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In this work, a newly discovered biomedical grade Magnesium–Lithium–Strontium (Mg–Li–Sr) alloy is machined using electrochemical machining technology. Two main output constraints employed on the research project to evaluate machinability are surface roughness (Ra) and material removal rate (MRR). Changing feed rate (FR), current, electrolyte concentration (EC), and voltage is required in order to carry out experimental experiments. The trials were designed using the Taguchi method. The ANOVA findings show that current is the most significant factor, after voltage as the most significant input parameter in regulating Ra and MRR. The ideal parameter configuration for the CRITIC-linked Deng’s similarity approach method was 5 V, 1 A of current, 0.4 mm/min of FR, and 20 g/l of EC. The final product was a 0.0323 mm/min MRR and a 2.61 μm surface roughness. Furthermore, the response variables are anticipated using the adaptive neuro-fuzzy Inference System, which finally results in predictions that are very similar to the experimental results.

The aim of this study is to discover the potential use of nutraceutical industrial cumin seed spent (NICUS) as an economical biosorbent for eliminating acid blue 113 (AB113), an azo dye, from water. The study investigates the influence of pH, adsorbent dosage, temperature, particle size, and initial dye concentration on the adsorption of AB113. Various isotherm models and kinetic models were studied. At equilibrium situations, the maximum trial adsorption volume (qe) was found to be 96 mg g−1. The main objective was to determine the suitability of the pseudo-second-order model for describing the kinetics of adsorption. Thermodynamic parameters ΔG0 ΔH0 ΔS0 revealed that the adsorption process was endothermic and non-spontaneous. The lower value of ΔH0 suggests a physical adsorption process. Analysis using FTIR and SEM spectra confirmed that the NICUS surface effectively adsorbed AB113. NICUS emerges as a promising adsorbent for the efficient deduction of AB113 from aqueous solutions.

Developing highly sensitive and selective non-enzymatic electrochemical biosensors for disease biomarker detection has become challenging in healthcare applications. However, advances in material science are opening new avenues for creating more dependable biosensing technologies. In this context, the present work introduces a novel approach by engineering a hybrid structure of zinc oxide nanorod (ZnO NR) modified with iron oxide nanoparticle (Fe2O3 NP) on an FTO electrode. This Fe2O3 NP-ZnO NR hybrid material functions as a nanozyme, facilitating the catalysis of cholesterol and enabling the direct transfer of electrons to the fluorine-doped tin oxide (FTO) electrode, limiting the need for costly and traditional enzymes in the detection process. This innovative non-enzymatic cholesterol biosensor showcases remarkable sensitivity, registering at 642.8 μA/mMcm2 within a linear response range of up to 9.0 mM. It also exhibits a low detection limit (LOD) of ∼12.4 μM, ensuring its capability to detect minimal concentrations of cholesterol accurately. Moreover, the developed biosensor displays exceptional selectivity by effectively distinguishing cholesterol molecules from other interfering biological species, while exhibiting outstanding stability and reproducibility. Our findings indicate that the Fe2O3 NP-ZnO NR hybrid nanostructure on the FTO electrode holds promise for enhancing biosensor stability. Furthermore, the present device fabrication platform offers versatility, as it can be adapted with various enzymes or modified with different metal oxides, potentially broadening its applicability in a wide range of biomarkers detection.

Nanotechnology provides a very good chance to research and develop multipurpose nanomaterials because of their smaller size, larger surface area, low cost, and nanoscale materials, which are auspicious tools for many biological applications. The AgVO3 nanoparticle synthesis employing plant extract has offered an eco-friendly alternative for the industry. Literature survey shows that no research has been performed on AgVO3 using jackfruit; hence, we prepared AgVO3 using jackfruit extract as a reducing agent by a simple, easy, and eco-friendly precipitation method. The characterization techniques used for synthesized AgVO3 nanoparticles were x-ray diffraction analysis, which determines the monoclinic structure of synthesized AgVO3 nanoparticles; Fourier transform infrared spectroscopy, which shows the bonding of V–O–V; and scanning electron microscopy and energy dispersive spectra (EDS), which confirm the size, shape, purity, and elemental composition. Brunauer–Emmett–Teller analysis confirms the pore size, pore volume, and surface area of synthesized AgVO3 nanoparticles, Raman studies show the crystalline property, and UV–Vis studies give information about the material’s formation and optical properties. The bandgap was calculated to be 2.54 eV. Furthermore, the photocatalytic studies show 98.14% degradation in 180 min using MB dye. We also performed scavenger studies for detection of OH· radicals and recyclability. Gram-negative (Klebsiella pneumonia and Pseudomonas aeruginosa) and gram-positive (Staphylococcus aureus and Bacillus subtilis) micro-organisms were used to determine the antimicrobial characteristics. The full analysis verifies AgVO3’s antibacterial activity against both gram-negative and gram-positive bacteria, as well as its excellent photocatalytic activities for the degradation of the organic dye methylene blue with a high degree of recyclability.

