Search

The Ramganga River basin, comprising three rivers, the Dhela, Dhandi, and Ramganga, plays a vital role in groundwater recharge, sustaining numerous industries, urban areas, and rural communities reliant on these rivers for daily activities. The study’s primary purpose was to analyze the groundwater quality in the context of potability, irrigation, and health risks to the local inhabitants of the Ramganga River basin. In 2021–2022, 52 samples (26 × 2) were collected from 13 locations in two different seasons, i.e., pre-monsoon and post-monsoon, and 20 physico-chemical and heavy metal and metalloids were analyzed using the standard protocols. The result shows that heavy metal and metalloids and metalloid concentrations of Zn (0.309–1.787 and 0.613–1.633); Fe (0.290–0.965 and 0.253–1.720), Cd (0.001–0.002 and 0.001–0.002); As (0.001–0.002 and 0.001–0.002), Cr (0.009–0.027 and 0.011–0.029), and Pb (−0.001–0.010 and 0.00–0.010) values in mg/L are present in both seasons. The groundwater quality index (GWQI), heavy metal pollution Index (HPI), and heavy metal evaluation index (HEI) were used to assess the water quality and metal pollution in the basin area. As per GWQI values, water quality lies from excellent water quality (41.639 and 43.091) to good water quality (56.326 and 53.902); as per HPI values, it shows good (29.51 and 30.03) to poor quality (60.26 and 59.75) and HEI values show the low-level contamination (1.03–2.57 and 1.13–3.37) of heavy metal and metalloids in both seasons. According to the potential health risk assessment, infants show low risk in pre-monsoon and low risk to medium post-monsoon, while children and adults show low risk to high risk in both seasons. From the health risk perspective, it shows that children and adults have more concerns about non-carcinogenic effects, so adequate remedial measures and treatment are required to avoid the groundwater quality of the Ramganga River basin.

The need to focus on traditional crops for food security has been realized across the globe. ‘Bhat’ is an indigenous soybean variety from the Indian Himalayan Region that has been neglected in recent times due to changing agricultural choices. The present study was conducted on 52 indigenous soybean accessions collected from different villages of Uttarakhand, a hilly state in Northern India, to determine the concentrations of various macro- and microelements in the crop. The analysis used the HHXRF (handheld X-ray fluorescence) spectroscopic technique and atomic absorption spectroscopy (AAS). The findings reveal that the ‘bhat’ is an extremely nutrient-rich crop with calcium being the most significant macronutrient (highest concentration of 27,300 ppm), followed by phosphorus, potassium, and sulphur found in the bhat seeds. The study suggests that samples from Pauri Garhwal (Gwad Khirsu, Bironkhal, Sripur), Tehri (PratapNagar, Singoli), Chamoli (Paini, and Agastyamuni) villages were rich in all the major macronutrients. Among the micronutrients, silicon was found to be the most dominant with the highest concentration of 1920 ppm. This was followed by the dominance of iron, zinc, and manganese in descending order of abundance. Tipri, Chandola Rai Goonth, Chopdiun, and Paini villages were found to have the highest concentrations of microelements. The statistical data analysis confirms that seed samples from different regions are significantly similar in terms of nutrient concentrations, except for Si and Fe, thereby indicating that ‘bhat’ from any of the villages is equally good for consumption. However, seed samples from certain regions were found to be contaminated with heavy metals, indicating soil pollution, which demands attention towards current agricultural practices. The findings show that the crop is an exceptional source of essential and quasi-essential elements and should be promoted to benefit the hill populations.

Since the COVID-19 outbreak, the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus has evolved into variants with varied infectivity. Vaccines developed against COVID-19 infection have boosted immunity, but there is still uncertainty on how long the immunity from natural infection or vaccination will last. The present study attempts to outline the present level of information about the contagiousness and spread of SARS-CoV-2 variants of interest and variants of concern (VOCs). The keywords like COVID-19 vaccine types, VOCs, universal vaccines, bivalent, and other relevant terms were searched in NCBI, Science Direct, and WHO databases to review the published literature. The review provides an integrative discussion on the current state of knowledge on the type of vaccines developed against SARS-CoV-2, the safety and efficacy of COVID-19 vaccines concerning the VOCs, and prospects of novel universal, chimeric, and bivalent mRNA vaccines efficacy to fend off existing variants and other emerging coronaviruses. Genomic variation can be quite significant, as seen by the notable differences in impact, transmission rate, morbidity, and death during several human coronavirus outbreaks. Therefore, understanding the amount and characteristics of coronavirus genetic diversity in historical and contemporary strains can help researchers get an edge over upcoming variants.

