Abstract: Epithelial recovery in inflammatory bowel disease (IBD) requires coordinated restoration of mucus, junctional regulation, secretory differentiation, stem-cell renewal and resistance to cellular stress. This critical narrative review examines evidence-supported protein networks spanning epithelial, immune and stromal compartments, with MTG16 positioned within a broader differentiation program. MUC2, TFF3, AGR2 and ZG16 support distinct aspects of mucosal defense; CLDN2, occludin, ZO-1 and long myosin light-chain kinase regulate different dimensions of permeability and repair. Stromal WNT/R-spondin support, ASCL2-dependent dedifferentiation and YAP/TAZ-associated reprogramming replenish damaged epithelium. XBP1, ATG16L1, caspase-8 and GPX4 connect secretory competence and stress resilience to inflammatory susceptibility. IL-22, IL-10, interferon-γ, TNF and amphiregulin have effects determined by cell compartment, cytokine combinations and exposure duration. The same broad repair environment can sustain inflammation, fibrosis or tumor-promoting states. Recent epithelial-memory studies further distinguish transient regeneration from persistent chromatin priming. The central unresolved question is which persistent protein activities, measured during well-documented remission, cause functional deficits and contribute to subsequent disease recurrence. We propose paired protein, chromatin and functional measurements with temporally controlled perturbation and longitudinal clinical validation. The resulting framework connects protein mechanisms to measurable recovery endpoints while separating established experimental findings from proposed analyses.

Abstract: Basalt is a promising geological medium for CO₂ storage because of its potential for permanent mineral trapping, although fluid–rock reactions can alter pore structure and hydraulic properties. This study investigates coupled axial deformation, hydraulic and geochemical evolution of basalt during CO₂-saturated brine flow at 88 °C and approximately 210 bar pore pressure. In situ axial deformation, differential pressure and apparent permeability were monitored continuously, while effluent chemistry, mineral saturation states and pore-structure properties were evaluated. Six axial deformation stages were identified, with a pronounced hydraulic transition after approximately 115 pore volumes (PV) injected. Larger deformation magnitudes coincided with decreasing differential pressure and increasing apparent permeability, and absolute axial strain change was positively correlated with stage-averaged apparent permeability (r = 0.919, R² = 0.8437). Absolute permeability increased from 2.41 to 8.55 mD, while measured porosity increased only slightly from 9.15% to 9.51%. Fe and SiO₂ concentrations generally increased during reactive flow, and late-stage saturation indices indicated thermodynamic favorability for selected secondary phases. Nitrogen adsorption measurements showed changes in accessible pore structure. These results demonstrate concurrent deformation, hydraulic and geochemical evolution and indicate that permeability evolution cannot be explained by changes in bulk porosity alone.

Abstract: We introduce a bitopological version of a Lie group by equipping a smooth Lie group with two possibly distinct compatible group topologies. The purpose is to separate the smooth structure from the global topological structures carried by the underlying group. We define bitopological Lie groups and their morphisms, investigate translations, identity components, products, subgroups and quotient structures, and give several examples. The classical theory of Lie groups is recovered when the two topologies coincide with the topology induced by the smooth structure. We also discuss some directions for further development of bitopological Lie theory.

Abstract: Credit-risk models may become unreliable when longitudinal observations are incomplete and predictive uncertainty is ignored. We propose a Structured Dynamic Bayesian Network and Bayesian Neural Network (Structured DBN + BNN) combining borrower-conditioned latent-state transitions, differentiable filtering, complementary GRU and direct-input encoders, and variational Bayesian discrimination. Training-time masking improves robustness to missing evidence, while reconstruction regularizes the latent states. At inference, Monte Carlo sampling, validation-based temperature scaling, predictive entropy, and mutual information support calibrated prediction and uncertainty-aware triage. On the Default of Credit Card Clients dataset, ten paired seeded evaluations show competitive clean-data discrimination, with an AUROC of 0.7828. Under 30% MCAR missingness, the model achieves an AUROC of 0.7623 and achieves a higher mean AUROC than the principal baselines drawn from recurrent, Bayesian, and Transformer model families; similar robustness is observed under MAR, MNAR, and recent-month removal. At 10% selective coverage, entropy-based ranking reduces the mean error to 3.51%. These findings show that the framework’s main benefit is robust, uncertainty-aware prediction when temporal evidence is incomplete, rather than uniformly superior discrimination on complete data.

