Global Shift Research Articles

SENTIMENT ANALYSIS OF ELECTRIC CAR PRODUCT TRENDS IN INDONESIA USING BM25 AND K-NEAREST NEIGHBOR

The global and Indonesian shift towards electric vehicles (EVs) is driven by efforts to reduce emissions and promote sustainable energy. Social media, especially Twitter, functions as an important measuring tool regarding public sentiment towards electric vehicles in Indonesia, so that it can influence policy making. This research uses the BM25 and K-Nearest Neighbor (KNN) methods to analyze sentiment, which aims to improve EV adoption strategies. Conducted in 2023, this research applies data mining, specifically Knowledge Discovery and Data Mining (KDD), analyzing primary and secondary data descriptively and quantitatively starting with data collection from Twitter, followed by data crawling and initial text processing. Next, labeling, term frequency (TF) and inverse document frequency (IDF) calculations were carried out using the BM25 and KNN methods, with an Evaluation and Validation Diagram that visualized the process. The findings show that negative sentiment dominates at 48% (4800 data), followed by 34% (3400 data) neutral sentiment and 18% (1800 data) positive sentiment. The balanced distribution of sentiment highlights the diverse perceptions of society. BM25 and KNN pre-processing methods effectively reduce overfitting and underfitting, especially in negative and neutral sentiments. Accuracy testing without BM25 resulted in 58.6% to 60.25%, while integrating BM25 with KNN increased accuracy by 12.5% to 71% to 72.75%. Understanding sentiment provides a basis for decision making and policy development, as well as providing insight into public perceptions of electric vehicles in Indonesia. Implications include leveraging positive sentiment for marketing, adjusting strategies, refining pricing, addressing infrastructure and reliability issues, and collaborating with governments to increase adoption of electric vehicles in society.

Diet affordability: a key dimension in the assessment of sustainable food systems and healthy diets.

A promulgated global shift toward a plant-based diet is largely in response to a perceived negative environmental impact of animal food production, but the nutritional adequacy and economic implications of plant-sourced sustainable healthy dietary patterns need to be considered. This paper reviews recent modeling studies using Linear Programming to determine the respective roles of animal- and plant-sourced foods in developing a least-cost diet in the United States and New Zealand. In both economies, least-cost diets were found to include animal-based foods, such as milk, eggs, fish, and seafood, to meet the energy and nutrient requirements of healthy adults at the lowest retail cost. To model a solely plant-based least-cost diet, the prevailing costs of all animal-sourced foods had to be increased by 1.1 to 11.5 times their original retail prices. This led to the inclusion of fortified plant-based foods, such as fortified soymilk, and a plant-based diet that was considerably (34-45%) more costly. The first-limiting essential nutrients were mostly the vitamins and minerals, with special focus on pantothenic acid, zinc, and vitamin B-12, when transitioning from an animal- and plant-containing least-cost diet to a plant-only based least-cost diet. Modeled least-cost diets based on contemporary food costs include animal-sourced foods, at least for developed high-income US and NZ food economies, and potentially for developing low- and middle-income countries, such as Indonesia. Modeling of least-cost diets that consist exclusively of plant-based foods is feasible, but at a higher daily diet cost, and these diets are often close to limiting for several key nutrients. Diet affordability, as a key dimension of sustainable healthy diets, and the respective economic roles of animal- and plant-sourced foods need to be considered.

Advanced Nanostructured Textile Catalysts for Enhanced Hydrogen Production in PEM Water Electrolysis: An Overview and Recent Developments

