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Hazard identification of endocrine-disrupting carcinogens (EDCs) in relation to cancers in humans
Endocrine disrupting chemicals or carcinogens have been known for decades for their endocrine signal disruption. Endocrine disrupting chemicals are a serious concern and they have been included in the top priority toxicants and persistent organic pollutants. Therefore, researchers have been working for a long time to understand their mechanisms of interaction in different human organs. Several reports are available about the carcinogen potential of these chemicals. The presented review is an endeavor to understand the hazard identification associated with endocrine disrupting carcinogens in relation to the human body. The paper discusses the major endocrine disrupting carcinogens and their potency for carcinogenesis. It discusses human exposure, route of entry, carcinogenicity and mechanisms. In addition, the paper discusses the research gaps and bottlenecks associated with the research. Moreover, it discusses the limitations associated with the analytical techniques for detection of endocrine disrupting carcinogens. 2024 Elsevier B.V. -
Dirty Tracks Across the Border: Global Operations of Extraction, Labour and Migration at a Railway Station on the BiharNepal Border
This article is based on an ethnography of the railway siding at Raxaul Junction railway station, a town on the BiharNepal border, which finds itself at the intersection of a massive logistical exercise by China in the form of the Belt Road Initiative, counter-logistical apparatus building by India and incremental hardening of an otherwise open border by Nepal. The article will analyse in detail the intricate network of the labour market that operates at and through the railway siding. It will also trace the origins of commodities used in the cement factories in the industrial corridor of Nepal that are extracted from some of the most deprived regions of India at great human and social costs. Finally, I will describe some of the latest exercises in logistical operations such as containerisation, opening of a new land port, the Integrated Check Post in Raxaul and operationalisation of a new dedicated freight corridor from Vishakhapatnam port to Raxaul, which is reconfiguring the logistical arrangements away from Kolkata and Haldia port and their implications on labour and labour practices. The Raxaul railway siding will be, hence, studied on multiple scales: global, national and local. The article will also try to understand the transformation of this very peculiar border town located on a unique border. This transformation is creating new labour processes, migratory processes and networks, and new modes of production of workers subjectivities and resistance along the global logistical apparatus and supply chains. It will also open up the possibilities of thinking conceptually about South Asian Border Systems. 2024 South Asian University. -
A versatile sensor capable of ratiometric fluorescence detection of trace water and turn-on detection of Cu2+ modulating the binding interaction of a Cu(ii) complex with BSA and DNA complemented by docking studies
A fluorescent molecule, pyridine-coupled bis-anthracene (PBA), has been developed for the selective fluorescence turn-on detection of Cu2+. Interestingly, the ligand PBA also exhibited a red-shifted ratiometric fluorescence response in the presence of water. Thus, a ratiometric water sensor has been utilized as a selective fluorescence turn-on sensor for Cu2+, achieving a 10-fold enhancement in the fluorescence and quantum yield at 446 nm, with a lower detection limit of 0.358 ?M and a binding constant of 1.3 106 M?1. For practical applications, sensor PBA can be used to detect Cu2+ in various types of soils like clay soil, field soil and sand. The interaction of the PBA-Cu(ii) complex with transport proteins like bovine serum albumin (BSA) and ct-DNA has been investigated through fluorescence titration experiments. Additionally, the structural optimization of PBA and the PBA-Cu(ii) complex has been demonstrated by DFT, and the interaction of the PBA-Cu(ii) complex with BSA and ct-DNA has been analyzed using theoretical docking studies. 2024 The Royal Society of Chemistry. -
Online cooperative learning: exploring perspectives of pre-service teachers after the pandemic
