Abstract: Aluminium powder, an energetic material, is prone to thermal runaway upon water exposure under local heat sources, yet the nonadiabatic mechanisms of micron sized accumulated aluminium powder under localized heating remain unclear. This study employs a proprietary characterization platform to investigate the effects of particle size, water content, and local heat source power on heat transfer in the dry state and on parameters including induction time, onset temperature, peak heat release rate, and reaction heat during the induction and main reaction phases. In the dry state, decreasing particle size enhances effective thermal conductivity and accelerates temperature rise, whereas elevated local heat source power exacerbates thermal inertia. Under local heating upon water exposure, reduced particle size significantly enhances reactivity; the reaction heat of 2 μm powder reaches 983 J/g, approximately fourfoldAs shown in Figure9 that of 106 μm powder. Water content exhibits nonmonotonic regulation, with onset temperature minimizing at 25% water content and 66.4 °C and reaction heat peaking at 33%. Paradoxically, elevated local heat source power suppresses reaction intensity, and reaction heat at 10 W is one sixth of that at 2.5 W, attributed to rapid product layer densification and the steam film barrier effect shifting the controlling mechanism from chemical to diffusion control. A coupled multifactorial predictive model incorporating the three factors was established with R2 of 0.92, providing data and guidance for aluminium powder storage hazard prevention.

Abstract: Binary sequences (binary codes), where the elements are −1 or +1, are useful in many fields, including communications, radar, sonar, mathematics, physics, and cryptography. This paper considers binary sequences with low aperiodic autocorrelations and focuses on the small peak sidelobe levels alongside the merit factor. Two families of binary sequences are considered, namely Rudin-Shapiro and Legendre sequences. For both families, we applied a heuristic algorithm to minimize the peak sidelobe levels for sequences of lengths up to 2^16 and 220−1, respectively. The main contribution of the article is two conjectures associated with Legendre sequences: (1) The obtained binary sequences with the best-known peak sidelobe levels have merit factor ≈5.0, (2) The number of elements that differ between the resulting binary sequences and the initial Legendre sequences follows a linear dependence on the sequence length (n), namely ≈0.01n. The Rudin-Shapiro sequences do not exhibit these properties, as worse peak sidelobe level and merit factor values were obtained. The number of elements that differ between the resulting binary sequences and the initial Rudin-Shapiro sequences is also much higher compared to that of the Legendre sequences.

Abstract: Existence of global smooth solutions to the three-dimensional (3D) Navier-Stokes equations is disproved for pressure-driven plane Poiseuille flow with no-slip boundary conditions. This study is rigorously grounded in Sobolev space analysis. We show that the solution breakdown arises from the regularity degeneration instead of velocity blow-up. For disturbed laminar plane Poiseuille flow, the instantaneous velocity field is decomposed into a time-averaged flow and a disturbance flow, both characterized by their regularity in Sobolev spaces. When the Reynolds number is larger than the critical Reynolds number, the nonlinear interaction modifies the mean flow profile, and the disturbance amplitude grows significantly. This amplification leads to a local cancellation between viscous terms of the mean flow and the disturbance flow, resulting in the total viscous term (i.e., the Laplacian term) vanishing locally at the critical point $(\boldsymbol{x}^*, t^*)$. The local vanishing viscous term leads to zero velocity according to the Energy-Velocity Monotonicity Principle (EVMP), which contradicts the non-vanishing incoming velocity, leading to formation of a singularity. This singularity induces a velocity discontinuity, which causes the $L^\infty$ -norm of the velocity gradient to diverge, violating the definition of a global smooth solution in Sobolev spaces. The analysis is strictly grounded in partial differential equations (PDE) theory, with all key steps validated by Sobolev space properties and a priori estimates.

