Search Results (5,231)

Energy-autonomous Internet of Things (IoT) nodes are becoming important components of distributed fieldbus and wireless networks used in building automation, industrial monitoring and wider smart systems. Their operation is constrained not only by the amount of harvested and stored energy, but also by sensing activity, communication cost, computational workload and required service quality. This review analyzes these dependencies from a cross-layer perspective linking energy harvesting and power management, field-level IoT nodes, wireless communication technologies, and edge–fog–cloud computing. The main contribution is a conceptual decision framework derived from the literature synthesis, linking service adaptation, communication-path feasibility and coordination scope to the placement of sensing, processing and inference functions. The analysis shows that energy autonomy cannot be achieved by optimizing individual nodes only. Wireless connectivity, network topology and communication overhead directly affect the feasibility of higher-level processing, while edge and fog resources can reduce field-node load and improve local service continuity. The proposed framework therefore combines energy feasibility, communication conditions, service requirements and coordination scope. The resulting guidelines are particularly relevant to building automation and smart IoT systems, supporting interoperable, adaptive and energy-efficient distributed wireless architectures. Full article

Over the past two decades, advances in molecular genetics, immunology, neuroimaging, fluid biomarkers, and artificial intelligence have substantially transformed the diagnosis, classification, and treatment of neuromuscular disorders. However, increasing biological precision has also highlighted an important distinction between identifying disease mechanisms and characterizing their functional expression. Clinical neurophysiology occupies a specific position within this evolving diagnostic landscape by directly assessing nervous system function and providing objective information on impulse conduction, neuromuscular transmission, motor unit integrity, physiological reserve, and disease activity. Consequently, neurophysiological assessment contributes not only to diagnosis but also to differential diagnosis, longitudinal monitoring, prognostic assessment, and therapeutic evaluation. In this critical review, I examine the factors that have progressively shifted clinical neurophysiology from an interpretative clinical discipline toward a more procedural role. Using representative examples from myasthenia gravis, immune-mediated neuropathies, myopathies, and amyotrophic lateral sclerosis, I discuss how physiological information complements molecular, serological, imaging, and other biological biomarkers. I further examine the emerging role of artificial intelligence, including its potential for automated signal analysis and quantitative assessment, as well as current limitations related to generalizability, validation, and overreliance on pattern recognition. I propose a complementary conceptual framework in which biological and molecular approaches characterize disease mechanisms, while clinical neurophysiology defines their functional expression and clinical relevance in the individual patient. Within this framework, clinical neurophysiology should not be considered an alternative to precision medicine, but an integrated physiological dimension of it, connecting biological characterization with clinically actionable functional information. Full article

Organizations face a persistent tension between the need to hold employees accountable for results and the need to grant them the autonomy that fuels motivation, learning, and innovation. This conceptual paper theoretically develops and formalizes the tight–loose–tight (TLT) framework, a sequenced and cyclical approach to resolving this tension at the level of the individual employee. In the first tight phase, leaders and employees establish clear goals, expectations, and metrics that connect individual aspirations to organizational objectives. In the loose phase, leaders grant employees autonomy over how the work is accomplished, consistent with self-determination theory. In the final tight phase, leaders inspect what they expect through regular observation, feedback, and coaching, which then feeds forward into renewed clarity at the start of the next cycle. The framework integrates goal-setting theory, self-determination theory, and feedback and coaching research into a single dynamic process model, and it is distinguished from prior tight and loose constructs in the literature on organizational excellence, participative leadership, and national culture. Five research propositions are developed, together with guidance on measurement and research design, a rule that fixes each phase transition at the opening of the cycle, criteria for scoring cycle fidelity, and the condition under which the framework would be refuted. The framework’s application in an AI-enabled workplace is also considered. Implications for managers, limitations, and future research are discussed. Full article