Mainly, research has explored pre-service teachers perspectives toward cooperative learning within face-to-face teaching. However, in a post-pandemic scenario, previous research has yet to effectively explore pre-service teachers (PSTs) perspectives toward online cooperative learning (OCL) in teacher education programs. So, recognizing the gap in the literature, this paper aims to explore the perspectives of PSTs towards OCL. The researchers employed a qualitative research design for the present study. The researchers conducted semi-structured interviews with 10 PSTs who underwent OCL during the pandemic. These PSTs may possess digital proficiency, virtual collaboration abilities, flexibility in evolving educational environments, and an enhanced understanding of online cooperative learning methodologies within modern education. Researchers employed a thematic analysis to analyze the qualitative data obtained. The various themes that emerged from the study are perceived benefits of OCL, challenges to OCL, technological proficiency, learning strategies and support, and building a supportive online learning community. Future researchers may contribute to advancing effective online learning practices by gaining a deeper understanding of pre-service teachers perspectives towards OCL through research on a larger scale, including various teacher education programs in various countries. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Experimental Investigation of Uniaxial Compressive Behavior of Composite Columns without and with Full and Partial CFRP Wraps
Concrete columns are the backbone of any major structure, and their strengthening, repair, and retrofit have always drawn special research attention. One of the techniques for strengthening and improving the ductility of concrete columns has been the application of carbon fiber-reinforced polymer (CFRP) materials. A total of 43 columns of different configurations were experimentally investigated to evaluate the uniaxial compressive behavior of composite columns. Experimental and international code-recommended load-carrying capacities, stress-strain relations, axial stiffness, ductility factor, and failure modes were examined in the study. When fully wrapped, the strength of both plain cement concrete and reinforced cement concrete columns improved by 21% each with reference to the unwrapped columns. In addition to providing the advantages of external confinement to the columns, full wrapping contributed to a strength increment of 21%, which compared well with the steel reinforcement contribution to a strength increment of 28% to 39%. The partial wrapping technique was found to be an economical alternative to the full wrapping technique, with strength enhancements of 6% to 12% in the case of both plain cement concrete and reinforced cement concrete partially wrapped columns. Two regression models for the load-carrying capacity for columns with and without wraps were developed with four key performance parameters: percentage steel reinforcement, percentage concrete, percentage carbon fiber-reinforced polymer wrap, and the weight of the specimen. The formulated models were validated and found to be robust and consistent with the results. 2024 American Society of Civil Engineers. -
Magnetohydro-convective instability in a saturated DarcyBrinkman medium with viscous dissipation
The influence of dissipation with viscosity on magnetohydro-convective instability in a saturated DarcyBrinkman medium is examined. The bottom boundary is designated as adiabatic, whereas the top boundary is isothermal. Numerical linear stability analysis investigates normal modes that disturb the horizontal base flow at different inclinations. The case study shows that the most unstable disturbances are horizontal rolls, normal modes characterized by a wave vector perpendicular to the main flow direction. The horizontal rolls are the favored instability mode. Barletta et al. also showed that horizontal rolls are more unstable than any other oblique roll mode in the hydromagnetic scenario. This finding provides insights into the behavior of MHD fluid flow and heat transfer in porous media, with implications for applications in geoscience, engineering, and environmental science. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Machine Learning in Financial Distress: A Scoping Review
Predicting financial distress is crucial for stakeholders, policymakers, governments, and management in decision-making processes. Researchers have developed various prediction models encompassing both traditional and machine-learning approaches. Notably, recent attention has shifted towards employing machine learning models to address the limitations of traditional methods. This study seeks to offer insights into current trends, identify gaps, and suggest future research directions using machine learning models for financial distress prediction, employing the PRISMA Extension for Scoping Reviews methodology. To achieve this, a comprehensive search was conducted across three databasesScience Direct, EBSCO, and ProQuestspanning from 2020 to 2023, identifying 34 relevant articles for analysis. The findings underscore the prevalent use of Support Vector Machine in financial distress prediction, followed by the Random Forest Classifier and Artificial Neural Network, with little attention paid to other models. Furthermore, the study underscores the necessity for more research in developing countries, noting the predominance of studies from developed nations. While machine learning models hold promise for enhancing the accuracy and efficiency of financial distress prediction, additional research is imperative to evaluate their effectiveness and applicability across diverse contexts. This scoping review aims to furnish researchers, policymakers, and institutions with valuable insights and policy recommendations, shedding light on underexplored machine-learning techniques. 2024, Iquz Galaxy Publisher. All rights reserved. -
