Search Results (5,429)

The use of artificial intelligence (AI) to recognize postures is a promising approach for the prevention of work-related musculoskeletal disorders (WMSDs). The aim was to conduct a systematic review with meta-analysis to assess the performance of work posture recognition systems during occupational activity. The results were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Google Scholar, IEEE Xplore, PubMed/MedLine, and ScienceDirect databases were screened without date restrictions. Two authors independently selected articles and extracted data. Studies were included if they presented a performance analysis of an AI deep learning (DL) or machine learning (ML) method that assessed the WMSD risk associated with working postures. Only peer-reviewed studies written in English including accuracy, precision, specificity, sensitivity, or F1-score values were included. The risk of bias was assessed using the Prediction Model Study Risk of Bias Assessment Tool. Of the 157 unique records, 58 studies were selected. The five performance parameters were investigated and averaged for seven occupational activities, eight posture categories, and the AI methods (ML vs. DL). Statistical analyses showed that DL methods produced better results. The reported systems detected sitting and standing postures with high accuracy. The solutions proposed in Manufacturing and Construction were the most numerous and the most effective on average. The major limitation lies in the wide variety of methods used. This analysis is a valuable source of information for designing new detection systems that are effective, ergonomic, easy to use, and acceptable so that humans remain at the center of the production process as defined by Industry 5.0. Full article

This research investigates the colonnade of Tomb 7 at the UNESCO World Heritage site of the Tombs of the Kings in Paphos, Cyprus. Specifically, a multi-drum column located at the south-east corner of the tomb is examined from both geometric and structural perspectives. Being the only standing element to support the entablature on that side of the tomb, the column is crucial for maintaining the structural stability of the monument. Numerical structural analyses are performed on the column via the finite element method (FEM), supported by close-range recording techniques—particularly terrestrial laser scanning (TLS)—to generate finite element (FE) models. Several modelling strategies capable of converting point cloud data into reliable structural models are developed and compared with the aim of identifying the most effective and cost-efficient approach. Each method is analyzed in detail to evaluate its workflow, assumptions, strengths, and limitations in the context of heritage structures with complex irregular geometries. Linear static and dynamic analyses are performed on five different FE models to assess the column’s mechanical response and to understand how differences in geometric representation affect the structural behaviour. The results indicate that all approaches adequately capture the general structural response. The comparison of the different modelling strategies highlights the trade-offs between geometric accuracy, computational efficiency, and practical usability. These outcomes indicate the potential and the current limitations of exploiting point cloud data for structural analysis and contribute to the development of more robust and accurate scan-to-FEM methodologies for the conservation and assessment of cultural heritage structures. Full article

This paper presents a data-driven modeling and sensorless angle–torque prediction method for a pneumatic soft bending actuator. The actuator contains no embedded angle or torque sensors; instead, only airflow and pressure sensors located in the external control box (standard components in pneumatic systems) are used during operation. The proposed method, and therefore eliminates the need for onboard sensing and detailed valve hysteresis modeling. Based on the ideal gas law, four continuous, monotonic, and single-valued pneumatic state equations were derived and experimentally validated. As a case study, a pneumatic soft actuator was designed to generate high torque for assisting knee and ankle extension. An experimental setup with multiple sensors collected key data on air mass, internal pressure, actuator torque, and bending angle. These additional sensors were used only during dataset generation. A data-driven modeling approach was developed with training neural networks to generate four fitting functions to predict actuator behavior, including equations for angle and torque prediction. An angle-sensorless closed-loop control simulation study, incorporating a PID controller, a proportional valve delay block, and torque prediction, demonstrated the controllability and computational feasibility of the proposed model as well as the actuator’s effectiveness in supporting additional weight during squat-to-stand motion. Full article

