Search Results (4,817)

Architectural discourse is a specialised language whose key terms shift with context, which complicates empirical claims about meaning. This study addresses this problem by testing whether a rigorously audited, reproducible NLP framework can recover a core theoretical distinction in architectural language, specifically the conceptual versus physical split, using Japanese terms as a focused case. The objective is to evaluate contextual embeddings against static baselines under controlled conditions and to release an end-to-end pipeline that others can rerun exactly. We assemble a ~1.98-million-word corpus spanning architecture, history, philosophy, and theology; train Word2Vec (CBOW, Skip-gram) and a fine-tuned BERT on the same sentences; derive embeddings; and cluster terms with k-means and Agglomerative methods. Internal validity is assessed using the Adjusted Rand Index against a phenomenological gold standard split; external validity is correlated with WordSim-353; robustness is examined through a negative-control relabelling and a definitional audit comparing FULL and CLEAN corpora; seeds, versions, and artefacts are pinned for exact reruns in the archived environment; and identity across different hardware is not claimed. The study finds that BERT cleanly recovers the split with ARI 0.852 (FULL) and 0.718 (CLEAN). BERT and CBOW show no seed variation. Both Word2Vec models hover near chance, but Skip-gram shows instability across seeds. We provide a transparent, reusable methodology, with released assets, that enables falsifiable and scalable claims about architectural semantics. Full article

This study presents a practical framework for the maximal covering location problem (MCLP) under uncertainty. The approach combines possibility theory with chance-constrained programming to represent both imprecision and randomness in demand. Demand is modeled as fuzzy random variables. Using the Zadeh extension principle, both the fuzzy and fuzzy random formulations are transformed into equivalent deterministic mixed-integer programs. Clear linearization steps are provided for the objective function and constraints. Two specifications are examined to reflect different attitudes toward risk. The first specification uses possibility measures, reflecting an optimistic stance, while the second uses necessity measures and represents a conservative approach. Computational experiments conducted in an urban facility context show that increasing the possibility or probability level results in more conservative solutions and a smaller amount of covered demand. In contrast, lower thresholds lead to more exhaustive coverage with greater exposure to uncertainty. In the deterministic scenario, full coverage becomes attainable as the number of facilities increases. Under uncertainty, the models balance coverage with robustness based on the chosen risk tolerance levels. The proposed framework serves as a flexible decision support tool, enabling planners to align facility location choices with their risk tolerance while maintaining tractability with standard optimization solvers. Full article

Within the field of assisted reproductive technologies (ARTs), embryologists regularly face the critical task of identifying embryos with the highest likelihood of implantation and survival. To help aid and standardize this practice, many embryo selection strategies have been developed to give the best chance of pregnancy success. Over the years, there has been a large increase in experimental studies conducted within this area of research. This increase has allowed for the formation of significant and plausible theories of embryo development, especially in cases where the most prominent factors seem identical. These advancements have both expanded the typical process of traditional treatments and have even paved the way for new techniques. The exact combination of all these relevant factors has not been fully elucidated into a single all-encompassing scheme for embryo decision. Morphological, genetic, and developmental indicators are well-studied individually, but the exact methods that should be prioritized in each scenario may change with respect to an individual patient. Deciding whether factors like age, egg quality, lifestyle choices, or previous medical history should alter methods of embryo ranking can result in conflict, especially in the case where a choice is being made between two similar embryos. This article reviews the conventional methods along with emerging technologies that provide the tools for embryologists to evaluate and rank embryos with high implantation potential (HIP). By showcasing these methods, including their respective benefits and drawbacks, this article provides information to allow clinicians to make effective decisions by integrating multiple approaches to embryo selection. Full article

To address the economic and reliability challenges of high-penetration renewable energy integration in electricity-heat-hydrogen integrated energy systems and support the dual-carbon strategy, this paper proposes an optimal dispatch method integrating Information Gap Decision Theory (IGDT) and Fuzzy Chance-Constrained Programming (FCCP). An IES model coupling multiple energy components was constructed to exploit multi-energy complementarity. A stepped carbon trading mechanism was introduced to quantify emission costs. For interval uncertainties in renewable generation, IGDT-based robust and opportunistic dispatch models were established; for fuzzy load uncertainties, FCCP transformed them into deterministic equivalents, forming a dual-layer “IGDT-FCCP” uncertainty handling framework. Simulation using CPLEX demonstrated that the proposed model dynamically adjusts uncertainty tolerance and confidence levels, effectively balancing economy, robustness, and low-carbon performance under complex uncertainties: reducing total costs by 12.7%, cutting carbon emissions by 28.1%, and lowering renewable curtailment to 1.8%. This study provides an advanced decision-making paradigm for low-carbon resilient IES. Full article

