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The ongoing trend of warming climate has made Glacial Lake Outburst Floods (GLOFs) a major cryospheric hazard worldwide, especially in the Himalayas. GLOFs in the Himalayan region are mostly caused by moraine-dammed proglacial lakes and ice-dammed lakes. These sporadic disasters have resulted in significant loss of life and property. This study offers a comprehensive analysis of the GLOF hazard potential of a potentially dangerous proglacial lake (PDGL) in the Ladakh region. This research explores the GLOF threat from the lake using multi-criteria analysis and advanced 2D hydrodynamic modeling approaches. The mass balance response of the mother glacier, its flow dynamics, and glacier-lake interactions were examined for the past 22 years. The findings show that over this period, the PDGL has had a notable expansion of 78.7%, accompanied by a significant recession of 13.2% in its feeding glacier. The glacier has witnessed an average thickness loss of ⁓7 m at the rate of 0.32 m a−1 during this period. The average, lowest, and maximum depth of the glacier were found to be 30.95, 14.30, and 50.57 m, respectively and the average velocity of the glacier was estimated as 3.38 m a−1. Because of the lake’s rapid expansion and steep surrounding slopes, it was classified as a high-hazard lake. The risk to the downstream community was assessed through 2D hydrodynamic modeling using the HEC-RAS tool. The maximum discharge under the worst-case scenario for the piping and overtopping failures was estimated as 3890.99 m3s−1 and 5111.39 m3s−1, respectively. The area potentially under the threat of inundation was calculated to be 4.74 and 5.38 km2 for the moderate and worst-case scenarios respectively. The expected maximum flood velocities range from 18.26 to 23.78 meters, respectively for the moderate and worst-case scenarios. At several locations in the downstream area, routed hydrographs representing the GLOF propagation were generated. The findings show that the flood wave in the worst-case scenario would arrive at the first settlement in 50 min, with a peak velocity of 12.36 m s−1. The potentially inundated area includes critical infrastructure such as bridges, residential houses, and roads. To mitigate the potential risk associated with this lake, a more detailed and on-site study is highly recommended.

Climate change poses significant challenges to the Himalayas, a region characterised by its fragile ecosystems and vulnerable communities dependent on environmental resources. Accurate climate data are crucial for understanding regional climatic variations and assessing climate change impacts, particularly in areas with limited observational networks. This study represents a pioneering effort in evaluating climatic fluctuations in the Jhelum basin, located in the North Western Himalayas, by utilising a diverse range of gridded meteorological datasets (APHRODITE, CHIRPS, CRU, and IMDAA) alongside observed climate data from the Indian Meteorological Department. The primary goal is to identify the most effective gridded climate data product for regions with limited data and to explore the potential of combining gridded data sets with observed data to understand climatic variability. Findings indicate a consistent upward trend in temperature across all datasets, with varying rates of increase. CRU records a rise of 1 °C in Tmax and 1.6 °C in Tmin, while APHRODITE shows a Tmean increase of approximately 1 °C. IMDAA reports increases in Tmax and Tmin. Observed mean annual Tmax and Tmin show net increases of 1 °C and 0.6 °C, respectively. Regarding precipitation, all datasets except IMDAA exhibit an increasing trend, contrary to observed data, which decreases from 1266 mm to 1068 mm over 40 years. CHIRPS, CRU, and APHRODITE display increasing trends, while IMDAA aligns closely with observed data but tends to overestimate precipitation by about 30%. Our research identifies IMDAA as the most suitable gridded climate data for the Jhelum basin in the North-western Himalayas. Despite some discrepancies in precipitation trends, IMDAA closely aligns with observed data, providing valuable insights for scholars and policymakers navigating climate data uncertainties in complex environments. Our findings contribute to informed decision-making and effective climate change mitigation strategies in the region.

