Search Results (2,223)

Synthetic aperture radar (SAR) exhibits all-day and all-weather capabilities, granting it significant application in remote sensing. However, interpreting SAR images requires extensive expertise, making SAR-to-optical remote sensing image translation a crucial research direction. While conditional generative adversarial networks (CGANs) have demonstrated exceptional performance in image translation tasks, their massive number of parameters pose substantial challenges. Therefore, this paper proposes ILF-BDSNet, a compressed network for SAR-to-optical image translation. Specifically, first, standard convolutions in the feature-transformation module of the teacher network are replaced with depthwise separable convolutions to construct the student network, and a dual-resolution collaborative discriminator based on PatchGAN is proposed. Next, knowledge distillation based on intermediate-layer features and channel pruning via weight sharing are designed to train the student network. Then, the bio-inspired dynamic search of channel configuration (BDSCC) algorithm is proposed to efficiently select the optimal subnet. Meanwhile, the pixel-semantic dual-domain alignment loss function is designed. The feature-matching loss within this function establishes an alignment mechanism based on intermediate-layer features from the discriminator. Extensive experiments demonstrate the superiority of ILF-BDSNet, which significantly reduces number of parameters and computational complexity while still generating high-quality optical images, providing an efficient solution for SAR image translation in resource-constrained environments. Full article

Hyperspectral imaging (HSI) systems often suffer from complex noise degradation during the imaging process, significantly impacting downstream applications. Deep learning-based methods, though effective, rely on impractical paired training data, while traditional model-based methods require manually tuned hyperparameters and lack generalization. To address these issues, we propose SS³L (Self-Supervised Spectral-Spatial Subspace Learning), a novel HSI denoising framework that requires neither paired data nor manual tuning. Specifically, we introduce a self-supervised spectral–spatial paradigm that learns noisy features from noisy data, rather than paired training data, based on spatial geometric symmetry and spectral local consistency constraints. To avoid manual hyperparameter tuning, we propose an adaptive rank subspace representation and a loss function designed based on the collaborative integration of spectral and spatial losses via noise-aware spectral-spatial weighting, guided by the estimated noise intensity. These components jointly enable a dynamic trade-off between detail preservation and noise reduction under varying noise levels. The proposed SS³L embeds noise-adaptive subspace representations into the dynamic spectral–spatial hybrid loss-constrained network, enabling cross-sensor denoising through prior-informed self-supervision. Experimental results demonstrate that SS³L effectively removes noise while preserving both structural fidelity and spectral accuracy under diverse noise conditions. Full article

Robin sequence (RS) is a rare congenital anomaly characterized by micrognathia, glossoptosis, and upper airway obstruction (UAO), often accompanied by a cleft palate. The Tübingen Palatal Plate (TPP), also referred to as the pre-epiglottic baton plate (PEBP), offers a non-surgical, functional orthodontic solution that improves airway patency and feeding by advancing the tongue base. This paper outlines the semi-digital clinical and technical workflow used for TPP treatment at Tübingen University Hospital. The protocol combines intraoral scanning (IOS), computer-aided design and manufacturing (CAD/CAM), and manual refinement for patient-specific appliance production. Practical steps, modifications for special cases and follow-up procedures are detailed, aiming to support clinical implementation at other centres. Based on the published literature and over three decades of experience, the protocol emphasizes safety, quality control, and interdisciplinary collaboration, with practical guidance provided to support implementation in other centres. The potential of digital workflows for data sharing, training, and multicenter collaboration is highlighted, while challenges such as the need for specialized expertise and technical resources are acknowledged. This guideline provides the first comprehensive and reproducible description of the Tübingen approach and aims to facilitate wider adoption of TPP therapy for infants with RS. Full article

