Search Results (777)

Accurate pavement performance prediction is critical for effective pavement management systems (PMS), enabling optimal maintenance and rehabilitation decisions. The Pavement Condition Index (PCI) is the most widely used performance indicator, yet reliable prediction requires models that capture full spectrum of deterioration drivers, including structural characteristics, traffic loads, and the increasingly impactful extreme climate events. While machine learning (ML) approaches have improved PCI prediction, most existing models overlook climate extremes. This study proposes a comprehensive ML-based PCI model that integrates extreme climate variables from the Expert Team on Climate Change Detection and Indices (ETCCDI). Eleven algorithms were evaluated on a dataset combining pavement age, structural characteristics, traffic loads, and extreme climate variables. Among the evaluated models, categorical boosting model achieved the lowest error values and the highest R² (0.81). Explainability analyses using feature importance and SHapley Additive exPlanations (SHAP) identified the number of icing days (ID), daily temperature range in December (DTR_Dec) and consecutive dry days (CDD) as the extreme climate indicators with the greatest negative predictive influence on PCI. Incorporating ETCCDI indices provided additional explanatory power beyond traditional annual average climatic variables, significantly improving both predictive accuracy and model interpretability. These findings highlight the importance of integrating standardized extreme climate indicators into PMS frameworks to support more resilient and sustainable pavement management under evolving climate conditions. Full article

Background/Objectives: Diabetic neuropathy (DN), a common complication of type 2 diabetes mellitus, manifests as peripheral nerve dysfunction with symptoms such as fatigue. Although exercise effectively reduces fatigue in neuropathy patients, precise detection methods are crucial to elucidate the role of rehabilitation. Accordingly, this study aimed to evaluate fatigue in DN patients using a multimodal approach (clinical and instrumental) and to compare the efficacy of aerobic versus resistance training on fatigue parameters. Methods: Eligible DN inpatients admitted for rehabilitation at the Neuromotor Rehabilitation Unit of the IRCCS ICS Maugeri Institute of Montescano (PV) were enrolled. Inclusion criteria included age between 65 and 85 years and confirmation via the Michigan Neuropathy Screening Instrument (anamnestic section: ≥7; clinical section: ≥2.5). Patients with confounding orthopedic, neurologic, or unstable cardiopulmonary/diabetic conditions were excluded. Overall, 36 participants were randomized into two groups: 17 underwent aerobic training (treadmill), while 19 received resistance training (elastic bands), both as supplements to a standard rehabilitation program. Assessments at baseline and post-training comprised clinical measures (Borg CR10 scale, Functional Independence Measure (FIM) total and subitems, Six-Minute Walk Test (6MWT), fasting blood glucose) and instrumental evaluations (sEMG of the tibialis anterior muscle to analyze conduction velocity intercept, slope, and changes). Results: All patients completed the protocol without dropout or adverse events. Both groups demonstrated significant improvements in FIM scores and post-exercise perceived exertion over time. Instrumental sEMG analysis confirmed a physiological fatigue trend manifested as conduction velocity reduction, yet revealed no significant differences between groups. Conclusions: Multimodal assessment provides an effective means to characterize fatigue in DN patients. Both aerobic and resistance modalities enhance functional independence and fatigue perception. Its early identification enables clinicians to tailor rehabilitation strategies to overcome exercise barriers. Full article

For the last three summers in Canada (2023–2025), and episodically in Siberia over the previous decade and a half, severe consequences from wildfires represent major ecological and societal impacts: the displacement of inhabitants; destruction of buildings, timber and infrastructure; and far-field air pollution. Wildfire occurrence is increasingly supported every summer by persistent surface warming and widespread atmospheric moisture deficits. The two recent major Canadian fire years in 2023 and 2025 show some contrasts: 2023 was dominated by an early June event with preconditioning, whereas 2025 saw repeated single events spanning June to early August, culminating in a significant late-summer event. Events in both years were associated with North Pacific–North American atmospheric blocking regimes. Over the longer term, 2003–2025, normalized June–September wildfire fraction anomalies in the Canadian sector (45–60° N, 150–60° W) show the post-2023 period as having new, clear, record-breaking fire intensities, highlighting wildfires as emerging dominant Arctic–subarctic extremes. Siberia shows an increase after 2010. Although multiple environmental Arctic–subarctic extremes are ongoing—such as sea-ice loss, storms, and glacial ice loss—the impacts from wildfires represent preeminent, growing societal consequences. Full article