Abstract: We ported EASA (Embedded Action Selection Architecture) [1], based on the basal ganglia model of [2], originally validated on a Khepera I with a gripper in a foraging task, to a modern rigid-body physics engine, with actual geometry extracted from the same hardware's robot definition files. The decision circuitry remained unchanged in its constants. The actual contact physics revealed several behaviors that previous platforms did not demonstrate in the same way, including gripping failures due to an off-center grasp, an arm that could remain indefinitely in a lowered position, and a periodic navigation orbit that avoided the center of the environment. A systematic dopamine sweep showed that the model's original calibration point, 0.2, corresponds to the observed minimum total task failure among five tested levels. We observed a specific mechanism behind a motor distortion effect already described in previous work with the same model: motor activity of behaviors that lose selection competence by filtering into the final robot command. Our results indicate that the effect does not appear to depend on simultaneous channel selection at the thalamic level but rather on a specific threshold at the motor activity combination stage [3]. A preliminary execution mode inspired by the procedure reported for real hardware showed worse performance at all dopamine levels tested, with no classical form of dithering explaining the effect [4]. This work suggests that porting a historical neuro-robotic model to a modern physics engine requires adjustments beyond a simple code translation.

Abstract: The Minimum Vertex Cover problem is NP-hard. Its classical polynomial-time approximation ratio is 2, and Khot and Regev showed that, assuming the Unique Games Conjecture (UGC), no polynomial-time algorithm can achieve a factor \(2-\varepsilon\) for any fixed \(\varepsilon>0\). We present FindVertexCover, a linear-time ensemble algorithm that runs seven independently valid vertex-cover heuristics on the input graph \(G=(V,E)\) and returns the smallest cover found, then prunes redundant vertices. Four of the seven candidates—and the final redundant-vertex pruning pass applied to each of them—adapt a published ensemble that proves an unconditional \(O(n+m)\) time and space bound and a worst-case approximation ratio at most 2 for every graph, where \(n=|V|\) and \(m=|E|\). \textsc{Salvador} extends that ensemble with two further linear-time candidates of its own and a sixth candidate, SolveVC, that reduces \(G\) to a linear-size planar forest core via a weighted Minimum Independent Dominating Set (MIDS) gadget and solves that gadget with an accuracy-controlled Baker-style PTAS whose layering width is \(k=\lceil 1/\varepsilon\rceil\); non-core edges are covered by a greedy repair step. At the package default \(\varepsilon=1\), the Baker layering width is \(k=1\) and the PTAS pass degenerates to its linear-time greedy baseline, so every one of the seven candidates—and hence the ensemble as a whole—runs in worst-case \(O(n+m)\) time; because one candidate is the classical maximal-matching heuristic, the ensemble unconditionally achieves approximation ratio at most 2 on every graph, a theorem rather than a conjecture. We conjecture a universal ratio bound \(R^\star<2\) for the default call; on a reproducible suite of 1,746 test graphs, ranging from exhaustively enumerated small graphs to random and adversarial graphs with up to 200,000 vertices, the observed ratio never exceeds $1.61$, well below the classical \(7/4\) mark. If a bound below 2 were proved for the ensemble, then, under the standard assumption \(\mathrm{P}\neq\mathrm{NP}\), the Khot–Regev UGC-based hardness theorem for Vertex Cover would force the Unique Games Conjecture to be false. An open-source implementation is released as the Salvador package (v0.0.7).