Recent advancements in AI have enabled autonomous agents to interact within complex environments, with deliberative BDI (Belief–Desire–Intention) agents standing out for their human-inspired reasoning capabilities. However, defining the initial beliefs that constitute an agent’s cognitive profile remains a significant challenge. This process often relies on manual approaches that limit scalability and validation. This study proposes the Personality–Role–Belief (P–R–B) Model for BDI agents, introducing a novel architecture for generating cognitive profiles applicable to domains such as social simulation and non-player characters (NPCs). The model translates Five-Factor Model (FFM) scores into specific social roles, assigning base beliefs to each. A key contribution is a weighting mechanism designed to resolve conflicts between beliefs when multiple roles coexist. Inspired by Cohen’s effect size conventions, this mechanism establishes an influence hierarchy that quantifies belief strength based on social roles. Consequently, this approach not only enables agents to exhibit coherent behavior consistent with their personality but also establishes a foundation for modeling ethical decision-making through role–trait alignment, thereby facilitating the creation of agents capable of navigating morally complex social contexts. Full article

With the growing global emphasis on space resources, the significance of space detection and surveillance technologies has escalated. Currently, space-based optical surveillance stands as the primary means for acquiring information on space objects. However, constrained by the diffraction limits of space telescopes, distant space objects are typically imaged as point sources. The resulting lack of sufficient spatial resolution renders traditional image-based recognition algorithms ineffective. In contrast, the Bidirectional Reflectance Distribution Function (BRDF) fully characterizes surface light scattering properties through four-dimensional features, significantly outperforming traditional two-dimensional spectral techniques in material identification. Consequently, leveraging BRDF signatures at varying phase angles has emerged as an effective approach for Space Object Identification. In this study, we developed an automated BRDF measurement system to characterize various typical aerospace materials and investigated the BRDF properties of mixed-material surfaces. A material composition ratio prediction model was constructed based on a One-Dimensional Convolutional Neural Network (1D-CNN). This model effectively extracts key features, including local slope variations and global waveform characteristics, from the BRDF curves. Experimental results demonstrate that the model achieves a maximum relative percentage error of 6.21%, implying a prediction accuracy for mixed-material composition ratios consistently exceeding 93.79%. Compared to image classification methods based on remote sensing imagery, the proposed approach offers higher computational efficiency, significantly reduced model complexity and computational cost, and enhanced robustness. This work provides essential data support for material identification by space-based telescopes and establishes an algorithmic and experimental foundation for intelligent space situational awareness systems. Full article

This paper examines the organizational competitiveness and strategic transformation of an elite professional football entity in the Greek Super League during the period 2018–2020, using Panathinaikos as a case study within a comparative framework including Olympiacos, AEK, and PAOK. This period marked a phase of enforced reorientation for Panathinaikos due to UEFA sanctions for overdue debts and the club’s exclusion from European competitions, which resulted in extensive squad renewal and increased reliance on academy-developed players. The aim of the study is to identify the factors shaping Panathinaikos’ strategic position, diagnose the causes of its lagging performance, and suggest directions for strategic repositioning. To this end, a multi-criteria framework based on the Analytic Hierarchy Process (AHP) is employed, integrating qualitative assessments, expert judgements, and quantitative performance indicators through pairwise comparisons, weight calculations, and consistency checks. The analysis is based on a conceptually original model that defines the Football Organization as an integrated system composed of two interdependent subsystems: the Football Club and the Football Team (competitive subsystem). This approach highlights that league standings do not always reflect overall performance dynamics, as they are influenced by both organizational and on-field factors. The findings indicate that Panathinaikos is lagging behind in key areas and that a structural discontinuity between the Club and the Team limits strategic coherence and the ability to create a sustainable competitive advantage. The study concludes with proposals for restructuring and strategic repositioning, while the proposed model functions as a transferable decision-support tool for assessing organizational competitiveness, with broader applicability to complex organizational systems beyond professional football. Full article

Three-dimensional (3D) bioprinting is an advanced additive manufacturing technology that utilizes bioinks composed of living cells and biomaterials to construct tissue-like structures for a wide range of medical applications. This paper reviews key applications, including tissue engineering, organ modeling and printing, drug testing and development, disease modeling, cosmetics and chemical testing, regenerative medicine, and personalized medicine. In parallel, biomimicry of natural plant architectures offers powerful opportunities for innovation in biomedical material design. Among these, the rose stands out for its intricate hierarchical geometry, which provides not only aesthetic appeal but also exceptional mechanical resilience. Incorporating rose-inspired structural elements into 3D-bioprinted medical constructs can significantly enhance mechanical strength, flexibility, and surface adaptability. This review also highlights plant- and rose-inspired approaches in medical applications and outlines the potential of rose-inspired 3D bioprinting to advance the design of functional and biomimetic tissue models. Nature provides a rich source of inspiration for biomimetic design, and translating biological principles into engineering solutions can contribute to sustainable technological development aligned with the Sustainable Development Goals (SDGs). In this regard, roses and other plant systems offer valuable structural and functional inspiration for advancing 3D bioprinting in medical applications. Full article

