Abstract: We ask how fast high-fidelity gear rattle can be simulated—and where, once chaos sets in, simulating trajectories stops being useful and must give way to computing structure. By high-fidelity we mean a nonsmooth model that retains the three-state backlash, a time-varying mesh stiffness, tooth friction, and a flexible modal reduction of the gear bodies. Exploiting the piecewise-linear structure, we propagate each backlash state with a segment-exact exponential step and fuse many mesh cycles into a single spectral map: the constant-contact fusion advances one mesh cycle in a single matrix–vector product (∼61 ns) and jumps 106 cycles in 634 ns, while the sparse-regime event-driven path reaches 16× real time with a brute-force cross-check at 7 × 10−15. We then show that singletrajectory depth and ensemble breadth strike the same memory-bandwidth wall, so a 56-core rattle atlas returns only 16.6× speedup (∼30% efficiency). Finally, with a largest Lyapunov exponent of ∼0.55 per rattle cycle, exponential compute buys only a linear gain in predictable horizon: beyond this Lyapunov wall the real-time target must shift from trajectories to invariant structure (Floquet skeletons, basin and attractor statistics). We report honest negative results, including a flexible model that admits no stable period-1 orbit (0/80 operating points).

Abstract: With the advancement of technology and the proliferation of big data, multi-label classification has been widely applied in fields such as medicine, education, and business. Most existing multi-label classification methods utilize a problem transformation approach, converting multi-label problems into single-label classification tasks. The Label Powerset (LP) method treats distinct combinations of labels as unique classes, subsequently utilizing single-label methods to construct classification models. While LP generally yields superior accuracy compared to other methods, it faces challenges due to the excessive number of label combinations. This leads to data sparsity for most of the label combinations (the few-shot problem) and class imbalance, as well as low efficiency when handling a large number of label combinations. Subsequent research has attempted to optimize LP by partitioning labels into multiple subsets, establishing an LP model for each subset, and predicting labels using a multi-model voting mechanism. However, these approaches require the pre-determination of the number and size of label subsets and suffer from issues such as performance instability and the complexity of parameter tuning. To address the previous issues, we propose a label subset selection method based on Genetic Algorithm (GA). By dynamically adjusting the size of label subsets, the method adaptively generates the most suitable label combinations guided by the GA's fitness function, thereby avoiding potential performance degradation caused by fixed parameter settings. Experimental results demonstrate that our method outperforms state-of-the-art LP-based label subset selection methods on most of the datasets.

Abstract: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have moved rapidly from metabolic medicine into neurology, but the evidence to mid-2026 refuses to resolve into a single narrative of neuroprotection. Large cardiovascular outcome trials establish these drugs for ischaemic stroke prevention, whereas rigorous phase 3 trials in Parkinson's disease and Alzheimer's disease found no effect on clinical progression despite favourable cerebrospinal fluid biomarker shifts. I argue that this pattern is not contradictory but structured by two axes. The first is tissue reversibility, which determines whether disease modification is possible at all: a remodellable vascular substrate responds, an autonomously degenerating parenchyma does not, and a functionally disordered but structurally intact network should. The second is molecular access, which determines which agent can work, and it inverts across indications: long-acting human analogues reduce stroke risk while short-acting exendins do not, yet exenatide lowers intracranial pressure in idiopathic intracranial hypertension because the choroid plexus lies outside the blood-brain barrier. Chronic migraine occupies the reversible, extra-barrier quadrant. Recent receptor-level work shows GLP-1-derived peptides inhibit TRPV1 noncompetitively at an extracellular site without hyperthermia, and that a fragment relieves pain independently of GLP-1 receptor signalling. This generates a falsifiable prediction - analgesia separable from weight loss - and a trial design capable of refuting it.

