Abstract: In people with dementia, sleep disturbances and circadian rhythm disruption, as well as heightened stress responses and behavioral and psychological symptoms of dementia (BPSD), constitute major drivers of nighttime agitation, delirium, falls, infections, emergency visits, hospitalization, and institutionalization, thereby sharply increasing caregiving burden and healthcare and long-term care costs. At the same time, conventional sleep hygiene and BPSD management approaches tend to rely on complex self-management models that presuppose “correct instruction,” which are prone to implementation failure in dementia due to impairments in executive function, attention, and memory. The purpose of this paper is not to present new efficacy data, but rather to reorganize existing evidence on sleep and stress/BPSD management from the perspective of “core active ingredients,” and to propose a reconfigured intervention framework that can realistically function in dementia care settings: the Dementia-adapted Sleep & Stress Management (D-SSM) framework. The proposed program retains three minimal core elements: (1) anchoring daily rhythms (fixed wake time and morning light exposure); (2) proactive removal of triggers for nighttime agitation and delirium (e.g., pain, constipation, dehydration, sleep deprivation); and (3) consistent, reassurance-oriented communication and standardized responses based on the DICE approach. This design suppresses reliance on complex self-judgment and multi-stage behavior change tasks. Future evaluation should prioritize implementation-focused outcomes that are directly linked to costs—such as nighttime caregiving frequency, incidence of delirium and BPSD, psychotropic medication use, and emergency visits—rather than focusing exclusively on falls or cognitive indices.

Abstract: In this study, ferulated arabinoxylans (FAXs) were extracted from maize bran by optimizing al-kaline extraction method and explored their purification, identification and antioxidant potential. The current results showed that FAXs yield ranged from 14.7 to 18.9 % from maize bran. It was found that the FAXs were mainly composed neutral sugars including xylose (21–44%), arabinose (12–30%), galactose (2.7-7.4%) and glucose (4.6–9.4%), with an A/X ratio of 0.68–0.74. In addition, FAXs extracts showed significantly (p < 0.05) high content of ferulic acid in bound form as com-pared to free form. Furthermore, biopolymers FAXs possess powerful radical scavenging prop-erties due to their polyphenolic content and structural characteristics. FTIR spectra of maize bran extracted FAXs exhibited the presence of polysaccharide compounds. The corresponding bands were related to glycosidic linkage, which is assigned to the C-OH bend vibration in FAX. In functional characteristics, FAXs showed high water holding capacity, emulsion properties and emulsion stability in all treatments. In current research, FAXs have been comprehensively char-acterized, and several promising applications across the food, pharmaceutical, and agricultural industries can be explored based on these findings.

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Embolization of intracardiac occlusion devices is an uncommon but potentially serious complication requiring interventional radiology management. We report a case of delayed migration of an Amplatzer patent foramen ovale occluder into the infrarenal abdominal aorta. An 18-year-old woman presented with acute abdominal pain one month after percutaneous PFO closure. Contrast-enhanced computed tomography performed for suspected intra-abdominal bleeding incidentally revealed the embolized device in the infrarenal aorta, with preserved renal artery patency. After multidisciplinary evaluation, endovascular retrieval was planned. Via right common femoral artery access, the device was successfully captured using a snare system and removed through a large-bore introducer sheath without complications. Final angiography confirmed normal aorto-iliac patency. This case highlights the importance of cross-sectional imaging and demonstrates that endovascular snare retrieval is a safe and effective first-line treatment for delayed device embolization.

Abstract: Commercial supersonic passenger transport has been absent from global aviation for more than two decades, largely due to regulatory, geographic, and economic constraints. While renewed interest in supersonic travel has emerged with advances in aircraft design, there remains a lack of scalable methods for assessing where such operations could be viable. This study evaluates supersonic feasibility at the route level using a data-driven framework that integrates engineering, regulation, and economics. A global dataset comprising 435 city-pair routes was constructed using aircraft performance estimates, great-circle routing, over-water routing fractions, and demand indicators derived from population and gross domestic product data. Routes were labeled as feasible or unfeasible based on domain-informed criteria, and supervised machine-learning models were trained to learn a continuous feasibility score between 0 and 1. A Decision Tree classifier was used to extract interpretable feasibility rules, while an Extreme Gradient Boosting (XGBoost) classifier provided predictive performance. Model behavior was analyzed using SHapley Additive exPlanations (SHAP). The results show that over-water routing fraction is the dominant determinant of feasibility, followed by time savings and great-circle distance, with demand contributing in marginal cases. The framework produces a ranked set of candidate routes as well as a predictive engine for future routes.

