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Towards disentangling environmental costs of India's agricultural trade network
No full textIndia faces a critical challenge in balancing its rising food demand with environmental sustainability. While the nation has achieved agricultural self-sufficiency, the environmental costs of production are escalating, with severe implications for soil, air, and water quality. The increasing reliance on interstate trade to meet growing consumption has further intensified the environmental burden on key agricultural regions. We herein investigate the environmental footprint of India's interstate agricultural trade network by analyzing the gross within-India trade network for cereal crops and disentangle underlying drivers resulting in environmental impacts. Using a recently developed pan-India nutrients data over the last decades, we found that excess nutrient pollution pressures are disproportionately concentrated in major production hubs such as north Indian food-bowl states like Punjab and Haryana, which simultaneously bear the brunt of air pollution (e.g., increased PM2.5 emissions) from agricultural residue burning and soil and water pollution from excess nutrient flows. Along with facing increasing mounting pressure of declining key (ground) water resources, these regions, though pivotal to national food security, face mounting environmental degradation that threatens their long-term integrity and viability. For example, at the current trend, trade-related burdens in these regions would demand over 350 billion cubic meters of (gray)water annually to maintain groundwater-related nutrient levels within safe limits. Our analysis highlights the challenging aspects of internal trade, which is undoubtedly a critical yet largely overlooked factor in developing effective regional air and water quality management strategies for India. We further present viable strategies based on nutrient-focused restructuring of India’s agricultural system, offering significant socio-environmental benefits by reducing nitrogen surplus by 16–24%, water use by 20–40%, and greenhouse gas emissions by 28% (113 Mt CO₂ eq), while enhancing farmer incomes and calorie production. Overall our research underscores the necessity for regional cooperation and targeted interventions to mitigate the environmental costs of agricultural trade while ensuring sustainable food security for India's growing population
Tool wear assessment in dry machining of Ti–6Al–4V using Taguchi approach
No full textTitanium alloys (Ti-alloys) are valued for their lightweight, high strength-to-weight ratio, and corrosion resistance, but they present machining challenges. Optimizing cutting parameters and tool selection is essential for improving machinability and surface integrity, particularly in aviation and biomedical applications requiring precision. A key issue in metal cutting is the high temperature at the tool-chip interface, which can lead to stiction and tool failure. This study evaluates the performance of bare, textured, and TiN-coated WC–Co tools in dry turning of Ti–6Al–4V alloy. Advanced microscopy techniques were employed to analyze tool wear. Using the Taguchi method for Design of Experiments (DoE), varying cutting speeds (Vc) and depths of cut (DoC) were analyzed with MINITAB 22. Textured tools exhibited enhanced wear resistance with increased DoC, while TiN-coated tools excelled at lower Vc. Energy dispersive X-ray (EDX) analysis indicated stiction issues in both tool types due to titanium’s solubility in the cobalt matrix, impacting tool longevity. Optimal cutting parameters were identified at Vc = 80 m/min and DoC = 0.25 mm, achieving flank wear (VB) below 300 µm, in line with ISO standards. This study underscores the significance of DoC in tool wear, highlighting that lower cutting speeds and greater DoCs yield optimal machining conditions for Ti–6Al–4V. Both texturing and coating enhance tool life and wear resistance, with texturing showing particular promise for future exploration
Far-Red BODIPY-Based Fluorescent Probe for the Selective Detection of Cysteine and Hydrogen Sulfide: Applications in Blood Serum Analysis and Live-Cell Imaging
No full textCysteine (Cys) is a crucial biomolecule involved in protein synthesis, antioxidant defense, and cellular signaling, while H2S serves as a gasotransmitter. The imbalance of these thiols is linked to a range of pathological conditions, highlighting the need for precise and reliable detection methods. Herein, we have developed a bright far-red fluorescent probe (BYN-DNS) for the selective and sensitive detection of Cys and H2S. The probe is synthesized using methoxy-1-naphthaldehyde modified BODIPY molecule (BYN-OH) functionalized with a 2,4-dinitrobenzene sulfonyl (DNS) moiety. The probe produces very low fluorescence due to ICT between the DNS group and the BYN-OH derivative. In the presence of Cys and H2S, the DNS group cleaved by nucleophilic substitution reaction, releasing the far-red fluorophore BYN-OH and resulting in an 81- and 122 fold increase in fluorescence at 610 nm, respectively. The probe exhibits significant selectivity for Cys and H2S compared to structurally similar thiol, including homocysteine (Hcy) and glutathione (GSH). The detection limits were calculated to be 85 nM for Cys and 68 nM for H2S. The quantum yield of the probe in the presence of H2S was calculated to be 0.63. The practical applicability and biocompatibility of BYN-DNS were confirmed via human blood serum analysis and live-cell fluorescence imaging
Prediction of Lateral Capacity of Flexible Pile Group Subjected to Lateral Load in Sloping Ground for Prescribed Displacement
No full textTo understand the resistance of laterally loaded pile groups in a slope, an experimental 1 g model study and a finite element analysis study were conducted. The parameters varied were soil shear strengths, spacing between the piles, slope angles and various pile positions. The pile group were placed along the slope at a position related to relative stiffness from the crest of the slope. Additionally, finite element analysis was carried where the soil was modelled as a Mohr–Coulomb material, and the pile was represented as a beam element. With an increase in shear strength and spacing, the lateral resistance increases. It decreased with an increase in steepness of the slope and when it was placed away from the crest of the slope, compared to horizontal ground. The bending moment was high for lower consistency and spacing, and it was high for higher slope angles and larger stiffness factors. The depth of the maximum bending moment increased when the pile moved along the slope. From the parametric study conducted, a non-dimensional chart was proposed to estimate the lateral bearing capacity of the pile group along the slope
Engineered fluorescent carbon dots for selective cellular bioeffects: a comparative study of cancer and normal cells
No full textUncertainty Bounds for Anomalous Geomagnetic Storm Forecasting - A Deep Learning Approach
No full textWe present a novel approach to forecast geomagnetic storms by employing a multitask multivariate transformer-based methodology. Our model demonstrates the ability to predict the Sym-H, Ap, and Kp indices simultaneously, which serve as widely recognized proxies for assessing geomagnetic activities. Diverging from prior models that heavily rely solely on solar-wind indices, our novel methodology aims to overcome their limitations and yield improved forecasting capabilities using a multitask prediction approach. Through rigorous training on a meticulously curated high-resolution dataset spanning from the 1990s, our model attains remarkable accuracy and reliability in predicting severe geomagnetic storms. Considering the profound implications of these storms on electric grids and communication systems, our overarching objective is to provide comprehensive forecasts with well-defined uncertainty bounds
Constraining the 3HDM parameter space
No full textOne of the standard ways to study scenarios beyond the Standard Model involves extending the Higgs Sector. This work examines the Three Higgs Doublet Model (3HDM) in a Type-Z or democratic setup, where each Higgs doublet couples exclusively to a specific type of fermion. The particle spectrum of the 3HDM includes four charged Higgs bosons, two CP-odd scalars, and three CP-even scalars. This work investigates the allowed mass and coupling parameter space in the Type-Z 3HDM after imposing all theoretical and experimental constraints. We extract the allowed parameter space under three distinct alignment-limit conditions or mass hierarchies leveraging machine learning techniques. Specifically, we analyze scenarios where the 125 GeV Higgs is the lightest, an intermediary, or the heaviest CP-even Higgs boson. Our findings indicate that while a single lighter CP-even Higgs boson below 125 GeV still remains a possibility, the presence of two lighter Higgses is ruled out