Rice blast and bacterial leaf blight, are major disease, significantly threatens rice yield in all rice growing regions under favorable conditions and identification of resistance genes and their superior haplotypes is a potential strategy for effectively managing and controlling this devastating disease. In this study, we conducted a genome-wide association study (GWAS) using a diverse set of 147 rice accessions for blast and bacterial blight diseases in replications. Results revealed 23 (9 for blast and 14 for BLB) significant marker-trait associations (MTAs) that corresponded to 107 and 210 candidate genes for blast and BLB, respectively. The haplo-pheno analysis of the candidate genes led to the identification of eight superior haplotypes for blast, with an average SES score ranging from 0.00 to 1.33, and five superior haplotypes for BLB, with scores ranging from 1.52cm to 4.86cm superior haplotypes. Among these, superior haplotypes LOC_OS12G39700-H4 and LOC_Os06g30440-H33 were identified with the lowest average blast scores of 0.00-0.67, and superior haplotype LOC_Os02g12660-H39 exhibited the lowest average lesion length (1.88 - 2.06cm) for BLB. A total of ten accessions for blast and eight accessions for BLB were identified carrying superior haplotypes were identified. These haplotypes belong to aus and indx subpopulations of five countries (Bangladesh, Brazil, India, Myanmar, and Pakistan). For BLB resistance, eight accessions from six countries (Bangladesh, China, India, Myanmar, Pakistan, and Sri Lanka) and four subpopulations (aus, ind1A, ind2, and ind3) were identified carrying superior haplotypes. Interestingly, four candidate genes, LOC_Os06g21040, LOC_Os04g23960, LOC_Os12g39700, and LOC_Os01g24640 encoding transposon and retrotransposon proteins were among those with superior haplotypes known to play a crucial role in plant defense responses. These identified superior haplotypes have the potential to be combined into a single genetic background through haplotype-based breeding for a broader resistance spectrum against blast and bacterial blight diseases.

Nitrite monitoring serves as a fundamental practice for protecting public health, preserving environmental quality, ensuring food safety, maintaining industrial safety standards, and optimizing agricultural practices. Although many nitrite sensing methods have been recently developed, the quantification of nitrite remains challenging due to sensitivity and selectivity limitations. In this context, we present the fabrication of enzymeless iron oxide nanoparticle-modified zinc oxide nanorod (α-Fe2O3-ZnO NR) hybrid nanostructure-based nitrite sensor fabrication. The α-Fe2O3-ZnO NR hybrid nanostructure was synthesized using a two-step hydrothermal method and characterized in detail utilizing x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). These analyses confirm the successful synthesis of an α-Fe2O3-ZnO NR hybrid nanostructure, highlighting its morphology, purity, crystallinity, and elemental constituents. The α-Fe2O3-ZnO NR hybrid nanostructure was used to modify the SPCE (screen-printed carbon electrode) for enzymeless nitrite sensor fabrication. The voltammetric methods (i.e., cyclic voltammetry (CV) and differential pulse voltammetry (DPV)) were employed to explore the electrochemical characteristics of α-Fe2O3-ZnO NR/SPCE sensors for nitrite. Upon examination of the sensor’s electrochemical behavior across a range of nitrite concentrations (0 to 500 µM), it is evident that the α-Fe2O3-ZnO NR hybrid nanostructure shows an increased response with increasing nitrite concentration. The sensor demonstrates a linear response to nitrite concentrations up to 400 µM, a remarkable sensitivity of 18.10 µA µM−1 cm−2, and a notably low detection threshold of 0.16 µM. Furthermore, its exceptional selectivity, stability, and reproducibility make it an ideal tool for accurately measuring nitrite levels in serum, yielding reliable outcomes. This advancement heralds a significant step forward in the field of environmental monitoring, offering a potent solution for the precise assessment of nitrite pollution.

A large quantity of water is required during the conventional curing methods. This becomes challenging in the areas facing water scarcity and for concreting work in high-rise structures. This work presents a solution for the need for concrete that does not require extra water for curing. In the proposed solution, calcium lignosulfonate in different percentages was introduced as a self-curing agent in fresh concrete. The hardened concrete with calcium lignosulfonate was cured at ambient conditions, whereas the hardened concrete without calcium lignosulfonate was submerged in water for curing. The properties of fresh and hardened concrete with and without calcium lignosulfonate are compared. The results show a continuous increase in the slump with the increase in calcium lignosulfonate. However, 0.3% calcium lignosulfonate is identified as the optimum percentage for the desired mechanical property. The durability under a saline environment is studied in terms of loss in strength. Further, the change in strength is correlated with the mineralogical changes studied using X-ray diffraction results.

The study utilizes a dataset with seven critical constraints and creates models that are estimated based on various metrics. The goal is to categorize and properly predict the water quality index (WQI) using the suggested models. The outcomes show that the implied models can accurately assess water quality and forecast WQI with high rates of success. Temperature, pH, dissolved oxygen (DO), conductivity, total dissolved solids (TDS), turbidity, and chlorides (Cl-) are some of the six crucial factors used in the study’s dataset. The mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2) are some of the metrics used to develop and assess the Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) models. The study also makes use of heat maps and correlation graphs to shed further light on the connections between various water quality measures. The color-coded values of the seven parameters, which represent the water quality level of the sample, are displayed on the heat map. The link between the two parameters is shown by the correlation graph between TDS and turbidity, which depicts their correlation coefficient. The study’s results show how effective machine learning algorithms may be as a tool for observing surface water quality. Himachal Pradesh is the tourist hub, so with the rapid increase in the volume of surface water contamination, the application of artificial intelligence will give a better view of data analytics and help with prediction and modeling. It was obtained from the study that the mean square error and root mean square error of ANN and LSTM lie between 0.52–6.0 and 0.04–0.21, respectively. However, the LSTM model’s accuracy is 95%, which is higher than the ANN model. The study highlights the importance of leveraging machine learning techniques in water quality monitoring to ensure the protection and management of water resources. With advancements in machine learning, artificial intelligence (AI) techniques have emerged as a promising tool for surface water quality monitoring. The major goal of the study is to explore the potential of two types of machine learning algorithms, namely artificial neural networks (ANNs) and long short-term memory (LSTM) models, for surface water quality monitoring.

