Search Results (221)

Recursive evidence fusion gives an intrusion detection system temporal memory, but it also gives unreliable windows and erroneous review outcomes a path to influence later diagnoses. Existing drift-handling, open-set, conformal, continual-learning, and human-in-the-loop methods provide useful signals or update classifiers and memories; they do not, by themselves, specify when a post-classification evidential state may be written or replaced. We present RTEF-IDS, a protocol that separates current action, model-evidence admission, reviewed-feedback admission, and history replacement. The protocol retains the history-relative reliability principle from our previous work, instantiates it for singleton-plus-ignorance IDS evidence, and assigns operation-specific credentials. Reviewed windows make no base-state change, mapped-known feedback may be appended, and replacement requires persistent confirmation. On 33,384 frozen windows, 30% retrospective admission excludes 26.3% of held-out-or-misclassified mass while retaining 94.8% of known-correct evidence. Under paired imperfect feedback, retrospective replacement increases one-window future history-state agreement by 0.107 in the primary block and 0.129 in IoT-23 leave-scenario-out replay. Under a past-only rolling-budget gate within externally supplied frozen partitions, the corresponding increments are 0.001 and 0.000, indicating that the tested gate exposes few qualifying replacement opportunities; bounded external short streams show the same opportunity constraint. Independent second review reduces false authorization from 5.66 to 0.124 per 1000 first-stage reviewed windows under independent errors and from 34.27 to 0.181 under five-window correlated errors, with a corresponding increase in review demand and a reduction in admitted corrective feedback. A shared systematic label alias remains unresolved by the tested review arms. These results support explicit, auditable state-mutation control while identifying the causal-opportunity and feedback-provenance conditions under which it operates. Full article

We develop a sheaf-theoretic framework for shape analysis of covered shapes, where measure is introduced only after the underlying local-to-global topological structure has been established. Starting from a finite cubical complex together with a finite admissible cover, we build a finite topological model from the overlap structure of the cover and define a component sheaf on this model. The local data of the sheaf records the connected pieces visible on individual patches, while the maps between them describe how these pieces fit together across overlaps. The resulting degree-zero sheaf cohomology recovers the connected components of the full shape by the standard descent of locally constant functions. We show that the isomorphism class of this sheaf is an invariant of covered shapes, that it strictly refines ${\beta }_0$ for a fixed labeled cover and can distinguish some shapes with identical full Betti vectors, although it does not determine higher Betti numbers in general, and that it behaves functorially under symmetries preserving the cover. For dyadic covers, we distinguish the overlapping closed cover used by the sheaf from a paired half-open measurable partition, investigate measurable refinements, introduce monotone notions of local complexity under corrected refinement hypotheses, construct canonical sheaf-induced measures on both the index set and the ambient domain, and establish convergence and localization results for regular closed sets under pixel refinement. The sheaf-theoretic axiomatization therefore offers two complementary benefits: topologically, it provides a finite-space and cohomological invariant of covered shapes; measure-theoretically, it gives a principled hierarchy of quantitative summaries built only after the local gluing structure has been preserved. Full article

