Search Results (389)

Background: Rapid population aging poses significant challenges to health and wellness systems, necessitating innovative technological interventions. Smart home technologies, particularly voice-activated intelligent assistants (smart speakers), represent a promising avenue for supporting aging populations. Objectives: This study critically examines the empirical literature on smart speakers’ influence on older adults’ health and well-being, mapping the characteristics of existing studies, assessing the current state of this domain, and providing a comprehensive overview. Methods: A mixed-methods systematic review was conducted in accordance with published guidelines. Bibliometric data, article purposes and outcomes, keyword network analysis, and mixed-methods findings from articles retrieved from five major databases were managed through the Covidence and VosViewer applications. Results: The majority of studies were conducted in the American region. Bibliometric analysis revealed five predominant thematic clusters: health management, psychological support, social connectedness, technology adoption, and usability. Findings demonstrated multifaceted benefits across several domains. Older adults reported improvements in daily living activities, enhanced emotional well-being, strengthened social connections, and overall health benefits. Qualitative evidence particularly emphasized the advantages of medication adherence, routine maintenance, and facilitated social support. However, mixed-method synthesis revealed significant barriers to adoption and sustained use, including privacy concerns, technical difficulties, cost constraints, and limited digital literacy among older users. Conclusions: The integration of smart speakers into the homes of older adults offers considerable potential to enhance technological wellness and promote successful aging in place, underscoring the need for structured integration of smart speaker technology and human-centered designs within geriatric care systems. Full article

This study explores how patients and stakeholders envision integrated digital health systems. Background/Objectives: Integrating artificial intelligence (AI), wearable data, electronic health records (EHRs), and patient-reported outcomes could enable proactive and personalized healthcare. However, current solutions remain fragmented and poorly aligned with user expectations. This study aimed to explore patient and stakeholder needs for AI-driven integration and propose a conceptual framework to inform future system design. Methods: As part of the NSF Innovation Corps (I-Corps) program, we conducted semi-structured interviews with 44 participants representing Health Enthusiasts, Chronic Condition Managers, and Low-Engagement Users. Interviews followed the I-Corps customer discovery framework and were thematically analyzed using a hybrid deductive–inductive approach. Results: Participants highlighted four priorities: (i) interoperability and unification of data from wearables, EHRs, and self-reports; (ii) actionable personalization with predictive insights; (iii) trust and transparency in AI recommendations, often requiring clinician oversight; and (iv) usability through low-friction, intuitive interfaces. Age- and persona-specific differences emerged: younger participants favoring predictive features and older participants emphasizing safety, reassurance, and clinical integration. Conclusions: This exploratory qualitative study identified stakeholder needs that informed a conceptual framework for integrated digital health platforms. While preliminary, the framework provides a blueprint for future technical development and validation of patient- and provider-centered systems. Full article

This study aims to help researchers quickly understand the latest research status of kiwifruit picking robots to expand their research ideas. The centralized picking of kiwifruit is confronted with challenges such as high labor intensity and labor shortage. A series of social issues including the decline in agricultural population and population aging have further increased the cost of its harvest. Therefore, intelligent picking robots replacing manual operations is an effective solution. This paper, through literature review and organization, analyzes and evaluates the performance characteristics of various current kiwifruit picking robots. It summarizes the key technologies of kiwifruit picking robots, from the aspects of robot vision systems, mechanical arms, and the end effector. At the same time, it conducts an in-depth analysis of the problems existing in automatic kiwifruit harvesting technology in modern agriculture. Finally, it is concluded that in the future, research should be carried out in aspects such as kiwifruit cluster recognition algorithms, picking efficiency, and damage cost and universality to enhance the operational performance and market promotion potential of kiwifruit picking robots. The significance of this review lies in addressing the imminent labor crisis in agricultural production and steering agriculture toward intelligent and precise transformation. Its contributions are reflected in greatly advancing robotic technology in complex agricultural settings, generating substantial technical achievements, injecting new vitality into related industries and academic fields, and ultimately delivering sustainable economic benefits and stable agricultural supply to society. Full article

