Search Results (3,171)

The article reflects on the care for the work of creation within Benedictine spirituality and within the broader tradition of the Cistercian Order. It seeks to demonstrate that monastic spirituality, though developed in a pre-modern context, contains enduring theological and ethical intuitions that remain relevant for contemporary ecological reflection. The starting point of the analysis is the Rule of Saint Benedict written by Benedict of Nursia, which, although it does not employ the modern vocabulary of ecology or environmental ethics, nevertheless articulates a coherent vision of human life characterized by reverence, moderation, and responsibility toward the created world. Particular attention is given to key spiritual and anthropological dimensions of the Benedictine tradition, such as attentive listening (obsculta), humility, moderation, stability, and responsible work, expressed synthetically in the principle ora et labora. These elements are interpreted not only as monastic disciplines shaping individual and communal life, but also as forming a relational anthropology in which the human person is understood as fundamentally embedded within a network of relationships with God, other people, and creation. In this sense, Benedictine spirituality already implies a non-exploitative attitude toward the natural world. The article then examines how concern for creation has been deepened and concretized in the spirituality, institutional practice, and historical development of the Cistercian Order. Drawing on selected Cistercian documents as well as contemporary monastic reflections, the study shows that care for the natural environment is inseparably linked with spiritual attentiveness to God, interior silence, openness of heart, and readiness to serve. The Cistercian tradition, with its emphasis on simplicity of life, manual labor, and harmonious integration with the surrounding environment, develops these Benedictine intuitions in a particularly concrete and historically embodied form. From this perspective, a pro-ecological attitude is not interpreted merely as a reactive response to contemporary environmental crises, but rather as a structural consequence of a theologically grounded vision of reality. It emerges from a deep relationship with God as Creator and from a sense of entrusted responsibility for creation understood as a gift rather than as an object of domination. Ecological sensitivity is thus presented as an intrinsic dimension of monastic spirituality rather than an external adaptation to modern concerns. The main research question of the article is: to what extent and in what way do Benedictine and Cistercian spiritual traditions provide theological, anthropological, and ethical foundations for an ecological attitude toward creation within the framework of contemporary integral ecology. To address this problem, the study employs qualitative research methods grounded in theological inquiry. The primary method is textual analysis of the Rule of Saint Benedict and selected Cistercian documents, complemented by theological–hermeneutical interpretation aimed at identifying key spiritual principles and their implicit ecological implications. In addition, the study applies a historical–critical perspective in order to situate monastic sources within their original cultural and theological context, as well as a comparative theological approach, which enables a dialogue between classical monastic spirituality and contemporary ecological theology. These methods are used not only to reconstruct historical meanings, but also to interpret monastic texts in light of contemporary debates on integral ecology, sustainability, and the ethics of responsibility for our common home. In this way, the article highlights a significant continuity between monastic wisdom and modern ecological reflection, showing their mutual capacity for enrichment. Full article

Mothers of preterm infants (PT; <37 weeks gestational age) face economic barriers to mother’s own milk (MOM) provision, including lack of paid maternity leave and unpaid workload that may prevent sustained MOM provision. The objective of this study was to understand how mothers of PT infants navigate decisions about MOM provision and paid and unpaid work. Semi-structured interviews were conducted with mothers of PT infants between 5 days and 10 weeks postpartum. Interviews included questions about responsibilities in the home, pre-delivery work experience and plans to provide MOM, and postpartum work experience and MOM provision. Data were analyzed using reflexive thematic analysis, following Braun and Clarke’s method. This study included 18 mothers, who were predominantly non-White (79%) and covered by Medicaid (72%) with infants born at a median gestational age of 32 weeks. Three themes emerged: (1) unexpected prenatal events create postpartum job uncertainty; (2) breastfeeding intentions are often derailed after PT delivery; and (3) the unpredictable reality of having a PT infant shifts maternal priorities and obligations related to paid and unpaid workload. PT delivery creates emotional and financial stress and uncertainty for new mothers. Although federal and employment-based paid leave may alleviate some financial stress for mothers employed prior to delivery in the United States, mothers who leave the workforce before delivery will not benefit from these policies. Policies are needed to support all mothers of PT infants in facilitating long-duration MOM provision, independent of employment status. Full article

