Stakeholders' perspectives on critical success factors for environmental social and governance (ESG) implementation.

Environmental Social and Governance (ESG) has emerged as a sensitive issue, attracting the attention of a large audience that could not be ignored. Government bodies continue to pass regulations mandating organizations to comply with ESG principles. However, many organizations have had unsatisfactory results while promoting sustainability ideals due to various challenges.

Comparative evaluation between Taguchi method and response surface method for optimization of electrocoagulation process in the context of treatment of dairy industry wastewater.

The presence of a large amount of organic and inorganic pollutants in dairy effluent is a substantial environmental issue. This study investigated electrocoagulation (EC) as a potential treatment method for dairy wastewater under different operating conditions, such as applied voltage (5-25 V), electrolysis time (30-90 min), and inter-electrode distance (1-2 cm) by using aluminum electrodes. This study focuses on achieving the maximum removal of BOD, COD, and nitrate in dairy effluents with the aforementioned operating conditions.

Dried fish dataset for Indian seafood: A machine learning application.

Dryingfish is a simple and economical way to process the catch. It creates a profitable business for coastal communities by providing a market for their catches, even during periods of abundance. It's a traditional method to preserve fish, especially valuable in regions where fresh fish isn't readily available or affordable throughout the year.

Impact of microplastics on strength parameters of clayey, Sandy, silty soil: A comparative assessment.

The comparative assessment of a variety of microplastic contamination on various soil types hasn't been extensively explored in existing literature. The present study focuses on the comparative analysis of the impact of environmentally relevant concentrations of LDPE, HDPE, and PVC microplastic contamination (2 %, 4 %, and 6 %) on index properties and strength parameters of sandy, silty and clayey soil types at varying observation days 5,10,15,20,25, and 30 days. Extensive experimental investigations are carried out to understand the effect of contamination on moisture content, specific gravity, liquid limit, plastic limit, plasticity index, optimum moisture content, maximum dry density, and shear strength parameters of the respective soil type.

Integrative approach for efficient detection of kidney stones based on improved deep neural network architecture.

In today's digital world, with growing population and increasing pollution, unhealthy lifestyle habits like irregular eating, junk food consumption, and lack of exercise are becoming more common, leading to various health problems, including kidney issues. These factors directly affect human kidney health. To address this, we require early detection techniques that rely on text data.

Differential Diagnosis, Prevention Measures, and Therapeutic Interventions for Enhanced Monkeypox (Mpox) Care.

Monkeypox (Mpox) is a rare viral disease that presents considerable challenges in healthcare settings, necessitating enhanced nursing care for effective management. This review thoroughly explores key aspects related to improving nursing care for Mpox. It commences by examining the background information on Mpox, encompassing its etiology, epidemiology, and modes of transmission.

Probabilistic Tractography-Based Tremor Network Connectivity in Tremor Dominant Parkinson's Disease and Essential Tremor plus.

The basal ganglia-thalamocortical (BGTC) and cerebello-thalamocortical (CTC) networks are implicated in tremor genesis; however, exact contributions across disorders have not been studied. Evaluate the structural connectivity of BGTC and CTC in tremor-dominant Parkinson's disease (TDPD) and essential tremor plus (ETP) with the aid of probabilistic tractography and graph theory analysis. Structural connectomes of the BGTC and CTC were generated by probabilistic tractography for TDPD ( = 25), ETP (ET with rest tremor, = 25), and healthy control (HC, = 22).

Application of the Nadaraya-Watson estimator based attention mechanism to the field of predictive maintenance.

Attention mechanism has recently gained immense importance in the natural language processing (NLP) world. This technique highlights parts of the input text that the NLP task (such as translation) must pay "attention" to. Inspired by this, some researchers have recently applied the NLP domain, based, attention mechanism techniques to predictive maintenance.

Unlocking the secrets of apple harvests: Advanced stratification techniques in the Himalayan region.

This study focuses on standardizing sampling techniques and comparing various methods of sample allocation to effectively estimate apple area and production in the Himalayan region of India. We investigate different stratification tools,in formulating a sampling plan using information gathered from select orchardists in the locale during the 2016-17 period, it becomes essential to explore diverse methodologies to define the most suitable stratum boundaries, ascertain the requisite number of strata, and identify the optimal sample size. The stratification process, underpinned by the "Area under Apple" variable, which demonstrates a pronounced association with apple production, assumes a central role in this endeavor Several methods are utilized to construct strata, such as equalizing strata totals, cumulative equalization, equalization of ½{r(x) + f(x)} and equalization of .

Modelling Key Drivers of Employee Behaviour for Personal and Professional Excellence.

Introduction: Though, having right set of behavioural skills is always been a priority of all organizations, nevertheless, today's organizations are investing too much on behavioural skill training to safeguard their brand value, bring-up the work culture, maintaining reputation, etc. Behavioural skills plays a vital role in personal development and well-being at student level also. This paper identifies and analyzes the fourteen behavioural skills which are vital in the personal and professional excellence development of a student.

Characterization of a novel inulosucrase from Lactiplantibacillus plantarum.

Fructansucrases produce fructans by polymerizing the fructose moiety released from sucrose. Here, we describe the recombinant expression and characterization of a unique fructansucrase from Lactiplantibacillus plantarum DKL3 that showed low sequence similarity with previously characterized fructansucrases. The optimum pH and temperature of fructansucrase were found to be 4.

CSDNet: A Novel Deep Learning Framework for Improved Cataract State Detection.

