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Declining levels of the water table in India have become a major concern, especially with climate change and burgeoning population compounding the problem and causing a perpetual state of water crisis. A better insight into the state of these precious resources is essential for their planned exploration and usage. This study introduces a novel machine learning ensemble model (ARZ ensemble), through an implementation of majority voting-based technique over its standalone classifier constituents, namely, Automatic Multilayer Perceptron (AutoMLP), random forest (RF), and ZeroR for undertaking the groundwater potential mapping for the Jabalpur district, Madhya Pradesh. Ten groundwater influencing factors (i.e., slope, rainfall, aspect, elevation, topographic wetness index, land use, lithology, distance from rivers, plan and profile curvature) and groundwater well locations from the study area were used to construct the spatial database. In order to validate the applicability of the proposed model, its performance was compared against a conventionally employed statistical method of Shannon's entropy (SE) model. The results revealed that the ARZ ensemble model (AUC: 0.8542) outperformed SE (AUC: 0.7639). The groundwater potential map revealed that approximately 4.18% of the region has very high groundwater potential, while 47.66% belongs to a low potential zone. Such information can hold solutions for a lot of the ailments afflicting these resources and can genuinely aid in the attempts to restore them to their natural state.
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Monitoreo del Ambiente , Agua Subterránea , Aprendizaje Automático , Redes Neurales de la Computación , RíosRESUMEN
Introduction: Light stress is an important factor limiting the biomass yield while combining forage production with crops or forestry. Guinea grass is a widely adapted perennial fodder grass. The species exhibits high degree of variation for morphology, adaptation and biomass yield. Objective: Since there is a need in identifying shade adapted forage grasses for the expanding area under agroforestry/silvipastures, the present investigation took the task of understanding how the morphologically distinct genotypes of guinea grass respond under different shaded intensities. Methods: In the present study, forty-four genotypes related with the shade response were studied in varying shading conditions (pure sunlight, 25, 50 and 75 % shade) created artificially. Results: Based on green and dry matter yields ranking, the genotype IG 01-98 performed the best followed by genotypes IG 01-92, IG 97-5, IG 97-6 and IG 01-89 in decreasing order. Particularly, IG 01-93 was identified as the best performing under 50 % shading conditions. On the other hand, most of the top ranking genotypes performed well both under open and up to 50 % of shade. Morphologically, these genotypes were taller and possessed longer and broader leaves. Under shaded conditions (over 50 %), leaf length and width showed an increasing trend compared to open conditions. Also, chlorophyll content increased with shading intensity. Conclusions: Most of the genotypes collected from the southern Indian humid tropical environment with early flowering nature were tolerant to shade. Differential genotypic response was observed for biomass yield and yield attributes under shade. The study established appreciable variability for shade tolerance among genotypes.
Introducción: El estrés leve es un factor importante que limita el rendimiento de la biomasa al tiempo que combina laproducción forrajera con los cultivos o la silvicultura. El zacate guinea es una planta de forraje perenne ampliamente adaptada. La especie presenta un alto grado de variación en su morfología, adaptación y rendimiento de biomasa. Objetivo: Como existe la necesidad de la identificación de pastos forrajeros adaptados a la sombra para el área de expansión bajo agroforestería /silvicultura, la presente investigación se realizó para entender cómo los genotipos morfológicamente distintos al zacate guinea responden a diferentes intensidades de sombra. Métodos: Se estudiaron 44 genotipos y su respuesta a los niveles de sombra: luz solar pura y 25, 50 y 75 % de sombra (creados artificialmente). Resultados: Basado en la clasificación de rendimientos demateria verde y seca, el genotipo IG 01-98 fue el mejor, seguido de los genotipos IG 01-92, IG 97-5, IG 97-6 e IG 01-89 en orden decreciente. Por su parte, el IG 01-93 fue identificado como el de mayor rendimiento bajo el 50 % de condición de sombra. La mayoría de los genotipos de primer nivel tuvieron un buen desempeño, tanto bajo sombra abierta como al 50 %. Morfológicamente, estos genotipos fueron más altos y poseían hojas más largas y más anchas. En condiciones de sombra, de más del 50 %, la longitud y ancho de la hoja mostraron una tendencia creciente en comparación con la condición abierta. El contenido de clorofila aumentó con la intensidad de la sombra. Conclusiones: La mayoría de los genotipos recolectados al sur de la India en un ambiente tropical húmedo y tienen una floración temprana, fueron tolerantes a la sombra. Se observó una respuesta genotípica diferencial para los atributos de rendimiento y rendimiento de biomasa bajo sombra. El estudio mostró la existencia de una variabilidad apreciable para la tolerancia a la sombra entre los genotipos.
