Phenotypic and genetic characterization of unexplored, potential cattle population of Madhya Pradesh.

Bawri or Garri, a non-descript cattle population managed under an extensive system in Madhya Pradesh state of India, was identified and characterized both genetically and phenotypically to check whether or not it can be recognised as a breed. The cattle have white and gray colour and are medium sized with 122.5 ± 7.5 cm and 109.45 ± 0.39 cm height at withers in male and female, respectively. Double-digest restriction site associated DNA (ddRAD) sequencing was employed to identify ascertainment bias free SNPs representing the entire genome cost effectively; resulting in calling 1,156,650 high quality SNPs. Observed homozygosity was 0.76, indicating Bawri as a quite unique population. However, the inbreeding coefficient was 0.025, indicating lack of selection. SNPs found here can be used in GWAS and genetic evaluation programs. Considering the uniqueness of Bawri cattle, it can be registered as a breed for its better genetic management.

Molecular and genetic diversity in isolates of Trypanosoma evansi from naturally infected horse and dogs by using RoTat 1.2 VSG gene in Madhya Pradesh, India.

BACKGROUND: Trypanosoma evansi is a protozoan parasite that can infect a wide range of animals and is widespread around the world. In this study, we analyzed four fatal cases of T. evansi infection using clinical, parasitological, and molecular approaches. We also explored the genetic diversity, demographic history, and population-genetic structure of T. evansi using available Rode Trypanozoon antigenic type (RoTat) 1.2 gene sequences. METHODS AND RESULTS: Clinical findings of infected animals revealed high fever, anemia, weakness, and anorexia. The animals were treated with diminazene aceturate, which was moderately effective, and hematobiochemical parameters showed changes in hemoglobin and glucose levels. The molecular and genetic diversity of T. evansi was analyzed using the RoTat 1.2 VSG gene. Phylogenetic and haplotype analysis revealed two distinct clusters of T. evansi circulating in India. The genetic diversity indices, neutrality tests, gene flow, and genetic differentiation outcomes confirmed the genetic diversity of the T. evansi population, with a lack of uniformity. The identification of two distinct clusters, exhibiting differential demographic histories and evolutionary forces, implies that the clusters may have undergone independent evolutionary trajectories or experienced different environmental pressures. CONCLUSION: The present findings underlined the need of an early and precise diagnosis in order to treat and control T. evansi infections, and the RoTat 1.2 VSG gene is an important genetic marker for understanding the genetic diversity and evolutionary history of T. evansi. This knowledge can be used to create tailored strategies to control and manage the infection in an endemic region.

Flood risk assessment in the Karamana river basin, Kerala, using HEC-RAS.

The State of Kerala has frequently been facing a series of flooding phenomena that have adversely affected its multiple sectoral growths. The floods of 2018 have happened to be one of the most devastating floods that have occurred in the State of Kerala. It was seen that nearly thirteen out of fourteen districts in Kerala were tremendously affected during the 2018 August floods. The worst affected districts during the 2018 floods were Trivandrum, Pathanamthitta, Idukki, Thrissur, Ernakulam, and Kottayam. A sub-region near the Karamana basin located in the Trivandrum district is considered for the present study. The Karamana sub-region is a highly urbanized area that is also more or less prone to intense riverine flooding. The major rivers-Karamana and Killi-along with their respective tributaries, are the water bodies in the study region. Extensive urbanization, along with the overflowing of rivers during monsoon seasons, has paved the way for intense flooding in the region. This, in turn, necessitates developing a flood model for the sub-region. The development of an efficient flood model will aid in understanding the future challenges related to a flooding event in a region. In this study, the flood return probability water levels for the 5-year, 10-year, 25-year, 50-year, 100-year, 250-year, and 500-year were estimated for the Karamana sub-region. Besides, the flood risk zoning for the study area was conducted and elaborated as very high risk, high risk, moderate risk, and low risk for the different areas of the sub-region. Overall, the study can be helpful in identifying the most vulnerable areas to flooding in the Karamana region. By the proper identification of vulnerable areas in the region, proper planning and early warning measures can be devised and carried out by policymakers.

Use of machine learning-based classification algorithms in the monitoring of Land Use and Land Cover practices in a hilly terrain.