Abstract: Persistent post-concussion symptoms (PPCS) following mild traumatic brain injury (mTBI) are common and frequently disabling. However, symptom persistence is often poorly correlated with injury severity or structural brain abnormalities. Increasing clinical and research evidence suggests substantial overlap between PPCS and functional neurological disorder (FND), yet this interface remains poorly synthesised and conceptually unresolved. To systematically review and synthesise the evidence linking mTBI with functional neurological symptoms, and to refine existing conceptual models by proposing a clinically useful framework for differentiating functional and organic contributions to persistent post-concussion presentations. A scoping review with narrative synthesis were conducted. Database searches yielded 120 records; after duplicate removal and abstract screening, 32 studies underwent full-text review. Included studies comprised systematic reviews, narrative and conceptual reviews, mechanistic hypothesis papers, primary observational studies, case series, case reports, and early interventional and neu-roimaging investigations examining functional neurological symptoms in the context of mTBI. The literature demonstrates substantial phenomenological overlap between PPCS and FND across cognitive, motor, sensory, visual, and seizure-related domains. Functional neurological symptoms can emerge after concussion and may closely resemble PPCS, often in association with psychiatric comorbidity, dissociation, trauma exposure, and maladaptive attentional or illness-belief processes. Objective neurological impairment and injury severity show weak and inconsistent associations with symptom persistence. The evidence base is dominated by clinic-derived observational studies, with no population-level incidence estimates identified. Functional neurological symptoms represent a significant and under-recognised contributor to persistent symptoms after mTBI. Existing evidence supports moving beyond binary organic–psychogenic models toward a functional–organic differentiation framework that acknowledges dynamic interactions between injury-related and functional mechanisms. Improved screening, diagnostic communication, and stratified management are likely to enhance outcomes for patients with persistent post-concussion symptoms.

Abstract: Background: Transradial access has become a preferred strategy for chronic total occlusion (CTO) percutaneous coronary intervention (PCI) because of lower access-site complication rates and increasing feasibility for complex CTO techniques using large-bore slender or sheathless systems. However, long-term outcomes after successful transradial CTO recanalization and their predictors remain incompletely defined. We aimed to identify long-term clinical and procedural predictors of major adverse cerebrovascular and cardiac events (MACCE) after successful transradial CTO PCI. Methods: We performed a prospective dual-center cohort study including 227 consecutive patients who underwent successful transradial CTO PCI at two high-volume catheterization laboratories with dedicated CTO programs. A total of 405 CTO PCI procedures were screened; all femoral-access cases were excluded and only transradial cases were eligible. Baseline clinical characteristics, left ventricular ejection fraction (LVEF), lesion complexity including J-CTO score, coronary disease extent, and procedural variables were prospectively collected and/or verified from institutional databases. The primary endpoint was MACCE, defined as a composite of all-cause death, non-fatal myocardial infarction, target vessel revascularization, and stroke/transient ischemic attack. Event rates were estimated using Kaplan-Meier methods. Predictors were explored using Cox proportional hazards regression with clinically relevant covariates and procedural characteristics entered into multivariable models. Results: Among 227 patients with successful transradial CTO recanalization and complete 5-year follow-up among survivors, cumulative MACCE and all-cause mortality were 44.0% and 21.5%, respectively. In multivariable Cox analysis, prior myocardial infarction, right coronary artery target vessel, and a higher number of implanted stents were independently associated with increased MACCE risk, whereas previous PCI and preserved LVEF (≥40%) were associated with lower MACCE risk. For all-cause mortality, preserved LVEF was independently protective, while right coronary artery target vessel intervention was associated with increased mortality risk; severe chronic kidney disease showed a significant univariable association and remained a strong signal after multivariable adjustment. Conclusions: After successful transradial CTO PCI, long-term MACCE appears to be driven primarily by baseline comorbidity and coronary disease burden rather than by access-related factors. Integrating clinical risk markers with anatomic and procedural markers may improve long-term prognostication and guide secondary prevention and follow-up after transradial CTO recanalization.