This article offers a comparative analysis of authoritarian governance in Egypt and Türkiye through the lens of two pivotal state–Islamist alliances: the early partnership and eventual rupture between Gamal Abdel Nasser and the Muslim Brotherhood (MB), and the strategic collaboration followed by confrontation between Recep Tayyip Erdoğan and the Gülen Movement (GM). Despite operating in different historical and institutional settings—a postcolonial military regime in Egypt and an electoral, hybrid regime in Türkiye—both leaders allied with influential religious actors during moments of transition to gain popular support and dismantle entrenched power structures. These alliances were instrumental and temporary: once religious movements developed autonomous influence, they were recast as threats and suppressed through legal, institutional, and religious mechanisms. This study traces how religious institutions like Egypt’s al-Azhar and Türkiye’s Diyanet were co-opted to delegitimize these former allies and justify state repression. While the MB pursued overt political goals and the GM functioned through civic and technocratic channels, both were ultimately excluded from the political order once they had been considered as threats to the central authority of the regime. This comparison underscores the strategic use of religion in authoritarian statecraft and the enduring tension between religious autonomy and centralized political control in Muslim-majority polities. Full article

Morchella spp. is a type of valuable and rare edible fungi cultivated in soil. Optimization of the cultivation medium for Morchella spp. is key to obtaining high-efficiency production in an ecologically friendly manner. Recently, the sustainable resource utilization of agricultural waste has gathered attention. Specifically, reusing tomato substrate, mushroom residues, and coconut shells can lower the production costs and reduce environmental pollution, demonstrating remarkable ecological and economic benefits. To determine the soil microbial communities of Morchella spp. using different culture medias and influencing factors, this study analysed the relative abundance of bacterial and fungal communities in natural soil, soil with 5% tomato substrate, soil with 5% mushroom residues, and soil with 5% coconut shells using Illumina NovaSeq high-throughput sequencing. In addition, intergroup differences, soil physiochemical properties, and product quality were also determined. Results demonstrated that agricultural waste consisting of mushroom residues, waste tomato substrate, and coconut shells can improve the efficiency of Morchella spp. cultivation. When considering yield and quality, mushroom residue achieved the highest yield (soil nutrient enrichment), followed by tomato substrate (water holding + grass carbon nutrient). All three types of agricultural waste promoted early fruiting, significantly increased polysaccharide, crude protein, and potassium content, and lowered crude fat and fibre. In regard to soil improvement, the addition of different materials optimized the soil’s physical structure (reducing volume weight and increasing water holding capacity) and chemical properties (enrichment of nitrogen, phosphorus, and potassium, regulating nitrogen and medium trace elements). For microbial regulation, the added materials significantly increased the abundance of beneficial bacteria (e.g., Actinomycetota, Gemmatimonadota and Devosia) and strengthened nitrogen’s fixation/nitration/decomposition functions. In the mushroom residue group, the abundance of Bacillaceae was positively related to yield. Moreover, it inhibited pathogenic fungi like Mortierella and Trichoderma, and lowered fungal diversity to decrease ecological competition. In summary, mushroom residues have nutrient releasing and microbial regulation advantages, while tomato substrate and coconut shells are new high-efficiency resources. These increase yield through the “physiochemical–microorganism” collaborative path. Future applications may include regulating the function of microorganisms and optimizing waste preprocessing technologies to achieve sustainability. Full article

Antimicrobial resistance (AMR) poses a significant global threat to human and animal health, necessitating robust surveillance and stewardship tools. While existing systems address aspects of veterinary AMR, a comprehensive, user-centric dashboard for U.S. veterinarians remains a critical unmet need. This study aimed to identify U.S. veterinarians’ preferences and perceived needs for such a dashboard, to help guide its design and development. A cross-sectional survey was conducted between January and March 2024, targeting U.S. veterinarians through professional channels. The survey instrument captured demographics, experiences with existing tools, preferences for data types and visualizations, desired technical specifications, and open-ended feedback. Of the 677 respondents, a near-unanimous consensus (over 75%) emerged on the importance of functionalities like antimicrobial stewardship education, off-label use guidance, surveillance data, and empirical treatment support. Over 70% expressed comfort sharing aggregated geographic and de-identified animal data. A strong preference was observed for making the dashboard accessible by veterinary colleges (78.87%), diagnostic laboratories (72.61%), and federal agencies (USDA: 71.47%, CDC: 66.67%, FDA: 62.11%), indicating a desire for a collaborative, authoritative system. The findings provide a robust foundation for developing a U.S. veterinary AMR dashboard. Future phases should adopt an iterative, user-centered design, incorporating qualitative research with diverse stakeholders and piloting a prototype with preferred institutional partners. This approach will ensure a trusted, sustainable tool that effectively translates surveillance data into actionable insights for improved animal and public health. Full article

