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.

Abstract: Climate fluctuations are expected to drive a decline in the growth of many conifer and broadleaf species, especially in the Mediterranean region, where these species grow at or very near the southern limits of their distribution. Such trends have important im-plications not only for forest productivity but also for plant diversity, as shifts in spe-cies performance may alter competitive interactions and long-term community com-position. Using tree-ring data sourced from two Abies cephalonica stands with different elevation in Mount Parnassus in Central Greece, we evaluate the growth responses of the species to climatic variability employing a dendroecological approach. We hy-pothesize that radial growth at higher elevations is more strongly influenced by cli-mate variability than at lower elevations. Despite the moderate to relatively good common signal indicated by the expressed population signal (EPS: 0.645 for the high-altitude stand and 0.782 for the low-altitude stand), the chronologies for both sites preserve crucial stand-level growth patterns, providing an important basis for ecological insights. The calculation of the Average Tree-Ring Width Index (ARWI) for both sites revealed that fir in both altitudes exhibited a decline in growth rates from the late 1980s to the early 1990s, followed by a general recovery and increase throughout the late 1990s. They also both experienced a significant decline in growth between approximately 2018 and 2022. The best-fit model for annual ring-width vari-ation at lower elevations was a simple autoregressive model of order one (AR1), where growth was driven exclusively by the previous year’s growth (p < 0.001). At the higher elevation, a more complex model emerged: while previous year’s growth remained significant (p < 0.001), other variables such as maximum growing season temperature (p = 0.041), annual temperature (inverse effect, p = 0.039), annual precipitation (p = 0.017), and evapotranspiration (p = 0.039) also had a statistically significant impact on tree growth. Our results emphasize the prominent role of carry-over effects in shaping their annual growth patterns.

Abstract: Background: Anorexia nervosa (AN) may require nasogastric tube (NGT) feeding when oral intake is insufficient. Evidence on psychological impact and prognostic correlates of NGT use in adolescents affected with AN is limited.Methods: fifty-seven adolescent inpatients (96.5% female; age range 12–18 years; mean age 15.0± 1.51 years) affected with AN admitted in a child psychiatry ward and treated with NGT renutrition in addition to oral nutrition were included in the study. A 21‑item VAS questionnaire was administered at intake (T0), after NGT introduction (T1), after one week of NGT use (T2) and after NGT dismissal (T3) to assess physical and psychological effects. Participants were also assessed with psychometric measures including personality (TCI), eating psychopathology (EDI‑2), general psychopathology (BDI‑II, SCL‑90‑R, TAS), and family functioning (FAD). The measures were compared between each timepoint with paired t‑tests and ANOVA for repeated measures. Pearson correlations were performed between the VAS scores and psychometric measures.Results: From admission to discharge, weight increased by +3.2 kg and BMI by +1.2 kg/m². Items 1, 3, 4, 6, 15, 18, 20 of the VAS questionnaire items showed significant improvement over time. TCI personality traits, EDI-2 eating and BDI, SCL-90 and TAS general psychopathology, and FAD family functioning were related to NGT perception by the AN adolescents. Conclusions: NGT was helpful in the weight progression during inpatients treatment. It was generally well tolerated, with progressive improvement in psychological and physical discomfort during treatment. The meaningful associations with specific psychometric features suggest the possibility to tailor the NGT use based on adolescent characteristics. Multidisciplinary care and tailored psychoeducation may enhance acceptance.

Abstract: This paper presents Sem4EDA, an ontology-driven and rule-based framework for automated fault diagnosis and energy-aware optimization in Electronic Design Automation (EDA) and Internet of Things (IoT) environments. The escalating complexity of modern hardware systems, particularly within IoT and embedded domains, presents formidable challenges for traditional EDA methodologies. While EDA tools excel at design and simulation, they often operate as siloed applications, lacking the semantic context necessary for intelligent fault diagnosis and system-level optimization. Sem4EDA addresses this gap by providing a comprehensive ontological framework developed in OWL 2, creating a unified, machine-interpretable model of hardware components, EDA design processes, fault modalities, and IoT operational contexts. We present a rule-based reasoning system implemented through SPARQL queries, which operates atop this knowledge base to automate the detection of complex faults such as timing violations, power inefficiencies, and thermal issues. A detailed case study, conducted via a large-scale trace-driven co-simulation of a smart city environment, demonstrates the framework’s practical efficacy: by analyzing simulated temperature sensor telemetry and Field-Programmable Gate Array (FPGA) configurations, Sem4EDA identified specific energy inefficiencies and overheating risks, leading to actionable optimization strategies that resulted in a 23.7% reduction in power consumption and 15.6% decrease in operating temperature for the modeled sensor cluster. This work establishes a foundational step towards more autonomous, resilient, and semantically-aware hardware design and management systems.

Abstract: Non-line-of-sight (NLOS) propagation poses a significant challenge to achieving high-accuracy ultra-wideband (UWB) indoor positioning. To address this issue, this study investigates solutions from two complementary perspectives: NLOS identification and error mitigation. First, an NLOS signal classification model is proposed based on multidimensional statistics of the channel impulse response (CIR). The model incorporates an attention mechanism and an improved snake optimization (ISO) algorithm, achieving significantly enhanced classification accuracy and robustness. Building on this foundation, a UKF–BiLSTM dual-directional mutual calibration framework is proposed to compensate for NLOS errors dynamically. The framework embeds the constant turn rate and velocity (CTRV) motion model within an unscented Kalman filter (UKF) to enhance trajectory modeling. It establishes a bidirectional correction loop with a bidirectional long short-term memory (BiLSTM) network. Through the synergy of physical constraints and data-driven learning, the framework adaptively suppresses NLOS errors. Experimental results demonstrate that the proposed classification model and positioning framework significantly outperform state-of-the-art methods, thereby providing a systematic solution for high-precision and robust UWB positioning in complex indoor environments.

Abstract: Gender incongruence significantly impacts the family system, yet the subjective experiences of caregivers remain relatively underexplored. This narrative review synthesizes contemporary evidence regarding psychological distress, emotional burden, and quality of life among caregivers of transgender and gender-diverse individuals. A targeted literature search of PubMed, Scopus, PsycInfo, and Google Scholar (2015-2025) was conducted, identifying 16 studies for thematic synthesis. Results indicate that caregivers consistently report elevated emotional distress, characterized by chronic anxiety, hypervigilance, and ambiguous loss. This burden is primarily driven by prolonged exposure to uncertainty, the weight of complex medical decision-making - particularly regarding fertility and hormone therapy - and vicarious minority stress stemming from social stigma and systemic barriers. Notably, distress is often intensified by sociopolitical climates rather than the transition process itself. Conversely, access to peer support networks, healthcare relationships, and engagement in advocacy emerged as vital protective factors facilitating resilience and adaptive meaning-making. We can conclude that caregiver well-being is a multifaceted process deeply embedded in social and institutional contexts. These findings underscore the necessity of integrated, family-centered medical-psychological models that explicitly support caregivers to ensure more equitable and effective gender-affirming care pathways.