Abstract In the intricate tapestry of environmental discourse, the field of political ecology emerges as a powerful lens through which we scrutinise the interplay of power, nature and society. This paper stages a dialogue with Paul Robbins to examine environmental justice, the decolonisation of political ecology, colonialism, sovereignty, climate change and capitalism. The dialogue challenges the conventional narratives of sovereignty and underscores the imperative of genuine decolonisation—beyond metaphorical interpretations—calling for the restitution of land and authority to Indigenous Peoples and other historically marginalised communities. The dialogue highlights the importance of moving away from capitalist systems that exacerbate environmental degradation. The dialogue calls for decolonising political ecology by including diverse perspectives, methodologies and ontologies and underlines the importance of control over productive resources. It emphasises that addressing the impacts of colonialism requires recognising and honouring the sovereignty of Indigenous Peoples and suggests that political ecology can contribute to decolonisation by focusing on sovereignty and supporting legal and institutional frameworks that empower marginalised communities. The paper discusses the way forward and the future trajectory of political ecology by suggesting that future research in political ecology should focus on diverse economies, embrace emerging technologies and rework academic institutions to value knowledge co‐production.

Climate change adaptation is a critical response to the challenges posed by climate change and is important for building resilience. Progress in adaptation efforts has been made globally, nationally, and locally through international agreements, national plans, and community-based initiatives. However, significant gaps exist in knowledge, capacity, and finance. The Adaptation Gap Report 2023, published by the United Nations Environment Programme (UNEP), examines the status of climate change adaptation efforts globally. The report highlights the widening adaptation finance gap and the deepening climate crisis. We analyse the key themes of the report and incorporate an analysis of the wider literature and insights from COP28 to substantiate key points and identify gaps where more work is needed to develop an understanding of climate change adaptation. This paper focuses on the underfinanced and underprepared state of global climate change adaptation efforts, the widening adaptation finance gap, slow progress in adaptation, gender equality and social inclusion issues, and challenges in addressing loss and damage. We provide a way forward for climate change adaptation and offer recommendations for future actions.

Acute emergencies have been neglected in efforts to understand and respond to the transformational climatic changes underway in the Arctic. Across the circumpolar north, social-technological changes, extreme weather, and changing ice conditions threaten lives and infrastructure, increasing the risk of mass casualty incidents (MCIs), particularly as they impact transportation systems including global shipping, aviation, and community use of semi-permanent trails on the ice, land, and water. The Arctic is an inherently dangerous environment to operate in, and due to living in permanent settlements and the uptake of mechanised modes of transportation and navigation technologies, people’s exposure to risks has changed. In responding to potential MCIs, emergency response systems face challenges due to remoteness, weather, and changing environmental conditions. We examine emergency response capacity in the Arctic, focusing on search and rescue and using examples from Canada and Greenland, identifying opportunities for enhancing emergency response as part of climate adaptation efforts.

Background: Class attendance is very important to improve academic performance in medical education. National Medical Commission has made it mandatory to have 75% attendance to appear in the university examination. Classroom teaching is necessary to develop competence in cognitive, affective, and psychomotor domains. The purpose of the present study was to analyze the causes of absenteeism in medical education. Methodology: This descriptive, cross-sectional study was conducted from phase 1 to phase III MBBS students of Government Medical College Srinagar, J and K, India. The response was collected through a structured, pretested, and prevalidated questionnaire. The attitude of medical students towards class absenteeism was obtained using the Likert scale. The response was analyzed using SPSS 22 software. Results: The results showed that major reasons for student absenteeism were poor teaching skills of teachers (mean 3.85), students studying through Self directed learning (SDL) (mean 3.75), unfavorable learning environment (mean 3.43), lack of sleep (mean 3.28), distraction due to concentration problems (mean 3.26) not interested with that subject (mean 3.09), ill-health (mean 2.57), traffic jams (mean 2.53), social media (mean 2.45), climatic conditions (mean 2.37), availability of online resources (mean 2.84), too much self-confidence (mean 2.61), lectures, not enough informative (mean 2.49), family issues (mean 2.01). Conclusion: The causes of student absenteeism are varied. Teachers have to be friendly and cooperative so that students can overcome their inhibitions and weaknesses. Constructive feedback and mentoring programs should be part of the curriculum.