The current high rate of urbanization in developing countries and its consequences, like traffic congestion, slum development, scarcity of resources, and urban heat islands, raise a need for better Land Use Land Cover (LULC) classification mapping for improved planning. This study mainly deals with two objectives: 1) to explore the applicability of machine learning-based techniques, especially the Random forest (RF) algorithm and Support Vector Machine (SVM) algorithm as the potential classifiers for LULC mapping under different scenarios, and 2) to prepare a better LULC classification model for mountain terrain by using different indices with combination of spectral bands. Due to differences in topography, shadows, spectral confusion from overlapping spectral signatures of different land cover types, and a lack of access for ground verification, classification in mountainous terrain is difficult task compared to plain terrain classification. An enhanced LULC classification model has been designed using two popular machine learning (ML) classifier algorithms, SVM and RF, explicitly for mountainous terrains by taking into consideration of a study area of Gopeshwer town in the Chamoli district of Uttarakhand state, India. Online-based cloud platform Google Earth Engine (GEE) was used for overall processing. Four classification models were built using Sentinel 2B satellite imagery with 20m and 10m resolutions. Two of these models (Model 'i' based on RF algorithm and Model 'ii' based on SVM algorithm) were designed using spectral bands of visible and infrared wavelengths, and the other two (Model 'iii' based on RF algorithm and Model 'iv' based on SVM algorithm) with the addition of indices with spectral bands. The accuracy assessment was done using the confusion matrix based on the output results. Obtained result highlights that the overall accuracy for model 'i' and model 'ii' were 82% and 86% respectively, whereas these were 87.17% and 87.2% for model 'iii' and model 'iv' respectively. Finally, the study compared the performance of each model based on different accuracy metrics for better LULC mapping. It proposes an improved LULC classification model for mountainous terrains, which can contribute to better land management and planning in the study area.

Assessment of snout analysis of Himalayan glaciers: impact studies on Pindari, Kafni, Sundardhunga, and Baljuri base camp glaciers.

There are several causes for the increasing rate of deglaciation, such as global warming, increase in the concentration of black carbon, and extensive use of fossil fuels which causes the change in the overall climate system and shifting glacier ecosystem. This study was conducted on Pindari valley glaciers part of lesser Himalaya in Uttarakhand. This study investigates to (1) monitor and map change in the frontal length or the snout region of a glacier that can be studied with the help of remote sensing techniques and (2) evaluate the decadal and annual retreat rate of the glacier from 1972 to 2018. The study applies both the maximum likelihood classifier and NDSI spectral indices based classification for extracting the glacier region for different periods. This study reveals a significant amount of retreats taking place in the selected glaciers, Pindari, Sundardhunga, Kafni, and Baljuri base camp glaciers, from 1972 to 2018 as 1719.95 m, 1751.21 m, 1057.01 m, and 810.78 m, respectively. The highest amount of change is noticed in Pindari and Sundardhunga glaciers, higher than ~ 1700 m. The study analyses temporal variation of the annual and decadal retreat rate in the Pindari valley glaciers, which would be helpful for the further study of the other glaciers.

Application of remote sensing in alpine grasslands cover mapping of western Himalaya, Uttarakhand, India.

Grasslands are the world's most extensive terrestrial ecosystem, which provides a variety of services for humans, such as carbon storage, food production, crop pollination, pest regulation, and are a major feed source for livestock. However, grasslands are today one of the most endangered ecosystems due to land-use change, agricultural intensification, land abandonment, as well as climate change. Grasslands are an integral part of human societies across the globe, which are broadly known as tropical savannah and temperate grasslands. In the Himalayan region, grasslands are found in more than 55% of the area and different climatic conditions lead to different varieties of grasslands like Danthonia grasslands, kobresia sedge meadow, etc. Grasslands deal with the spatial and temporal distribution of heterogeneous landscapes, which support a high diversity of various species. Owing to very rugged terrain and inaccessibility, the information on the extent of alpine grassland and percent grass cover (%) across the meadows is limited. Therefore, the present attempt was made to assess the current status of grassland in the alpine region of Uttarakhand above 3000 m asl. LANDSAT-8 (OLI and TIRS sensors) satellite data were used to delineate the grasslands using normalized difference vegetation indices (NDVIs) of the alpine region with the help of over 179 ground truth points out of which 50 points are testing points and 129 points are training points. Grass covers (%) were also assessed in the whole alpine region of Western Himalaya of Uttarakhand which nearly consists of over 75 meadows by using random plots (1 × 1 m, total 10 per site) in each meadow. Overall, 89.52% accuracy was achieved based on 50 randomly selected testing points. A total of 4949.25 sq. km area is under the different percentage of grass cover in the alpine region of Uttarakhand, Western Himalaya. Danthonia grasslands below 4000 m and Kobresia sedge meadows above 4000 m elevation are dominant in the state. In the alpine region, over 1056 sq. km grassland area have less than 10% grass cover indicating higher degraded and cold desert areas and only 565.69 sq. km area have more than 60% grass cover, which is highly favorable for rich biodiversity and grazing.

