Pandemic A H1N1 (2009) Preparedness Efforts, Compliance, Ethical Considerations: A Retrospective Study on Hijli Rural Hospital (RH)

• Used Indian national Pandemic Preparedness Plan (2009) as plan under consideration• Conducted an informal interview with the Hijli Rural Hospital staff• Utilized the theory of social justice• Identified strengths and omissions in the• Identified strengths and omissions in the pandemic preparation of RH• Identified ethical issues ensuing from the omissions• Recommendations with national and global significance</p

Association between unclean cooking fuel use and hearing problems among adults aged ≥65 years, a cross-sectional study

Background and Aims: Literature suggests that outdoor air pollutant exposure is associated with hearing problems, but examination of this link has not extended to any potential association between hearing ability and the use of unclean cooking fuels. The current paper investigates whether such a link exists, utilizing a large sample of older adults from low- and middle-income countries (LMICs) where such fuels are commonly used.Methods: Data from the Study on global AGEing and adult health (SAGE) were analyzed. This is a nationally representative and cross-sectional data set collected for the World Health Organization for residents of South Africa, China, Ghana, India, Mexico, and Russia. A range of “unclean” cooking fuels were assessed, namely agriculture or crop, animal dung, coal or charcoal, Kerosene or paraffin, shrubs or grass, and wood. Hearing problems referred to the interviewer-rated presence of this condition. Statistical analysis was done using multivariable logistic regression.Results: The present work analyzed data from 14,585 individuals aged ≥ 65 years [mean (SD) age 72.6 (11.5) years; 55.0% females]. In the overall sample and in the final adjusted model, unclean cooking fuel use was associated with a significantly increased risk of hearing problems (OR = 1.68 (95% CI = 1.22–2.30). This association was significant for females (OR = 2.36; 95% CI = 1.53–3.63) but not for males (OR = 1.20; 95% CI = 0.79–1.81).Conclusion: Unclean cooking fuel use is associated with an increased risk of hearing problems among adult residents of LMICs over 65 years of age, particularly among females. Findings from this study support the development of Sustainable Development Goal 7 (United Nations), which advocates for fairer and more sustainable access to modern energy, as well as a means to prevent avoidable hearing problems.</p

Enhancing Malware Detection Through Machine Learning Using XAI with SHAP Framework

Malware represents a significant cyber threat that can potentially disrupt any activities within an organization. There is a need to devise effective proactive methods for malware detection, thereby minimizing the associated risks. However, this task is challenging due to the ever-growing volume of malware data and the continuously evolving techniques employed by malicious actors. In this context, machine learning models offer a promising approach to identify key malware features and facilitate accurate detection. Machine learning has proven to be effective in detecting malware and has recently gained widespread attention from both the academic and research sectors. Despite their effectiveness, current research on machine learning (ML) models for malware detection often lacks necessary explanations for the selection of key features. This opacity of ML models can complicate the understanding of the outputs, errors, and decision-making processes. To address this challenge, this research uses Explainable AI (XAI), particularly the SHAP framework, to enhance transparency and interpretability. By providing extensive insights into how each feature contributes to the model’s conclusions, the approach further improves the model’s accountability. An experiment was conducted to demonstrate the applicability of the proposed method, beginning with the training of the chosen machine learning models, including Random Forest, Adaboost, Support Vector Machine and Artificial Neural Network, for detecting malware, and concluding with the explanation of the decision-making process using XAI techniques. The results showed high accuracy in malware detection, along with comprehensive explanations of the feature contributions, which justifies the outputs produced by the models.</p

Exercise training and inflammatory adipokines in patients with type 2 diabetes: a systematic review, meta-analysis, and meta-regression