Background/Objectives: Elderly patients with acute upper gastrointestinal bleeding (UGIB) are a high-risk group with significant morbidity and mortality. Various risk scoring systems have been devised to predict clinical outcome in UGIB, but their effectiveness in geriatric patients is unclear. The purpose of the present study was to evaluate the predictive performance of established UGIB risk scores in older adults and to compare the predictive performance of the C-reactive protein–albumin–lymphocyte (CALLY) index with conventional UGIB risk scores. Methods: This study was a retrospective single-center analysis of a cohort of patients aged ≥65 years presenting with acute non-variceal upper gastrointestinal bleeding (UGIB) who had esophagogastroduodenoscopy from January to December 2025. Scores for Glasgow-Blatchford Score (GBS), Rockall, AIMS65, ABC, MAP(ASH), CANUKA, T-score, and CALLY index were calculated. The primary management endpoint was the requirement for endoscopic hemostatic treatment. Secondary outcomes were blood transfusion necessity, rebleeding, intensive care unit (ICU) admission, length of hospital stay, and 30-day death. The predictive performance of each scoring system was assessed by receiver operating characteristic (ROC) curve analysis. Results: We enrolled 113 patients (mean age 77.7 ± 8.3 years; 59.3% male), of whom 42 (37.2%) required endoscopic hemostatic treatment. No single risk score consistently outperformed the others across all clinical outcomes. GBS showed the highest observed AUC for predicting the need for transfusion (AUC = 0.892), whereas Rockall showed the highest observed AUC for rebleeding (AUC = 0.739) and ICU admission (AUC = 0.668). In the exploratory mortality analysis based on seven deaths, the directionally corrected AUC was 0.846 for CALLY, 0.756 for MAP(ASH), and 0.742 for CANUKA; no pairwise AUC comparisons were performed for this outcome. The CALLY index showed modest discrimination for endoscopic hemostatic therapy (AUC = 0.664). In the exploratory rebleeding analysis, CALLY yielded an AUC of 0.724; however, this estimate was based on only eight events. Lower CALLY levels were associated with increased 30-day mortality, whereas the CALLY index was not significantly associated with transfusion requirements or length of hospital stay. After correction for multiple comparisons, CALLY showed significantly lower discriminatory performance for transfusion requirement than GBS, T-score, CANUKA, and MAP(ASH), whereas no significant differences were observed for endoscopic intervention or ICU admission. Conclusions: No single risk score was able to predict all clinically important outcomes in older adults with acute UGIB. Conventional scoring systems remained useful for several established clinical outcomes, whereas the CALLY index showed modest discrimination for endoscopic hemostatic therapy. Its findings for rebleeding and 30-day mortality were exploratory because of the limited number of events and require external validation. More prospective multicenter studies are needed to confirm the clinical value of the CALLY index in older individuals with UGIB. Full article

Soft-ground finite-element analyses commonly reduce curved Oedometer compression to one constant slope, obscuring where stress-level curvature affects boundary-value predictions. AJOP-T embeds the differentiable Arc Joint via Optimum Parameters map in continuous teardrop bounding-surface plasticity while retaining the inherited yield geometry, non-associated flow, radial mapping and SMP-transformed stress. High-order denotes only the map’s derivative hierarchy: its first two derivatives define tangent hardening and hardening curvature, not gradient, fractional, nonlocal or rate order. This first-phase formulation is deliberately rate-independent and retains constant κ to isolate compression-map hardening; time-dependent and nonlinear cyclic swelling responses are outside its claims. The formulation recovers constant-slope hardening asymptotically, yields a closed-form admissibility boundary, is invariant under SMP, and recovers the parent isotropic normally consolidated settlement equation. Four natural-clay compression maps were fitted; triaxial evidence is fitted for comparison except for one held-out Eastern Osaka extension path. Three implementations agree to at least five significant figures. Paired undrained strip-footing analyses reduce centre settlement by 31.8% in the curved regime but only 0.27% near the high-stress asymptote. A predicted 1.6% low-stress strength-ratio drift is below the reviewed data scatter and is not claimed as experimentally validated. Full article

