference | No more, have another, undecided, declared infecund, sterilized |
20 | Marital Status | Married, others |
21 | Decision making for using contraception | Respondent, others |
Description of independent variables.
The frequency distribution was used to describe the background characteristics of the respondents. In this study, we developed a Hierarchical Logistic Regression classifier in machine learning approaches that were used to select potential risk factors related to the contraceptive practice of women in Bangladesh by using the largest value of AUC (
Flow diagram for hierarchical logistic regression classifier in the machine learning process.
To meet the objective of the study, we fitted numerous numbers of model where the full model is denoted by
After selecting the final model, we applied the 7 most popular machine learning classifiers to predict contraceptive practice among ever-married women aged 15–49 in Bangladesh. In this study, we used seven different popular ML algorithms (Logistic Regression (LR), Random Forest (RF), Naïve Bayes (NB), Least Absolute Shrinkage and Selection Operation (LASSO), Classification Trees (CT), AdaBoost, and Neural Network (NN)). A detailed description of the algorithms used is available in the literature [27, 28, 29, 30, 31, 32].
The Statistical Package for Social Science (SPSS) version 25 and R version 4.0.0 software were used for data management and analysis.
Data from ever-married women aged 15–49 was used in this study. Only ever-married women aged 15–49 was considered for the final analysis based on this criterion. Then, apply data preparation methods; for example, first find out missing data from the overall dataset. It is well known that the main drawbacks of missing information in a dataset are the reduced statistical power (because it reduces the number of samples n, the estimates will have larger standard errors). The main disadvantages of missing data in a dataset are statistical power reductions, which are well-known (because it reduces the number of samples n, the estimates will have larger standard errors). There are numerous imputation methods for imputing missing values nowadays, including direct deletion, mode imputation, hot-deck imputation, and so on [33]. A lower threshold of 5% missingness has been suggested in the literature [34]. We utilized the direct deletion method because this study had a low rate of missing values, which means we removed all missing values from the data set and conducted the analysis using the entire data set. The next step after missing value processing is to normalize/standardize the variables, which is useful when the data distribution is unknown. As a result, normalization is not required for any machine learning approach, especially in categorical data. Finally, all machine learning classifiers included in this study were performed on 70% of the respondents in each group (training data set,
Flow chart of the development of the seven machine learning classifiers.
We used the following criteria to evaluate the ML algorithms’ performance: confusion matrix, receiver operating characteristic (ROC), and the area under that curve (AUC). Generally, a confusion matrix has four possible prediction outcomes, such as TR = true positives, TN = true negatives, FP = false positives, and FN = false negatives. Several performance measures, including accuracy, precision, recall, and the F1 score, are usually calculated using these four potential outcomes to assess the classifier. The ROC curves have been calculated by utilizing the predicted outcomes as well as the true outcomes. To examine the ML algorithms’ discriminating powers, the AUC of the ROC has been averaged for the test data sets [35]. Theoretically, the AUC should be between 0 and 1, with 1 being the most extreme value for an ideal classifier. Since the usual lower bound for random classification is 0.5, an AUC greater than 0.5 has at least some capacity to separate between cases and non-cases [36]. In addition to these measures, we also used Cohen’s kappa statistic, which is a better measure to examine the agreement between two raters. It is calculated by utilizing the predicted and the actual classifications in a data set. The value of Cohen’s kappa statistic is
Table 2 shows the percentage distribution of women according to the selected socio-demographic characteristics of Bangladesh. The majority of women (19%) are between the ages of 25 and 29. The majority of them (35%) are from the Dhaka division, Muslims (90%), living in male-headed households (89%), and in the rural areas (72%). In terms of working status, slightly more than two-thirds (67%) of women are not currently involved in any kind of income-generating activities, and 80% of them do not have any media exposure. The majority of women (77% of them) married before their 18th birthday, and 79% of them were not breastfeeding their children at the time of the survey. The findings also show that around 96 to 97% of women are not amenorrheic (96%) or abstaining (97%). In terms of wealth status, 42% of the women were from rich families. Approximately half of the women (46%) had secondary or higher education. The majority of the husbands (44%) had a secondary or higher level of education. The number of women who knew about sexually transmitted infections (STIs) was found to be 67%. The majority of women (46%) have had 2–3 children, while 53% have 1–2 living children. The ideal number of children was 2–3 (86%) and more than half (57%) of the women were not interested in having another child. The vast majority of women are currently married (94%), and only 9% can make the decision to use a contraception method on their own. Regarding contraception use, according to the 2014 BDHS, 58.9% of women used it.
Characteristics | Sample women | |
---|---|---|
No. | % | |
15–19 | 2029 | 11.4 |
20–24 | 3224 | 18.0 |
25–29 | 3390 | 19.0 |
30–34 | 3047 | 17.1 |
35–39 | 2315 | 13.0 |
40–44 | 2092 | 11.7 |
45–49 | 1766 | 9.9 |
Barisal | 1111 | 6.2 |
Chittagong | 3301 | 18.5 |
Dhaka | 6223 | 34.8 |
Khulna | 1838 | 10.3 |
Rajshahi | 2103 | 11.8 |
Rangpur | 2056 | 11.5 |
Sylhet | 1232 | 6.9 |
Islam | 16,096 | 90.1 |
Other | 1767 | 9.9 |
Male | 15,854 | 88.8 |
Female | 2009 | 11.2 |
Urban | 5047 | 28.3 |
Rural | 12,816 | 71.7 |
No | 11,947 | 66.9 |
Yes | 5912 | 33.1 |
No | 14,316 | 80.1 |
Yes | 3547 | 19.9 |
<18 | 13,657 | 76.5 |
18+ | 4206 | 23.5 |
No | 14,033 | 78.6 |
Yes | 3830 | 21.4 |
No | 17,054 | 95.5 |
Yes | 809 | 4.5 |
No | 17,341 | 97.1 |
Yes | 522 | 2.9 |
Poor | 6767 | 37.9 |
Middle | 3560 | 19.9 |
Rich | 7536 | 42.2 |
No education | 4455 | 24.9 |
Primary | 5209 | 29.2 |
Secondary + | 8199 | 45.9 |
No education | 5189 | 29.0 |
Primary | 4289 | 27.3 |
Secondary+ | 7795 | 43.6 |
No | 11,947 | 66.9 |
Yes | 5912 | 33.1 |
0–1 | 5670 | 31.7 |
2–3 | 8139 | 45.6 |
4+ | 4054 | 22.7 |
None | 1814 | 10.2 |
1–2 | 9478 | 53.1 |
3+ | 6571 | 36.8 |
0–1 | 1127 | 6.3 |
2–3 | 15,308 | 85.7 |
4+ | 1429 | 8.0 |
No more | 9555 | 56.7 |
Have another | 5293 | 31.4 |
Undecided | 462 | 2.7 |
Declared infecund | 561 | 3.3 |
Sterilized | 986 | 5.8 |
Married | 16,858 | 94.4 |
Others | 1005 | 5.6 |
Respondent | 1515 | 8.5 |
Others | 16,348 | 91.5.5 |
Using | 10,527 | 58.9 |
Not Using | 7336 | 41.1 |
Percentage distribution of ever- married women age between 15 and 49 by selected socio-demographic characteristics.