The global shift toward an aging population presents significant challenges for healthcare systems. This is compounded by rising disability rates, fragmented care models that struggle to meet complex needs, and a digital divide caused by the emergence of smart technologies. This work aims to evaluate how the digital divide affects the adoption, usability, and perceived benefits of smart home technologies designed to support activities of daily living and health monitoring. The influences of socioeconomic status and geographic location (urban versus rural) on the digital divide are considered. Four databases (Web of Science™, Scopus^®, PubMed^®, and IEEE Xplore^®) were searched between 2014 and 2026, resulting in 71 studies that examined older adults, smart home technologies for daily living or health monitoring, and factors related to the digital divide. Findings were synthesized using the Technology Acceptance Model, Van Dijk’s Digital Divide Framework, and Health Behavior Models. Three key barriers were identified—economic, technical, and social—which disproportionately affected vulnerable groups. Smart Home Health Technologies (SH2Techs) present adoption challenges distinct from standalone devices because they require integrated infrastructure and sustained engagement. Limited research addressing the usability of non-clinical SH2Techs has identified the need for co-design, simplified interfaces, targeted training, and policy reforms to support equitable aging in place. Full article

Advancements in rechargeable batteries and environmental awareness campaigns have highlighted the importance of electric vehicles (EVs) in recent times. The influx of EVs has posed challenges in almost all areas of technology, including demand-side management (DSM). Extra generating units are switched ON to meet the resultant higher electricity demand, thus reducing the sustainability of the system. To overcome this challenge, effective DSM techniques integrating renewable energy sources are proposed to efficiently utilize the existing generating capacity. The primary goal is to fairly distribute available resources among smart homes and EV owners using the Shapley value and tau value. In this work, two scenarios are examined. First, a community energy storage (CES) approach is adopted to maximize CES revenue, reduce the grid peak-to-average ratio (PAR), and minimize electricity costs. Second, a coordinated group of EVs is utilized to minimize the impact of charging loads during peak hours while concurrently reducing EV charging costs. Simulation results show a reduction in the grid PAR from 2.468 to 1.799, or 27.1%, together with an average reduction of approximately 3% in the electricity cost of participating smart homes. In the EV scenario, optimal scheduling reduces total charging expenditure by 24.8% and lowers the system peak by 2.65% relative to uncoordinated charging of the same fleet, with the total cost distributed among the vehicles by the Shapley value. Benchmarking against a proportional-to-demand rule shows that the tau-value allocation coincides with proportional sharing, whereas the Shapley allocation shifts 4.2% of the allocation away from the household contributing most to the system peak. The framework provides a fair and individually rational cost allocation layer for community-scale peer-to-peer energy markets. Full article

Wrist accelerometers are widely used in clinical trials for continuous assessment of participants’ day-to-day physical activity and function, through derivation of metrics such as time spent in sedentary, non-sedentary, light, and moderate-to-vigorous physical activity (MVPA). Multiple algorithms have been proposed to derive these physical activity endpoints; however, the agreement across the endpoints derived from these algorithms has not been thoroughly explored. In this work, we leverage a publicly available dataset, CAPTURE-24, including wrist accelerometer data and experts’ annotations of various physical activities for 151 healthy adults, monitored at-home for one day, to compare three literature algorithms: Algorithm #1, SciKit Digital Health (SKDH), from Adamowicz et al., Algorithm #2 from Staudenmayer et al., and Algorithm #3 from Montoye et al. Algorithms’ outputs were assessed against experts’ annotations via paired t-tests, Pearson’s correlation (R), Bland–Altman analysis, accuracy, sensitivity, specificity, and F1-score. Algorithm #1 and Algorithm #2 showed stronger correlation and lower bias with experts’ annotations for time in sedentary (Algorithm #1: R = 0.91), and MVPA (Algorithm #1: R = 0.63), compared to Algorithm #3. In addition, Algorithm #1 and Algorithm #3 outperformed Algorithm #2 for time in light activity. Future work using longer monitoring periods and reference calorimetry devices should be performed to confirm the reproducibility of these findings. Full article

