Search Results (13,581)

Interpreters who translate for refugees are regularly confronted with traumatic content. Listening regularly to and translating potentially traumatizing stories make interpreters vulnerable to secondary traumatization. The current study aimed to investigate secondary traumatic stress (STS) in interpreters working with refugees and to identify potential risk and protective factors. In this cross-sectional study, 64 interpreters from Austria, Germany, and Switzerland participated. STS, compassion satisfaction, burnout, and resilience were assessed using the Secondary Traumatic Stress Scale, Professional Quality of Life Scale, and Connor–Davidson Resilience Scale. Sociodemographic data were collected (e.g., experiences with translation in psychotherapy, personal backgrounds of forced displacement, and personal experiences with psychotherapy as a client). Subgroup comparisons were conducted to identify risk factors for STS. A total of 43 participants (67%) showed at least mild STS. STS was significantly associated with burnout. Personal experiences of forced displacement, gender, and working context had no impact on STS. Interpreters with personal experiences of psychotherapy showed a higher level of STS as well as higher resilience than those without personal experiences of psychotherapy. Independent of personal experiences of forced displacement, gender, and working context, interpreters who work with refugees are at high risk of STS. Regular training and supervision for interpreters who work with refugees should thus be offered as standard practice. Full article

Timely and accurate identification of surface damage in hydraulic structures is essential for maintaining structural integrity and ensuring operational safety. Traditional manual inspections are time-consuming, labor-intensive, and prone to subjectivity, especially for large-scale or inaccessible infrastructure. Leveraging advancements in aerial imaging, unmanned aerial vehicles (UAVs) enable efficient acquisition of high-resolution visual data across expansive hydraulic environments. However, existing deep learning (DL) models often lack architectural adaptations for the visual complexities of UAV imagery, including low-texture contrast, noise interference, and irregular crack patterns. To address these challenges, this study proposes a lightweight, robust, and high-precision segmentation framework, called LFPA-EAM-Fast-SCNN, specifically designed for pixel-level damage detection in UAV-captured images of hydraulic concrete surfaces. The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. The experimental results on a custom UAV-based dataset show that the proposed damage detection method achieves superior performance, with a precision of 0.949, a recall of 0.892, an F1 score of 0.906, and an IoU of 87.92%, outperforming U-Net, Attention U-Net, SegNet, DeepLab v3+, I-ST-UNet, and SegFormer. Additionally, it reaches a real-time inference speed of 56.31 FPS, significantly surpassing other models. The experimental results demonstrate the proposed framework’s strong generalization capability and robustness under varying noise levels and damage scenarios, underscoring its suitability for scalable, automated surface damage assessment in UAV-based remote sensing of civil infrastructure. Full article

Invasive fungal infections (IFIs) represent a growing global health threat, particularly for immunocompromised populations, with mortality exceeding 1.5 million deaths annually. Despite their clinical and economic burden—costing billions in healthcare expenditures—fungal infections remain underprioritized in public health agendas. This review examines the current landscape of antifungal therapy, focusing on advances, challenges, and future directions. Key drug classes (polyenes, azoles, echinocandins, and novel agents) are analyzed for their mechanisms of action, pharmacokinetics, and clinical applications, alongside emerging resistance patterns in pathogens like Candida auris and azole-resistant Aspergillus fumigatus. The rise of resistance, driven by agricultural fungicide use and nosocomial transmission, underscores the need for innovative antifungals, rapid diagnostics, and stewardship programs. Promising developments include next-generation echinocandins (e.g., rezafungin), triterpenoids (ibrexafungerp), and orotomides (olorofim), which target resistant strains and offer improved safety profiles. The review also highlights the critical role of “One Health” strategies to mitigate environmental and clinical resistance. Future success hinges on multidisciplinary collaboration, enhanced surveillance, and accelerated drug development to address unmet needs in antifungal therapy. Full article

