Sharada Kunwor, Sami Lama, Surya Raj Niraula
et al.
Introduction: Resilience enables older adults to cope with and adapt to challenges, promoting stability or positive personal growth. In old age, vulnerabilities such as multi morbidity, bereavement, social isolation, and financial constraints elevate mental health risks, including depression and anxiety. Higher trait resilience strongly correlates with improved mental well-being in this population. This study was to assessed resilience and mental well-being among older adults.
Methods: A community-based descriptive cross-sectional study was conducted in Dharan Sub-Metropolitan city. Five wards were randomly selected from twenty. A simple random sampling method was used to choose respondents, with informed consent obtained prior to interviews. Data were collected using a structured questionnaire and analyzed with the Statistical Package for Social Sciences version 11.5. Descriptive and inferential statistics were used.
Result: A total of 166 elderly participants were included in the study, of whom 71 (42.77%) were male and 95 (57.23%) were female. The median resilience score was 69.50 (IQR: 59.25–74.00; 95% CI: 67.70–71.30), and the median mental well-being score was 55.00 (IQR: 52.00–58.00; 95% CI: 54.27–55.73).
Conclusion: The resilience of the elderly participants was moderate to high, and their mental well-being was generally satisfactory.
Under the low carbon goal, recycling power batteries (PBs) from new energy vehicles (NEVs) is a crucial measure to address resource shortages and reduce carbon emissions. This study examined the insufficient collaboration among the responsible entities and the imperfections in market mechanisms within the PB recycling system. We overcome the limitations of traditional tripartite evolutionary game models by developing a four-party evolutionary game model that incorporates the government, manufacturers, recyclers, and consumers to investigate the strategic interactions within the extended producer responsibility (EPR) framework. Using MATLAB 2023a numerical simulations and Lyapunov stability analysis, we found that the system’s stability and efficiency depend on stakeholder collaboration and effective government policy guidance. The system evolves toward a Pareto optimal state when all parties adopt proactive recycling strategies. Meanwhile, ensuring substantial profits for manufacturers and recyclers is critical for the feasibility and stable operation of compliant recycling channels. While manufacturers and recyclers are more sensitive to subsidies than consumers, consumer decision-making is key to market stability. Long-term excessive subsidies may lead to diminishing marginal benefits. Strategic recommendations are provided for policymakers and stakeholders to enhance the efficiency and sustainability of the PB recycling system.
Viacheslav Davydenko, Anna Kavunska, Viacheslav Barba
The study focuses on the conceptual, theoretical, empirical and methodological foundations of a legal and economic nature, concerning the legal support for the activities of operational units of the National Police in preventing cybercrime, in the context of economic globalisation and existential challenges. Methodology. The present study employed both general and special methods of cognition. Utilising the dialectical method, the author evaluated the essence of countering cybercrime by operational police units in terms of its prevention and prevention of these offences in the legal and economic planes, according to a diverse range of parameters. The analysis established the foundations for a multidimensional study of all the characteristic features of cybercrime prevention in the context of economic integration, in terms of economic and legal etymology. The synthesis established the conditions necessary for the generalisation of the distinctive features of the activities of police operational units. The formal legal method enabled the correct interpretation of the content of legal acts defining the general and special legal regimes of preventive activities of operational police units within the context of economic globalisation and existential challenges. The purpose of the article is to provide a comprehensive analysis of the potential areas for improvement in the activities of the operational units of the National Police in order to prevent cybercrime in the context of economic globalisation and existential challenges. The results of the study demonstrated that the role of the operational units of the National Police in preventing cybercrime in the context of economic globalisation and existential challenges encompasses a range of complex measures in various areas of activity of the relevant police unit, primarily in ensuring cybersecurity. It has been determined that there are specific areas in which the operational units of the National Police can enhance their efforts to combat cybercrime. These areas have been identified in the context of economic globalisation and existential challenges. Conclusion. The advent of cybercrime can be attributed to the prevailing technological transformations in the economy, particularly with regard to the dissemination of information as the primary resource and catalyst for societal advancement. The author's position is that the implementation of economic policies aimed at curbing cybercrime should encompass the following measures: the establishment of a fair and balanced tax system, the formulation of a strategic economic development policy, the promotion of production-oriented initiatives, and the allocation of resources towards the enhancement of public services. From the standpoint of a company's economic security, measures to prevent cybercrime are crucial, due to both local and global economic factors. The analysis of cybercrime legislation enabled the identification of measures of general and special competence taken by the operational units of the National Police. Concurrently, within the legislative framework on national security, which encompasses cybersecurity, the National Police is delineated as a subject of counteraction to such crime, signifying a specialised competence. Concomitantly, the general competence in combating and preventing cybercrime is reflected in the primary function of the National Police, namely to ensure public safety and order, protect human rights and freedoms, the interests of society and the state, and combat crime, including in cyberspace. The primary focus of the implementation of the special competence of operational police units is the Cyber Police Department, which is an integral component of the National Police. The Cyber Police Department is responsible for conducting comprehensive operational and investigative activities as a component of the broader strategy to prevent cybercrime. The authors support the view that the following measures, carried out by operational police units, stand out as effective means of countering cybercrime under conditions of existential challenges associated with armed aggression. These measures include counterintelligence, operational and investigative work, and procedural work to counter relevant information threats; the introduction of incentive measures aimed at creating their own information product; the development of their own information and telecommunications infrastructure; and the establishment of communication between civil society and law enforcement agencies in this area.