Critical energy infrastructures (CEIs) are fundamental pillars for economic and social development. However, their accelerated digitalization and the convergence between operational technologies (OTs) and information technologies (ITs) have increased their exposure to advanced cyber threats. This study examines the evolution of OT cybersecurity models with artificial intelligence in the energy sector between 2015 and 2024, through a systematic literature review following a four-phase method (planning, development, results, and analysis). To this end, we answer the following questions about the aspects of CEI cybersecurity models: What models exist? What energy services, technical means, and facilities do they encompass? And what algorithms do they include? From an initial set of 1195 articles, 52 studies were selected, which allowed us to identify 49 cybersecurity models classified into seven functional categories: detection, prediction and explanation; risk management; regulatory compliance; collaboration; response and recovery; architecture-based protection; and simulation. These models are related to 10 energy services, 6 technical means, 10 types of critical facilities, and 15 AI algorithms applied transversally. Furthermore, the integrated and systemic relationship of these study aspects has been identified in an IT-OT cybersecurity model for CEIs. The results show a transition from conventional approaches to solutions based on machine learning, deep learning, federated learning, and blockchain. Algorithms such as CNN, RNN, DRL, XAI, and FL are highlighted, which enhance proactive detection and operational resilience. A broader coverage is also observed, ranging from power plants to smart grids. Finally, five key challenges are identified: legacy OT environments, lack of interoperability, advanced threats, emerging IIoT and quantum computing risks, and low adoption of emerging technologies. Full article

The healing issue is a central, not completely understood, problem in pharmacology, approached by many concepts. One of the most well-known is Robert’s and Szabo’s concept of cytoprotection, which holds innate cell (epithelial (Robert), endothelial (Szabo)) integrity, protection/maintenance/reestablishing in the stomach to be translated to other organ therapy (cytoprotection→organoprotection) via cytoprotection agent’s effect. Thereby, we defend stable gastric pentadecapeptide BPC 157 therapy, efficacy, pleiotropic beneficial effects along with high safety (LD1 not achieved) against Józwiak and collaborators’ review speculating its negative impact, speculation of angiogenesis toward tumorogenesis, increased NO and eNOS, toward damaging free radicals formation, and neurodegenerative diseases (Parkinson’s disease and Alzheimer’s disease). Contrarily, in wound healing and general healing capabilities as reviewed, as a cytoprotective agent, and native cytoprotection mediator, BPC 157 controls angiogenesis and the NO-system healing functions, and counteracts the pathological presentation of neurodegenerative diseases in acknowledged animal models (i.e., Parkinson’s disease and Alzheimer’s disease), and presents prominent anti-tumor potential, in vivo and in vitro. BPC 157 resolved cornea transparency maintenance, cornea healing “angiogenic privilege” (vs. angiogenesis/neovascularization/tumorogenesis), does not produce corneal neovascularization, but rather opposes it, and per Folkman’s concept, it demonstrates anti-tumor effect in vivo and in vitro. BPC 157 exhibits a distinctive effect on NO-level (increase vs. decrease), always combined with counteraction of free radicals formation, and in mice and rats, BPC 157 therapy counteracts Parkinson’s disease-like and Alzheimer’s disease-like disturbances. Thus, BPC 157 therapy means targeting angiogenesis and NO’s cytotoxic and damaging actions, but maintaining, promoting, or recovering their essential protective functions. Full article