Abstract: Automated fake news detection has advanced substantially through transformer-based classification, yet two critical gaps persist in the literature: static models degrade as misinformation tactics evolve, and high-performing systems rarely reach end users in accessible forms. This paper addresses both gaps through a system that couples RoBERTa-based classification with a post-deployment continuous learning pipeline and a browser-native Chrome extension. We curate a corpus of 70,556 unique articles from three established benchmark datasets—ISOT, WELFake, and the COVID-19 Constraint dataset—after eliminating 42.9% of initially gathered samples as cross-dataset duplicates. A systematic comparison of XGBoost (95.88%), DistilBERT (97.74%), and RoBERTa-base (98.51%) establishes the production model, with selection driven primarily by false negative rate: RoBERTa achieves 1.09%, a 69% reduction over XGBoost and 28% over DistilBERT. A documented vulnerability of transformer classifiers is susceptibility to formally-worded misinformation that mimics journalistic style. We construct a dedicated adversarial training set of 70 examples spanning health misinformation, suppression narratives, and election fraud claims, and demonstrate that targeted fine-tuning raises adversarial detection accuracy from approximately 40% to 95.71% while maintaining 98.60% accuracy on standard benchmarks—achieved through experience replay that prevents catastrophic forgetting. For deployment, ONNX INT8 quantization reduces model size from 500MB to 125MB without accuracy loss, enabling inference on free CPU infrastructure. A GitHub Actions pipeline collects fresh labeled articles nightly, and a FastAPI service running on Hugging Face Spaces serves predictions with 150–200 ms latency. A Chrome extension providing paragraph-level hover detection, LIME-based word attribution, source credibility scoring, and multilingual support across 19 languages makes the system accessible to non-technical users. End-to-end evaluation across 50 curated articles yields 98% accuracy; research-backed adversarial testing across seven categories achieves 91.7%, with perfect detection on adversarial attacks, AI-generated misinformation, temporal domain shifts, and multilingual content.

Abstract: A metal recycling facility scrapyard fire that burned for four days continuously in February 2020 in rural Minnesota resulted in firefighters from around Minnesota to mobilize and aid. Combusted material included cars, refrigerators, metals, glass, foam, insulation. Urine, blood and serum specimens were collected one day later. Parameters collected included: CBC with differential, BMP, blood heavy metals, urine heavy metals, and serum heavy metals. This massive and prolonged industrial fire provided an opportunity for biomonitoring of hazardous, and unique, exposures acutely, in concordance with concerns raised by the employees at risk. Initial analysis of these results did not find evidence of acute concern regarding the biomonitoring results. However, some of these results may portend the potential for long-term consequences such as the development of occupational cancers, especially if there was recurrent exposure in prior or proceeding fires.

Abstract: Background/Objectives: Coexistence of systemic sclerosis and sarcoidosis is very ra-re. Both are systemic autoimmune diseases with lung involvement but with different pathogenesis. In contrast to findings of mid- to upper-lobe interstitial lung disease (ILD) or/with hilar lymphadenopathy in sarcoidosis, the most common lung manifes-tation of systemic sclerosis is lower-lobe ILD, which is typically characterized by a nonspecific interstitial pneumonia pattern. Distinction between lung involvement re-lated to each disease is crucial due to different therapeutic approach Methods We present herein a serie of three overlap cases: two with sarcoidosis onset before the diagnosis of systemic sclerosis and the other with systemic sclerosis onset before sarcoidos. Results: A review of cases of concomitant sarcoidosis and systemic sclerosis is dis-cussed, including the pathophysiology of each disease with shared pathways leading to the development of both conditions in one patient Conclusions: The systemic sclerosis-sarcoidosis overlap is a high-risk phenotype. Early recognition and a personalized, aggressive therapeutic approach are essential to alter the natural history of these two converging fibrotic and granulomatous processes.