The physicochemical controls on gold precipitation in orogenic gold deposits remain poorly constrained, with traditional fluid inclusion and isotopic studies often yielding ambiguous results due to overprinting or incomplete records. This study addresses this challenge using chlorite—a sensitive mineral proxy for fluid conditions—as a quantitative sensor in the Jinshan orogenic gold deposit (>200 t Au) of the Jiangnan orogenic belt, South China. Hosted in Neoproterozoic phyllite within NE–NNE-trending ductile–brittle shear zones, Jinshan features auriferous quartz–polymetallic sulfide veins with prominent chlorite alteration. Integrating high-resolution SEM-EPMA analyses of multi-generational chlorite with thermodynamic modeling, we reconstruct the temporal evolution of temperature, oxygen fugacity (fO₂), pH and sulfur fugacity (fS₂) during ore formation. Four paragenetic stages are identified: Stage 1 (ankerite–quartz), Stage 2 (pyrite–arsenopyrite–quartz), Stage 3 (quartz–gold–polymetallic sulfide), and Stage 4 (chlorite–carbonate–quartz). Electron microprobe analysis reveals that the chlorite composition changes from Fe-rich chamosite (Stage 2) to Mg-rich clinochlore (Stage 3) and then to Fe-rich chamosite (Stage 4). Chlorite from Stage 2 (Chl-1) formed metasomatically at low fluid/rock ratios, while Stage 3 and 4 chlorites (Chl-2 and Chl-3) precipitated directly from higher fluid/rock ratio fluids. Chlorite compositions record a critical Stage 2–3 transition involving cooling from ~ 320 °C to ~ 260 °C, reduction (log fO₂ from –33.6 to –39.7), and alkalinization, and sulfur fugacity remained stable within a narrow range (log fS₂ = –13.6 to –8.0), followed in Stage 4 by minor reheating to ~280 °C, re-acidification, and a slight rebound in oxygen fugacity. Thermodynamic simulations reveal that the destabilization of Au(HS)₂^- complexes, primarily driven by the synergistic effects of cooling, pH increase, and decreasing oxygen fugacity, triggered gold precipitation during the main ore stage. Results demonstrate that abrupt cooling coupled with fluid alkalinization and reduction exerted the dominant control on gold precipitation in Jinshan, resolving long-standing debates on ore-forming mechanisms and highlighting chlorite as a robust quantitative sensor for fluid evolution. Full article

Past restoration of hardwood forests prioritized planting of woody vegetation cover, particularly oaks (Quercus spp.). This restoration regime often did not consider other microhabitat components, which failed to restore habitat complexity. Giant cane (Arundinaria gigantea (Walter) Muhl.) was an important microhabitat feature for creating a dense understory structure within the hardwood forest landscape. Many bird species are associated with stands of giant cane (canebrakes) for food, cover, and nesting ground. The decline of canebrakes may reduce nesting and foraging habitat, negatively impacting bird communities. Here, we used a hierarchical multi-species occupancy model to assess how giant cane and its associated overstory forest structure influenced breeding bird occupancy in southern Illinois. Bird surveys were conducted from May to July 2022–2024 at 100 site-years using passive acoustic monitoring. Responses to the vegetation structure (tree density and size) and canebrakes varied among species and nesting guilds (overstory, understory, and ground). Occurrence probabilities of 54% of the bird species increased with the presence of canebrake. We did not find any significant relationships between bird occupancy and vegetation structure and canebrake characteristics. Overall, maintaining a hardwood forest stand with a heterogeneous canopy cover would create variations in light environments, allowing canebrakes to benefit bird species across nesting guilds. Full article