Abstract Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future.

Abstract In today's fast-paced society, environmental breakdown is an ecumenical concern. This dilemma is tangled up with the unaccountable anthropogenic activities that are causing significant public health issues. Because of the rapid pace of development, urban soil and water pollution is progressively acting as a sink for a variety of contaminants, including heavy metals, pesticides, petroleum waste, radioactive moieties, etc. Phytoremediation is a low-cost, high-efficient method of extracting or removing pollutants from the environment. Water is transpired by green plants in order to move nutrients from the soil to the site of photosynthesis. During this process, pollutants in the water are also taken up and sequestered, digested, or drained out. This technique has many benefits over conventional approaches which is aesthetically pleasing and has long-term applicability. Phytoremediation could be a viable option to decontaminate heavy metal-polluted sites, particularly when the biomass produced during the process could be economically utilized in the form of bioenergy. Depending on the method used and nature of the contaminant involved, phytoremediating areas where metals and other inorganic compounds exist may utilize one of several techniques as discussed in the present study which are phytodegradation, phytoextraction, phytostimulation, phytostabilization, phytofiltration, phytovolatalization, etc. Phytoremediation is an emerging technology that employs the natural, biological, chemical, or physical processes of plants to remove, detoxify, or immobilize environmental contaminants in a growth matrix. This approach is hence an innovative tool with a great potential to decontaminate soil and water. Phytoremediation is a promising technique for ensuring the sustainability of future generations and reducing pollution.

The production and disposal of plastics have become significant concerns for the sustainability of the planet. During the past 75 years, around 80% of plastic waste has either ended up in landfills or been released into the environment. Plastic debris released into the environment breaks down into smaller particles through fragmentation, weathering, and other disintegration processes, generating microplastics (plastic particles ≤ 5 mm in size). Although marine and aquatic ecosystems have been the primary focus of microplastic pollution research, a growing body of evidence suggests that terrestrial ecosystems are equally at risk. Microplastic contamination has been reported in various terrestrial environments from several sources such as plastics mulch, pharmaceuticals and cosmetics, tire abrasions (tire wear particles), textiles industries (microfibers), sewage sludge, and plastic dumping. Recent studies suggest that the soil has become a significant sink for pollutants released into terrestrial ecosystems and is often contaminated with a mixture of organic and inorganic pollutants. This has gradually caused adverse impacts on soil health and fertility by affecting soil pH, porosity, water-holding capacity, and soil microbial enzymatic activities. Microplastics can interact with the co-existing pollutants of the environments by adsorbing the contaminants onto their surfaces through various intermolecular forces, including electrostatic, hydrophobic, non-covalent, partition effects, van der Waals forces, and microporous filling mechanisms. This subsequently delays the degradation process of existing contaminants, thereby affecting the soil and various ecological activities of the ecosystem. Thus, the present article aims to elucidate the deleterious impact of microplastics and their interactions with other pollutants in the terrestrial ecosystem. This review also addresses the impact of microplastics in disrupting the soil sustainability of the planet.

The Ramganga River basin, comprising three rivers, the Dhela, Dhandi, and Ramganga, plays a vital role in groundwater recharge, sustaining numerous industries, urban areas, and rural communities reliant on these rivers for daily activities. The study's primary purpose was to analyze the groundwater quality in the context of potability, irrigation, and health risks to the local inhabitants of the Ramganga River basin. In 2021–2022, 52 samples (26 × 2) were collected from 13 locations in two different seasons, i.e., pre-monsoon and post-monsoon, and 20 physico-chemical and heavy metal and metalloids were analyzed using the standard protocols. The result shows that heavy metal and metalloids and metalloid concentrations of Zn (0.309–1.787 and 0.613–1.633); Fe (0.290–0.965 and 0.253–1.720), Cd (0.001–0.002 and 0.001–0.002); As (0.001–0.002 and 0.001–0.002), Cr (0.009–0.027 and 0.011–0.029), and Pb (−0.001–0.010 and 0.00–0.010) values in mg/L are present in both seasons. The groundwater quality index (GWQI), heavy metal pollution Index (HPI), and heavy metal evaluation index (HEI) were used to assess the water quality and metal pollution in the basin area. As per GWQI values, water quality lies from excellent water quality (41.639 and 43.091) to good water quality (56.326 and 53.902); as per HPI values, it shows good (29.51 and 30.03) to poor quality (60.26 and 59.75) and HEI values show the low-level contamination (1.03–2.57 and 1.13–3.37) of heavy metal and metalloids in both seasons. According to the potential health risk assessment, infants show low risk in pre-monsoon and low risk to medium post-monsoon, while children and adults show low risk to high risk in both seasons. From the health risk perspective, it shows that children and adults have more concerns about non-carcinogenic effects, so adequate remedial measures and treatment are required to avoid the groundwater quality of the Ramganga River basin. [ABSTRACT FROM AUTHOR]