Abstract: Peripheral neuropathy from diabetic, oncological, or traumatic etiologies degrades gait mechanics, increasing peak plantar pressures (PPP) and tissue ulceration risks. This feasibility study evaluates a customizable fabrication protocol using thermo-mechanically synthesized re-entrant auxetic foam insoles (sizes 6–11) with targeted dome-shaped inserts. Bilateral dynamic gait analysis was conducted across a heterogeneous neuropathic cohort (N=9; 5 females, 4 males) utilizing a P-Walk 600 pressure plate and a MARVUE 2D motion capture system. To control structural shoe variance across testing conditions, all subjects were equipped with standardized footwear featuring pre-installed conventional memory foam. To overcome small-sample parametric limits and evaluate structural predictability, a non-parametric bootstrap resampling analysis (B=1,000) was executed. The native auxetic foam demonstrated mechanical reliability, yielding a tightly bound distribution with a highly constrained bootstrap standard deviation (σ*) of 12.063 kPa and a baseline Consistency Rank of 1—indicating a 100% statistical probability of outperforming traditional controls. While a structural break-in period was required for re-entrant cell adaptation, custom insoles ultimately reduced PPP by up to 62.2% in systemic polyneuropathies, shifting the loading signature beneath the clinical safety target threshold (<200 kPa) in 55% of cases. Conversely, customization triggered an adverse volumetric crowding effect in focal mononeuropathies, identifying un-customized native foam as the superior intervention for localized trauma by preventing premature cellular self-contact. Re-entrant auxetic structures reliably accommodate heterogeneous pathomechanics, offering a mathematically verified pathway for advanced patient-specific orthotic interventions.

Abstract: Structured AbstractBackgroundGeneral medicine departments frequently encounter patients presenting with overlapping infectious, metabolic, cardiovascular, renal, respiratory, and autoimmune disorders. Such patients often require multidisciplinary management and individualized treatment strategies.ObjectiveTo describe the clinical characteristics, investigations, management approaches, and outcomes of a series of complex medical cases admitted to a secondary care hospital in Southern India.MethodsA retrospective observational case series was conducted using hospital records of nine patients admitted between May 2026 and June 2026 under the Department of General Medicine. Data regarding demographics, presenting symptoms, comorbidities, diagnostic investigations, therapeutic interventions, multidisciplinary involvement, and clinical outcomes were extracted and analyzed descriptively.ResultsThe case series included severe bronchopneumonia with respiratory failure (n=2), methotrexate-induced pancytopenia with diabetic ketoacidosis (n=1), viral fever with inflammatory polyarthritis (n=1), dengue fever with thrombocytopenia and hepatic dysfunction (n=1), infective myocarditis (n=1), acute kidney injury with urinary retention (n=1), obstructive uropathy secondary to bladder carcinoma (n=1), urosepsis (n=1), and necrotizing fasciitis with sepsis (n=1). Diabetes mellitus was the most frequent comorbidity. Intensive care support was required in five patients. Multidisciplinary care resulted in favorable outcomes in eight patients, while one patient required continued specialist follow-up for malignancy-related disease.ConclusionThis case series highlights the broad clinical spectrum encountered in general medicine practice and emphasizes the importance of early diagnosis, multidisciplinary collaboration, and individualized management in improving outcomes in complex medical patients.

Abstract: Abandoned paddy wetlands (APWs), which are converted from rice paddy wetlands (RPWs) due to natural or artificial cessation of farming, function as crucial carbon sinks. Although APWs serve as vital cultural and ecological resources providing essential ecosystem services, these excellent ecosystems are often inadequately managed, leading to rapid degradation and transformation into carbon emission sources. This study was conducted to quantify the carbon accumulation capacity of reference APWs distributed across the central region of the Republic of Korea. In accordance with the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance for Land Use, Land-Use Change and Forestry (GPG-LULUCF), soil samples were collected from each APW at a depth of at least 30 cm. Subsequently, soil organic matter (OM) content, soil organic carbon (SOC; g/kg), and soil organic carbon storage per unit area (SOCS; kg/m²) were calculated. Additionally, carbon absorption based on land cover was measured within the hydro-ecological impact zone (a 300-m buffer zone) surrounding the APWs, and carbon accumulation via the biomass of dominant vegetation was evaluated. For APWs dominated by woody plants, carbon storage was determined by tree height, diameter at breast height (DBH), and population size, whereas population coverage size determined carbon storage in wetlands dominated by herbaceous plants or mixed woody-herbaceous communities. The results revealed that the average OM of the APWs was 33.7 g/kg, and the SOC per unit weight was 19.54 g/kg. The accumulated SOCS per unit area was mathematically corrected from 67.97〖" kg/m" 〗^2 to 61.20±22.28〖" kg/m" 〗^2, which is approximately 8.5 to 40 times higher than the average SOCS of forest soils in South Korea (7.19 kg/m² in Jeju Island) and urban parks (1.56 to 2.84 kg/m²). Furthermore, the average carbon absorption within the hydro-ecological impact zone increased rapidly over time, rising from 20.45 tCO₂/ha in 2000 to 35.30 tCO₂/ha in 2013, and reaching 38.14 tCO₂/ha in 2021.

