NrfA is the molecular marker for dissimilatory nitrate reduction to ammonium (DNRA) activity, catalysing cytochrome c nitrite reductase enzyme. However, the limited study has been made so far to understand the structural homology modeling of NrfA protein in DNRA bacteria. Therefore, three model DNRA bacteria (Escherechia coli, Wolinella succinogenes and Shewanella oneidensis) were chosen in this study for in-silico protein modeling of NrfA which roughly consists of similar length of amino acids and molecular weight and they belong to two contrasting taxonomic families (γ-proteobacteria with nrfABCDEFG and ε-proteobacteria with nrfHAIJ operon). Multiple bioinformatic tools were used to examine the primary, secondary, and tertiary structure of NrfA protein using three distinct homology modeling pipelines viz., Phyre2, Swiss model and Modeller. The results indicated that NrfA protein in E. coli, W. succinogenes and S. oneidensis was mostly peri-plasmic and hydrophilic. Four conserved Cys-X1-X2-Cys-His motifs, one Cys-X1-X2-Cys-Lys haem-binding motif and Ca ligand were also identified in NrfA protein irrespective of three model bacteria. Moreover, 11 identical conserved amino acids sequence was observed for the first time between serine and proline in NrfA protein. Secondary structure of NrfA revealed that α-helices were observed in 77.9%, 73.4%, and 77.4% in E. coli, W. succinogenes and S. oneidensis, respectively. Ramachandran plot showed that number of residue in favored region in E. coli, W. succinogenes and S. oneidensis was 97.03%, 97.01% and 97.25%, respectively. Our findings also revealed that among three pipelines, Modeller was considered the best in-silico tool for prediction of NrfA protein. Overall, significant findings of this study may aid in the identification of future unexplored DNRA bacteria containing cytochrome c nitrite reductase. The NrfA system, which is linked to respiratory nitrite ammonification, provides an analogous target for monitoring less studied N-retention processes, particularly in agricultural ecosystems. Furthermore, one of the challenging research tasks for the future is to determine how the NrfA protein responds to redox status in the microbial cells.
Increasing groundwater pollution through toxic contamination is the primary concern for severe environmental and health hazards across the world. Groundwater resources are more vulnerable to toxic contamination compared to surface water because they require a long time to restore. Groundwater vulnerability and risk assessment is a challenging task among the researchers responsible for quality monitoring and management of groundwater. In this regard, predictive modeling for groundwater vulnerability is essential to defend the vulnerability of groundwater resources in current scenario. Contamination of groundwater with arsenic (As) and fluoride (F‾) poses a threat to human health in the Bengal delta region. This study developed a framework approach to assess groundwater vulnerability and related health hazard risks in the South 24 Parganas district of West Bengal, India. For modeling groundwater vulnerability, the Logistic regression (LR) method coupled with fifteen hydrogeochemical parameters was used for modeling. The health hazard risk of this study region was assessed using the human health hazard index. Furthermore, hydrogeochemical properties and groundwater quality were assessed through Piper, USSL, and Wilcox's diagram accordingly. The study revealed that F‾, depth, PO42− and SO42− are the highest controlling factors of groundwater vulnerability in this area. It is also found that because of the presence of alkaline organisms in groundwater, it is unfit for farming and drinking purposes as well. The evaluation matrices used in this study revealed that LR gives optimal prediction results (AUC-ROC is 0.891 and 0.861, kappa index is 0.810 and 0.720 in training and validation, respectively) in groundwater vulnerability. The applied approach in this study may be useful to other regions for predicting groundwater vulnerability and for the sustainable adoption of several management strategies. In the future, deep learning as well as other sophisticated learning algorithms should be useful for optimal prediction of groundwater resources.
Vulnerability of groundwater is critical for the sustainable development of groundwater resources, especially in freshwater-limited coastal Indo-Gangetic plains. Here, we intend to develop an integrated novel approach for delineating groundwater vulnerability using hydro-chemical analysis and data-mining methods, i.e., Decision Tree (DT) and K-Nearest Neighbor (KNN) via k-fold cross-validation (CV) technique. A total of 110 of groundwater samples were obtained during the dry and wet seasons to generate an inventory map. Four K-fold CV approach was used to delineate the vulnerable region from sixteen vulnerability causal factors. The statistical error metrics i.e., receiver operating characteristic-area under the curve (AUC-ROC) and other advanced metrices were adopted to validate model outcomes. The results demonstrated the excellent ability of the proposed models to recognize the vulnerability of groundwater zones in the Indo-Gangetic plain. The DT model revealed higher performance (AUC = 0.97) followed by KNN model (AUC = 0.95). The north-central and north-eastern parts are more vulnerable due to high salinity, Nitrate (NO3−), Fluoride (F−) and Arsenic (As) concentrations. Policy-makers and groundwater managers can utilize the proposed integrated novel approach and the outcome of groundwater vulnerability maps to attain sustainable groundwater development and safeguard human-induced activities at the regional level.