Abstract: This paper proposes the Computable Structure of National Narrative (CSNN) framework, treating state-level political texts as engineering-oriented governance systems. Using President Xi Jinping's 2026 New Year Address as a case study, it constructs a multi-level variable and causal pathway model encompassing ‘governance input—transformation mechanism—governance output’. The research integrates computational content analysis, sentiment analysis, and semantic network analysis to transform the text into a reproducible variable system: independent variables encompass development/innovation, people's livelihoods, culture, discipline, and external governance narratives; mediating variables include policy perceptibility, emotional resonance, and governance credibility; dependent variables are governance legitimacy and social cohesion; external uncertainty is introduced as a moderating factor. Results reveal: national narratives exhibit stable functional paragraph sequencing; sentiment is not an end-stage effect of communication but a key mediator in generating governance legitimacy; governance legitimacy displays structural output characteristics, dependent on the convergence of multiple mediating pathways. This study contributes a computable, interpretable, and transferable toolchain for political narrative research, providing a reproducible empirical framework for cross-year, cross-national, and multimodal expansion.

Abstract: Unlike skeletal Class I and II patients, the application of maxillomandibular advancement (MMA) in skeletal Class III patients with obstructive sleep apnea (OSA) is not well documented. The aim of this scoping review was to explore the variations and outcomes of MMA techniques in this unique subgroup. A comprehensive search of PubMed, Embase, Cochrane and LILACS databases were conducted for articles published up to May 2025. Nine studies met the inclusion criteria. Three main variations of MMA were identified: (1) Bimaxillary advancement, which provides the most significant airway enlargement across all pharyngeal regions but carries the highest risk of facial aesthetic distortion; (2) Maxillary advancement with mandibular auto-rotation, a less invasive option suited for patients with isolated maxillary retrusion and symmetrical mandibular anatomy; (3) Maxillary advancement with mandibular setback, which addresses aesthetic concerns in patients with mandibular excess but may compromise oropharyngeal airway space. All variations were reported to be effective in treating OSA but with different considerations. Surgical planning for skeletal Class III patients with OSA should be individualized based on craniofacial morphology, anatomical site of airway obstruction, and aesthetic considerations. A decision flowchart was shared in this study.

Abstract: The human connectome displays nontrivial large-scale organization despite being assembled through decentralized, local biological processes. Most generative models reproduce selected connectomic features by invoking global optimization principles, predefined wiring targets or developmental templates. This leaves unresolved which properties of the connectome are genuine consequences of local interactions and which require additional mechanisms operating beyond local scales. We introduce a simulation framework conceptually aligned with recent theoretical results showing that global coherence can arise from local compatibility alone. Networks are generated exclusively through local constraints: nodes interact within bounded spatial neighborhoods, edge formation is probabilistic and local, and incompatible configurations are suppressed without reference to any global objective, target topology, or long-range coordination. Ensembles of simulated networks are compared with empirically reported human connectome descriptors using quantitative statistics and qualitative structural criteria. Several mesoscopic properties, including high clustering, modular organization, motif enrichment and short-range wiring bias, emerge robustly under local interaction rules and compatibility. In contrast, other features such as absolute connectivity scale, rich-club organization and long-range hub-to-hub coupling, systematically diverge from empirical values. Unlike optimization-based or template-driven models, our framework does not aim to reproduce the full connectome. Instead, it identifies which properties are structurally implied by locality and which remain underdetermined, providing a complementary explanatory perspective. Our results support a principled classification of connectome properties according to their dependence on local compatibility constraints, clarifying the explanatory scope and limits of decentralized network formation, and suggesting several directions for further work.