Abstract: Background: Respectful maternity care is recognized as a core component of high-quality maternal and newborn services, affirming women’s right to dignified, equitable, and person-centered care throughout pregnancy, childbirth, and the postnatal period. It goes beyond clinical safety to include emotional support, clear communication, respect for women’s autonomy, and protection from mistreatment. Family-centred maternal and newborn care complements this by actively involving women’s families and support networks, promoting shared decision-making and continuity of care from pregnancy through early neonatal life. Methods: A descriptive cross-sectional survey was conducted among midwives working in public maternity settings, using non-probability snowball sampling. Data was collected using a structured questionnaire that included demographic variables and a self-report checklist on antenatal, intrapartum, and postnatal support, as well as collaboration and support from healthcare professionals. Data was subsequently analyzed in SPSS Version 26 using descriptive statistics, exploratory factor analysis, and correlation. Results: Intrapartum support showed strong positive correlations with antenatal support (r = 0.555, p < .001) and immediate postpartum support (r = 0.529, p < .001), indicating significant associations. Similarly, human and safe care correlated positively with monitoring and interventions (r = 0.528, p < .001) and with immediate postpartum support (r = 0.559, p < .001). Conclusion: Enhancing support systems during the antenatal, intrapartum, postnatal, and early neonatal periods, together with strong professional collaboration and effective monitoring, can enhance the provision of respectful, high-quality, evidence-based care.

Abstract: Fowl adenovirus serotype 11 (FAdV-11) is an important viral pathogen affecting both broiler and layer chickens and is the primary causative agent of inclusion body hepatitis (IBH), resulting in substantial economic losses through reduced meat and egg production worldwide. Despite its economic significance, no commercial vaccine is currently available specifically against FAdV-11. In the present study, to the best of our knowledge, the first immunoinformatics-based multi-epitope vaccine candidate against FAdV-11 was designed using conserved regions of the penton and fiber proteins. Conserved B-cell, cytotoxic T-lymphocyte (CTL), and helper T-lymphocyte (HTL) epitopes were identified, screened for antigenicity, allergenicity, toxicity, and immunogenicity, and assembled into a multi-epitope vaccine construct using appropriate linker peptides and a β-defensin adjuvant. The designed vaccine exhibited favorable physicochemical properties and was predicted to be highly antigenic, non-allergenic, and non-toxic. Secondary and tertiary structure prediction, refinement, and validation confirmed the structural stability and reliability of the vaccine construct. Molecular docking and molecular dynamics simulation analysis demonstrated stable interactions with immune-related Toll-like receptors (TLRs), while immune simulation predicted robust humoral and cellular immune responses with the establishment of long-term immunological memory. Codon optimization yielded a Codon Adaptation Index (CAI) of 0.982, and in silico cloning into the pET-28a(+) expression vector suggested efficient recombinant expression in Escherichia coli. Collectively, these findings indicate that the proposed vaccine represents a promising candidate for the prevention of FAdV-11-induced IBH in poultry. Nevertheless, comprehensive in vitro and in vivo studies are required to validate its immunogenicity, safety, and protective efficacy.