Background/Objectives: A knowledge gap persists regarding anticoagulation therapy after endovascular stent insertion for malignant superior vena cava obstruction (mSVCO). Guidelines are supported by retrospective studies with a radiological focus and lack specific drug recommendations. No studies to date have captured the multi-disciplinary nature of decision-making over time. Methods: This single-center retrospective service evaluation includes patients with solid organ malignancy who received a stent for mSVCO between July 2016 and May 2022. Patient and treatment characteristics, clinical outcomes and prescribing decisions were collected from medical records and analyzed. Results: Of 49 patients (55% female, mean age 59), 73% had metastatic extra-thoracic disease at stent insertion. Technical success was achieved in 98% of cases and 92% survived to discharge. Forty-eight patients were followed until death. Median survival was 2.4 months. Post-procedure imaging (performed in 55% of patients) revealed 10 (21%) cases of systemic venous thromboembolism and 7 cases of stent thrombosis. Forty-four (91%) patients received anticoagulation therapy (62% therapeutic dose low molecular weight heparin). Those with thrombotic complications were fitter pre-procedurally than the rest of the cohort. There was one case of major bleeding. Twenty-two instances of therapy modification occurred following the initial plan, including nine changes due to a patient preference for oral therapy. Conclusion: Patients undergoing stenting for mSVCO demonstrate high thrombotic risk and a poor prognosis. Anticoagulation plans are frequently modified post discharge due to changing risk profiles and patient preferences. Multi-disciplinary collaboration is essential to support patient-centered and individualized management. Future research should investigate direct oral anticoagulants and anti-platelet therapy and develop risk assessment tools for this population. Full article

During water flooding processes, the high viscosity of heavy oil and significant reservoir heterogeneity often lead to severe water channeling and low sweep efficiency. Addressing the limitations of traditional hydrophobically associating polymer-based profile-control agents—such as significant adsorption loss, mechanical degradation during reservoir migration, resulting in a limited effective radius and short functional duration—this study developed a polymeric graded profile-control agent suitable for highly heterogeneous conditions. The physicochemical properties of the system were comprehensively evaluated through systematic testing of its apparent viscosity, salt tolerance, and anti-aging performance. The microscopic oil displacement mechanisms in porous media were elucidated by combining CT scanning and microfluidic visual displacement experiments. Experimental results indicate that the agent exhibits significant hydrophobic association behavior, with a critical association concentration of 1370 mg·L⁻¹, and demonstrates a “low viscosity at low temperature, high viscosity at high temperature” rheological characteristic. At a concentration of 3000 mg·L⁻¹, the apparent viscosity of the solution is 348 mPa·s at 30 °C, rising significantly to 1221 mPa·s at 70 °C. It possesses a salinity tolerance of up to 50,000 mg·L⁻¹, and a viscosity retention rate of 95.4% after 90 days of high-temperature aging, indicating good injectivity, reservoir compatibility, and thermal stability. Furthermore, within a concentration range of 500–3000 mg·L⁻¹, the agent can effectively emulsify Gudao heavy oil, forming O/W emulsion droplets with sizes ranging from 40 to 80 μm, enabling effective plugging of pore throats of corresponding sizes. CT scanning and microfluidic displacement experiments further reveal that the agent possesses a graded control function: in the near-wellbore high-concentration zone, it primarily relies on its aqueous phase viscosity-increasing capability to control the mobility ratio; upon entering the deep reservoir low-concentration zone, it utilizes “emulsion plugging” to achieve fluid diversion, thereby expanding the sweep volume and extending the effective treatment period. This research outcome provides a new technical pathway for the efficient development of highly heterogeneous heavy oil reservoirs. Full article

Declining fertility and population aging intensify labor shortages, making women’s reemployment after caregiving a policy priority. Using Taiwan as a case study, this study develops a real-time public opinion analysis system to complement delayed surveys and capture emerging barriers in labor-market reintegration. Drawing on 2022–2024 social media posts, the system applies sentiment co.mputing, clustering, and algorithmic attention to map four phases: withdrawal, intention, search, and reintegration. Findings show that younger women stress flexibility and childcare, while older returnees prioritize skill renewal and confidence rebuilding; sectoral variation supports life-cycle and clockspeed theories. Policy recommendations emphasize subsidies, training, quotas, and street-level implementation. Beyond technical contributions, the study embeds digital transformation (DT) into labor governance, showing a shift from as-is retrospective surveys to to-be-real-time monitoring. This transformation enhances policy agility, inclusiveness, and alignment with citizens’ lived experiences. The system thus functions as both a tool for rapid intervention and a DT-driven theoretical lens extending reemployment scholarship, offering transferable insights for aging societies. Full article