In the initial step of the analysis, we applied hierarchal logistic regression to select the final model. Here, each variable was considered as one model. We added a potential risk factor (variable) to the previous model that was considered a new model in this analysis (Table 3). For example, in the initial model
Model | Model |
---|---|
M1 = respondent age | M12 = M11 + wealth status |
M2 = M1 + division | M13 = M12 + women education |
M3 = M2 + religion | M14 = M13 + husband education |
M4 = M3 + Sex of household head | M15 = M14 + sexually transmitted infection (STI) |
M5 = M4 + residence | M16 = M15 + children ever born |
M6 = M5 + respondent working status | M17 = M16 + number of living children |
M7 = M6 + FP media exposure | M18 = M17 + ideal number of children |
M8 = M7 + age at first marriage | M19 = M18 + fertility preference |
M9 = M8 + currently breastfeeding | M20 = M19 + marital status |
M10 = M9 + currently amenorrhoeic | M21 = M20 + decision making for using contraception |
M11 = M10 + currently abstaining |
Create a model-based hierarchical approach.
All models were statistically significant (
Model | AUC | DeLong’s test for AUC ( | Decision | Model selection |
---|---|---|---|---|
M1 | 0.629 | −9.26 (0.000) | M2 has a significantly different AUC from M1 | M2 is selected |
M2 | 0.660 | |||
M3 | 0.662 | −2.16 (0.031) | M3 significantly different AUC from M2 | M3 is selected |
M4 | 0.713 | −16.21 (0.000) | M4 significantly different AUC from M3 | M4 is selected |
M5 | 0.714 | −2.03 (0.041) | M5 had significantly different AUC from M4 | M5 is selected |
M6 | 0.715 | −2.24 (0.025) | M6 had significantly different AUC from M5 | M6 is selected |
M7 | 0.716 | −0.61 (0.545) | M7 had not significantly different AUC from M6 | M7 is not selected |
M8 | 0.716 | −2.63 (0.008) | M8 had a significantly different AUC from M6 | M8 is selected |
M9 | 0.723 | −4.34 (0.000) | M9 had a significantly different AUC from M8 | M9 is selected |
M10 | 0.762 | −14.38 (0.000) | M10 had a significantly different AUC from M9 | M10 is selected |
M11 | 0.773 | −8.05 (0.000) | M11 had a significantly different AUC from M10 | M11 is selected |
M12 | 0.773 | −0.72 (0.472) | M12 had not a significantly different AUC from M11 | M12 is not selected |
M13 | 0.774 | −2.22 (0.029) | M13 had a significantly different AUC from M11 | M13 is selected |
M14 | 0.775 | −2.17 (0.030) | M14 had a significantly different AUC from M13 | M14 is selected |
M15 | 0.776 | −2.13 (0.033) | M15 had a significantly different AUC from M14 | M15 is selected |
M16 | 0.799 | −11.81 (0.000) | M16 had a significantly different AUC from M15 | M16 is selected |
M17 | 0.813 | −9.26 (0.000) | M17 had a significantly different AUC from M16 | M17 is selected |
M18 | 0.816 | −4.74 (0.000) | M18 had a significantly different AUC from M17 | M18 is selected |
M19 | 0.828 | −11.45 (0.000) | M19 had a significantly different AUC from M18 | M19 is selected |
M20 | 0.847 | −14.69 (0.000) | M20 had a significantly different AUC from M19 | M20 is selected |
M21 | 0.866 | −21.75 (0.000) | M21 had a significantly different AUC from M20 | M21 is selected |
Best model selection based on Delong’s test.
This study used seven different machine algorithms to classify contraceptive practices among married women both training and an experimental/test dataset. Performance parameters (such as accuracy, precision, recall, F1, specificity, and AUC value) were used to compare the predictive performance of these algorithms. In addition, Cohen Kappa’s statistical information was used to determine the discriminant accuracy of the algorithm. The prediction results with performance parameters for each algorithm are shown in Table 5 and Figure 3.
Model name | Accuracy (95% CI) | Cohen’s kappa | Precession | Recall | F1 | AUC | Specificity |
---|---|---|---|---|---|---|---|
LR | 78.52 (77.39, 79.61) | 0.5559 | 81.23 | 82.39 | 81.81 | 86.57 | 73.03 |
RF | 77.57 (76.43, 78.68) | 0.5288 | 78.32 | 85.35 | 81.69 | 84.07 | 66.53 |
NB | 76.56 (75.40, 77.69) | 0.4995 | 75.73 | 88.32 | 81.54 | 84.17 | 59.90 |
LASSO | 79.08 (77.96, 80.16) | 0.5601 | 79.39 | 86.85 | 82.96 | 86.59 | 68.06 |
CT | 78.57 (77.45, 79.67) | 0.5464 | 78.16 | 88.06 | 82.81 | 85.59 | 65.13 |
AdaBoost | 78.50 (77.37, 79.59) | 0.5523 | 80.20 | 84.08 | 82.10 | 86.15 | 70.59 |
NN | 79.34 (78.23, 80.42) | 0.5626 | 78.71 | 88.76 | 83.44 | 86.90 | 65.99 |
Performance evaluation for seven ML algorithms (test data set).