A systematic review was conducted to identify ergonomic risk factors associated with musculoskeletal disorders in the limbs of mining workers, the assessment methods used, and their relationships. Following PRISMA 2020 guidelines, 53 studies from Scopus, ScienceDirect, Web of Science, MDPI, and IEEE Xplore (January 2015–May 2026) were included. Eleven risk factors were identified, with vibration (18 studies) and working hours (12 studies) being the most frequently reported. Five individual assessment methods (ISO/IEC 2631-1, REBA, OWAS, NIOSH, Risk Score), one symptom questionnaire (Nordic Questionnaire), and five hybrid/advanced methods (Bayesian Network + REBA, RULA + Nordic, SEM + Participatory Ergonomics, DMQ + Logistic Regression, RULA + Fuzzy Logic) were identified. Fifteen limb segments were evaluated, with the back (15 studies), shoulders (12 studies), and neck (12 studies) being the most studied, while wrists and elbows were notably absent. Hybrid methods demonstrated superior accuracy compared to individual approaches. Underground mining studies (58%) predominated over open-pit operations (42%). The findings provide an integrated framework connecting risk factors, affected limbs, and assessment tools. Critical gaps were identified, including the lack of wrist/elbow evaluation, underrepresentation of female miners, and absence of AI-based assessment systems. Four key challenges are proposed for future research, including developing deep learning-based ergonomic assessment tools and implementing real-time monitoring systems. Full article

This study develops a techno-economic sizing and energy-management framework based on the Hippopotamus Optimization Algorithm (HOA) for hydrogen-integrated autonomous Hybrid Renewable Energy Systems (HRES) for rural electrification. A representative remote community in Tabuk, Saudi Arabia, is investigated using 11 years of NASA POWER satellite-derived meteorological data. The modelled community is constructed from a synthesised connected-load inventory representing approximately 600 households and 3000 residents; accordingly, the results represent a simulation-based planning case study rather than a validated design for a specific settlement. Seven configurations combining photovoltaic generation, wind turbines, battery storage, hydrogen production and storage, fuel cells, and diesel generation are evaluated considering Total Net Present Cost, CO₂ emissions, and Loss of Power Supply Probability (LPSP), with a Demand Response Management System (DRMS) incorporated into the framework. The three objectives are combined using a weighted-sum scalar formulation, complemented by a hard-constrained formulation for reliability. HOA is benchmarked against Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Grasshopper Optimization Algorithm (GOA), Walrus Optimizer (WO), and Osprey Optimization Algorithm (OOA) under a common budget of 10,000 objective-function evaluations per run and 10 independent runs. Under the constrained formulation, six of the seven configurations satisfy LPSP ≤ 5% within the investigated sizing bounds, with costs of energy (COE) ranging from $0.1046/kWh for PV/wind/battery to $0.1357/kWh for wind/battery/diesel; the fully renewable PV/wind/hydrogen configuration is feasible at $0.1195/kWh. Only the wind-free configuration fails to satisfy both imposed constraints because of the 30% diesel-energy limit rather than reliability. Evaluation over the eleven individual meteorological years shows that all designs violate the 5% reliability criterion in every year, reaching 2.0–2.9 times the design LPSP because hour-of-year averaging removes prolonged low-resource periods. Re-optimization against the worst observed year increases COE by 33–63% and storage capacity by factors of three to five, with hydrogen storage in the fully renewable configuration increasing from 10 to 75.4 kg. Sensitivity analysis identifies wind availability as the dominant economic parameter, with a 20% wind-speed reduction increasing COE by 36.1%. The DRMS reduces the peak-to-average ratio by 20.0% for the assumed evening-peaking profile, whereas no reduction is obtained for an afternoon-peaking profile consistent with measured Saudi residential demand. These findings demonstrate that meteorological and demand-profile representation materially affects autonomous HRES sizing and should be explicitly considered when interpreting techno-economic optimization results. Full article

