Abstract: Energy security and stability are related to the national economy and people's livelihood. Effectively improving the resilience of energy industry supply chain is the key factor to realize energy security and stability. Based on the panel data of 30 provinces in China from 2013 to 2023, this paper empirically explores the influence mechanism of new quality productivity on the resilience of energy industry supply chain. It is found that the new quality productivity can significantly enhance the resilience of the energy industry supply chain. The regulatory effect test results show that the energy supply level can positively promote the new quality productivity and improve the resilience of the energy industry supply chain. The results of threshold effect test show that the level of urbanization development and the degree of industrial synergy agglomeration make the new quality productivity have a nonlinear influence on the resilience of energy industry supply chain. The results of heterogeneity test show that the productivity of new quality plays a more obvious role in promoting the resilience of energy industry supply chain in the central region and the regions with higher information level.

Abstract: Background: Autism spectrum disorder (ASD) affects approximately 1-2% of children worldwide, yet its etiology remains incompletely understood. Emerging evidence suggests that parental autoimmune diseases significantly increase offspring autism risk, with psoriasis (OR 1.59), type 1 diabetes (OR 1.49-2.36), and rheumatoid arthritis (OR 1.51) showing particularly strong associations. Hypothesis: I propose that autism is fundamentally an immune-metabolic disorder characterized by TNF-α-mediated mitochondrial dysfunction leading to cerebral energy deficiency. This energy deficit impairs two critical processes: (1) synaptic pruning during neurodevelopment, and (2) real-time social cognition including gaze processing and emotion recognition. The primary mechanism involves TNF-α pathway dysregulation—through genetic inheritance from parents with autoimmune diseases and/or through direct fetal exposure to elevated maternal TNF-α during pregnancy. Additionally, for cases without parental autoimmune history, I propose a speculative secondary mechanism: mitonuclear immune conflict, where paternal immune genes may partially recognize maternal mitochondria as non-self, generating endogenous TNF-α. Novel Prediction: Based on this framework, I predict that parents with normal-tension glaucoma (NTG)—another TNF-α-mediated condition characterized by neurodegeneration independent of intraocular pressure—will show elevated prevalence of autistic offspring. This prediction has not been tested in any published study. Implications: This hypothesis unifies disparate observations about autism pathophysiology and suggests that anti-inflammatory interventions targeting the TNF-α pathway may have therapeutic potential, particularly when administered early in neurodevelopment.

Abstract: Background: Burnout among university students is a growing mental health concern, particularly during and after the COVID-19 pandemic. Academic, psychological, social, and individual factors contribute to burnout, but comprehensive synthesis across studies is limited. Methods: A systematic literature review was conducted following PRISMA guidelines. Scopus-indexed articles published between 2020 and 2025 were analyzed. Twenty-five empirical studies examining factors influencing burnout among university students were included. Key study characteristics, outcome variables, and associated factors were extracted and synthesized thematically. Results: Prevalence of burnout ranged from 38% to over 60% among university students. Academic factors such as high study load, curriculum demands, and prolonged study hours were common risk factors. Psychological factors including stress, anxiety, and depression also contributed to higher burnout levels. Protective factors included resilience, self-efficacy, social support, and academic engagement. Emerging challenges such as problematic social media use and digital distractions further exacerbated burnout by increasing mental fatigue, reducing concentration, and impairing sleep quality. Conclusion: Comprehensive institutional strategies including mental health support, workload management, resilience-building programs, promotion of social support, and interventions to reduce digital distractions are essential to mitigate burnout and promote student well-being. Future research should focus on longitudinal and experimental studies to evaluate intervention effectiveness across diverse educational contexts.