Effect of cumulus cells of cumulus-oocyte complexes on in vitro maturation, embryonic developmental and expression pattern of apoptotic genes after in vitro fertilization in water buffalo (Bubalus bubalis).

In the present study, the potential of different grades of cumulus-oocyte complexes (COCs) for in vitro maturation (IVM) and embryonic development was assessed. Further, the association of the expression pattern of anti-apoptotic Mcl-1 and pro-apoptotic Bax genes in embryonic development was analyzed. Abattoir derived oocytes were graded into grade A and B based on surrounding cumulus rings. Out of 1050 ovaries, a total number of 770 and 1360, were of grade A and B COCs, respectively, were aspirated. After IVM, grade A COCs had a significantly higher number of polar bodies (92.04 ± 0.60%) as compared to grade B (85.88 ± 0.46%). On IVF and embryo culture, grade A COCs produced the significantly higher rate of cleavage and blastocyst (90.44 ± 0.71% and 41.55 ± 0.96%) as compared to grade B COCs (79.77 ± 0.76% and 30.44 ± 0.96%). The transcriptional analysis of apoptotic genes expression by Real-time PCR revealed a significantly higher expression of Mcl-1 gene in embryos of grade A as compared to grade B, whereas, the relative expression of Bax gene was down-regulated in grade A than grade B embryos. Thus it was concluded that the pattern of apoptotic genes expression in early-stage embryos can be used as a marker gene to predict the developmental competence of COCs.

Managing water quality of a river using an integrated geographically weighted regression technique with fuzzy decision-making model.

In the recent times, water quality of most of the rivers in India has been steadily degrading due to increasing numbers of point and non-point sources of pollution. The tremendous increase in population, rapid urbanization, change in irrigation patterns, and unplanned growth of industries without proper enforcement of environmental standards are some of the major causes for poor quality of river water. In addition, unpredictable and scanty rainfall is resulting in uncertain natural stream flow which further leads to uncertainty in assessing and predicting the quality of river water. This paper deals with the assessment of the overall status of water quality of a river by developing a fuzzy-based water quality evaluation system. The quality of water needed for different beneficial uses is based on the value of various parameters. Since the quality attributes of the parameters are fuzzy in nature, they have been described by the linguistic variables. The water quality index of each specific site is then calculated by aggregating the attributes with respect to their degree of importance, which is also expressed in the form of linguistic terms. Finally, a case study of the river Yamuna has been carried out to evaluate the fuzzy comprehensive water quality index (FCWQI). In this study, the FCWQI has been determined only for the use of water for drinking purposes though this model can be applied for other uses as well. The FCWQI developed herein is based on an integrated approach, which clearly describes the overall state of the water quality by a single rational number. Spatial and parametric sensitivity of the FCWQI model of the river basin is also determined using GIS-based geographically weighted regression technique. The methodology suggests a novel way of introducing parametric sensitivity in defining water quality indices used for surface water quality assessment.

Holistic approach for quantification and identification of pollutant sources of a river basin by analyzing the open drains using an advanced multivariate clustering.