In the present study, the quality of the surface water of the Gomti river (Lucknow, India) was investigated. Lucknow is situated in the centre of Uttar Pradesh, which is most the populated state in India. The locality has experienced rapid, unregulated development activities and population growth in recent decades, both of which have had a negative impact on its ecosystem and environment. Continuous monitoring is required to maintain the ecosystem at the desired level. Nine samples of river water were collected from the Gomti River in Lucknow, and they were analysed for a total of nine different characteristics, including pH, turbidity (Tur), dissolved oxygen (DO), total dissolved solids (TDSs), chemical oxygen demand (COD), chloride ion (Cl-) concentration, temperature (T), biochemical oxygen demand (BOD5) and total hardness (TH). The observed data were analysed using multivariate statistical methods. A cluster analysis (CA) was used to sort the sampling locations into different groups, and a principal component analysis (PCA) was used to find the different sources of pollution. Using a cluster analysis, all the water quality parameters were divided into three groups. Cluster 1 represented the less polluted sites, cluster 2 represented the moderately polluted sites and cluster 3 represented the highly polluted sites. Sampling sites SS8, SS4, S99 and SS7 were highly polluted because of nearby pollution sources such as domestic wastewater and runoff storm water. The principal component analysis yielded two meaningful components that explained 82.4% of the total variation in the data. The first factor and second factor explained 59.022 and 23.363 percentages of the total variance, respectively. It was noticed that major sources of pollution for the Gomti river are storm water runoff and the release of domestic and industrial wastewater from residents and industries, respectively. This study will help policy makers to ensure sustainable practices and reduce negative impacts on the availability and quality of water, allowing for the most efficient use of the Gomti River.

The model was created to assist in the appropriate allocation of water to produce crops to optimize net profit through monthly reservoir operation. The model maximizes net crop revenue and determines the type and size of the cultivated crop for each zone, taking into account monthly reservoir water availability. The following factors constrain the optimization model: (1) monthly reservoir water availability; (2) monthly water demand and irrigated farmland for crops; (3) limited crop areas in each zone; (4) projected final storage; (5) proportional sharing rule (PSR) for each zone. The linear programming (LP) algorithm is used to formulate the model, which is then solved using the general algebraic modeling system (GAMS). The model is applied to Hali Dam and validated using two criteria: (1) baseline scenarios (non-PSR) and (2) PSR scenarios in which all zones must have the same amount of water. The results demonstrate that the PSR scenarios give all of these zones identical rights for water delivery, with a total net profit reduction of around 2.6 percent at the planned final storage of 100 Hm3. As a result, the current model can be utilised to optimize dam water consumption in the future. The methodology is applied to a reservoir of Hali Dam in Saudi Arabia to demonstrate the model’s practical application.

The current research focuses on nanoparticles’ ground-improvement potential using clayey soil mixed with varying amounts of the nanoparticles “Silicon Carbide”. With an increase in the amount of nanomaterial, a tendency of improvement has been recorded in liquid and plastic limits, as well as the plasticity index. The maximum reduction in liquid limit (15.8%), plastic limit (13.6%), and plastic index (18.7%) was recorded at 0.25 gm of Silicon Carbide as compared to control (0 gm of SiC). There was a 26.7% and 33.3% increase in the cohesion of soil at 0.25 gm and 0.3 gm of Silicon Carbide, respectively. Furthermore, when the Silicon Carbide content increased from 0.25 gm, the rate of increment of friction angle also increased. It was 87.5% and 137.5% at 0.25 gm and 0.3 gm of Silicon Carbide, respectively. Furthermore, 0.3 gm of Silicon Carbide, is found to be optimal within the scope of the experiment as at this amount of Silicon Carbide both cohesion and angle of friction attained maximum. XRD, SEM, and FTIR were used to confirm the findings. It concludes that by using even a small amount of nanomaterial, an appreciable change in the properties of clayey soil can be obtained in the field. First published online 16 December 2022

This study focuses on the application of multi-sensor satellite archived data products and ancillary data for the evaluation of drought vulnerability. The use of a subjective model, namely Analytical Hierarchy Process (AHP) integrated with Geographical Information System (GIS) and various influencing parameters, emerged as a powerful tool for the gauged and ungauged watershed. The Kangsabati river basin, located in the southern part of West Bengal (India), is facing issues of overexploitation of groundwater, climate variation, and unsystematic agricultural practices that are inducing the water crisis and vulnerability of the basin to drought conditions. In this study, 11 parameters, namely elevation, slope, aspect, LULC, population density, normalized difference vegetation index (NDVI), normalized difference drought index (NDDI), land surface temperature (LST), normalized difference water index (NDWI), vegetation condition index (VCI), and soil moisture index (SMI) were used to delineate the drought in the catchment of Kangsabati River. Findings of this study using Analytical Hierarchy Process (AHP) integrated with a GIS platform, show that, nearly 28.5% of the area falls under the medium drought category, followed by the high (21.1%), no drought (20%), low (19.5%), and very high (10.6%) drought categories in the study area. The study also suggests Nature Based Solution (NBS) in Disaster Risk Reduction (DRR) strategies such as ecosystem-based approaches (EBA) and blue infrastructure for Drought Risk Reduction for drought mitigation in the study area.

The failure of an embankment causes loss of lives, massive damage to infrastructure and the interruption of basic facilities; it has thus drawn increasing attention from researchers. When compared to other types of embankment disasters, overtopping-related embankment breaches are much more frequent. The study of the breach mechanism of embankments due to overtopping is becoming more and more essential for developing evacuation plans, early warning systems and damage assessment. To recognize the breach activities of embankments, it is necessary to find out discrete breach considerations like breach depth, breach initiation, breach width, etc. In the present study, a total of six tests were performed in a narrow flume using an embankment model. By conducting different experiments, it was observed that embankment breaching may be described in three stages, i.e., initial erosion, headcut erosion and lateral erosion. Furthermore, erosion is a three-dimensional process that occurs during embankment breaching, with the majority of erosion movement being associated with lateral broadening. The rate of headcut migration also has an impact on the widening rate. Furthermore, it depends upon the type of fill material and dam geometry. Also, the observed effect of moisture content on breach widening proved that the rate of widening was strongly influenced by water content. A drop of about 50% in moisture content causes approximately a 20% decrease in time to failure. In the present study, it is observed that breach shape could not be assumed to be regular shape like rectangle or trapezoid, as described in the literature. The trials were carried out in a narrow flume under constant hydraulic conditions, which are two of the study’s limitations.