Forecasting the Volatility of Indian Forex Market: An Evidence from GARCH Model
Forecasting the volatility of forex market will create more trading opportunities to investors, despite of ups and downs in the forex market. The present study attempted to examine how the volatility in the exchange rate between Indian rupee and selected four foreign currencies, such as US dollar, euro, Japanese yen and British pound, can influence the market return. The data, used in the present study, covered the daily price observation of four foreign currencies, for a period of 5 years, from 2019-2023. The GARCH (1, 1) (generalized autoregressive conditional hetero skedasticity) was used for develop the model for foreign exchange (FX) rates volatility. Mean equation model confirmed that the series had attained stationary and previous price did influence the current price. It was also supported by co-efficient values in the variance equation. The co-efficient value, in the variance equation, was around one, which showed that the forex market was efficient. Further, it was validated that the volatility shocks in forex market were quite persistent. The active investors in the market may use this opportunity immediately. The policy maker may correct this deviation through timely intervention in the currency market. 2024, Iquz Galaxy Publisher. All rights reserved. -
Quantum-inspired meta-heuristic approaches for a constrained portfolio optimization problem
Portfolio optimization has long been a challenging proposition and a widely studied topic in finance and management. It involves selecting and allocating the right assets according to the desired objectives. It has been found that this nonlinear constraint problem cannot be effectively solved using a traditional approach. This paper covers and compares quantum-inspired versions of four popular evolutionary techniques with three benchmark datasets. Genetic algorithm, differential evolution, particle swarm optimization, ant colony optimization, and their quantum-inspired incarnations are implemented, and the results are compared. Experiments have been carried out with more than 10 years of stock price data from NASDAQ, BSE, and Dow Jones. This work proposes several enhancements to allocate funds efficiently, such as improved crossover techniques and dynamic and adaptive selection of parameters. Furthermore, it is observed that the quantum-inspired techniques outperform the classical counterparts. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
An Efficient Deep Learning Model Using Harris-Hawk Optimizer for Prognostication of Mental Health Disorders
Mental health disorders are primarily life style driven disorders, which are mostly unidentifiable by clinical or direct observations, but act as a silent killer for the impacted individuals. Using machine learning (ML), the prediction of mental ailments has taken significant interest in medical informatics community especially when clinical indicators are not there. But, majority studies now focus on usual machine learning methods used to predict mental disorders with few organized health data, this may give wrong signals. To overcome the drawbacks of the conventional ML prediction models, this work presents Deep Learning (DL) trained prediction model for automated feature extraction to realistically predict mental health disorders from the online textual posts of individuals indi cating suicidal and depressive contents. The proposed model encompasses three phases named pre-processing, feature extraction and optimal prediction phase. The developed model utilizes a novel Sparse Auto-Encoder based Optimal Bi-LSTM (SAE-O-Bi-LSTM) model, which integrates Bi-LSTM and Adaptive Harris-Hawk Optimizer (AHHO) for extracting the most relevant mental illness indicating features from the textual content in the dataset. The dataset utilized for training consist of 232074 unique posts from the "SuicideWatch" and "Depression" subreddits of the Reddit platform during December 2009 to Jan 2021 downloaded from Kaggle. In-depth comparative analysis of the testing results is conducted using accuracy, precisions, F1 score, specificity, and Recall and ROC curve. The results depict considerable improvement for our developed approach with an accuracy of 98.8% and precision of 98.7% respectively, which supports the efficacy of our proposed model. The Author(s) 2024. -
Memorialisation and Identity in Mah India: Revealing French Colonial Legacies