Abstract: Background: Hallucination the generation of factually incorrect, internally in consistent, or ungrounded content remains a critical barrier to safe LLM deployment in high-stakes domains. Existing detection methods typically require external knowledge bases, model ne-tuning, or cloud API access, limiting applicability in local inference contexts. Methods: We evaluate the Kerimov–Alekberli (K–A) information-geometric framework as a real-time, inference-time hallucination detector across six open-source LLMs deployed locally on Apple M5 Silicon via Ollama v0.23.2 (Q4_K_M quantisation). The K–A framework monitors the KL divergence between consecutive output distributions relative to a Fisher Information Metric (FIM)-derived threshold (τ = 0.065), triggering First-Passage Time (FPT) alarms when generation departs from the stable Riemannian output manifold. We evaluate 120 responses (6 models × 20 questions) drawn from three established benchmarks: HaluEval (14 questions; categories: Fact, Confuse, Date, Num, Trap), FEVER (4 questions; adversarial fact verification), and SimpleQA (2 questions; precise factual recall). All questions are classified as difficulty level Hard, targeting known LLM failure modes including o-by-one numerical errors, geographical traps, and disputed-attribution confounds. Results: The K–A framework achieves a session hallucination detection rate of 90.9% (20/22 hallucinated responses correctly flagged) with zero false positives on correct responses (0/98). Model-level hallucination rates vary dramatically: deepseekr1:latest (Qwen3 CoT architecture, 5.2GB) exhibits a 95% hallucination rate (19/20 questions) with 100% K–A detection; gemma3:27b (Gemma3, 17.4GB) and gemma3:latest (4.3B, 3.3GB) achieve 0% hallucination. Two K–A false negatives involve con dent factual errors below the KL threshold. Average KL divergence for hallucinated responses (D̅_KL = 0.068 ± 0.004) is significantly higher than for correct responses (D̅_KL = 0.042 ± 0.016). Conclusions: K–A achieves competitive hallucination detection without external knowledge bases, ne-tuning, or cloud infrastructure, processing each response in real time with negligible overhead. The deepseek-r1 result reveals a fundamental tension between chain-of thought reasoning depth and factual precision on concise queries that warrants systematic investigation.

Abstract: (1) Background: Indonesia faces the dual challenge of a high tuberculosis (TB) burden and increasing drug resistance. Conventional molecular diagnostics frequently fail to detect isoniazid resistance and nontuberculous mycobacteria (NTM). This study evaluates a domestic multiplex Open PCR system in Medan, Indonesia. (2) Methods: From July to November 2025, 1,569 sputum specimens from suspected TB pa-tients were analysed using the Indigen MTB/NTM/DR-TB Real-time PCR Kit Gen 2. (3) Results: Mycobacterial DNA was detected in 421 specimens (26.8%). Among these, 396 (94.1%) were drug-susceptible TB, while 16 (3.8%) showed resistance, predominantly INH mono-resistance (n=14; 0.89% of total). Additionally, 9 cases (2.1%) involved NTM or TB-NTM co-infections. Tertiary hospitals showed significantly higher positivity rates (33.5%) than primary care (18.9%; p < 0.001). TB status was significantly associated with male (p = 0.0052) and older age (p = 0.006), whereas resistance profiles and NTM distribu-tion were consistent across all demographic groups (p > 0.80). (4) Conclusions: The Open PCR system effectively identified INH resistance and NTM cases overlooked by standard rifampicin-only assays. By bridging diagnostic gaps across a decentralized referral network, this facilitates rapid and targeted therapy. Integrating multiplex domestic innovations into national diagnostic algorithms is essential for achieving Indonesia’s TB elimination targets.