Entity-aware quality assessment may reduce false interpretations of electronic health record (EHR) data, but evidence from small, rule-aligned benchmarks cannot establish operational effectiveness. We revised H-StreamQ as a proof-of-concept framework and evaluated its laboratory component using the complete MIMIC-IV v3.1 labevents file (158,374,764 events; 313,442 patients). Ten thousand patients were sampled across laboratory-activity quintiles and split at patient level into training (6000), threshold-calibration (2000), and test (2000) groups. The independent test set contained 918,651 numeric laboratory events. Without excluding naturally alerted records, 54,788 mutually exclusive defects were introduced using subtle value shifts, unit/scale errors, mapping errors, delayed records, and patient-clustered correlated defects. Rules, a context-aware Isolation Forest, their union (Hybrid), a context-free Isolation Forest, Local Outlier Factor (LOF), and linear and radial-basis-function (RBF) One-Class support vector machines (OCSVMs) were compared at a threshold fixed by a 2.5% calibration alert budget. Patient-cluster bootstrap intervals and event-micro and patient-macro results were reported. Rules alone achieved the highest event-micro F1-score (0.637; 95% confidence interval [CI] 0.547–0.722), followed by Hybrid (0.576; 0.484–0.668) and RBF One-Class SVM (0.559; 0.433–0.670). Hybrid increased recall over rules by only 0.004 (95% CI 0.003–0.006) while reducing F1 by 0.061 and increasing the background-alert rate by 0.015. Context conditioning did not improve aggregate Isolation Forest performance. In six batch-level drift simulations, an exponentially weighted moving average (EWMA) and a fixed-window monitor detected 97–100% and 98–100% of changes, respectively, whereas a custom Hoeffding adaptive-window detector was more conservative and often missed smaller or recurrent changes. These results support H-StreamQ as an explainable research framework, not as a validated clinical or production system. Patient-macro F1, which weights every patient equally, was substantially lower than event-micro F1 for every method (rules 0.395 versus 0.637; Hybrid 0.320 versus 0.576), indicating that event-level performance is weighted towards high-activity patients. Precision and F1 are computed relative to injected synthetic labels and are not clinically adjudicated estimates. The entity-aware architecture spans patients, admissions, diagnoses, transfers, and dictionaries, but the quantitative detection benchmark evaluates the numeric laboratory component only; other entities are used for linkage and contextual attachment and are audited descriptively rather than evaluated against labels. Full article

The conductor temperature of cross-linked polyethylene (XLPE) high-voltage direct-current (HVDC) cables governs ampacity assessment and insulation life management, yet it cannot be measured in service, and finite-element simulation is too expensive for real-time use. This paper presents a physics-informed neural network (PINN) that embeds the transient heat-conduction equation, a temperature-dependent Joule source, and the boundary and initial conditions into the training loss of a neural surrogate. Three ingredients adapt the framework to power cables: a layer-aware material mapping over the eight heterogeneous cable layers; an electro-thermal coupling through the temperature dependence of the conductor conductivity, handled during training by a convergent Picard-type evaluation of the Joule source; and a condition-embedding input treating the load current and ambient temperature as continuous parameters so that a single network covers the admissible current–ambient envelope of the studied cable configuration. Validated against finite-element references under fifteen operating conditions, the model attains a root-mean-square error of $0.0024$ K (mean over five training seeds) on a held-out condition relative to a finite-element reference whose mesh-discretization error a refinement study bounds at about $0.04$ K while reducing the governing-equation residual by approximately 28-fold relative to an identically sized data-driven network at statistically indistinguishable pointwise accuracy. The physics prior also renders degradation under training-data reduction more graceful and improves extrapolation to unseen ambient temperatures, whereas current extrapolation remains the most challenging transfer. The differentiable surrogate identifies the load current and the unmeasurable conductor hotspot from ten surface sensors within seconds, at below 9 ms per ${10}^5$ queries. A loss-weight sensitivity study and a three-dimensional cable-end-effect case on a second material configuration are also reported. All reference data are numerical; experimental cable-loop validation remains for future work. Full article

A control that cannot be audited is a control that does not yet exist operationally. Commercial off-the-shelf (COTS) Internet of Things (IoT) devices in Ambient Assisted Living (AAL) environments expose this problem sharply: they export raw behavioural telemetry rather than the security-auditable event records required by the logging and monitoring controls of ISO/IEC 27001:2022. This study formalises that deficit as the Admissibility Gap, a weighted, field-level measure of the mismatch between native device output and the evidentiary requirements of Annex A. An audit of four publicly available AAL datasets (CASAS, SPHERE, UCI HAR, OPPORTUNITY) confirms that identity attribution, integrity, firmware version, and privacy-minimisation governance fields are universally absent, establishing that the gap is systemic. To close it, this study proposes the Compliance Transformation Layer, an edge middleware applying three rules: LDAP-based identity attribution, keyed HMAC-SHA256 integrity sealing with firmware baseline injection, and privacy-preserving GPS truncation. An experimental campaign on 10,000 synthetic records reduced the weighted Admissibility Gap deficit from 57.0% to 4.7% (an illustrative figure under the authors’ weight vector; because the transformation rules apply deterministically, this is a demonstration of sufficiency rather than an independent validation, and its direction is robust to the weighting), with outputs mapped to the Microsoft Sentinel Common Event Format schema and the BSI IT-Grundschutz OPS.1.1.5 logging requirements. Benchmarking on Raspberry Pi 4 hardware yielded a mean per-record latency of 1.574 ms at idle, demonstrating that audit-ready logging is achievable from the edge gateway inward on commodity hardware without hardware or firmware modification. The integrity and identity guarantees are enforced from the point of gateway ingestion; the device-to-gateway segment is treated as a declared trust boundary. Full article