The facial muscles are crucial for nonverbal communication, physiological functions, and articulation. Unlike skeletal or masticatory muscles, they lack fascia, attach directly to the skin and function without joint-mediated movements or visual feedback. The aim of this study was to reconstruct the facial musculature using high-resolution computerised tomography (CT) and 3 Tesla magnetic resonance imaging (MRI) on 14 body donors, yielding segmented 3D datasets of the facial muscles, as well as bony and soft-tissue head structures. We hypothesise that the facial musculature comprises functional subunits with variable geometries that extend beyond classical anatomical definitions, with attachment points and three-dimensional positioning that differ from conventional descriptions. The most significant finding was that MRI could not resolve individual facial muscles as depicted in anatomical atlases. Instead, the musculature appeared as a single continuous sheet of muscle, embedded in fatty tissue and not attached to the bone. Whether the facial musculature is in fact continuous or consists of several muscles connected by connective tissue remains unclear. The difficulty of segmentation varied depending on the region; the zygomatic muscle was the easiest to separate, whilst the orbicularis oculi, frontalis and platysma muscles proved particularly difficult due to their thin, flat morphology. Full article

Small-scale industrial buildings commonly accommodate production areas and office units within the same building, where visual connectivity between these spaces is required to facilitate the monitoring and supervision of production processes. However, this functional requirement may increase airborne noise transmission from production areas to adjacent office spaces, thereby adversely affecting acoustic comfort. This study proposes an integrated acoustic design approach to improve the acoustic performance of small-scale industrial buildings while preserving the required visual connectivity. A woodworking workshop and its adjacent office unit in the Design and Application Laboratory Building at Eskişehir Technical University were selected as a case study. Existing acoustic conditions were determined through in-situ noise measurements. The airborne sound insulation performance of individual building elements was evaluated using Prediction Sound Insulation (INSUL 6.2), while room-scale acoustic performance, including flanking sound transmission, was assessed using Kalksandstein (KS 8.03). The results identified the aluminum-framed glazed partition system as the dominant airborne sound transmission path between the workshop and the office. Following the numerical evaluation of the proposed design modifications, the DnT,A values were predicted to increase from approximately 33 dB to 57 dB, thereby exceeding the Class D acoustic performance criterion specified in the Turkish Regulation on the Protection of Buildings Against Noise (BGKKHY) for existing buildings. The results demonstrate that effective acoustic retrofit cannot be achieved by considering individual building elements alone, but requires the integrated evaluation of spatial organization, critical transmission paths, and receiver conditions. The proposed approach provides a practical framework for the acoustic design and retrofit of small-scale industrial buildings where visual supervision must be maintained. Full article

The Qiongzhusi Formation, a thick and vertically heterogeneous marine shale sequence in southern China, presents substantial obstacles to efficient hydraulic stimulation when conventional horizontal-well staged fracturing is applied, owing to marked interlayer contrasts in mineralogy, rock mechanics, and natural fracture intensity. To address this challenge, this study develops an integrated methodological framework that combines a comprehensive fracability index (IFI) with discrete-element-based fluid–solid coupling simulations, aimed at elucidating fluid-driven fracture propagation behaviors and their corresponding flow performance under separate-layer fracturing conditions. Using Well Z202 as a field case, the IFI is first constructed by incorporating mineral composition, mechanical properties, and natural fracture attributes to quantitatively rank the stimulability of individual layers. Subsequently, a discrete element hydraulic fracturing model is established, which explicitly resolves the transient fluid flow within fracture networks, the pressure-dependent initiation and extension of tensile fractures, and the dynamic evolution of fracture aperture and permeability in response to varying injection rates and fluid viscosities. The simulations reveal that fracture network geometry—and hence the effective fluid-flow pathway—is governed by a tripartite interplay: brittle mineral content dictates the locus of initial fracture opening, natural fracture density and orientation control fluid diversion and network interconnectivity, and the in situ stress state modulates fracture complexity and vertical growth potential. Critically, the results demonstrate that high-angle natural fractures substantially enhance vertical fluid connectivity, with a single perforation cluster generating a stimulated fracture height of up to 23.7 m, a finding corroborated by post-fracturing temperature logging. The modeled fracture heights align closely with field-observed production contributions: lower perforation clusters, which develop greater fracture half-heights, account for 4.0–4.6% of gas production, whereas upper clusters contribute only 1.4–2.9%, confirming the dominant influence of downward fluid-driven fracture propagation. Overall, the proposed workflow—integrating quantitative fracability evaluation, fluid–solid coupled numerical simulation, and field flow-data validation—offers a robust theoretical foundation for optimizing separate-layer fracturing design, with direct implications for injection strategy, fracture conductivity maintenance, and long-term productivity forecasting in thick shale reservoirs. Full article