Background: Coronary artery disease (CAD) commonly coexists with chronic obstructive pulmonary disease (COPD), but may be under-recognised, since symptoms such as dyspnoea and chest discomfort are often attributed to lung disease. We hypothesised that coronary artery disease is highly prevalent in patients with COPD, even in the absence of typical angina symptoms. Methods: This study aimed to detect CAD in patients with COPD. We conducted a single-centre observational study, including 76 patients with no known previous cardiovascular events. To detect ischaemic heart disease, three methods were used, according to standard clinical indications: coronary angiography, coronary CT, and calcium score analysis on chest CT. The findings were categorised according to lesion severity and vessel involvement. Results: A substantial proportion of patients with COPD harboured previously undiagnosed atherosclerotic coronary disease (78%). However, most detected disease was non-obstructive atherosclerosis (56%), whereas severe stenosis was present in approximately one-third of patients (32%). Single-vessel disease accounted for 37% of cases, while the remaining patients exhibited multi-vessel involvement. Nevertheless, only a small proportion of patients had typical angina symptoms (11.8%), and the most frequent complaint was effort dyspnoea (50%). Patients not receiving inhaled corticosteroid therapy were more likely to have extensive coronary artery disease (χ² (6)= 14.228, p = 0.027). Conclusions: These findings support our hypothesis that atherosclerotic coronary disease is often under-recognised in patients with COPD. ICS-containing therapy appeared to be associated with less extensive coronary artery involvement; however, this observation should be interpreted cautiously. Full article

Aerosol–cloud interactions (ACIs) remain a long-standing uncertainty in quantifying cloud microphysical properties, convection, and precipitation. There are fewer investigations into the effects of ACIs on the southwest vortex (a mesoscale circulation with a spatial scale of 300–500 km). Satellite-retrieved MODIS data (2002–2022) reveals a decreasing trend in the June–August (JJA) seasonal mean ice droplet effective radius (DER_Ice) over the Sichuan Basin (SCB) since 2013, corresponding to China’s emission reduction efforts. Concurrently, post-2013 trends exhibit a positive shift in cloud-top height (CTH) and a negative trend in cloud-top pressure (CTP), collectively indicative of intensified convective activity. This contradicts the conventional conclusion that increased anthropogenic emissions reduce droplet effective radius (DER) and intensify convection under constant cloud water content. To address this discrepancy, we simulated the precipitation event caused by the southwest vortex (SWV) during 11–14 August 2020, under distinct initial aerosol loading (clean vs. polluted), using the fully coupled WRF-ACI-Full cloud-resolving model (incorporating sophisticated aerosol parameterizations). Results show that increased aerosols reduce basin-averaged precipitation by 0.54% and updraft speed by 0.37% in the polluted case compared to the clean case, which is negligible. These findings differ from previous studies on ACI-related cloud and precipitation responses. Full article

Modern oceanographic studies demonstrate that marginal seas and semi-restricted marine environments, including epicontinental seas and carbonate platforms, are highly sensitive to changes in circulation, freshwater input, stratification, and redox conditions, allowing climatic perturbations to be recorded with high fidelity. Understanding the behavior of such systems under icehouse conditions is therefore important for interpreting climate variability in both ancient and modern oceans. The Late Paleozoic Ice Age was a prolonged icehouse interval characterized by repeated glacial and interglacial oscillations, yet its climate dynamics are still mainly constrained by Gondwanan glacigenic records and low-latitude carbonate successions. High-resolution climate information from mid-latitude regions remains limited. The purpose of this study is to obtain high-resolution mid-latitude geochemical constraints on climate variability during the Late Paleozoic Ice Age using a semi-restricted marine carbonate succession. Specifically, this study aims to (1) establish high-resolution carbon and oxygen isotope records from well-preserved carbonate samples spanning the Visean to Asselian interval; (2) identify and characterize major glacial to interglacial cycles recorded in the succession; (3) evaluate the extent to which semi-restricted paleogeography amplifies isotopic responses relative to coeval low-latitude open-marine settings and (4) assess the climatic significance of a short-lived negative carbon isotope excursion during the middle Bashkirian. Here we present high-resolution carbon and oxygen isotope records from a Visean to Asselian marine carbonate succession deposited in a semi-restricted basin. Stable isotope analyses of well-preserved carbonate samples document temporal variations in carbonate carbon and oxygen isotopes. The records resolve at least three major glacial to interglacial cycles, with isotope shifts substantially larger than those reported from coeval low-latitude open-marine settings. Carbon isotope variations reach up to 7.7‰, while oxygen isotope variations reach up to 9.2‰. These pronounced responses are attributed to semi-restricted paleogeography, facies heterogeneity, and the sensitivity of marine carbonate systems to stratification, redox variability, and organic carbon cycling. A short-lived negative carbon isotope excursion during the middle Bashkirian may record a Northern Hemisphere deglaciation event superimposed on the broader Gondwanan icehouse background, a signal that is not clearly expressed in other regions. Overall, this study describes new mid-latitude geochemical constraints on Late Paleozoic climate variability and offers valuable analogs for understanding climate responses in modern marginal marine systems. Full article

The downscaling of VLSI technologies has exacerbated the susceptibility of integrated circuits (ICs) to radiation-induced Single-Event Transients (SETs). This work presents UPSET, a comprehensive and technology-independent EDA framework for probabilistic SET analysis using Static Timing Analysis (STA). Unlike traditional simulation-based methods that suffer from prohibitive runtimes, UPSET leverages graph-based propagation with advanced logical, electrical, and timing-window masking models to evaluate circuit sensitivity efficiently. Key contributions include a novel “Electrical Masking Window” (EMW) criterion that effectively filters non-full-rail pulses early in reconvergent logic and a TimeStamp-based propagation mode that accurately handles complex signal reconvergence with Boolean evaluation. The experimental results over some featured benchmarks demonstrate a speedup of more than 25,000× compared with SPICE while maintaining a tight 4.56% error bound in pulse width estimation. Moreover, experimental validation on 50 benchmarks across varying complexities showcases that EMW enhancement reduces the pessimism to circuit sensitivity by up to 25% on average, providing tighter upper bounds while maintaining scalability to million-gate designs. By integrating seamlessly with standard industrial formats (LEF, DEF, LIB, or SPEF), UPSET enables scalable, accurate soft SET sensitivity assessment for modern digital designs, establishing a robust foundation for automated radiation hardening flows. Full article