Abstract: We introduce and develop a Banach-manifold version of partially negative dimensional product manifolds (PNDP-manifolds). The construction is based on the observation that the virtual negative dimension of a PNDP fiber can be encoded analytically by a Fredholm index rather than by an ordinary finite-dimensional dimension. This leads naturally to a theory of Banach PNDP-manifolds in which the base is a Banach manifold, the fiber is modeled on a Banach derived-differential object, and the virtual dimension is defined by a Fredholm index. We establish basic structural results for Banach PNDP-manifolds, including a local normal form, a virtual-dimension formula, invariance under compact perturbations, and a criterion for the Einstein equation for warped Banach PNDP geometries under a finitedimensional reduction hypothesis. We then introduce strong and weak symplectic Banach PNDP-manifolds and prove that symplectic structures are compatible with the virtual decomposition when the positive and obstruction directions form a symplectic Fredholm pair. A central part of the paper concerns the Fredholm–Lagrangian Grassmannian. We define the PNDP Maslov index by reducing a path of Fredholm Lagrangian PNDP-subspaces to a finite-dimensional crossing problem. We prove homotopy invariance, additivity, concatenation, direct-sum additivity, naturality under symplectic isomorphisms, and invariance under admissible PNDP symplectic reduction. Several explicit examples are given, including constant negative-index bundles, a finite-dimensional PNDP model, a Hilbert-space loop with non-zero Maslov index, and a warped Banach PNDP model. The theory provides a common framework connecting PNDP geometry, Fredholm operators, Einstein-type warped products, symplectic Banach geometry, spectral flow, and Maslov index theory

Abstract: Infrared sea surface image segmentation is a fundamental task in marine perception, but its performance degrades significantly due to faint wave textures, blurred sea-sky boundaries, and low contrast. To address these issues, this paper proposes a Dual-branch Semantic Adaptive Fusion Gate UNet (DSAFG-UNet). The method replaces the static concatenation in the skip connections of standard UNet with a Dual-branch Semantic Adaptive Fusion Gate (DSAF-Gate) module, which adaptively fuses global semantic and local edge information to dynamically filter skip-connection features. Meanwhile, a multi-scale edge loss and a multi-scale context module are introduced to cooperate with the gating mechanism from the perspectives of boundary supervision and global perception, respectively. Experiments show that DSAFG-UNet achieves an mIoU of 91.96% and a sea-class F1-Score of 98.30%, outperforming gating-based models, multi-scale context models, and attention-based models on multiple accuracy metrics, with good stability and generalization, although its computational efficiency still needs improvement. In summary, the proposed model achieves strong overall performance in infrared sea surface segmentation and provides an effective solution for sea-region segmentation.

Abstract: This paper studies the stationary balancing of a full-scale bicycle robot using a scissored-pair control moment gyroscope (CMG). The test robot weighs 60 kg and includes two counter-rotating flywheels, a 20:1 geared gimbal system, an inertial measurement unit (IMU), and an embedded controller. For controller design, a simplified nonlinear model of the roll and CMG dynamics is derived and linearized around the upright position. The main contribution of this work is the experimental testing of a PDD2-LQR controller. This controller keeps the standard LQR state-feedback baseline and adds feedback from the roll error, roll rate, and filtered roll acceleration. Instead of redesigning the whole controller, the same LQR gains are used in both the baseline LQR and PDD2-LQR setups. This allows us to directly evaluate the benefit of the extra PDD2 terms on the same hardware under the same actuator limits. Experiments were carried out using PID, LQR, and PDD2-LQR controllers. The PDD2-LQR controller reached an average RMSE of 0.660 degrees and an average MAE of 0.477 degrees. These values represent improvements of about 51.8% and 43.2%, respectively, compared with the standard LQR controller. Overall, the results show that adding roll-motion feedback to the baseline controller significantly improves stationary balancing performance.

Abstract: Sensor failures, communication interruptions, and other monitoring problems can lead to missing acceleration responses in structural health monitoring of offshore platforms. To address this issue, a hierarchical feature fusion reconstruction (HFFR) method is proposed. The method employs multi-scale local morphology encoding to characterize local response morphology over different temporal neighborhoods, uses bidirectional temporal modeling to capture response evolution before and after the missing data, and adaptively weights temporal information according to feature correlation. A dataset is constructed using numerical simulation data from an offshore platform under different wave–current conditions, and the proposed method is evaluated through ablation and comparative experiments. After introducing multi-scale local morphology encoding and adaptive feature weighting into the bidirectional temporal modeling framework, the RMSE decreases from 0.5036 to 0.1109, while R² increases from 0.7581 to 0.9883, confirming the effectiveness of the hierarchical information representation framework. The results show that HFFR can recover the major peaks and valleys, amplitude envelopes, and local fluctuations of the missing responses, thereby improving both reconstruction accuracy and the preservation of dynamic response characteristics. The current validation is mainly based on high-fidelity numerical simulations; therefore, the applicability of the proposed method in real monitoring environments should be further verified through physical model tests.