Background: Pain is a prevalent and distressing symptom for children with cancer, negatively affecting quality of life and family functioning. While most research focuses on hospital-based care, many pain episodes occur at home, where parents act as primary caregivers with limited access to evidence-based symptom management. Young children are particularly vulnerable due to limited self-reporting capacity and reliance on parental assessment. We aimed to explore parent experiences and pediatric oncology clinician perceptions of young children’s cancer pain at home, its impact on families, and recommended supports. Methods: Using an interpretive descriptive qualitative design, we conducted semi-structured interviews with parents of children aged 2–11 years undergoing outpatient cancer treatment and clinicians at two hospitals in Canada and the United States. Data were analyzed using thematic analysis. Results: In total, 21 parents and 21 clinicians participated. Three themes were developed: (1) the multifaceted experience of young children’s cancer pain at home, (2) the ripple effects of a young child’s cancer pain on the family unit, and (3) assessing and treating children’s cancer pain at home. Conclusion: Managing cancer pain at home places substantial emotional and practical demands on the families of young children. Our findings highlight that structured supports providing parents and clinicians with education, effective communication pathways, and collaboration opportunities may optimize home-based pain care, reduce caregiving burden, and improve outcomes for children and their families. Full article

In the current digital era, the spread of fake news presents serious difficulties. This study offers a thorough analysis of recent developments in false news automatic detection techniques, from traditional methods to the most recent developed models like large language models. The review identifies four perspectives on automatic detection of fake news that are oriented towards knowledge, style, propagation, and source of the misinformation. This paper describes how automatic detection methods use data science techniques such as deep learning, large language models, and traditional machine learning. In addition to discussing the shortcomings of existing approaches, such as the absence of datasets, this paper emphasizes the multidimensional function of large language models in creating and identifying fake news while underlining the necessity for textual, visual, and audio common analysis, multidisciplinary collaboration, and greater model transparency. Full article

New York State and New York City (NYC) developed hepatitis C (HCV) elimination plans to reduce premature deaths and new infections. NYC Health + Hospitals (NYC H + H), the municipal healthcare system for NYC serving over a million individuals annually, designed electronic health record (EHR) tools that collaboratively facilitated screening, linkage, and tracking of patients diagnosed with HCV through to cure. This study reviews the impact of this group of EHR tools by comparing data on HCV testing, linkage, and cure for 12 months before tools were released and a second 12-month period coinciding with the release of tools. Indicators related to HCV screening, diagnoses, treatment initiation, and cure were assessed. All indicators reviewed improved following the implementation of EHR tools. The proportion of individuals screened increased from 34% pre-intervention to 46% during the implementation phase; the number of individuals on direct-acting antivirals increased by 11%; and the number of individuals reaching cure increased by 37%. Efforts to collaboratively develop custom interlinking EHR tools to establish a systematic process proved impactful. Integrating the needs and functions of different care settings and the structure of the local epidemic allowed for the successful development and implementation of impactful resources. Full article

Historic and cultural towns are undergoing spatial restructuring and memory ruptures in the context of urban–rural transformation. Collective memory depends on the continuity of public space, with generational differences playing a key role in its transmission. This study uses Menghe Town in Changzhou, Jiangsu Province, as a case to explore the role of public space in collective memory transmission through interviews, emotional mapping, and intergenerational co-construction analysis. The findings show the following: (1) Interviews and emotional mapping reveal that memories of traditional spaces like farmland have weakened, while emerging public spaces such as squares and walkways have become new memory nodes, reflecting a dynamic “carrying-transformation-reproduction” mechanism. (2) Intergenerational emotional mapping reveals that the transformation of spatial functions has driven the reconstruction of cultural identity, shifting villagers’ sense of place from clan and production-based spaces to modern public spaces. (3) Intergenerational emotional mapping and co-construction analysis reveal significant generational differences in memory perception and spatial use: the older generation relies on ancestral halls and farmland, the middle generation on factories and streets from the “agriculture-to-industry” period, and the younger generation on modern facilities like squares and schools. This study proposes the “Narrate—Preserve—Participate” model, explaining memory transmission across generations and offering insights for intergenerational collaboration and differentiated preservation in public space planning. Full article