The Indian Sundarban is one of the most vulnerable eco-regions of the world and its vulnerability has increased manifold in the last two decades. Despite the insecurities and risks, people do not always migrate and often prefer to stay back by adjusting their lives and livelihood. This article explores the practice of immobility and the process of decision-making that results in immobility. Based on empirical research carried out at Gobardhanpur village in South 24 Parganas district of West Bengal, India, this article examines how people readjust themselves and remain voluntarily immobile instead of facing high vulnerability caused by different shocks or stresses. The empirical research was carried out with the help of both quantitative and qualitative research methods including household-level questionnaire survey, in-depth interviews and focus group discussions. The findings show that whilst the region supports multiple occupations, fishing is the prime occupation of the people. During the monsoon period, diversification in terms of livelihood is low, as fishing supports maximum respondents. In contrast, low fish catch during the off-monsoon season is responsible for high livelihood diversification. Circular migration is a very common adaptive strategy to overcome the livelihood crisis during the off-monsoon season, especially amongst the younger members of the households. The remittances earned through circular migration supplement the household income and secure their livelihood. Moreover, institutional help, robust social networks and attachment to the place also play a role in controlling the decision of immobility.
The problem of drought in India is a major issue in terms of various adverse impacts on livelihood of society. Drought Early Warning System (DEWS), a real-time drought-monitoring tool, has reported that over a fifth of India's geographical area (21.06 %) is suffering drought-like situations. This is 62 % larger than the drought-affected area during the same period last year, which was 7.86 %. Drought affects 21.06 %, with conditions ranging from unusually dry to extremely dry. While 1.63 % and 1.73 % of the area are experiencing ‘extreme’ or ‘exceptional’ dry conditions, 2.17 % is experiencing ‘severe’ dry conditions. Under ‘moderate’ dry circumstances, up to 8.15 % is possible. In this perspective groundwater vulnerability assessment in the overall country is needed for implementing the sustainable and long-term strategies for escaping from this type of hazardous situation. The main objective of this study is to estimate the drought vulnerability in changing climate which eventually influences the food security of India. The groundwater overdraft is one of the crucial elements in agricultural drought vulnerability. Various related parameters have been selected for estimating the drought vulnerability and its impact to food security in India. Here, MaxEnt (maximum entropy) and ANN (analytical neural network) has been considered in this perspective. The AUC values for the training datasets in the ANN and MaxEnt model are 0.891 and 0.921, respectively. The AUC values in ANN and MaxEnt model for the validation datasets are 0.876 and 0.904, respectively. Here MaxEnt model is most optimal than ANN considering predictive accuracy. From this study analysis it is established that western, south and middle portion of country is very much prone to drought vulnerability. So, special emphases in terms of the regional planning have to be taken into consideration for sustainable planning.
Two new species and a new record of blood sucking biting midges of the subgenus Lasiohelea Kieffer, 1921 of the genus Forcipomyia Meigen, 1818 are described after the morphological and molecular data. The new species. Forcipomyia (Lasiohelea) peditata and F. (L.) falcata were fetched from the Sub-Himalayan region, and F. (L.) parvitas (Liu and Yu, 1996) from both the Gangetic plain and western plateau regions of West Bengal. The DNA barcoding of Mitochondrial COX I gene has also been used as molecular evidence.
Study shows that COVID-19 cases, deaths and recoveries vary in macro level. Geographical phenomena may act as potential controlling factor. The present paper investigates spatial pattern of COVID-19 cases and deaths in West Bengal (WB), India and assumes Kolkata is the source region of this disease in WB. Thematic maps on COVID related issues are prepared with the help of QGIS 3.10 software. As on 15th January 2021, WB has 564032 number of COVID-19 cases which is 0.618% to the total population of the state. However, the COVID-19 case for India is 0.843% and for world is 1.341% to its total population. Lorenz Curve shows skewed distribution of the COVID-19 cases in WB. 17 (90%) districts hold 84.11% of the total population and carry 56.30% of the total COVID-19 cases. However, the remaining two districts—Kolkata and North 24 Parganas—hold remaining 43.70% COVID-19 cases. Correlation coefficient with COVID-19 cases and Population Density, Urban Population and Concrete Roof of their house are significant at 1% level of significance.