Coastal promenades support outdoor physical activity, yet how spatial morphology relates to thermal–response patterns during winter exercise remains unclear. This study examined physiological, cognitive, and psychological responses during standardized brisk walking at three coastal promenade locations in Qingdao, China. Sixteen healthy young adults completed the same protocol at all locations. Air temperature, relative humidity, wind speed, spatial characteristics, and multidimensional human responses were analyzed using linear mixed models. Linear mixed models identified an enclosure ratio × air temperature interaction for mind–body connection: the temperature–mind–body connection relationship was more negative in the semi-enclosed condition than in the open conditions, indicating greater temperature sensitivity in the semi-enclosed setting. Other spatial–thermal and thermal/individual associations across physiological, cognitive, affective, exercise-related, and thermal-perceptual outcomes were exploratory or response-specific. Together, these findings characterize winter coastal walking as a multidimensional human–environment experience. They also motivate future design tests that combine spatial diversity with opportunities for users to choose between exposure and localized protection. Full article

Communities in Miami face persistent disparities in HIV prevention, including low uptake of pre-exposure prophylaxis (PrEP) and gaps in routine HIV testing. These inequities are shaped by co-occurring structural conditions, such as food insecurity, housing instability, discrimination, transportation barriers, and broader barriers to care. Understanding how these conditions interconnect may inform approaches to sustained engagement in HIV prevention. We examined how structural and sociodemographic conditions and food insecurity were interconnected and reflective of overall structural vulnerability. We conducted a cross-sectional network analysis using data from 2755 surveys collected during Phases 1 and 2 of the Five Point Initiative (FPI), a community-engaged, place-based sexual health implementation strategy in Miami. Partial correlation networks were estimated using the EBICglasso algorithm across key structural barriers to HIV prevention. We calculated network centrality metrics (strength, betweenness, closeness) to characterize the relative connectivity and positioning of conditions within the network. Secondarily, we used traditional mixed correlations to characterize bivariate associations among structural and sociodemographic factors. Multiple regression also examined associations of barriers to care, discrimination, ethnicity, education, housing instability, and income with food insecurity. Additional models examined whether these differed by race. Food insecurity emerged as having the highest strength, closeness, and betweenness centrality within the network and showed the strongest association with barriers to care. Greater food insecurity was also associated with higher discrimination, lower income, unstable housing, and Latino ethnicity. Additional significant connections among variables were also found. Similarly, in secondary bivariate analyses, food insecurity was positively correlated with barriers to care (r = 0.331), discrimination (r = 0.251), ethnicity (r = 0.141), and housing instability (r = 0.125), and negatively correlated with income (r = −0.150) and education (r = −0.079). The multivariable regression model predicting food insecurity was statistically significant, F(6, 2612) = 65.8, p < 0.001, with association directions generally consistent with the network findings. Race did not significantly moderate most individual associations with food insecurity. Race by housing interaction was significant (p = 0.03), indicating that participants who identified as Black or African American with insecure housing were more likely to experience food insecurity. Overall, the findings indicate that food insecurity occupies a prominent position within an interconnected system of social and structural constraints around HIV prevention. Structural barriers to HIV prevention operate as a mutually reinforcing system rather than isolated challenges. Addressing highly connected constraints, particularly food insecurity, housing instability, and barriers to care, through place-based, community-engaged strategies may yield compounded benefits across the prevention continuum. These findings highlight potential priorities for structural intervention in Ending the HIV Epidemic (EHE) priority jurisdictions. Full article

