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This article examines whether, and under what conditions, there is room for new mosques in Belgian cities by analyzing how media controversies around mosque projects are assembled. We study a corpus of press articles (2014–2024) using a two-step approach: First, keyword mapping identifies dominant discursive patterns across six themes (mobility, legality, size and visibility, social cohesion and integration, security and extremism, financing). Second, argument coding links lexical signals to public modes of judgment through actor–network theory (ANT) and controversy registers. Applied to five case studies across Flanders, Wallonia, and the Brussels-Capital Region, this framework offers comparative depth. The results show that identity and security controversies frequently outweigh strict urban planning controversies; neutral planning criteria (e.g., traffic congestion, permit compliance) are often recoded as symbolic markers of alterity. Regional contrasts provide nuance to this pattern: in Flanders, politicization through security/identity is salient; in Wallonia, debates emphasize size, form, and spatial integration; in Brussels-Capital, technico-legal compliance intertwines with aesthetic visibility. Media operate as boundary objects that hierarchize registers and amplify controversies. We conclude that mosques are treated less as ordinary urban infrastructure than as contested symbols of belonging and visibility. Moving toward negotiated pluralism requires institutional mechanisms that ensure transparency, equal treatment, local anchoring, and symbolic requalification. Full article

Bone regeneration relies on the coordinated interplay between mechanical and biological cues. Piezoelectric composites, capable of converting mechanical strain into electrical signals, offer a promising approach to stimulate osteogenesis. This study aimed to develop and characterize polycaprolactone (PCL) and barium titanate (BaTiO₃) composite scaffolds fabricated through thermally induced phase separation (TIPS), and to systematically evaluate the effects of polymer concentration and ceramic incorporation on scaffold morphology, porosity, mechanical properties, and cytocompatibility were systematically evaluated. The resulting scaffolds exhibited a highly porous, interconnected architecture, with 9% PCL formulation showing the most uniform morphology and consistent mechanical and biological behavior. Incorporation of BaTiO₃ did not alter pore structure or compromise cytocompatibility but slightly enhanced stiffness and surface uniformity. SEM-based image analysis confirmed homogeneous BaTiO₃ dispersion across all formulations. MTT assays and confocal microscopy demonstrated robust pre-osteoblast adhesion and spreading, particularly on denser composite scaffolds, confirming that the inclusion of BaTiO₃ supports a favorable environment for cell proliferation. Overall, optimizing polymer concentration and ceramic dispersion enables fabrication of structurally coherent, cytocompatible scaffolds. The findings establish structure–property–biology relationships that serve as a baseline for future investigations into the electromechanical behavior of PCL/BaTiO₃ scaffolds and their potential to promote osteogenic differentiation under physiological loading. Full article

Background: Although circular RNAs are increasingly implicated in host responses, their longitudinal behaviors to predict outcomes in severe COVID-19 remain unclear. The purpose of this study is to distinguish the circRNA signature associated with COVID-19 outcome. Method: Public total RNA-seq data from GEO (GSE273149) were used to assess circRNA differences among COVID-19 non-survivors, COVID-19 survivors, and patients with acute respiratory distress syndrome (ARDS) serving as severity-matched disease controls at two timepoints: Early (Day 3) and Late (Days 7 to 10). Differential expression was assessed after quality filtering, with the results reported as significant (FDR < 0.05) or suggestive (0.05–0.10); |log₂FC| ≥ 1 was used as a guide for interpretation. Early and Late effects were combined using a two-timepoint, precision-weighted approach to prioritize time-consistent signals. Results: A distinction between non-survivors and survivors was observed, with nine significant and four suggestive candidates identified in the combined analysis; in addition, some candidates indicated a difference between survivors and ARDS controls. Early and Late effects primarily occurred in the same direction, and several circRNAs that were borderline at one timepoint became significant when the two timepoints were combined. Conclusion: This time-resolved, precision-weighted analysis of public RNA-seq data reveals stable circRNA differences between key clinical groups (patients with severe COVID-19 and those with ARDS), improving detection and interpretability relative to single-timepoint tests and yielding a concise set of candidates suitable for mechanistic follow-up and potential biomarker development. Full article