Avian paramyxovirus serotype-1 (AMPV1) infects a wide range of avian species leading to broader range of clinical symptoms. The ease of transmission has allowed the virus to spread worldwide with varying degree of virulence depending upon virus strain and host range. Rapid detection is an important step to prevent an outbreak of the disease. The present study was carried out to detect APMV-1 from chicken reared in Kashmir Valley. Out of 12 suspected disease outbreaks, all were positive for AMPV-1. APMV-1 was detected using Matrix Protein gene (M gene) by RT-PCR. Detection by M gene is used for primary screening of the APMV-1 in chicken with both virulent and avirulent forms.

The introduction of the space object conjunction method in electromagnetic compatibility modeling and simulation is quite a novel concept. It is useful for the stochastic analysis of an electromagnetic (EM) environment which is based on the probability of conjunction assessment. The space conjunction methodology is anticipated as the frontline defense for the protection of active satellites in space. EM congestion occurs in an environment with the increase in the number of operational EM devices. In a theoretical sense, this congestion is analogous to the space conjunction. Therefore, the space conjunction model can be applied in the EM scenarios. In this paper, we have investigated the application of the defined conjunction model by using the analytical expression of the probability of electromagnetic conjunction, which is based on the orbital parameters of the system under test. Additionally, we have elaborated the influence of these orbital parameters on the probability of conjunction. The simulations have been performed by considering different EM scenarios and the results are validated by using Monte Carlo simulations. The results show that errors in the analytical and Monte Carlo simulations are within a 1% range, which makes the analytical model effective. Computationally, the proposed analytical model is cost effective as compared to the numerical method, i.e., Monte Carlo. Moreover, from the results, it has been validated that the probability of conjunction increases with the increase in transmitted power and decreases with the compatible threshold limit of the receiving system, thus, making this method useful for analyzing the electromagnetic environment and as a frontline safety tool for electromagnetic systems.

Recent advance in medical education is in correlation with the advances in information technology and thus computer-based learning is being increasingly employed. The objective of the present study was to design and evaluate an e-learning module in anatomy and assess the perceptions of students and faculty about this e-learning module. The participating students were randomized into three groups by block stratified randomization and Google groups were created for each of the three groups. The e-learning module was implemented in three sessions by rotating the three groups. Validated questionnaires were sent to faculty and participating students via Google forms to obtain feedback. The results of ANOVA showed that there was a significant difference among the groups in terms of marks obtained with conventional (F = 2.403, P = 0.103), online (F = 6.050, P = 0.005), and blended (F = 5.801, P = 0.006). Post hoc comparisons using the Tukey HSD test, about the gain of knowledge, indicated that the results were insignificant when comparing the conventional group with the online group, but were significant when comparing the blended group with the conventional and online group. The qualitative data regarding the perception of students toward e-learning were analyzed using thematic analysis. The introduction of an interactive e-learning module in anatomy was effective and well received by the students and faculty. The study showed that blended learning has a positive impact on the students' learning by improving cognitive gain and receptive perception for e-learning.