With increasing population and industrialization, the water quality of freshwater sources like rivers, lakes, and ponds is becoming increasingly degraded. Most of the rivers in India are becoming polluted, including the Godavari. With the construction of dams, new industries and unsustainable agricultural practices in the Godavari basin, the water characteristics are degrading spatially and temporally. The present study emphasizes the analysis of water quality parameters like temperature, pH, Dissolved Oxygen (DO), conductivity, Biological Oxygen Demand (BOD), nitrate, and faecal coliform concentration in the Godavari basin. This was achieved by analysis of data taken from the Central Pollution Control Board, India (CPCB) for 21 stations around the Godavari basin over a span of five years from 2015 to 2019. The Pearson Correlation coefficient for the water quality parameters was assessed to study the relationship among the parameters. Variation in the water quality parameter is observed from the graphs for each station for respective years. It was found that conductivity and DO, temperature and pH and DO and faecal coliform are negatively correlated. It was also observed that DO has a negative correlation with pH, BOD and faecal coliform, indicating the utilization of dissolved oxygen at higher rates due to increasing degradation of organic matter by aerobic microorganisms in the river. One-way ANOVA was applied to find out significant temporal variations and it was observed that temperature, pH, and faecal coliform level had significantly changed the overdue course of time (F(4, 115) = 2.451, p < 0.05). The obtained results from the analysis indicate that the selected water quality parameters have varied significantly spatially, whereas temporally, according to the ANOVA coefficient, only temperature, pH and faecal coliform had shown significant differences during the selected timeframe. Hence, the present study highlighted the deteriorating water quality of the Godavari River over time.

Soil is a heterogeneous material, and its properties are vital from an agricultural perspective and for groundwater management. However, limited studies have been performed on the soil characteristics (soil texture, water-holding capacity, and soil compositions) of a single pumping well, especially in Malaysia. This article focuses on the soil characteristics and elemental analysis of a single borehole with 11 samples collected around Labu Kubong, Perak. The soil properties were analyzed in the context of particle size distribution (PSD) using the laser diffraction method (LDM), as well as soil composition for elemental analysis using a scanning electron microscope coupled with an energy dispersive X-ray (SEM-EDX). The LDM results revealed the average percentage of clay, silt, and sand to be 0%, 6%, and 94%, respectively, indicating most particles comprised sand particles which in percentages demonstrated a sandy texture with less silt content. Additionally, the water holding capacity is low because of major coarse sand particles in alluvial formations. Moreover, SEM-EDX outcomes displayed an average percentage of elemental composition reported as follows: C (40.77%), O (34.33%), Si (10.66%), Al (5.82%), Fe (1.10%), K (1.10%), As (0.05%), Na (0.04%), and Be (5.62%). Consequently, SEM-EDX outcomes showed these elements were derived from silicified quartz, feldspar, and iron-bearing minerals that originated from shale formations, and the presence of carbon indicates peat formation. Therefore, this study provides information on a single pumping well from an irrigation practice, and this study also recommends regional to global scale studies for supporting sustainable groundwater development worldwide.

The United Nations Sustainable Development Goal (SDG) ensures adequately accessible water and management for all. Due to the rapid increase in population and industries along the Ganga river, it is necessary to estimate the water budget to fulfill the demand for water in the future. The Mann-Kendall (MK) test conducted on the Noah-Land Surface Model data for 72 years results in a maximum declining trend of water budget in the Yamuna Lower (Q = −3.82 BCM/year), and a minimum in the Damodar sub-basin (Q = −0.10 BCM/year). All the sub-basins show an increase in groundwater level (mbgl) except the Kali Sindh, which shows a decreasing trend (Q = −0.07 m/year). The percentage change was also estimated in all the sub-basins, including various parameters such as precipitation, evapotranspiration, runoff, water budget, and temperature. The extremely severe groundwater drought was estimated using the Standard Groundwater Level Index (SGWLI), from which the values for the Ram Ganga Confluence (SGWLI = 2.44; 2005), Upper stream of Gomti (SGWLI = 2.06; 2014), Ghaghra (SGWLI = 2.22; 2005), Ram Ganga (SGWLI = 2.28; 2005), Yamuna Lower (SGWLI = 2.13; 2007), Kali Sindh (SGWLI = 2.30,2.67; 2002, 2003), Chambal Upper (SGWLI = 2.30,2.20; 2001, 2003), Son (SGWLI = 2.02; 2010), Gandak (SGWLI = 2.37; 2010), Kosi (SGWLI = 2.08; 2012), Damodar (SGWLI = 2.72; 2010), and Bhagirathi (SGWLI = 2.06; 2014) were obtained for a total of 62,050 observed well data.The obtained in-situ point data is converted into the surface raster using a geostatistical technique. Our results show a declining trend in the water budget of all the 19 sub-basins of the Ganga basin and also the groundwater drought in several parts.