The need to focus on traditional crops for food security has been realized across the globe. 'Bhat' is an indigenous soybean variety from the Indian Himalayan Region that has been neglected in recent times due to changing agricultural choices. The present study was conducted on 52 indigenous soybean accessions collected from different villages of Uttarakhand, a hilly state in Northern India, to determine the concentrations of various macro- and microelements in the crop. The analysis used the HHXRF (handheld X-ray fluorescence) spectroscopic technique and atomic absorption spectroscopy (AAS). The findings reveal that the 'bhat' is an extremely nutrient-rich crop with calcium being the most significant macronutrient (highest concentration of 27,300 ppm), followed by phosphorus, potassium, and sulphur found in the bhat seeds. The study suggests that samples from Pauri Garhwal (Gwad Khirsu, Bironkhal, Sripur), Tehri (PratapNagar, Singoli), Chamoli (Paini, and Agastyamuni) villages were rich in all the major macronutrients. Among the micronutrients, silicon was found to be the most dominant with the highest concentration of 1920 ppm. This was followed by the dominance of iron, zinc, and manganese in descending order of abundance. Tipri, Chandola Rai Goonth, Chopdiun, and Paini villages were found to have the highest concentrations of microelements. The statistical data analysis confirms that seed samples from different regions are significantly similar in terms of nutrient concentrations, except for Si and Fe, thereby indicating that 'bhat' from any of the villages is equally good for consumption. However, seed samples from certain regions were found to be contaminated with heavy metals, indicating soil pollution, which demands attention towards current agricultural practices. The findings show that the crop is an exceptional source of essential and quasi-essential elements and should be promoted to benefit the hill populations. [ABSTRACT FROM AUTHOR]

Biodegradation was considered a promising and environmentally friendly method for treating environmental pollution caused by diuron. However, the mechanisms of biodegradation of diuron required further research. In this study, the degradation process of diuron by Achromobacter xylosoxidans SL-6 was systematically investigated. The results suggested that the antioxidant system of strain SL-6 was activated by adding diuron, thereby alleviating their oxidative stress response. In addition, degradation product analysis showed that diuron in strain SL-6 was mainly degraded by urea bridge cleavage, dehalogenation, deamination, and ring opening, and finally cis, cis-muconic acid was generated. The combined analysis of metabolomics and transcriptomics revealed the biodegradation and adaptation mechanism of strain SL-6 to diuron. Metabolomics analysis showed that after the strain SL-6 was exposed to diuron, metabolic pathways such as tricarboxylic acid cycle (cis, cis-muconic acid), glutathione metabolism (oxidized glutathione), and urea cycle (arginine) were reprogrammed in the cells. Furthermore, diuron could induce the production of membrane transport proteins in strain SL-6 cells and overexpress antioxidant enzyme genes, finally ultimately promoting the up-regulation of genes encoding amide hydrolases and dioxygenases, which was revealed by transcriptomics studies. This work enriched the biodegradation mechanism of phenylurea herbicides and provided guidance for the removal of diuron residues in the environment and promoting agriculture sustainable development [ABSTRACT FROM AUTHOR]

This study presents a comprehensive assessment of the performance of popular pitcher-type point-of-use (POU) water filters to remove PFAS contaminants from tap waters. The evaluated filters, Brita (Elite and Standard), Zero Water, Aquagear, and Clearly Filtered, were tested for their efficacy in removing 75 targeted PFAS, total organic carbon (TOC), total dissolved solids (TDS), chloride, and sulfate from two Canadian tap waters with background Σ75 PFAS concentrations of 13 and 56 ng/L. Overall, the performances of the filters varied depending on the structure of the filter media, the water source, and the specific contaminants present. ZeroWater was the top performer in the case of total PFAS removal. The volume-weighted average removal of total PFAS after 160 L of filtration using Saint-Donat tap water was 99% for Zero Water, 99% for Clearly Filtered, 77% for Aquagear, and 20% for Brita (Elite). In the case of Montreal tap water, which had different water characteristics and lower total PFAS levels, the volume-weighted average removal for PFAS was ≈100% for Zero Water, 96% for Clearly Filtered, 60% for Aquagear, 48% for Brita (Elite), and 38% for Brita (Standard). Both laboratory and home tests involving Zero Water filters yielded similar high-performance results using Montreal tap water. Although Zero Water exhibited high PFAS removal (99%) in Saint-Donat water, TDS and TOC desorption and a significant drop in pH were observed after 80 L, a phenomenon which was explained by the higher total concentration of anions in this water. In contrast, no desorption was observed in Montreal tap water for TDS and TOC due to the lower concentrations of anions. The Aquagear filter demonstrated an unusual increase in concentrations of sulfate after the initial 20 L, which needs further evaluation. This study discusses individual filter performance, the influence of tap water characteristics, and the potential to meet the new NSF guidelines, which provides valuable insights for consumers seeking to choose an appropriate easy-to-use water filtration system to ensure safe and clean drinking water in different regions. [ABSTRACT FROM AUTHOR]