With the increasing age and traffic load of highway networks in China, preventive maintenance has become a critical strategy for extending pavement service life and improving infrastructure sustainability. However, the lack of standardized post-evaluation systems has hindered the scientific assessment of maintenance effectiveness. This study proposes a systematic post-evaluation framework for highway preventive maintenance projects based on the Hazard Analysis and Critical Control Points (HACCP)-Inspired methodology (Applying Principles of Hazard Analysis and CCP Identification). Adopting a full life-cycle perspective, the framework identifies critical control points (CCPs) across pre-, mid-, and post-implementation phases, targeting six key dimensions: ecological and environmental hazards, resource utilization hazard, engineering safety risks, engineering quality risks, socioeconomic benefit hazards, and social living environment hazards. A multi-level evaluation indicator system is constructed using hierarchical clustering and weighted through the Analytic Hierarchy Process (AHP). The framework is applied to a preventive maintenance project on the Jinghuan Expressway in Tianjin, China, demonstrating strong practical applicability. The final evaluation score of 84.1 out of 100 confirms the technical adequacy of the project while revealing areas for improvement in clean energy adoption and substructure monitoring. This framework provides a robust basis for standardizing post-evaluation practices and promoting sustainable highway maintenance management. Full article

The current transformation of global energy systems has been the subject of a multi-faceted scientific discourse for years. Researchers focus on technical and technological aspects, seeking new and improved alternatives to current solutions. They also analyse formal and legal frameworks of the changes and evaluate their economic aspects or environmental effects. The public’s attitude towards the changes in light of demanding environmental conditions is investigated the least. In particular, little heed is paid to the opinions of rural populations, especially in Poland. In light of the above, this paper aims to analyse the issue of Poland’s energy transition and the public’s perception of the challenges of environmental protection and the resulting need to improve energy solutions to promote the dissemination of renewable energy sources. The research area was Poland, and detailed research was conducted in five districts (Małopolska region), where the age of the respondents was taken as the differentiating feature. The study was based on a literature review and, at a detailed level, on a diagnostic survey among residents of Wadowicki, Miechowski, Krakowski, Limanowski, and Tarnowski Districts. The 2024 CAPI (Computer Assisted Personal Interviewing) survey involved 300 randomly selected interviewees. The study employed a qualitative and quantitative approach, utilising statistical tools such as Spearman’s rank correlation coefficient analysis, the Kruskal–Wallis rank test, and the nonparametric Mann–Whitney U test. The statistical analysis was supported by IBM’s SPSS v.25. The results show that the majority of the population understand and agree with the need for an energy transition in Poland towards renewable energy. Indications of no opinion or in favour of non-renewable energy in the Polish energy system are distinct. This class of indications is determined by the interviewees’ age and suggests potential for improving public awareness of the matter in the group of mature respondents. Full article

New-generation batteries are attracting increasing interest in response to today’s energy storage challenges, as evidenced by the steady rise in scientific publications on the topic. However, their industrial deployment remains limited due to the complexity of aging mechanisms, which are still poorly understood and difficult to control. While several promising developments have emerged in laboratory settings, they remain too immature to be scaled up. These aging processes, which directly affect the performance, safety, and lifespan of battery systems, also determine their technical and economic viability. This review offers a comparative analysis of aging phenomena—both specific to individual technologies and common across systems—drawing on findings from accelerated testing, post-mortem analyses, and modeling. It highlights critical failures such as interface instability, loss of active material, and mechanical stress, while also identifying shared patterns and the unique features of each technology. By combining experimental data with theoretical approaches, the article proposes an integrated framework for understanding and prioritizing aging mechanisms by technology type. It underscores the limitations of current characterization techniques, the urgent need for harmonized testing protocols, and the importance of standardized data sharing. Finally, it outlines possible avenues for improving the understanding and mitigation of aging phenomena. Full article

