Search Results (603)

Anxiety disorders represent a significant global health challenge, yet a substantial treatment gap persists, motivating the development of scalable digital health solutions. This study investigates the potential of integrating passive physiological data from consumer wearable devices with subjective self-reported surveys to predict state–trait anxiety. Leveraging the multi-modal, longitudinal LifeSnaps dataset, which captured “in the wild” data from 71 participants over four months, this research develops and evaluates a machine learning framework for this purpose. The methodology meticulously details a reproducible data curation pipeline, including participant-specific time zone harmonization, validated survey scoring, and comprehensive feature engineering from Fitbit Sense physiological data. A suite of machine learning models was trained to classify the presence of anxiety, defined by the State–Trait Anxiety Inventory (S-STAI). The CatBoost ensemble model achieved an accuracy of 77.6%, with high sensitivity (92.9%) but more modest specificity (48.9%). The positive predictive value (77.3%) and negative predictive value (78.6%) indicate balanced predictive utility across classes. The model obtained an F1-score of 84.3%, a Matthews correlation coefficient of 0.483, and an AUC of 0.709, suggesting good detection of anxious cases but more limited ability to correctly identify non-anxious cases. Post hoc explainability approaches (local and global) reveal that key predictors of state anxiety include measures of cardio-respiratory fitness (VO₂Max), calorie expenditure, duration of light activity, resting heart rate, thermal regulation and age. While additional sensitivity analysis and conformal prediction methods reveal that the size of the datasets contributes to overfitting, the features and the proposed approach is generally conducive for reasonable anxiety prediction. These findings underscore the use of machine learning and ubiquitous sensing modalities for a more holistic and accurate digital phenotyping of state anxiety. Full article

Introduction: Cancer cachexia is associated with systemic inflammation and metabolic derangement, leading to muscle atrophy, which affects over 80% of pancreatic cancer patients, the highest rate among all malignancies, negatively impacting quality of life and significantly reducing survival rate. Malnutrition, skeletal muscle loss (sarcopenia), and imbalanced energy expenditure are indicators of cachexia. No established screening tools in clinical practice are specific and sensitive enough to detect pancreatic cancer in its early stages. Objective: This paper aims to provide new insights by examining contributing factors in the development of cachexia and exploring future directions for managing cachexia to improve quality of life and overall survival in patients with pancreatic cancer. Conclusions: It is clinically vital to identify nutritional risks and consider aggressive nutritional interventions as soon as pancreatic cancer is diagnosed to (1) stabilize body weight, (2) decrease the disease-associated burden, and (3) improve the quality of life. To support the clinical management of cachexia in this population, more research is needed. Specifically, research is needed to identify biomarkers, such as muscle fiber-related genes, optimize drug delivery tailored to the specific metabolic and molecular profile, combine chemotherapeutic agents with nutritional supplements, and consider non-pharmacological interventions such as acupuncture and exercise specifically for cancer-cachexia patients. A multifaceted approach will help achieve a better quality of life and prolonged overall survival in patients with pancreatic cancer. Full article

Bridges play an increasingly indispensable role in endorsing the economic and social development of societies by linking highways and facilitating the mobility of people and goods. Concurrently, they are susceptible to high traffic volumes and an intricate service environment over their lifespans, resulting in undergoing a progressive deterioration process. Hence, efficient measures of maintenance, repair, and rehabilitation planning are critical to boost the performance condition, safety, and structural integrity of bridges while evading less costly interventions. To this end, this research paper furnishes a mixed review method, comprising systematic literature and scientometric reviews, for the meticulous examination and analysis of the existing research work in relation with maintenance fund allocation models of bridges (BriMai_all). With that in mind, Scopus and Web of Science databases are harnessed collectively to retrieve peer-reviewed journal articles on the subject, culminating in 380 indexed journal articles over the study period (1990–2025). In this respect, VOSviewer and Bibliometrix R package are utilized to create a visualization network of the literature database, covering keyword co-occurrence analysis, country co-authorship analysis, institution co-authorship analysis, journal co-citation analysis, journal co-citation, core journal analysis, and temporal trends. Subsequently, a rigorous systematic literature review is rendered to synthesize the adopted tools and prominent trends of the relevant state of the art. Particularly, the conducted multi-dimensional review examines the six dominant methodical paradigms of bridge maintenance management: (1) multi-criteria decision making, (2) life cycle assessment, (3) digital twins, (4) inspection planning, (5) artificial intelligence, and (6) optimization. It can be argued that this research paper could assist asset managers with a practical guide and a protocol to plan maintenance expenditures and implement sustainable practices for bridges under deterioration. Full article