Systems thinking (ST) is a foundational cognitive skillset to advance sustainability education but has not been well examined for learners prior to higher education. This case study research in rural middle schools in the Midwestern U.S. examines systems thinking outcomes of a place-based energy literacy unit focused on energy-efficient building design. The unit employs the science of energy-efficient, green buildings to illuminate the ways in which energy flows between natural and built environments. The unit emphasized electrical, light, and thermal energy systems and the ways these systems interact to create functional and energy-efficient buildings. This study focuses on three case study classrooms where students across schools (n = 89 students) created systems models as part of pre- and post-unit tests (n = 162 models). The unit tests consisted of student drawings, annotations, and writings, culminating into student-developed systems models. Growth from pre- to post-test was observed in both the identification of system elements and the linkages between elements. System elements included in the models were common classroom features, such as windows, lights, and temperature control, suggesting that rooting the unit in place-based teaching may support ST skills. Full article

The Varnous Mt. area in the northern Pelagonian Nappe is characterized by the intrusion of an Early Permian pluton, with its tectonic setting and igneous petrology well constrained in earlier studies. The metamorphic basement rocks warrant further detailed investigation due to their complex history. These rocks are polymetamorphosed, preserving a sequence of overprinting metamorphic and deformational events. The metapelitic rocks have undergone an initial, pre-Carboniferous regional metamorphism of unknown grade before or during Hercynian Orogeny, followed by a thermal metamorphic event associated with the intrusion of the Varnous pluton at 297 Ma. The assemblage attributed to this event is And + Crd + Bt + Ms (west), while the first assemblage identified at the eastern part is Sil + Bt + Gt. Additionally, three regional tectonometamorphic events occurred during the Alpine Orogeny. For the Alpine events, the assemblages are as follows: first, the development of St + Gt + Chl + Kfs + Pl + Qtz at 150–130 Ma; second, retrograde metamorphism of these assemblages with Cld + Gt + Ser + Mrg + Chl ± Sil (Fi) at 110–90 Ma; and finally, mylonitization of all previous assemblages at 90–70 Ma with simultaneous annealing and formation of Cld + Chl + Ms. Full article

Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article

This article describes the design, methods, and baseline characteristics of the social needs assessment (SNA) of participants enrolled in an ongoing randomized clinical trial implementing a comprehensive approach to improving diabetes self-management and providing an intensive Diabetes Self-Management Education and Support (iDSMES) Program at St. Vincent’s House Clinic, a primary care practice serving resource-challenged diverse populations in Galveston, Texas. Standardized SNA was conducted to collect information on financial needs, psychosocial well-being, and other chronic health conditions. Based on their identified needs, participants were referred to non-medical existing community resources. A series of in-depth interviews were conducted with a subset of participants. A team member independently categorized these SNA narratives and aggregated them into two overarching groups: medical and social needs. Fifty-nine participants (with a mean age of 53 years and equal representation of men and women) completed an SNA. Most (71%) did not have health insurance. Among 12 potential social needs surveyed, the most frequently requested resources were occupational therapy (78%), utility assistance (73%), and food pantry services (71%). SNA provided data with the potential to address barriers that may hinder participation, retention, and outcomes in diabetes self-management. SNA findings may serve as tertiary prevention to mitigate diabetes-related complications and disparities. Full article

A novel stainless steel with high Mn and Mo content (much higher than traditional stainless steel), designated CH241SS, was developed as a potential replacement for Cr-Mo-V alloy steel in the cold forging applications of precision industry. Through carbon reduction in an environmentally friendly manner and a two-stage heat treatment process, the hardness of as-cast CH241 was tailored from HRC 37 to HRC 29, thereby meeting the industrial specifications of cold-forged steel (≤HRC 30). X-ray diffraction analysis of the as-cast microstructure revealed the presence of a small amount of ferrite, martensite, austenite, and alloy carbides. After heat treatment, CH241 exhibited a dual-phase microstructure consisting of ferrite and martensite with dispersed Cr(Ni-Mo) alloy carbides. The CH241 alloy demonstrated excellent high-temperature stability. No noticeable softening occurred after 72 h for the second-stage heat treatment. Based on the mechanical and room-temperature tensile fatigue properties of CH241-F (forging material) and CH241-ST (soft-tough heat treatment), it was demonstrated that the CH241 stainless steel was superior to the traditional stainless steel 4xx in terms of strength and fatigue life. Therefore, CH241 stainless steel can be introduced into cold forging and can be used in precision fatigue application. The relevant data include composition design and heat treatment properties. This study is an important milestone in assisting the upgrading of the vehicle and aerospace industries. Full article