This paper develops an analytical framework for the joint design of central bank digital currency (CBDC) and its underlying ledger architecture. We treat a digital monetary system as a tuple M = (S, R, C, I)—supply state, rule set, circulation parameters, and incentive structure—and read centralized, permissioned-distributed, and hybrid ledger designs as parameter settings on M. Two analytical propositions extend the framework. Proposition A locates a threshold above which a retail holding cap ceases to bind, building on the Brunnermeier–Niepelt neutrality condition. Proposition B characterizes the fixed point of the rule-update map under bounded policy shocks and reports its mean-square convergence rate. Each proposition is paired with a stylized numerical exercise; neither claims empirical validation. A comparative section then traces how the institutional environments of Singapore, the European Union, the United States, and China fix admissible regions in M before any architectural choice. What we contribute is a parametric vocabulary for techno-institutional comparison, not a new architecture; the principal limitation is the absence of pilot-data calibration, which we list as the highest-priority continuation. Full article

This paper investigates a nonlinear inverse problem in a time fractional diffusion-wave equation, in which a spatially varying potential coefficient is recovered from noisy final-time measurements. A local uniqueness result for the inverse problem is first established in a finite-dimensional admissible space. To support the reconstruction, the Fréchet derivative of the forward map and its adjoint representation are derived to provide the gradient information required in the inversion procedure. A Banach space regularization scheme with a combined $L^1$ and $L^2$ penalty is then proposed to stabilize the nonlinear inverse problem, and the resulting nonsmooth minimization problem is solved by a locally linearized split Bregman iterative scheme. Numerical experiments in one and two spatial dimensions demonstrate the accuracy and stability of the proposed method for smooth, corner-type, localized, and discontinuous coefficient profiles. Full article

Hydrodynamic cavitation is increasingly investigated as a process-intensification technology for liquid processing and complex or waste-derived streams. Conventional Venturi cavitators rely on fixed geometries selected for nominal operating conditions, whereas practical processes may involve variable fluid properties, flow rates, pressure conditions, and treatment objectives. This mismatch can produce unstable cavitation regimes, excessive or insufficient treatment severity, and inefficient use of pressure energy. This article introduces the Dynamic Circular Venturi Adaptive (DCVA), a reconfigurable circular Venturi framework in which the internal profile is treated as an operating variable rather than only as a fixed design feature. Unlike the previously proposed Dynamic Venturi Reuleaux Actuated (DVRA) concept, which uses a non-circular Reuleaux-section Venturi with boundary-imposed swirl, the DCVA retains an axisymmetric circular geometry and relies on controlled profile reconfiguration without swirl forcing. The framework defines equivalent geometric parameters, an admissible design space, plant-measurable operating indicators, and representative architectures for single-parameter and multiparametric reconfiguration. A numerical demonstration of the parametric design workflow is provided using an automated axisymmetric finite-element computational fluid dynamics (CFD) procedure that links CAD generation, meshing, flow simulation, post-processing, and iterative geometry updating to identify the throat configuration associated with cavitation inception. The results support CFD-assisted configuration selection, commissioning-map development, and future supervisory control, while prototype realization and experimental benchmarking remain necessary for full device-level validation. Full article