Purpose: This study examines sustainability communication's direct and indirect effects on consumer loyalty and brand reputation. It also aims to identify sustainable practices that enhance consumer behaviour and brand reputation. Methodology: The study used a cross-sectional survey design and collected data from 500 participants through an online survey. The survey included measures of sustainability communication, consumer loyalty, brand reputation, and demographic variables. Structural equation modelling (SEM) was used to test the hypothesised relationships between the variables. Findings: The results of the SEM analysis suggest that sustainability communication has a direct and positive effect on consumer loyalty, which in turn positively impacts reputation. Furthermore, the study identifies specific sustainability practices, such as reducing the carbon footprint and promoting ethical sourcing, that can positively influence consumer behaviour and brand reputation. Implications: The study underscores the significance of adept sustainability communication for fostering consumer loyalty and boosting brand reputation. Focusing on initiatives like loyalty programs and personalised offers can harness this connection. Additionally, the research identifies critical sustainable practices – carbon reduction, ethical sourcing, and renewable energy investment – that foster positive consumer behaviour and brand reputation. Originality/value: This study provides new insights into the mechanisms by which sustainability communication can influence consumer behaviour and brand reputation. The study identifies the importance of consumer loyalty as a mediator between sustainability communication and brand reputation. It recommends companies seeking to enhance their brand reputation through sustainability practices. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to evaluate, explore, and characterise the perceptions of the Indian private sector employers on the 21st century 4Cs (critical thinking, communication, creativity, and collaboration) skills gap, which affects their productivity. Need for Study: This research aims to shed light on the significant issue of the soft skills gap, precisely the 4Cs skills in India. Soft skills, including the 4Cs, are complex and crucial for organisations, and the shortage of these skills among the workforce is a growing concern. This research addresses enterprises' challenges in bridging this gap by exploring different ways to utilise these skills. Methodology: Fifty-six respondents were interviewed based on cluster sampling. An invitation was sent to 40 private sector organisations from five different industries. Only 15 organisations agreed to participate in the interview process. Findings: A total of seven were generated from the data, which included: (1) explicit and timely feedback; (2) compassion and understanding; (3) motivation deficiency; (4) lack of collaboration synergies; (5) lack of practical knowledge; (6) interpersonal skills; and (7) creating team culture. Implication: Given the prevalent skills gap, it is challenging for Indian industries and organisations to remain competitive in the global market. Investing in the education system, providing students with the necessary academic and vocational skills, and equipping them with soft skills, such as the 21st century 4Cs skills is essential to address this issue. Investment is necessary to prepare the workforce to meet the demands of emerging businesses and technologies, ensuring that industries and organisations remain competitive. [ABSTRACT FROM AUTHOR]

Purpose: This study delves into the complex realm of consumer behavior by exploring the impact of distinct shopping motives, encompassing status, value and gratification, on store satisfaction within the domain of organic food retail. Moreover, it seeks to decipher the influence of perceptual disparities between male and female patrons on the intricate nexus between shopping experience and consumer loyalty within organic food stores. Design/methodology/approach: A comprehensive dataset comprising responses from 400 participants was gathered and subjected to confirmatory analysis and structural equation modeling. These analytical tools were employed to dissect the data, validate the underlying research framework and unveil critical insights. Findings: The empirical analysis, facilitated by structural equation modeling, substantiates that organic food stores prioritize the organic attribute, primarily centered on healthiness, often to the detriment of broader conceptual and social aspects. This validates the interplay between shopping experience dimensions, customer contentment, loyalty and the intent to revisit. Gender, as a moderator, exerts a discernible influence on these relationships, highlighting distinct shopping behaviors among male and female consumers when gauging the influence of shopping experience dimensions within organic food retail establishments. Practical implications: The implications of this research resonate deeply within the organic food retail landscape. The insights garnered provide valuable guidance to organic food retailers aiming to enhance their store ambiance and allure, thereby fostering sustained customer satisfaction. This, in turn, augments the propensity for customer loyalty and repeat patronage, a particularly pressing concern in today's fiercely competitive retail milieu. Furthermore, the study carries significant ramifications for organic food producers and governmental entities, outlining a framework for augmenting the value proposition of organic foods in alignment with customer experiential paradigms. Originality/value: In a milieu characterized by the emergence of novel product categories and industry entrants, the study fills a critical void by investigating customer satisfaction within the broader retail food sector, with specific focus on organic food stores. Moreover, the research embarks on a pioneering exploration of the prospective trajectory of organic food stores in the Indian context, employing a marketing lens and grounded in the theory of needs satisfaction. [ABSTRACT FROM AUTHOR]

Climate change adaptation is a critical response to the challenges posed by climate change and is important for building resilience. Progress in adaptation efforts has been made globally, nationally, and locally through international agreements, national plans, and community-based initiatives. However, significant gaps exist in knowledge, capacity, and finance. The Adaptation Gap Report 2023, published by the United Nations Environment Programme (UNEP), examines the status of climate change adaptation efforts globally. The report highlights the widening adaptation finance gap and the deepening climate crisis. We analyse the key themes of the report and incorporate an analysis of the wider literature and insights from COP28 to substantiate key points and identify gaps where more work is needed to develop an understanding of climate change adaptation. This paper focuses on the underfinanced and underprepared state of global climate change adaptation efforts, the widening adaptation finance gap, slow progress in adaptation, gender equality and social inclusion issues, and challenges in addressing loss and damage. We provide a way forward for climate change adaptation and offer recommendations for future actions. [ABSTRACT FROM AUTHOR]