The rate of municipal solid waste (MSW) generation in developing countries is continuously growing in proportion to the gross national product. Landfilling, incineration, composting, and waste to energy (WtE) have a brief history as management strategies for MSW in India. Economic evaluation via cost benefit analysis (CBA) of MSW is establishing the most appropriate treatment/disposal strategy and it is often a major concern for solid waste management (SWM) policymakers. Thus, this study aims to analyze the municipal solid waste management (MSWM) activities in India’s capital, Delhi, and the CBA of MSWM systems to identify the major problems and limitations involved. Sixty-six samples totaling 6,600 kg were collected and analyzed at random from various locations, including the sources of generation, composting plants, and disposal sites. Storage, collection, transportation, and recycling information were gathered from departments such as Municipal Corporation of Delhi (MCD), New Delhi Municipal Corporation (NDMC), Central Pollution Control Board (CPCB), and self-surveys. The total costs of each MSW option were calculated for cost analysis. The results revealed a high organic moisture content, indicating the possibility of composting and bio-methanation, except for waste from commercial, institutional area and restaurants that can be used to develop Refuse Derived Fuel (RDF). It was also revealed that only about 80% of the garbage generated in Delhi is collected. In terms of treatment and disposal, the MCD has proposed additional facilities such as disposal through sanitary landfills with linings, as well as a system for leachate collection and disposal. Furthermore, construction and demolition waste are used in the construction of various pavement components, such as base coarse, surface coarse, and so on. The total social value added by garbage trade operations in Delhi is expected to be INR 358.7 crores (approximately 46.60 million USD) between 2017 and 2020. Recycling saves the municipal budget about INR 17.6 crores (approximately 2.3 million USD per year).

The Himalayan region is prone to landslides. Rainfall-induced slope failure activities in the Indian Himalaya cause considerable damage, posing a serious risk to life and property. This study attributes information regarding landslide triggering parameters to further delineate landslide susceptibility maps of Himachal Pradesh in the Himalayan region. The landslide inventory map was created using information from field visits, Linear Imaging Self-Scanning Sensor (LISS III), and Google Earth. Thereafter, eight landslide causative factors, viz. slope, aspect, curvature, elevation, Landuse Landcover (LULC), soil, lithology, and drainage density were performed by employing the weight of evidence (WOE), information value method (IVM) and the frequency ratio (FR) methods. Using the ArcGIS reclassification tool, the final landslide susceptibility zonation (LSZ) maps were categorized into five susceptibility zones: “very low, low, medium, high, and very high.” The success rate for WOE, FR, and IVM models was determined as 76.27%, 78.20%, and 76.09% respectively, depicting that the FR model based LSZ map is more accurate. According to the FR model based LSZ map, the highly susceptible classes in the case of aspect, curvature, and lithology are southeast, concave, and TBS, respectively. The sparsely vegetated areas are more prone to landslides than the other LULC areas. The higher elevations, ranging from 1191 to 1434, 1434–1655, and 1655–1876 m, are more vulnerable to landslide activities as compared to low elevations. The slope classes 30–45 and 45–60, medium drainage density class and fine loamy class of soils are more likely to landslides. The prepared susceptibility zone map can be used for future mitigation planning in the high and very high susceptibility zones in order to reduce landslide-related human and economic losses.

Early-stage uric acid (UA) abnormality detection is crucial for a healthy human. With the evolution of nanoscience, metal oxide nanostructure-based sensors have become a potential candidate for health monitoring due to their low-cost, easy-to-handle, and portability. Herein, we demonstrate the synthesis of puffy balls-like cobalt oxide nanostructure using a hydrothermal method and utilize them to modify the working electrode for non-enzymatic electrochemical sensor fabrication. The non-enzymatic electrochemical sensor was utilized for UA determination using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The puffy balls-shaped cobalt oxide nanostructure-modified glassy carbon (GC) electrode exhibited excellent electro-catalytic activity during UA detection. Interestingly, when we compared the sensitivity of non-enzymatic electrochemical UA sensors, the DPV technique resulted in high sensitivity (2158 µA/mM.cm2) compared to the CV technique (sensitivity = 307 µA/mM.cm2). The developed non-enzymatic electrochemical UA sensor showed good selectivity, stability, reproducibility, and applicability in the human serum. Moreover, this study indicates that the puffy balls-shaped cobalt oxide nanostructure can be utilized as electrode material for designing (bio)sensors to detect a specific analyte.

Abstract Among the different challenges related to rice (Oryza sativa L.) cultivation, drought, bacterial leaf blight (BLB), and blast are the key stresses that significantly affect grain yield (GY) in rice. To ameliorate this issue, marker‐assisted forward breeding (MAFB) coupled with a simultaneous crossing approach was used to combine three drought tolerant quantitative trait loci (QTL)—qDTY1.1, qDTY3.1, and qDTY12.1—four BLB genes—Xa4, xa5, xa13, and Xa21—and one blast‐resistance gene, Pi9, in the elite rice cultivar Lalat. The introgression lines (ILs) developed in the current study were phenotypically screened for drought, BLB, and blast resistance at the F7–F8 generation. Under the reproductive stage (RS) drought stress, the yield advantage of ILs, with major‐effect QTL (qDTY) over elite parent Lalat, ranges from 9 to 124% in DS2019 and from 7 to 175% in WS2019. The selected ILs were highly resistant to BLB, with lesion lengths ranging from 1.3 to 3.0 cm and blast scores ranging from 1 to 3. ILs that were tolerant to RS drought, resistant to BLB, and blast disease and had similar or higher yields than Lalat were analyzed for grain quality. Six ILs were found to have similar grain quality characteristics to Lalat including hulling, milling, head rice recovery (HRR), chalkiness, alkali spreading value (ASV), and amylose content (AC). This study showed that MAFB, together with simultaneous crossing, would be an effective strategy to rapidly combine multiple stresses in rice. The ILs developed in this study could help to ensure yield sustainability in rainfed environments or be used as genetic material in future breeding programs.

