Search Results (1,828)

This paper extends previous work on echo chambers modeled by an Ising-like system at zero temperature (Spontaneous Symmetry Breaking, Group Decision Making and Beyond 1: Echo Chambers and random Polarization, Symmetry 2024, 16(12), 1566). There, polarization emerged as a spontaneous symmetry-breaking process with a randomly selected direction. Here using a mean-field analysis and Monte Carlo simulations I show that this mechanism is highly vulnerable to minimal distortions. An external symmetry-breaking field, even very small, suffices to impose a global direction and suppress opposite domains, producing distorted full polarization. In contrast, a handful of quenched local fields with zero average do not erase polarization but reorganize it into opposing domains. Remarkably, as few as two opposed fields, if placed at tipping sites, can redirect the entire system. These fragile sites, indistinguishable from others, act as hidden tipping points that amplify microscopic biases into macroscopic outcomes. The difference in local field proportions is found to be instrumental to guaranteeing a winning majority. The results highlight how minimal, strategically placed interventions can override autonomous self-organization. The results could, if applicable to social media platforms, question their presumed democratic nature of consensus. Full article

Governmental organizations, projects, and initiatives in Saudi Arabia have focused specifically on the fisheries and the aquaculture sector to reduce reliance on imports, achieve self-sufficiency, and significantly contribute to food security. To accommodate the annual population increase, Saudi Arabia needs to enhance its fish production. This study aims to illustrate the impact of credit on the fisheries sector by examining the factors that affect fish output in Saudi Arabia, both in general and in specific contexts. The research employed annual time series data to estimate the Cobb–Douglas production function. The study computed the Cobb–Douglas model in an error correction format due to the stationarity characteristic of the data. The results show that fish production in Saudi Arabia is significantly enhanced by the number of fishermen, marine fisheries, aquaculture farms, and financial resources. Furthermore, the results reveal that economies of scale play a crucial role in the Saudi fishing industry. Nevertheless, since the data indicates that the influence of marine fisheries on fish output in Saudi Arabia in the long run surpasses that of aquaculture farms, the researchers recommend an increase in aquaculture production. Sustainable methods for fish production, such as minimizing overfishing and bycatch, improving water and environmental quality, and promoting the traceability of fish populations, should be prioritized in the advancement of the fisheries sector. Full article

Background: Diabetes and mental health conditions frequently co-occur, with depression and anxiety affecting up to 20–30% of people with diabetes. These comorbidities worsen glycemic control, adherence, and quality of life, yet mental health is often neglected in diabetes care. Integrating mental health services into diabetes management is recommended by international organizations to improve patient outcomes. Objectives: To systematically review the evidence on integrated mental health interventions in diabetes care, compared to usual diabetes care, in improving patient outcomes (glycemic control, mental health, adherence, quality of life). Methods: We searched PubMed/MEDLINE, Embase, PsycINFO, and Scopus (2000 through July 2024) for studies of diabetes care integrating mental health support (e.g., collaborative care, co-location, stepped care, or digital interventions). Inclusion criteria were controlled trials or cohort studies involving individuals with type 1 or type 2 diabetes receiving an integrated mental health intervention, with outcomes on glycemic control and/or mental health. Two reviewers independently screened titles/abstracts and full texts, with disagreements resolved by consensus. Data on study design, population, intervention components, and outcomes were extracted. Risk of bias was assessed using Cochrane or appropriate tools. Results: Out of records identified, 64 studies met inclusion criteria (primarily randomized controlled trials). Integrated care models consistently improved depression and anxiety outcomes and diabetes-specific distress, and yielded modest but significant reductions in glycated hemoglobin (HbA1c) compared to usual care. Many interventions also enhanced treatment adherence and self-management behaviors. For example, collaborative care trials showed greater depression remission rates and small HbA1c improvements (~0.3–0.5% absolute reduction) relative to standard care. Co-located care in diabetes clinics was associated with reduced diabetes distress, depression scores, and HbA1c over 12 months. Digital health integrations (telepsychiatry, online cognitive-behavioral therapy) improved psychological outcomes and adherence, with some reporting slight improvements in glycemic control. Integrated approaches often increased uptake of mental health services (e.g., higher referral completion rates) and showed high patient satisfaction. A subset of studies reported fewer emergency visits and hospitalizations with integrated care, and one economic analysis found collaborative care cost-effective in primary care settings. Conclusions: Integrating mental health into diabetes care leads to better mental health outcomes and modest improvements in glycemic control, without adverse effects. Heterogeneity across studies is noted, but the overall evidence supports multidisciplinary, patient-centered care models to address the psychosocial needs of people with diabetes. Healthcare systems should prioritize implementing and scaling integrated care, accompanied by provider training and policy support, to improve outcomes and bridge the persistent treatment gap. Future research should focus on long-term effectiveness, cost-effectiveness, and strategies to reach diverse populations. Full article