The mother’s love is vital for adolescent development, yet there is a lack of specific tools to measure its psychological absence. This study aimed to develop the Mother-Love Absence Scale (MLAS) by revising the Father-Love Absence Scale (FLAS) and verify its reliability and validity among adolescents. Study 1 included 2700 junior and senior high school adolescents. The junior and senior high school samples were each randomly split into two subsamples. One subsample was used for Exploratory Factor Analysis (EFA), while the other was used for Confirmatory Factor Analysis (CFA), internal consistency reliability tests, and cross-gender measurement invariance tests. The results indicated that the factor structure of the MLAS was consistent with that of the FLAS, both comprising four factors: emotional absence, cognitive absence, behavioral absence, and volitional absence. Furthermore, multi-group confirmatory factor analysis verified the gender invariance of the scale. In Study 2, 193 adolescents were surveyed to conduct a CFA and a criterion-related validity analysis. The results of the CFA again demonstrated a good model fit for the four-factor structure. The criterion-related validity analysis indicated that the mother-love absence was negatively connected with parent–child interaction and positively correlated with parental phubbing. Therefore, the revised MLAS has well reliability and validity and can be a reliable instrument for measuring mother-love absence in adolescents.
The deployment of electric vehicle charging stations (EVCSs) is crucial for the large-scale adoption of electric vehicles and the sustainable energy development of global cities. However, existing research on the spatial distribution of EVCSs has provided limited analysis of spatial equity from the perspective of supply–demand relationships. Furthermore, studies examining the influence of the built environment on EVCS accessibility are scarce, and often rely on single methods and perspectives. To explore the spatial characteristics of EVCS accessibility and its influencing factors, using multi-source urban spatial data, this study initially employs the Gaussian two-step floating catchment area (G2SFCA) method to measure and analyze the spatial distribution characteristics of EVCS accessibility in Guangzhou, China, with consideration of supply–demand relationships. Subsequently, it integrates the MGWR and random forest (RF) models to comprehensively investigate the impact mechanism of the built environment on EVCS accessibility from the perspectives of spatial heterogeneity and non-linear relationship. The results show that the EVCS accessibility exhibits a “ higher in the west and lower in the east, with extreme core concentration” distribution pattern, and has significant spatial autocorrelation. The built-environment variables exhibit different scale effects and spatial non-stationarity, with widespread non-linear effects. Among them, the auto service, distance to regional center, and distance to subway station play important roles in influencing EVCS accessibility. These findings offer important guidance for the efficient and equitable layout of EVCSs in high-density cities.
Biplab Bhattacharjee, Shubham Kumar, Piyush Verma
et al.
The increase in digital disruptions and changing preferences of different stakeholders has led to digital adoption in all hierarchies of business ecosystem. This study focused on the identification of the determinants of digitalization in unorganized small, localized retail outlets (Kirana stores) of an emerging economy. A theoretical model was constructed with certain modifications based on technology adoption models such as Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to study the impact on business performance in general and as an effect of pandemic. A survey of 285 Unorganized Localized Retail Outlets Stores from different regions of India was used to validate this theoretical model, and structural equation modeling was then further employed. The findings underscore that cost, compatibility, perceived ease of use, and perceived usefulness significantly affect the intention to digitalize. By addressing the post-pandemic impact of digitalization within an unorganized sector in an emerging economy, this study adds to the scant literature that exists in this context.