Abstract Background Unfavorable climatic changes have led to an increased threat of several biotic and abiotic stresses over the past few years. Looking at the massive damage caused by these stresses, we undertook a study to develop high yielding climate-resilient rice, using genes conferring resistance against blast (Pi9), bacterial leaf blight (BLB) (Xa4, xa5, xa13, Xa21), brown planthopper (BPH) (Bph3, Bph17), gall midge (GM) (Gm4, Gm8) and QTLs for drought tolerance (qDTY 1.1 and qDTY 3.1 ) through marker-assisted forward breeding (MAFB) approach. Result Seven introgression lines (ILs) possessing a combination of seven to ten genes/QTLs for different biotic and abiotic stresses have been developed using marker-assisted selection (MAS) breeding method in the background of Swarna with drought QTLs. These ILs were superior to the respective recurrent parent in agronomic performance and also possess preferred grain quality with intermediate to high amylose content (AC) (23–26%). Out of these, three ILs viz., IL1 (Pi9+ Xa4+ xa5+ Xa21+ Bph17+ Gm8+ qDTY 1.1 + qDTY 3.1 ), IL6 (Pi9+ Xa4+ xa5+ Xa21+ Bph3+ Bph17+ Gm4+ Gm8+ qDTY 1.1 + qDTY 3.1 ) and IL7 (Pi9+ Xa4+ xa5+ Bph3+ Gm4+ qDTY 1.1 + qDTY 3.1 ) had shown resistance\tolerance for multiple biotic and abiotic stresses both in the field and glasshouse conditions. Overall, the ILs were high yielding under various stresses and importantly they also performed well in non-stress conditions without any yield penalty. Conclusion The current study clearly illustrated the success of MAS in combining tolerance to multiple biotic and abiotic stresses while maintaining higher yield potential and preferred grain quality. Developed ILs with seven to ten genes in the current study showed superiority to recurrent parent Swarna+drought for multiple-biotic stresses (blast, BLB, BPH and GM) together with yield advantages of 1.0 t ha− 1 under drought condition, without adverse effect on grain quality traits under non-stress.

Transition metal oxide (TMO)-based nanomaterials are effectively utilized to fabricate clinically useful ultra-sensitive sensors. Different nanostructured nanomaterials of TMO have attracted a lot of interest from researchers for diverse applications. Herein, we utilized a hydrothermal method to develop porous nanosheets of cobalt oxide. This synthesis method is simple and low temperature-based. The morphology of the porous nanosheets like cobalt oxide was investigated in detail using FESEM and TEM. The morphological investigation confirmed the successful formation of the porous nanosheet-like nanostructure. The crystal characteristic of porous cobalt oxide nanosheets was evaluated by XRD analysis, which confirmed the crystallinity of as-synthesized cobalt oxide nanosheets. The uric acid sensor fabrication involves the fixing of porous cobalt oxide nanosheets onto the GCE (glassy carbon electrode). The non-enzymatic electrochemical sensing was measured using CV and DPV analysis. The application of DPV technique during electrochemical testing for uric acid resulted in ultra-high sensitivity (3566.5 µAmM−1cm−2), which is ~7.58 times better than CV-based sensitivity (470.4 µAmM−1cm−2). Additionally, uric acid sensors were tested for their selectivity and storage ability. The applicability of the uric acid sensors was tested in the serum sample through standard addition and recovery of known uric acid concentration. This ultrasensitive nature of porous cobalt oxide nanosheets could be utilized to realize the sensing of other biomolecules.

The tunnels in present-day cities are experiencing varying degrees of loading conditions ranging from static to extreme loading. Therefore, the stability of underground tunnels needs to be analyzed and understood for safer and strengthened design. The present study was conducted to simulate the impact loading conditions due to a missile traveling at a velocity of 5 Mach for different rock tunnels. The nonlinear continuum finite element analysis has been carried out through Abaqus and Explicit. The four different types of sandstones considered in the present study include Kota, Jamrani, Singrauli, and Jhingurda sandstones. An elastoplastic Mohr–Coulomb constitutive material model has been considered to model the behavior of rock surrounding the tunnel opening. The tunnel has an opening of 7 m in diameter (d), and 50 m in height and breadth, with 50 m of longitudinal length. The deformation and stress in the rock and the damage to the concrete lining have been compared in different cases. The Concrete–Damage–Plasticity (CDP) model and the Johnson–Cook model were considered for modelling of the RC lining and steel reinforcement. It was concluded that Jhingurda sandstone has maximum deformations due to impacts caused by missiles.

Nexrutine (NX), a marketable herbal extract from a traditional Chinese herbal plant, Phellodendron amurense, is majorly used for the resolution of inflammation, gastroenteritis, and some tissue-specific cancer. Strategies for the identification of the safety of anticancer solutions of plant origin are an important area of study. The present investigation assesses the single and repeated dose (28 days) toxicity of NX following OECD guidelines 425 and 407, respectively. Briefly, to identify acute toxic properties of NX, a dose of 2000 mg/kg b. wt was administered once orally. Simultaneously, repeated dose toxicity was evaluated through daily administration of the three different doses (250, 500, 750 mg/kg b. wt) of NX for 28days. The single administration of NX showed no signs of toxicity and morbidity, suggesting LD50 of NX more than 2000 mg/kg b. wt. Furthermore, repeated dose exposure of NX for 28 days did not show any sign of toxicity. Hematology, serum biochemistry, and histopathological analysis also did not show any significant abnormalities. However, a marginal decrease in triglyceride, cholesterol, and glucose levels along with mild tubular degeneration in the kidney was also noticed in the high dose NX treatment group. Overall, the findings of the study suggest that NX is safe for use up to 500 mg/kg b.wt.