Mining induced displacement and its impact on social environment has been researched with an immense interest in social sciences for a long period of time. The present study deals with the impact of mining-induced displacement and rehabilitation on psycho-social behaviour in Sonepur–Bazari open cast coal mining area. Place attachment, landscape value and trust have been taken into consideration to understand the effect on psycho-social behaviour in the respective area. Data for this investigation are predominantly derived from semi structured questionnaire survey of 282 participants from 14 villages of the study area. Cronbach’s Alpha has been calculated to test the internal consistency and reliability of the questions. To measure the answers 5-point Likert scale has been used. The responses have systematically analysed after simulation and it has been concluded that the monitory compensation comprehensively contributed to improve the monthly income of the project affected families but the grim reality is that it does not help to improve the place attachment of the residents with their land rather a weak attachment has been found in the rehabilitation sites. The values of landscapes are also drastically changes from pre displacement to post displacement period. Trust has been calculated as an indicator of community attachment. The result indicates that the trust within a community becomes weak after displacement and a negative correlation has been found between mining-induced income inequality and trust.
The present investigation explores the spatial and seasonal variations in potentially toxic element (PTEs) concentrations and contamination level assessment of groundwater samples in and around the Asansol industrial city, eastern India. The representative samples of groundwater from 24 different locations were analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH) and PTEs, e.g., Pb, Cu, Cd, Zn, Fe and Cr for pre-monsoon and post-monsoon. The pH level of examined groundwater samples is under the desirable limit with few exceptions (S5, S11 and S16 in pre-monsoon and S12 in post-monsoon). The recorded values for Pb, Cd, Fe and Cr in many sampling stations found higher than the prescribed limits of Indian standards (IS 10500: 2012) in both the seasons. The mean contamination factor (C f) for PTEs in the groundwater is in the order of Cr [ Fe [ Cd [ Pb [ Cu [ Zn and Fe [ Cr [ Cd [ Pb [ Cu [ Zn, with mean contamination index (C d) value of 2.83 and 2.72 in pre-monsoon and post-monsoon season, respectively , indicating moderate level of contamination in the examined area. Geospatial depiction of HPI values shows high level of contamination during pre-monsoon (58.3% sampling sites) and post-monsoon (45.8% sampling sites) in majority of sampling sites. Further, application of multivariate statistical analysis ascertains that the PTEs in groundwater are majorly derived from anthropogenic activities such as open-cast mining, thermal power plants, iron and steel().,-volV) (01234567 89().,-volV) industries, sponge iron and other metallurgical industries , and leachate from urban and industrial wastes along with limited contribution from geogenic and lithogenic sources. The health risk assessment demonstrates that the non-carcinogenic risk (due to PTEs) in adults is in the sequence of Cr [ Cd [ Pb [ Fe [ Cu [ Zn, while for children the order is Cr [ Pb [ Cd [ Fe [ Cu [ Zn for both the seasons. The results also reveal higher chance of occurrence of carcinogenic risk due to Cr (ILCR [ 1.0E-04) for children and adults in both the seasons.
Local graph symmetry groups act in a non-identical fashion on just a proper (local) subset of a graph’s vertices, and consequent theorems for adjacency matrices simplify eigen-solutions. These theorems give a way to deal with a hierarchy of local sub-symmetries, such as are manifested by so-called “dendrimers”, which are (highly) branched polymers obtainable at a given generation number r from the polymer at the preceding generation number (r − 1) by connecting d copies of new branching monomer units to each end-unit of this preceding tree-like dendrimer, the initial generation number r = 1 consisting of a single monomer unit connected to d others. Our local symmetry methodology leads to an (essentially) analytic eigen-solution for the Bethe tree case, with the branching units just single sites—but further there result novel (qualitatively distinctive) features: eigenvector localization and eigenvalue clumping. Moreover, these novel characteristics persist for more general “dendrimers”, here considered and illustrated in the context of electronic structure of conjugated-carbon π-networks. The overall view here is of a systematic development and characterization for such dendrimer polymers paralleling some aspects of the standard development and characteristics for linear-chain benzenoid polymers—for instance, that of plotting eigen-energies as a function of symmetry. Clumping of eigen-spectra, and localization features in dendrimer eigenfunctions occur and are examined.