Area under curve of all seven machine learning classifiers.
Table 5 shows that the logistic regression classifier has an accuracy of 78.52%. The precision and recall of the fitted model were 81.23% and 82.39%, respectively, while the F1 score was 81.81%. The area under the curve (AUC) was calculated to be 86.57%. The prediction performance result of a random forest was displayed with an accuracy of 77.57%. Here, the precision, recall, and F1 score of the random forest classifier were 73.82%, 85.35%, and 81.99%, respectively. The AUC, in this case, was 84.07%. The final accuracy of the naïve Bayes classifier was 76.56%, with a precision of 75.73% and a recall of 88.32%. The F1 score and the AUC value, in this case, were 81.54% and 84.17%, respectively. Using Least Absolute Shrinkage and Selection Operator (LASSO) analysis, the accuracy in the test data set was seen as 79.08% with precession and recall of 79.39% and 86.85% respectively, and the F1 score was 82.96%. According to the test observation results, the classification tree method showed 78.57% accuracy in predicting contraceptive practice among married women, with a precession of 78.16%, a recall of 88.06%, an F1 score of 82.81%, and an AUC value of 85.59%. For AdaBoost, these values are 78.05% (accuracy), 80.20% (precession), 84.88% (recall), 82.10% (F1 score) and 86.15% (AUC). Finally, we used an artificial neural network and obtained an accuracy of 79.34%. Here, other parameters such as precession, recall, F1 score, and AUC are 78.71%, 88.76%, 83.44%, and 86.90% respectively. Among the seven classifiers, we obtained the best performance from NN in terms of both accuracy and AUC. Cohen’s kappa value is 0.5626.
This violin plot shows the relationship of seven classifiers to accuracy. The shaded areas detail the distribution of the data in each classifier. Figure 4 shows that NN provided the highest mean accuracy, followed by LASSO and AdaBoost. Unlike the boxplot, the entire distribution of the 10-fold accuracy can be visualized in this violin plot (Figure 4).
Violin plots of the 10-fold cross-validation.
This is the very first study that uses a hierarchical logistic classifier in a machine learning approach. Then the predictive performance of the hierarchical logistic classifier was compared with the other six machine learning algorithms’ predictive power. In this study, the use of contraception among ever-married women in Bangladesh has been predicted using sociodemographic factors. This study can provide policymakers and academics with a starting point to examine key outlines in a larger framework and raise noteworthy interventions.
The study found that the prevalence of contraception was almost 59% in Bangladesh. The prevalence rate of contraceptives in India is 54%, while the rates were 47%, 34%, and 65%, respectively, for Nepal, Pakistan, and Sri Lanka [37, 38]. As the government of Bangladesh is committed to the London Summit on Family Planning to improve contraceptive access and use among impoverished people in both urban and rural areas [39], the findings of this study will provide grounding direction for the increase in the prevalence of contraception.
In this study, we used hierarchical LR, RF, NB, LASSO, CT, AdaBoost, and NN machine learning techniques to predict contraceptive practice among ever-married women in Bangladesh. The current analysis was to evaluate which performed better based on the accurate prediction rate of contraceptive use for 2014, BDHS data sets. Moreover, there was no evidence of scientific study that used a hierarchical logistic classifier and several supervised learning. In this study, 70% of the respondents were used for model tuning purposes, and the remaining 30% were used to check model performance, for the model tuning was performed using 10-fold cross-validation on the training dataset. The researcher observed that cross-validation is most commonly used to evaluate model performance [40]. The prediction of contraceptive use was measured by performance parameters (such as accuracy, precision, recall, F1, and AUC value) compared to the performance of seven different machine learning classifiers in this analysis. Cohen’s kappa, the proportion of predicted to actual classification in the dataset, is used to assimilate model perfection. Among the used models, the Neural Network outperformed other models with an accuracy of 79.34%. Additionally, in terms of Cohen kappa, the result of this analysis also highlighted that the Neural Network provides the best predictive performance (Cohen’s
In this paper, we investigate the hierarchical logistic regression classifier in machine learning approaches to identify potential risk factors related to contraceptive practices of women in Bangladesh. In summary, we conclude that all of the selected covariates were significant determinants for contraceptive practice except FP Mass media exposure and wealth status according to the hierarchical logistic regression classifier in machine learning approaches based on the Delong test. Here, we compared seven supervised machine learning algorithms to predict contraceptive practice among ever-married women aged between 15 and 49 years in Bangladesh. The NN model has exhibited the best results based on the performance parameters, having demonstrated an accuracy of 79.34%, a precision of 78.71%, a recall of 88.76%, an F1 score of 83.44%, and an AUC value of 86.90. Among the seven algorithms, the NN model performs the best in terms of accuracy, Cohen’s kappa statistic, and area under the curve (AUC). This study recommends the use of the NN model and policymakers should pay attention to continuing this study in the future.
A special thank goes to the Demographic Health Surveys for enabling us to use Bangladesh Demographic Health Survey data for our study from https://dhsprogram.com/data/.
The authors declare that they are not competing of interest.
This study did not receive funding.
This study was analyzed using secondary data, which were available at “https://dhsprogram.com/data/”.