Energy storage facilities serve as flexible resources that comprehensively support grid operations; they are also essential, especially when the thermal power plants that previously served as regulators run out. Electricity is becoming the dominant carrier through which the bulk of consumers’ energy needs are met. The efficiency of long-distance transmission and the ease of conversion to other forms of energy in Poland are attributed to the national grid. Thanks to the development of new technologies and distribution channels, energy is changing its supply network system. The purpose of this article is to discuss the economic viability of energy storage systems and their strategic role in the energy transition. The research methods used are data analysis, and the dependence on capital expenditures ($CAPEX$) and operating costs ($OPEX$) of energy storage in distribution channels. Energy storage facilities operated by grid companies account for 90% of the installed capacity, but there is a noticeable increase in the number of prosumer installations, with an energy storage of up to 50 KWh at microinstallations. Full article

To achieve carbon peak and neutrality goals and promote sustainable development, the power sector, as China’s largest source of carbon emissions, is the first industry to implement the national carbon emission trading scheme (ETS). A differences-in-differences model is employed on firm-level data to assess the causal impact of China’s national ETS, launched in 2017, on the sustainable technology progress of power generation enterprises. This study employs green patents and total factor productivity as measures for sustainable technology progress and then explores mechanisms and heterogeneity of the impact. Results show that: (1) The national ETS has a positive effect on green innovation capability and efficiency in the power industry, and the increasing causal effect is mainly achieved through research and development expenditure. (2) The national ETS exerts a more significant positive effect on power generation enterprises that are non-state-owned, have smaller asset scale, demonstrate superior environmental performance, and are located in the eastern region. However, there is no significant difference in total factor productivity across power enterprises. (3) Green innovations are predominantly concentrated in new energy and hybrid power generation enterprises. This study contributes to the literature by providing novel empirical evidence from China’s national ETS, highlighting its dual impact on innovation and productivity within a unified framework. The findings not only offer targeted recommendations for China’s power sector but also serve as an important reference for other high-emitting industries and other regions worldwide facing the same challenges in their pursuit of sustainable development. Full article

Using systematic literature observations, this study explains how 3D printing technology is being applied to innovative sustainable construction (Systematic Literature Review). Additive manufacturing, also referred to as 3D printing technology, has greatly increased productivity and adoption in the building sector. The utilization of eco-friendly materials, enhancing sustainable building practices, and the environmental impact of 3D printing technology in comparison to conventional techniques are the three primary areas of attention for this study. By reducing material waste through additive manufacturing methods, 3D printing technology may employ alternative resources like fly ash, geopolymers, and limestone calcined clay (LC3) cement, which lowers carbon emissions considerably, according to observation data. This technology also speeds up the construction process, saves costs, and enables complex architectural designs that are difficult to achieve with conventional methods. There are still a number of issues, though, such as the high upfront expenditures of supplies and equipment and the long-term robustness of the molded structures that are produced. Nevertheless, 3D printing has enormous potential to transform building methods into more effective and ecologically friendly ones as a result of technological advancements and growing knowledge of desirability. This research provides valuable insights for stakeholders in supporting wider application of this technology to achieve sustainable development goals. Full article