Unlike single-converter grid-connected systems and multi-converter grid-forming (GFM) systems operating in islanded mode, grid-connected multi-converter systems comprising parallel grid-following (GFL) and GFM converters exhibit more complex internal interactions. The negative damping of GFL converters and the low-frequency inertia of GFM converters can reinforce each other, increasing the risk of wideband oscillations. Conventional impedance models do not fully account for frequency-coupling effects among converters, which can lead to impedance-model mismatch and invalidate the Nyquist criterion. Moreover, the high order of the transfer functions of multi-converter systems makes frequency sweeps difficult. Conversely, time-domain state-space models neglect the dynamics of individual control loops, resulting in inaccurate modeling and distorted parameter-sensitivity results. This paper develops a heterogeneous small-signal model that captures the full dynamics of GFM and GFL converters and uses an eigenvalue-sensitivity criterion to reveal their behavior under coupled parameters. On this basis, the effects of GFM inertia and damping on GFL variables, as well as the effect of phase-locked loop (PLL) bandwidth on the eigenvalues of the GFM system, are investigated. The proposed model and associated stability analysis provide a basis for assessing the stability of such systems and optimizing system parameters. Finally, simulations verify the conclusions. Full article

Background/Objectives: Acquired brain injury (ABI) can disturb sexual regulation, but the literature does not support a single lesion-to-behavior relationship. This critical narrative review evaluates hypersexuality, sexual disinhibition, and rare acquired paraphilic manifestations after traumatic brain injury (TBI) and stroke, and asks how sparse, heterogeneous evidence can inform proportionate clinical care. Methods: PubMed/MEDLINE, Scopus, and Web of Science were searched up to 6 August 2026. Two reviewers independently screened records and full texts. Evidence appraisal considered methodological quality, directness, and competing explanations. Thirteen English-language case-based publications were assessed, with neurological observations distinguished from pharmacological comparators. Results: Sexual dysfunction is common after ABI, whereas dysregulated sexual behavior is less frequent and poorly quantified. TBI primarily supports a distributed vulnerability model involving diffuse axonal injury and disruption of frontal regulatory connections. Stroke can nominate strategic candidate nodes, but lesion-network effects and clinical context remain decisive. Clinical observations associate inappropriate sexual behavior with broader behavioral difficulties, without establishing a uniform syndrome. Recent guidelines support individualized sexuality care, while contemporary imaging studies strengthen network plausibility without directly establishing sexual-dysregulation mechanisms. Conclusions: A phenotype-first framework separates dysfunction from dysregulation and distinguishes direct clinical evidence from mechanistic extrapolation. Assessment should establish what changed and whether reversible contributors explain the behavior before assigning a persistent phenotype. Management should match the dominant clinical problem, preserve consensual intimacy, and use the least restrictive targeted strategy. Explicit monitoring should determine whether benefit justifies continued treatment. Case-based evidence and language-restricted selection limit generalizability; prospective studies require standardized phenotypes and repeated observation across settings. Full article