Providing safe drinking water for the entire world's population is essential for ensuring sustainable development. The presence of harmful compounds in aquifers, majorly toxic elements, is a serious environmental concern around the globe. This research aimed to quantify for the initial period the amounts of toxic elements in freshwater in the Dehradun Industrial Region of Uttrakhand, India, as well as the associated health risks. The PTEs (potentially toxic elements) Fe, Cd, Mn, Cu, Cr and Pb, Zn, Ni is measured by AAS and compared to BIS and WHO requirements for drinking safety. The order of mean trace element values in all groundwater samples were determined as Fe > Zn > Cu > Ni > Co > Cd > Pb. HPI was discovered to be higher than high class during the research period (HPI > 30), but under the severe contamination criterion of 100. Iron's MI and PI values were consistently over the threshold limit during the research period, and certain toxic elements were discovered exceptionally near the threshold limit, indicating a severe future influence on groundwater quality. According to PCA (principal component analysis), CM (correlation matrix), and potential health hazard, maximum levels of toxic elements in groundwater in the Dehradun region are attributed to land use patterns, anthropogenic activity, industrial activity, fertilizer and pesticide leaching, and residential waste into the aquifer system. The findings of this study could aid local planners and policymakers in preventing health risks from contaminated aquifers through the deployment of suitable monitoring and mitigation measures. [ABSTRACT FROM AUTHOR]

Since the COVID-19 outbreak, the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus has evolved into variants with varied infectivity. Vaccines developed against COVID-19 infection have boosted immunity, but there is still uncertainty on how long the immunity from natural infection or vaccination will last. The present study attempts to outline the present level of information about the contagiousness and spread of SARS-CoV-2 variants of interest and variants of concern (VOCs). The keywords like COVID-19 vaccine types, VOCs, universal vaccines, bivalent, and other relevant terms were searched in NCBI, Science Direct, and WHO databases to review the published literature. The review provides an integrative discussion on the current state of knowledge on the type of vaccines developed against SARS-CoV-2, the safety and efficacy of COVID-19 vaccines concerning the VOCs, and prospects of novel universal, chimeric, and bivalent mRNA vaccines efficacy to fend off existing variants and other emerging coronaviruses. Genomic variation can be quite significant, as seen by the notable differences in impact, transmission rate, morbidity, and death during several human coronavirus outbreaks. Therefore, understanding the amount and characteristics of coronavirus genetic diversity in historical and contemporary strains can help researchers get an edge over upcoming variants. [ABSTRACT FROM AUTHOR]

The current study reports the synthesis of sustainable nano-hydroxyapatite (nHAp) using a wet chemical precipitation approach. The materials used in the green synthesis of nHAp were obtained from environmental biowastes such as HAp from eggshells and pectin from banana peels. The physicochemical characterization of obtained nHAp was carried out using different techniques. For instance, X-ray diffractometer (XRD) and FTIR spectroscopy were used to study the crystallinity and synthesis of nHAp respectively. In addition, the morphology and elemental composition of nHAP were studied using FESEM equipped with EDX. HRTEM showed the internal structure of nHAP and calculated its grain size which was 64 nm. Furthermore, the prepared nHAp was explored for its antibacterial and antibiofilm activity which has received less attention previously. The obtained results showed the potential of pectin-bound nHAp as an antibacterial agent for various biomedical and healthcare applications. [ABSTRACT FROM AUTHOR]