This research investigates the structural drivers of Poland’s energy transition to decarbonization and wider sustainable development goals. With a focus on the period 2010–2023, we use longitudinal regression analysis and cluster-based segmentation to examine the dynamic interactions between investment expenditure, deployed renewable capacity, and innovation expenditure in driving renewable electricity production. Our findings suggest that although installed capacity continues to be the nearest cause of renewable energy output, innovation expenditure has an extraordinarily large marginal effect, acknowledging the system-transformational role of technology innovation in low-carbon systems. Regression specifications suggested that the establishment of Poland’s transformation process is not only guided by the growth in capital, but also by the systemic embedment of knowledge-driven innovation. Cluster analysis reveals three successive stages of sectoral development—initial growth (2010–2013), consistent expansion (2014–2019), and rapid transformation (2020–2023)—with blended policy actions and structural effects. Despite the long shadow of Poland’s coal-linked past and post-2015 stagnation in innovation, the results signal a major move towards a more low-emitting, resilient power system. The report offers empirical facts and prescriptive evidence to guide policy formulation supporting collective, innovation-driven approaches essential for driving energy change in coal-dominated economies. Full article

Food insecurity remains a persistent global challenge, despite significant advancements in agricultural production and technology. The main objective of this study is to identify and quantitatively assess some of the structural determinants influencing country-level food insecurity and provide an empirical background for policy-making aimed at achieving the Sustainable Development Goal of Zero Hunger (SDG 2). This study employs a beta regression model in order to study moderate or severe food insecurity across 153 countries, using a cross-sectional dataset that integrates economic, agricultural, political, and demographic independent variables. The analysis identifies low household per capita final consumption expenditure (β = −9 × 10⁻⁵, p < 0.001), high income inequality expressed as a high GINI coefficient (β = 0.047, p < 0.001), high long-term inflation (β = 0.0176, p = 0.003), and low economic globalization (β = −0.021, p = 0.001) as the most significant predictors of food insecurity. Agricultural variables such as land area (β = −1 × 10⁻⁵, p = 0.02) and productivity per hectare (β = −9 × 10⁻⁵, p = 0.09) showed limited but statistically significant inverse effects (lowering food insecurity), while factors like unemployment, political stability, and conflict were not significant in the model. The findings suggest that increased economic capacity, inequality reduction, inflation control, and global trade integration are critical pathways for reducing food insecurity. Future research could employ beta regression in time-series and panel analyses or spatial models like geographically weighted regression to capture geographic differences in food insecurity determinants. Full article

With environmental and economic disruptions occurring faster than ever before, the link between green innovation and national competitiveness deserves further analysis. This article investigates how sustainability-oriented strategies (particularly investments in research and development (R&D), renewable energy, and innovation capacity) affect the performance of environmental goods exports and national economic resilience. An exploratory cross-sectional analysis is conducted using multiple linear regression models applied to a sample of 14 countries, including the seven most sustainability-oriented economies and seven countries whose economic growth relies predominantly on fossil fuels. The results suggest a strong positive relationship between R&D expenditure and green trade competitiveness, while renewable energy consumption indicators produce mixed or even negative short-term effects. Adjusted net savings emerge as a robust indicator of both growth and competitiveness. However, no significant associations were found between renewable energy indicators and economic resilience, highlighting transitional trade-offs and institutional barriers inherent in ecological transformation. The study contributes to the growing literature on green transitions by combining macroeconomic indicators of innovation and sustainability with export performance. Policy implications include aligning innovation strategies with trade objectives, improving the measurement of green competitiveness, and supporting institutional preparedness for the transition. Full article