As the global focus shifts towards a zero-emission society, hydrogen has emerged as a critical element in various industries, particularly in green hydrogen production. A promising method for this is Polymer Electrolyte Membrane Water Electrolysis (PEMWE), which uses pure water and electricity to produce high-purity hydrogen. However, the efficiency of PEMWE is highly dependent on the effectiveness of its catalysts, particularly in the context of the catalyst-coated membranes (CCMs) employed in these systems. Conventional preparation of these CCMs involves multiple steps, including synthesis and application of a catalyst ink, which often leads to catalyst agglomeration and requires high Ir (Iridium) loadings to maintain uniformity and performance.In our latest study, we have developed a novel approach using ultralight conductive IrO2 nanostructured textiles (NST) as a catalyst layer for PEMWE. This innovative method successfully circumvents the issue of electrically isolated inactive catalysts, a common problem with lower Ir amounts in traditional catalyst layers. By employing a process of sputtering IrO2 onto water-soluble polymer nanofibers, we have achieved facile CCM preparation and demonstrated unprecedented long-term hydrogen evolution with ultra-low Ir mass loadings at high rates. Our study revealed that the high performance of these CCMs is derived from their low resistivity and unique porous three-dimensional structure.The preparation of NST involves dissolving polyvinylpyrrolidone (PVP) in methanol, followed by electrospinning this solution onto a metal-foil collector. The resulting PVP nanofibers then undergo a sputtering process to deposit IrO2, forming the nanostructured textiles. This method eliminates the need for wet chemical routes and labor-intensive processes typically associated with conventional catalyst layer preparations, thus offering a more environmentally friendly and scalable alternative.Our performance evaluations of these NST CCMs, with varying Ir mass loadings, have shown significant advancements. The operational cell voltages of CCMs containing as little as 0.05 mg-Ir cm−2 were suppressed across all investigated current densities compared to conventional CCMs. Notably, operational voltages remained below 2 V even at the highest current density of 7 A cm−2. This level of performance is unprecedented for CCMs with such low catalyst amounts. Additionally, the long-term stability of these CCMs was remarkable, with operational times exceeding 1500 hours without significant increases in voltage, showcasing their potential for practical applications.An essential aspect of our study was the analysis of the electrical properties and the surface structure of the IrO2 NSTs. We observed that the electrical conductivity of these textiles was significantly higher than that of conventional catalyst layers. This high conductivity, coupled with the unique interconnected structure of the textiles, ensures efficient electrical contact between nano catalysts and the current collector, thus avoiding the formation of isolated catalysts. Our analyses revealed that the IrO2 NSTs have unique surface terminations and a high number of undercoordinated surface Ir atoms, contributing to their high intrinsic catalytic activity.Further insights were gained through operando X-ray absorption spectroscopy (XAS) measurements, which showed that the IrO2-nanostructured textiles possess a large number of D-band holes and are intrinsically highly active. This finding is crucial as it links the unique chemical state of the textiles to their high activity in oxygen evolution reactions (OER), a key process in PEMWE.Our recent developments in nanostructured textile catalysts for PEMWE mark a significant leap in hydrogen production technology. By demonstrating high-rate hydrogen production at low operational voltages and with significantly lower Ir mass loadings compared to conventional CCMs, we have addressed major challenges in the field. These advancements not only enhance the efficiency and sustainability of hydrogen production but also open avenues for applying this technology to other electrochemical conversion cells, paving the way for broader applications and further research. In this talk, we discuss the latest activity on NST, and highlight the challenges and opportunities for hydrogen production.

(Invited) A Polaron Paradigm for Perovskite Nanocrystal Emitting States

Perovskite NCs such as CsPbBr3 have numerous uses. Most involve exploiting their light emission and are motivated by their defect tolerance and large, as-made emission quantum yields. Absent, though, is a fundamental understanding of perovskite NC emitting states, central to these applications. Of particular note are observations of near-universal, size-, temperature-, and composition-dependent absorption/emission Stokes shifts where observed energy differences are between absorbing and emitting states.Very little is known about the origin of these shifts. Moreover, little is known about the exact identity of the emitting state. This is to be contrasted to more conventional NCs such as CdSe where band edge exciton fine structure quantitatively accounts for both global and resonant Stokes shifts, with emission emerging from a dark exciton. Although similar perovskite NC fine structure might account for their shifts, both theory and experiment predict bright/dark fine structure splittings easily an order of magnitude too small to account for experiment.We now propose that perovskite NC emitting states are polarons, which result from the lattice accommodation of photogenerated charges. Polaron binding energies and lifetimes are, in turn, suggested to be the origin of observed size-, temperature-, and composition-dependent absorption/emission Stokes shifts and excited state lifetimes. This represents a significant departure from more conventional descriptions of NC band edge states, which exclusively involve exciton fine structure and dark exciton emitting states.