In this paper, the growing significance of data analysis in manufacturing environments is exemplified through a review of relevant literature and a generic framework to aid the ease of adoption of regression-based supervised learning in manufacturing environments. To validate the practicality of the framework, several regression learning techniques are applied to an open-source multi-stage continuous-flow manufacturing process data set to typify inference-driven decision-making that informs the selection of regression learning methods for adoption in real-world manufacturing environments. The investigated regression learning techniques are evaluated in terms of their training time, prediction speed, predictive accuracy (R-squared value), and mean squared error. In terms of training time (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>T</mi><mi>T</mi></mrow></semantics></math></inline-formula>), <i>k</i>-NN20 (<i>k</i>-Nearest Neighbour with 20 neighbors) ranks first with average and median values of 4.8 ms and 4.9 ms, and 4.2 ms and 4.3 ms, respectively, for the first stage and second stage of the predictive modeling of the multi-stage continuous-flow manufacturing process, respectively, over 50 independent runs. In terms of prediction speed (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>S</mi></mrow></semantics></math></inline-formula>), DTR (decision tree regressor) ranks first with average and median values of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5.6784</mn><mo>×</mo><msup><mn>10</mn><mn>6</mn></msup></mrow></semantics></math></inline-formula> observations per second (ob/s) and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4.8691</mn><mo>×</mo><msup><mn>10</mn><mn>6</mn></msup></mrow></semantics></math></inline-formula> observations per second (ob/s), and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4.9929</mn><mo>×</mo><msup><mn>10</mn><mn>6</mn></msup></mrow></semantics></math></inline-formula> observations per second (ob/s) and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5.8806</mn><mo>×</mo><msup><mn>10</mn><mn>6</mn></msup></mrow></semantics></math></inline-formula> observations per second (ob/s), respectively, for the first stage and second stage of the predictive modeling of the multi-stage continuous-flow manufacturing process, respectively, over 50 independent runs. In terms of R-squared value (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>), BR (bagging regressor) ranks first with average and median values of 0.728 and 0.728, respectively, over 50 independent runs, for the first stage of the predictive modeling of the multi-stage continuous-flow manufacturing process, and RFR (random forest regressor) ranks first with average and median values of 0.746 and 0.746, respectively, over 50 independent runs, for the second stage of the predictive modeling of the multi-stage continuous-flow manufacturing process. In terms of mean squared error (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>M</mi><mi>S</mi><mi>E</mi></mrow></semantics></math></inline-formula>), BR (bagging regressor) ranks first with average and median values of 2.7 and 2.7, respectively, over 50 independent runs, for the first stage of the predictive modeling of the multi-stage continuous-flow manufacturing process, and RFR (random forest regressor) ranks first with average and median values of 3.5 and 3.5, respectively, over 50 independent runs, for the second stage of the predictive modeling of the multi-stage continuous-flow manufacturing process. All methods are further ranked inferentially using the statistics of their performance metrics to identify the best method(s) for the first and second stages of the predictive modeling of the multi-stage continuous-flow manufacturing process. A Wilcoxon rank sum test is then used to statistically verify the inference-based rankings. <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>D</mi><mi>T</mi><mi>R</mi></mrow></semantics></math></inline-formula> and <i>k</i>-NN20 have been identified as the most suitable regression learning techniques given the multi-stage continuous-flow manufacturing process data used for experimentation.
Engineering machinery, tools, and implements, Technological innovations. Automation
ABSTRACT Widely available digital technologies are empowering citizens who are increasingly well informed and involved in numerous water, climate, and environmental challenges. Citizen science can serve many different purposes, from the “pleasure of doing science” to complementing observations, increasing scientific literacy, and supporting collaborative behaviour to solve specific water management problems. Still, procedures on how to incorporate citizens’ knowledge effectively to inform policy and decision-making are lagging behind. Moreover, general conceptual frameworks are unavailable, preventing the widespread uptake of citizen science approaches for more participatory cross-sectorial water governance. In this work, we identify the shared constituents, interfaces, and interlinkages between hydrological sciences and other academic and non-academic disciplines in addressing water issues. Our goal is to conceptualize a transdisciplinary framework for valuing citizen science and advancing the hydrological sciences. Joint efforts between hydrological, computer, and social sciences are envisaged for integrating human sensing and behavioural mechanisms into the framework. Expanding opportunities of online communities complement the fundamental value of on-site surveying and indigenous knowledge. This work is promoted by the Citizens AND HYdrology (CANDHY) Working Group established by the International Association of Hydrological Sciences (IAHS).
This short contribution offers a perspective on the general topic of the Special Issue reflecting on the evolution of fashion and its contemporary meaning. Starting from a discussion of how the nature of fashion was shaped and contributed in turn to shape several founding ideas of modern civilization, it introduces some possible directions for re-signifying fashion, transforming its social and cultural function toward more sustainable paradigms.