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We have demonstrated a simple and scalable fabrication process for defect-rich MoS2 directly from ammonium tetrathiomolybdate precursor using intense pulse light treatment in milliseconds durations. The formation of MoS2 from the precursor film after intense pulsed light exposure was confirmed with XPS, XRD, electron microscopy and Raman spectroscopy. The resulting material exhibited high activity for the hydrogen evolution reaction (HER) in acidic media, requiring merely 200 mV overpotential to reach a current density of 10 mA cm-2. Additionally, the catalyst remained highly active for HER over extended durability testing with the overpotential increasing by 28 mV following 1000 cycles. The roll-to-roll amenable fabrication of this highly-active material could be adapted for mass production of electrodes comprised of earth-abundant materials for water splitting applications.
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This study assessed the fluoride (F-) pollution in groundwater samples (n = 170) of tribal regions around Bailadila Iron Ore Mines [BIOM] Complex of Dantewada District, India. Weathering of carbonate and silicate clays were important geogenic sources of dissolved ions. A Piper diagram showed a Ca-HCO3 water type, with positive chloro-alkaline indices illustrating the occurrence of direct base-exchange reactions. The F- concentrations varied from 0.08 to 1.95 mg L-1 with a mean value of 0.9 ± 0.3 mg L-1. Only two groundwater samples showed F- concentrations > 1.5 mg L-1, the drinking water guideline established by the World Health Organization (WHO) and Bureau of Indian Standards (BIS). Factor analysis showed high loadings of HCO3- and F-, indicating alkaline conditions, favoring the dissolution of F- in the groundwater. The K fluor value is less than 10-10.6, indicating that the dissociation of fluorite is very slow. As a result, groundwater locations were under-saturated with respect to fluorite.
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Monitoreo del Ambiente/métodos , Fluoruros/análisis , Sedimentos Geológicos/química , Agua Subterránea/química , Contaminantes Químicos del Agua/análisis , Agua Potable/análisis , Humanos , IndiaRESUMEN
Chromium (Cr), nickel (Ni) and lead (Pb) contamination was investigated in wheat cultivated rain-fed and irrigated rural agricultural soils (n = 31) of Tonalite-Trondjhemite Series in Central India. The soil sampling was carried out by using stratified random sampling method. The mean concentrations of Cr, Ni and Pb were 54.8, 38.1 and 68.9 mg/kg, respectively. The average values of enrichment factor (EF), geoaccumulation index (I geo ) and contamination factor (CF) followed the order as: Pb > Ni > Cr. Distribution patterns of soil parent material and weathering processes govern mineral enrichments, irrespective of rainfed or irrigated agricultural practices. Principal component analysis (PCA) showed strong loading of Cr and Ni (PC1) and Pb and clay (PC3). The strong loading on Cr and Ni indicates soils are originating from basic and volcanic rocks in the study area. The strong loading of Pb and clay indicates Pb is strongly adsorbed on clay minerals and Fe-oxides. The cancer risk (CR) index showed negligible carcinogenic risk to the residing population. However, hazard index (HI) values for children exceed the safe limit (HI > 1) for Cr and Pb. Spatial distribution of pollution load index suggest highest pollution in the northeastern part of the district. The study revealed that geogenically enriched soils of the area are suitable for agricultural activities under present conditions.
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Cromo/análisis , Monitoreo del Ambiente , Plomo/análisis , Níquel/análisis , Contaminantes del Suelo/análisis , Agricultura , Silicatos de Aluminio , Niño , Arcilla , Contaminación Ambiental/análisis , Contaminación Ambiental/estadística & datos numéricos , Humanos , India , Metales Pesados/análisis , Suelo/químicaRESUMEN
Assessment of the anthropogenic impacts on bioavailability, mobility, immobility and toxicity of four micronutrients (Cu, Fe, Mn, and Zn) were carried out by Community Bureau of Reference (BCR) fractionation scheme in agricultural soils (n = 10) around Jharia coalfield, eastern India. The relative abundance of micronutrients was as follows: Fe > Mn > Zn > Cu. The enrichment factor was >1 for Zn (6.1) and Cu (1.8) near coal mining area indicated toward soil pollution due to coal mining activities and application of inorganic fertilizers. The I geo values of micronutrients were <0 suggest no pollution with respect to Cu, Fe, Mn and Zn. Correlation analysis showed geogenic origin of soil micronutrients and derived mainly from weathering of minerals present in the parent rock. The mean values of Cu, Mn and Zn were less than certified reference material indicating highly leached agricultural soils in the study region. BCR fractionation of micronutrients showed that a single element could not reveal all types of chemical reactions occurring in soil consortium.