Trajectory planning for logistics UAVs in complex environments faces a key challenge: balancing global search breadth with fine constraint accuracy. Traditional algorithms struggle to simultaneously manage large-scale exploration and complex constraints, and lack sufficient modeling capabilities for multi-UAV systems, limiting cluster logistics efficiency. To address these issues, we propose a GWOP algorithm based on dual-layer fusion of GWO and GRPO and incorporate a graph attention network (GAT). First, CEC2017 benchmark functions evaluate GWOP convergence accuracy and balanced exploration in multi-peak, high-dimensional environments. A hierarchical collaborative architecture, “GWO global coarse-grained search + GRPO local fine-tuning”, is used to overcome the limitations of single-algorithm frameworks. The GAT model constructs a dynamic “environment–UAV–task” association network, enabling environmental feature quantification and multi-constraint adaptation. A multi-factor objective function and constraints are integrated with multi-task cascading decoupling optimization to form a closed-loop collaborative optimization framework. Experimental results show that in single UAV scenarios, GWOP reduces flight cost (FV) by over 15.85% on average. In multi-UAV collaborative scenarios, average path length (APL), optimal path length (OPL), and FV are reduced by 4.08%, 14.08%, and 24.73%, respectively. In conclusion, the proposed method outperforms traditional approaches in path length, obstacle avoidance, and trajectory smoothness, offering a more efficient planning solution for smart logistics. Full article

Families in rural communities face a constellation of challenges that significantly hinder their ability to support adolescents. Our study aimed to explore family functioning as a protective factor for adolescent mental health from the perspective of parents in rural communities of southern Ecuador, using Photovoice as a participatory research tool. The research design corresponds to Participatory Action Research. Five Focus Group Discussions (FGDs) were conducted. A total of 29 parents of adolescents participated in the study. The research team employed qualitative content analysis for the interpretation phase. Through photographs and focus groups, parents commented on aspects of family life that they perceived as necessary for supporting adolescents, such as effective communication, cohesion, supervision, and expressions of care. The main conclusion indicated that the implementation of Photovoice converted participants from subjects to collaborators, allowing them to critically reflect on their behaviors while aiding or reinforcing in the co-creation of strategies. Full article

Background: Themanagement of occupational respiratory diseases (ORDs) requires a multidisciplinary approach, yet collaboration between pulmonologists and occupational physicians is often fragmented, potentially compromising patient outcomes. This study aimed to systematically compare the management strategies for ORDs between these two specialties in Italy to identify gaps and opportunities for integration. Methods: A cross-sectional survey was conducted using a structured 12-item questionnaire distributed to board-certified pulmonologists and occupational physicians across Italy. The questionnaire assessed diagnostic pathways, therapeutic strategies, preventive measures, and patterns of interdisciplinary collaboration. A total of 102 specialists (51 pulmonologists and 51 occupational physicians) completed the survey. Comparative analyses were performed using Pearson’s ${\chi }^2$ tests. Results: Significant divergences in practice were identified. Pulmonologists primarily focused on clinical diagnosis, utilizing pulmonary function tests (34.3%) and imaging (11.8%), and favored pharmacotherapy (27.5%) as the first-line treatment, in alignment with clinical guidelines. Conversely, occupational physicians prioritized detailed occupational and exposure histories (15.7%) and preventive interventions aimed at exposure reduction (15.7%). While both groups acknowledged the importance of collaboration, a substantial number reported that it occurred only occasionally (17.6% of pulmonologists and 12.7% of occupational physicians), indicating a significant gap in integrated care. Shared barriers included poor patient adherence and limited access to advanced diagnostic tools. Conclusions: While sharing a common foundation in diagnostic and preventive principles, pulmonologists and occupational physicians in Italy operate with distinct, complementary approaches that remain insufficiently integrated. The observed fragmentation in diagnostic and therapeutic pathways underscores an urgent need for shared national guidelines, structured interdisciplinary training, and formalized communication protocols. Bridging this disciplinary divide is essential to delivering holistic care, optimizing worker health, and preserving work ability. Full article