Abstract: Industrial Internet of Things (IIoT) and SCADA-connected networks face disruptive DDoS events where detection must be both accurate and low-latency at the edge. This study benchmarks deep reinforcement learning (DRL) for real-time binary attack detection and proposes a Proximal Policy Optimisation (PPO) detector tailored for deployment. Five DRL agents—DQN, Double DQN, Duelling DQN, DDPG, and PPO—are trained under a unified preprocessing pipeline (automatic label mapping, numeric-feature selection, robust scaling, and class balancing) and evaluated on three representative datasets: KDDCup99, CIC-DDoS2019, and Edge-IIoTset. We report accuracy, precision/recall, F1-score, false-positive/false-negative rates, and AUC-ROC, alongside CPU latency to reflect operational constraints. Across all datasets, PPO achieves the best accuracy–latency trade-off, reaching 99.3% accuracy on KDDCup, 99, 93.7% on CIC-DDoS2019, and 95.5% on Edge-IIoTset, while maintaining inference latency below 0.23 ms per sample. PPO also converges faster and is more sample-efficient than value-based alternatives. For practical adoption, the trained PPO policies are exported to ONNX (one model per dataset), enabling lightweight, PyTorch-independent inference on resource-constrained industrial gateways.

Abstract: Background: The antimicrobial peptide LL-37 has emerged as a key mediator linking innate and adaptive immunity and has been implicated in the pathogenesis of immune-mediated inflammatory diseases. While circulating levels of LL-37 and anti-LL-37 antibodies have been investigated in several conditions, their presence and relevance within the local joint microenvironment remain insufficiently explored. This study aimed to evaluate anti-LL-37 antibodies in synovial fluid from patients with psoriatic arthritis (PsA), rheumatoid arthritis (RA), and knee osteoarthritis (GoA), and to analyze their associations with pro-inflammatory cytokines. Methods: Synovial fluid samples were obtained from patients with PsA, RA, GoA, and from healthy controls. Levels of anti-LL-37 antibodies, IL-1β, IL-6, and IL-23 were measured using enzyme-linked immunosorbent assay (ELISA). Correlation analyses were performed to assess relationships between anti-LL-37 antibodies and cytokine levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of anti-LL-37 antibodies. Results: Anti-LL-37 antibody levels were significantly elevated in synovial fluid from patients with PsA compared to RA, GoA, and healthy controls. Patients with RA exhibited lower anti-LL-37 levels despite pronounced elevations of IL-1β and IL-6. In GoA, anti-LL-37 concentrations were comparable to those of healthy controls. A strong positive correlation between anti-LL-37 antibodies and IL-23 was observed in PsA, whereas correlations with IL-1β and IL-6 were more prominent in RA. ROC analysis demonstrated moderate diagnostic accuracy of anti-LL-37 antibodies in distinguishing PsA from healthy controls, but limited utility in RA and GoA. Conclusions: The findings support a disease-specific role of anti-LL-37 antibodies in the immunopathogenesis of psoriatic arthritis and highlight their association with the IL-23/Th17 axis within the synovial microenvironment. Anti-LL-37 antibodies may serve as a complementary biomarker for PsA and provide further insight into the distinct immunological mechanisms underlying inflammatory versus degenerative joint diseases.

Abstract: The convergence characteristics of an online gradient learning technique for training Pi–Sigma higher-order neural networks under a smoothed L1 regularization framework with adaptive momentum are examined in this research. Although Pi-Sigma networks can effectively represent high-order nonlinear interactions, nonconvexity, parameter coupling, and noise sensitivity in online contexts make training them difficult. In order to overcome these problems, we avoid the nondifferentiability of the traditional L1 norm while promoting sparsity by using a differentiable approximation of the L1 penalty. Furthermore, an adaptive momentum term is added to speed up convergence and stabilize weight updates. We construct important lemmas that describe the behavior of the smoothed regularizer and momentum dynamics, make modest assumptions on the activation functions, data sequence, and learning parameters, and create a unified mathematical model for the suggested learning rule. These findings allow us to demonstrate that the online approach guarantees the weight sequence's boundedness, the gradients' convergence to zero, and the corresponding energy function's monotonic reduction. In comparison to existing models, numerical studies show that the suggested approach produces stable convergence, enhanced sparsity, and decreased gradient oscillation. Empirical plots of loss evolution, gradient norms, and weight norms are used to validate the theoretical results. The robustness of the suggested learning framework and its applicability for nonlinear function approximation and online learning tasks in higher-order neural networks are highlighted by the agreement between theoretical results and actual data.