Background: Improvements in adipocytes levels can reduce the risk of diabetes and cardiovascular disease, indicating adipocytes to be a hopeful remedial target in type 2 diabetes mellitus (T2DM) and other related diseases. However, there is no consensus on the role of various exercise training on adipokines in T2DM and the results are contradictory. Therefore, this systematic review, meta-analysis, and meta-regression investigated the effects of different types of exercise training on some inflammatory adipokines concentrations in T2DM.Methods: A systematic search was conducted in PubMed/MEDLINE, Web of Science, Embase, Google Scholar, and Cochrane up to September 2024. Studies investigating the effects of exercise training on Resistin, apelin, visfatin, and vaspin were included. Meta-analysis was performed using a random-effect model (DerSimonian-Laird method) to calculate weighted means differences with 95% confidence intervals (CIs). The Cochrane Collaboration's tool was also used to asses risk of bias of studies.Results: Analysis of 36 studies (50 intervention arms, n = 1811) demonstrated that exercise training significantly decreased resistin (mean difference [MD]: −1.02 ng/ml, 95% CI −1.48 to −0.57, p Conclusions: Overall, aerobic and combined training decreased inflammatory adipokines with a positive supplementary effect for patient with T2DM.Registration: PROSPERO registration no. CRD42024617538.</p

Pronouns, Pin Badges and Pride: LGBTQ+ Student Experiences of Inclusion and Belonging in a UK University

This article provides findings from a small-scale project undertaken to understand the student experience of the lesbian, gay, bisexual, transgender, and queer plus (LGBTQ+) student community in a large post-92 university in England. Focus groups were conducted with students that explored areas of student life, including support, the campus environment, and belonging. A social constructivist theoretical perspective underpins the article. Students develop common knowledge via social processes that are powerfully influenced by cultural factors that are constantly in a state of flux. The article also rejects essentialist delineations of LGBTQ+ gender and sexuality and subscribes instead to a Butlerian framework of identity where behaviours associated with gender and sexuality are instruments of regulatory regimes. Even within a university culture that is inclusive and welcoming, opportunities were not always provided for LGBTQ+ students to speak about their personal lives and identities authentically, and university classrooms did not always feel like safe places for students. Whilst staff were generally helpful and supportive to their LGBTQ+ students, many lacked the knowledge and skills to confidently meet the needs of these students, particularly those identifying as trans and non-binary. The recommendations include calls for universities to commit to high-quality mandatory training for staff so that trans and non-binary students in particular are supported by staff appropriately equipped to support their needs.</p

Insect trafficking: a green criminological perspective

In May of 2025, four men were sentenced in a Kenyan court for the attempted smuggling of ants. This case underscores a largely overlooked dimension of global wildlife crime: the trafficking of insects. This article aims to discuss the nature of insect trafficking in legal, criminological, and conservation discourses and to argue for its inclusion in broader debates within environmental justice discourse. Exploring legal and policy dimensions of wildlife trafficking through a green criminological lens, this paper underscores the anthropocentric bias in wildlife protection, which marginalises non-charismatic species despite their ecological importance. It concludes that a shift toward ecological and species justice is necessary, advocating for more inclusive legal definitions, improved enforcement mechanisms, and interdisciplinary research. Recognising insects as victims of environmental harm is essential for developing holistic responses to wildlife crime and advancing the goals of green criminology.</p

Political “color” and the impact of climate risks on output growth: evidence from a panel of US states

In this paper, we show that the effect of climate risks on economic growth in a panel of 48 contiguous states of the US is contingent on the party affiliation of the local politicians, as captured by a Democratic-Republican Index (DRI). Specifically, our results, based on a regime-dependent local projections model, indicate that extreme weather-related shocks tend to negatively impact output growth more severely, especially in the medium- to long-run, in the Republican-leaning states with low-DRI values compared to those characterized by high-DRIs over the annual period 1967 - 2023. In addition, when we incorporate the information on states that have undertaken explicit targets for reduction of greenhouse gas emissions, following the Climate Change Action Plan implemented in 1993, we find that the significant long-horizon negative effect continues to hold only for the states with low-DRIs, i.e., those that are Republicans-oriented.</p

Structural empowerment and speaking up among overseas trained nurses in the United Kingdom, National Health Service

