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This book shows the effectiveness of DRASTIC model in a geographical setting for validation of vulnerable zones and presents the optimization of parameters for the development of precise maps highlighting several zones with varied contamination. Impact of vadose zone has also been assessed by considering every sub-surface layer.

The book summarizes the role of multiple enzyme targets and strategies to design and develop novel drug candidates for Alzheimer's disease (AD). It brings together researchers across the globe having varied scientific backgrounds and expertise in a single volume.The chapters highlight current information scientists have unraveled about the origin, pathogenesis and prevention of AD. The contributions consider both established and emerging drug targets viz. Tau proteins, TREM, and microglia. Topics covered in the book include multi-target anti-Alzheimer's agents, epigenetic modifications, and the role of specific proteins like TMP21 and Tau in AD. A section dedicated to pharmacological treatments discusses the significance of tubulin-modifying enzymes, memantine, and glutamate antagonists. Enzymatic targets for drug discovery are thoroughly examined, focusing on cholinesterase, secretases, and other enzymes. Additionally, the book explores innovative nano-carrier-based drug delivery methods, emphasizing the crucial role of nanotechnology in effective Alzheimer's treatment. The book aims to inform students and researchers in the field of neuroscience, medicine and pharmacology about current research and biochemical nuances of AD pathogenesis and enzymatic drug targeting strategies. Readership Students and researchers in the field of neuroscience, medicine and pharmacology.

Background Wood apple is a hardy yet underutilized fruit tree of the Indian subcontinent, valued for its nutritional, medicinal, and ecological significance. Despite its potential as a climate-resilient fruit species, the determinants of yield variability remain poorly characterized. This study aimed to quantify how morphometric descriptors of canopy architecture, floral, and fruit traits explain yield variation across 62 wood apple genotypes. By integrating multivariate statistics with explainable machine-learning models (Random Forest + SHAP), we provide the first data-driven framework for identifying trait combinations that govern productivity in this underutilized tree species. The approach offers a novel, interpretable path toward ideotype selection and precision orchard design. Results Extensive morphometric variability was observed across the 62 genotypes for vegetative, foliar, floral, fruit and seed traits, indicating a broad genetic base. Yield per tree ranged widely from 35 to 127 kg, with a mean of 75 kg tree⁻¹. Principal Component Analysis (PCA) showed that canopy architecture, branch traits, and leaf–fruit attributes collectively explained 31.1% of the total variation. Correlation analysis revealed positive associations of yield with tree shape, pulp colour, and fruit-bearing tendency, whereas ornamental fruit traits and excessive spine density were negatively related. The optimized Random Forest (RF) model achieved strong predictive performance on the test dataset (R² = 0.84; RMSE = 9.45 kg; MAE = 7.12 kg), significantly outperforming Multiple Linear Regression (R² = 0.62), Support Vector Regression (R² = 0.76), and the Deep Learning (MLP) model (R² = 0.71). RF identified tree shape (16%), open flower colour (11.3%), and pulp colour (9.0%) as the most influential predictors of yield. SHAP analysis further clarified the non-linear and interactive effects among traits, highlighting the combined influence of canopy vigour, reproductive efficiency, and fruit-quality attributes on productivity. Hierarchical clustering grouped the genotypes into three clusters, with Cluster 2 characterized by compact canopies, superior reproductive traits, and desirable pulp features showing the highest and most stable yield (mean 84.6 kg tree⁻¹). Cluster 0 displayed moderate-to-high yields (79.7 kg tree⁻¹) but with greater variability, while Cluster 1 comprised the lowest-yielding genotypes (70.4 kg tree⁻¹). These findings confirm that productivity in wood apple is jointly regulated by architectural and reproductive traits through coordinated source–sink dynamics. Conclusions Wood apple yield is governed by an integrated suite of architectural and reproductive traits, rather than single descriptors. Genotypes with compact canopies, regular bearing habit, and consumer-preferred pulp characteristics emerge as promising ideotypes for high productivity and orchard efficiency. By combining Random Forest and SHAP, this study demonstrates the practical value of explainable machine-learning tools in identifying actionable trait combinations and providing a robust, trait-based framework to support data-driven breeding and climate-smart orchard design in underutilized perennial fruit crops.

Energy Management: Conservation and Audit discusses the energy scenario including energy conservation, management, and audit along with the methodology supported by industrial examples. Energy economics of systems has been elaborated with concepts of life cycle assessment and costing, and rate of return. Topics such as energy storage, cogeneration, and waste heat recovery to energy efficiency have been discussed. The challenges faced in conserving energy sources (steam and electricity) have been elaborated along with the improvements in the lighting sector. Further, it covers optimization procedures for development in the industry related to energy conservation. It is focused on researchers, senior undergraduate and graduate students in energy management, sustainable energy, renewable energy, energy audits, and energy conservation. This book covers current information related to energy management and includes energy audit and reviews all the leading equipment (boilers, CHP, pumps, heat exchangers) as well as procedural frameworks (energy audits, action planning, monitoring). It includes energy production and management from an industrial perspective along with highlighting the various processes involved in energy conservation and auditing in various sectors and associated methods. It also explores future energy options and directions for energy security and sustainability.