The increasing complexity of residential energy systems and the growing penetration of distributed resources require practical energy-management solutions that extend beyond conventional metering. This paper presents the design and implementation of a real-time Internet of Things (IoT)-based energy-management system for monitoring and controlling household energy consumption under different operating conditions. The proposed system adopts a dual-processor architecture, in which a primary microcontroller performs time-critical electrical measurements and low-level load switching, while a secondary processor operates as a local IoT gateway for data handling, rule-based control decisions, local visualization, and message queuing telemetry transport (MQTT)-based cloud communication through a 4G link. The contribution of this work is not associated with the individual use of dual processing, cellular communication, cloud monitoring, load shedding, or backup power, as these technologies have been previously reported in smart-metering and home energy-management systems. Instead, the study focuses on their coordinated integration within a residential-scale prototype that combines calibrated per-load monitoring, priority-based load control, outage-resilient reporting, and credit-aware load restriction. The system measures voltage, current, active and apparent power, power factor, and energy consumption for individual loads and supports centralized visualization through a cloud-based dashboard. The prototype was experimentally evaluated under three representative scenarios: overload, main power outage, and low-credit operation. In the overload scenario, automatic priority-based load shedding reduced the total load by up to 75%. During power outages, a battery-supported subsystem maintained monitoring and communication for real-time outage reporting. In the low-credit scenario, non-essential loads were disconnected when the user balance fell below a predefined threshold, while essential loads remained energized. The results demonstrate that the implemented prototype can provide integrated monitoring, local rule-based control, cloud reporting, and backup-supported operation within a unified residential energy-management platform. Full article

Deploying human pose estimation on low-cost, accelerator-free hardware remains a key open question for smart home activity recognition, where affordability and wide availability often matter as much as raw inference speed. This work addresses that question by evaluating thermal-image pose estimation on a Raspberry Pi 5, a CPU-only single-board computer with no dedicated neural-network accelerator. Building on a previously collected single-person thermal dataset of 2500 images annotated with 17 body keypoints, YOLOv8-pose, YOLO11-pose, and YOLO26-pose models were trained across five model scales (n–x) at three input resolutions ($640\times 512$, $320\times 256$, and $160\times 128$ px) and deployed on the Raspberry Pi 5. Models were evaluated in native PyTorch, ONNX, and NCNN export formats, with per-image latency, power consumption, energy per frame, and pose mAP50–95 measured for each configuration. Pose accuracy scaled consistently with model size and input resolution, reaching up to 95.6% pose mAP50–95 for YOLO26-x at $640\times 512$ px, with diminishing returns for the largest model scales. Export-format conversion to ONNX or NCNN preserved pose accuracy almost exactly relative to native PyTorch, with mean degradation below 0.6 percentage points, in contrast to the accuracy loss associated with numerical-precision reduction on GPU-accelerated platforms. NCNN consistently achieved the lowest per-image latency and energy consumption among the three formats, delivering up to 2.1–4.3× speed-up over PyTorch while keeping power draw up to 10 W across all configurations. The findings indicate that, unlike GPU-based edge deployment where precision reduction is the dominant efficiency driver, export-format optimization governs the latency–power–energy trade-off on CPU-only hardware, and that NCNN-based deployment on low-cost, widely available single-board computers offers a practical alternative for smart home thermal pose estimation. Full article