Abstract: To systematically evaluate the growth heterosis and genetic characteristics of the hybrid offspring E. moara ♀ × E. tukula ♂, this study assessed the phenotypic growth pattern through a comparative breeding experiment and cytogenic and molecular genetic characteristics through integrated chromosomal karyotype and mitogenomic analyses. The results showed that at 9 months of age, the body weight of the hybrid offspring reached 137.08 ± 26.41 g, which was 1.50 times that of the maternal E. moara (91.60 ± 18.63 g), but significantly lower than that of the paternal E. tukula (178.19 ± 32.74 g), exhibiting a mid-parent growth heterosis (1.62%). The chromosome number of the hybrid offspring was 2n=48, with a karyotype formula of 2sm+1st+45t, NF=51, and an intermediate chromosomal composition between the parents. The mitochondrial genome was 16,405 bp, and its gene composition, arrangement order, base composition and codon usage preference were highly consistent with those of E. moara. A phylogenetic analysis further supported that its mitochondrial genome strictly followed maternal inheritance. This study provides a theoretical foundation for evaluating the breeding potential and germplasm characteristics of E. moara ♀ × E. tukula ♂ hybrids.

Abstract: In the broader context of the ecological transition, it is essential to identify solutions that ensure indoor environmental quality encompassing thermal, visual, acoustic, and indoor air quality conditions to safeguard occupant health and well-being. These solutions should also meet the demand for energy-efficient buildings. With specific regard to thermal environments, a distinction must be made between residential and non-residential settings, where comfort conditions can be achieved, and industrial environments, where thermal stress—and consequently health risks—may arise. To evaluate the quality of a thermal environment, key metrics are necessary. These include the Predicted Mean Vote (PMV) for thermal comfort, Predicted Heat Strain (PHS) and the Wet Bulb Globe Temperature (WBGT) for hot environments, and Required Insulation (IREQ) for cold environments, all governed by ISO-EN standards. The use of indices in residential and non-residential buildings outlines two critical challenges. The first relates to the fact that, in certain instances involving non-air-conditioned buildings, conditions can be borderline between comfort and thermal stress, which must be accurately identified. Secondly, the application of indices frequently neglects necessary variables, disregarding the fundamental limitations and operational boundaries inherent to both objective and personal input quantities. Moreover, the use of measurement devices inconsistent with the minimum requirements laid down by the standards in the field results in unwanted biases with unforeseeable consequences. This review explores the formulation, use, and limitations of the four indices mentioned, providing a perspective on their future development. It establishes the criteria for reliable long-term assessments of thermal and energy environments, encompassing the analysis of both hot and cold strains.

Abstract: Resolvent Monte Carlo estimates eigenvalues of large matrices by sampling Markov chains and reading the target value off a truncated resolvent quotient, trading exact arithmetic for a stochastic error that the almost-optimal sampling scheme is designed to suppress. We study when that error vanishes outright. We derive an exact closed-form identity for the variance of the moment estimators of a general, possibly signed matrix, and use it to isolate a hierarchy of zero-variance notions ranging from the most local, which constrains only the first draws, through the finite-truncation regime that a practical run can certify, to the global regime in which every moment estimator is deterministic. We separate determinism of the estimator from correctness of the eigenvalue it reports, and exhibit the exact conditions under which each notion holds and the examples that separate them. A single edgewise condition, which we call the eigen-triple condition, forces the truncated quotient to equal the target eigenvalue in finite samples; the associated moment and quotient variances are second order in the maximal edge defect and vanish at the eigen-triple. A linear-time procedure certifies the condition.