Background/Objectives: Poly(lactide-co-glycolide) (PLGA) microspheres support long-acting drug delivery, but their release profiles are difficult to predict because burst release, diffusion, polymer degradation, and formulation-dependent effects interact across multiple time scales. This study aimed to develop a continuous-time model that combines accurate release prediction with physically admissible trajectories and release-component attribution. Methods: MC-NODE encodes ten drug, polymer, and formulation descriptors, decomposes the non-negative release rate into burst, diffusion, degradation-associated late-stage, and neural-residual components, and applies a formulation-dependent plateau through a semi-analytical state map. The model was evaluated on a literature-curated dataset containing 321 in vitro release curves, 4913 observations, 89 drugs, and 113 publications using DOI-grouped five-fold cross-validation, complementary extrapolation and sparse-sampling protocols, synthetic mechanism-recovery experiments, and retrospective orthogonal consistency analysis. Results: MC-NODE achieved an RMSE of $0.094\pm 0.005$ and an $R^2$ of $0.854\pm 0.018$, with all 321 out-of-fold trajectories satisfying monotonicity and range criteria. It recovered synthetic contribution labels more accurately than the ablated variants. The degradation-associated late-stage contribution showed positive associations with experimental degradation, molecular-weight loss, pore-evolution, and mass-loss indicators, while the diffusion contribution was positively associated with an experimental diffusion indicator. Dominant-process agreement was 83.3%, and matched external or out-of-fold trajectories achieved an RMSE of $0.108\pm 0.020$. Under drug-grouped, chemical-cluster, and alternative sparse-sampling evaluations, MC-NODE retained the lowest absolute trajectory-level errors among the compared models. Conclusions: MC-NODE improves formulation-level PLGA release prediction while preserving continuous, monotonic, and bounded trajectories. Its component outputs provide experimentally supported, model-attributed summaries for comparative formulation analysis. Full article

Reliable nonlinear structural analysis requires hysteretic parameters that reproduce cyclic stiffness, strength, pinching, degradation, and energy dissipation. Conventional calibration is often tailored to one constitutive model and unit system, while repeated population searches become costly as dimensionality and parameter coupling increase. This study develops a unified physics-constrained deep reinforcement learning framework for OpenSees Steel02 and DowelType identification. Target responses and candidate parameters are expressed in dimensionless coordinates; bounded latent variables are decoded into admissible model parameters and mapped back to source units after calibration. A twin-delayed deep deterministic policy gradient (TD3) agent performs continuous search, with differential evolution providing local refinement when required. Validation used synthetic targets, random initial vectors, public steel records, and ten experimental hysteresis records from the authors’ research group; particle swarm optimization and a genetic algorithm served as benchmarks. The framework satisfied an NRMSE threshold of 0.02 in all 384 held-out Steel02 evaluations and achieved a mean NRMSE of 0.0166 on synthetic DowelType targets. On the ten experimental DowelType records, TD3+DE reached a mean NRMSE of 0.0654 and 30% success under the relaxed 0.05 threshold, giving accuracy comparable with tuned PSO at the same online OpenSees-call budget while retaining a reusable learned initialization step. One normalized workflow can rapidly obtain response-equivalent fits for distinct hysteretic laws and return solver-ready parameters in physical units. Full article

Cerebrovascular diseases are among the leading causes of mortality and disability worldwide. This study aimed to identify geographic patterns and sex differences in unplanned hospital admissions for cerebrovascular diseases, and to assess their association with ambient air pollution within small areas of Asturias, a northern region of Spain that exhibits elevated rates of mortality and morbidity from these pathologies. The study included 20,305 unplanned hospital admissions recorded between 2016 and 2023. Standardized admission ratios, smoothed relative risks, and posterior risk probabilities were estimated using reparameterized Besag–York–Mollié models at the census tract level. Global and Local Moran’s I statistics were computed to evaluate the spatial correlation of admissions. Subsequently, estimates of PM₁₀ and PM_2.5 concentrations were incorporated into the models, adjusting for average net income per person, to assess their association with admission risk and their contribution to the geographical patterns observed. Spatial analysis revealed marked inequalities in cerebrovascular admissions both between sexes and across small areas. High-risk clusters were consistently identified in the north-central coastal area for both sexes. For men, higher PM₁₀ and PM_2.5 levels were statistically significantly associated with hospitalizations (PM₁₀: RR = 1.08, 95% CI: 1.02–1.14; PM_2.5: RR = 1.22, 95% CI: 1.07–1.40, per 5 µg/m³ increase) and explained part of the spatial variability observed. For women, neither pollutant showed statistically significant associations nor appeared to be associated with the geographic patterns. Integrating both geographic and sex-related factors is essential for identifying high-risk areas and potential risk factors in the burden of cerebrovascular disease. In men, exposure to PM₁₀ and PM_2.5 was associated with cerebrovascular hospitalizations and explained part of the spatial variability observed, while no such association was found in women. Full article