Under high-Mach-number flight conditions, the combustion chambers of hypersonic vehicles encounter extreme thermal environments marked by unilateral heating, high-heat-flux density, and supercritical pressure. Traditional hydrocarbon fuel cooling often suffers from insufficient heat sinks, high-temperature cracking and coking blockages, making it difficult to meet long-endurance thermal protection requirements. Liquid metal, due to its extremely high thermal conductivity, wide liquid phase temperature range, low Prandtl number and electromagnetic pump driving capability, has become a key technology for breaking through the bottleneck of high-heat-flux thermal protection. Apart from the magnitude of heat flux, the heat-transfer time scale (such as the characteristic thermal response time of the wall and the fluid) is also crucial. During hypersonic flight, transient thermal loads can change within milliseconds, requiring rapid thermal response. Liquid metals, due to their high thermal diffusivity, have a shorter thermal diffusion time compared to hydrocarbon fuels. This review employs a systematic literature review of approaches using gallium-indium-tin alloy, GaInSn, focusing on three core directions: the flow and heat-transfer characteristics of liquid metals, the optimization of cooling micro-channels, and the application of thermal protection systems. It summarizes the research progress at home and abroad, compares and analyzes the performance differences and applicable scenarios of typical liquid-metal working fluids, and summarizes the advantages and disadvantages of existing models, structural designs, and system schemes. The research shows that liquid metals can significantly alleviate thermal stratification and eliminate coking, and deep, narrow, tree-shaped, and biomimetic micro-channels can effectively enhance heat transfer. The liquid-metal-fuel dual-channel waste heat recovery and thermoelectric power generation system has demonstrated engineering application potential. Currently, the field still faces key challenges, such as unclear heat-transfer mechanisms under extreme conditions, the lack of general heat-transfer correlation formulas, insufficient compatibility with high-temperature materials, poor miniaturization and vibration resistance of electromagnetic pumps, and low system integration. In the future, efforts should be focused on developing multi-field coupled heat-transfer models under extreme thermal environments using engineered micro-channel structures, corrosion-resistant materials, and lightweight electromagnetic pumps, promoting the research and development of integrated thermal protection, heating and power generation systems, and providing support for the development of advanced thermal management systems for hypersonic aircraft and aviation engines. Full article

Ankle injuries may lead to severe complications, including chronic instability and reduced mobility. Rehabilitation therefore plays a critical role in restoring normal ankle function and preventing long-term impairment. However, conventional manual physiotherapy presents several limitations, such as limited availability of therapists, variability in treatment, and reduced accessibility for home-based rehabilitation. Consequently, significant research efforts have been devoted to the development of robotic and mechatronic devices for ankle rehabilitation. In this work, we propose the design of a simple and cost-effective parallel mechanism dedicated to ankle rehabilitation. The proposed device is based on a closed-chain kinematic architecture capable of reproducing the three principal rotational degrees of freedom of the ankle joint. This configuration enables controlled and repeatable rehabilitation exercises while ensuring mechanical stability and compactness. Furthermore, the device is designed to allow patients to perform rehabilitation exercises autonomously, without the continuous assistance of a physiotherapist, both in clinical environments and in home-based rehabilitation settings. Full article

Tourism scholarship has long treated technological innovation as an accelerant bolted onto a stable practice: people move through physical space to consume experiences, then return home. This conceptual paper asks what happens to the field’s theory once that assumption is relaxed. Rather than forecasting a single future, the paper develops a structured conceptual foresight framework to examine how emerging technological trajectories may challenge the constitutive assumptions of tourism theory. Drawing on tourism scholarship alongside developments in computation, the biosciences, and cognitive science, the framework integrates established concepts from futures studies including Voros’s futures cone, Inayatullah’s causal layered analysis, and Dator’s four generic futures to explore alternative trajectories for tourism. This analysis identifies four constitutive assumptions on which tourism theory quietly rests, namely geographic displacement, embodied co-presence, the destination as passive stage, and the tourist–host dyad, together with a typology of de-anchoring that traces what becomes of the field as each assumption loosens. Four conceptual scenarios follow: the dematerialization of place, biologically mediated travel, autonomous destination ecosystems, and the erosion of the tourist–host distinction. Some sit in the cone’s plausible band; others are placed at its preposterous edge on purpose to stress-test the field’s categories rather than to predict events. Throughout, the analysis stays tethered to tourism and hospitality concerns: destination economics, the work of destination management organizations, labor displacement, experiential inequality, the measurement infrastructure behind tourism statistics, and the shift from sustainability toward regeneration. We close with a research agenda for an anticipatory, theory-building stream within the field. Full article