Abstract: In people with dementia, malnutrition and dehydration are strongly associated with declines in physical function, increased susceptibility to infection, delirium, worsening behavioral and psychological symptoms of dementia (BPSD), and earlier hospitalization and institutionalization. Epidemiological and clinical studies in older adults and people with dementia consistently demonstrate that adequate intake of energy, protein, and fluids does not treat dementia itself, but plays a critical role in suppressing reversible factors that can rapidly exacerbate disease progression.However, many conventional nutrition education and dietary interventions implicitly assume cognitive abilities such as self-management of food intake, understanding of nutrients, and judgment in food selection. For people with dementia, these assumptions often render implementation and continuation difficult. As a result, an “implementation gap” emerges in which theoretically valid nutritional interventions fail to function effectively in real-world clinical and caregiving settings.The purpose of this paper is to reconceptualize dietary and nutritional interventions for people with dementia by systematically separating (1) core active ingredients from (2) elements that generate excessive cognitive and operational burden. By integrating existing guidelines, intervention studies, and clinical epidemiological research, we propose an implementation-adapted minimal model consisting of: (1) ensuring one protein item at each meal, (2) daily fluid intake of 1.2–1.5 liters, and (3) meal environment design that does not require choice or judgment.This model does not aim to directly modify the neurodegenerative pathology of dementia. However, by suppressing “progression accelerators” such as malnutrition, dehydration, infection, delirium, and BPSD, it offers high practical utility for both clinical practice and long-term care policy.

Abstract: This paper examines the Lambert conformal conic (LCC) projection. Although its equations are well established, they are rederived here because a new notation, V, defined as the reciprocal of the commonly used U, is introduced to simplify the expressions. Using the resulting distortion formulas, the conditions determining whether the projection has two, one, or no standard parallels are obtained. To identify an optimal LCC configuration, we adopt a criterion requiring that the local linear scale factors at the two boundary parallels be equal, and that the maximum scale factor exceed 1 by the same amount that the minimum falls below 1. Applying this criterion to the territory of Bulgaria, we compute a new, optimized pair of standard parallels, which constitutes the main contribution of this study.

Abstract:

Multimessenger constraints tightly bound the gravitational-wave speed to be luminal, posing a strong filter for modified gravity. We develop a symmetry-selected Palatini framework with torsion where exact quadratic-order luminality is built in (not tuned). The observable sector is defined by (i) a scalar PT projector keeping scalar densities real and parity-even, and (ii) projective invariance implemented via a non-dynamical Stueckelberg compensator entering only through its gradient. Under posture (A1–A6), we prove: (C1) torsion is algebraically unique and reduces to a pure-trace form aligned with the compensator gradient; (C2) three PT-even constructions—rank-one determinant, closed-metric deformation, and CS/Nieh–Yan—are bulk-equivalent up to improvement terms; (C3) a coefficient-locking identity enforces K=G for tensor modes on admissible domains, yielding cT=1 with two propagating polarizations. Beyond leading order, the framework predicts a falsifiable correction δcT²(k)=b k²/Λ² (k≪Λ), implying slope 2 in log–log fits across PTA/LISA/LVK bands. To support reproducibility, a public repository provides figure generators, coefficients, and tests directly validating (C1)–(C3).

Abstract: White matter hyperintensities (WMH) exhibit distinct spatial patterns, with differing prevalence and morphology in periventricular and deep regions. SPAN-WMH incorporates anatomical knowledge by generating probabilistic structural priors that reflect these region-specific distributions and embedding them into a spatially adaptive attention mechanism. The network modulates feature responses according to the anatomical context, enabling improved discrimination of subtle, region-dependent lesion patterns. Experiments on 1,100 subjects from WMH2020 show substantial improvements: deep-WMH Dice increases from 0.643 to 0.742 (+15.4%), periventricular Dice rises from 0.821 to 0.884 (+7.7%), and HD95 decreases by 28.3%. Small-region IoU improves by 12.1%, highlighting better detection of scattered deep lesions.