Abstract: This article examines the existential predicament of the digital age through the lens of Paul Tillich’s theory of ultimate concern. While traditional ethical principles often prove abstract when confronted with algorithmic power, an existential inquiry reveals a deeper crisis: digital technology is systematically eroding the essential determinations of the human being—freedom, wholeness, and a unified self-awareness—which are the subjective prerequisites for ultimate concern. Specifically, algorithmic power disciplines choice, scoring mechanisms fragment the life narrative, and virtual identity dissolves the embodied anchor of the self. This leads to a double paralysis of the existential imperative of seeking life and avoiding death: the source of motivation is exhausted by the disenchantment of death and the transfer of existential anxiety, while the direction of pursuit is collapsed by the virtualisation of existence and digital idolatry. To resolve this, the article proposes a two-fold path of existential practice: first, reclaiming the subjective determinations of the human within technological enclosures; second, reconstructing the dialectical movement of seeking life and avoiding death. By transforming digital anxiety into existential anxiety and discerning ultimate symbols from digital idols, individuals can maintain a dimension of transcendence and affirm their humanity in-spite-of the pressures of the system through the courage to be.

Abstract: Actin remodeling accompanies myoblast proliferation, lineage commitment, elongation, fusion, and myofibril assembly, but these changes do not constitute a single linear pathway. This review separates three experimentally distinguishable scales of actin function in skeletal myogenesis. First, the balance between monomeric and filamentous actin controls myocardin-related transcription factor–serum response factor (MRTF–SRF) signaling and thereby couples cytoskeletal state to gene expression. Second, integrin–FAK–Rho signaling and actomyosin tension influence YAP/TAZ activity, with outcomes that depend on cell state, density, mechanical context, and the non-equivalent functions of YAP and TAZ. Third, spatially restricted branched actin networks generate protrusive force at the fusogenic synapse, while a mechanically reinforced receiving-cell cortex provides counterforce and cooperates with membrane fusogens to form and enlarge fusion pores. We compare evidence from cultured myoblasts, developmental models, and adult muscle regeneration, with attention to what each assay measures. We propose that bulk actin abundance, filament turnover, mechanical tension, and local actin architecture should be treated as separate variables. This framework reconciles apparently conflicting results and identifies experiments that can distinguish correlation from causal actin-to-nucleus signaling during muscle formation and repair.

Abstract: Background: Gulf Cooperation Council (GCC) populations combine intense ultraviolet B (UVB) radiation with widespread hypovitaminosis D and multiple sclerosis (MS) burden. We examine this Arabian Gulf vitamin D–MS paradox as an exposure–biology–inference problem rather than a single causal pathway. Methods: We conducted a structured narrative review and regional synthesis using a structured search of PubMed/MEDLINE, Embase, Scopus, Web of Science, and regional sources (January 1990–August 2026), followed by a targeted September 2026 update incorporating the Bahrain Research Square preprint. Evidence was appraised for ascertainment, assay heterogeneity, temporality, confounding, ancestry transferability, replication, and intervention design. Results: Low 25-hydroxyvitamin D [25(OH)D] recurs across the GCC despite abundant UVB. In Bahrain, mean 25(OH)D was lower during April–September than October–March (21.1±17.4 vs 34.7±21.2 nmol/L); secondary calculation gave a difference of −13.6 nmol/L (95% CI −17.3 to −9.9; Cohen’s d=0.72). A September 2026 preprint identified 876 actively followed Bahraini patients, corresponding to crude registry-based prevalence of 117.2 per 100,000 (95% CI 109.4–125.0), and 48 new diagnoses during March 2025–March 2026, yielding incidence of 6.4 per 100,000 (95% CI 4.7–8.5). Centralized national referral and DMT delivery support high completeness of the contemporary clinical numerator, while denominator projection and lack of age/sex standardization remain limitations. Regional genetic, EBV, obesity, smoking, diagnostic-era, and treatment-related evidence supports a multifactorial model. Conclusions: Vitamin D is a plausible modifiable component of multifactorial MS susceptibility, not a stand-alone explanation for GCC epidemiological change. Deficiency should be corrected for general health, but no MS-specific serum target or lifelong high-dose regimen is established. Contemporary Bahrain data strengthen evidence of substantial national MS burden while showing that higher prevalence need not imply a proportional rise in annual incidence. Ancestry-aware longitudinal GCC studies are needed.