With an aging population and the widespread adoption of smart technologies, elderly residents’ perceived safety in smart apartments has become a critical determinant of their quality of life and their acceptance of technology. However, much of the current research remains confined to either technical or psychological dimensions, with insufficient attention to the systematic interactions among multiple factors as experienced by elderly populations. This study aims to systematically evaluate and optimize the living environments of older adults, with the goal of enhancing their overall quality of life and subjective well-being. This study employs the DANP–mV model to empirically analyze the safety perception of older adults in smart apartments, integrating case-based investigation and evaluation to propose targeted optimization strategies and improvement pathways. Unlike traditional approaches that treat criteria as independent, this hybrid model reveals the interdependencies among factors and establishes a more realistic prioritization of improvement actions. The study found that, compared with merely reinforcing physical security measures, factors such as enhanced remote security support, a stronger sense of control and coping confidence, and higher satisfaction with the protective system exert a more fundamental influence on the overall safety perception. These results demonstrate that adopting a systems-thinking approach shifts the focus of decision-making from superficial safety risks to underlying causal drivers, thereby mitigating resource allocation imbalances and enhancing the effectiveness and sustainability of safety improvement measures. Full article

Artificial intelligence (AI) is profoundly transforming heritage tourism through the incorporation of technological solutions that reconfigure the ways in which cultural heritage is conserved, interpreted, and experienced. This article presents a critical and systematic review of current AI applications in this field, with a special focus on their impact on destination management, the personalization of tourist experiences, universal accessibility, and the preservation of both tangible and intangible assets. Based on an analysis of the scientific literature and international use cases, key technologies such as machine learning, computer vision, generative models, and recommendation systems are identified. These tools enable everything from the virtual reconstruction of historical sites to the development of intelligent cultural assistants and adaptive tours, improving the visitor experience and promoting inclusion. This study also examines the main ethical, technical, and epistemological challenges associated with this transformation, including algorithmic surveillance, data protection, interoperability between platforms, the digital divide, and the reconfiguration of heritage knowledge production processes. In conclusion, this study argues that AI, when implemented in accordance with principles of responsibility, sustainability, and cultural sensitivity, can serve as a strategic instrument for ensuring the accessibility, representativeness, and social relevance of cultural heritage in the digital age. However, its effective integration necessitates the development of sector-specific ethical frameworks, inclusive governance models, and sustainable technological implementation strategies that promote equity, community participation, and long-term viability. Furthermore, this article highlights the need for empirical research to assess the actual impact of these technologies and for the creation of indicators to evaluate their effectiveness, fairness, and contribution to the Sustainable Development Goals. Full article

This study adopts a systems perspective to examine the persistent effects of China’s One-Child Policy (OCP) on the subjective well-being of older adults, emphasizing structural persistence, reinforcing feedback, and path-dependent lock-in in complex socio-technical systems. Using nationally representative data from the China Longitudinal Aging Social Survey (CLASS-2014), we exploit the OCP’s formal rollout at the end of 1979—operationalized with a 1980 cutoff—as a quasi-natural experiment. A Fuzzy Regression Discontinuity (FRD) design identifies the Local Average Treatment Effect of being an only-child parent on late-life well-being, mitigating endogeneity from selection and omitted variables. Theoretically, we integrate three lenses—policy durability and lock-in, intergenerational support, and life course dynamics—to construct a cross-level transmission framework: macro-institutional environments shape substitution capacity and constraint sets; meso-level family restructuring reconfigures support network topology and intergenerational resource flows; micro-level life-course processes accumulate policy-induced adaptations through education, savings, occupation, and residence choices, with effects materializing in old age. Empirically, we find that the OCP significantly reduces subjective well-being among the first generation of affected parents decades later (2SLS estimate ≈ −0.23 on a 1–5 scale). The effects are heterogeneous: rural residents experience large negative impacts, urban effects are muted; men are more adversely affected than women; and individuals without spouses exhibit greater declines than those with spouses. Design validity is supported by a discontinuous shift in fertility at the threshold, smooth density and covariate balance around the cutoff, bandwidth insensitivity, “donut” RD robustness, and a placebo test among ethnic minorities exempt from strict enforcement. These results demonstrate how demographic policies generate lasting impacts on elderly well-being through transforming intergenerational support systems. Policy implications include strengthening rural pension and healthcare systems, expanding community-based eldercare services for spouseless elderly, and developing complementary support programs. Full article