Glioblastoma (GBM) is the most malignant primary brain tumor, characterized by extensive heterogeneity, invasiveness, infiltrating behavior, and resistance to standard therapies, including radiation and temozolomide (TMZ). Despite considerable efforts in investigating its pathophysiology, GBM represents one of the most challenging cancers to treat, with a median survival rate under 15 months and a 5-year survival rate below 5%. A major barrier to progress in GBM therapy development is the lack of reliable preclinical models that faithfully recapitulate the tumor’s molecular heterogeneity, invasive behavior, and complex microenvironment. Traditional cell lines and xenograft models often fail to reflect the key pathological features of human GBM, including immune suppression, vascular abnormalities, and treatment resistance. In recent years, attention has focused on the development of numerous clinically relevant GBM models based on brain organoids as a powerful “disease-in-a-dish” model. They strongly mimic GBM key histopathological and molecular features, such as the tumor’s cellular heterogeneity, genetic landscape, and microenvironment, enabling more accurate studies of tumor biology, invasion, and therapeutic response in a controlled in vitro setting. Notably, research in microgravity offers a unique and promising platform to study cancer biology under conditions that enhance tissue self-organization, mimic aspects of tumor growth, and potentially unveil novel therapeutic vulnerabilities. This review compares organoids to conventional preclinical models, tracing their historical development and salient features, focusing on the preparation and use of organoids in GBM research. We also introduce a novel and promising field of organoid application: space-based organoid brain research. Full article

General self-efficacy is identified as a modifiable determinant of adolescent mental health and well-being. This study sought to better understand how conditions in different environments of adolescents’ lives and socio-demographic factors are associated with adolescents’ general self-efficacy. We conducted a hierarchical multi-variable linear regression analysis based on survey data from 2021 of a large population-based sample of Norwegian adolescents (n = 15,040). We found that better Relation to peers (β = 0.20, 95% CI [0.18; 0.22]) and Academic/social relation to teachers (β = 0.13, 95% CI [0.11; 0.14]), Perceived neighbourhood safety (β = 0.08, 95% CI [0.06; 0.10]), and Participation in physical activities (β = 0.07, 95% CI [0.06; 0.09]) had medium to small positive associations with adolescents’ general self-efficacy, whilst Parental involvement, Participation in organized music/cultural leisure activities, and Perceived access to neighbourhood leisure arenas had negligible associations with general self-efficacy. Boys reported a stronger general self-efficacy than girls (β = −0.17, 95% CI [−0.19; −0.16]) and Age and Socio-economic status had small positive associations with general self-efficacy (β = 0.08, 95% CI [0.07; 0.10] and 0.04, 95% CI [0.02; 0.06], respectively). We found some small moderation effects by socio-demographic factors in the associations between environmental factors and general self-efficacy. Our findings suggest that general self-efficacy-promoting initiatives that target adolescents apply a multi-sectorial and multi-level approach and pay particular attention to gender differences. A focus on facilitating adolescents’ experiences of mastery and access to relevant successful role models and supportive behaviour by adults and peers in the various contexts seems to be of particular importance. Full article