The cage-free egg sector: perspectives of Indian poultry producers.

India is ranked as the 2nd largest egg producer in the world. Despite the prevalence of backyard poultry (free range), a majority of the commercial egg-laying hens in the country are still housed in battery cages. There is a global shift toward cage-free eggs, due to regulations and increased demand from conscious consumers and food corporations. However, there are very few commercial cage-free facilities in India to meet this demand. The aim of this study was to undertake a needs-assessment survey of Indian egg producers on cage-free production, and understand what support is needed to build the capacities of the cage-free egg production sector to develop it into a viable and sustainable alternative to battery cage eggs. The results showed that nearly all producers agreed on the need for additional support in shifting to, and operating in, the cage-free sector. This included support in the form of financial assistance, technical training, and promotion of the cage-free sector. The results of this study highlight the pressing need for government and private support, in the absence of which cage-free producers are compelled to compete with battery cage poultry producers on prices, which will result in increased losses and failure of the sector, since they have not yet achieved economies of scale.

Energy Management System for an Industrial Microgrid Using Optimization Algorithms-Based Reinforcement Learning Technique

The climate crisis necessitates a global shift to achieve a secure, sustainable, and affordable energy system toward a green energy transition reaching climate neutrality by 2050. Because of this, renewable energy sources have come to the forefront, and the research interest in microgrids that rely on distributed generation and storage systems has exploded. Furthermore, many new markets for energy trading, ancillary services, and frequency reserve markets have provided attractive investment opportunities in exchange for balancing the supply and demand of electricity. Artificial intelligence can be utilized to locally optimize energy consumption, trade energy with the main grid, and participate in these markets. Reinforcement learning (RL) is one of the most promising approaches to achieve this goal because it enables an agent to learn optimal behavior in a microgrid by executing specific actions that maximize the long-term reward signal/function. The study focuses on testing two optimization algorithms: logic-based optimization and reinforcement learning. This paper builds on the existing research framework by combining PPO with machine learning-based load forecasting to produce an optimal solution for an industrial microgrid in Norway under different pricing schemes, including day-ahead pricing and peak pricing. It addresses the peak shaving and price arbitrage challenges by taking the historical data into the algorithm and making the decisions according to the energy consumption pattern, battery characteristics, PV production, and energy price. The RL-based approach is implemented in Python based on real data from the site and in combination with MATLAB-Simulink to validate its results. The application of the RL algorithm achieved an average monthly cost saving of 20% compared with logic-based optimization. These findings contribute to digitalization and decarbonization of energy technology, and support the fundamental goals and policies of the European Green Deal.

Advancing Sustainable Transportation Education: A Comprehensive Analysis of Electric Vehicle Prototype Design and Fabrication

The global shift towards electric vehicles (EVs) has necessitated a paradigm shift in engineering education, emphasizing hands-on experiences and innovative learning approaches. This review article presents a comprehensive analysis of the design and fabrication process of an educational EV prototype, highlighting its significance in preparing future engineers for the rapidly evolving EV industry. The article delves into the historical development and recent trends in EVs, providing context for the growing importance of practical skills in this field. A detailed examination of the key components and systems in modern EVs, such as battery packs, electric motors, transmission systems, and chassis design, lays the foundation for understanding the complexities involved in EV prototype development. The methodology section explores the research approach, conceptual design, simulations, material selection, and construction techniques employed in the creation of an educational EV prototype. The evaluation and testing phase assesses the prototype’s performance, safety, and reliability, offering valuable insights into the lessons learned and areas for improvement. The impact of such projects on engineering education is discussed, emphasizing the importance of hands-on learning experiences and interdisciplinary collaboration in preparing students for future careers in the EV industry. The article concludes by addressing common challenges faced during EV prototype projects and providing recommendations for future educational initiatives in this field.