Abstract: Promising results in the regeneration of skin lesions have been demonstrated with the use of natural (organic) products, such as dermal dressings made of polysaccharides (chitosan complexed with xanthan), as they promote a hydrated and thermally insu-lating microenvironment, allowing gas exchange; and sources rich in growth factors such as autologous platelet-rich plasma (PRPa), which contains transforming growth factor beta (TGF-β), vascular endothelial (VEGF) and platelet-derived (PDGF), re-sponsible for stimulating the inflammatory cascade and healing. The aim of this study was to evaluate the action of a polymeric membrane (chitosan, xanthan and β-glycan) and PRPa on healing in vivo, used alone or in combination. For the tests, rabbits un-derwent a surgical procedure to induce the lesion and were distributed into a control group (GC), membrane group (GM), PRPa group (GPa) and membrane group associated with PRPa (GMPa), evaluated at moments M0, M7, M14, M21 and M28 (28 days). Wound color and exudation, presence of infection and inflammation, formation of granulation, scarring and necrotic tissue, morphological and morphometric analysis were evaluated. Statistical analyzes of the results were performed using the Software R® software, adopting a significance level of 5%. While statistical differences between treatments in healing time were not significant (p>0.05), all wounds achieved 100% retraction by M21. Notably, at M7, PRPa alone and in combination with the membrane contributed to higher wound retraction percentages (29.71% and 21.65%, respectively) compared to the control group (16.96%). These findings suggest that the complexed membrane, alone or combined with PRPa, fosters a humid environment, gas exchange, and antimicrobial activity crucial for healing, with PRPa further enhancing early wound retraction. It is concluded that the treatment of experimental surgical wounds with biodressings such as PRPa alone or associated with a complexed membrane of chitosan, xanthan, and β-glycan significantly contributes to wound retraction, in addition to offering a propitious and indispensable environment for the healing cascade, such as a humid environment, gas exchange, and antibacterial action. Future studies should consider a larger number of animals per group, histological evaluation for global tissue assess-ment, and collagen quantification.

Abstract: In this paper, which is entirely unconditional, we prove a sharpened almost-all theorem with fully explicit effective constants for the restricted weighted Goldbach sum$$R_{a,q}(N)\mspace{6mu}: = \mspace{6mu}\sum_{\substack{p_{1} + p_{2} = N \\ p_{1} \equiv a\ (mod\ q)}}^{}(\log p_{1})(logp_{2}),\quad q \geq 1,\quad gcd(a,q) = 1,$$whose expected main term is $M_{a,q}(N) = C_{2}S(N)N/\varphi(q)$, where $C_{2} = 0.6601618\ldots$ is the twin-prime constant and $S(N)$ is the binary singular series.Our results are organised around four pillars. (I) We give a complete character-pair decomposition of the second moment of the error $E(N): = R_{a,q}(N) - M_{a,q}(N)$, extracting the exact diagonal constant $G/(2\varphi(q))$, where $G = \prod_{p > 2}^{}(1 + (p - 1)^{- 2}) \in \lbrack 1.41320886,1.41320899\rbrack$ is the Gallagher--Goldston constant. (II) We establish a uniform minor-arc $L^{4}$ bound$$\int_{\mathfrak{m}}^{}|S(\alpha)|^{4}\, d\alpha\mspace{6mu} \leq \mspace{6mu}\kappa_{safe} \cdot 2^{A} \cdot \frac{X^{3}}{(logX)^{A}},\quad\quad\kappa_{safe} = 4.40,$$by combining the complete Vaughan identity with the Bombieri--Vinogradov theorem in integral form, giving an explicit derivation of $\kappa_{explicit} = C_{V}^{2}c_{L^{2}} = 4.004$ before applying a rigorous $10\%$ safety margin. (III) We derive the effective almost-all theorem$$\#\left\{ N \leq X\text{ even}:|R_{a,q}(N) - M_{a,q}(N)| > C(A,q)\, N(logN)^{- 3} \right\}\mspace{6mu} \ll_{A,q}\mspace{6mu} X(logX)^{- A},$$with the explicit constant $K: = 2C(1,4) \leq 38.02$, obtained from $C(1,4) \leq 19.01$ via a Stechkin-type optimisation. (IV) We prove a Pintz-type exceptional-set bound on $\{ N \leq X:R_{a,q}(N) = 0\}$.Every statement in the main body carries the tag \[PROVED\]. No Generalised Riemann Hypothesis, no zero-density hypothesis, no ternary sum $W_{a,q}(n)$, no spectral input, and no Chen-type sieve are used anyware.