Taking Harbin morning market as a case study, this study explores sustainable production schemes for generating sense of place in urban spaces amid the trend of modernization. Employing grounded theory, it develops an analytical model consisting of three components: space, humans, and materials. The findings reveal that place identity emerges from functional redundancy and self-organizing spatial layouts, where the hybrid logic of spatial design, the non-programmed interactions of human actors, and the material networks together enable tourists to transform from spectators into embodied participants. Theoretically, this study proposes a hybrid logic and challenges high modernism. It emphasizes that fully mobilizing the spontaneous vitality of every actor in the space is more effective than unilaterally improving rules and functions, offering a sustainable path for nurturing localized cultural ecosystems against homogenization. Full article

Intestinal organoids possess self-organizing capacity and recapitulate essential features of intestinal architecture and function, making them powerful models for investigating development, disease mechanisms, pharmacological testing, and host–microbe interactions. Although standardized protocols for chicken intestinal organoids have been established, a defined culture system for ducks has not been available. In this study, we optimized crypt isolation procedures and culture medium composition to establish a reproducible system tailored to duck intestinal stem cells. Among various digestive solutions, ethylene glycol tetraacetic acid (EGTA) achieved the highest crypt isolation efficacy and organoid survival. Suspension culture resulted in better survival, proliferation, and differentiation of intestinal stem cells than air–liquid interface and embedding methods (p < 0.05). Immunofluorescence and real-time PCR indicated the presence of multiple epithelial lineages, including stem cells, Paneth cells, enterocytes, goblet cells, and enteroendocrine cells. Media supplemented with CHIR99021 and LDN193189 (CL) supported growth comparable to that of media with EGF, Noggin, and R-spondin 1 (ENR). Duckling serum and specific factors, such as SB203580 and retinol, further improved organoid formation and promoted differentiation. While long-term passaging and expansion remain technically challenging, this work provides the first duck intestinal organoid model and lays the foundation for future applications in avian intestinal research, including nutrition, disease modeling, and intervention strategies. Full article

This study presents fractal technology as a foundational approach to sustainable growth in the artificial intelligence (AI) era and Industry 5.0. We explore how the principles of fractal geometry, including self-similarity and recursive properties, improve scalability, efficiency, and adaptability in AI-driven systems. Representative applications include neural networks, decentralized control, and intelligent manufacturing, where fractal-based design enables modularity, fault tolerance, and optimized resource use. Case studies and theoretical models demonstrate that a fractal frameworks provide a viable path toward long-term, self-organizing industrial innovation and sustainability-oriented vision of Industry 5.0. Theoretical perspectives are strengthened by connections to nonextensive Tsallis statistics and parallels with complex systems in quantum field theory, suggesting the universality of fractal laws across disciplines. Case studies confirm that fractal frameworks offer a viable path toward long-term, self-organizing industrial innovation, contributing to the emerging field of fractal engineering and providing a systems-level paradigm for sustainable technological evolution. Full article

The optimal computing ability of spiking neural networks (SNNs) mainly depends on the connection weights of their synapses and the thresholds that control the spiking. In order to realize the optimization calculation of different objective functions, it is necessary to modify the connection weights adaptively and make the thresholds dynamically self-learning. However, it is very difficult to construct an adaptive learning algorithm for spiking neural networks due to the discontinuity of neuron spike sending process, which is also a fatal problem in this field. In this paper, an efficient adaptive learning algorithm for spiking neural networks is proposed, which adjusts the weights of synaptic connections by a learning factor adaptively and adjusts the probability of spike sending by the self-organizing learning method of the dynamic threshold, so as to achieve the goal of automatic global search optimization. The algorithm is applied to the learning task of global optimization, and the experimental results show that this algorithm has good stability and learning ability, and is effective in dealing with complex multi-objective optimization problems of spatiotemporal spike mode. Moreover, the proposed framework explicitly leverages problem and model symmetries. In Traveling Salesman Problems, distance symmetry (d(i, j) = d(j, i)) and tour permutation symmetry are preserved by our spike-train-based similarity and energy updates, which do not depend on node labels. Together with the homogeneous neuron dynamics and balanced excitatory–inhibitory populations, these symmetry-aware properties reduce the effective search space and enhance the convergence stability. Full article