Effects of Whole-Body Vibration Training on Improving Physical Function, Cognitive Function, and Sleep Quality for Older People with Dynapenia in Long-Term Care Institutions: A Randomized Controlled Study

As the global demographic shifts toward an aging population, aging-related problems, particularly in older individuals with dynapenia, are increasingly gaining attention. However, interventional studies focusing on physical and cognitive function and sleep quality in such individuals are limited, indicating a need for further exploration. The present study investigated the effects of whole-body vibration (WBV) training on physical and cognitive function and sleep quality in older people with dynapenia residing in long-term care institutions. This study was a randomized controlled trial. The experimental group underwent WBV training three times a week for 3 months, whereas the control group continued with their regular daily care routine. Statistical analyses were performed using the Traditional Chinese version of SAS Statistics version 9.4. Paired t tests, a one-way analysis of variance, independent t tests, and generalized estimating equation analysis were performed. The results revealed that compared with the control group, the experimental group experienced significant improvements in grip strength, instrumental activities of daily living, cognitive function, and sleep quality in terms of latency and duration. These findings suggest that 3 months of WBV training can effectively enhance physical and cognitive function and sleep quality in older people with dynapenia residing in long-term care institutions.

Photovoltaics Energy Potential in the Largest Greek Cities: Atmospheric and Urban Fabric Effects, Climatic Trends Influences and Socio-Economic Benefits

This comprehensive study explores the influence of aerosols and clouds on solar radiation in the urban environments of nine of Greece’s largest cities over the decade from 2014 to 2023. Utilizing a combination of Earth Observation data, radiative transfer models, and geographic information systems, the research undertook digital surface modeling and photovoltaic simulations. The study meticulously calculated the optimal rooftop areas for photovoltaic installation in these cities, contributing significantly to their energy adequacy and achieving a balance between daily electricity production and demand. Moreover, the research provides an in-depth analysis of energy and economic losses, while also highlighting the environmental benefits. These include a reduction in pollutant emissions and a decrease in the carbon footprint, aligning with the global shift towards local energy security and the transformation of urban areas into green, smart cities. The innovative methodology of this study, which leverages open access data, sets a strong foundation for future research in this field. It opens up possibilities for similar studies and has the potential to contribute to the creation of an updated, comprehensive solar potential map for continental Greece. This could be instrumental in climate change mitigation and adaptation strategies, thereby promoting sustainable urban development and environmental preservation.

Investigating and predicting the role of photovoltaic, wind, and hydrogen energies in sustainable global energy evolution

The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil fuels. This review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar, wind, and hydrogen. This transition economically challenges traditional energy sectors while fostering new industries, promoting job growth, and sustainable economic development. The transition to renewable energy demands social equity, ensuring universal access to affordable energy, and considering community impact. The environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological footprint. This study highlights the rapid growth of the global wind power market, which is projected to increase from $112.23 billion in 2022 to $278.43 billion by 2030, with a compound annual growth rate of 13.67%. In addition, the demand for hydrogen is expected to increase, significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero emissions. By 2028, renewables are predicted to account for 42% of global electricity generation, with significant contributions from wind and solar photovoltaic (PV) technology, particularly in China, the European Union, the United States, and India. These developments signify a global commitment to diversifying energy sources, reducing emissions, and moving toward cleaner and more sustainable energy solutions. This review offers stakeholders the insights required to smoothly transition to sustainable energy, setting the stage for a resilient future.

Optimizing EV charging stations: a simulation-based approach to performance and grid integration

This study addresses the optimization of electric vehicle (EV) charging stations, focusing on enhancing performance and grid integration through a comprehensive simulation approach. By employing advanced simulation tools in Simulink® and MATLAB®, alongside electrical installation planning with SIMARIS®, we meticulously analyze the charging process, infrastructure requirements, and their implications on the power grid. Our results demonstrate significant improvements in charging station efficiency and reliability, highlighting the effectiveness of our proposed control strategies and harmonic mitigation techniques. Notably, the integration of renewable energy sources emerges as a pivotal factor in reducing operational costs and carbon emissions, furthering the sustainability of EV charging solutions. The research delineates the environmental benefits, emphasizing the reduction of greenhouse gas emissions and enhancement of urban air quality, pivotal in the global shift towards cleaner transportation modes. This work contributes valuable insights into the design and grid integration of EV charging stations, offering a scalable model for future infrastructure development. It serves as a critical resource for engineers, policymakers, and stakeholders in the realm of electric mobility, advocating for a strategic transition to EVs supported by robust and efficient charging infrastructure.