Structural empowerment within workplaces plays a crucial role in enabling the overseas trained nurses' confidence to speak up against unsafe practice and be affected by adverse workplace culture. In this study levels of structural empowerment were explored utilizing the Condition for Work Effectiveness Questionnaire 2 and hypothetical vignettes to understand speaking-up practices among Overseas trained nurses.Moderate levels of structural empowerment were perceived in the domains of access to opportunity (M = 4.05; SD = 0.09) and access to information (M = 3.52; SD = 0.77). Lower levels were perceived in the domains of access to resources (M = 3.04, SD = 0.88) and access to support (M = 3.49; SD = 0.91). The majority (95.8 %) reported high levels of willingness to speak-up. Access to opportunity and information positively influenced speaking up.Nurses perceive that opportunities to gain new skills and knowledge and information about the values and goals of the organization can empower them to speak up. These areas should be developed in NHS, messages reinforced, and initiatives taken to build confidence around patient safety practices. Their perceived inadequate access to support, through feedback and guidance from co-workers and inadequate access to resources, indicates a need to optimize strategies to address these areas to maintain and enhance patient safety culture.</p

The role of sense of place in maintaining resilience in social-ecological systems: a case study of the sacred groves in the Western Ghats, India

The exclusion of people from conservation decision-making poses a significant challenge, affecting the effectiveness and efficiency of conservation actions. However, understanding the intricate social-ecological relationship between people and places necessitates a paradigm shift to address conservation challenges through a stewardship-focused resilience approach. Focusing on social-ecological systems (SES) such as the devrahati (sacred groves, SG) in the northern Western Ghats, India, this study explores the local community's sense of place (SoP), shaped by their lived experiences, emotions, and perceptions, as a crucial link between social and ecological aspects that foster resilience of these systems.Place-based concepts like place meanings, place attachments, and place attitudes were investigated using a qualitative approach combining semi-structured interviews and participatory observations. Data was collected from the local community members to gain insights into their knowledge, practices, and beliefs related to the devrahati. Thematic analysis was conducted to identify recurring patterns and themes that illustrate what shapes the SGs.The devrahatis are a complex sacred space deeply intertwined with the community’s history, spirituality, and identity. They have multifaceted meanings that seep deep into spiritual, ecological, and cultural aspects; however, changing relationships impact the frequency and nature of people-place interactions with the space. The shift from working-spiritual landscapes to primarily spiritual landscapes, along with generational and gender disconnects with the place, and weak governance, is leading to the erosion of knowledge and the weakening of ritual practices. This research provides valuable empirical evidence for using SoP to build stewardship-focused resilience in the devrahati.While the research establishes the deep-rooted significance of SoP in the people-place relationship, it also offers a useful tool, the linked SES-SoP framework (framework), for identifying and understanding opportunities to cultivate knowledge sharing, which can encourage social learning, fostering a sense of ownership, enhancing collective efficacy and empowering local actors to develop a shared understanding and vision for a resilient future. The framework's six enablers (understanding social-ecological diversity, connectivity, participation and partnership, governance, funding/ resources, and learning and evaluation) facilitate identifying the challenges and assist in making coherent decision-making for resilient SES.</p

Multi-stage deep learning for intrusion detection in Industrial Internet of Things

The Industrial Internet of Things (IIoT) facilitates enhanced automation, predictive maintenance, real-time monitoring, and data analytics across various sectors, including manufacturing, energy, transportation, agriculture, and supply chain management, thereby improving productivity, efficiency, and operational safety. However, as IIoT networks continue to expand, it is imperative to secure them against increasingly sophisticated cyber threats. Deep Learning (DL) techniques have been extensively utilized for intrusion detection within IIoT systems. Nevertheless, addressing the class imbalance problem remains a significant challenge. The underrepresentation of certain attack types in training data frequently results in the development of DL models that struggle to accurately detect these categories of malicious activities. This limitation represents considerable risks to the security of IIoT networks, as undetected attacks and false alarms may lead to severe operational disruptions. In this paper, we propose a multi-stage deep learning (MSDL) method specifically designed to enhance intrusion detection within IIoT networks by addressing the class imbalance issue. We assessed the effectiveness of our approach utilizing two highly imbalanced datasets: X-IIoTID and WUSTL-IIoT. Our experimental findings indicate that the proposed MSDL method surpasses the baseline DL models as well as state-of-the-art oversampling and undersampling techniques. Specifically, the MSDL method exhibits significant improvements in recognizing minority-class attacks that are frequently misclassified. Consequently, the implementation of the MSDL for intrusion detection is anticipated to strengthen the overall security and resilience of IIoT systems, providing stronger protection against a diverse array of cyber threats in industrial applications.</p