Background/Objectives: Virtual home health care (VHHC) is increasingly used to support chronic disease management, yet patient satisfaction is often examined through a linear barrier-focused lens, in which more barriers are assumed to produce lower satisfaction. This study introduced a satisfaction resilience framework to identify factors associated with preserved satisfaction among barrier-exposed VHHC users. Methods: This cross-sectional analysis included 517 adults with chronic diseases who had used VHHC services and were recruited across five regions of Saudi Arabia. Patients were classified by barrier load and overall satisfaction into four groups: Resilient, Vulnerable, Comfortable, and Disengaged. Group differences were examined using one-way ANOVA, chi-square tests with Cramér’s V, point-biserial correlations, and a linear probability model restricted to high-barrier patients. Results: Overall, 167 patients (32.3%) reported high barrier exposure. Among them, 109 (65.3%) were classified as Resilient and 58 (34.7%) as Vulnerable, despite statistically equivalent barrier counts. Resilient patients reported higher motivation count, provider trust, perceived effectiveness, and functional equivalence with in-person care. Lifestyle-integration motivations, particularly avoiding work absence and waiting rooms, differentiated Resilient from Vulnerable patients, whereas access-related motivations did not. Perceived functional equivalence showed the largest between-group effect. In the high-barrier subsample, motivation count and provider trust were independently associated with Resilient status, while demographic variables were not significantly associated with it. Conclusions: Satisfaction with VHHC among chronic disease patients is not determined by barrier exposure alone. Service-design and communication strategies that strengthen lifestyle integration, functional equivalence beliefs, and provider trust may help healthcare teams support satisfaction resilience among patients who experience barriers to virtual care. Full article

Neonates born at higher altitudes may be at increased risk for adverse outcomes due to lower ambient oxygen availability. Despite frequent use of home oxygen therapy following neonatal intensive care unit (NICU) discharge, evidence-based guidelines assessing discharge readiness and oxygen prescribing in high-altitude settings remains limited. This study aimed to identify factors associated with adverse events following discharge and characterize infants discharged with home oxygen therapy in New Mexico. A retrospective chart review was conducted of infants discharged with home oxygen therapy from the University of New Mexico Hospital (UNMH) NICU from 1 July 2018 through 1 July 2023. We found that lower room air trial oxygen saturation and lower birth weight were both significantly associated with adverse events after discharge. These findings informed implementation institutional discharge protocols that indicated minimum room air saturation thresholds prior to discharge and oxygen adjustments for higher altitude. Although implementation of these protocols was not associated with a statistically significant reduction in adverse events, this work established a foundation for future multicenter collaboration with other centers at high altitude to validate these findings and further refine evidence-based discharge practices for infants living at high altitude. Full article