Mah nestled in the Mahdistrict of the Puducherry Union Territory in India, holds profound historical ties to French colonial India. Unlike the broader Indian subcontinent, which witnessed fervent anti-colonial movements against British rule leading to political decolonisation in 1947, Mahexperienced a belated political awakening, reluctantly integrating into the Indian Union in 1954. Despite the withdrawal of the French, the enduring legacy of French colonial ideology and culture continued to shape the ethos of Mah In contemporary times, a significant presence of French nationals in India, particularly in Pondicherry, Karaikal, and Mah has fostered the evolution of a unique linguistic identity known as Indian French. Within Mah landmarks such as St. Teresas Shrine, the Statue of Marianne in Tagore Park at Cherukallayi, remnants of St. George Fort, and sculptures inspired by M. Mukundans novel On the Banks of the Mayyazhi stand as tangible vestiges of the erstwhile French presence. Serving as repositories of bygone French culture, these sites emerge as dynamic arenas of memory production. Notably, Tagore Park in Mah adorned with fictional documentation through sculptures, assumes a pivotal role as a space that harmonizes memory and history, functioning as a reservoir for collective memory concerning French colonial rule. Mah deliberate urban planning reflects a nuanced approach, embodying the concept of a living testament to French colonialism rather than a conventional museum. This architectural strategy underscores the deliberate preservation and commemoration of Mah historical past. Through interviews with French nationals residing in Mah this research explores how these landmarks have become pivotal in the production of memories and the construction of identities for the French community in India and Mah Leveraging Maurice Halbwachs theoretical framework, the study unveils the intricate interplay between collective memory and present-day identity formation, shedding light on the transformation of personal memory into historical memory and its subsequent amalgamation into collective memory. With close to 50 French families residing in and around Mahstill, the study involves interviews with ten families, focusing on landmarks like St. Teresas Shrine, the Statue of Marianne, the ruins of St. George Fort, and sculptures based on one of M. Mukundans novels. So, through interviews of the French citizens of Mah this paper highlights how the cultural artefacts and popular landmarks of Mahbecome sites of memory of the French colonisation. 2024, The International Academic Forum (IAFOR). All rights reserved. -
Optical Resonator-Enhanced Random Lasing using Atomically Thin Aluminium-based Multicomponent Quasicrystals
Photon trapping inside a gain medium using a dispersed two-dimensional (2D) passive scatterer is an impetus to obtain incoherent random lasing (ic-RL) emission due to non-resonant feedback. An optical resonator (OR) can be used to influence such lasing thresholds. Non-noble nanomaterials-based quasicrystals (QCs) are an intriguing research prospect due to their potential surface plasmon resonance (SPR) property and ability to be exfoliated into 2D. In this work, an aluminium-based multicomponent alloy (Al70Co10Fe5Ni10Cu5) has been synthesized via the arc melting method. Thereafter, ultrasonication-based liquid phase exfoliation was used to obtain 2D quasicrystals (2D-QCs). The SPR-induced light scattering properties of synthesized 2D-QCs were exploited to obtain ic-RL from DCM dye gain medium under 532 nm, 10 ns, 10 Hz pulsed laser pumping. The plasmonic field enhancement property of 2D-QCs which enables the gain medium to absorb photons outside its peak absorption band has been demonstrated. The transition from ic-RL to OR-enhanced ic-RL and vice versa in the presence of resonator walls has been achieved by tweaking the device architecture. In this way, the ability of 2D-QCs to be potential passive scatterers and the controllability of lasing thresholds in the presence of an OR has been demonstrated. 2024 Elsevier Ltd -
I Dont Play Games: Migrant Workers and Digital Media in Bengaluru
The great impact of media technologies in reordering almost every facet of modern life has been noted by theorists for over a century now, particularly since the idea of the global village imagined by media theorists, and enabled by globalisation and digital technology has become an inescapable reality. The new experience of time and space bears upon various dimensions of life, including the nature of work, the organisation of time and the place of leisure within these rhythms. This article attempts to engage with this very weighty body of scholarship in a modest way, through ethnographic research, to understand how mobile phones and internet technologies structure the experience of everyday life for low-income migrant workers in Bengaluru. The sites include a construction site and a hookah bar, and the study focuses on mobile gaming and the structuring of migrant social networks. 2024 South Asian University. -
Assessment of artificial intelligence-based digital learning systems in higher education amid the pandemic using analytic hierarchy