Immunomodulatory activity of hot aqueous extract of Neolamarckia cadamba leaves with particular reference to splenocyte proliferation and induction of cytokines has been investigated using Wistar albino rat model. Study of hot aqueous extract (HAE) of N. cadamba leaves over cell mediated immune response was carried out using six groups (Gp-I as control, Gp-II treated with 20 µg/mL HAE, Gp-III treated with 50 µg/mL HAE, Gp-IV treated with 100 µg/mL HAE, Gp-V treated with 250 µg/mL HAE and Gp-VI treated with 500 µg/mL HAE) of Wistar albino rats containing six animals in each. In vitro cell mediated immune response was assayed by 3-(4, 5-Dimethylthiazolyl)-2, 5-diphenyl tetrazolium bromide (MTT) using Concanavalin A (Con A) stimulated splenocytes in presence of different concentrations of HAE (20-500 µg/mL). Tumor necrosis factor-α (TNF-α), Interferon-γ (IFN-γ), Interleukin-10 (IL-10) and Interleukin-4 (IL-4) were assayed in culture supernatant of splenocyte by sandwich ELISA in presence of different concentrations of HAE (20-500 µg/mL). In vitro study revealed dose dependent proliferation of Con A treated splenocyte. Augmentation in the proliferation of splenocytes reflects cell mediated immunostimulatory potential of HAE. Dose dependent significant decreased (p < 0.01) in the level of IL-10 and TNF-α was observed in supernatant of 48 hours splenocytes culture in presence of increasing concentrations of HAE while IFN-γ level was found to be increased significantly (p < 0.01) with increase in HAE concentrations. It is concluded that HAE of N. cadamba leaves regulate the networking of cytokines, suggesting its possible role in regulating the activity of immune system of host. [ABSTRACT FROM AUTHOR]

Traditionally, rice leaf disease identification relies on a visual examination of abnormalities or an analytical result obtained by growing bacteria in the research lab. This method of visual evaluation is qualitative and error-prone. On the other hand, an artificial neural network system is fast and more accurate. Several pieces of research using traditional machine learning and deep convolution neural networks (CNN) have been utilized to overcome the issues. Still, these methods need more semantic contextual global and local feature extraction. Due to this, efficiency is less. Hence, in the present study, a multi-scale feature fusion-based RDTNet has been designed. The RDTNet contains two modules, and the first module extracts feature via three scales from the local binary pattern (LBP), gray, and a histogram of orient gradient (HOG) image. The second module extracts semantic global and local features through the transformer and convolution block. Furthermore, the computing cost is reduced by dividing the query into two parts and feeding them to convolution and the transformer block. The results indicate that the proposed method has a very high average precision, f1-score, and accuracy of 99.55%, 99.54%, and 99.53%, respectively. It is suggestive of improved classification accuracy using multi-scale features and the transformer. The model has also been validated on other datasets confirming that the present model can be used for real-time rice disease diagnosis. In the future, such models can be used for monitoring other crops, including wheat, tomato, and potato. [ABSTRACT FROM AUTHOR]

The production and disposal of plastics have become significant concerns for the sustainability of the planet. During the past 75 years, around 80% of plastic waste has either ended up in landfills or been released into the environment. Plastic debris released into the environment breaks down into smaller particles through fragmentation, weathering, and other disintegration processes, generating microplastics (plastic particles ≤ 5 mm in size). Although marine and aquatic ecosystems have been the primary focus of microplastic pollution research, a growing body of evidence suggests that terrestrial ecosystems are equally at risk. Microplastic contamination has been reported in various terrestrial environments from several sources such as plastics mulch, pharmaceuticals and cosmetics, tire abrasions (tire wear particles), textiles industries (microfibers), sewage sludge, and plastic dumping. Recent studies suggest that the soil has become a significant sink for pollutants released into terrestrial ecosystems and is often contaminated with a mixture of organic and inorganic pollutants. This has gradually caused adverse impacts on soil health and fertility by affecting soil pH, porosity, water-holding capacity, and soil microbial enzymatic activities. Microplastics can interact with the co-existing pollutants of the environments by adsorbing the contaminants onto their surfaces through various intermolecular forces, including electrostatic, hydrophobic, non-covalent, partition effects, van der Waals forces, and microporous filling mechanisms. This subsequently delays the degradation process of existing contaminants, thereby affecting the soil and various ecological activities of the ecosystem. Thus, the present article aims to elucidate the deleterious impact of microplastics and their interactions with other pollutants in the terrestrial ecosystem. This review also addresses the impact of microplastics in disrupting the soil sustainability of the planet. [ABSTRACT FROM AUTHOR]

Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future. [ABSTRACT FROM AUTHOR]