The East China Sea (ECS) is a globally active region for internal solitary waves (ISWs); however, its overall spatiotemporal distribution remains poorly understood. To address this gap, this study proposes a deep learning method based on multi-source remote sensing imagery (MODIS and SAR) for the intelligent identification and pixel-level segmentation of ISWs in the ECS. We adopted the TransUNet model, which combines the global context-capturing capability of Transformers with the fine-grained segmentation advantages of U-Net to effectively handle the large-scale continuous characteristics of ISWs. The model achieved a Dice coefficient of 71.0% and a precision of 72.7% on the test set, significantly outperforming existing models such as FCN, SegNet, DeepLabV3+, and U-Net. Using this automated framework, multi-source satellite data from 2002 to 2024 were processed to generate the first high-resolution spatiotemporal map of ISWs covering the entire ECS. The map reveals two spatial hotspots: a primary one at the shelf break northeast of Taiwan and a secondary one in the waters southwest of Jeju Island. Furthermore, ISWs exhibit a marked seasonal cycle in both occurrence frequency and properties, peaking in summer and minimizing in winter. This seasonal pattern aligns closely with the physics of internal tide generation via body forcing. By providing the first long-term, high-resolution ISW dataset for the entire ECS, this study demonstrates the potential of deep learning techniques for ISW research in complex marginal seas. Full article

The ecological status of lakes based on ichthyofauna, as defined by the Water Framework Directive, is assessed using intercalibrated methods. However, the methods adopted (in Poland, the Lake Fish Index LFI-EN method, based on results of one-off fishing with multi-mesh gillnets) are labor-intensive and do not allow for frequent repeat testing. Therefore, the concept of a simple model describing changes in the relative number of single traces in the vertical profile (according to the TS target strength distribution) in a lake is presented, as well as an index (the sum of deviations from such a model), enabling quantification of the similarity of TS distributions in lakes with this model. Preliminary analyses were conducted on acoustic data collected in Lake Dejguny. This lake—the condition of which could be estimated based on historical data using the relationships between LFI and the degree of lake eutrophication (expressed by Carlson’s TSI)—was assessed as having a good status in 2006, whereas in 2021, (based on LFI-EN) it had a moderate status. The study tested the TS distribution model, calculated as the arithmetic mean of the relative number of single traces in 2 m-thick layers. It was also shown that the proposed indicator can effectively signal deterioration of ecological status—the sum of the absolute values of the TS distribution deviations in 2021 (moderate status) from the model was more than seven times greater than the sum of the deviations of the distributions from which the model was built (good status). The obtained results confirmed the hypothesis about the possibility of determining a characteristic distribution of single traces in the vertical profile when the lake was classified as being in good condition. Full article

Location estimation is significant in this era of the Internet of Things (IoT). Satellite and cellular signals are often blocked indoors, prompting researchers to explore alternative wireless technologies for indoor positioning. Among these, Wi-Fi Received Signal Strength (RSS) with fingerprinting is dominant in large, multi-floor buildings due to its existing infrastructure, acceptable accuracy, low cost, easy deployment, and scalability. This study aims to systematically search and review the literature on the use of real Wi-Fi RSS fingerprints for indoor localization or positioning in large, multi-floor buildings, in accordance with PRISMA guidelines, to identify current trends, performance, and gaps. Our findings highlight three main public datasets in this fields (covering areas over 10,000 sq.m). Recent trends indicate the widespread adoption of Deep Learning (DL) techniques, particularly Convolutional Neural Networks (CNNs) and Stacked Autoencoders (SAEs). While buildings (in the same vicinity) and their respective floors are accurately identified, the maximum average error remains around 7 m. A notable gap is the lack of public datasets with detailed room or zone information. This review intends to serve as a guide for future researchers looking to improve indoor location estimation in large, multi-floor structures such as universities, hospitals, and malls. Full article

The endogenous money creation paradigm posits that banks generate money through lending, with deposits serving as a byproduct. This study investigates the mechanism driving the “credit–deposit paradox” during Poland’s high-interest-rate environment, introducing innovative methodological approaches to quantify systemic monetary impairment. Using comprehensive monthly data from 2006 to 2024, we employ a mixed-methods framework featuring: (1) Bayesian vector autoregression with Minnesota priors to test dynamic interdependencies; (2) a novel money shortage indicator (MSI) that operationalizes credit–deposit decoupling through three theoretically grounded components; (3) Markov regime-switching analysis to identify persistent monetary stress regimes. Key findings reveal a structural decoupling between deposit growth and credit creation, with robust evidence that exogenous money inflows accumulate as idle deposits rather than stimulating lending. The economy experienced significant periods of money shortage conditions, with the most severe impairment occurring during recent high-stress periods. The analysis confirms the dominance of cost-push inflation from energy and food prices, while monetary factors played a limited role. High interest rates amplified credit demand suppression, creating conditions consistent with endogenous money creation disruption. Methodologically, this study enables three key advances: (1) systematic measurement of monetary transmission breakdowns; (2) empirical identification of structural factors disrupting credit–deposit dynamics; (3) temporal characterization of monetary stress persistence patterns. These contributions advance the endogenous money framework by demonstrating its vulnerability to behavioral, policy-induced, and exogenous disruptions during high-stress periods. Practically, the MSI offers policymakers a real-time diagnostic tool for identifying monetary transmission breakdowns, while the regime analysis informs targeted countercyclical measures. Specific policy recommendations include developing sector-specific liquidity facilities, coordinating fiscal transfers with monetary policy to prevent deposit–loan decoupling, and prioritizing supply-side interventions during cost-push inflation episodes. By integrating post-Keynesian theory with empirical evidence from Poland, this study contributes to understanding money creation mechanisms in highly stressed economic environments. Full article