The devastating effects of the 2020 worldwide COVID-19 virus epidemic prompted widespread lockdowns and restrictions, which will continue to be felt for decades. The repercussions of the pandemic have been most noticeable among educators and their students, which boosts the effectiveness of various AI-based learning systems in the education system. This study examines the AI-based digital learning platforms in higher education institutions based on various characteristics and uses of these systems. Several significant aspects of AI-based digital learning systems were obtained from the available literature, and significant articles were selected to properly examine various characteristics and functions of AI-based digital learning platforms used by multiple higher education institutions. The analytical hierarchy process (AHP) is employed to rank multiple AI-based learning systems based on key factors and their sub-factors. The studys outcome revealed which AI systems are effectively used in developing digital learning systems by various higher education institutions. The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024. -
LP norm regularized deep CNN classifier based on biwolf optimization for mitosis detection in histopathology images
Mitosis detection, a crucial biomedical process, faces challenges like cell morphology variability, poor contrast, overcrowding, and limited annotated dataset availability. This research presents a novel method for mitosis detection in histopathological images highlighting two important contributions using a Bi-wolf optimization-based LP norm regularized deep Convolutional neural network (CNN) model. This hybrid optimization protocol is the key to the precise calibration of model parameters and effective training, which translates into optimal classifier performance. The results reveal that this model achieves high accuracy, sensitivity, and specificity values of 96.69%, 91.89%, and 97.74% respectively. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Artificial intelligence service agents: a silver lining in rural India
Purpose: The study aims to examine the impact of an artificial intelligent service agent (AISA) on customer services to the rural population provided by KAYA, Kotak Life's AI-enabled insurance chatbot avatar that offers quality insurance services. Design/methodology/approach: Multi-stage cluster sampling method was adopted to collect the responses from the 707 customers across the rural population of southern states of India. SPSS V.2 and Smart PLS 4 were used to apply simple percentage analysis, multiple linear regression analysis, and structural equation modeling (SEM) to validate the hypothesis. The dependent variables are economic performance and market performance based on the independent variables: efficiency, security, availability, enjoyment and contact. Findings: The study revealed that efficiency and security are the highest predictors and the most influencing variables in predicting the economic and market performance of the insurance companies in determining the quality of service when rendered through AISA among the customers. Efficiency, security, availability, contact and enjoyment are the critical dimensions of AISA. It has a more significant impact on quality service (claim processing) to the rural population. It improves the economic and market performance among the insurance companies and the rural population. Originality/value: Customers need convenience when making claims. Even little challenges might lead to stress and unhappiness, depending on the situation. Restrictions on where customers can file claims may not be the most outstanding service insurance firms can offer, given rising travel and commuting costs and widening geographical borders. Customers value proactive communication from service providers about the status of their insurance claims. 2023, Emerald Publishing Limited. -
Global iPhone Local Labour: Exploring ICT Production, Labour and Cultural Production
A theory of value pertinent to the contemporary iPhone era focuses on formal and informal labour circuits. This study extends this framework by examining a labour dispute in an iPhone factory near Bangalore, delving into its dissemination through media and the broader critical political economy surrounding the recent iPhone production in India. Furthermore, it incorporates a geographical perspective into the circuit framework to illustrate the movement of capital and labour in Bangalore, rekindling discussions on coreperiphery dynamics in the context of capital and labour migration. Further, this research builds upon the typography of worker-generated content by illustrating a specific category of such content within the iPhone labour dispute. Utilising a critical political economy of media approach, this article aims to assess the broader implications of the updated framework and to open new avenues for research within the emerging field of information communication technologies, cultural production and labour. 2024 South Asian University. -