This study investigates changes in Near-Surface Air Temperature (NSAT) over the South African region using weather station data, reanalysis products, and Coupled Model Intercomparison Project Phase 6 (CMIP6) model outputs. It is shown that, based on ERA5 reanalysis, the average NSAT increase in the region (45–10° S, 0–50° E) for the period 1940–2023 was 0.11 ± 0.04 °C. Weak multi-decadal changes in NSAT were observed from 1940 to the mid-1970s, followed by a rapid warming trend starting in the mid-1970s. Weather station data generally confirm these results, although they exhibit considerable inter-station variability. An ensemble of 33 CMIP6 models also reproduces these multi-decadal NSAT change characteristics. Specifically, the average model-simulated NSAT values for the region increased by 0.63 ± 0.12 °C between the periods 1940–1969 and 1994–2023. Based on the results of the comparison between weather station observations, reanalysis, and models, we utilize projections of NSAT changes from the analyzed ensemble of 33 CMIP6 models until the end of the 21st century under various Shared Socioeconomic Pathway (SSP) scenarios. These projections indicate that the average NSAT of the South African region will increase between 1994–2023 and 2070–2099 by 0.92 ± 0.36 °C under the SSP1-2.6 scenario, by 1.73 ± 0.44 °C under SSP2-4.5, by 2.52 ± 0.50 °C under SSP3-7.0, and by 3.17 ± 0.68 °C under SSP5-8.5. Between 1994–2023 and 2025–2054, the increase in average NSAT for the studied region, considering inter-model spread, will be 0.49–1.15 °C, depending on the SSP scenario. Furthermore, climate warming in South Africa, both in the next 30 years and by the end of the 21st century, is projected to occur according to all 33 CMIP6 models under all considered SSP scenarios. The main spatial feature of this warming is a more significant increase in NSAT over the landmass of the studied region compared to its surrounding waters, due to the stabilizing role of the ocean. Full article

Posterior capsule opacification (PCO), a frequent complication of cataract surgery, arises from dysregulated wound healing and fibrotic transformation of residual lens epithelial cells. While transcriptomic and machine learning (ML) approaches have elucidated fibrosis-related pathways in other tissues, the molecular divergence between regenerative and fibrotic outcomes in the lens remains unclear. Here, we used an ex vivo chick lens injury model to simulate post-surgical conditions, collecting RNA from lenses undergoing either regenerative wound healing or fibrosis between days 1–3 post-injury. Bulk RNA sequencing data were normalized, log-transformed, and subjected to univariate filtering prior to training LASSO, SVM, and RF ML models to identify discriminatory gene signatures. Each model was independently validated using a held-out test set. Distinct gene sets were identified, including fibrosis-associated genes (VGLL3, CEBPD, MXRA7, LMNA, gga-miR-143, RF00072) and wound-healing-associated genes (HS3ST2, ID1), with several achieving perfect classification. Gene Set Enrichment Analysis revealed divergent pathway activation, including extracellular matrix remodeling, DNA replication, and spliceosome associated with fibrosis. RT-PCR in independent explants confirmed key differential expression levels. These findings demonstrate the utility of supervised ML for discovering lens-specific fibrotic and regenerative gene features and nominate biomarkers for targeted intervention to mitigate PCO. Full article

As the electromagnetic spectrum is a limited and valuable resource, auctions have emerged as an effective tool for promoting efficient allocation and generating revenue. This article proposes a theoretical review of the most commonly used auction formats for spectrum auctions, highlighting the primary strengths and weaknesses of each format. Additionally, comparisons are made between the revenue generated by different auction formats and the corresponding countries in North and South America during the 21st century. The conclusion drawn is that the Combinatorial Clock Auction format is the preferred choice, as it consistently leads to more efficient allocation, as measured by the revenue generated from each auction. Full article