AI-assisted Optimal Energy Conversion for Cost-Effective and Sustainable Power Production from Biomass-Fueled SOFC Equipped with Hydrogen Production/Injection

This study introduces a novel energy conversion and management framework to reduce carbon emissions in the energy sector and expedite the global shift towards sustainable practices. The system is driven by biomass-based solid oxide fuel cells for efficient power generation. Central to this approach lies the integration of additional hydrogen injection provided by a thermally-driven vanadium chloride cycle, aiming to enhance the quality of the syngas entering the fuel cells. The system is also combined with a super-critical CO2 cycle that generates power by passively enhancing performance through flue gas condensation. The proposed model's feasibility is evaluated in depth, techno-economically, considering thermodynamics and specific cost theories. As part of artificial intelligence, a neural network model is coupled with the genetic algorithm to determine the best operating status while minimizing computation time. According to the results, the suggested new integration results in higher efficiency and lower cost than a similar system without hydrogen injection. The results further show that the triple-objective optimization achieves output power, second-law efficiency, and overall system cost of 3425kW, 48.5%, and 2.3M$/year, respectively. Eventually, the gasifier is the main contributor to the highest level of exergy destruction, and fuel utilization and current density are the most important parameters in modeling.

Appropriate analysis on properties of various compositions on fluids with and without additives for liquid insulation in power system transformer applications

Transformer is a well-known power system apparatus utilized in conjunction with solid insulations such as paper and press board, as well as liquid insulations like mineral oil, a petroleum-based fluid. Despite the notable drawbacks associated with mineral oil, such as limited resources for future generations and its non-eco-friendly nature, its usage remains ubiquitous. There is a growing imperative to explore alternative fluids that surpass mineral oil in terms of environmental impact and performance. Amidst the global shift towards green energy, this study focuses on vegetable seed oils such as corn oil, soybean oil, mustard oil, and rice bran oil as potential substitutes. The research evaluates these oils based on key transformer properties including breakdown voltage, water content, interfacial tension, viscosity, acidity, flash point, and fire point. Interestingly, rice bran oil and soybean oil exhibit promising characteristics that suggest they could effectively replace petroleum-based fluids in transformers. Furthermore, the study extends to blending mineral oil with vegetable seed oils in various compositions, incorporating natural and synthetic antioxidant additives ranging from 0 to 1%. Comparative analyses between samples with and without additives reveal that the inclusion of 1% propyl gallate yields outstanding performance improvements. For instance, a blend comprising 25 ml of mineral oil and 25 ml of soybean oil, supplemented with 1% propyl gallate, demonstrates 90% higher effectiveness compared to other blends and additives tested. Moreover, the research employs statistical regression analysis to establish relationships between different parameter variables, providing deeper insights into the performance and compatibility of these blended oils in transformer applications. This comprehensive investigation underscores the potential of vegetable seed oils as viable alternatives to mineral oil, contributing to the advancement of eco-friendly solutions in power systems.

Economic growth in OPEC nations: The role of renewable energy consumption, CO2 emissions, and foreign direct investment

Background: The nations that make up OPEC (the Organization of the Petroleum Exporting Countries) have traditionally depended on gas and oil export earnings. However, there is a significant global shift towards renewable energy in an effort to reduce the impact of climate change. This research aims to analyze the effect of Renewable Energy Consumption, CO2 Emissions, and Foreign Direct Investment (FDI) on the Economic Growth in OPEC Nations partially and simultaneously. Methods: In this research, panel data regression analysis techniques are combined with quantitative research approaches. Secondary data from the World Development Indicators (WDI) for the years 2001–2020 were used in this research. Finding: This research showed that the Renewable Energy Consumption and CO2 Emissions variables do not affect economic growth in OPEC countries. Meanwhile, the foreign direct investment variable has a positive and significant effect on economic growth in OPEC countries. Conclusion: OPEC countries need to diversify their economies and reduce their dependence on oil as there is a global shift towards cleaner energy. Novelty/Originality of this article: This study analyzes the impact of Renewable Energy Consumption, CO2 Emissions, and Foreign Direct Investment on Economic Growth in OPEC countries using panel data regression analysis. The study's findings show that only Foreign Direct Investment positively and significantly impacts economic growth.