Abstract: Generative models have achieved remarkable success in producing realistic images and short video clips, but existing approaches struggle to maintain *persistent worldcoherence over long durations and across multiple modalities. We propose Multimodal Supervisory Graphs (MSG), a novel framework for world modeling that unifies geometry (3D structure), identity (consistent entities), physics (dynamic behavior), and interaction (user/agent inputs) in a single abstract representation. MSG represents the environment as a dynamic latent graph, factorized by these four aspects and trained with cross-modal supervision from visual (RGB-D), pose, and audio streams. This unified world abstraction enables generative AI systems to maintain consistent scene layouts, preserve object identities over time, obey physical laws, and incorporate interactive user prompts, all within one model. In our experiments, MSG demonstrates superior long-term coherence and cross-modal consistency compared to state-of-the-art generative video baselines, effectively bridging the gap between powerful short-term video generation and persistent, interactive world modeling. Our framework outperforms prior methods on metrics of identity consistency, physical plausibility, and multi-view geometry alignment, enabling new applications in extended reality and autonomous agent simulation.

Abstract: Genetic variation underlies the capacity of populations to adapt, yet what drives how this variation is generated and maintained in natural populations remains poorly understood. Fundamental processes such as mutation, ploidy, and recombination are known to shape genetic variation and adaptive potential but are typically studied in isolation and under controlled laboratory conditions. How these processes act together under varying environmental conditions to structure genetic variation across complex natural populations remains unresolved. In yeasts, these processes are dependent on reproductive mode, ploidy shifts, and environmental stressors which jointly shape genomic stability and adaptive potential. Here we review our current knowledge on the roles of mutation, ploidy, and recombination in adaptation in the model yeasts Saccharomyces cerevisiae and the human pathogenic Cryptococcus. We highlight heterogeneity in mutation rates, recombination, and ploidy states across strains, environments, and populations, challenging the assumption that these parameters are uniform. We argue that fluctuating environments, increasingly driven by climate change, are likely to intensify interactions among these processes in ways that remain difficult to predict. Integrating population genomics with ecologically realistic frameworks will be essential for understanding natural evolutionary dynamics and anticipating fungal adaptation and disease emergence.

Abstract: Background/Objectives: Tai Chi (TC) practice has been shown to have positive effects on the physical, psychological, and cognitive health of older adults. However, dis-crepancies persist regarding its effectiveness compared to strength training (ST). The aim of this study was to determine the impact of TC training compared to ST on phys-ical performance, body composition, cognitive function, and psychological well-being in older adults. Methods: A quasi-experimental study was conducted with a conven-ience sample of 68 women ≥60 years, divided into three groups: (i) Tai Chi Group (TCG) n=26; (ii) Strength Training Group (STG) n=21; and (iii) Control Group (CG) n=21. The TC and STG groups performed physical training four days a week, 60min/day, for six months. All participants were assessed for physical performance (FP), body composition, cognition, and psychological well-being before and after the intervention. Results: TCG showed statistically significant positive changes compared to CG after the intervention in the following physical fitness tests: 4-meter walk (base-line, 4.7 ± 2.2; post, 3.7 ± 0.9, p = 0.01); chair stand-up and sit-down (baseline, 13.2 ± 4; post, 9.5 ± 3.2, p = 0.021). Similarly, the TCG group showed a significant increase in handgrip strength (baseline, 19.8 kg; post, 20.9 kg, p = 0.02), along with a reduction in body fat percentage (baseline, 49.2%; post, 45.8%, p = 0.045); an increase in skeletal muscle mass (baseline, 16.3 kg; post, 18.0 kg, p = 0.0001); and skeletal muscle mass in-dex (p = 0.001). Furthermore, in the TCG showed an increase in psychological well-being (+15%) and a decrease in depressive symptoms (-12.5%; p< 0.05). Conclu-sion: Our findings suggest that Tai Chi has a better effect than strength training on physical performance, body composition, and hand strength in older adults living in the community. It also helps maintain cognitive function and improve depression and well-being.