Introduction: Rheumatic diseases, including spondyloarthritis, systemic lupus erythematosus, Takayasu’s nonspecific aortoarteritis, Behcet’s disease, and Kawasaki disease, are more prevalent among Asian populations. The indigenous Sakha people, who live in the harsh conditions of the North and the Arctic regions, exhibit a unique pattern of health issues. AIM: The objective of the study is to characterize the ethnic characteristics of juvenile idiopathic arthritis (JIA) among children from the indigenous population of the Republic of Sakha (Yakutia) and compare them with Caucasians (Russians) living in the same region. This comparison aims to inform the development of tailored diagnostic and treatment strategies. Methods: The comprehensive, single-center, retrospective cohort study included medical data of all Sakha (n = 168) and Russian ethnic patients (n = 48) with JIA who were examined and treated at the Pediatric Center’s Cardiorheumatology Department at the Republican Hospital No. 1–M.E. Nikolaev National Center of Medicine—between 2016 and 2023. The ethnicity was self-reported. The standard clinical procedures and laboratory assessments, as well as the current treatment regimen, were thoroughly reviewed. Results: It was found that children of Sakha descent had a later onset of juvenile idiopathic arthritis (JIA), which was associated with the enthesitis-related arthritis (ERA) categories (51.2% vs. 18.3%, p = 0.0002). They also exhibited higher prevalence of enthesitis (19% vs. 2.0%, p = 0.003), sacroiliitis (23.8% vs. 2.0%, p = 0.0003), and HLA-B27 antigen positivity (46.3% vs. 14.6%, p = 0.00005). The Sakha population exhibited a notably higher prevalence (41.7%) of ERA, compared to the Russian population (33.3%; p = 0.0003), and they initiated biologic therapy at a later stage. However, remission rates were lower among Sakha children (29.2%) than among Russian children (72.2%, p = 0.002), as was their likelihood of achieving remission (Log-Rank test, p = 0.005), regardless of the JIA categories (p = 0.008). Sakha children had a 64.4% reduced chance of achieving remission on the first bDMARD, compared to Russian children (HR = 0.36, 95% CI: 0.18–0.71, p = 0.004). Conclusions: Distinct variations in the progression and treatment outcomes of JIA were observed between Sakha children and Caucasians. A tailored approach to the care of JIA patients is essential, considering their ethnic background. Full article

Hydroponic farming offers sustainability benefits, but its microbial safety remains a concern, particularly regarding antimicrobial resistance (AMR) transmission. This study evaluated the potential for conjugative plasmid transfer of multidrug-resistant bacteria in hydroponic systems, using Salmonella Saintpaul B23 as a donor and various Escherichia coli strains and a self-isolated Salmonella strain from a hydroponic system as recipients. The tested bacteria are human enteric bacteria and may have a chance of being introduced into hydroponic systems. The transconjugation assay was conducted in hydroponic solutions and on different hydroponic components. Results revealed that hydroponic solutions and plant substrates could support significant transconjugation (>4 log CFU transconjugants detected in per mL hydroponic solution and >4 log CFU transconjugants detected in per g plant substrates), while facility surfaces showed minimal transfer (<1 log CFU transconjugants detected on per cm² surface). UV irradiation reduced plasmid transfer rates significantly (p < 0.05), suggesting its potential as a mitigation strategy, though proper implementation is critical. Antibiotic residues at sub-minimum inhibitory concentrations exhibited varying effects on AMR propagation, with gentamicin and chloramphenicol unexpectedly reducing transconjugants. These findings highlight the complex dynamics of AMR transmission in hydroponics and underscore the importance of monitoring, UV application, and cautious use of recycled waste to ensure microbial safety and mitigate AMR risks in agricultural production. Full article

Obesity is a significant risk factor for cardiovascular diseases. Although previous studies have shown uncertainty about its role in aortic dissection (AD), our clinical observations showed that most younger patients with acute AD have a significantly higher body mass index. The underlying reasons are yet to be investigated. Recent studies have suggested that obesity is linked to vascular pathophysiology, including endothelial injury, medial remodeling and deficiency, perivascular adipose tissue dysfunction, and systemic dysfunction. Understanding the association between obesity and acute AD can aid in recognizing high-risk populations, providing an earlier chance of diagnosis and intervention, and improving clinical outcomes for acute AD in young obese patients. This review analyzes and integrates current data to explain the potential role of obesity in acute AD pathogenesis. Full article