Phosphate is emerging as an active mediator of oxidative stress and vascular injury in chronic kidney disease (CKD). This emerging pathophysiological framework, referred to as “Phosphatopathy”, describes the systemic syndrome driven by chronic phosphate overload and characterized by oxidative stress, inflammation, endothelial dysfunction, vascular calcification, cellular senescence, and metabolic imbalance. Beyond being a biochemical marker, phosphate overload triggers NOX-derived reactive oxygen species (ROS), activates Wnt/β-catenin and TGF-β signaling, and disrupts the FGF23–Klotho axis, promoting endothelial dysfunction, vascular calcification, and left ventricular hypertrophy (LVH). These pathways converge with systemic inflammation and energy imbalance, contributing to the malnutrition–inflammation–atherosclerosis (MIA) syndrome. Experimental and clinical data reveal that the phosphate/urinary urea nitrogen (P/UUN) ratio is a sensitive biomarker of inorganic phosphate load, while emerging regulators such as microRNA-125b and calciprotein particles integrate phosphate-driven oxidative and inflammatory responses. Therapeutic strategies targeting phosphate burden—rather than serum phosphate alone—include dietary restriction of inorganic phosphate, non-calcium binders, magnesium and zinc supplementation, and activation of important pathways related to the activation of antioxidant defense such as AMP-activated protein kinase (AMPK) and SIRT1. This integrative framework redefines phosphate as a modifiable upstream trigger of oxidative and metabolic stress in CKD. Controlling phosphate load and redox imbalance emerges as a convergent strategy to prevent vascular calcification, improve arterial stiffness, and reduce cardiovascular risk through personalized, mechanism-based interventions. Full article

Inappropriate use of antibiotics can stimulate antimicrobial resistance, since bacteria are capable of circumventing pharmacological action through various resistance mechanisms. Recently, during the COVID-19 pandemic, there has been an increase in the use of antimicrobials. This is an analytical, quantitative, and retrospective study on bacterial resistance and mortality in Intensive Care Unit (ICU) patients from 2017 to 2022. This study analyzed sociodemographic aspects, clinical, and laboratory parameters in patients admitted to the ICU. A total of 221 medical records of patients with multidrug-resistant bacteria in the ICU were included, with an outcome of 95 discharges (42.98%) and 126 deaths (53.01%). An increase in the prevalence of bacterial resistance in the ICU was identified during the Pandemic period, when compared to the Pre-Pandemic period. It was identified that the increase in bacterial resistance of some pathogens was associated with death. It was also observed that age was a factor for an increased risk of mortality in the ICU, no matter the sex of the patient. Importance of careful analysis in the use of antimicrobials, as well as in the care of ICU patients and in the surveillance of bacterial infections by health professionals. Full article

Peanut, as an important economic crop, is widely cultivated and rich in nutrients. Classifying peanuts based on the number of seeds helps assess yield and economic value, providing a basis for selection and breeding. However, traditional peanut grading relies on manual labor, which is inefficient and time-consuming. To improve detection efficiency and accuracy, this study proposes an improved BTM-YOLOv8 model and tests it on an independently designed pod detection device. In the backbone network, the BiFormer module is introduced, employing a dual-route attention mechanism with dynamic, content-aware, and query-adaptive sparse attention to extract features from densely packed peanuts. In addition, the Triple Attention mechanism is incorporated to strengthen the model’s multidimensional interaction and feature responsiveness. Finally, the original CIoU loss function is replaced with MPDIoU loss, simplifying distance metric computation and enabling more scale-focused optimization in bounding box regression. The results show that BTM-YOLOv8 has stronger detection performance for ‘Quan Hua 557’ peanut pods, with precision, recall, mAP50, and F1 score reaching 98.40%, 96.20%, 99.00%, and 97.29%, respectively. Compared to the original YOLOv8, these values improved by 3.9%, 2.4%, 1.2%, and 3.14%, respectively. Ablation experiments further validate the effectiveness of the introduced modules, showing reduced attention to irrelevant information, enhanced target feature capture, and lower false detection rates. Through comparisons with various mainstream deep learning models, it was further demonstrated that BTM-YOLOv8 performs well in detecting ‘Quan Hua 557’ peanut pods. When comparing the device’s detection results with manual counts, the R2 value was 0.999, and the RMSE value was 12.69, indicating high accuracy. This study improves the efficiency of ‘Quan Hua 557’ peanut pod detection, reduces labor costs, and provides quantifiable data support for breeding, offering a new technical reference for the detection of other crops. Full article