Modern human civilization has suffered from the disastrous impact of COVID-19, but it teaches us the lesson that the environment can restore its stability without human activity. The government of India (GOI) has launched many strategies to prevent the situation of COVID-19, including a lockdown that has a great impact on the environment. The present study focuses on the analysis of PM2.5 concentration levels in pre-locking, lockdown, and unlocking phases across ten major 10 cities of Maharashtra (MH) that were the COVID hotspot of India during the COVID-19 outbreak; Phase-wise and year-wise (2018-2020) hotspot analysis, box diagram and line graph methods were used to assess spatial variation in PM2.5 across MH cities. Our study showed that The PM2.5 concentration level was severe at pre lockdown stage (January- March) and it decrease dramatically at the lockdown stage, later it also increase in its previous position at the unlocking stages i.e. PM2.5 decreased dramatically (59%) during the lockdown period compared to the pre-lockdown period due to the shutdown of outdoor activities. It returns to its previous position due to the unlocking situation and increases (70%) compared to the lockdown period which illustrated the ups and downs of PM2.5 and ensures the position of different cities in the AQI categories at different times. In the pre-lockdown phase maximum PM2.5 concentration was in NAV (358) and MUM (338), PUN (335), NAS (325) subsequently whereas at the last of the lockdown phase it becomes CHN (82), NAG (76), and SOL (45) subsequently. Hence, the restoration of the environment during the lockdown phase was temporary rather than permanent. Therefore, our findings propose that several effective policies of government such as relocation of polluting industries, short-term lockdown, odd-even vehicle number, installation of air purifiers, and government strict initiatives are needed in making a sustainable environment. Keywords: PM2.5; Sustainable; Hotspot; lockdown; COVID-19
We study the impact of local dynamics on the appearance of chimera patterns in coupled oscillators. For this we introduce a control parameter that explicitly changes the local dynamics from a van der Pol (vdP) to a hybrid oscillator. It is well established that in vdP oscillators only amplitude mediated chimeras occur, however, remarkably, we show that as we go from vdP to hybrid oscillator, both amplitude mediated chimeras and amplitude chimeras appear in the network. Moreover, for a wide range of control parameter, we have identified stable amplitude chimeras induced by the interplay of the control parameter and coupling strength. Through Floquet theory and numerical measures, we provide support for our findings. Apart from the impact of local dynamics, for the first time, our study demonstrates the appearance of chimeras in hybrid oscillators, which are widely used to model robotic limb movement and pedestrian dynamics.
Mechanistic understanding of enzymatic activation and transformation of small molecules to value added product(s), is a long-term challenge in biological and energy-related chemistry. In this chapter we assess our research contributions illustrating the prospects of the Ru(edta) complexes (edta4 − = ethylenediaminetetraacetate) as potential model for rational understanding the role of the metalloenzymes that efficiently catalyze the transformation of small molecules to value added product(s). The current research contributions compiled herein, reveal the enzyme mimicking ability of Ru(edta) complexes pertaining to the reduction of O2 to H2O2, reduction of CO2 to HCOOH, oxidation and S-nitrosylation of biological thiols, and cross-talk between NO and H2S. These processes are conversed in more details, highlighting the mechanistic aspects of the aforementioned reactions that occur in nature, and are catalyzed by active sites of metalloenzymes. An overview of the advancement in this research and prospect of such complexes in bio-mimetic activation of small molecules is presented herein.
Recently, the government of India has promulgated a sudden move of demonetisation. Such move can be considered as a type of forced formalization. Porta and Shleifer (2014) deals with the issue of formal informal interactions and comes out with an interesting conclusion. The informal sector does not merely exist for taking advantage of legal loopholes. Even if these loopholes are somehow stitched, the informal sector will not become formal. The clue perhaps lies in an old view expressed by Chayanov that in certain circumstances an informal sector can outperform a modern capitalist sector. This paper is a modest attempt to include this clue in a formal model of the simplest possible type that tries to unravel the relation between formal and informal sector as also the consequences of policies that leads to forced formalisation.
