Search Results (2,324)

Weight stigma often appears in research as individual prejudice and its interpersonal harms, yet women’s accounts show that devaluation also persists through routine, socially organized evaluation. This article examines weight stigma through visibility by treating looking as a patterned interpretive practice with moral and relational consequences. We conducted three in-person focus groups with women in Chile who self-identified as fat (N = 20) in Santiago, Coquimbo, and Valdivia between April and September 2024 and analyzed the data using reflexive thematic analysis. Participants described visibility as a shifting landscape of evaluative looks that travel across everyday domains while retaining recognizable moral logics. We develop a typology of four gazes: an expulsive/invisibilizing gaze that denies fit and belonging; a disciplinary gaze that frames correction as care and produces self-surveillance; a derisive gaze that punishes through contempt; and a brave gaze that offers conditional recognition by praising ordinary presence as exceptional. Women located these gazes in ordinary interactions and in infrastructures that stabilize evaluation, including public seating norms, retail sizing routines, clinical measurement, mirrors, and photographic and digital practices. These findings suggest that reducing weight stigma requires changing not only attitudes but also the scripts and material arrangements that organize visibility and make evaluation routine. Full article

In response to the growing need for accurate forecasting of electricity generation from PV installations, which is crucial both for enhancing self-consumption and for balancing the power grid, this study presents a comparative analysis of selected machine learning models. The research focuses on the XGBoost algorithm and LSTM neural networks, applied to predict PV energy production based on meteorological data and historical generation records from four medium-sized PV installations (30–50 kWp) located in Poland. Meteorological data were retrieved from open sources and combined with actual production measurements to build the training dataset. This paper discusses the challenges posed by these data at the given latitude, as well as issues related to processing data from newly launched installations. The performance of both approaches was evaluated in short- and medium-term forecasting, with particular attention to prediction accuracy, robustness to noisy data, and the ability to capture nonlinear relationships. Full article

Challenges caused by climate change increase concern for achieving global sustainability. Although citizen awareness is increasing, ensuring sustainability in key sectors like construction is necessary. Achieving sustainability requires essential actions that, however, could have a negative impact on economic performance. Studies on renewable energy installations tend to prioritize performance or sustainability, rather than facing the strategic challenge to find the balance between both. The present work fits this framework through managing renewable energy operations in a construction materials factory of Grupo Puma, located in Spain. The objective of the proposed methodology is to identify key performance indicators (KPIs) for the FV installation and to simulate energy flows using a validated model within a digital simulation environment. This study proposes a trinomial of KPIs—self-consumption, solar utilization, and avoided CO₂ emissions—as more stable indicators than conventional metrics. The Pareto front analysis shows that self-consumption can be increased by up to 20% with only an approximate 10% reduction in solar utilization. This finding offers a clear strategic recommendation: prioritizing higher self-consumption is a viable industrial strategy to enhance Grupo PUMA’s sustainability performance while maintaining acceptable economic efficiency. Full article

The digital nomad economy—the ecosystem in which professional skills are traded through online platforms independent of geographic co-location—dynamically recombines skills into project-based portfolios with absent firm-level hierarchy. Yet it remains shaped by platform taxonomies, interfaces, and ranking/recommendation incentives. This study examines the emergent structure within this setting using the Semantic-Structural Systems Analysis (S²SA) framework, which integrates LLM-assisted skill extraction, transformer-based semantic embeddings, and multi-layer network analysis. We analyze a dual-source dataset comprising approximately 50,000 public Upwork profiles from a top-rated/high-earning segment (January–March 2023) and 2.0 million Reddit posts and comments (2018–2023) from remote-work and digital-nomad communities. The resulting skill network exhibits a pronounced core–periphery organization and modular “skill ecotopes” corresponding to coherent functional specializations. In predictive models of skill-level effective hourly rates, semantic brokerage and semantic diversity function as robust predictors of higher rates, significantly outperforming popularity-only baselines. Longitudinal discourse analyses surrounding the COVID-19 pandemic and the generative AI shock reveal rapid attentional shifts followed by the emergence and recombination of new skill clusters. We interpret these results as evidence consistent with constrained self-organization in platform-mediated labor markets. To support replication, prompts, parameters, and robustness checks are fully reported. Full article