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Yildirim",coverURL:"https://cdn.intechopen.com/books/images_new/10989.jpg",editedByType:"Edited by",editors:[{id:"140612",title:"Prof.",name:"Metin",middleName:null,surname:"Turan",slug:"metin-turan",fullName:"Metin Turan"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10360",title:"Nitrogen in Agriculture",subtitle:"Physiological, Agricultural and Ecological Aspects",isOpenForSubmission:!1,hash:"5fc080ff8941417e9eeaf0ced2b5523a",slug:"nitrogen-in-agriculture-physiological-agricultural-and-ecological-aspects",bookSignature:"Takuji Ohyama and Kazuyuki Inubushi",coverURL:"https://cdn.intechopen.com/books/images_new/10360.jpg",editedByType:"Edited by",editors:[{id:"30061",title:"Prof.",name:"Takuji",middleName:null,surname:"Ohyama",slug:"takuji-ohyama",fullName:"Takuji Ohyama"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8533",title:"Pesticides",subtitle:"Use and Misuse and Their Impact in the Environment",isOpenForSubmission:!1,hash:"420a19fa07c8510eeb08decebed430cc",slug:"pesticides-use-and-misuse-and-their-impact-in-the-environment",bookSignature:"Marcelo Larramendy and Sonia Soloneski",coverURL:"https://cdn.intechopen.com/books/images_new/8533.jpg",editedByType:"Edited by",editors:[{id:"14764",title:"Dr.",name:"Marcelo L.",middleName:null,surname:"Larramendy",slug:"marcelo-l.-larramendy",fullName:"Marcelo L. Larramendy"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4637",title:"Toxicity and Hazard of Agrochemicals",subtitle:null,isOpenForSubmission:!1,hash:"6aff74df1ea32df7f1e20e29c8363ff5",slug:"toxicity-and-hazard-of-agrochemicals",bookSignature:"Marcelo L. Larramendy and Sonia Soloneski",coverURL:"https://cdn.intechopen.com/books/images_new/4637.jpg",editedByType:"Edited by",editors:[{id:"14764",title:"Dr.",name:"Marcelo L.",middleName:null,surname:"Larramendy",slug:"marcelo-l.-larramendy",fullName:"Marcelo L. Larramendy"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:4,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"64602",doi:"10.5772/intechopen.82418",title:"Environmental Risk of Groundwater Pollution by Pesticide Leaching through the Soil Profile",slug:"environmental-risk-of-groundwater-pollution-by-pesticide-leaching-through-the-soil-profile",totalDownloads:3098,totalCrossrefCites:25,totalDimensionsCites:69,abstract:"Adsorption, degradation, and movement are the key processes conditioning the behavior and fate of pesticides in the soil. Six processes that can move pesticides are leaching, diffusion, volatilization, erosion and run-off, assimilation by microorganisms, and plant uptake. Leaching is the vertical downward displacement of pesticides through the soil profile and the unsaturated zone, and finally to groundwater, which is vulnerable to pollution. Pesticides are frequently leached through the soil by the effect of rain or irrigation water. Pesticide leaching is highest for weakly sorbing and/or persistent compounds, climates with high precipitation and low temperatures, and soils with low organic matter and sandy texture. On the contrary, for pesticides with a low persistence that disappear quickly, the risk of groundwater pollution considerably decreases. Different and varied factors such as physical-chemical properties of the pesticide, a permeability of the soil, texture and organic matter content of the soil, volatilization, crop-root uptake, and method and dose of pesticide application are responsible for the leaching rate of the pesticides. Soils that are high in clays and organic matter will slow the movement of water, attach easily to many pesticides, and generally have a higher diversity and population of soil organisms that can metabolize the pesticides.",book:{id:"8533",slug:"pesticides-use-and-misuse-and-their-impact-in-the-environment",title:"Pesticides",fullTitle:"Pesticides - Use and Misuse and Their Impact in the Environment"},signatures:"Gabriel Pérez-Lucas, Nuria Vela, Abderrazak El Aatik and Simón Navarro",authors:[{id:"202983",title:"Dr.",name:"Simón",middleName:null,surname:"Navarro",slug:"simon-navarro",fullName:"Simón Navarro"},{id:"202988",title:"Dr.",name:"Nuria",middleName:null,surname:"Vela",slug:"nuria-vela",fullName:"Nuria Vela"},{id:"206059",title:"Dr.",name:"Gabriel",middleName:null,surname:"Pérez-Lucas",slug:"gabriel-perez-lucas",fullName:"Gabriel Pérez-Lucas"},{id:"283154",title:"Mr.",name:"Abderrazak",middleName:null,surname:"El Aatik",slug:"abderrazak-el-aatik",fullName:"Abderrazak El Aatik"}]},{id:"48594",doi:"10.5772/60911",title:"Environmental Exposure and Health Effects Associated with Malathion Toxicity",slug:"environmental-exposure-and-health-effects-associated-with-malathion-toxicity",totalDownloads:2726,totalCrossrefCites:18,totalDimensionsCites:35,abstract:"Malathion (O,O-dimethyl-S-1,2-bis ethoxy carbonyl ethyl phosphorodithionate) is a non-systemic, wide-spectrum pesticide. It is widely used throughout the world for agricultural, residential, and public health purposes, mainly to enhance food production and to provide protection from disease vectors. Malathion preference over other organophosphate pesticides relates to its low persistence in the environment as it is highly susceptible to hydrolysis, photolysis, and biodegradation. However, numerous malathion poisoning incidents including acute and chronic cases have been reported among pesticide workers and small children through accidental exposure. Malathion toxicity is compounded by its reactive metabolites and also depends upon the product purity, route of exposure, nutritional status, and gender of exposed individuals. Its metabolic oxidation in mammals, insects, and plants leads to the formation of malaoxon which appears to be several times more acutely toxic and represents the primary cause of malathion’s toxicity. Depending on the level of exposure, several signs and symptoms of toxicity including numbness, tingling sensation, headache, dizziness, difficulty breathing, weakness, irritation of skin, exacerbation of asthma, abdominal cramps, and death have been reported. Similar to other organophosphate pesticides, malathion exerts it toxic action by binding to acetylcholinesterase enzyme and inhibiting its activity, leading to accumulation of acetylcholine in synaptic junctions, which in turn results in overstimulation of cholinergic, muscarinic, and nicotinic receptors, and subsequent induction of adverse biologic effects. This chapter provides an update and analysis of the production and use, environmental occurrence, molecular mechanisms of toxicity, genotoxicity and carcinogenicity, and adverse human health effects associated with malathion exposure.",book:{id:"4637",slug:"toxicity-and-hazard-of-agrochemicals",title:"Toxicity