Global scarcity of freshwater has been gearing towards an unsustainable river basin management and corresponding services to the humans. It needs a holistic approach, which exclusively focuses on effective river water quality monitoring and quantification and identification of pollutant sources, in order to address the issue of sustainability. These days, rivers are heavily contaminated due to the presence of organic and metallic pollutants released from several anthropogenic sources, such as industrial effluents, domestic sewage, and agricultural runoff. It is astonishing to note that even in many developing countries, most of these contaminants are carried through open drains, which enter river premises without proper treatment. Such practice not only devastates riverine ecosystem but also gives rise to deadly diseases, such as minimata and cancer in humans. Considering these issues, the present study develops a novel approach towards simultaneous identification of major sources of pollution in the rivers, along with critical pollutants and locations using an advanced hierarchical cluster and multivariate statistical analysis. A systematic approach has been developed by agglomerating both R-mode and Q-mode analysis, which develops monoplots, two-dimensional biplots, rotated component matrices, and dendrograms (using "SPSS" and "Analyse It" software) to reveal relationships among various quality parameters to identify the pollutant sources along with clustering of critical sampling sites and pollutants. A case study of the Ganges River Basin of India has been considered to demonstrate the efficacy and usefulness of the model by analyzing 85 open drains. Both organic and metallic pollutants are analyzed simultaneously as well as separately to get a holistic understanding of all the relationships and to broaden the perspective of water characterization. Results provide a comprehensive guidance to the policy makers and water managers to optimize corrective efforts, minimize further damage, and improve the water quality condition to ensure sustainable development of the river basin.

Impact assessment of fly ash on ground water quality: An experimental study using batch leaching tests.

The fly ash, generated at the coal-based thermal power plant, is always a cause of concern to environmentalists owing to its adverse impact on air, water and land. There exists a high environmental risk when it is disposed to the environment. Thus, two different type of fly ash samples (FA-1 and FA-2) have been considered in this study to examine the leaching potential of the elements magnesium, aluminium, silicon, calcium, titanium, vanadium, chromium, manganese, iron, nickel, cobalt, copper, zinc, arsenic, selenium, strontium, cadmium, barium and lead for different types of leachant. Toxicity characteristics leaching procedure and ASTM tests have been performed in the laboratory to simulate different natural leaching scenarios. Characterisation of samples have been done through X-ray diffraction and field emission gun scanning electron microscope. The effect of different liquid to solid ratios (i.e. 5, 10, 20 and 50) on the mobilisation of elements has been analysed. The results indicated that the maximum leaching of all elements occurred at a liquid to solid ratio of 5 except for arsenic, barium and silicon. The groundwater analysis has also been done to understand the actual effects of leachate. The elements presenting the highest leachability in the two fly ash samples under all tested conditions were magnesium, aluminium, silicon and calcium. It has been observed that calcium exhibits greater leaching effects than all other constituents. The study presented here has been found very useful for assessing contamination levels in groundwater owing to leaching effects of fly ash under different scenarios, which can be helpful to prevent spreading of the contaminants by efficient management of fly ash.

Studies on ontogeny and reproductive behaviour of Lepisorus nudus (Hook.) Ching (Polypodiaceae).

In-vitro studies of the ontogeny and mating system of the gametophytes of Lepisorus nudus were carried out through multispore and isolate cultures lasting 23 weeks. Spore germination begins early, on day 5-6. Spore germination pattern was Vittaria type and the germination percentage reached 82.69% (± 3.20%). Filamentous gametophyte did not branch and never produce separate prothalli. Occasionally the branching and separate prothalli were produced from mature and cordate gametophytes. Prothallial development was Drynaria type (cordate gametophytes with notched apex) contrary to other known species of Lepisorus, where gametophyte development was Kaulinia type (strap gametophytes without apical notch). Gametophyte production in multispore cultures reached up-to 75.6% (± 18.85%). All isolates initially produced archegonia and antheridia only after a prolonged cessation of production in archegonia. In contrast, only 37.2% (±12.63%) of individuals in multispore culture exhibited the same pattern with 29.8% (±7.56%) developing as males that did not produce archegonia by the end of the study. Only 37.2% (±12.63%) of archegoniate gametophytes developed antheridia by the end of the study and only once archegonia had degenerated; i.e., a temporal gap existed in expression of female and male gametangia. In multispore culture, only 26.21% (±5.70%) sporophytes developed on 160th day by fusion of female and male gametes that were derived from matings between sib gametophytes. In contrast, isolated gametophytes did not produce sporophytes. In isolate gametophytes, mature archegonia could not take delivery of male gametangia because antheridia were produced sequentially. This study suggests that the sequential expression of gametangia and absence of the intragametophytic selfing may also be a possible cause of reproductive barriers. Lepisorus nudus promotes inter-gametophytic selfing as an adaptive mechanism for reproductive success in multispore culture. This study presents a detailed account on reproductive biology of the taxa whose population is decreasing at distressing rate.