Abstract: Contemporary intensive care is operating in an environment with high complexity cases, large volumes of information, and vast physiological, biological and therapeutical data, collected from laboratory results, investigations, therapies for organ support, collected from systems that operate in parallel. The lack of interoperability contributes to infor-mation overload, alarm fatigue, and delayed decision-making. The Smart ICU concept has emerged to address these limitations by integrating medical devices, information systems and artificial intelligence into a unified system that allows interoperable data integration and predictive analytics. Aim: The purpose of this article is to provide a narrative review of the Smart ICU concept, with a specific focus on the cardiac intensive care unit. It summarizes Smart ICU architec-ture, data integration, clinical support and applicability in monitoring perioperative in-flammation in cardiac surgery. We describe the Smart ICU architecture, from data acquisition to storage and analytics, highlighting the difference between Smart ICU, Artificial Intelligence and Tele-ICU, and we underlie the predictive analytics as a supportive tool, and its influence on clinical out-come. Cardiac ICU application: Cardiac ICUs offer a data-dense, temporally well-defined model following cardiac surgery with cardiopulmonary bypass, where data concerning patients hemodynamics, perfusion data, biological and inflammatory markers intertwine. Cardiac Smart ICU models could recognize early signs of hemodynamic compromise and low car-diac output states and identify early indicators of post-cardiac surgery complications. Neutrophil activation and complete blood count–derived indices may be used as dy-namic biological data for Smart Cardiac ICU models. Conclusion: The Smart Cardiac ICU may support earlier risk stratification, therefore earlier diagnostic and therapeutic interventions, but its clinical value requires prospective, mul-ticentre validation. Cardiopulmonary bypass–induced inflammation may offer an ideal setting to integrate physiological, procedural, and immunological data into bedside pre-dictive models.

Abstract: This paper presents a machine learning-based decision support system for mul-ticlass defect detection, utilizing exclusively heterogeneous legacy process data to mini-mize manual inspection time in foundries. Validated on 51,377 products across 193 defect categories, the methodology resolves structural data inconsistencies through k-nearest neighbors (kNN) imputation and piecewise Winsorization. A multi-stage feature selection cascade, incorporating variance thresholding, correlation filtering, and Random Forest Feature Importance (RFFI), reduces the feature space from 139 to 78 process-critical varia-bles. Following Synthetic Minority Over-sampling Technique (SMOTE)-based class bal-ancing, five classifiers were benchmarked via 10-fold cross-validation and optimized us-ing the macro-averaged F3-score to mathematically penalize undetected defects. Light Gradient Boosting Machine (LightGBM) and Random Forest (RF) provided superior pre-dictive baselines. To enforce strict zero-defect constraints, an asymmetric risk function shifted decision boundaries, enabling risk-calibrated base models to reduce manual in-spection volume by 9.2% with zero defect escapes. To resolve conflicting predictions, mul-ti-algorithm decision fusion was implemented. By statistically evaluating the joint proba-bilities of the base models' post-calibration outputs, a Naive Bayes Stacking meta-classifier effectively neutralizes single-algorithm inductive biases. Ultimately, synthesizing these F3-optimized, risk-calibrated base models via meta-learning successfully isolated true de-fect-free components, maximizing the final inspection time reduction to 14.1% while strictly maintaining zero defect escapes.

Abstract: Background/Objectives The accurate estimation of glomerular filtration rate (GFR) is essential for assessing trends in the prevalence (CKD), yet standard serum creatinine (SCr)-based estimates (eGFR_SCr) are limited by individual variations in muscle mass. While demographic surrogates like age and sex are typically used to account for these variations, they often lead to eGFR misclassification in individuals. This study investi-gated whether normalizing SCr to Dual-energy X-ray absorptiometry (DEXA)-derived Lean Mass Index (LMI) improves the association with cardiometabolic risk. Methods We analyzed data from 11,143 adults (mean age 46.0 ± 17.2 years) in the Austrian LEAD (Lung, hEart, sociAl, boDy) cohort. Individual SCr concentrations were normalized to sex- and age-specific LMI reference values to calculate LMI-adjusted eGFR (eGFR_LMISCr). The strength of associations between eGFR_SCr and eGFR_LMISCr with cardiometabolic risk factors (dyslipidemia, hypertension, pre-diabetes/diabetes, and metabolic syndrome) was compared using age- and sex-adjusted logistic regression with bootstrap resampling. Results While eGFR_SCr and eGFR_LMISCr were highly correlated (R2 = 0.897), LMI adjust-ment led to significant reclassification between CKD stages G1, G2, and G3a. eGFR_LMISCr demonstrated significantly stronger associations with dyslipidemia, arterial hyperten-sion, pre-diabetes/diabetes, and metabolic syndrome compared to standard eGFR_SCr. Longitudinal analysis showed that LMI adjustment stabilizes eGFR change estimates, particularly in younger men. Conclusion Adjusting serum creatinine for LMI signifi-cantly enhances the epidemiological utility of GFR estimation. GFR_LMISCr improves car-diometabolic risk stratification, potentially offering a valuable method to "salvage" the utility and comparability of eGFR_SCr in historic cohorts in early-stage filtration impair-ment in settings where DEXA but not Cystatin C is available.