Wireless Sensor Networks (WSNs) are vital to a wide range of applications, spanning from environmental monitoring to safety-critical systems. Ensuring dependable operation in these networks critically depends on selecting an optimal node scheduling algorithm; however, this remains a major challenge since no single approach performs best under all conditions. To address this issue, this paper proposes an AI-driven framework that evaluates scenario-specific functional requirements—such as coverage, connectivity, and network lifetime—to identify the optimal node scheduling algorithm from a pool that includes Hidden Markov Models (HMMs), BAT, Bird Flocking, Self-Organizing Maps (SOFMs), and Long Short-Term Memory (LSTM) networks. The framework was evaluated using a neural network trained on simulated data and tested across five real-world scenarios: healthcare monitoring, military operations, industrial IoT, forest fire detection, and disaster recovery. The results clearly demonstrate the effectiveness of the proposed framework in identifying the most suitable algorithm for each scenario. Notably, the LSTM algorithm frequently achieved near-optimal performance, excelling in critical objectives such as network lifetime, connectivity, and coverage. The framework also revealed the complementary strengths of other algorithms—HMM proved superior for maintaining connectivity, while Bird Flocking excelled in extending network lifetime. Consequently, this work validates that a scenario-aware selection strategy is essential for maximizing WSN dependability, as it leverages the unique advantages of diverse algorithms. Full article

Acute pancreatitis (AP) is an inflammatory disorder of the pancreas that can lead to serious systemic complications. Its clinical presentation varies widely, ranging from mild, self-limiting symptoms to severe, life-threatening illness. Currently, there are no specific therapies approved for the treatment of AP, and management primarily relies on supportive care. However, a growing number of clinical trials have evaluated the translational potential of effective therapies derived from experimental models and have identified promising pharmacological agents that may help ameliorate disease severity. Alongside pharmacological approaches, nutritional management of AP has been gaining increasing attention. Evidence supports the use of enteral nutrition over parenteral feeding, as it is associated with a lower risk of necrotic infections, multiple organ dysfunction, mortality, and other associated complications of AP. In this review, we summarize the therapeutic potential of pharmacological and dietary/nutritional interventions, including naturally occurring bioactive compounds, for AP in the context of its molecular pathology, with the aim of supporting improved clinical decision-making, enhancing patient outcomes, and informing future research directions. Full article

Multiple-mode immunoassays have the advantages of self-correction, self-validation, and high accuracy and reliability. In this work, we developed a strategy for the design of triple-mode immunoassays with the self-assemblies of three-in-one small molecules as signal reporters. Pyrroloquinoline quinone (PQQ), with a well-defined redox peak and excellent spectroscopic and fluorescent signals, was chosen as the signaling molecule. PQQ was coordinated with Cu²⁺ to form metal–organic nanoparticle as the signal label. Hexahistidine (His₆)-tagged recognition element (recombinant streptavidin) was attached to the Cu-PQQ surface through metal coordination interaction between the His₆ tag and the unsaturated metal site. The captured Cu-PQQ nanoparticle released a large number of PQQ molecules under an acidic condition, which could be simultaneously monitoring by electrochemical, UV-vis, and fluorescent techniques, thereby allowing for the development of triple-model immunoassays. The three methods were used to determine the concentration of carcinoembryonic antigen (CEA) with the detection limits of 0.01, 0.1, and 0.1 ng/mL, respectively. This strategy opens up a universal route for the preparation of multiple-model signal labels and the oriented immobilization of bioreceptors for molecular recognition. Full article