Abstract: This study investigates how Digital Twins, photogrammetry, and related 3D technologies are transforming cultural heritage preservation, with a particular focus on Irish case studies. Heritage sites face increasing threats from climate change, conflict, natural decay, and limited conservation resources. Traditional methods-while culturally significant-struggle to meet modern preservation demands due to their cost, time requirements, and limited precision. Digital tools offer new solutions: photogrammetry enables accurate, low-cost 3D documentation; laser scanning provides high-precision structural data; and Digital Twins support predictive maintenance, environmental monitoring, and virtual engagement. Through a mixed-methods approach combining literature review, case studies, surveys, and interviews, the research evaluates four major Irish digital heritage initiatives: Beyond 2022, Spike Island, Ogham in 3D, and the Digital Repository of Ireland. Findings show strong benefits in documentation accuracy, asset management, and public accessibility, but also highlight barriers such as funding gaps, limited digital skills, and long-term data storage challenges. The study concludes that Ireland has significant potential for leadership in digital heritage but requires a coordinated national strategy to support training, infrastructure, ethical data management, and sustainable digital preservation practices.

Abstract: Large language models (LLMs) have turned artificial intelligence infrastructure from a supporting concern into a primary determinant of model capability, development velocity, reliability, and cost. A modern AI platform is not simply a collection of accelerators: it is a vertically integrated system spanning power and cooling, compute and memory, scale-up and scale-out networks, storage and data pipelines, compilers and communication libraries, distributed training, post-training, inference serving, cluster control, and lifecycle governance. This paper develops a systems-oriented taxonomy of that stack. It distinguishes three planes—resources, execution, and lifecycle control—and analyzes how the requirements of pretraining, post-training, and online inference differ. Particular attention is given to distributed parallelism, state sharding, checkpointing, data quality, key–value cache management, continuous batching, prefill–decode disaggregation, observability, and multi-tenant scheduling. The analysis shows that LLM infrastructure is governed by shifting bottlenecks: training alternates among arithmetic, communication, memory, and input/output limits, whereas online generation is frequently constrained by memory capacity, bandwidth, queueing, and tail latency. The paper concludes with a measurement framework and research agenda centered on composable parallelism, heterogeneous and disaggregated resources, reliable long-running jobs, efficient reasoning and agent workloads, security, and energy-aware operation. The resulting taxonomy provides a common vocabulary for studying AI infrastructure as a complete sociotechnical system rather than as isolated hardware or software components.

Abstract: Generative artificial intelligence (AI) intensifies a long-standing question for religious education (RE): what is education for when information, explanation, and polished synthesis are available on demand? Using Catholic religious education (CRE) as a situated case, this conceptual article argues that wisdom should orient RE without displacing knowledge. Drawing on virtue ethics, Catholic thought, philosophy of education, and recent scholarship on digital religion and AI, it develops four dimensions of wisdom-centered RE: epistemic judgment, practical-moral discernment, relational responsibility, and tradition-situated orientation toward ultimate goods. It concludes with implications for curriculum, pedagogy, assessment, teacher formation, and interfaith and public RE.

Abstract: Background/Objectives: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), initially developed for glycemic control and now widely used for weight management, affect appetite, satiety, gastrointestinal function, and body weight in ways that may support or complicate eating disorder (ED) recovery. This review examines emerging evidence on GLP-1 RA use across ED presentations and considers implications for recovery-oriented care. Methods: We conducted a narrative synthesis of peer-reviewed research, review articles, and relevant clinical guidance addressing GLP-1 RA mechanisms, ED psychopathology and treatment, and recovery-related clinical and psychosocial considerations. Results: Evidence is most developed for binge-eating disorder (BED), but remains preliminary and inconsistent. Some observational findings suggest reductions in binge eating symptoms, whereas a placebo-controlled trial found greater weight loss without a significant between-group difference in binge-eating episodes. Evidence for bulimia nervosa, anorexia nervosa, atypical anorexia nervosa, and other specified feeding or eating disorder presentations is sparse. For restrictive and purging presentations, appetite suppression, early satiety, delayed gastric emptying, and gastrointestinal adverse effects may reinforce restriction, complicate symptom monitoring, or interfere with nutritional rehabilitation. Conclusions: GLP-1 RAs are not established treatments for ED psychopathology, and changes in weight, metabolic health, or selected symptoms should not be equated with multidimensional ED recovery. When these medications are prescribed for appropriate medical indications or investigated as adjunctive treatments, ED screening, informed consent, multidisciplinary monitoring, and assessment of psychological, nutritional, behavioral, and functional outcomes are warranted.