and Hazard of Agrochemicals",fullTitle:"Toxicity and Hazard of Agrochemicals"},signatures:"Paul B. Tchounwou, Anita K. Patlolla, Clement G. Yedjou and\nPamela D. Moore",authors:[{id:"113353",title:"Prof.",name:"Paul",middleName:null,surname:"Tchounwou",slug:"paul-tchounwou",fullName:"Paul Tchounwou"}]},{id:"48553",doi:"10.5772/60767",title:"Ecotoxicology of Glyphosate and Glyphosate-Based Herbicides — Toxicity to Wildlife and Humans",slug:"ecotoxicology-of-glyphosate-and-glyphosate-based-herbicides-toxicity-to-wildlife-and-humans",totalDownloads:2609,totalCrossrefCites:10,totalDimensionsCites:20,abstract:"The use of agrochemicals, especially herbicides, is necessary to control pests in order to produce adequate food for the global population (estimated at 7 billion). Glyphosate and glyphosate-based herbicides have been used extensively for this purpose but recent studies have reported these chemical substances to be found in aquatic ecosystems, wildlife and humans in various quantities. In this chapter, we reviewed the impacts of glyphosate and glyphosate-based herbicides on wildlife and humans using measured endpoint effects caused by genotoxicity, cytotoxicity and reproductive toxicity. We used findings from different current investigations to demonstrate adverse effects, or otherwise, of glyphosate exposure to wildlife and humans. Our review reveals that glyphosate and its formulations may not only be considered as having genotoxic, cytotoxic or endocrine disrupting properties but they may also be causative agents of reproduction abnormalities in both wildlife and humans. Furthermore, the extensive use of glyphosate-based herbicides in genetically modified glyphosate-resistant plants grown for food and feed should be of grave concern since they can be sources of genotoxicity, cytotoxicity, and reproductive toxicity in wildlife and humans.",book:{id:"4637",slug:"toxicity-and-hazard-of-agrochemicals",title:"Toxicity and Hazard of Agrochemicals",fullTitle:"Toxicity and Hazard of Agrochemicals"},signatures:"Paul K. Mensah, Carolyn G. Palmer and Oghenekaro N. Odume",authors:[{id:"169135",title:"Dr.",name:"Paul",middleName:null,surname:"Mensah",slug:"paul-mensah",fullName:"Paul Mensah"},{id:"173888",title:"Prof.",name:"Carolyn",middleName:null,surname:"Palmer",slug:"carolyn-palmer",fullName:"Carolyn Palmer"},{id:"175580",title:"Dr.",name:"Oghenekaro Nelson",middleName:null,surname:"Odume",slug:"oghenekaro-nelson-odume",fullName:"Oghenekaro Nelson Odume"}]},{id:"65766",doi:"10.5772/intechopen.84161",title:"Pesticides, Anthropogenic Activities, and the Health of Our Environment Safety",slug:"pesticides-anthropogenic-activities-and-the-health-of-our-environment-safety",totalDownloads:1464,totalCrossrefCites:7,totalDimensionsCites:16,abstract:"Mankind depends on agricultural products for food consumption. Increasing population (more than 7 billion) requires significant growth in crop yield to meet essential demand. This aim was achieved through the use of pesticides to protect crops from diseases. Pesticides are toxic by design for organisms that can threaten food products. Their mode of action is by targeting systems or enzymes in the pests that may be similar to human system and therefore pose risks to human health and the environment as well. The WHO recommended classifying pesticides according to their toxicity and chemicals according to their chronic health and environmental hazards.",book:{id:"8533",slug:"pesticides-use-and-misuse-and-their-impact-in-the-environment",title:"Pesticides",fullTitle:"Pesticides - Use and Misuse and Their Impact in the Environment"},signatures:"Mona Saud AL-Ahmadi",authors:[{id:"276726",title:"Ph.D.",name:"Mona",middleName:null,surname:"AL-Ahmadi",slug:"mona-al-ahmadi",fullName:"Mona AL-Ahmadi"}]},{id:"48545",doi:"10.5772/60739",title:"Environmental Risk Assessment of Agrochemicals — A Critical Appraisal of Current Approaches",slug:"environmental-risk-assessment-of-agrochemicals-a-critical-appraisal-of-current-approaches",totalDownloads:2594,totalCrossrefCites:9,totalDimensionsCites:14,abstract:"This chapter provides insights into the difficulties and challenges of performing risk evaluations of agrochemicals. It is a critical review of the current methodologies used in ecological risk assessment of these chemicals, not their risks to humans. After an introduction to the topic, the current framework for ecological risk assessment is outlined. Two types of assessments are typically carried out depending on the purpose: i) regulatory assessments for registration of a chemical product; and ii) ecological assessments, for the protection of both terrestrial and aquatic ecosystems, which are usually site-specific. Although the general framework is well established, the methodologies used in each of the steps of the assessment are fraught with a number of shortcomings. Notwithstanding the subjectivity implicit in the evaluation of risks, there is scepticism in scientific circles about the appropriateness of the current methodologies because, after so many years of evaluations, we are still incapable of foreseeing the negative consequences that some agrochemicals have in the environment. A critical appraisal of such methodologies is imperative if we are to improve the current assessment process and fix the problems we face today. The chapter reviews first the toxicity assessment methods, pointing to the gaps in knowledge about this essential part of the process and suggesting avenues for further improvement. Deficiencies in the current regulations regarding toxicity testing are discussed, in particular the effect of the time factor on toxicity and the issue of complex mixtures. Other matters of concern are the extrapolation of toxicity data from the individual to the population and community levels, and the sub-lethal effects. The exposure assessment methods are dealt with in a second place. These rely on modelling and actual measurements of chemical residues in the environment. Various techniques employed to determine to exposure and bioavailability of agrochemicals to the various organisms in both aquatic and terrestrial ecosystems are reviewed. Again, the shortcomings and gaps in knowledge are addressed and suggestions for improvement are pointed out. Then, the process of putting together the information from the toxicity and exposure assessments to evaluate risks is discussed. Tiers I and II of the risk assessment are reviewed. The challenge here is to keep objectivity in the evaluations; this may require the introduction of new methods of risk assessment. Finally, the risk assessment implies establishing a management strategy that aims at reducing or minimising the impacts of agrochemicals