Climate warming is one of the most pressing global changes, with profound consequences for biodiversity, ecosystem functioning, and the provision of ecosystem services. Although warming is expected to alter soil nutrient cycling and plant community structure, the mechanisms through which it reshapes ecosystem multifunctionality (EMF) remain insufficiently understood. Here, we conducted a 3-year field warming experiment in an alpine grassland to assess how warming influences plant diversity, soil nutrients, and their joint effects on EMF. We found that plant α-diversity declined in both control and warming groups in 2021 and partially recovered by 2023, though recovery was weaker under warming. In contrast, β-diversity (turnover) showed a continuous increasing trend under warming across years, although differences from the control were not statistically significant. EMF, evaluated with single- and multi-threshold approaches, exhibited a consistent decline, with warming accelerating this reduction and producing more complex bimodal fluctuations within intermediate threshold ranges (55–75% and 80–90%). Warming also restructured the functional drivers of EMF: soil organic carbon (SOC) and available nitrogen (AN) emerged as dominant regulators, whereas the contributions of total nitrogen and turnover weakened. Collectively, these findings demonstrate that warming not only alters biodiversity patterns and ecosystem functions but also reshapes the soil–plant–function feedbacks that sustain EMF. By identifying SOC and AN as critical mediators, this study highlights a mechanistic pathway through which climate warming may undermine ecosystem resilience and long-term sustainability, providing insights essential for predicting terrestrial ecosystem responses under future climate scenarios. Full article

This study explores how social innovation and multi-level governance (MLG) can enhance regional resilience and help overcome the Middle-Income Trap (MIT) through cooperative, community-driven strategies. Focusing on Hungarian self-governments, it examines twinning partnerships—formal relationships between settlements—as potential catalysts of social innovation and regional cohesion. A nationwide questionnaire survey (Number of settlements surveyed: 409; representative by settlement type) conducted between 2024 and 2025 evaluated the motivations, intensity and impacts of these partnerships. The findings reveal that intraethnic twinning networks are more socially active and locally grounded, strengthening community identity and civic participation, even though they provide limited direct economic benefits. By fostering trust, collaboration, and cross-border interaction, these partnerships act as effective platforms for social innovation, supporting more inclusive and territorially integrated development across Central and Eastern Europe. Full article

In the literature, fatigue-loaded reinforced concrete (RC) beams have been the subject of several experimental investigations; however, few numerical studies have specifically examined this behavior. The primary goal of this study is to create and validate a comprehensive nonlinear finite element (FE) modeling framework that combines an existing concrete damage model with specialized modelling techniques (e.g., material modelling, structural modelling, mesh configuration) to forecast the behaviour of reinforced concrete beams under monotonic fatigue loads and track the failure progress. This was accomplished by implementing suitable constitutive and structural models pertaining to concrete and reinforcing steel using VecTor2 finite element software. The Lü concrete damage model, which accounts for the accumulated damage in the concrete at each loading cycle, was taken from the literature to enhance the numerical findings. A number of published experimental tests conducted under monotonic fatigue loading were used to assess the accuracy of the suggested numerical model. The obtained numerical results demonstrated that the FE model may be used to simulate the monotonic fatigue behaviour of various RC beam types. The monotonic fatigue results were significantly improved by applying the Lü concrete damage model. Additionally, the FE model was implemented into practice to offer valuable information on failure mechanisms, fracture patterns, and strain profiles at different loading cycles. Full article

Background/Objectives: This study evaluated the concordance between sputum and bronchoscopic specimens in diagnosing nontuberculous mycobacteria (NTM) pulmonary disease. Methods: We retrospectively analyzed patients with NTM isolated from respiratory specimens between 2010 and 2022. Our analysis assessed species concordance across the two diagnostic methods and compared clinical outcomes between patients with multiple positive cultures and those with a single positive culture. Results: A total of 400 patients were included, 100 of whom underwent bronchoscopy. Among these, 61 demonstrated concordant NTM species between sputum and bronchoscopic specimens, while 38 had NTM cultured from only one source. One patient showed a discordant result, with Mycobacterium abscessus isolated from bronchoalveolar lavage and Mycobacterium avium from sputum. Multivariate analysis identified several factors associated with radiologic progression or the need for treatment: body mass index (HR, 0.847; 95% CI, 0.794–0.902; p < 0.001), membership in the single-isolation group (HR, 0.400; 95% CI, 0.184–0.871; p = 0.021), and fibrocavitary radiologic type (HR, 2.318; 95% CI, 1.470–3.655; p < 0.001). Conclusions: Only a small number of cases showed different NTM species identified by sputum and bronchoscopy. Full article