Abstract: Traditional e-commerce visualization relies on static 3D spins or pre-rendered videos, which fail to convey material properties such as stiffness, flexibility, or sole compression. This lack of tactile feedback creates a "trust gap" for online buyers. In this paper, we introduce PhysiGen, a "What If?" viewer that allows users to apply virtual forces to product models. Leveraging a novel Action-Conditional Reconstruction technique, our system utilizes a physics-informed world model to generate short video sequences of deformation (e.g., shoe twisting, foam compression) based on user input. We demonstrate that this approach significantly increases buyer confidence by bridging the "tactile gap" in online shopping, achieving a 45% increase in user engagement compared to static viewers.

Abstract: Ion channels in biological membranes often form spatially localized clusters that exhibit cooperative gating behavior, where the activity of one channel can modulate the opening probability of its neighbors. Understanding such inter-channel interactions is crucial for elucidating the molecular mechanisms underlying complex electrochemical signaling and for advancing channel-targeted pharmacology. In this study, we introduce a simplified stochastic model of multi-channel gating that enables systematic analysis of cooperative phenomena under controlled conditions. Two complementary information-theoretic measures, i.e., Shannon entropy and Sample entropy, are applied to simulated multi-channel datasets to quantify the degree and modality of inter-channel cooperativity. The analyzed signals include idealized total current traces and the corresponding dwell-time sequences of channel cluster states. We demonstrate that the dependence of Shannon entropy calculated for the idealized cluster currents on cluster size distinguishes non-cooperative from cooperative dynamics. Similarly, the Sample entropy of dwell-time series is also a potent indicator of inter-channel cooperation. Additionally, this metric provides enhanced sensitivity to temporal regularities in dwell-time data. The observed entropic signatures allow for classification of clusters according to the strength and mode of inter-channel coupling (non-, positively-, and negatively-cooperative). Thus, they extend a general analytical framework for interpreting multi-channel recordings. These findings, based on our simple model of channel cluster, establish entropy-based analysis as a promising approach for probing real collective gating in ion channel systems or simple biomimetic multi-nanopore devices, where some deviations from the idealized approach are expected.

Abstract: This study aims development of wood-based particleboard contributing to resource, environmental and health impact issues. Conventional particleboard industry uses synthetic, mostly formaldehyde-based adhesives concerning environmental, health and utilization risks. Due to the increase of prices, restrictions and competition in wood processing industry the issue of biomass resources for particleboard production gains another primary importance. Responding to the outlined issues the study investigates suitability of available sawdust resources from production residues of cellular wood materials and recycled particleboards combined with natural suberinic acids as binder derived from birch outer bark. Impact of furnish structure, binder content (15–21%), pressing temperature (190–220 ℃), pressing rate (0.9–1.7 min/mm) and density (650–850 kg/m3) on the obtained particleboard properties was evaluated. Results show that it is possible to achieve requirement values proposed for boards for use as interior fitments including furniture according to EN 312, Type P2 for thickness swelling (≤ 17%) and internal bonding (≥ 0.40 N/mm2). The bending properties of the obtained particleboards are very close to the requirement values (MOE ≥ 1800 N/mm2, MOR ≥ 11 N/mm2), suggesting for the further improvement at the target density levels. Furnish structure, board thickness, density and pressing temperature are the most influencing factors on the achieved properties.

Abstract: In this paper we conduct a model free analysis of the expansion of the universe using stellar luminosity data that is available for redshifts, z< 1.8. Our results lead to an expansion velocity of 6.87  0.36 × 106 ms-1, and Hubble constant of 70.9  3.7 km/s/Mpc consistent with other theories. This analysis leads us to a new theory to explain the expansion of the universe that augments general relativity to create a container within which quantum effects can be explained by treating time as an artefact of a fourth, expanding, spatial dimension. We show that the theory can be applied to not only explain mass creation, the speed of light limit, gravity, black holes without singularities and other macroscopic effects, but also to interpret physical effects at the subatomic level such as wave particle duality and electron spin. It provides a solution to the double slit conundrum and can explain how quantum entangled partners can behave in a quantum way and pass seemingly time-defying information. The theory also provides a quantitative link to the fine structure constant from the expansion velocity.