under normal agricultural scenarios. Recommendations are often case-specific and need to be based on sound science as well as common sense principles. The chapter concludes with a summary of issues that need to be considered for improving risk assessments of agrochemicals.",book:{id:"4637",slug:"toxicity-and-hazard-of-agrochemicals",title:"Toxicity and Hazard of Agrochemicals",fullTitle:"Toxicity and Hazard of Agrochemicals"},signatures:"Francisco Sánchez-Bayo and Henk A. Tennekes",authors:[{id:"74970",title:"Dr.",name:"Francisco",middleName:null,surname:"Sánchez-Bayo",slug:"francisco-sanchez-bayo",fullName:"Francisco Sánchez-Bayo"},{id:"173845",title:"Dr.",name:"Henk",middleName:null,surname:"Tennekes",slug:"henk-tennekes",fullName:"Henk Tennekes"}]}],mostDownloadedChaptersLast30Days:[{id:"78542",title:"Mitigation of Climate Change by Nitrogen Managements in Agriculture",slug:"mitigation-of-climate-change-by-nitrogen-managements-in-agriculture",totalDownloads:304,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Soil is one of the important sources of nitrous oxide (N2O), which is generally producing through soil microbial processes, such as nitrification and denitrification. Agricultural soils receive chemical and organic fertilizers to maintain or increase crop yield and soil fertility, but several factors are influencing N2O emissions, such as types and conditions of soil and fertilizer, and rate, form, and timing of application. Mitigation of N2O is a challenging topic for future earth by using inhibitors, controlled-release fertilizers, and other amendments, but the cost and side effects should be considered for feasibility.",book:{id:"10360",slug:"nitrogen-in-agriculture-physiological-agricultural-and-ecological-aspects",title:"Nitrogen in Agriculture",fullTitle:"Nitrogen in Agriculture - Physiological, Agricultural and Ecological Aspects"},signatures:"Kazuyuki Inubushi and Miwa Yashima",authors:[{id:"108366",title:"Dr.",name:"Kazuyuki",middleName:null,surname:"Inubushi",slug:"kazuyuki-inubushi",fullName:"Kazuyuki Inubushi"},{id:"429712",title:"Dr.",name:"Miwa",middleName:null,surname:"Yashima",slug:"miwa-yashima",fullName:"Miwa Yashima"}]},{id:"48594",title:"Environmental Exposure and Health Effects Associated with Malathion Toxicity",slug:"environmental-exposure-and-health-effects-associated-with-malathion-toxicity",totalDownloads:2723,totalCrossrefCites:18,totalDimensionsCites:35,abstract:"Malathion (O,O-dimethyl-S-1,2-bis ethoxy carbonyl ethyl phosphorodithionate) is a non-systemic, wide-spectrum pesticide. It is widely used throughout the world for agricultural, residential, and public health purposes, mainly to enhance food production and to provide protection from disease vectors. Malathion preference over other organophosphate pesticides relates to its low persistence in the environment as it is highly susceptible to hydrolysis, photolysis, and biodegradation. However, numerous malathion poisoning incidents including acute and chronic cases have been reported among pesticide workers and small children through accidental exposure. Malathion toxicity is compounded by its reactive metabolites and also depends upon the product purity, route of exposure, nutritional status, and gender of exposed individuals. Its metabolic oxidation in mammals, insects, and plants leads to the formation of malaoxon which appears to be several times more acutely toxic and represents the primary cause of malathion’s toxicity. Depending on the level of exposure, several signs and symptoms of toxicity including numbness, tingling sensation, headache, dizziness, difficulty breathing, weakness, irritation of skin, exacerbation of asthma, abdominal cramps, and death have been reported. Similar to other organophosphate pesticides, malathion exerts it toxic action by binding to acetylcholinesterase enzyme and inhibiting its activity, leading to accumulation of acetylcholine in synaptic junctions, which in turn results in overstimulation of cholinergic, muscarinic, and nicotinic receptors, and subsequent induction of adverse biologic effects. This chapter provides an update and analysis of the production and use, environmental occurrence, molecular mechanisms of toxicity, genotoxicity and carcinogenicity, and adverse human health effects associated with malathion exposure.",book:{id:"4637",slug:"toxicity-and-hazard-of-agrochemicals",title:"Toxicity and Hazard of Agrochemicals",fullTitle:"Toxicity and Hazard of Agrochemicals"},signatures:"Paul B. Tchounwou, Anita K. Patlolla, Clement G. Yedjou and\nPamela D. Moore",authors:[{id:"113353",title:"Prof.",name:"Paul",middleName:null,surname:"Tchounwou",slug:"paul-tchounwou",fullName:"Paul Tchounwou"}]},{id:"64602",title:"Environmental Risk of Groundwater Pollution by Pesticide Leaching through the Soil Profile",slug:"environmental-risk-of-groundwater-pollution-by-pesticide-leaching-through-the-soil-profile",totalDownloads:3095,totalCrossrefCites:25,totalDimensionsCites:69,abstract:"Adsorption, degradation, and movement are the key processes conditioning the behavior and fate of pesticides in the soil. Six processes that can move pesticides are leaching, diffusion, volatilization, erosion and run-off, assimilation by microorganisms, and plant uptake. Leaching is the vertical downward displacement of pesticides through the soil profile and the unsaturated zone, and finally to groundwater, which is vulnerable to pollution. Pesticides are frequently leached through the soil by the effect of rain or irrigation water. Pesticide leaching is highest for weakly sorbing and/or persistent compounds, climates with high precipitation and low temperatures, and soils with low organic matter and sandy texture. On the contrary, for pesticides with a low persistence that disappear quickly, the risk of groundwater pollution considerably decreases. Different and varied factors such as physical-chemical properties of the pesticide, a permeability of the soil, texture and organic matter content of the soil, volatilization, crop-root uptake, and method and dose of pesticide application are responsible for the leaching rate of the pesticides. Soils that are high in clays and organic matter will slow the movement of water, attach easily to many pesticides, and generally have a higher diversity and population of soil organisms that can metabolize the pesticides.",book:{id:"8533",slug:"pesticides-use-and-misuse-and-their-impact-in-the-environment",title:"Pesticides",fullTitle:"Pesticides - Use and Misuse and Their Impact in the Environment"},signatures:"Gabriel Pérez-Lucas, Nuria Vela, Abderrazak El Aatik and Simón Navarro",authors:[{id:"202983",title:"Dr.",name:"Simón",middleName:null,surname:"Navarro",slug:"simon-navarro",fullName:"Simón