Abstract: Alpacas have gained increasing popularity in Poland; however, no official national standards for their husbandry have yet been established. This study aimed to evaluate alpaca husbandry practices on Polish farms using an anonymous questionnaire. A total of 44 farms were included in the analysis, all of which kept alpacas, while only 9.1% also maintained llamas. A high level of adherence to preventive healthcare practices was observed, with regular deworming implemented on 90.9% of farms and vaccination reported by all respondents. Dietary supplementation was also widely practiced, with vitamin D being the most frequently administered supplement (90.9%). However, the assessment of biosecurity measures revealed important deficiencies in epidemiological risk management, as only 59.3% of owners quarantined newly introduced animals before integrating them into the herd. These findings provide the first comprehensive overview of alpaca husbandry practices in Poland and may serve as a basis for future research and the development of official husbandry standards for alpacas.

Abstract: Moringa stenopetala is a nutritionally rich medicinal plant widely used in traditional medicine for managing metabolic, infectious, inflammatory, and chronic diseases. Despite its extensive ethnomedicinal use, its pharmacological effects and safety profile are reported variably across experimental and regulatory studies. To summarize the pharmacological activities, safety profile, and experimental evidence of Moringa stenopetala based on in vitro and in vivo studies. A narrative synthesis of published experimental studies, including in vitro assays, in vivo animal models, toxicity studies, and chemical analyses, was performed. Studies evaluating metabolic, antimicrobial, cardiovascular, neurological, anticancer, reproductive, and toxicological outcomes were included. The findings were synthesized qualitatively. This review demonstrated that Moringa stenopetala possesses broad pharmacological activities in both in vitro and in vivo models. Leaf extracts at 250–500 mg/kg for 14–28 days significantly reduced blood glucose, improved lipid profiles, and restored pancreatic β-cells in diabetic animals. Antioxidant studies showed strong radical-scavenging activity and increased levels of endogenous antioxidant enzymes. Antimicrobial investigations demonstrated potent antibacterial and antifungal effects, with MIC values as low as 0.31 mg/mL. Antiparasitic studies using 400 mg/kg for 7 days reduced parasitemia and improved survival in infected mice. Cardiovascular studies using 10–1000 mg/kg extracts showed antihypertensive, vasorelaxant, diuretic, and natriuretic effects. Additional studies reported analgesic, anti-inflammatory, anticonvulsant, neuroprotective, antidiarrheal, and anticancer activities. Toxicological evaluations showed favorable safety profiles, with LD50 values >5000 mg/kg and minimal organ toxicity. Moringa stenopetala possesses broad pharmacological potential supported mainly by preclinical evidence. However, toxicity studies indicate possible dose-dependent safety concerns, particularly at high exposure levels. The absence of human clinical confirmation highlights the need for further translational and clinical research.

Abstract: Marine plastic debris provides persistent artificial substrates for microbial colonization, yet the fungal component of the plastisphere remains poorly characterized. Using ITS metabarcoding and culture-based isolation approaches, we characterized the early mycobiome associated with polyethylene, polypropylene, polystyrene, and polyethylene terephthalate (PET) plastic pellets deployed in an Eastern Mediterranean Sea (EMS) marina. The sequence-based communities were taxonomically heterogeneous, with only a limited effect of polymer type. Ascomycota, Zoopagomycota, and Basidiomycota were the dominant phyla identified by the ITS sequence analysis, while Linderina and Starmerella were the dominant genera. In contrast, the cultured isolates belonged exclusively to the phyla Ascomycota and Mucoromycota, with the Aspergillus genus accounting for 52.3% of the isolates. We further recorded physiological responses of 11 Aspergillus isolates to pristine and UV-weathered PET, including attachment, pigmentation, and plastic gravimetric weight loss. A. niger OC26 also exhibited strong peroxidase activity, together with a broad transcriptional response to PET exposure, including 216 upregulated genes and significant enrichment of peroxidase- and membrane-associated functions. UV weathering induced a limited but distinct additional transcriptional shift. Together, these findings indicate that early plastic-associated fungal communities in the EMS are taxonomically diverse, and include metabolically versatile Aspergillus strains that mount distinct physiological and transcriptional responses to PET exposure.