Development of a HEC-HMS-based watershed modeling system for identification, allocation, and optimization of reservoirs in a river basin.

One of the primary objectives of river basin planning and management is to assess the behavior of the river towards man-made and natural changes. In recent times, the self-purifying capacity of the river is found to be substantially affected because of extensive use of water for agricultural and industrial purposes. Any variation in the flow regime of a river poses a severe impact on the aquatic ecosystem, which affects its self-purifying capacity. Diverting river water for industrial and agricultural uses through dams and barrages reduces the natural flow rate of the river. The present study develops a novel approach by coupling Watershed Modeling System (WMS ver. 10.1) with linear optimization to provide an alternate means of water supply for such users. To explain the effectiveness of the model, a case study on the Ganges river basin of India has been considered. The ecosystem of the Ganges provides such a magnificent biological fabric, that its self-purifying capacity exceeds that of any other river water across the globe. However, the industries found in the river's most polluted stretch consume around 1200 million liters of water every day. In addition, 80% of the river water diverts at Narora barrage for agricultural purposes. As a result, the flow of the river in dry seasons is as less as 300 m3/s. The study suggests the need to develop economically feasible and efficient storage reservoirs to store the rainwater, which can be used to supply industrial and agricultural needs. The WMS software is used to acquire the watershed basin, outlet location, simulated runoff volume, proposed reservoir site, and the hydrograph using the monitored rainfall data of 5 years (2010-2014). The simulated runoff volume is then used to develop an optimization model to determine the required capacity of each reservoir using LINGO software (ver. 16.0). Four different storage reservoirs are proposed in the selected industrial sites of Unnao district, Uttar Pradesh, India. These reservoirs can supply the needs of industries, and thus reducing their dependency on the river Ganges. The model developed herein acts as an effective tool for giving a possible solution to large-scale water supply problems in the river basins, and also guides the decision makers towards restoring the stream flow.

Assessment of air quality in Haora River basin using fuzzy multiple-attribute decision making techniques.

This paper deals with assessment of air quality in Haora River basin using two techniques. Initially, air quality indices were evaluated using a modified EPA method. The indices were also evaluated using a fuzzy comprehensive assessment (FCA) method. The results obtained from the fuzzy comprehensive assessment method were compared to that obtained from the modified EPA method. To illustrate the applicability of the methodology proposed herein, a case study has been presented. Air samples have been collected at 10 sampling sites located along Haora River. Six important air pollutants, namely, carbon monoxide, sulfur dioxide, nitrogen dioxide, suspended particulate matter (SPM), PM10, and lead, were monitored continuously, and air quality maps were generated on the GIS platform. Comparison of the methodologies has clearly highlighted superiority and robustness of the fuzzy comprehensive assessment method in determining air quality indices under study. It has effectively addressed the inherent uncertainties involved in the evaluation, modeling, and interpretation of sampling data, which was beyond the scope of the traditional weighted approaches employed otherwise. The FCA method is robust and prepares a credible platform of air quality evaluation and identification, in face of the uncertainties that remain eclipsed in the traditional approaches like the modified EPA method. The insights gained through the present study are believed to be of pivotal significance in guiding the development and implementation of effective environmental remedial action plans in the study area.

Effect of varying hydrologic regime on seasonal total maximum daily loads (TDML) in an agricultural watershed.

Rising hypoxia due to the eutrophication of riverine ecosystems is primarily caused by the transport of nutrients. The majority of existing TMDL models cannot be efficienty applied to represent nutrient concentrations in riverine ecosystems having varying flow regimes due to seasonal differences. Accurate TMDL assessment requires nutrient loads and suspended matter estimation under varying flow regimes with minimal uncertainty. Though a large database can enhance accuracy, it can be resource intensive. This study presents the design of an innovative modeling strategy to optimize the use of existing datasets to effectively represent streamflow-load dynamics while minimizing uncertainty. The study developed an approach to assess TMDLs using six different flux models and kriging techniques (i) to enhance the accuracy of nutrient load estimation under different hydrologic regimes (flow stratifications) and (ii) to derive an optimal modeling strategy and sampling scheme for minimizing uncertainty. The flux models account for uncertainty in load prediction across varying flow strata, and the deployment of multiple load calculation procedures. Further, the proposed flux approach allows the determination of load exceedance under different TMDL scenarios aimed at minimizing uncertainty to achieve reliable load predictions. The study employed a 10-year dataset (2009-2018) consisting of daily flow data (m3/sec) and weekly data (mg/L) for nitrogen (N), phosphorus (P) and total suspended solids (TSS) concentrations in three distinct agricultural sites in+ the Minnesota River Watershed. The outcomes were analyzed geospatially in a Geographic Information System (GIS) environment using the kriging interpolation technique. The study recommends (i) triple stratification of flows to obtain accurate load estimates, and (ii) an optimal sampling scheme for nitrogen and phosphorous with 30.6 % and 49.8 % datapoints from high flow strata. The study outcomes are expected to contribute to the planning of economically and technically sound combinations of best management practices (BMPs) required for achieving total maximum daily loads (TMDL) in a watershed.