Abstract: Probiotic effects in dogs may depend not only on the bacterial strain but also on host-related characteristics. Differences in body size are associated with distinct gastrointestinal and microbial features that may influence responses to nutritional interventions. This study evaluated the effects of Limosilactobacillus reuteri DSM 32203 in healthy small-breed dogs and investigated whether responses differed between Chihuahua and Dachshund dogs with different body weights. Healthy adult dogs were supplemented daily with L. reuteri DSM 32203, and body weight, body condition score, fecal score, fecal moisture, total lactobacilli, and total coliforms were evaluated throughout the study. Supplementation improved fecal quality, with increased consistency and reduced moisture, and fecal scores reaching or approaching the optimal value. An increase in total lactobacilli and a reduction in total coliforms was also observed. These findings are consistent with previous observations obtained with the same strain in other canine breeds. However, the greater reduction in total coliforms compared with our previous studies in larger breeds may suggest that the response to a defined probiotic strain varies among canine phenotypes. Although body size cannot be established as a direct causal factor, these findings provide preliminary evidence that host characteristics may contribute to probiotic responsiveness.

Abstract: Dissociative Identity Disorder (DID), formerly known as multiple personality disorder, is recognized as one of the most complex conditions in the fields of psychiatry and psychology. Initially associated with interpretations of demonic possession, it later came to be understood from a clinical perspective through the contributions of scholars such as Rush, Charcot, and Janet, who emphasized its dissociative nature. The former diagnostic category of hysteria was subsequently reorganized within modern psychiatric classification systems while preserving its underlying conceptual framework. Furthermore, widely publicized cases, such as The Three Faces of Eve and Sybil, contributed to strengthening the association between DID and early-life trauma. It is estimated that 1.5% of the Brazilian population is affected by DID. Between 2018 and 2023, Brazil's Ministry of Health recorded 3,667 cases. This study was conducted as a narrative, descriptive, and exploratory literature review, drawing on databases including Google Scholar, SciELO, and PePSIC, as well as scientific publications, using specific search descriptors related to dissociation and Dissociative Identity Disorder.

Abstract: Beverage carbohydrate content is a major determinant of acute glycemia, whereas responses to unsweetened spice infusions and mineral-rich water remain uncertain. This randomized, controlled, parallel-group study compared six beverages in healthy university students aged 19–25 years after an overnight fast. In total, 180 participants were randomly assigned using permuted blocks with allocation concealment (30/group) to 250 mL of orange juice, a honey drink, ginger infusion, cinnamon infusion, Zamzam water, or plain bottled water; outcome assessors were blinded. A protocol analysis included 144 participants (24/group). Capillary glucose, based on triplicate readings, was assessed before and 60 min after consumption. Within-group changes were assessed using paired t-tests and compared across groups using one-way analysis of variance. Mean glucose increased after honey (+20.09 mg/dL; 95% CI, 15.50–24.68; p < 0.0001) and orange juice (+17.33 mg/dL; 95% CI, 6.10–28.56; p = 0.0058). Changes after cinnamon (−3.58 mg/dL), ginger (−3.91 mg/dL), and plain water (−2.84 mg/dL) were not statistically significant. Zamzam water produced a within-group increase (+9.83 mg/dL; 95% CI, 5.20–14.46; p = 0.0003), with a post-consumption mean of 89.00 mg/dL. Overall changes differed among groups (p < 0.0001). The Zamzam findings are exploratory and require confirmation using standardized beverage composition, repeated measurements, and direct between-group estimates.