Abstract:

Capsicum species are widely used as ornamental. In the post-production stage the exposure to ethylene causes chlorophyll degradation and the leaves and fruits abscission, which resulting in loss of commercial value. This work aimed to evaluate and select pepper elite lines to ethylene insensitivity and their stability in two years of evaluation. Forty genotypes were evaluated at 48, 72 and 96 hours after exposure to ethylene in two years, with three replicates in an entirely randomized design. The evaluated variables were number of leaves, number of fruits and chlorophyll a and b. The variables were evaluated before the ethylene treatment and the plants were stored in airtight chambers (60L) with 10μL L^-1 ethylene. New evaluations were made at 48, 72 and 96 hours after the exposition. Leaf and fruit abscission were expressed as loss percentage compared to time zero, before ethylene exposure. The data were subjected to analysis of variance. The means were grouped by Scott-Knott criteria (p≤0.01). The more stable lines with insensitivity to ethylene (55.50.4.1.2, 56.26.24.1.4, 56.26.33.1.9, 17.15.48.1.2, 56.26.15.1.5, 56.26.33.1.5, 17.15.4.1.9, 56.26.34.1.2, UFPB284, UFPB58, UFPB393 and UFPB291) must be registered as new cultivars. They can be used to insert ethylene insensitivity into susceptible cultivars.

Abstract: Adolescents with cognitive disabilities face unique developmental, social, and functional challenges that complicate their access to autonomy, education, and participation. Assistive technology (AT) has emerged as a powerful tool to support communication, learning, and daily functioning in this population. However, its deployment introduces complex ethical concerns. This narrative review critically examines the ethical considerations associated with AT use for adolescents with cognitive disabilities, focusing on five key themes: consent and decision-making, autonomy and independence, privacy and data protection, accessibility and usability, and equity in access and implementation.This review screened 50 documents, of which 20 were retained for full inclusion based on their relevance to ethical concerns in the use of assistive technology Key Themes in the Literature or adolescents with cognitive disabilities. Findings highlight the need for adolescent-centered approaches that respect evolving capacities, cultural contexts, and individual agency. Ethical AT implementation must move beyond procedural compliance to foster inclusive, responsive, and participatory practices. This review contributes a structured ethical framework specific to the use of assistive technology (AT) among adolescents with cognitive disabilities, an area that remains underexplored in current literature. While previous studies have discussed general ethical concerns related to AT or disability, few have integrated adolescent developmental theory, rights-based ethics, and practical considerations into a single, coherent review. By organizing ethical issues around five core themes consent and decision-making, autonomy, privacy, accessibility, and equity, this paper advances a more narrative review and adolescent-specific ethical lens for understanding AT implementation. It emphasizes adolescence as a unique developmental stage marked by emerging autonomy, evolving identity, and shifting capacities, all of which are critical to ethical decision-making but are often overlooked in existing research. The review concludes with recommendations for policy development, participatory research, and capacity-building among educators, developers, and caregivers. It calls for ethical reflection to be embedded not only in the design and deployment of AT, but also in training programs and institutional practices. As AT continues to evolve, ethical practices must evolve in tandem, ensuring that technological tools empower rather than marginalize adolescents with cognitive disabilities and that implementation is both developmentally appropriate and socially acceptable.

Abstract: Molecular pattern recognition is ubiquitous in nature, from the primitive chemotaxis systems of bacteria to the highly complex brains of mammals. To date, numerous setups have been developed that mimics such behavior and enable molecules to perform various computational tasks. However, there is still no generalized approach that allows biomolecular systems to achieve the same universality and flexibility in computation as brain structures or artificial neural networks. Molecular commutation is a recently discovered, fundamentally distinct mechanism of biological information processing and storage using weak affinity interactions of virtually any molecules governed by the law of mass action. Using this principle, here, we demonstrate the first universal, dataset-independent two-step methodology for building DNA-based molecular neural networks for solving machine learning tasks. The networks are initially solved as affinity matrices with reasonable-for-real-life constraints using backpropagation-like algorithms. While, these matrices are suitable for any type of biomolecules (DNA, proteins, etc.), we further demonstrate that DNA ensembles can be identified that fit such matrices and allow successful in silico operation of the neural networks. We constructed DNA networks for solving three machine learning benchmark tasks — IRIS flowers classification (IRIS dataset, 4-input, 3-class classification), housing prices prediction (California Housing dataset, 8-input regression), and handwritten digit recognition (MNIST dataset, 784-input, 10-class classification — with performance comparable to classical machine learning algorithms (accuracy for IRIS and MNIST in 80-95 % range). The versatility of the approach, its applicability to arbitrary data, and the complexity of recognizable patterns significantly extends the boundaries of existing views on molecules as computational entities.