In today's fast-paced society, environmental breakdown is an ecumenical concern. This dilemma is tangled up with the unaccountable anthropogenic activities that are causing significant public health issues. Because of the rapid pace of development, urban soil and water pollution is progressively acting as a sink for a variety of contaminants, including heavy metals, pesticides, petroleum waste, radioactive moieties, etc. Phytoremediation is a low-cost, high-efficient method of extracting or removing pollutants from the environment. Water is transpired by green plants in order to move nutrients from the soil to the site of photosynthesis. During this process, pollutants in the water are also taken up and sequestered, digested, or drained out. This technique has many benefits over conventional approaches which is aesthetically pleasing and has long-term applicability. Phytoremediation could be a viable option to decontaminate heavy metal-polluted sites, particularly when the biomass produced during the process could be economically utilized in the form of bioenergy. Depending on the method used and nature of the contaminant involved, phytoremediating areas where metals and other inorganic compounds exist may utilize one of several techniques as discussed in the present study which are phytodegradation, phytoextraction, phytostimulation, phytostabilization, phytofiltration, phytovolatalization, etc. Phytoremediation is an emerging technology that employs the natural, biological, chemical, or physical processes of plants to remove, detoxify, or immobilize environmental contaminants in a growth matrix. This approach is hence an innovative tool with a great potential to decontaminate soil and water. Phytoremediation is a promising technique for ensuring the sustainability of future generations and reducing pollution. [ABSTRACT FROM AUTHOR]

This paper introduces a comprehensive and systematic Design of Experiments based methodology deployed in conjunction with a multi-physics engine air-path and combustion co-simulation, leading to the development of a global transient simulation capability for engine out NOx emissions. The proposed multi-physics engine simulation framework couples a real-time one-dimensional air flow model with a Probability Density Function based Stochastic Reactor Model that accounts for detailed in-cylinder combustion chemistry to predict combustion emissions. The integration challenge stemming from the different computation complexities and time scales required to ensure adequate fidelity levels across multi-physics simulations was addressed through a comprehensive Design of Experiments methodology to develop a reduction of the slower Stochastic Reactor Model simulation to enable a transient simulation focussed on NOx emissions. The Design of Experiments methodology, based on Optimal Latin Hypercube design experiments, was deployed on the multi-physics engine co-simulation platform and systematically validated against both steady state and transient light-duty Diesel engine test data. The surrogate selection process included the evaluation of a range of metamodels, with Kriging metamodels selected based on both the statistical performance criteria and consideration of physical phenomena trends. The transient validation was carried out on a simulated New European Drive Cycle against the experimental data available, showing good capability to capture transient NOx emission behaviour in terms of trends and values. The significance of the results is that it proves the transient and drive cycle capability of the multi-physics simulation platform, suggesting a promising potential applicability for early powertrain development work focussed on drive cycle emissions. [ABSTRACT FROM AUTHOR]

This study inspected the job of the capacity to understand people at their core to emotional wellness. In this review, the distinguished psychological wellness parts are uneasiness, misery, self-efficacy, and flexibility. This correlational exploration utilized relapse examinations were directed to analyze the correlational connections among factors The outcomes showed the EI is negative foresee uneasiness and discouragement, and reactivity, a part of flexibility. I was displayed to anticipate self-adequacy and strength among adolescents emphatically. These outcomes offer help for the possibility that sincerely canny people are more probable strong, have selfawareness adequacy, and, are less restless, less discouraged, and less receptive. The outcomes then show the versatile worth of the ability to appreciate people on a profound level, that is to say, it permits a person to decidedly adapt and conform to his/her current circumstance. [ABSTRACT FROM AUTHOR]

The study investigated chromium (Cr) in the Yamuna river at Mathura - Agra region in Uttar Pradesh, India. The water and fish samples were collected quarterly from the sites, i.e. Vrindavan (Vihar ghat) and Agra (Renuka ghat) from October 2018 to January 2020.The average Cr concentration in water at the Vrindavan site was observed to be maximum (2.27 mg/l) than the Agra site (1.93 mg/l) in the month of April 2019 compared to its BIS/WHO standards (0.05 ppm). Among the samples of fish organs like gill, liver, muscle and kidney, maximum Cr concentration was found in the samples of gills from Vrindavan (Vihar ghat) site (9.63μg/g) and from Agra (Renuka ghat) site (7.78 μg/g) being above the standards values (1 μg/g by European union commission; 0.15 μg/g by Federal Environmental Protection Agency (FEPA) and World Health Organization (WHO). The Cr concentration in the samples was in the order of gill > liver > muscle > kidney. The lower Bio-concentration factor (BCF) and target hazard quotients (THQ) in the muscles indicated fish to be safe for consumption. Heavy metal pollution index (HPI) and Pearson's correlation coefficient analysis indicated more HPI (2676.67) and a positive correlation between all the samples. The contamination degree (Cd) values were above the critical level at both the sampling sites-Vrindavan (38) and Agra (28). The higher pollution indices (HPI, HEI, Cd values) indicated higher degree of contamination in water samples. Hence strategies need to be formulated to check the rising concentration of heavy metals and ensure the safety of the people in the nearby areas. [ABSTRACT FROM AUTHOR]