Abstract: Inhomogeneous magnetic field distributions in high-frequency planar transformers frequently cause severe localized thermal hotspots and elevated leakage inductance. Traditional interleaved winding designs rely heavily on empirical trial-and-error, which becomes computationally prohibitive for multi-layer parallel structures due to the factorial "curse of dimensionality." To address this bottleneck, this paper proposes a universal, data-driven optimization methodology. First, a quantitative one-dimensional prefix-sum model is established to correlate winding arrangements with spatial magnetomotive force (MMF) distributions, effectively simplifying the electromagnetic evaluation. Subsequently, a customized Genetic Algorithm (GA) framework, featuring physical-constraint-preserving operators such as Order Crossover (OX), is introduced to efficiently navigate the high-dimensional discrete search space. Using an extreme 26-layer complex parallel winding configuration (Np:Ns = 9:2) as a primary case study, the proposed GA method effectively bypasses over 1.5 million permutations, converging to the global optimum within 100 generations. The optimized structure achieves profound peak-shaving, drastically reducing both the peak MMF and total uncoupled magnetic energy area. This methodology provides a systematic, computationally lightweight EDA solution that fundamentally replaces empirical trial-and-error in the design of high-frequency magnetic components.

Abstract: Nonlinear dynamical systems often exhibit complex collective behavior arising from the interaction of multiple elementary modes. In this work we investigate the aggregation of a countable family of dynamical modes generated by Lotka-Volterra systems and study the resulting structure in a Hilbert space of observables. The classical Lotka-Volterra equations form a fundamental class of nonlinear models describing interacting populations through coupled differential equations, while Koopman operator theory provides a framework in which nonlinear dynamics can be represented as a linear evolution acting on observable functions.We show that a countable aggregation of such dynamical modes admits a well-defined limit in a Hilbert space when the coefficients belong to l2. The resulting aggregated observable evolves according to the associated Koopman semigroup, yielding a linear representation of the underlying nonlinear dynamics in the observable space. We further prove that the geometry induced by this aggregated dynamics admits a canonical class of equivalent metrics generated by coercive operators, ensuring that the stability topology of the system is independent of the particular metric chosen within this class.Finally, we illustrate the theoretical framework by introducing a social risk functional defined as a quadratic observable associated with the induced metric. This example demonstrates how application-specific quantities can naturally arise from the geometric structure generated by aggregated nonlinear dynamics.

Abstract: Objectives: This prospective, open‑label, non‑randomized study evaluated a specific combination of cystine, B vitamins, and minerals (Pantovigar^® vegan) in 34 women (aged 30-75 years) with diffuse hair loss (Modified Savin Score 1–3) for improvements in hair condition and product acceptance and safety following up to 6 months of intake of one test product capsule three times daily. Methods: Hair condition was assessed using phototrichogram analysis, and participants completed a product acceptance questionnaire. Blood nutrient levels associated with hair loss were measured at baseline, and at 3 and 6 months. Results: From baseline to 6 months, a significant increase of 2.35% in the rate of anagen (p = 0.012) and a decrease of 2.35% in the rate of telogen (p = 0.012) hairs resulted in an increase of 2.37% in the ratio of anagen/telogen hair rate (p = 0.013), reflecting a proportionate increase in the number of terminal hairs in the anagen phase. Most participants agreed with positive questionnaire hair condition statements. Increased levels of B vitamins, ferritin, and hematocrit did not exceed established tolerable upper limits, and no serious undesired effects were reported. Conclusion: The study results suggested that the specific nutrient combination of cystine, B vitamins, and minerals in the test product is beneficial to hair condition, is well‑accepted, and safe for use in the management of diffuse hair loss in women. Clinical Trial Registration: [https://clinicaltrials.gov/study/NCT05943860]; identifier [NCT05943860]; date of registration: June 21, 2023; retrospectively registered.