The growing demographic trend of an aging population, particularly in remote rural areas, exacerbates social isolation and limits access to essential goods and services. This vulnerability highlights a pressing need to develop sustainable solutions for their mobility and support. Using Geographic Information Systems (GISs) and network analysis, a workflow was developed to optimize road-based transport for the elderly. The analysis utilized an electric vehicle, with its range limitations, influenced by road slopes, being a critical variable for assessing route efficiency. Two potential solutions were investigated: (1) the delivery of goods and medicines and (2) the transport of passengers and medicines. The methodology was tested using the Municipality of Seia, Portugal, as a case study, with a defined weekly visit frequency. The results demonstrate that both proposed solutions are technically viable for implementation, with the transport of passengers and medicines being the most effective option. This study provides a foundational framework for developing practical, demand-oriented, sustainable transport and logistics services to support isolated elderly populations. Full article

Background/Objectives: Blood vessel tortuosity can complicate endovascular procedures such as endovascular thrombectomy in acute ischemic stroke. This study aimed to assess the morphometric characteristics of carotid arteries and investigate the association between the tortuosity of the carotid arteries and the technical aspects of endovascular thrombectomy, patient demographics and clinical characteristics, and treatment outcome. Methods: This retrospective study included 84 patients with ischemic stroke treated by endovascular thrombectomy at the newly established thrombectomy-capable stroke center. The following data were collected from prethrombectomy computed tomography angiography: aortic arch type, type of carotid artery tortuosity, and tortuosity index (TI). The technical aspects of the procedure, as well as patient demographics, were collected from the radiological information system. Results: Time from arterial puncture to the first pass was significantly shorter in patients with a nontortuous carotid artery compared to a tortuous one (p = 0.006). There were no significant differences in the number of passes, total duration of the procedure, and the difference in National Institutes of Health Stroke Scale (NIHSS) score before and after the procedure regarding the form of tortuosity. Patients with hypertension had significantly higher tortuosity index values compared to those without hypertension (p = 0.008), and patients with a nontortuous carotid tree were significantly younger compared to those with all forms of tortuosity (p = 0.003). Conclusions: The majority of patients had tortuous carotid arteries, which were associated with older age and hypertension. A high index of tortuosity was associated with a longer time from arterial puncture to the first pass, but not to the treatment outcome. Preprocedural recognition of carotid artery tortuosity may aid in endovascular thrombectomy procedural planning. Full article

In the context of the new power system, high-current switchgear is prone to various faults due to complex operation environments and severe load fluctuations. Among them, an abnormal temperature rise can lead to contact oxidation, insulation aging, and even equipment failure, posing a serious threat to the safety of the distribution system. The operation risk assessment of high-current switchgear has thus become a key to ensuring the safety of the distribution system. Ensemble learning, which integrates the advantages of multiple models, provides an effective approach for accurate and intelligent risk assessment. However, existing ensemble learning methods have shortcomings in feature extraction, time-series modeling, and generalization ability. Therefore, this paper first preprocesses and reduces the dimensionality of multi-source data, such as historical load and equipment operation status. Secondly, we propose an operation risk assessment method for high-current switchgear based on ensemble learning: in the first layer, an improved random forest (RF) is used to optimize feature extraction; in the second layer, an improved long short-term memory (LSTM) network with an attention mechanism is adopted to capture time-series dependent features; in the third layer, an adaptive back propagation neural network (ABPNN) model fused with an adaptive genetic algorithm is utilized to correct the previous results, improving the stability of the assessment. Simulation results show that in temperature rise prediction, the proposed algorithm significantly improves the goodness-of-fit indicator with increases of 15.4%, 4.9%, and 24.8% compared to three baseline algorithms, respectively. It can accurately assess the operation risk of switchgear, providing technical support for intelligent equipment operation and maintenance, and safe operation of the system. Full article