Background: Chemotherapy-induced cardiotoxicity constitutes subclinical myocardial dysfunction, arrhythmias, pericarditis, coronary vasospasm, and significant symptomatic heart failure. Anthracyclines pose higher risk for long-term cardiac dysfunction, with increased incidences of morbidity and mortality. Hence, early detection of chemotherapy-induced cardiac dysfunction may prompt an earlier treatment modification. Aim: To evaluate global, longitudinal, radial, and circumferential strain changes in adult patients undergoing anthracycline chemotherapy along with the usefulness of three-dimensional (3D) echocardiography as the new modality over two-dimensional (2D) echocardiography. Methods: This was a single centre, prospective, observational study that included asymptomatic patients free from any cardiac signs and symptoms attributable to heart failure, who underwent potentially cardiotoxic chemotherapy for malignancy from December 2017 to November 2018 at a tertiary care centre in India. Baseline demographics were recorded, and 2D and 3D echocardiography was performed at baseline and after completion of four cycles of chemotherapy. Results: All the 55 patients received a cumulative dose of doxorubicin of less than 550 mg/m2. Follow-up period from the beginning of doxorubicin therapy was 108 ± 14 days. 9 patients were excluded from the study due to poor 3D images, so data analysis was done only for 46 patients. In 2D echocardiography, only global longitudinal strain (GLS) was observed to be significantly reduced (Δ18.33%; P

The elite Indian rice variety, Naveen is highly susceptible to major biotic and abiotic stresses such as blast, bacterial blight (BB), gall midge (GM) and drought which limit its productivity in rainfed areas. In the present study, a combined approach of marker-assisted forward (MAFB) and back cross (MABC) breeding was followed to introgress three major genes, viz., Pi9 for blast, Xa21 for bacterial blight (BB), and Gm8 for gall midge (GM) and three major QTLs, viz., qDTY1.1, qDTY2.2 and qDTY4.1 conferring increased yield under drought in the background of Naveen. At each stage of advancement, gene-based/linked markers were used for the foreground selection of biotic and abiotic stress tolerant genes/QTLs. Intensive phenotype-based selections were performed in the field for identification of lines with high level of resistance against blast, BB, GM and drought tolerance without yield penalty under non-stress situation. A set of 8 MAFB lines and 12 MABC lines with 3 to 6 genes/QTLs and possessing resistance/tolerance against biotic stresses and reproductive stage drought stress with better yield performance compared to Naveen were developed. Lines developed through combined MAFB and MABC performed better than lines developed only through MAFB. This study exemplifies the utility of the combined approach of marker-assisted forward and backcrosses breeding for targeted improvement of multiple biotic and abiotic stress resistance in the background of popular mega varieties.

The shortage of natural aggregates has compelled the developers to devote their efforts to finding alternative aggregates. On the other hand, demolition waste from old constructions creates huge land acquisition problems and environmental pollution. Both these problems can be solved by recycling waste materials. The current study aims to use recycled brick aggregates (RBA) to develop eco-friendly pervious concrete (PC) and investigate the new concrete’s structural performance and pore structure distributions. Through laboratory testing and image processing techniques, the effects of replacement ratio (0%, 20%, 40%, 60%, 80%, and 100%) and particle size (4.75 mm, 9.5 mm, and 12.5 mm) on both structural performance and pore feature were analyzed. The obtained results showed that the smallest aggregate size (size = 4.75 mm) provides the best strength compared to the large sizes. The image analysis method has shown the average pore sizes of PC mixes made with smaller aggregates (size = 4.75 mm) as 1.8–2 mm, whereas the mixes prepared with an aggregate size of 9.5 mm and 12.5 mm can provide pore sizes of 2.9–3.1 mm and 3.7–4.2 mm, respectively. In summary, the results confirmed that 40–60% of the natural aggregates could be replaced with RBA without influencing both strength and pore features.

By the year 2035 it is estimated that Delhi and Mumbai will become two of the most populous cities around the globe. The massive population growth rate has led to the rise of land scarcity, urbanization, and industrialization and developments for rapid transit systems have made accordingly. Modern rapid transit systems comprise Metro rails and subways etc., and increase underground-construction activities. Nowadays, the tunnel-construction process heavily relies on massive machineries such as tunnelling-boring machines (TBM) and operations that produce great hindrance in the soil mass resulting in ground settlement at the surface. This study aimed to address these issues through small-scale laboratory experiments and further amplification to real-valued problems utilizing numerical methods. A cubic box of edge length 1 m made up of mild steel was generated to simulate a tunnelling operation and aluminum-made lining were used to simulate concrete tunnel linings. A finite element-based numerical investigation was done for a 2D elastoplastic numerical tunnel model with dimensions of 42 m × 42 m. Analysis was carried out on Optum G2 software. The analyzed variations in lining shapes of lining included circular, horseshoe, arch, elliptical, and square. Results showed that elliptical-shaped linings experienced the least ground settlement and these are recommended for places where surface settlement may cause major damage. It is also recommended that square-shaped linings should not be used in such situations due their higher settlement values.

Aluminum-based composites with characteristics such as low density and high strength to weight ratio have been identified to be one of the best-emerging alternatives. The lightweight composite is gaining popularity, particularly in the automotive industry. The composite’s qualities make it a prospective material to replace significant materials that are now used in the automobile industry. For lightweight products, various weight reduction solutions were proposed. In the present work, one such lightweight composite was fabricated by using a stir casting process, which includes reinforcement powders viz. carbon nanotube and fly ash to pure aluminum. The use of fly ash helps in reducing the overall associated cost of the material as well as provides low density. The work aims to identify the amount of fly ash (by weight %) suitable to avail good mechanical properties. In concern with the mechanical properties, density, yield strength, ultimate tensile strength, and wear resistance of the composite specimen were examined. Moreover, the artificial neural network was adopted to identify minimum volumetric wear for a given set of conditions. From the results, it was perceived that with the increase in fly ash content, the volumetric wear of the fabricated composite decreases. However, with the increase in load and speed, the volumetric wear rate increases.