Abstract: The physiological acidity of the skin microenvironment constitutes a paramount component of passive innate defense against pathogenic colonization and subsequent dysbiosis. The objective of this review is to critically evaluate the sequelae of chronic epidermal barrier exposure to chemical exfoliants and to elucidate the impact of hydroxy acids on microbiota stability. An analysis of recent literature delineates fundamental discrepancies in their antimicrobial mechanisms, inflammatory modulation, and induction of stratum corneum desquamation. Conventional exfoliants, notably glycolic and salicylic acids, exhibit the capacity for passive diffusion into bacterial cells, where they undergo dissociation, precipitating destructive cytoplasmic acidification; furthermore, salicylic acid specifically downregulates crucial transcription factors. While these mechanisms facilitate the efficacious eradication of pathogenic organisms, they concurrently jeopardize commensal populations, which may paradoxically pave the way for secondary dysbiosis and opportunistic colonization. Next-generation acids, such as lactobionic acid, emerge as a highly promising, albeit insufficiently investigated, alternative. They exhibit the capacity to compromise bacterial cell walls and intercalate with microbial DNA. Future paradigms regarding the utilization of hydroxy acids in clinical dermatology must extend beyond traditional macroscopic endpoints to encompass the preservation of microbiome diversity and stability, thereby precluding chronic impairment of the associated protective barrier.

Abstract: This paper examines the transmission of monetary policy through bank credit by distinguishing between credit to non-financial corporations and household credit in an emerging economy. Using an ARDL–ECM framework with structural break analysis, it investigates the relationships between credit, the policy rate, and inflation over time. The results suggest that the conventional interest rate channel is limited, as the policy rate does not exhibit a statistically robust association with credit in either the short or long run. Inflation shows a differentiated and context-dependent association, remaining weak for corporate credit but more consistently related to household credit, which may reflect the role of nominal conditions in shaping borrowing behavior. Credit dynamics also differ across segments. Household credit appears more persistent and adjusts gradually, whereas corporate credit is less inertial but more sensitive to instability, pointing to heterogeneous adjustment processes. In addition, the estimated relationships are not stable over time, as their sensitivity to macroeconomic variables varies across periods. Overall, the findings indicate that monetary transmission is heterogeneous and time-varying rather than uniform. These results should be interpreted as conditional relationships within the empirical framework and provide a disaggregated perspective on how macroeconomic conditions are associated with credit dynamics in bank-based emerging economies.

Abstract: Background/Objectives: Eating disorders (EDs) are among the most severe psychiatric conditions affecting young people, with increasing prevalence in the post-pandemic period. This study assessed the prevalence of ED risk and dysfunctional eating behaviors among Italian university students, a population poorly characterized with respect to ED risk, and examined associations with key socio-demographic and anthropometric variables. Methods: A cross-sectional online screening study was conducted between August 2023 and February 2026 with 401 Italian university students (women: n = 306; men: n = 95). Participants completed the validated Italian versions of the Eating Attitudes Test-26 (EAT-26) and the Eating Disorder Examination Questionnaire 6.0 (EDE-Q 6.0), alongside self-reported anthropometric data. Multiple linear regression analyses were performed to identify predictors of ED risk scores. Results: 37.9% of participants had an abnormal BMI (19.7% underweight; 18.2% overweight or obese). EAT-26 scores exceeded the clinical cut-off in 28.4% of participants (women: 35.6%; men: 5.3%). EDE-Q 6.0 global scores exceeded the clinical cut-off in 21.0% (women: 25.8%; men: 5.3%). Only 45.4% showed no anthropometric or psychometric risk indicators. Gender was the strongest predictor of both EAT-26 and EDE-Q 6.0 scores. BMI was negatively associated with EAT-26 scores in the total sample and in women, while a positive association between BMI and EDE-Q 6.0 scores was observed in men. Conclusions: A substantial proportion of Italian university students, particularly women, presented clinically significant ED risk. The combined use of anthropometric and psychometric screening tools provides a more comprehensive risk assessment than either measure alone, highlighting the need for multidimensional screening programs.