Abstract: Cement-stabilized soil is widely used for ground improvement but suffers from brittleness and low tensile strength. This study investigates a sustainable composite integrating waste brick powder (WBP, 5%) and glass fiber (GF, 0–2.0%) to enhance mechanical performance and microstructural integrity. Unconfined compressive strength (UCS), splitting tensile strength (STS), and scanning electron microscopy were evaluated at 3, 14, and 28 days. Results reveal stress-state-dependent reinforcement: UCS peaked at 2.0% GF with gains of 18.1%, 7.3%, and 9.1%, while STS maximized at 1.5% GF (43% increase), declining 14.3% at 2.0% due to fiber agglomeration. Post-peak ductility improved markedly, with the residual strength ratio increasing from 12.4% to 43.2% and the ductility index from 1.18 to 1.85. Microstructural analysis confirmed that uniform fiber dispersion enables crack bridging and interfacial load transfer, whereas agglomeration creates localized weak zones. The composite avoids approximately 85 kg CO₂eq per cubic meter by valorizing construction waste. These findings establish quantitative, stress-state-dependent design guidance for sustainable cement-stabilized soil composites.

Abstract: Freshwater bivalves are a poorly represented but biogeographically informative component of Chilean inland waters. Their distribution offers a useful framework for evaluating latitudinal gradients, historical biogeography and the southern limits of non-marine molluscs in South America. Here, we present a georeferenced synthesis and annotated checklist of Chilean inland-water bivalves based on 90 occurrence records compiled from the literature and associated datasets. The records comprise 12 species in four genera: Diplodon, Musculium, Pisidium and Sphaerium, belonging to Hyriidae and Sphaeriidae. Diplodon chilensis was the most frequently recorded species, with 52 records and a latitudinal range from approximately 30.5°S to 46.6°S. By contrast, the southernmost records were represented by Sphaeriidae, especially Pisidium magellanicum from Laguna El Salto, Isla Navarino, at approximately 55.0°S. Other high-latitude records included Pisidium lebruni from Punta Arenas, Musculium patagonicum from Puerto Natales and Pisidium chilense from the Aysén Region. The dataset indicates contrasting biogeographical patterns between large-bodied hyriid mussels and small-bodied sphaeriid clams. Whereas Diplodon appears mainly associated with central-southern and Patagonian continental freshwater systems, Sphaeriidae extend farther south into Magellanic and sub-Antarctic environments. This contrast may reflect differences in dispersal capacity, ecological tolerance, habitat use and historical responses to Quaternary glaciations. The checklist and distributional synthesis provide a baseline for future taxonomic, phylogeographical and conservation studies of Chilean freshwater bivalves.

Abstract: Postoperative atrial fibrillation (POAF) after cardiac surgery is often managed as a transient inpatient arrhythmia, yet recurrent or silent atrial fibrillation (AF) after discharge may expose a vulnerable atrial substrate and change decisions about stroke prevention, anticoagulation and bleeding risk. This issue is particularly relevant in cancer survivors, in whom active malignancy, previous cardiotoxic therapy, frailty, anaemia, thrombocytopenia, hypercoagulability and planned oncological procedures can make standard POAF follow-up insufficient. This narrative review synthesises literature from POAF, cardio-oncology, wearable electrocardiographic monitoring and health informatics to examine whether digital rhythm surveillance could support post-discharge risk reassessment in this population. Direct evidence linking cancer, cardiac surgery, POAF and digital monitoring remains limited; therefore, the proposed “Digital Cancer-POAF Survivorship Pathway” is presented as a conceptual, hypothesis-generating framework for structured follow-up rather than as a validated clinical algorithm. Digital monitoring could improve detection of missed post-discharge AF, but only if results lead to clear clinical decisions, predefined AF-burden thresholds and prospective testing against clinical outcomes.