In a laboratory, a model of a mid-channel bar is built to study the turbulent flow structures in its vicinity. The present study on the turbulent flow structure around a mid-channel bar is based on unravelling the fluvial fluxes triggered by the bar’s 3D turbulent burst phenomenon. To this end, the three-dimensional velocity components are measured with the help of acoustic doppler velocimetry (ADV). The results indicate that the transverse component of turbulent kinetic energy cannot be neglected when analyzing turbulent burst processes, since the dominant flow is three-dimensional around the mid-channel bar. Due to the three-dimensionality of flow, the octant events approach is used for analyzing the flow in the vicinity of the mid-channel bar. The aim is to develop functional relationships between the stable movements that are modelled in the present study. To find the best Markov chain order to present experimental datasets, the zero-, first-, and second-order Markov chains are analyzed using the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). The parameter transition ratio has evolved in this research to reflect the linkage of streambed elevation changes with stable transitional movements. For a better understanding of the temporal behaviors of stable transitional movements, the residence time vs. frequency graphs are also plotted for scouring as well as for depositional regions. The study outcome herein underlines the usefulness of the octant events approach for characterizing turbulent bursts around mid-channel bar formation, which is a precursor to the initiation of braiding configuration.

Protective coatings for harsh environments are always welcome, but they must overcome profound challenges, including corrosion and wear resistance. The purpose of this study is to look into the long-term potentiodynamic polarization measurements and dry tribometric behavior of plasma-sprayed amorphous coatings on AISI 1035 mild steel. To investigate the impact of unique active polarization potentials on the electrochemical studies of the iron-based amorphous layer, which compares favorably to AISI 1035 mild steel, the active potential polarization curve and friction coefficient tests were performed. Scanning electron microscopy (SEM) and energy dispersive x-ray (EDX) analyses were used to investigate the coating’s corrosion behavior. Their mechanical (Tribometric tests at higher sliding speeds) and chemical properties (electrochemical potentiodynamic polarization investigations) have also been thoroughly investigated. There is enough validation that these protective coatings can be used in hostile environments. The effects of long-term corrosion for 24 and 48 h were thoroughly examined. Tribometric examinations revealed that amorphous layers are highly resistant under dry conditions, as they offered a very low and stable friction coefficient less than 4 μ with micro Vickers hardness 1140 ± 22.14 HV, which is more than twice as compared to mild steel AISI 1035. The corrosion resistance of coatings in 3.5 wt % NaCl solution displays active transition characteristics of activation, passivation, over passivation, and pitting, as shown by the potentiodynamic polarization curves.

Increasing infrastructure growth has forced the construction industry to look for wasteful, cheap, and suitable materials for construction. An investigation into the geotechnical utilization of fly ash was carried out in the present study. Practical applications normally involve the use of large quantities of fly ash, so proper mixing of the fly ash with other materials may not be significantly achieved. Therefore, the present paper investigates the behaviour of a fly ash–bentonite layered system with different ratios. The physical properties and chemical composition of fly ash and bentonite were determined. SEM and energy dispersive X-ray experiments were also used to investigate the morphology and phase compositions of fly ash and bentonite. A series of consolidated undrained (CU) triaxial tests on fly ash–bentonite were carried out to investigate shear strength characteristics. Fly ash (F) and bentonite (B) were used in the following ratios: 1:1 (50% F:50% B), 2:1 (67% F:33% B), 3:1 (75% F:25% B), and 4:1 (80% F:20% B), with different numbers of interfaces (N), i.e., 1, 2, and 3 for each ratio. The deviator stress and cohesion value were found to increase with the number of interfaces for each ratio. The angle of shear resistance changed marginally with the increase in the fly ash–bentonite ratios and varying interfaces.

Cosmetic industries are highly committed to finding natural sources of functional active constituents preferable to safer materials to meet consumers’ demands. Marine macroalgae have diversified bioactive constituents and possess potential benefits in beauty care products. Hence, the present study was carried out to characterize the biochemical profile of marine macroalga Chaetomorpha crassa by using different techniques for revealing its cosmetic potentials. In results, the FTIR study characterized the presence of different bioactive functional groups that are responsible for many skin-beneficial compounds whereas six and fifteen different important phycocompounds were found in GCMS analysis of ethanolic and methanolic extracts, respectively. In the saccharide profile of C. crassa, a total of eight different carbohydrate derivatives were determined by the HRLCMS Q-TOF technique, which showed wide varieties of cosmetic interest. In ICP AES analysis, Si was found to be highest whereas Cu was found to be lowest among other elements. A total of twenty-one amino acids were measured by the HRLCMS-QTOF technique, which revealed the highest amount of the amino acid, Aspartic acid (1207.45 nmol/mL) and tyrosine (106.77 nmol/mL) was found to be the lowest in amount among other amino acids. Their cosmetic potentials have been studied based on previous research studies. The incorporation of seaweed-based bioactive components in cosmetics has been extensively growing due to its skin health-promoting effects.

Epidemiological studies suggested that plant-based dietary supplements can reduce the risk of liver cancer. Nexrutine (NX), an herbal extract from Phellodendronamurense, has been shown to have anti-inflammatory, anti-microbial and anti-tumor activities. In the present study, we have shown the anti-tumor potential of NX against Solt-Farber model with elimination of PH, rat liver tumor induced by diethylnitrosoamine (DEN) as carcinogen and 2-acetylaminofluorene (2-AAF) as co-carcinogen. The elucidation of mechanistic pathways was explored in human liver cancer cells. Dietary intake of NX significantly decreased the cell proliferation and inflammation, as well as increased apoptosis in the liver sections of DEN/2-AAF-treated rats. Moreover, NX (2.5–10 μg/ml) exposure significantly decreased the viability of liver cancer cells and modulated the levels of Bax and Bcl-2 proteins levels. NX treatment resulted in increased cytochrome-c release and cleavage of caspases 3 and 9. In addition, NX decreased the expression of CDK2, CDK4 and associated cyclins E1 and D1, while up-regulated the expression of p21, p27 and p53 expression. NX also enhanced phosphorylation of the mitogen-activated protein kinases (MAPKs) ERK1/2, p38 and JNK1/2. Collectively, these findings suggested that NX-mediated protection against DEN/2-AAF-induced liver tumorigenesis involves decrease in cell proliferation and enhancement in apoptotic cell death of liver cancer cells.