The development of low-altitude passenger transport and emerging short-haul air services has made inter-county short-distance routes an important subject for regional aviation market research and preliminary planning. However, piloted eVTOL and low-altitude short-haul passenger services remain at an early stage, lacking continuous and stable historical operational data for supervised modelling. Moreover, unobserved county-level routes cannot be simply regarded as having no market potential. This study formulates county-level candidate route identification as a large-scale priority ranking problem under sparse proxy labels and develops a multi-relational graph ranking framework. The framework integrates county attributes, mobility, transport impedance, high-speed rail substitution conditions, and estimated air travel time variables through multiple relational graphs, and employs an MR-GAT ranking model to learn relative priorities among candidate routes using a pairwise ranking objective. Observed civil aviation route labels and flight frequencies are used as primary supervision signals, while airport catchment weak labels are introduced for auxiliary analysis. Experiments conducted over 240,350 county-level candidate ODs show that, across ten random seeds, the MR-GAT model achieves a mean internal Top-1000 recall of 16.33%, compared with 7.55% for XGBoost and 2.00% for the gravity-based heuristic. Paired bootstrap analysis further supports the higher internal top-ranked retrieval performance of MR-GAT over XGBoost. Ten-seed relational ablation shows relatively small differences among individual relation-removal variants, indicating that no single relational graph dominates the ranking performance under the current evaluation setting. Sensitivity analysis further shows that the resulting ranking is highly robust to uniform additions of up to 90 min to the estimated air travel time. Analysis of the resulting candidate set indicates that high-ranking ODs are typically associated with stronger inter-county interactions, higher ground-transport impedance, and limited direct high-speed rail connectivity. The framework therefore provides an analytical screening tool for reducing a large candidate space to a smaller set of links for subsequent market and operational feasibility assessment. Full article

Transposon integration is influenced by genomic context, but the contribution of three-dimensional genome organization to transposon mobility remains poorly understood. Here, we developed T7-Mediated Unique-barcode Recovery sequencing (TMUR-seq), combining T7-based junction enrichment with uniquely barcoded Sleeping Beauty (SB) transposons to track secondary transposition events and their relationships to individual donor sites. Using this approach, we characterized genome-wide secondary SB transposition in human cells and analyzed the effects of genomic distance, donor-specific directionality, and chromatin organization on target selection. Secondary transposition was strongly dependent on linear genomic distance but showed pronounced donor-specific directional asymmetries, including recurrent mirror-image patterns at neighboring donor sites. Secondary integratiotes also showed enrichment for Hi-C contacts with their donor loci within approximately 50 kb after accounting for genomic distance, consistent with a contribution of local three-dimensional chromatin organization to target selection. An extended chromosome 2 donor cluster further illustrated how donor distribution, chromatin state, domain organization, and local three-dimensional connectivity can coincide with highly asymmetric integration patterns and regions of pronounced integration depletion. Together, these findings indicate that secondary SB transposition is not entirely random and is shaped by the combined effects of genomic distance and local genomic context. TMUR-seq provides a framework for tracking donor–recipient relationships and investigating the genomic determinants of transposon mobility. Full article

Bridge infrastructure worldwide is under increasing pressure from ageing assets, growing traffic demand, environmental deterioration, and the need for more effective lifecycle management. Although bridge-monitoring technologies have developed rapidly, much of the existing research has focused on individual sensing techniques, while the integration of heterogeneous information across different spatial scales has received comparatively less attention. This review takes an information-centric perspective on intelligent bridge monitoring and focuses on three representative technologies that provide complementary information at the material, structural, and network scales: Ground-Penetrating Radar (GPR) for assessing material condition, distributed optical-fibre sensing (DOFS) for monitoring structural response, and satellite remote sensing for providing network-scale information. Instead of comparing these technologies solely for their sensing principles, the review considers their complementary roles in bridge engineering and proposes a Material–Structural–Network (M–S–N) framework to organise monitoring information across scales. Recent developments in multi-source information fusion, AI-based interpretation, connected monitoring systems, autonomous monitoring, and self-evolving Digital Twins are also reviewed. Together, these advances indicate a shift from simply collecting monitoring data towards integrating information, extracting engineering knowledge, and supporting intelligent decisions. Based on this perspective, a Multi-Scale Integration Framework is proposed to illustrate how observations at different scales can be combined to provide a more complete understanding of bridge condition, structural performance, and infrastructure-network context. Future bridge monitoring should therefore move beyond isolated sensing and data collection towards multi-scale information generation and integration, supporting predictive maintenance, resilient asset management, and intelligent lifecycle decision-making across bridge networks. Full article