Abstract:

Objectives: We investigated the effects of Continuous Positive Airway Pressure (CPAP) on blood pressure (BP) and vigilance in taxi drivers with obstructive sleep apnea (OSA). Methods: Taxi drivers aged ≥60 years were recruited for polysomnography. Those diagnosed with OSA underwent 6 months of CPAP therapy. Baseline and follow-up assessments included 24-hour ambulatory blood pressure monitoring (ABPM) and the psychomotor vigilance test (PVT). Results: Among the 32 participants, 22 (68.8%) were diagnosed with OSA (median age 63.0 [62.0–65.0] years; 21 males). The average CPAP adherence was 3.1±2.3 hours per night, with 23.5% using CPAP for more than 4 hours per night. There were no significant changes in 24-hour mean systolic ABPM (125.9 [116.8–134.9] mmHg to 126.0 [118.3–133.7] mmHg; p=0.93) or reaction times measured by PVT (2.0 [0.0–3.0] lapses to 2.0 [1.0–3.0] lapses; p=0.82) after CPAP therapy. Conclusion: A high prevalence of OSA was observed among taxi drivers. CPAP adherence was suboptimal and did not result in significant improvements in BP or vigilance.

Abstract: HIV infection is a nowadays pathology that affect persons from all of the world. Pathogenesis of the HIV-infection and cancer is a great problem, with a complexity directions in research. More important in HIV infection to patients, is also to take into consideration others things, such as prevention, diagnosis, monitoring, treatment, including control measures. This previously mentioned, should be supported by statistical studies that report on restricted or extended geographical areas, to the level of social class and age. In our written text we try to describe from our opinion, strategies in HIV, infection, status knowing as a social and as a healthcare problem.

Abstract: Background/Objectives: Atrial fibrillation (AF) is closely associated with adverse remodeling of the left atrium (LA). This study evaluated the impact of LA diameter on long-term outcomes following radiofrequency ablation (RFA) of the pulmonary veins and assessed LA and left ventricular (LV) remodeling over a seven-year follow-up period. Methods: A total of 117 patients with symptomatic, drug-refractory AF underwent RFA. Structural remodeling was evaluated using echocardiography. Long-term outcomes were categorized using the Pulmonary Vein Isolation Outcome Degree (PVIOD), a four-level classification reflecting procedural and clinical success. Results: After seven years, 32.5% of patients who achieved successful sinus rhythm maintenance after a single RFA (PVIOD 1) demonstrated significant reverse remodeling of LA and LV. LA diameter decreased from 39.3±0.6 mm to 36.5±0.6 mm (p< 0.001); LV end-diastolic diameter (LVEDD) from 53.1±0.6 mm to 50.9±0.7 mm (p=0.008); LV end-systolic diameter (LVESD) from 34.7±0.8 mm to 32.0±0.1 mm (p=0.005); and LV ejection fraction (LVEF) increased from 56.8±0.8% to 62.1±1.1% (p< 0.001). Among patients with long-term success after multiple procedures (PVIOD 2; 29.1%), LA diameter decreased significantly from 41.9±0.7 mm to 40.2±0.6 mm (p=0.044), without significant ventricular changes. Patients achieving clinical success (PVIOD 3; 14.5%) showed no significant structural changes. Those with procedural and clinical failure (PVIOD 4; 23.9%) exhibited progressive negative remodeling: LA diameter increased from 44.7±0.7 mm to 47.4±0.7 mm (p=0.006); LVEDD from 52.8±0.9 mm to 57.1±0.6 mm (p< 0.001); LVESD from 36.5±1.1 mm to 40.7±1.2 mm (p=0.006); and LVEF decreased from 50.7±1.7% to 43.8±1.8% (p=0.004). Conclusions: Early and successful single RFA performed in patients with normal LA diameter is associated with complete reverse remodeling and prevention of AF recurrence. As LA size increases, the likelihood of achieving durable procedural success decreases, emphasizing the importance of timely intervention before significant left atrial enlargement develops.