Regulation of oxidative stress towards origin of favorable internal redox cue plays a decisive role in salinity stress acclimation and least studied in rice and hence is the subject of present investigation. Redox landscaping of seedlings of ten experimental land races of rice of coastal Bangladesh grown under post imbibitional salinity stress (PISS) has been done through characterization of ROS-antioxidant interaction dynamics at metabolic interface, transcriptional reprogramming of redox-regulatory genes along with the assessment of biomarkers of oxidative threat for standardizing redox strategies and quality parameters for screening. The results exhibited a strong correlation between salinity induced redox status (pro-oxidant/antioxidant ratio, efficacy of H2O2 turnover through integrated RboH-Ascorbate–Glutathione/Catalase pathway and estimation of sensitive redox biomarkers of oxidative deterioration) and germination phenotypes of all landraces of rice. Transcript abundance of the marker genes of the enzymes associated with central antioxidant hub for H2O2 processing (CatA, OsAPx2, SodCc2, GRase and RboH) of all experimental landraces of the rice advocate the central role of H2O2 turnover dynamics in regulating redox status and salinity tolerance. Landraces suffering greater loss of abilities of decisive regulation of H2O2 turnover dynamics exhibited threat on the oxidative windows of the germinating seeds under salinity.
The ideal condition of earthworm gut promotes growth and multiplication of beneficial soil microorganisms eliminating pathogens and converts organic wastes into nutrients rich compost. The present study has been carried out to determine the population dynamics of earthworm gut bacteria and to find out relative abundance of different functional bacterial groups in the foregut, midgut, and hindgut of earthworm Perionyx excavatus. To assess bacterial diversity, a viable plate count method was adopted. In the different gut region of earthworm, aerobic heterotrophic, amylolytic, Bacillus, Gram-negative, proteolytic, fat hydrolyzing, nitrate-reducing, nitrifying, asymbiotic nitrogen-fixing, Azotobacter, and phosphate solubilizing bacterial populations ranged from 22.2 to 241.6 × 10⁶, 8.0 to 171.60 × 10⁶, 1.83 to 2.79 × 10⁶, 10.68 to 23.04 × 10⁴, 3.70 to 5.52 × 10⁴, 59.60 to 208.40 × 10⁴, 1.86 to 7.34 × 10⁴, 10.94 to 19.78 × 10⁴, 0.80 to 3.42 × 10⁴, 7.83 to 13.70 × 10⁴, 1.31 to 2.67 × 10⁴ cfu/ml gut suspension, respectively. The results of the one-way ANOVA revealed that the bacterial load of most of the bacterial groups was significantly higher (p < 0.05) in the hindgut region, followed by midgut and foregut. Only the density of the proteolytic group was significantly higher (p < 0.05) in the midgut region followed by foregut and hindgut. Starch hydrolyzing bacteria constitute the largest group of bacteria in the gut content. From principal component analysis, two components were extracted with the eigenvalues of 8.485 and 1.132. Agglomerative hierarchical cluster analysis revealed that the bacterial populations were clustered into four different groups. Quantitative variation among bacterial groups in earthworm’s gut seems to determine the soil health and composting efficiency; from this point of view, the present study will provide a better understanding about different functional bacterial groups of earthworm’s guts and might be helpful in sustainable agriculture and waste management.
Malaria is a serious vector borne disease transmitted by different species of Anopheles mosquitoes. The present study was aimed to isolate and characterize the bacterial flora from the gut of larvae of An. subpictus Grassi (1899) prevalent in Hooghly and explore their roles in host survival and development. Mosquito larvae and adults were collected from field and were maintained in laboratory. Bacterial load in the larval mid-gut was determined, and predominant strains were isolated and characterized by polyphasic approach. Role of these bacteria in larval survival and development were assayed. Bacterial load in the gut of larvae was found to vary in field-collected and lab-reared mosquitoes in different seasons. Morphological, bio-chemical, and molecular analyses explored four common bacterial isolates, namely Bacillus subtilis, Bacillus pumilus, Bacillus cereus, and Proteus vulgaris in the larval gut throughout the year. Larval survival rate was greatly reduced (0.06) and time of pupation was prolonged (17.8 ± 0.57) [days] in the absence of their gut bacteria. Total tissue protein (7.78 ± 0.56) [µg/mg], lipid (2.25 ± 0.19) [µg/mg] & carbohydrate (16.5 ± 0.79) [µg/mg] contents of larvae, and body weight & wing length of adult male (0.17 ± 0.02 & 1.74 ± 0.43) [mm] & female (0.19 ± 0.02 & 1.99 ± 0.46) [mm] mosquitoes were also found to be greatly reduced in the absence of gut bacteria. Developmental characteristics were restored with the introduction of culture suspension of all four resident gut bacterial isolates. Present study indicates that the mosquitoes largely depend on their gut bacteria for their survival and development. So, manipulation or control of this gut bacterial communities might inhibit survival and development of vector mosquitoes.
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