Recently, numerous countries have experienced devastating wildfires, leading to significant destruction and loss of life. These catastrophic events highlight the shortcomings in current building regulations and testing methods. There is a pressing need for a more profound understanding of the characteristics and behaviour of large outdoor fires to address these inadequacies effectively. Wildfires can spread to structures located at the wildland–urban interface, leading to further fire propagation from one building to another. In this study, the Fire Dynamics Simulator (FDS) model was validated using experimental data from the National Institute of Standards and Technology (NIST). The experiment consisted of a target wall and a small wooden shed containing six wooden cribs as fuel, with a separation distance of 3 m. Both FDS and the experiment proved that 3 m is the safe separation distance. Different shed materials, such as steel, were used, which reduced the total heat release rate by 40% and the flame height by 20%. The effects of wind speed and direction were investigated using two wooden sheds in FDS to observe fire spread between them. The safe separation distance was 3 m for both wind speeds (2 and 5 m/s) in all directions, where the critical temperature was not reached to cause self-ignition of the second shed, except in the north direction (inward) at a speed of 5 m/s. When the separation distance increased to 3.5 m, the average heat flux at the other shed reduced to 3.18 kW/m², which did not cause self-ignition. Therefore, the safe separation distance between two structures for a wind speed of 5 m/s should be 3.5 m to mitigate the spread of fire based on the shed dimensions and the fire source load. Full article

Clouds are a key factor affecting solar radiation, and their dynamic variations directly cause uncertainty and fluctuations in photovoltaic (PV) power output. To improve PV power prediction accuracy, this paper proposes an enhanced short-term photovoltaic power forecasting approach based on a hybrid neural network architecture using features extracted from satellite cloud images. First, a dual-layer image fusion method is developed for satellite cloud images from different wavelengths and spectral bands, effectively improving fusion accuracy. Second, texture descriptors derived from the Gray-Level Co-occurrence Matrix and multiscale information obtained via the wavelet transform are employed for feature extraction from fused images. Combined with a residual network (ResNet), an optical flow method, as well as an LSTM-based temporal modeling module, multidimensional features of the predicted cloud images are obtained. An improved Bayesian optimization (IBO) algorithm is then employed to derive the optimal fused features, thereby improving the matching between cloud image features and PV power. Third, an enhanced hybrid architecture integrating a convolutional neural network and long short-term memory units with a multi-head self-attention mechanism is developed. Numerical weather prediction (NWP) meteorological features are incorporated, and a tilted irradiance model is introduced to calculate the solar irradiance received by PV modules for use in near-term photovoltaic power forecasting. Finally, measurements collected at a photovoltaic power plant located in Hebei Province are used to validate the proposed method. The results show that, relative to the SA-CNN-MSA-LSTM and BO-CNN-LSTM models, the developed approach lowers the RMSE to an extent of 22.56% and 4.32%, while decreasing the MAE by 24.84% and 5.91%, respectively. Overall, the proposed model accurately captures the characteristics of predicted cloud images and effectively improves PV power prediction accuracy. Full article