In the intricate tapestry of environmental discourse, the field of political ecology emerges as a powerful lens through which we scrutinise the interplay of power, nature and society. This paper stages a dialogue with Paul Robbins to examine environmental justice, the decolonisation of political ecology, colonialism, sovereignty, climate change and capitalism. The dialogue challenges the conventional narratives of sovereignty and underscores the imperative of genuine decolonisation—beyond metaphorical interpretations—calling for the restitution of land and authority to Indigenous Peoples and other historically marginalised communities. The dialogue highlights the importance of moving away from capitalist systems that exacerbate environmental degradation. The dialogue calls for decolonising political ecology by including diverse perspectives, methodologies and ontologies and underlines the importance of control over productive resources. It emphasises that addressing the impacts of colonialism requires recognising and honouring the sovereignty of Indigenous Peoples and suggests that political ecology can contribute to decolonisation by focusing on sovereignty and supporting legal and institutional frameworks that empower marginalised communities. The paper discusses the way forward and the future trajectory of political ecology by suggesting that future research in political ecology should focus on diverse economies, embrace emerging technologies and rework academic institutions to value knowledge co‐production. [ABSTRACT FROM AUTHOR]

To achieve high quality localization of nodes, a smart-mesh strategy is employed in the discontinuous Galerkin time-domain (DGTD) simulation. The strategy is able to adjust adaptively the nodes defined on the unstructured triangular element in real-time simulation, thus an arbitrary or uncertain shaped object can be modeled accurately. The benefits of smart-mesh strategy are demonstrated for a partially dielectric filled cavity with microscale random material height and uncertain rough interface. Numerical experiments show that the smart-mesh approach can capture fine structural information and achieve more effective positions to match variable shapes. [ABSTRACT FROM AUTHOR]

"I have chosen to no longer be apologetic for my femininity. And I want to be respected in all my femaleness." (Adichie, 15). Kamala Surayya (1934-2009), popularly known as Madhavikutty and Kamala Das, is beyond doubt the greatest woman poet in contemporary Indo-Anglian literature. Her poetic collection includes: Summer in Calcutta (1965), The Descendants (1967), The Old Playhouse And Other Poems (1973), The Anamalai Poems (1985), The Best of Kamala Das (1991) and Only Soul Knows How To Sing (1996). Kamala Das's poetry is replete with feministic ethos. She repudiated the archaic and somewhat sterile aestheticism for an independence of mind and body. Her poetry conveys her aversion to male domination and to the artificialities of modern life in which she feels suffocated. Her poetry is remarkably realistic and feministic. The paper aims at a feminist reading of Kamala Das's poetry whereby she effectively subverts the ingrained elements of patriarchy, privileging female will, choice and strength. [ABSTRACT FROM AUTHOR]

Attripate Krishnaswami Ramanujan (1929-1993) is one of the greatest modern poets of his generation. Startling originality and moving artistry are the key features of his poetry. His Indian experience is at the heart of his poetry. However, interestingly, none of the poems are vogue generalizations about India. On the other hand, they are rooted in peculiar experiences. His attitude towards India is more realistic than his contemporaries who portray India as a metaphysical rather than as a concrete, pragmatic space. His Indianness is, therefore, tempered by the right dose of irony and cosmopolitanism. Ramanujan is, therefore, a poet whose description of the Indian landscape is artistically realistic and in portraying his motherland realistically he has no parallel. The paper aims at studying Ramanujan's verse from the realistic perspective with special reference to his poem A River. [ABSTRACT FROM AUTHOR]