Obesity (lipotoxicity) results from a chronic imbalance between energy intake and expenditure. It is strongly associated with type 2 diabetes mellitus (T2DM, glucotoxicity) and considered a major risk factor for the development of metabolic complications. Their convergence constitutes “diabesity”, representing a major challenge for public health worldwide. Limited treatment efficacy highlights the need for novel, multi-targeted therapies. Non-shivering thermogenesis (NST), mediated by brown and beige adipose tissue and skeletal muscle, has emerged as a promising therapy due to its capacity to increase energy expenditure and improve metabolic health. Also, skeletal muscle plays a central role in glucose uptake and lipid oxidation, further highlighting its relevance in diabesity. This review explores current and emerging knowledge on physiological stimuli, including cold exposure, physical activity, and fasting, as well as bioactive ingredients and drugs that stimulate NST in thermogenic tissues. Special emphasis is placed on melatonin as a potential regulator of mitochondrial function and energy balance. The literature search was conducted using MEDLINE and Web of Science. Studies were selected based on scientific relevance, novelty, and mechanistic insight; prioritizing human and high-quality rodent research published in peer-reviewed journals. Evidence shows that multiple interventions enhance NST, leading to improved glucose metabolism, reduced fat accumulation, and increased energy expenditure in humans and/or rodents. Melatonin, in particular, shows promise in modulating thermogenesis through organelle-molecular pathways and mitochondrial protective effects. In conclusion, a multi-target approach through the activation of NST by physiological, nutritional, and pharmacological agents offers an effective and safe treatment for diabesity. Further research is needed to confirm these effects in clinical practice and support their use as effective therapeutic strategies. Full article

The synergistic advancement of “Digital China” and “Beautiful China” represents a pivotal national strategy for achieving high-quality economic development and a low-carbon transition. To illuminate the intrinsic mechanisms linking the digital economy (DE) to urban carbon emission performance (CEP), this study develops a novel two-sector theoretical framework. Leveraging panel data from 278 Chinese prefecture-level cities (2011–2023), we employ a comprehensive evaluation method to gauge DE development and utilize calibrated nighttime light data with downscaling inversion techniques to estimate city-level CEP. Our empirical analysis integrates static panel fixed effects, panel threshold, and moderating effects models. Key findings reveal that the digital economy demonstrably enhances urban carbon emission performance, although this positive effect exhibits a threshold characteristic linked to the maturity of digital infrastructure; beyond a specific developmental stage, the marginal benefits diminish. Crucially, this enhancement operates primarily through the twin engines of fostering technological innovation and driving industrial structure upgrading, with the former playing a dominant role. The impact of DE on CEP displays significant heterogeneity, proving stronger in northern cities, resource-dependent cities, and those characterized by higher levels of inclusive finance or lower fiscal expenditure intensities. Furthermore, the effectiveness of DE in reducing carbon emissions is dynamically moderated by policy environments: flexible economic growth targets amplify its carbon reduction efficacy, while environmental target constraints, particularly direct binding mandates, exert a more pronounced moderating influence. This research provides crucial theoretical insights and actionable policy pathways for harmonizing the “Dual Carbon” goals with the overarching Digital China strategy. Full article

This article examines the evolution of the most extensively researched subjects in e-mobility during the previous two decades. The objective of this analysis is to identify the lessons that the State of Kuwait, which is falling behind other nations in terms of e-mobility, can learn from in its efforts to adopt electric vehicles (EVs). To strengthen the body of knowledge and determine the most effective and efficient route to an “EV-ready” nation, the authors compiled data on the latest developments in the EV industry. A bibliometric analysis was performed on 3962 articles using VOSviewer software, which identified six noteworthy clusters that warranted further discussion. Additionally, we examined the sequential progression of these clusters as follows: (1) the environmental ramifications of electric mobility; (2) advancements in EV technology, including range extension and soundless engines, as well as the capital expenditure (CAPEX) and operating expenditure (OPEX) of purchasing and operating EVs; (3) concerns regarding the effectiveness and durability of EV batteries; (4) the availability of EV charging stations and grid integration; (5) charging time; and, finally, (6) the origin and source of the energy used in the development of e-mobility. Delineating critical aspects in the development of e-mobility can help to equip policymakers and decision makers in Kuwait in formulating timely and economical choices pertaining to sustainable transportation. This study contributes by cross-walking six global bibliometric clusters to Kuwait’s ten EV adoption barriers and mapping each to actionable policy levers, linking evidence to deployment guidance for an emerging market grid. Unlike prior bibliometric overviews, our analysis is Kuwait-specific and heat-contextual, and it reports each cluster’s size and recency to show where the field is moving. Using Kuwait driving logs, we found that summer (avg 43.2 °C) reduced the effective full-charge range by 24% versus pre-winter (approximately 244 km vs. 321 km), underscoring the need for shaded PV-coupled hyper-hubs and active thermal management. Full article