Given the complex risk factors associated with youth offending, a comprehensive approach is needed to support the reintegration of incarcerated youth. Canine-assisted interventions (CAIs), involving structured, facilitator-guided programs with dogs, have emerged as a strategy to promote human well-being while sometimes attending to animal wellness. This scoping review, conducted following the Joanna Briggs Institute methodology, examines the characteristics and benefits of CAIs for youth aged 12–17 involved in the criminal justice system. This review included studies published in English through 2024, focusing exclusively on dog-based interventions. Studies were sourced from databases and grey literature between 1998 and 2020. This review maps program designs, objectives, participant profiles, practitioner qualifications, dog roles, and reported outcomes for the youth participants and dogs. Findings reveal that some studies reported improved participant behavioural, psychological, and social outcomes, while few found no significant differences or noted symptom worsening. Some studies noted that training dogs in a CAI may boost their chances of adoption. Gaps include non-standardized terminology, need for more research, inadequate handler training, and insufficient focus on animal welfare. The study concludes that standardized protocols, enhanced handler training, and rigorous program evaluation are essential for ethical and effective CAI implementation that contributes to the well-being and successful reintegration of youth following incarceration. Full article

Exclusive residential developments have drawn growing attention in South African cities, where urbanisation and socioeconomic disparities continue to reshape the built environment. This study examines the underlying drivers of their proliferation and presents a taxonomy of the key forces influencing their growth. The aim is to present results of a study that sought to examine the driving forces behind the growth of exclusive residential developments. Drawing from a literature review and a quantitative inquiry approach, primary data was also collected from 109 built environment professionals. Descriptive and inferential statistical methods, particularly exploratory factor analysis (EFA), were employed to enhance the analysis. The descriptive assessment, utilising the mean score (MS) ranking technique, revealed that one of the primary factors influencing the development of exclusive residential communities was the perception among prospective residents that these environments offer enhanced safety and security. Additionally, there is a good chance that these developments may increase in value. Furthermore, the EFA revealed that the underlying grouped factors for exclusive development were ‘free market capitalism’; ‘safety and security’; ‘local demand’; ‘public–private partnership (PPP)’; ‘affordability’; and ‘profit seeking’. These findings suggest that if housing costs rise, the average citizen may not be able to afford them due to the emphasis on maximising profits over affordability. Safety and security precautions can create a sense of exclusivity and seclusion in these communities, possibly cutting them off from the larger local community and affecting local demand for goods and services outside the community’s borders. Full article

Future Artemis-class missions to Mars will expose astronauts to prolonged space radiation (SR), sleep disruption, and operational demands requiring greater autonomy, placing decision making and executive function at heightened risk. Both SR and sleep fragmentation (SF) independently impair cognition, yet their combined effects remain poorly understood. Using the Associative Recognition Memory and Interference (ARMIT) task, we assessed cognitive performance in male rats exposed to 10 cGy of Galactic Cosmic Ray simulation (GCRsim), SF, or both. Under well-rested conditions, GCRsim-exposed rats exhibited overt deficits in the C.1.2 stage, performing at chance when reinforcement contingencies shifted, consistent with impaired cognitive flexibility. In contrast, high-performing GCRsim-exposed rats that initially performed comparably to Sham s revealed latent deficits following a single night of SF. Specifically, the SF-induced loss of C.1.3 performance was accompanied by perseverative errors (persistently selecting outdated cues despite negative feedback), reflecting impaired attentional control and decision updating. Sham s maintained stable performance after SF. These findings support a two-hit vulnerability model in which SR primes corticostriatal and frontoparietal networks for collapse under subsequent sleep disruption. Operationally, this suggests that astronauts may display either persistent or stress-induced deficits, with both modes threatening mission success. Identifying mechanisms of such vulnerabilities is essential for countermeasure development. Full article

In recent years, monoclonal antibodies targeting key cytokines underlying the occurrence of psoriatic skin lesions and joint involvement, i.e., Tumor Necrosis Factor-alpha (TNF-α), Interleukin 17 (IL-17), Interleukin 12 (IL-12), and Interleukin 23 (IL-23), have become more commonly used in the therapy of psoriasis. Due to the high effectiveness, a favorable safety profile, and growing availability of biological treatment methods, the number of patients receiving chronic monoclonal antibody therapy is increasing each year. However, the factors affecting the effectiveness of biological drugs are not fully recognized. The study aimed at analyzing the clinical profile of patients and non-specific inflammatory markers in terms of the response to the psoriasis treatment with IL-17, IL-23, IL-12/23, and TNF-α inhibitors. The analysis involved 185 patients receiving biological therapy in the Department of Dermatology and Venereology at the Medical University of Lodz, which resulted in a total of 222 treatment cycles (TC). The super-response was defined as 100% reduction in the Psoriasis Area and Severity Index (PASI 100), at week 16 (±4 weeks) of therapy. Our study indicates that the chance of achieving a super-response was higher among younger patients with no psoriatic lesions on palms and soles, not suffering from non-alcoholic fatty liver disease, previously treated with methotrexate, and characterized by a higher level of derived Neutrophil-to-Lymphocyte Ratio (dNLR) at the beginning of treatment. Full article