The Indian retail sector has seen a boom from past few years. The rise in the disposal income, urbanization and increasing FDI has helped the industry grow. India is ranked 6th largest country in terms of food and grocery. The food and grocery sector is the largest category with in the retail sector India. In order to survive in the market competition to have loyal customers is a very important for the organizations. A deeper understanding of what engenders store loyalty would be beneficial to retailers in developing appropriate strategies to satisfy loyal customers and to maintain a competitive advantage. The objective of the study will be to analyze the store loyalty of grocery retail. The data will be collected from the customers who will be shopping at these selected stores. The total of 300 customers from selected city will be sampled using mall intercept survey. This research consists of three variables, store image, store satisfaction and store loyalty. The independent variable is store image and it was divided into eight variables Store satisfaction will be introduced as mediator variable between store image and store loyalty. Store loyalty is the dependent variable for this study. The Results of the study showed that there exists a mediating relation between Store image and Store loyalty through Store Satisfaction. More ever the study also reveals the direct effect of some variables of store image with store loyalty. [ABSTRACT FROM AUTHOR]

A frequent cause of auto accidents is disregarding the proximal traffic of an ego-vehicle during lane changing. Presumably, in a split-second-decision situation we may prevent an accident by predicting the intention of a driver before her action onset using the neural signals data, meanwhile building the perception of surroundings of a vehicle using optical sensors. The prediction of an intended action fused with the perception can generate an instantaneous signal that may replenish the driver’s ignorance about the surroundings. This study examines electromyography (EMG) signals to predict intention of a driver along perception building stack of an autonomous driving system (ADS) in building an advanced driving assistant system (ADAS). EMG are classified into left-turn and right-turn intended actions and lanes and object detection with camera and Lidar are used to detect vehicles approaching from behind. A warning issued before the action onset, can alert a driver and may save her from a fatal accident. The use of neural signals for intended action prediction is a novel addition to camera, radar and Lidar based ADAS systems. Furthermore, the study demonstrates efficacy of the proposed idea with experiments designed to classify online and offline EMG data in real-world settings with computation time and the latency of communicated warnings.

The present study has attempted to create and examine a conceptually grounded working model that examines the moderating influence of utilitarian and hedonic shopping values with Indian grocery stores on the association between usage of Private Label (PL) and Store Loyalty (SL). For this, primary data was collected from 350 consumers, from different stores in India selling PL products. The theoretical model was analyzed using SEM. The findings of the study reflect that an inverse relationship between PL usage and SL. However, the presence of utilitarian shopping value reverses this into a positive linkage between PL usage and SL. This finding reflects some intriguing ramifications for retailers and corporate. For instance, evolving and aligning different marketing strategies help the retailers in creating the necessary USV so as to create shopping involvement that may help retailers to upgrade their SL in a favourable manner over the long term. Earlier research has not examined the involvement of PL items from the viewpoint of shopping value. Subsequently, this paper endeavours to examine the regulating effect of shopping value on the PL consumption and SL.

Inadequate training data is a significant challenge for deep learning techniques, particularly in applications where data is difficult to get, and publicly available datasets are uncommon owing to ethical and privacy concerns. Various approaches, such as data augmentation and transfer learning, are employed to address this problem, which help to some extent in removing this limitation. However, after a certain amount of data augmentation, the quality of the generated data stalls, and transfer learning suffers from the issue of negative transfer. This paper proposes a novel generative adversarial network-based synthetic data training (GAN-ST) model to generate synthetic data for training a lightweight convolutional neural network (CNN). An enhanced generator is proposed to quickly saturate and cover the colour space of the training distribution. The GAN-ST model is based on Deep Convolutional Generative Adversarial Network(s) (DCGAN) and Conditional Generative Adversarial Network(s) (CGAN) models, which consist of an enhanced generator. The study evaluates the accuracy of a CNN model on the MNIST and CIFAR 10 datasets using both original and synthetic data. The results revealed an impressive classifier accuracy on the MNIST dataset, achieving an accuracy of 99.38% on GAN-ST-generated synthetic training data, which is only 0.05% lower than the performance on original data-based training. The classifier performance on the CIFAR dataset is also remarkable, achieving an accuracy of 90.23%. The performance of CNN trained using GAN-ST-based synthetic data is notable, with the most considerable improvement of 0.66% and 7.06%, over a single GAN-based synthetic data training for the MNIST and CIFAR datasets, respectively. By training two GANs independently, the GAN-ST model covers different parts of the original data distribution, resulting in a more diverse and realistic training data set for the classifier. This diverse set of synthetic data, when used to train a CNN, shows better generalization to new data, leading to improved classification accuracy., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)