Navarro"},{id:"202988",title:"Dr.",name:"Nuria",middleName:null,surname:"Vela",slug:"nuria-vela",fullName:"Nuria Vela"},{id:"206059",title:"Dr.",name:"Gabriel",middleName:null,surname:"Pérez-Lucas",slug:"gabriel-perez-lucas",fullName:"Gabriel Pérez-Lucas"},{id:"283154",title:"Mr.",name:"Abderrazak",middleName:null,surname:"El Aatik",slug:"abderrazak-el-aatik",fullName:"Abderrazak El Aatik"}]},{id:"77770",title:"Mycorrhizal Fungi and Sustainable Agriculture",slug:"mycorrhizal-fungi-and-sustainable-agriculture",totalDownloads:327,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"The 20thcentury witnessed an augmentation in agricultural production, mainly through the progress and use of pesticides, fertilizers containing nitrogen and phosphorus, and developments in plant breeding and genetic skills. In the naturally existing ecology, rhizospheric soils have innumerable biological living beings to favor the plant development, nutrient assimilation, stress tolerance, disease deterrence, carbon seizing and others. These organisms include mycorrhizal fungi, bacteria, actinomycetes, etc. which solubilize nutrients and assist the plants in up taking by roots. Amongst them, arbuscular mycorrhizal (AM) fungi have key importance in natural ecosystem, but high rate of chemical fertilizer in agricultural fields is diminishing its importance. The majority of the terrestrial plants form association with Vesicular Arbuscular Mycorrhiza (VAM) or Arbuscular Mycorrhizal fungi (AMF). This symbiosis confers benefits directly to the host plant’s growth and development through the acquisition of Phosphorus (P) and other mineral nutrients from the soil by the AMF. They may also enhance the protection of plants against pathogens and increases the plant diversity. This is achieved by the growth of AMF mycelium within the host root (intra radical) and out into the soil (extra radical) beyond. Proper management of Arbuscular Mycorrhizal fungi has the potential to improve the profitability and sustainability of agricultural systems. AM fungi are especially important for sustainable farming systems because AM fungi are efficient when nutrient availability is low and when nutrients are bound to organic matter and soil particles.",book:{id:"10360",slug:"nitrogen-in-agriculture-physiological-agricultural-and-ecological-aspects",title:"Nitrogen in Agriculture",fullTitle:"Nitrogen in Agriculture - Physiological, Agricultural and Ecological Aspects"},signatures:"Soibam Helena Devi, Ingudam Bhupenchandra, Soibam Sinyorita, S.K. Chongtham and E. Lamalakshmi Devi",authors:[{id:"301167",title:"Dr.",name:"E. Lamalakshmi",middleName:null,surname:"Devi",slug:"e.-lamalakshmi-devi",fullName:"E. Lamalakshmi Devi"},{id:"311911",title:"Dr.",name:"S.K.",middleName:null,surname:"Chongtham",slug:"s.k.-chongtham",fullName:"S.K. Chongtham"},{id:"345840",title:"Dr.",name:"Ingudam",middleName:null,surname:"Bhupenchandra",slug:"ingudam-bhupenchandra",fullName:"Ingudam Bhupenchandra"},{id:"423173",title:"Mrs.",name:"Soibam",middleName:null,surname:"Helena Devi",slug:"soibam-helena-devi",fullName:"Soibam Helena Devi"},{id:"423177",title:"Dr.",name:"Soibam",middleName:null,surname:"Sinyorita",slug:"soibam-sinyorita",fullName:"Soibam Sinyorita"}]},{id:"77147",title:"Influence of Heavy Metals on the Nitrogen Metabolism in Plants",slug:"influence-of-heavy-metals-on-the-nitrogen-metabolism-in-plants",totalDownloads:305,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"As an essential element, Nitrogen is needed in large quantities for being an important component of cellular constituents and for plant metabolism, and its deficiency is one of the most common limitations for plant development. The study of the toxic effects of metal in plants involves a complex system of reactions that can be better determined once having a large attention of the different backgrounds of occurence to determinate how to proceed. The objective of this review is to add scientific knowledge, addressing the main functionalities and characteristics of this relation heavy metals – nitrogen metabolism in plant. Increasing industrialization and urbanization had anthropogenic contribution of heavy metals in biosphere and had largest availability in ecosystems. This toxicity in plants varies with plant species, specific metal, concentration, soil composition, as many heavy metals are considered to be essential for plant growth. Were provided data and reviews regarding the effect of heavy metals on nitrogen metabolism of plants and the responses of plants and the cross-talk of heavy metals and various stressors factors. Is clear to understand the relation between metals amount and the benefit or harm caused on plants, determining then, which mechanism should be activated to protect your physiological system.",book:{id:"10360",slug:"nitrogen-in-agriculture-physiological-agricultural-and-ecological-aspects",title:"Nitrogen in Agriculture",fullTitle:"Nitrogen in Agriculture - Physiological, Agricultural and Ecological Aspects"},signatures:"Vitor Nascimento, Glauco Nogueira, Gabriel Monteiro, Waldemar Júnior, Joze Melissa Nunes de Freitas and Cândido Neto",authors:[{id:"332095",title:"Dr.",name:"Cândido",middleName:null,surname:"Neto",slug:"candido-neto",fullName:"Cândido Neto"},{id:"332157",title:"Prof.",name:"Joze",middleName:null,surname:"Freitas",slug:"joze-freitas",fullName:"Joze Freitas"}]}],onlineFirstChaptersFilter:{topicId:"28",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:139,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:122,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:10,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. 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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. 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A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null},{id:"20",title:"Animal Nutrition",coverUrl:"https://cdn.intechopen.com/series_topics/covers/20.jpg",isOpenForSubmission:!0,annualVolume:11416,editor:{id:"175967",title:"Dr.",name:"Manuel",middleName:null,surname:"Gonzalez Ronquillo",slug:"manuel-gonzalez-ronquillo",fullName:"Manuel Gonzalez Ronquillo",profilePictureURL:"https://mts.intechopen.com/storage/users/175967/images/system/175967.png",biography:"Dr. Manuel González Ronquillo obtained his doctorate degree from the University of Zaragoza, Spain, in 2001. He is a research professor at the Faculty of Veterinary Medicine and Animal Husbandry, Autonomous University of the State of Mexico. He is also a level-2 researcher. He received a Fulbright-Garcia Robles fellowship for a postdoctoral stay at the US Dairy Forage Research Center, Madison, Wisconsin, USA in 2008–2009. He received grants from Alianza del Pacifico for a stay at the University of Magallanes, Chile, in 2014, and from Consejo Nacional de Ciencia y Tecnología (CONACyT) to work in the Food and Agriculture Organization’s Animal Production and Health Division (AGA), Rome, Italy, in 2014–2015. He has collaborated with researchers from different countries and published ninety-eight journal articles. He teaches various degree courses in zootechnics, sheep production, and agricultural sciences and natural resources.