Cataracts, known for lens clouding and being a common cause of visual impairment, persist as a primary contributor to vision loss and blindness, presenting notable diagnostic and prognostic challenges. This work presents a novel framework called the Cataract States Detection Network (CSDNet), which utilizes deep learning methods to improve the detection of cataract states. The aim is to create a framework that is more lightweight and adaptable for use in environments or devices with limited memory or storage capacity.

Decoding the role of aldosterone in glycation-induced diabetic complications.

Diabetes-mediated development of micro and macro-vascular complications is a global concern. One of the factors is hyperglycemia induced the non-enzymatic formation of advanced glycation end products (AGEs). Accumulated AGEs bind with receptor of AGEs (RAGE) causing inflammation, oxidative stress and extracellular matrix proteins (ECM) modifications responsible for fibrosis, cell damage and tissue remodeling.

Detecting health misinformation: A comparative analysis of machine learning and graph convolutional networks in classification tasks.

In the digital age, the proliferation of health-related information online has heightened the risk of misinformation, posing substantial threats to public well-being. This research conducts a meticulous comparative analysis of classification models, focusing on detecting health misinformation. The study evaluates the performance of traditional machine learning models and advanced graph convolutional networks (GCN) across critical algorithmic metrics.

Towards secure IoT networks: A comprehensive study of metaheuristic algorithms in conjunction with CNN using a self-generated dataset.

The Internet of Things (IoT) has radically reformed various sectors and industries, enabling unprecedented levels of connectivity and automation. However, the surge in the number of IoT devices has also widened the attack surface, rendering IoT networks potentially susceptible to a plethora of security risks. Addressing the critical challenge of enhancing security in IoT networks is of utmost importance.

Exploring the abundance of microplastics in Indian landfill leachate: An analytical study.

Landfills are a major source of many emerging pollutants, including microplastics (MPs). This makes them a potential threat to human and environmental health and calls for a more detailed analysis of their hazard potential. India is a developing country with multiple unscientific waste dumping sites.

Public health nurse perspectives on predicting nonattendance for cervical cancer screening through classification, ensemble, and deep learning models.

Objectives: Women's attendance to cervical cancer screening (CCS) is a major concern for healthcare providers in community. This study aims to use the various algorithms that can accurately predict the most barriers of women for nonattendance to CS.

Design: The real-time data were collected from women presented at OPD of primary health centers (PHCs).

Benzyl isothiocyanate as an alternative to antibiotics? a comparative in vivo study using Pseudomonas aeruginosa infection as a model.

Due to over-prescription of antibiotics, antimicrobial resistance has emerged to be a critical concern globally. Many countries have tightened the control of antibiotic usage, which, in turn, promotes the search for alternatives to antibiotics. Quite a few phytochemicals have been investigated.

Design of antipodal vivaldi antenna with patch and corrugations for 5G applications.

A compact 1 × 4 antipodal Vivaldi antenna (AVA) array designed for 5 G applications is introduced in this study. An elliptical-shaped parasitic patch and corrugation are strategically employed to enhance gain and bandwidth, making it well-suited for 5 G applications. The resulting AVA array with corrugation and parasitic patch (AVA-PC) is designed and simulated on ANSYS HFSS, demonstrating a stable gain ranging from 10 dBi to 11.

Examining the relationship between pro-environmental consumption behaviour and hedonic and eudaimonic motivation.

The present study examines the factors that influence the adoption of environmentally friendly products and environmentally conscious consumption by individuals. The conceptual framework incorporates environmental knowledge, perceived behavioral control, environmental concern, and perceived consumer efficacy in order to highlight the factors that contribute to environmental consciousness. Incorporating the theories of reasoned action and planned behavior, 479 participants completed structured questionnaires as part of this study.

Plausible role of INPP4A dysregulation in idiopathic pulmonary fibrosis.

INPP4A has been shown to be involved in the regulation of cell proliferation and apoptosis of multiple cell types including fibroblasts. Previous reports from our group have demonstrated the role of inositol polyphosphate 4-phosphatase Type I A (INPP4A) in these functions. Though existing evidences suggest a critical role for INPP4A in the maintenance of lung homeostasis, its role in chronic lung diseases is relatively under explored.

Novel design of cryptographic architecture of nanorouter using quantum-dot cellular automata nanotechnology.

The article introduces a revolutionary Nanorouter structure, which is a crucial component in the Nano communication regime. To complete the connection, many key properties of Nanorouters are investigated and merged. QCA circuits with better speed and reduced power dissipation aid in meeting internet standards.

Ensemble Learning for Higher Diagnostic Precision in Schizophrenia Using Peripheral Blood Gene Expression Profile.

Introduction: Stigma contributes to a significant part of the burden of schizophrenia (SCZ), therefore reducing false positives from the diagnosis would be liberating for the individuals with SCZ and desirable for the clinicians. The stigmatization associated with schizophrenia advocates the need for high-precision diagnosis. In this study, we present an ensemble learning-based approach for high-precision diagnosis of SCZ using peripheral blood gene expression profiles.

Clinical and Biochemical Characteristics of COVID-19-Associated Acute Kidney Injury (COVAKI): A Proof-of-Concept Case-Control Study.

Introduction Acute kidney injury (AKI) develops in 20-70% of patients with COVID-19. AKI is a syndromic diagnosis with multiple causes and outcomes. This cross-sectional study explored different outcomes of AKI in patients admitted with COVID-19.