Handwashing is one of the recommended measures during the COVID-19 period to limit the spread of the disease and also contributes to the prevention of WASH-related illnesses. The objective of this study is to analyze the impact of using a handwashing device on household healthcare expenditures in Cameroon, particularly during the period of strict COVID-19 strict restrictions. The data used were collected in September 2021 from 604 Cameroonian households in the Centre and Littoral regions as part of a study funded by the International Development Research Centre (IDRC). To account for unobserved heterogeneity affecting both the decision to use a handwashing device and household healthcare expenditures, an Endogenous Switching Regression (ESR) model was employed. The results highlight that the main determinants of a household’s decision to use handwashing devices include environmental factors such as the region, given its importance in the implementation of communication strategies, as well as specific characteristics of the household head. Furthermore, the use of this device leads to a reduction of approximately 52% in healthcare expenditures for households that used it, which corresponds to an average amount of 12,900 CFA francs. Full article

Although organizational resilience is well established, refining the systematic quantitative evaluation of health systems resilience (HSR) remains an ongoing opportunity for advancement. Research either focuses on individual HSR indicators, such as social welfare policy, public expenditure, health insurance, healthcare quality, and technology, or broadly examines socio-economic factors, highlighting the need for a more comprehensive methodological approach. This study employed the Slacks-Based Measure (SBM) within Data Envelopment Analysis (DEA) to analyze efficiency by maximizing outputs. It systematically examined key HSR factors across countries, providing insights for improved policymaking and resource allocation. Taking a five-year (2016–2020) dataset that covered 55 to 56 countries and evaluating 17 indicators across governance, health systems, and economic aspects, the paper presents that all sixteen top-ranked countries with a perfect efficiency score of 1 belonged to the high-income group, with ten in Europe, highlighting regional HSR differences. This paper concludes that adequate economic resources form the foundation of HSR and ensure stability and sustained progress. A properly supported healthcare workforce is essential for significantly enhancing health systems and delivering quality care. Last, effective governance and the equitable allocation of resources are crucial for fostering sustainable development and strengthening HSR. Full article

This study evaluates the competitiveness and sustainable development prospects of French-speaking African countries by constructing a comprehensive framework integrating the TOPSIS method and adaptive LASSO algorithm. Using multivariate data from sources such as the World Bank, 30 indicators covering core, basic, and auxiliary competitiveness were selected to quantitatively analyze the competitiveness of 26 French-speaking African countries. Results show that their comprehensive competitiveness exhibits spatial patterns of “high in the north and south, low in the east and west” and “high in coastal areas, low in inland areas”. Algeria, Morocco, and six other countries demonstrate high competitiveness, while Central African countries generally show low competitiveness. The adaptive LASSO algorithm identifies three key influencing factors, including the proportion of R&D expenditure to GDP, high-tech exports, and total reserves, as well as five secondary key factors, including the number of patent applications and total number of domestic listed companies, revealing that scientific and technological investment, financial strength, and innovation transformation capabilities are core constraints. Based on these findings, sustainable development strategies are proposed, such as strengthening scientific and technological research and development and innovation transformation, optimizing financial reserves and capital markets, and promoting China–Africa collaborative cooperation, providing decision-making references for competitiveness improvement and regional cooperation of French-speaking African countries under the background of the “Belt and Road Initiative”. Full article