A multidisciplinary study was conducted to reconstruct the paleoenvironmental evolution of Maladroxia Bay, one of the principal bays of the islet of Sant’Antioco in southwestern Sardinia, over the past eight millennia. As part of an archaeological landscape project, this study explores the paleogeography and environment of the bay from a diachronic perspective to gain insights into the Holocene relative sea level history, shoreline displacements, and the environmental conditions during different phases. This study is based on an analysis of four sediment cores in conjunction with a chronological model that is based on radiocarbon dates. Four relative sea level indicators were produced. These are the first such indicators from the early and middle Holocene for the island of Sant’Antioco. The results indicate that in the early Holocene, the area was a terrestrial, fluvial environment without marine influence. In the 6th millennium BCE, the rising sea level and marine transgression resulted in the formation of a shallow inner lagoon. It reached its maximum extent in the middle of the 5th millennium BCE. Afterwards, a gradual transition from lagoon to floodplain, and a seaward shift of the shoreline occurred. The lagoon potentially served as a valuable source of food and resources during the middle Holocene. During the Nuragic period (2nd to 1st millennium BCE), the Bay of Maladroxia was very similar to how it is today. Its location was ideal for use as an anchorage, due to the calm and sheltered conditions that prevailed. Full article

Straw returning (ST) significantly improves soil quality and profoundly impacts soil microorganisms. However, the effects of different ST application amounts on the soil bacterial community remain unclear, and more studies on optimal ST application amounts are warranted. This study aimed to investigate the bacterial diversity and composition, as well as physicochemical properties, of soil in a corn field with 5-year ST amounts of 0, 3, 4.5, 5, and 6 t/hm², respectively. The results indicated that ST significantly reduced soil bulk density and increased soil pH and nutrients. Meanwhile, ST had a significant effect on the bacterial composition, and the bacterial diversity increased significantly after ST. The relative abundance of Proteobacteria and Acidobacteria increased dramatically, whereas that of Actinobacteria significantly decreased after ST. The amount of ST had threshold effects on soil physicochemical properties and the dominant bacterial phyla. Moreover, the co-occurrence networks indicated that bacterial stability first increased and then decreased with the increase in ST amounts. Soil organic carbon and total nitrogen concentrations were the main drivers of bacterial diversity, whereas soil pH and total nitrogen concentrations were the main drivers of bacterial composition. This study strengthens the fact that ST amounts have threshold effects on the soil physicochemical properties and soil microorganisms, and ST amounts of 3–5 t/hm² were appropriate. Full article

Non-agricultural business activity of farmers is crucial not only for stabilizing farm income but also for the multifunctional development of rural areas. Capturing changes in the level and nature of this activity supports the development of sustainable agricultural and rural policy. In this context, this study aimed to identify the scale and types of non-agricultural business activity and to recognize the main determinants of such business activities undertaken by farmers in Poland between 2002 and 2022. Sectoral-level data from the Agricultural Censuses and cyclical studies of the structure of farms and household budgets were used to approximate underlying motivations for running non-agricultural business (opportunity vs. necessity entrepreneurship). The findings indicate that, in Poland, the impact of regressive factors remains strong, pushing farmers to take on additional business activity due to the large share of small and very small farms. However, during the 21st century, a gradual spread of opportunity entrepreneurship among Polish farmers has been observed. This study highlights the rationale for supporting non-agriculture business activity motivated by progressive factors to increase the income resilience of farmer households and the sustainable development of agriculture. The article indicates the need for further research on the motives for undertaking non-agricultural economic activities by farmers and the impact of this activity on the allocation of farm resources. Full article

Plastic waste accumulation is one of the most pressing environmental challenges of the 21st century, owing to the widespread use of synthetic polymers and the limitations of conventional recycling methods. Among available strategies, chemical upcycling via depolymerization has emerged as a promising circular approach that converts plastic waste back into valuable monomers and chemical feedstocks. This article provides an in-depth narrative review of recent progress in the upcycling of major plastic types such as PET, PU, PS, and engineering plastics through thermal, chemical, catalytic, biological, and mechanochemical depolymerization methods. Each method is critically assessed in terms of efficiency, scalability, energy input, and environmental impact. Special attention is given to innovative catalyst systems, such as microsized MgO/SiO₂ and Co/CaO composites, and emerging enzymatic systems like engineered PETases and whole-cell biocatalysts that enable low-temperature, selective depolymerization. Furthermore, the conversion pathways of depolymerized products into high-purity monomers such as BHET, TPA, vanillin, and bisphenols are discussed with supporting case studies. The review also examines life cycle assessment (LCA) data, techno-economic analyses, and policy frameworks supporting the adoption of depolymerization-based recycling systems. Collectively, this work outlines the technical viability and sustainability benefits of depolymerization as a core pillar of plastic circularity and monomer recovery, offering a path forward for high-value material recirculation and waste minimization. Full article