Aerosol–cloud interactions (ACIs) remain a long-standing uncertainty in quantifying cloud microphysical properties, convection, and precipitation. There are fewer investigations into the effects of ACIs on the southwest vortex (a mesoscale circulation with a spatial scale of 300–500 km). Satellite-retrieved MODIS data (2002–2022) reveals a decreasing trend in the June–August (JJA) seasonal mean ice droplet effective radius (DER_Ice) over the Sichuan Basin (SCB) since 2013, corresponding to China’s emission reduction efforts. Concurrently, post-2013 trends exhibit a positive shift in cloud-top height (CTH) and a negative trend in cloud-top pressure (CTP), collectively indicative of intensified convective activity. This contradicts the conventional conclusion that increased anthropogenic emissions reduce droplet effective radius (DER) and intensify convection under constant cloud water content. To address this discrepancy, we simulated the precipitation event caused by the southwest vortex (SWV) during 11–14 August 2020, under distinct initial aerosol loading (clean vs. polluted), using the fully coupled WRF-ACI-Full cloud-resolving model (incorporating sophisticated aerosol parameterizations). Results show that increased aerosols reduce basin-averaged precipitation by 0.54% and updraft speed by 0.37% in the polluted case compared to the clean case, which is negligible. These findings differ from previous studies on ACI-related cloud and precipitation responses. Full article

Background: Although frailty has emerged as an important determinant of outcomes following cardiovascular surgery, the clinical significance of early postoperative physical frailty assessed during the acute recovery phase has not been investigated. Methods: We conducted a single-center retrospective observational study including patients who underwent cardiac or aortic surgery and completed a standardized physical function assessment within 10 days postoperatively. Physical frailty was defined using four objective indicators: Medical Research Council (MRC) sum score, gait speed, Timed Up and Go test, and five-times sit-to-stand test. Frailty was defined as the presence of ≥3 abnormal physical frailty indicators. Clinical outcomes included hospital length of stay (LOS) and postoperative medical complications. Negative binomial regression was used to evaluate factors associated with hospital LOS. Results: Among 441 patients included in the analysis, 308 (69.8%) were classified as frail. Frail patients were older and demonstrated significantly impaired physical performance across all frailty indicators (all p < 0.001). Frailty was associated with longer ICU stay and hospital LOS (both p < 0.001). In multivariable negative binomial regression, postoperative frailty was independently associated with prolonged hospital LOS (incidence rate ratio [IRR] 1.38, 95% CI 1.26–1.51; p < 0.001), after adjustment for age and timing of frailty assessment. Additional adjustment for surgical approach and surgical target did not improve model fit. Postoperative frailty was not significantly associated with the overall incidence of medical complications. Conclusions: Early postoperative physical frailty, assessed during the acute recovery phase, is independently associated with prolonged hospitalization after cardiac and aortic surgery. These findings suggest that early functional vulnerability captures clinically meaningful risk beyond surgical characteristics and may serve as a valuable target for postoperative risk stratification and rehabilitation planning. Full article

Characterizing both the CO₂ distribution and wind dynamics in the Martian mesosphere and lower thermosphere is vital for planetary atmospheric science and mission planning. In this work, we propose a novel dual-channel passive limb-viewing imaging system designed to simultaneously observe partial CO₂ column density and line-of-sight (LOS) wind speed from ultraviolet and visible airglow emissions under dayside and terminator illumination conditions. A dichroic beam splitter separates the ultraviolet and visible channels, ensuring high optical throughput and independent optimization of both subsystems. The ultraviolet channel targets O(¹S) 297.2 nm emission, a well-established Martian limb emission driven by CO₂ photodissociation under solar Lyman-α flux. By applying narrow-band imaging and brightness inversion, this channel provides quantitative constraints on CO₂ column density with a stable and well-defined response function. In the visible channel, we introduce a lens array-based compact static Michelson interferometer optimized for the O(¹S) 557.7 nm green line emission, which has been observed in the Martian dayside limb, providing Doppler wind measurements in the 60–180 km altitude range. Radiative transfer simulations using Mars Climate Database indicate retrieval precisions of ±6~8% for CO₂ column density and better than ±5 m/s for wind speed within the primary emission layer (approximately 60–160 km) under representative dayside limb conditions. This dual-parameter remote sensing concept simultaneously constrains the composition and dynamics of the Martian mesosphere and lower thermosphere region, addressing a long-standing observational gap. The compact and modular design of the system makes it well suited for future Mars orbiter payloads under nominal dayside and terminator observation geometries, providing critical data for validating global circulation models and supporting future entry, descent, and landing system design. Full article