Although underwater gliders are highly energy-efficient platforms capable of long-duration and large-scale ocean observation, their lack of self-propulsion requires external assistance for recovery upon mission completion. In harsh and dynamic marine environments, reliably detecting the glider and accurately estimating its three-dimensional position are critical to ensuring the recovery operations are safe and efficient. This paper proposes a perception framework based on deep learning to detect underwater glider hulls and estimate their three-dimensional relative positions using camera–sonar multi-sensor fusion. This approach integrates a hierarchical convolutional neural network (CNN) vision encoder and a transformer-based architecture to estimate the glider’s spatial location and heading direction simultaneously. The hierarchical CNN encoder extracts multi-level, semantically rich visual features, thereby improving robustness to visual degradation and environmental disturbances common in underwater settings. Additionally, the transformer incorporates a variable mixture-of-experts (vMoE) mechanism that adaptively allocates expert networks across layers, enhancing representational capacity while maintaining computational efficiency. The resulting pose estimates enable precise, collision-free ROV navigation for automated recovery and onboard sensor inspection tasks. Experimental results, including ablation studies, validate the effectiveness of the proposed components and demonstrate their contributions to accurate glider hull detection and three-dimensional localization. Overall, the proposed framework provides a scalable, reliable perception solution that allows for the safe, autonomous recovery of underwater gliders with an ROV in realistic ocean environments. Full article

The aim of this study was to examine the factors associated with COVID-19-related fear in older adults from Kazakhstan, and to explore its associations with sociodemographic characteristics, health status and multiple domains of quality of life in a regional context. A total of 445 individuals aged 60 and above from both urban and rural locations in Kazakhstan participated in this cross-sectional study. To assess the quality of life among older people we used the OPQoL (Older People’s Quality of Life) Scale. Further variables were evaluated: sociodemographic (age, gender, education level, marital status, and place of residence); health-related (self-reported overall health, hypertension, diabetes, cerebrovascular disease, cardiovascular disease, and chronic obstructive pulmonary disease (COPD); and COVID-19-related fear variable. Female gender (OR = 2.344; p = 0.001), present hypertension (OR = 2.106; p = 0.008), the specialized secondary educational level (OR = 2.321; p = 0.012) and at the border of significance university educational level (OR = 1.832; p = 0.051) were variables significantly associated with the COVID-19-related fear in older adults. For individuals with reported COVID-19-related fear, advanced age was significantly negatively associated with leisure and activities domain (B = −0.747; p = 0.020) of OPQoL; better self-reported overall health was significantly positively associated with life overall domain (B = 0.691; p < 0.001), health domain (B = 1.320; p < 0.001), psychological and emotional well-being domain (B = 0.395; p = 0.001), home and neighborhood domain (B = 0.249; p = 0.036), independence, control over life and freedom domain (B = 1.082; p < 0.001), financial circumstances domain (B = 1.132; p < 0.001), and leisure and activities domain (B = 0.556; p = 0.026) of OPQoL; present hypertension was significantly negatively associated with health domain (B = −0.888; p = 0.004) of OPQoL; present cardiovascular disease was significantly negatively associated with life overall domain (B = −0.588; p = 0.027), health domain (B = −0.967; p = 0.009), and independence, control over life and freedom domain (B = −0.542; p = 0.039) of OPQoL; being single was significantly negatively associated with life overall domain (B = −0.481; p = 0.033), social relations domain (B = −0.671; p = 0.014) and financial circumstances domain (B = −0.694; p = 0.036) of OPQoL; and urban place of residency was significantly positively associated with health domain (B = 0.735; p = 0.011) and psychological and emotional well-being domain (B = 0.483; p = 0.010) of OPQoL. Our findings pointed that numerous variables were associated with the COVID-19-related fear and quality of life domains regarding COVID-19-related fear in older adults from Kazakhstan during pandemics. Full article