Sustainable innovation: Economic valuation of wood waste for sustainable development at PT Wapoga Mutiara Industries

Background: This study describes the economic valuation of wood waste at PT Wapoga Mutiara Industries using the Market Price Approach to calculate the Total Economic Value (TEV) derived from utilising production waste. This research uses qualitative methods to explore how processed wood waste contributes economically to the company and the local community. Wood waste in industrial processes is often an underutilised asset. However, at PT Wapoga Mutiara Industries, innovative practices have turned this by-product into a significant economic opportunity. Method: This research investigated the direct use value of wood waste - mainly wood chips and sawdust - converted into local charcoal products, a resource increasingly recognized for its environmental and economic benefits. The research assessed the monthly economic impact of these waste products, measuring their market value to quantify the total benefits accruing to the local economy. Findings: The findings from this study are considerable, showing that wood chips alone contribute IDR 42,300,000 to the economy each month. Sawdust was processed in the same way, adding IDR 72,860,000 per month. Combined, these waste materials contribute a total direct use value of IDR 166,160,000 per month to the local economy, which on average provides a potential income of IDR 1,350,700 per person per month, suggesting there is significant economic potential from sustainable wood waste management practices. Conclusion: In addition, the study provides insight into the broader implications of such valuation practices, demonstrating that with the right innovations, what is often considered industrial waste can be re-evaluated as a viable economic resource. This aligns with the global shift towards more sustainable industrial processes, where waste minimisation and reuse contribute to environmental sustainability, economic resilience, and community well-being. Novelty/Originality of this study: This study presents a comprehensive analysis of the economic valuation of wood waste in the processing industry, demonstrating the significant potential of innovative waste management practices. This research opens up new perspectives on how industrial 'waste' can be transformed into valuable economic resources, supporting environmental sustainability and the well-being of local communities.

The impact of energy (Electricity) losses on load capacity factor: A dynamic ARDL-based evidence from Pakistan

The energy-environment interplay has raised significant concerns among policymakers and experts, with the global shift towards renewable energy being hailed as a key solution to reduce pollution emissions. However, in addition to energy production, the efficient transmission and distribution of electricity is also important which also poses considerable challenges to environmental sustainability. This study aims to investigate the effect of electricity losses on environmental sustainability measured by load capacity factor (LCF). This study uses the DARDL (DARDL) method and Kernel-based Regularized Least Squares (KRLS) to analyze the influence of electricity losses, foreign direct investment (FDI), economic growth, and industrial output on LCF in Pakistan from 1981 to 2022. The electricity losses significantly undermine environmental sustainability by reducing LCF. However, FDI positively influences LCF, but economic growth and industrial output exert a detrimental effect. Additionally, the study observes that both positive and negative counterfactual 10 % shocks in electricity losses result in negative and positive impacts on LCF. Whereas, 10 % positive counterfactual shocks in FDI positively affect LCF. KRLS analysis confirms the robustness of the DARDL estimates. The study underscores that efficient energy transmission and distribution is pivotal in safeguarding environmental sustainability.

Impact of the Built Environment on Ageing in Place: A Systematic Overview of Reviews

Background: As the global demographic shifts towards an ageing population, the significance of the built environment in facilitating ageing in place gains prominence. This study addresses the critical question of how a built environment can support older adults’ independence and enhance their quality of life. Method: Utilising a systematic review of review papers, this research scrutinises existing literature to uncover the influence of urban planning, physical accessibility, and residential design on the older people’s physical and mental well-being. More specially, the study methodically examines existing review articles that span various aspects of the built environment related to ageing in place. Results: The analysis reveals that specific elements of the built environment, notably rational urban planning and accessible urban spaces, as well as adaptable housing designs, significantly impact ageing individuals’ health, social engagement, and overall satisfaction with life. It also identifies contradictions in the effects of environmental features on cognitive health and well-being, underscoring areas that warrant further exploration. Conclusions: The study concludes that thoughtful urban and housing designs are pivotal in creating age-friendly environments that support ageing in place. It emphasises the need for future research and policy development aimed at enhancing the living conditions of older adults within their communities.