Abstract: Palmatine chloride (berbericinine, C₂₁H₂₂ClNO₄) is a protoberberine alkaloid found in several plants including Rhizoma Coptidis, Cortex Phellodendri, Rhizoma Corydalis, Guduchi (Tinospora cordifolia), and Tinospora sagittata roots. Palmatine chloride (PA) is known as an inhibitor of dopamine generation. However, its effect on endoplasmic reticulum (ER) stress-related macrophage activation caused by endotoxin (lipopolysaccharide) is not well known yet. In this study, effects of PA on pyroptotic responses of mouse macrophages (RAW 264.7) activated by endotoxin were investigated using Griess reagent assay for nitric oxide (NO) production, fluo-4 assay for cytosolic calcium release, dihydrorhodamine 123 assay for hydrogen peroxide production, multiple cytokine assay for cytokines production, real-time PCR for inflammatory genes transcriptions, and flow cytometry assay for p38 MAPK activation. Results revealed that PA significantly reduced excessive production levels of NO, hydrogen peroxide, pro-inflammatory cytokines (such as interleukin (IL)-6, CCL3 (MIP-1α), and CSF2 (GM-CSF)), and cytosolic calcium release in endotoxin-stimulated RAW 264.7, but significantly increased the production of anti-inflammatory cytokine IL-10. PA inhibited endotoxin-induced transcripts of Chop, Stat1, Fas, and c-Fos in activated RAW 264.7. It also decreased p38 MAPK phosphorylation and level of Fas in RAW 264.7 stimulated by endotoxin. To further interpret these findings, a network pharmacology-informed analysis based on large-scale literature mining was performed, supporting the multi-target regulatory role of PA in ER stress-related pathways. Briefly, PA exerts anti-inflammatory effects on endotoxin-stimulated RAW 264.7 via calcium-CHOP pathway, consequently reducing endotoxin-induced production of pro-inflammatory mediators (NO, cytokines, etc.) and relieving ER stress-related pyroptotic cascade.

Abstract: Early 2026 has witnessed significant volatility in the oil market, and an energy crisis is expected in the coming months. Large-scale LLM inference continues to consume substantial power in data centers and improving inference efficiency is therefore increasingly important for energy sustainability of AI economy. Semi-structured N:M sparsity, most notably 2:4 (50%) and potentially 1:4 (75%), offers a hardware-friendly path to lower compute and energy, and has been supported in modern GPU designs. Yet existing training methods for 2:4 sparsity (e.g., STE-based approaches) often incur large accuracy drops relative to dense baselines, and practical support for 1:4 remains limited in current software stacks. As a result, attention has shifted toward quantization and mixture-of-experts, leaving high-sparsity N:M pre-training underexplored. Here we introduce a paradigm shift: we treat neural networks as complex systems whose sparse connectivity can be trained using network-science principles formalized by Cannistraci–Hebb sparse-to-sparse training (CHT), coupled with a tailored optimizer. We propose CHTsNM, a sparse-to-sparse training framework centered on Topology-Aware Newton–Schulz (TANS) optimization. TANS makes Newton–Schulz-style matrix updates compatible with dynamically changing semi-structured sparse topologies via active-mask projection, active-support RMS matching, and refresh-aware ramping after topology updates. CHTsNM further incorporates two lightweight mechanisms: Contextually Modulated LoRA (CoMoLoRA) for input-adaptive low-rank residual compensation, and Motif Pattern Revisitation (MPR) to improve exploration of legal row-wise N:M patterns. Across 4 LLaMA pre-training benchmarks, CHTsNM with 2:4 sparsity achieves performance close to dense baselines on most tasks and yields sparse-over-dense gains on 8 tasks. 1:4 sparsity approaches dense performance, though does not yet consistently surpass it. For hardware evaluation, we report measured speedups for native 2:4 execution on current NVIDIA GPUs, and provide a clearly labeled CSR sparse-GEMM surrogate analysis to estimate the acceleration potential of 1:4. Overall, although not implement on hardware yet, our results identify 1:4 sparse pre-training as a promising direction and establish TANS sparse-to-sparse optimization as a practical step toward future high-sparsity N:M accelerators.