The integration of information technologies into operational technology (OT) environments that encompass industrial control systems (ICSs), Supervisory Control and Data Acquisition (SCADA) systems, and critical infrastructure such as water and wastewater management facilities has introduced significant cybersecurity vulnerabilities alongside urgent questions of ethics and accountability. The existing digital forensic ethics frameworks were developed for enterprise IT contexts and provide no specific governance for investigations conducted within safety-critical OT environments, where a forensic misstep can disrupt water delivery or disable safety controls. This paper employs a four-stage qualitative research design that consists of a systematic literature review, ethical framework analysis grounded in principlism cyberethics principles, forensic process mapping, and multi-case analysis of five documented real-world incidents to address this gap. The paper identifies and categorizes six primary ethical challenges that are unique to OT/ICS/SCADA digital forensics, maps each to the investigative phase at which it arises, proposes theWater ICS SCADA Ethical Digital Forensics (WISE-DF) framework as a six-phase principled investigation model with ethical safeguards embedded as mandatory procedural gates, and provides actionable recommendations for investigators, organizations, and policymakers. Validation employs three complementary approaches: standards-alignment against the National Institute of Standards and Technology (NIST) Special Publications (SP800-82r3) and Internal Report (IR 8428), the AmericasWater Infrastructure Act of 2018 (AWIA 2018), and the Environmental Protection Agency (EPA 2024); counter-argument testing of each recommendation; and Daubert-consistency evaluation assessing whether WISE-DF compliance produces forensic evidence that is capable of meeting U.S. federal admissibility requirements. Although the Daubert standard applies specifically to U.S. federal proceedings, the ethical framework and WISE-DF gates are designed to be generalizable across jurisdictions. Water and wastewater management serves as the primary illustrative case domain; the framework is designed to be generalizable across OT sectors. Full article

Background and Objectives: The Hypotension Prediction Index (HPI) is a predictive algorithm that enables proactive management of intraoperative hypotension (IOH) and has been integrated into finger cuff devices for practical use in obstetric settings. This study aims to evaluate the effectiveness of HPI in reducing IOH during elective cesarean sections (CS). Materials and Methods: This randomized controlled trial enrolled parturients undergoing elective CS under spinal anesthesia. The parturients were randomized to either the HPI or the control group using non-invasive blood pressure (NIBP) monitoring. The primary outcome was the time-weighted average mean arterial pressure below 65 mmHg (TWA-MAP < 65 mmHg). Secondary outcomes included maternal nausea and vomiting, intraoperative fluid and vasopressor requirements, incidences of hypertension and bradycardia, estimated blood loss, duration of high-dependency unit admission, fetal Apgar scores, umbilical cord pH, and length of neonatal intensive care unit (NICU) stay. Results: A total of 100 parturients were enrolled in the study, with 96 included in the analysis. Baseline demographic characteristics were similar between the groups. The TWA-MAP < 65 mmHg was significantly lower in the HPI group (0.24 [0, 0.70] vs. 1.67 [0.71, 2.57] mmHg; p < 0.001). The incidence of intraoperative and postoperative nausea and vomiting were significantly reduced in the HPI group (p < 0.01). Incidence of intraoperative hypertension and bradycardia, fetal Apgar scores, umbilical cord pH, and length of NICU stay did not differ between the two groups (p > 0.05). Conclusions: HPI-guided management was associated with a reduction in hypotension burden and perioperative nausea and vomiting. Full article