Prevalence and factors associated with depression among the elderly in rural areas of central India: a mixed method study

Background: The global demographic shift towards an aging population has raised concerns about the mental health of the elderly, particularly in rural areas. This study sought to tackle this issue by quantitatively evaluating the prevalence of geriatric depression in rural areas of central India and qualitatively investigating the factors that contribute to late-life depression. Methods: This mixed-method study conducted in the rural areas of central India aimed to assess the prevalence of depression among the elderly and explore gender-specific factors contributing to late-life depression. Results: Quantitative data were collected from 308 elderly individuals aged 60 years and above, revealing a high prevalence of depressive symptoms (75.6%). Factors significantly associated with depression included female gender, age over 70 years, lower educational attainment, financial dependency, and comorbidities. Qualitative analysis through focus group discussions highlighted gender-specific perceptions of depression risk factors, emphasizing the need for tailored interventions. Conclusions: The findings underscore the urgent need for targeted mental health interventions addressing socio-economic disparities and gender-specific challenges in rural elderly populations. A nuanced, gender-sensitive approach is crucial for promoting well-being and reducing the burden of depression among the elderly in rural central India.

Temperature Behavior in Headlights: A Comparative Analysis between Battery Electric Vehicles and Internal Combustion Engine Vehicles

In the context of a global shift towards renewable energies and climate change mitigation, the market for electric vehicles has experienced a remarkable upswing, with battery electric vehicles (BEVs) leading this transformative wave. The appeal of BEVs lies in their ability to significantly curtail CO2 emissions by supplanting the traditional internal combustion engine (ICE) with an electric motor. This pivotal change in vehicular technology extends its influence to various subsystems, including automotive lighting. Headlights are particularly sensitive to the thermal environment they operate in, which can profoundly affect their functionality and durability. The removal of an ICE in BEVs typically results in a reduction in heat exposure to headlight components, prompting a potential reevaluation of their design. This article presents a comprehensive analysis of temperature distributions within headlight units, comparing BEVs and ICE vehicles. The study encompasses a robust dataset of nearly 30,000 vehicles from around the globe, taking into account the impact of ambient temperature on headlight operation. The investigation delineates the distinct thermal behaviors of the two vehicle categories and offers strategic recommendations for conceptual modifications of headlights in BEVs. These adjustments are aimed at enhancing headlight efficacy, prolonging lifespan, and furthering the sustainability objectives of electric mobility.

Safe Transition from Open to Total Minimally Invasive Esophagectomy for Cancer Utilizing Process Management Methodology.

Background: The global shift from open esophagectomy (OE) to minimally invasive esophagectomy (MIE) for treating esophageal cancer is well-established. Recent data indicate that transitioning from hybrid minimally invasive esophagectomy (hMIE) to total minimally invasive esophagectomy (tMIE) can be challenging due to concerns about higher leakage rates and lower lymph node counts, especially at the beginning of the learning curve. This study aimed to demonstrate that a safe transition from OE to tMIE for cancer is possible using process management methodology. Methods: A step-change approach was adopted in process management planning, with hMIE serving as an intermediate step between OE and tMIE. This single-center, case-control study included 150 patients who underwent the Ivor Lewis procedure with curative intent for esophageal cancer. Among these patients, 50 underwent OE, 50 hMIE (laparoscopic procedure followed by conventional right thoracotomy), and 50 tMIE (laparoscopic and thoracoscopic approach). A preceptored training scheme was implemented during execution, and treatment results were monitored and controlled to ensure a safe transition. Results: During the transition, the tMIE group was not worse than the hMIE and OE groups regarding operation duration (p = 0.135), overall postoperative complications (p = 0.020), anastomotic leakage rates (p = 0.773), 30-day mortality (p = 1.0), and oncological outcomes (based on R status (p = 0.628) and 2-year survival (p = 0.967)). Additionally, the tMIE group showed superior results in terms of major postoperative pulmonary complications (p = 0.004) and ICU stay duration (p < 0.001). Conclusions: Utilizing managerial methodology and practice in surgery, as a bridge between interdisciplinary and transdisciplinary approaches, demonstrated that transitioning from OE to tMIE, with hMIE as an intermediate step, is safe and feasible without compromising outcomes.