The present study aims to determine the impact of COVID-19 pandemic confinement on air quality among populous sites of four major metropolitan cities in India (Delhi, Mumbai, Kolkata, and Chennai) from January 1, 2020 to May 31, 2020 by analyzing particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ammonia (NH3), sulfur dioxide (SO2), carbon monoxide (CO), and ozone levels. The most prominent pollutant concerning air quality index (AQI) was determined by Pearson's correlation analysis and unpaired Welch's two-sample t test was carried out to measure the statistically significant reduction in average AQI for all the four sites. AQI significantly plummeted by 44%, 59%, 59%, and 6% in ITO-Delhi, Worli-Mumbai, Jadavpur-Kolkata, and Manali Village-Chennai respectively. The findings conclude a significant improvement in air quality with respect to reduction of 49–73%, 17–63%, 30–74%, and 15–58% in the mean concentration of PM2.5, PM10, NH3, and SO2 respectively during the confinement for the studied locations. The p values for all of the four studied locations were found significantly less than the 5% level of significance for Welch's t test analysis. In addition, reduced AQI values were highly correlated with prominent pollutants (PM2.5 and PM10) during Pearson's correlation analysis. These positive results due to pandemic imprisonment might aid to alter the current policies and strategies of pollution control for a safe and sustainable environment. [ABSTRACT FROM AUTHOR]

Prediction of engine-out emissions with high fidelity from in-cylinder combustion simulations is still a significant challenge early in the engine development process. This article contributes to this fast evolving body of knowledge by focusing on the evaluation of NOx emission prediction capability of a probability density function-based stochastic reactor engine models for a Diesel engine. The research implements a systematic approach to the study of the stochastic reactor engine model performance, underpinned by a detailed space-filling design of experiments (DoE)-based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of both in-cylinder conditions and NOx output. The approach proposed in this article introduces an automatic stochastic reactor engine model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach. This aims to exploit opportunities for internal stochastic reactor engine model parameters tuning to achieve good overall modelling performance as a trade-off between physical in-cylinder measurements accuracy and the output NOx emission predictions error. The results from the case study provide a valuable insight into the effectiveness of the stochastic reactor engine model, showing good capability for NOx emissions prediction and trends, while pointing out the critical sensitivity to the external input parameters and modelling conditions. [ABSTRACT FROM AUTHOR]

Mycobacterium avium subspecies paratuberculosis (MAP) causes granulomatous intestinal disease in animals (Johne's diseases). MAP has also been associated with several autoimmune disorders. In this study, we screened serum samples from confirmed patients of thyroid and type 1 diabetes for the presence of antibody against MAP. We used newly developed 'cocktail ELISA' (based on recombinant secretary proteins) and extensively validated 'indigenous ELISA' (based on whole cell protoplasmic antigen) and both the tests were also compared for their diagnostic potential. A total of 90 serums samples were included of which anti-MAP antibodies was detected in 28.8% and 26.6% of samples by indigenous ELISA (iELISA) and cocktail ELISA (cELISA), respectively. There was almost perfect agreement between the two tests in detecting the anti-MAP antibodies. Study raises concern on high detection of anti-MAP antibodies in human, thus warranting necessary control measure to minimize MAP exposure in human beings. [ABSTRACT FROM AUTHOR]

Nowadays, the bioremediation of toxic pollutants is a subject of interest in terms of health issues and environmental cleaning. In the present review, an eco-friendly, cost-effective approach is discussed for the detoxification of environmental pollutants by the means of natural purifier, i.e., blue-green algae over the conventional methods. Industrial wastes having toxic pollutants are not able to eliminate completely by existing the conventional techniques; in fact, these methods can only change their form rather than the entire degradation. These pollutants have an adverse effect on aquatic life, such as fauna and flora, and finally harm human life directly or indirectly. Cyanobacterial approach for the removal of this contaminant is an efficient tool for sustainable development and pollution control. Cyanobacteria are the primary consumers of food chain which absorbed complex toxic compounds from environments and convert them to simple nontoxic compounds which finally protect higher food chain consumer and eliminate risk of pollution. In addition, these organisms have capability to solve secondary pollution, as they can remediate radioactive compound, petroleum waste and degrade toxins from pesticides. [ABSTRACT FROM AUTHOR]