\n\nDr. Ronquillo’s research focuses on the evaluation of sustainable animal diets (StAnD), using native resources of the region, decreasing carbon footprint, and applying meta-analysis and mathematical models for a better understanding of animal production.",institutionString:null,institution:{name:"Universidad Autónoma del Estado de México",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"28",title:"Animal Reproductive Biology and Technology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/28.jpg",isOpenForSubmission:!0,annualVolume:11417,editor:{id:"177225",title:"Prof.",name:"Rosa Maria Lino Neto",middleName:null,surname:"Pereira",slug:"rosa-maria-lino-neto-pereira",fullName:"Rosa Maria Lino Neto Pereira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9wkQAC/Profile_Picture_1624519982291",biography:"Rosa Maria Lino Neto Pereira (DVM, MsC, PhD and) is currently a researcher at the Genetic Resources and Biotechnology Unit of the National Institute of Agrarian and Veterinarian Research (INIAV, Portugal). She is the head of the Reproduction and Embryology Laboratories and was lecturer of Reproduction and Reproductive Biotechnologies at Veterinary Medicine Faculty. She has over 25 years of experience working in reproductive biology and biotechnology areas with a special emphasis on embryo and gamete cryopreservation, for research and animal genetic resources conservation, leading research projects with several peer-reviewed papers. Rosa Pereira is member of the ERFP-FAO Ex situ Working Group and of the Management Commission of the Portuguese Animal Germplasm Bank.",institutionString:"The National Institute for Agricultural and Veterinary Research. Portugal",institution:null},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. 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(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. 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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 is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null}]},{type:"book",id:"9963",title:"Advances and Applications in Deep Learning",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/9963.jpg",slug:"advances-and-applications-in-deep-learning",publishedDate:"December 9th 2020",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"0d51ba46f22e55cb89140f60d86a071e",volumeInSeries:4,fullTitle:"Advances and Applications in Deep Learning",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. 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Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"333753",title:"Dr.",name:"Rais",middleName:null,surname:"Ahmed",slug:"rais-ahmed",fullName:"Rais Ahmed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333753/images/20168_n.jpg",biography:null,institutionString:null,institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. Govindarajan completed his BSc degree in Zoology at Government Arts College (Autonomous), Kumbakonam, and MSc, MPhil, and PhD degrees at Annamalai University, Annamalai Nagar, Tamil Nadu, India. He is serving as an assistant professor at the Department of Zoology, Annamalai University. His research interests include isolation, identification, and characterization of biologically active molecules from plants and microbes. He has identified more than 20 pure compounds with high mosquitocidal activity and also conducted high-quality research on photochemistry and nanosynthesis. He has published more than 150 studies in journals with impact factor and 2 books in Lambert Academic Publishing, Germany. He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"322007",title:"Dr.",name:"Maria Elizbeth",middleName:null,surname:"Alvarez-Sánchez",slug:"maria-elizbeth-alvarez-sanchez",fullName:"Maria Elizbeth Alvarez-Sánchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",country:{name:"Mexico"}}},{id:"337443",title:"Dr.",name:"Juan",middleName:null,surname:"A. 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Gonzalez-Sanchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Puerto Rico System",country:{name:"United States of America"}}},{id:"337446",title:"Dr.",name:"Maria",middleName:null,surname:"Zavala-Colon",slug:"maria-zavala-colon",fullName:"Maria Zavala-Colon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Puerto Rico, Medical Sciences Campus",country:{name:"United States of America"}}},{id:"338856",title:"Mrs.",name:"Nur Alvira",middleName:null,surname:"Pascawati",slug:"nur-alvira-pascawati",fullName:"Nur Alvira Pascawati",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universitas Respati Yogyakarta",country:{name:"Indonesia"}}}]}},subseries:{item:{id:"10",type:"subseries",title:"Animal Physiology",keywords:"Physiology, Comparative, Evolution, Biomolecules, Organ, Homeostasis, Anatomy, Pathology, Medical, Cell Division, Cell Signaling, Cell Growth, Cell Metabolism, Endocrine, Neuroscience, Cardiovascular, Development, Aging, Development",scope:"Physiology, the scientific study of functions and mechanisms of living systems, is an essential area of research in its own right, but also in relation to medicine and health sciences. The scope of this topic will range from molecular, biochemical, cellular, and physiological processes in all animal species. Work pertaining to the whole organism, organ systems, individual organs and tissues, cells, and biomolecules will be included. Medical, animal, cell, and comparative physiology and allied fields such as anatomy, histology, and pathology with physiology links will be covered in this topic. 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Dr. Rutland also obtained an MMedSci (Medical Education) and a Postgraduate Certificate in Higher Education (PGCHE). She is the author of more than sixty peer-reviewed journal articles, twelve books/book chapters, and more than 100 research abstracts in cardiovascular biology and oncology. She is a board member of the European Association of Veterinary Anatomists, Fellow of the Anatomical Society, and Senior Fellow of the Higher Education Academy. 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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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