Abstract: The default mode network (DMN) is a large brain network that is most active when we are at rest or thinking about ourselves. It plays a key role in shaping our sense of self through memory, understanding others, and imagining the future. Recent research shows that problems with the DMN has a major role in anxiety disorders. People with anxiety often show a mix of DMN underconnectivity during rest, which disrupts their internal narrative, and overactivity when facing threats or focusing on tasks. These issues are made worse by poor coordination with the brain’s salience network and executive control networks, creating an imbalance that leads to symptoms like constant rumination, negative memory bias, and unhelpful self-focus. We look at these patterns in generalized anxiety disorder, social anxiety disorder, and show how a disrupted self-narrative and increased self-other monitoring contribute to symptoms. We also discuss how treatments such as cognitive-behavioral therapy, mindfulness, and new medications can help rebalance the DMN and reduce anxiety. While current research has some limitations, focusing on the DMN may help guide the development of better treatments for anxiety disorders.

Abstract:

Baird’s tapir (Tapirus bairdii) plays an important ecological role in Mesoamerican forests as a browser and seed disperser, earning it the nickname of “gardener of the forest”. However, knowledge of its diet composition remains scattered. We reviewed and analyzed the available literature of diet composition of Baird’s tapir throughout its geographic distribution. We compiled evidence from 25 studies related to these topics. Baird’s tapir was found to consume 511 plant taxa belonging to 407 genera and 122 families. Five types of dietary components have been identified: fibre (stems), leaf, fruit, bark and flowers. The influence of seasonality on the tapir’s diet is unclear due to the underestimation of some components (fruit). We identified limitations in the techniques used to determine diet components and study designs. Future research should focus on develop novel techniques to improve the quantification of dietary components. Additionally, the direct and indirect effects of Baird’s tapir’s diet and plant consumption on ecosystem dynamics should be investigated to clearly understand the functional role of this species.

Abstract:

Background/Objectives: Cancer-related cognitive impairment (CRCI) affects 44-75% of cancer survivors, significantly impacting quality of life. While cognitive rehabilitation is recommended as a first-line intervention, implementation remains challenging, with high attrition rates. Acceptability is critical for implementation success yet remains understudied. This study developed and validated the Acceptability of Cognitive Rehabilitation Interventions Survey - Cancer Survivors (ACRIS-CS) and examined prospective acceptability among Portuguese cancer survivors. Methods: A web-based cross-sectional study was conducted with 154 non-central nervous system (non-CNS) cancer survivors (94.8% female; 72.7% breast cancer; mean age 47.28 years, SD = 8.96). Acceptability was assessed using the newly developed 11-item ACRIS-CS, grounded in the Theoretical Framework of Acceptability. Psychometric properties were evaluated through exploratory factor analysis (EFA) and internal consistency. Multiple regression analyses explored factors associated with acceptability. Results: EFA identified three factors explaining 68.70% of the variance: (1) affective attitude and perceived effectiveness, (2) perceived benefits and self-efficacy, and (3) perceived burden. Internal consistency was acceptable (α = 0.85). Survivors reported high prospective acceptability (mean = 67.36/100), with 21.4% scoring above 75. Affective attitude/effectiveness showed the highest ratings (mean = 75.43), whereas perceived burden was moderate (mean = 49.35). Being in active treatment and having prior knowledge of CRCI predicted higher acceptability (R² adjusted = 0.113). Conclusions: The ACRIS-CS is a valid and reliable measure of prospective acceptability for cognitive rehabilitation among cancer survivors. High acceptability indicates strong receptivity, while concerns about burden highlight the need for flexible delivery formats. By identifying survivors who may be less receptive before treatment begins, the ACRIS-CS can support the integration of cognitive rehabilitation into survivorship care and inform tailored strategies—such as targeted psychoeducation—to enhance adherence and improve clinical outcomes.