Proteases have characteristics of biotechnological interest and have thus become important industrial enzymes. We report the production of thermostable protease and its characterization in Bacillus species, which is a thermotolerant bacterium; Bacillus subtilis is widely used for isolating protease enzyme. Gelatin was used as the substrate in nutrient agar medium for screening and showed the maximum zone of activity (22 mm) after overnight incubation and addition of the indicator. Under submerged fermentation conditions, a high level of protease production was found at 45 °C after 36 h at pH 10, with continuous agitation (180 rpm). The presence of galactose and peptone in the medium enhanced enzyme production by 0.5% when compared with other carbon and nitrogen sources. Thus, such additions can augment protease production and their application in various industries. [ABSTRACT FROM AUTHOR]

Tomato leaf curl virus (TLCV) is a major viral disease in tomato that causes quantitative and qualitative losses to the crop. One hundred and fifty three tomato genotypes were screened for three consecutive years (2006–09) under glasshouse and field conditions for TLCV resistance. The incidence of disease was higher during the Rabi season as compared to the Kharif season trials. The reactions of different genotypes were studied by artificial inoculation. Based on the coefficient of infection, nine genotypes (viz. EC-520049 (Solanum chmielewskii), EC-520058, EC-520060 and EC-520061 (S. habrochaites), EC-520070, EC-520071, EC-520077, EC-520079 (S. pimpinellifolium) and H-88-78-1(S. lycopersicum; a derivative of S. habrochaites f. glabratum) were found to be highly resistant in both environments. H-88-78-1 was used for inheritance studies during 2008–10. Using F2 Mendelian segregation, populations showed a 3 (resistant):1 (susceptible) ratio for TLCV disease and were proposed to have both additive and dominant non-allelic gene interactions for various traits. [ABSTRACT FROM PUBLISHER]

Introduction: Yoga has beneficial effects on memory. In females, left hemisphere of the brain is responsible for verbal memory and right hemisphere is responsible for the spatial memory, while the opposite is true for males. Aim: Aim of the present was to study the effect of unilateral right nostril breathing, left nostril breathing and alternate nostril breathing on verbal and spatial memory scores. Materials and Methods: A total of 51 female subjects (age 18-25 years, mean±SD =21.71±3.11) were taken and divided into three groups (n=17). Each group was imparted one of the three different types of nostril breathing practices such as Right Nostril Breathing (RNB), Left Nostril Breathing (LNB) and Alternate Nostril Breathing (ANB) for 1 week for 45 minutes daily. Subjects were given the memory test, before and after 45 minutes of intervention for three consecutive days. Memory tests were performed by using Wechsler Adult Intelligent Scale. Statistical Analysis: Results were analysed by ANOVA with SPSS version 17.0. Results: Results showed that there was increase in recall of digit span-forward, digit-span backward, associate learning and spatial memory scores with RNB, LNB and ANB, which were statistically highly significant (p<0.005). Conclusion: Inclusion of nostril breathing in exercise regimen may be helpful in improving recall of memory. [ABSTRACT FROM AUTHOR]

Nowadays, there is a large demand for nutrient-dense fruits to promote nutritional and metabolic human health. The production of commercial fruit crops is becoming progressively input-dependent to cope with the losses caused by biotic and abiotic stresses. A wide variety of underutilized crops, which are neither commercially cultivated nor traded on a large scale, are mainly grown, commercialized and consumed locally. These underutilized fruits have many advantages in terms of ease to grow, hardiness and resilience to climate changes compared to the major commercially grown crops. In addition, they are exceptionally rich in important phytochemicals and have medicinal value. Hence, their consumption may help to meet the nutritional needs of rural populations, such as those living in fragile arid and semi-arid regions around the world. In addition, local people are well aware of the nutritional and medicinal properties of these crops. Therefore, emphasis must be given to the rigorous study of the conservation and the nutritional characterization of these crops so that the future food basket may be widened for enhancing its functional and nutritional values. In this review, we described the ethnobotany, medicinal and nutritional values, biodiversity conservation and utilization strategies of 19 climate-resilient important, underutilized fruit crops of arid and semi-arid regions (Indian jujube, Indian gooseberry, lasora, bael, kair, karonda, tamarind, wood apple, custard apple, jamun, jharber, mahua, pilu, khejri, mulberry, chironji, manila tamarind, timroo, khirni). [ABSTRACT FROM AUTHOR]