On-off fluorescence detection of exposed phosgene via pyrazine ring formation on a triphenyl amine backbone supplemented with a theoretical approach and practical environmental applications
Using 4-(diphenylamino)benzaldehyde as the fluorophore and 2,3-diaminomaleonitrile, a fluorescent probe known as 2-amino-3-(((E)-4-(diphenylamino)benzylidene)amino)-maleonitrile (ADM) has been developed for the selective detection of phosgene through a unique cyclization pathway producing a substituted pyrazine derivative attached to a triphenyl amine backbone. This reaction led to a notable reduction in the emission intensity of ADM at 565 nm. This is the first study that reports ADM as a sensory material for the selective detection of phosgene, achieved by forming a new heterocyclic pyrazine structure. With a quick response time of only 80 seconds, the detection limit of the probe ADM towards phosgene has been calculated as 4.23 ?M. Several spectroscopic methods, including UV-vis, emission spectroscopy, mass spectrometry, and computational investigations are used to study the sensing behavior. In practical applications, the sensor ADM can be used for soil analysis, the dipstick method, and the detection of phosgene from chlorinated hydrocarbon sources such as dichloromethane, chloroform and household solvents like paint remover. 2024 The Royal Society of Chemistry. -
Indian Social Stock Exchange as a Funding Avenue for Social Enterprises
Purpose: The growth of Indian social enterprises faces a significant obstacle, which is a lack of access to finance. The social stock exchange was recently launched to cater to this problem. This study explored the financial challenges the selected social enterprises faced in India and analyzed the performance of small and medium enterprises platforms. Methodology: Three variables were subjected to descriptive analysis: migration to the principal board, funds generated, and listings by small and medium-sized enterprises. Furthermore, market volatility was evaluated using the generalized autoregressive conditional heteroskedasticity (GARCH) model. To explore financial constraints, primary research entailed conducting in-depth interviews utilizing the case study technique with both for-profit and non-profit social companies. Findings: The findings from the study concluded that IPO financing significantly supported Indian SMEs. Additionally, social enterprises face significant financing challenges related to affordability, availability, and regulation. Social stock exchange presents a promising solution to these constraints. Practical Implications: The study has recommended defining social enterprises legally will help in strengthening the operating framework of a social stock exchange. The study emphasized the important role of finance in the viability of social enterprises by highlighting financial challenges. The findings provided useful information for various stakeholders to bridge the funding gap, thereby promoting the potential advantages of the social stock exchange platforms. Originality: The study addressed the research gap with an examination of small and medium enterprise platforms and the influence of the social stock exchange on social enterprise financing in India. Primary data from both for-profit and non-profit social entrepreneurs added a disaggregated dimension. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Pemetrexed loaded gold nanoparticles as cytotoxic and apoptosis inducers in lung cancer cells through ROS generation and mitochondrial dysfunction pathway
Supramolecular nanoparticles containing peptides and drugs have recently gained recognition as an effective tumor treatment drug delivery system. A multitarget drug termed pemetrexed is effective against various cancers, including nonsmall cell lung cancer. The work aims to establish the capability of pemetrexed gold nanoparticles (PEM-AuNPs) to induce apoptosis and explore molecular changes. X-ray diffraction, Fourier-transform infrared spectroscopy, ultravioletvisible spectroscopy, scanning electron microscope, and transmission electron microscope were used to investigate the synthesized nanoparticles. The MTT assay was utilized to investigate the anticancer properties of PEM-AuNPs at varying concentrations (50, 100, and 200M). PEM-AuNPs demonstrated a decrease in cell viability with 55.87%, 43.04%, and 25.59% for A549 cells and 54.31%, 37.40%, and 25.84% for H1299 cells at the respective concentrations. To assess apoptosis and perform morphological analysis, diverse biochemical staining techniques, including acridine orange-ethidium bromide and 4?,6-diamidino-2-phenylindole nuclear staining assays, were employed. Additionally, 2?,7?-dichlorofluorescein diacetate staining confirmed the induction of reactive oxygen species generation, while JC-1 staining validated the impact on the mitochondrial membrane at the IC50 concentration of PEM-AuNPs. Thus, the study demonstrated that the synthesized PEM-AuNPs exhibited enhanced anticancer activity against both A549 and H1299 cells. 2024 International Union of Biochemistry and Molecular Biology, Inc.