Individual vocal recognition is essential for social cohesion and survival among conspecifics. In sheep, it facilitates postnatal identification and strengthens the mother–offspring bond. Although vocal individuality has been well-documented in lambs and ewes, little is known about whether rams—typically reared separately in farming systems—exhibit acoustic distinctiveness. This study investigated whether rams express vocal individuality across different emotional contexts and whether their calls convey contextual information. Adult rams’ vocalizations were recorded across five emotionally distinct contexts: physical and visual isolation (morning and evening), auditory exposure to ewes’ bells without visual contact, feed anticipation, and feed denial. Implementing discriminant function analyses and linear mixed models, we assessed individual distinctiveness and contextual variation in acoustic parameters. Rams exhibited vocal individuality ranging from 59% to 80%, with higher distinctiveness in negative contexts compared to positive ones. Vocal distinctiveness persisted across contexts, albeit to a lesser degree, suggesting some degree of acoustic stability. Calls were classified above chance by context, suggesting rams use vocalizations to convey affective states. Formant dispersion and amplitude variation were the most informative raw acoustic parameters under negative from positive contexts. The findings indicate that rams exhibit context-dependent vocal individuality, potentially conveying affective states through vocalizations. Full article

Eye movement is an important tool used to investigate cognition. It also serves as input in human–computer interfaces for assistive technology. It can be measured with camera-based eye tracking and electro-oculography (EOG). EOG does not rely on eye visibility and can be measured even when the eyes are closed. We investigated the feasibility of detecting the gaze direction using EOG while having the eyes closed. A total of 15 participants performed a proprioceptive calibration task with open and closed eyes, while their eye movement was recorded with a camera-based eye tracker and with EOG. The calibration was guided by the participants’ hand motions following a pattern of felt dots on cardboard. Our cross-correlation analysis revealed reliable temporal synchronization between gaze-related signals and the instructed trajectory across all conditions. Statistical comparison tests and equivalence tests demonstrated that EOG tracking was statistically equivalent to the camera-based eye tracker gaze direction during the eyes-open condition. The camera-based eye-tracking glasses do not support tracking with closed eyes. Therefore, we evaluated the EOG-based gaze estimates during the eyes-closed trials by comparing them to the instructed trajectory. The results showed that EOG signals, guided by proprioceptive cues, followed the instructed path and achieved a significantly greater accuracy than shuffled control data, which represented a chance-level performance. This demonstrates the advantage of EOG when camera-based eye tracking is infeasible, and it paves the way for the development of eye-movement input interfaces for blind people, research on eye movement direction when the eyes are closed, and the early detection of diseases. Full article

This paper proposes TreeHelper, an IoT solution that aims to improve authorization and monitoring practices, in order to help authorities act faster and save essential elements of the environment. It is composed of two important parts: a web platform and an edge AI device placed on the routes of tree logging trucks. The web platform is built using Spring Boot for the backend, React for the frontend and PostgreSQL as the database. It allows transporters to request wood transport authorizations in a straight-forward manner, while giving authorities the chance to review and decide upon these requests. The smart monitoring device consists of a Raspberry Pi for processing, a camera for capturing live video, a Coral USB Accelerator in order to accelerate model inference and a SIM7600 4G HAT for communication and GPS data acquisition. The model used is YOLOv11n and it is trained on a custom dataset of tree logging truck images. Model inference is run on the frames of the live camera feed and, if a truck is detected, the frame is sent to a cloud ALPR service in order to extract the license plate number. Then, using the 4G connection, the license plate number is sent to the backend and a check for an associated authorization is performed. If nothing is found, the authorities are alerted through an SMS message containing the license plate number and the GPS coordinates, so they can act accordingly. Edge TPU acceleration approximately doubles TreeHelper’s throughput (from around 5 FPS average to above 10 FPS) and halves its mean inference latency (from around 200 ms average to under 100 ms) compared with CPU-only execution. It also improves p95 latency and lowers CPU temperature. The YOLOv11n model, trained on 1752 images, delivers high validation performance (precision = 0.948; recall = 0.944; strong mAP: mAP50 = 0.967; mAP50-95 = 0.668), allowing for real-time monitoring. Full article