This paper mainly studies the equivariant Hopf bifurcation of a delayed reaction–diffusion predator–prey model with stage structures on a two-dimensional circular domain. Firstly, we calculate the existence of steady-state solutions, and then analyze the existence of Hopf and equivariant Hopf bifurcation for the model according to bifurcation theory. Secondly, we calculate the normal form of the equivariant Hopf bifurcation. Finally, we conduct numerical simulations to verify the conclusion. And through simulation, we obtain a spatially homogeneous periodic solution, and spatially inhomogeneous periodic solution including rotating waves and standing waves on a two-dimensional circular domain, which shows rich dynamic properties on a two-dimensional space. Full article

Efficient and clean separation of residual plastic mulch film is the primary bottleneck hindering its resource-oriented reutilization. Currently, the field faces critical technical challenges, most notably the elusive motion mechanisms of flexible materials and the inherent difficulty of film–impurity separation. To address these issues, this study investigates a drum-type mulch-film impurity-removal unit by modeling the throw-off motion mechanism of the material stream, followed by comprehensive multiphysics simulation and optimization. First, to overcome the simulation hurdles typical of flexible materials, “Meta-particles” and the “Bonding V2” contact model were implemented on the EDEM platform to establish a discrete element method (DEM) framework. The resulting analysis revealed a non-linear transport trajectory and morphological evolution within the drum flow field, characterized by a “wall-adhering–slipping–throwing” sequence. These findings were further quantified through MATLAB-based numerical calculations to determine collision frequency and axial residence behavior. Second, ANSYS modal analysis verified the dynamic stability of the frame structure, confirming that the operating frequency (2.37 Hz) remains well below the first natural frequency (6.77 Hz). Furthermore, Box–Behnken response surface methodology (RSM) was employed to elucidate the coupled effects of key process parameters. The results demonstrated that separation efficiency and impurity-removal mass are predominantly governed by the quadratic terms of the inclination angle and rotational speed, respectively. After multi-objective optimization and engineering refinement, the optimal operating parameters were established: a film length of 220 mm, an inclination angle of 3°, and a drum rotational speed of 25 r/min. Bench tests indicated that, under these optimal conditions, the impurity-removal rate stabilized between 71.5% and 72.4%, satisfying the design requirement (≥70%). By elucidating the drum’s throw-off screening mechanism, this study achieves a coordinated improvement in both impurity-removal mass and separation efficiency, resolving long-standing engineering uncertainties regarding film–impurity trajectories and providing a theoretical foundation for the clean treatment of waste mulch film. Full article

This paper presents a transient performance comparison of a flat-plate solar collector (FPSC) and a sun-tracked parabolic trough collector (PTC) with a double U-tube receiver. Both collectors were modeled using in-house transient mathematical models and validated against experimental data obtained from a dedicated test stand. After validation, annual simulations were conducted for Kraków, Poland, using hourly meteorological data from the PVGIS database. The analysis focused on the long-term thermal and economic performance of both collector types under identical boundary conditions. The electricity demand of the tracking system was included using a constant motor power assumption. A simplified techno-economic evaluation was performed using the Levelized Cost of Heat (LCOH), accounting for investment costs, operating and maintenance expenses, auxiliary electricity consumption, system degradation, and cost escalation over a 20-year lifetime. For a comparable aperture area, the calculated LCOH amounted to 0.096 EUR/kWh for the sun-tracked PTC and 0.041 EUR/kWh for the stationary FPSC. The results indicate that, despite higher thermal performance, the examined PTC configuration is not economically competitive for low-temperature heat production under the assumed cost structure, mainly due to its higher investment cost. Full article