Abstract: Synaptic plasticity relies on precise spatial and temporal compartmentalization of signaling within dendritic spines, presynaptic terminals, and axonal domains. This compartmentalization is progressively reinforced by experience through activity-dependent remodeling of spine geometry, cytoskeletal scaffolds, calcium handling, and local protein synthesis, allowing plasticity signals to remain localized and terminate appropriately. Here, a unifying framework is proposed in which neurodegenerative diseases emerge when the capacity to maintain and renew these compartments declines. In this state, plasticity induction remains largely preserved, but signaling becomes spatially diffuse and temporally prolonged, imposing chronic structural and energetic stress on synapses and axons. Proteins such as tau and α-synuclein, which normally support cytoskeletal organization and dynamic phase-separated assemblies, become destabilized under these conditions leading to pathological aggregation. This framework provides an explanation for early synaptic dysfunction, selective neuronal vulnerability, long presymptomatic phases, network-level disease propagation, the protective effects of education and cognitive engagement, and the limited efficacy of proteinopathy centric therapeutic strategies. Neurodegeneration is thus best conceptualized as a failure of experience-built synaptic compartmentalization, with protein aggregation arising downstream of this primary vulnerability.

Abstract: The Supra-Omega Resonance Theory (SORT) is presented as a closed structural architecture that unifies multiple scientific domains under an invariant mathematical core. The framework is constructed around a finite and closed set of 22 idempotent resonance operators, a global consistency projector, and a calibrated projection kernel. Together, these elements define a mathematically frozen architecture that admits no arbitrary extensions and precedes empirical integration by design. Version 6 of SORT establishes architectural completion. The operator algebra is closed under composition, global consistency is enforced via a light-balance condition, and validation bounds are defined as invariant thresholds. The same mathematical core is realized across distinct domains, including cosmology, artificial intelligence systems, quantum systems, and complex systems, each interpreting the invariant structure through domain-specific semantics while preserving algebraic identity. Empirical confrontation is positioned as a subsequent phase rather than a present objective. The decision to complete the architecture prior to data integration is methodological, ensuring that future empirical validation is reproducible, unambiguous, and structurally grounded. The MOCK v4 environment enforces deterministic execution, cryptographic reproducibility, and layered consistency verification as architectural features rather than auxiliary tooling. This article constitutes a programmatic statement for the SORT research program. It documents a structurally complete theory architecture prepared for empirical validation while remaining independent of any specific phenomenological application.

Abstract:

Background & Objectives: Venous thromboembolism (VTE) is a major cardiovascular complication in cancer patients and leading cause of morbidity and mortality. The aim of the study was to evaluate the incidence, timing, clinical predictors, and management of VTE in patients with breast cancer (BC), undergoing oncological therapy, and to propose a risk-adapted strategy for thrombosis monitoring and prevention. Methods: In this retrospective single-center study, 116 women with histologically confirmed BC (stages I–IV) treated between 2021 and 2024 were included. Patients were divided according to the occurrence of objectively confirmed VTE. Clinical characteristics, comorbidities, laboratory parameters, cancer-related factors, and treatment modalities were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of VTE. Results: VTE occurred in 25 patients (21.6%), predominantly within the first 12 months after cancer diagnosis. Patients who developed VTE were significantly older and more frequently had hypertension, dyslipidemia, hyperglycemia, anemia, and leukocytosis. Multivariate analysis identified age≥55 years, poor performance status (ECOG ≥3), and elevated glucose level as independent predictors of VTE. Deep vein thrombosis of the lower and upper extremities was the most common manifestation (52%), while pulmonary embolism was present in 24% of cases, either alone or in combination (20%). Direct oral anticoagulants were the most frequently used long-term anticoagulant therapy. Conclusions: VTE is a clinically relevant and relatively frequent complication in patients with BC, particularly during the early period of anticancer treatment. Patient-related and metabolic factors play a key role in thrombosis risk, underscoring the need for individualized, risk-adapted approaches to VTE prevention and monitoring in these populations.