Fecal sludge characterization, treatment, and resource recovery options: a state-of-the-art review on fecal sludge management.

A rise in population and urbanization demanded that a robust fecal sludge management (FSM) value chain be used to restructure the sanitation system throughout the world securely. A significant global need exists to adopt efficient and sustainable FSM. On-site sanitation systems (OSS) produce fecal sludge (FS). FS is produced when excreta and blackwater are combined and stored or treated, either alone or in combination with greywater. FS can be semisolid or slurry and raw or partially digested. Critical examination of FS characteristics, i.e., biochemical oxygen demand (BOD), chemical oxygen demand (COD), total solids (TS), and pathogen count, varies from 600-56,836 mg/l, 6656 to 201,200 mg/l, 830-123,000 mg/l, and 105 to 109 E. coli/l of FS respectively. Helminth eggs range from 2500-25,000/l of FS. Public health and the environment are negatively impacted by septic tank overflows and the careless discharge of FS into open spaces affecting groundwater quality, water bodies, irrigation fields, open drains, places outside villages, etc. Thus, deciding on a proper treatment technology for FS before discharging it into open land or reusing FS is essential to create a pollution-free environment. This paper highlights the practices adopted for FSM under its different processes, such as collecting, characterization, treating, and reusing of on-site FS and bibliometric analysis on documents on fecal sludge. A thorough analysis has been carried out by reviewing all important literature available globally.

Removal of COD and color from textile industrial wastewater using wheat straw activated carbon: an application of response surface and artificial neural network modeling.

A novel approach has been undertaken wherein chemically modified wheat straw activated carbon (WSAC) as adsorbent is developed, characterized, and examined for the removal of COD and color from the cotton dyeing industry effluent. Thirty experimental runs are designed for batch reactor study using the central composite method (CCM) for optimizing process parameters, namely biochar dose, time of contact, pH, and temperature, for examining the effect on COD and color-removing efficiency of WSAC. The experimental data have been modeled using the machine learning approaches such as polynomial quadratic regression and artificial neural networks (ANN). The determined optimum conditions are pH: 7.18, time of contact: 85.229 min, adsorbent dose: 2.045 g/l, and temperature: 40.885 °C, at which the COD and color removal efficiency is 90.92 and 94.48%, respectively. The nonlinear pseudo-second order (PSO) kinetic model shows good coefficient of determination (R2 ~ 1) values. The maximum adsorption capacity for COD and color by WSAC is at the pH of 7, the temperature of 40 °C, adsorbent dose of 2 g/l is obtained at the contact time of 80 min is 434.78 mg/g and 331.55 PCU/g, respectively. The COD removal and decolorization is more than 70% in the first 20 min of the experiment. The primary adsorption mechanism involves hydrogen bonding, electrostatic attraction, n-π interactions, and cation exchange. Finally, the adsorbent is environmentally benign and cost-effective, costing 16.66% less than commercially available carbon. The result of the study indicates that WSAC is a prominent solution for treating textile effluent. The study is beneficial in reducing the pollutants from textile effluents and increasing the reuse of treated effluent in the textile industries.

Wetland functional assessment and uncertainty analysis using fuzzy α-cut-based modified hydrogeomorphic approach.