Most existing studies on the cost competitiveness of self-consumption PV systems fail to jointly consider key technical, economic, and user-specific factors—such as the share of PV electricity self-consumed, energy exported or imported from the grid, and time-of-use electricity pricing—all of which significantly influence investment viability. To address these gaps, this study introduces a novel method based on a new model to calculate the unit cost of electricity consumption from the user’s perspective (C_EC, in €·kWh⁻¹). The array DC power rating is then optimally sized—assuming ideal orientation and tilt—to minimize C_EC. A self-consumption PV system is considered cost-competitive when the annualized minimized C_EC is lower than the applicable regulated electricity tariff. Colombia is selected as a case study to demonstrate the novel method due to the limited deployment and analysis of self-consumption PV systems in the country. The method is applied across residential, commercial, and industrial sectors in various locations. The resulting annualized minimized C_EC values (0.35–8.85 c€/kWh) are consistently below the corresponding regulated tariffs, demonstrating the economic viability of properly sized PV systems. The method’s adaptability to international tariff frameworks makes it a valuable tool for global application and a useful resource for policymakers and stakeholders. Full article

Earthfill dams located in seismic regions are highly vulnerable to earthquake-induced deformations, particularly when founded on soft alluvial soils. This study presents a comparative numerical investigation of earthfill dams with asphalt and clay cores subjected to seismic loading. A 20 m-high zoned embankment dam founded on soft alluvial deposits was modeled in PLAXIS2D and subjected to four earthquake records. The dynamic responses at the crest and downstream slope were evaluated in terms of acceleration, settlement, and lateral displacement. The results indicate that while lateral displacements are nearly identical for both core types, dams with clay cores experience significantly higher seismic settlements, reaching up to 35% more than those with asphalt cores under strong earthquake loading. Overall, the asphalt core demonstrated enhanced resilience, exhibiting reduced settlement due to its higher stiffness, viscoelastic behavior, and inherent capacity for self-healing following seismic loading. Full article

Aimed at the problems of severe layover, interferometric phase aliasing and phase jumps caused by dense urban features, which lead to difficulties in phase unwrapping and insufficient automation and intelligence in building areas under complex scenes, this paper proposes a phase reconstruction and unwrapping method for interferometric synthetic aperture radar (InSAR) building layover areas in complex scenarios integrated with YOLOv11. Based on a self-constructed dedicated dataset, the YOLOv11 object detection network is trained to identify and locate building layover areas in synthetic aperture radar (SAR) images and extract their original interferometric phases. On this basis, by integrating the building facade interferometry model and the interferometric phase gradient model, regions dominated by facade scattering are effectively identified, and their interferometric phases are reconstructed to reduce scattering interference from non-relevant areas. Finally, the reconstructed phase is unwrapped using a quality-guided phase unwrapping method. Experimental results demonstrate that the proposed method can automatically and intelligently achieve phase unwrapping in building areas under complex scenes, providing reliable technical support for urban deformation monitoring and 3D reconstruction. Full article

Background/Objectives: Dominant models of successful aging emphasize health, autonomy, and active engagement, often excluding older adults belonging to vulnerable groups, such as those living in long-term care facilities (LTCFs). This study aims to address this limitation by exploring how LTCF residents define “aging well” and by examining whether they perceive themselves as aging well according to their own criteria. Methods: A qualitative design was employed using semi-structured interviews with 30 residents aged 67–95 living in three long-term care facilities located in Barcelona, Spain. Interview transcripts were analyzed using inductive thematic analysis. Results: Five core themes emerged in the participants’ definitions of aging well: health, attitude, social ties, security, and activities. Health was the most frequently mentioned domain but was conceptualized in undemanding terms, focusing on basic autonomy and cognitive functioning. Psychological attitudes and meaningful social relationships were also key, alongside contextual factors, such as security and access to activities. Two-thirds of the participants perceived themselves as aging well, with justifications closely aligned with their personal definitions; negative self-perceptions were mainly associated with poor health, loss of autonomy, or loneliness. Conclusions: The findings suggest that, in contrast with academic definitions, LTCF residents define aging well in a broader, more context-sensitive manner, which allows them to view themselves positively despite their limitations. Person-centered care environments may play a crucial role in supporting aging well in institutional settings. Full article