Abstract: On the basis of the isomorphic algebraic structures of the field of complex numbers ℂ and the 2-dimensional Euclidean field of real vectors V₂, in terms of identical geometric products of elements, this paper brings integral identities for scalar and vector fields in V₂, which are vector analogues of the well-known integral identities of complex analysis. Consequently, in this paper, Theorem 1., which is a generalized fundamental theorem of integral calculus in the field V₂, is the vector analogue of the Cauchy theorem of complex analysis. Therefore, special attention is paid to the vector analogue of Cauchy's calculus of residues in the field V₂. Finally, at the very end of the paper, the algebraic structure of the 3D field of vectors V₃ is presented, as well as the corresponding fundamental integral identities.

Abstract: High-fidelity telepresence requires the reconstruction of photorealistic 3D avatars in real-time to facilitate immersive interaction. Current solutions face a dichotomy: they are either computationally expensive multi-view systems (e.g., Codec Avatars) or lightweight mesh-based approximations that suffer from the "uncanny valley" effect due to a lack of high-frequency detail. In this paper, we propose Mono-Splat, a novel framework for reconstructing high-fidelity, animatable human avatars from a single monocular webcam video stream. Our method leverages 3D Gaussian Splatting (3DGS) combined with a lightweight deformation field driven by standard 2D facial landmarks. Unlike Neural Radiance Fields (NeRFs), which typically suffer from slow inference speeds due to volumetric ray-marching, our explicit Gaussian representation enables rendering at >45 FPS on consumer hardware. We further introduce a landmark-guided initialization strategy to mitigate the depth ambiguity inherent in monocular footage. Extensive experiments demonstrate that our approach outperforms existing NeRF-based and mesh-based methods in both rendering quality (PSNR/SSIM) and inference speed, presenting a viable, accessible pathway for next-generation VR telepresence.

Abstract: Diminished Reality (DR)—the ability to visually remove real-world objects from a live Augmented Reality (AR) feed—is essential for reducing cognitive load and decluttering workspaces. However, existing techniques face a critical challenge: removing an object creates a visual void ("hole") that must be filled with a plausible background. Traditional 2D inpainting methods lack temporal consistency, causing the background to flicker or slide as the user moves. In this paper, we propose Clean-Splat, a novel framework for real-time, multi-view consistent object removal. We leverage 3D Gaussian Splatting (3DGS) for scene representation and integrate a View-Consistent Diffusion Prior to hallucinate occluded background geometry and texture. Unlike previous NeRF-based inpainting which is prohibitively slow, our method updates the 3D scene representation in near real-time, enabling rendering at >30 FPS on consumer hardware. Extensive experiments on real-world cluttered scenes demonstrate that Clean-Splat achieves state-of-the-art perceptual quality (LPIPS) and temporal stability compared to existing video inpainting approaches.

Abstract: The purpose of this study is the exploration of the catalytic performance of ZSM-5 zeolite produced from iron rich fly-ash without further addition of iron sites, in the removal of paracetamol through heterogenous Fenton reaction. The structural and textural characterization by powder X-ray diffraction and N2 adsorption isotherms showed that pure ZSM-5 phase was synthesized, but lower crystallinity and textural parameters were obtained when confronting with commercial ZSM-5. The XPS analysis revealed the presence of significant amounts of iron as well as yttrium, which increased the electronic properties of the samples surface, when compared with iron impregnated commercial ZSM-5. The catalytic reaction was followed through UV-spectroscopy and kinetic models were applied to the data, with the best fit obtained for pseudo-first-order model. All fly ash-based zeolites present enhanced paracetamol removal when compared with commercial iron loaded ZSM-5 which may be attributed to the more disorganized structure, able to accommodate large paracetamol species (dimers). On the other hand, the effect of yttrium on the electronic properties of iron sites may increase the formation of ●OH radicals, thus increasing the removal rate of paracetamol.