Wetlands are significant ecosystems which perform several functions such as ground water recharge, flood control, carbon sequestration, and pollution reduction. Accurate evaluation of wetland functions is challenging, due to uncertainty associated with variables such as vegetation, soil, hydrology, land use, and landscape. Uncertainty is due to the factors such as the cost of evaluating quality parameters, measurement, and human errors. This study proposes an innovative framework based on modified hydrogeomorphic approach (HGMA) using fuzzy α-cut technique. HGMA has been used for wetland functional assessment and α-cut technique is used to characterize uncertainty corresponding to the input variables and wetland functions. The most uncertain variables were found to be the density of wetlands and basin count in the landscape assessment area with the scores of 4.38% and 3.614% respectively. Among the functions, the highest uncertainty is found in functional capacity index (FCI) corresponding to water storage (1.697%) and retain particulate (1.577%). The quantified uncertainty can help the practitioners to make informed decisions regarding planning best management practices for preserving and restoring the wetland functionality.

Lytic Polysaccharide Monooxygenase Activity of Tma12 Is Critical for Its Toxicity to Whitefly.

Lytic polysaccharide monooxygenases (LPMOs) are powerful redox enzymes that transform complex carbohydrates through oxidation and make them suitable for saccharification by canonical hydrolases. Due to this property, LPMOs are considered to be a valuable component of enzymatic consortia for industrial biorefineries. Tma12 is a fern entomotoxic protein that kills whitefly and has structural similarities with chitinolytic LPMO. However, its enzymatic activity is poorly understood. Studying the role of the LPMO-like activity in the insecticidal function of Tma12 can be of considerable importance. Our results show that Tma12 preferentially binds and digests ß-chitin. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis shows that the digestion of chitin produces chitin oligosaccharides of various lengths (DP2-DP7). The Michaelis constant (km) and catalytic constant (kcat) for hydrocoerulignone are 0.022 mM and 0.044 s-1, respectively. The attenuation of catalytic activity through diethylpyrocarbonate modification abolishes the insecticidal activity of the protein. Our findings reveal that (a) Tma12 is an active LPMO and (b) LPMO activity is indispensable for its function as a bioinsecticide.

Phase III Pivotal comparative clinical trial of intranasal (iNCOVACC) and intramuscular COVID 19 vaccine (Covaxin®).

One of the most preferable characteristics for a COVID-19 vaccine candidate is the ability to reduce transmission and infection of SARS-CoV-2, in addition to disease prevention. Unlike intramuscular vaccines, intranasal COVID-19 vaccines may offer this by generating mucosal immunity. In this open-label, randomised, multicentre, phase 3 clinical trial (CTRI/2022/02/40065; ClinicalTrials.gov: NCT05522335), healthy adults were randomised to receive two doses, 28 days apart, of either intranasal adenoviral vectored SARS-CoV-2 vaccine (BBV154) or licensed intramuscular vaccine, Covaxin®. Between April 16 and June 4, 2022, we enrolled 3160 subjects of whom, 2971 received 2 doses of BBV154 and 161 received Covaxin. On Day 42, 14 days after the second dose, BBV154 induced significant serum neutralization antibody titers against the ancestral (Wuhan) virus, which met the pre-defined superiority criterion for BBV154 over Covaxin®. Further, both vaccines showed cross protection against Omicron BA.5 variant. Salivary IgA titers were found to be higher in BBV154. In addition, extensive evaluation of T cell immunity revealed comparable responses in both cohorts due to prior infection. However, BBV154 showed significantly more ancestral specific IgA-secreting plasmablasts, post vaccination, whereas Covaxin recipients showed significant Omicron specific IgA-secreting plasmablasts only at day 42. Both vaccines were well tolerated. Overall reported solicited reactions were 6.9% and 25.5% and unsolicited reactions were 1.2% and 3.1% in BBV154 and Covaxin® participants respectively.

Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds.

Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, 'hydro-conditioning' employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated. Parallel processing of both hDEMs revealed that 'ground truthing' plays a critical role in the accurate placement of breach lines for allowing water movement through digitally elevated surfaces. Outcomes guide the practitioners in selecting appropriate hDEM (manual or automated) depending on the complexity of modeled hydrological pathways, which is essential for planning BMPs in a cost-effective manner at different spatial scales. Modeling results show that hDEMs greatly influence hydrological connectivity, catchment boundaries, BMP locations, treatment capacities, and related costs. The accuracy of hDEMs was verified using a robust sub-basin scale validation approach. The study recommends a hybrid approach for utilizing the strengths of both, automated and manual hDEMs for efficient agricultural farm pollution in an economical manner.