As urban housing becomes increasingly compact and companion animals become more deeply integrated into domestic life, human–cat cohabitation presents design challenges related to spatial efficiency, furniture wear, maintenance, and everyday coexistence. This study examines shared-interface conflicts in compact apartments and proposes an integrated SOR–Kano–FBS pathway for sustainable human–cat shared furniture design. In-home observations, semi-structured interviews, behavioral path recording, and Kano questionnaires were used to identify high-frequency activity contexts and prioritize user requirements. These requirements were translated through the FBS model into functional objectives, behavioral scripts, and structural strategies. The results indicate that ease of cleaning and maintenance, structural stability and user-perceived safety, and dedicated scratching guidance primarily represent must-be requirements. Movement-path separation, centralized storage, and aesthetic integration function as performance-enhancing requirements, whereas shared yet stratified zoning, elevated observation points, and moderate visual connection improve the cohabitation experience. Two conceptual designs—a human–cat shared living-room sofa system and a foldable work/study system—were developed. Their descriptive comprehensive acceptance indices were 0.802 and 0.794, respectively, while a combined conventional-furniture reference set scored 0.520. Because the reference set represented two conventional activity contexts, these values were used only as diagnostic, user-perception-based evidence and not as inferential proof or a direct ranking between the schemes. The findings suggest that the proposed pathway can support design-level sustainability in compact human–cat cohabitation; however, further validation through physical prototypes, long-term in-home testing, and life-cycle assessment is required. Full article

This paper examines how exclusionary epistemic practices embedded in science as a discipline are reproduced in classroom settings and how these practices can be disrupted when teachers adapt existing materials toward goals of epistemic inclusion. The inequities in access, participation, and representation in science that are reproduced at a societal level are developed in the classroom. Students learn how to do science—they develop the epistemic and social practices of the scientific discipline—in science education classes. When exclusion of some students from classroom knowledge building is normalized, marginalization becomes part of how students learn to engage in science and engineering practices. Drawing on a curricular redesign project conducted during the COVID-19 transition to virtual learning, the study highlights how the repositioning of teachers as active agents and experts in curriculum adaptation was central to the work. Using qualitative data-driven coding with productive disciplinary engagement and epistemic inclusion to guide the analysis, critical cases of curricular adaptations were developed with 10 elementary science teachers during a year-long project-based learning online science curriculum enactment project. Five themes associated with disruption of entrenched exclusionary practices emerged that can be codified as adaptation principles: 1. adapt features of project-based learning to: (1) bring in and leverage students’ identities and intellectual resources from home; (2) provide student-centered choice; (3) elicit diverse knowledge, expertise and ideas; (4) support students to make use of many different modalities; (5) dismantle the usual (traditional) structures between the teacher and students. Full article

Diagnosing faults across different smart homes is hard: sensor names, layouts, and daily routines differ from home to home, so a model trained in one home rarely works in another. We study an ontology-guided framework for cross-home fault diagnosis, but our main contribution is a benchmark-validity audit—a systematic check of whether the datasets used to evaluate such systems actually measure fault detection. Using the public Center for Advanced Studies in Adaptive Systems (CASAS) smart-home datasets (homes hh101–hh110) and real household power data (HomeC, UMass Smart*), we show that much of the high cross-home accuracy reported on these benchmarks is an artifact of features that re-encode the labelling rules rather than evidence of transfer: when those features are removed, the macro-averaged F1 score (macro-F1) collapses toward the level obtained with randomly permuted labels. We therefore treat these datasets as semantic-transfer and benchmark-validity studies, not fault-detection results. The framework’s distinguishing component is a counterfactual calibration layer that returns a probability for its recommended intervention; on a controlled structural causal model with known interventions, it achieves a Brier skill score of $0.369$ for intervention-success probabilities. Separately, on the simulation-derived LBNL Fan Coil Unit benchmark, a conventional gradient-boosted multiclass fault classifier achieves accuracy comparable to a random forest but about six times lower expected calibration error ($0.026$ vs. $0.159$) under a scenario-matched split. This calibration advantage does not generalize to held-out simulation scenarios, where the calibration error rises to $0.372$; we report this negative result as a limitation. We are explicit about scope: the ontology reasoner and the real-stream causal graph are only partially implemented, and the counterfactual recommendations are validated only under controlled or simulated conditions, not in deployed homes. The results are intended for researchers who build or benchmark sensor-based fault-diagnosis models, for dataset curators, and for practitioners who need calibrated rather than merely accurate outputs. All code, the proxy-label rules, and the leakage audit are released. Full article