Self-regulation is widely theorized as a foundation for early mathematics achievement, yet little is known about how specific forms of teacher scaffolding advance this process in preschool classroom contexts. Drawing on sociocultural and self-regulation theories, this study conceptualizes scaffolding as a mechanism through which teachers support children’s attention, working memory, and behavioral regulation during mathematics instruction. We extend theory by distinguishing three domains of scaffolding—Instructional Strategies, Management Organization, and Warmth Responsivity—and examining how each uniquely relates to children’s math outcomes. Participants were 416 preschoolers (M age = 59.7 months) and 18 head teachers in Santiago, Chile. Teachers’ scaffolding behaviors were video recorded and coded at the beginning and end of the school year, and children’s math achievement was assessed with the Woodcock-Muñoz III. Multilevel models controlling for prior achievement, age, income, and gender revealed that Management Organization was positively associated with math achievement, while Warmth Responsivity was negatively associated, and Instructional Strategies showed no significant effect. These findings refine theoretical models by showing that organizational scaffolding plays a particularly important role in supporting math learning, whereas warmth responsivity may function as compensatory scaffolding in response to children’s difficulties. The study advances understanding of how the quality and type of scaffolding shape the developmental pathway from self-regulation to mathematics achievement. Full article

This white paper, prepared by a consortium of Canadian national and provincial organizations and experts, outlines urgent strategies to curb the rising incidence of HPV-related cancers, of which, cervical cancer is currently the fastest-growing cancer in Canada. Despite school-based vaccination programs, the national HPV vaccine uptake remains suboptimal at about 64%, far below the 90% coverage target by 2025 necessary to eliminate cervical cancer by 2040. The report emphasizes a multi-pronged approach: support access to HPV vaccination with expanded funding policies and education around school-based programs while addressing inequities in underserved populations. HPV testing is highlighted as the preferred method for cervical cancer screening, offering higher sensitivity than Pap smears. Self-collection is presented as an innovative strategy to reduce barriers, particularly for marginalized groups, with promising evidence from Canadian pilots and international models. Crucially, we call for investment in comprehensive, population-based databases to track vaccination, screening participation, and follow-up care. Robust registries would allow targeted outreach to under- or never-screened individuals, ensure timely follow-up of abnormal results, and measure the impact of prevention programs across Canada. With vaccination, equitable access to HPV testing, integration of self-collection, and strong data systems, Canada can achieve its goal of eliminating cervical cancer within two decades. Full article

Population mobility links cities, propelling the spatiotemporal spread of urban pandemics and adding complexity to disease dynamics. It also closely shapes, and is shaped by, the selection and intensity of intervention measures. Revealing the multistage spatial-temporal dynamics of cross-regional epidemic continuity under this interaction is often overlooked but critically important. This study innovatively applies a self-organizing map (SOM) neural network to classify cities into six distinct types based on population mobility characteristics: high-inflow core (HIC), low-inflow core (LIC), low-inflow sub-core (LISC), high-outflow semi-peripheral (HOSP), equilibrious semi-peripheral (ESP), and low-outflow peripheral (LOP). Building on this, we propose a novel SEIR-AHQ theoretical framework and construct an epidemiological model using network-coupled ordinary differential equations (ODEs). This model captures the dynamic interplay between inter-city population mobility and intervention measures, and quantifies how heterogeneous city types shape the evolution of epidemic transmission across the coupled mobility network. The results show that: (1) Cities with stronger population mobility face significantly higher infection risks and longer epidemic durations, characterized by “higher peaks and longer tails” in infection curves. HIC cities experience the greatest challenges, and LOP cities experience the least. (2) Both higher transmission rates and delayed intervention timings lead to exponential growth in infections, with nonlinear effects amplifying small changes disproportionately. (3) Intervention efficacy follows a “diminishing marginal returns” pattern, where the incremental benefits of increasing intervention intensity gradually decrease. This study offers a novel perspective on managing interregional epidemics, providing actionable insights for crafting tailored and effective epidemic response strategies. Full article