We present the observations and the results of our experience from many hours of constructing, assembling, handling, and interacting with our functional reconstruction models of the Antikythera Mechanism. The parts were constructed and the models were assembled by applying a strict Constructional Protocol for a Research Grade functional reconstruction, after a careful study of the Personal Constructional Characteristics/Design Style of the (unknown today) ancient craftsman, retracted from the mechanical parts of the Mechanism’s fragments. During the extensive use of our models, it was concluded that two important and mandatory indicators are missing from all current reconstructions of the Mechanism. The two indicators are necessary for the Antikythera Mechanism to be considered as a complete and self-contained operational time-measuring device which provided direct astronomical and calendar information without additional calculations. The two operations related to the preserved remains were located on gear b1 and its lost Cover Disc. The reconstruction of those missing parts was done according to the Constructional Protocol. The extensive analysis of the Antikythera Mechanism’s operations leads to the understanding of the Mechanism as a luni-(solar) time-measuring device, as opposed to the notion that it was a mechanical planetarium presenting the hypothesized planetary motions and positions. Full article

We present the case of a 25-year-old male who attended a dermatological online consultation due to a whiplash-shaped, pruritic rash. The lesions in the form of well-demarcated linear erythematous papules, located mainly on the trunk and arms, had first appeared four days prior to the consultation. Chronic disease history was negative and similar symptoms never appeared previously. After reviewing the clinical images and excluding dermatographism, flagellate dermatitis was suspected. The diagnosis was subsequently confirmed when the patient reported having consumed undercooked shiitake mushrooms two days prior to the onset of the lesions. Topical corticosteroids and oral antihistamines were recommended, and the patient was informed about the necessity of high-temperature preparation of shiitake mushrooms in the future. Flagellate dermatitis is a rare entity speculated to be a hypersensitivity reaction to lentinan, a heat-labile polysaccharide found in shiitake mushrooms (Lentinus edodes). Symptoms include characteristic papular or vesicular lesions erupting in a linear pattern resembling whiplash marks, usually on the trunk and extremities. While the condition is self-limiting, the awareness of its manifestation is important in order to prevent unnecessary biopsies. Patients should be educated to avoid further exposure to lentinan, as instances of severe reactions following repeated contact have been described. Full article

Background: CrossFit is a high-intensity training modality experiencing global growth, but its injury risk profile remains debated. Existing epidemiological studies show a significant geographical bias, with a complete lack of data from North Africa, including Libya. To the best of our knowledge, this study provides the first epidemiological data on CrossFit injuries in Libya, addressing this geographical gap. This study aimed to determine the prevalence, characteristics, and associated risk factors of musculoskeletal injuries among CrossFit athletes in Tripoli, Libya. Study Design: This descriptive, cross-sectional study utilized a convenience sample of CrossFit athletes. Data were collected via a self-administered, paper-based questionnaire adapted from validated epidemiological surveys. Methods: A total of 137 male CrossFit athletes from four affiliated gyms in Tripoli were enrolled. Participants completed a self-administered questionnaire collecting sociodemographic data, training characteristics, and injury history based on a time-loss definition (missing ≥1 training day or seeking medical attention) over a 12-month recall period. Data were analyzed using descriptive statistics. Logistic regression was used to identify injury predictors. Results: The injury prevalence was 40.6%. The shoulder (33.3%) and lumbar spine (25.3%) were the most frequently injured anatomical locations. The primary mechanism of injury was sudden movement (38.6%), and the most common type of injury was tendinopathy (34.5%). The cohort was characterized by relatively young athletes with high training frequency, nearly half of whom had less than six months of training experience. Longer training duration was the only significant independent predictor of injury (OR = 0.136, 95% CI [0.034–0.543] for beginners vs. experienced athletes; p = 0.009), indicating that experienced athletes were at higher risk. Conclusions: Libyan CrossFit athletes experience high injury rates, with longer training duration—not novice status—predicting injury. These findings underscore the urgent need for standardized coaching and gym affiliation in developing fitness markets to mitigate technique-related injuries and ensure safe sport participation. Full article