The outcomes of the Winter Storm URI in Houston (February 2021) and its impact on awnings highlighted how climate change has altered the load combinations considered in design codes such as ASCE 7-16, introducing new uncertainties due to freezing storm events. Previously unused load categories are now presenting significant challenges, as designers assumed sufficient safety factors would prevent failures. This research investigates the consequences of the storm and offers guidelines for conservative awning design in zero ground snow load zones, emphasizing wind load as the primary design load in regions with no active snow zone. Additionally, an attempt has been made in this research to examine the importance of anchor reliability in concrete structures, particularly under environmental stress such as winter storms. Factors like improper installation, edge distance, and embedment depth significantly affect anchor performance, potentially leading to premature failure modes like concrete breakout, pullout, or rusting from water accumulation. Through field investigations and theoretical analyses, the research evaluates the axial load capacity of anchors, taking into account edge distance, embedment depth, and environmental factors like ice accumulation. The study stresses the need for proper anchor geometry, drainage, and reinforcement to ensure structural safety. By following the proposed recommendations, engineers can mitigate adverse effects and enhance the durability and safety of concrete structures, even under extreme weather conditions. Full article

Background: Motor imagery-based brain-computer interfaces (MI-BCIs) enable individuals who are unable to perform physical movements to interact with the external world by imagining movements. Users are typically classified as good performers or BCI-illiterate based on the classification accuracy of distinct EEG patterns (e.g., 60% or 70%). Yet, studies show that approximately 70% of users fall within intermediate accuracies between 60% and 80%, and although exceed the chance level, they often fail to achieve reliable MI-BCI control. Intermediate users often exhibit asymmetric motor imagery abilities between left and right hands, highlighting the need for refined early assessment and stratified training approaches. Methods: We employed ICA to decompose each participant’s EEG data and extract independent ERD/ERS components as indicators using a rule-based automated framework. This framework integrated dipole localization, ERD/ERS characteristics, and frequency-band power features of ICs. Importantly, we applied a power spectral parameterization approach to remove the 1/f-like background activity in power estimation and used statistical methods to precisely estimate the latency and duration of ERD. The extracted indicators were subsequently subjected to clustering analysis to categorize participants into four groups. Results: In addition to good performers (24.8%) and poor performers (35.8%), two groups were identified: LgoodRpoor (27.5%), who performed well in left-hand MI but poorly in right-hand MI, and LpoorRgood (11.9%), who showed the opposite pattern. Notably, these unilateral performers did not show significant differences in contralateral ERD but exhibited substantial differences in ipsilateral ERS. Conclusions: The proposed independent event-related brain dynamics model enables more refined stratification of MI-BCI users. Findings from this characterization study may inform the design of graded training protocols, especially for users demonstrating unilateral motor imagery proficiency. Full article

Background/Objectives: Proton pump inhibitors (PPIs) are widely used, yet questions persist about kidney-related adverse events. We evaluated disproportional reporting of acute kidney injury (AKI) and tubulointerstitial nephritis (TIN) with PPIs in the FDA Adverse Event Reporting System (FAERS) from 2020 to 2025. Methods: FAERS reports were screened using MedDRA Preferred Terms. Report characteristics and annual counts of AKI and TIN reports were summarized. Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Empirical Bayes Geometric Mean (EBGM), and Information Content (IC) were used to assess disproportionality. Results: We identified 13,654 PPI-associated AKI reports and 2409 TIN reports in FAERS (2020–2025). Reports were predominantly from the United States, and missing age/sex information was common. Hospitalization was reported in 12.3% of AKI and 22.7% of TIN reports, and death in 9.1% and 5.0%, respectively. Across all years, disproportionality analyses using ROR, PRR, EBGM, and IC consistently met signal thresholds for both outcomes, with stronger signals in 2020–2022 and attenuation thereafter alongside declining report counts. Conclusions: FAERS data show persistent disproportional reporting of AKI and TIN with PPI use. Causality cannot be inferred, but the findings support cautious, indication-based PPI prescribing and highlight the need for robust studies to clarify renal safety. Full article

Ice cores retrieved from the Third Pole provide invaluable information about past and present environmental changes. Here we present, for the first time, a continuous tritium and plutonium isotope profile of the Puruogangri ice field, Tibetan Plateau, China, for the last 70 years. The age-depth profile has been composed by different time anchors such as the onset of thermonuclear weapon tests, the so-called bomb peak of tritium, the Chernobyl event, and the time of ice coring. The accumulation rate of ice calculated from the age-depth relation shows a decrease after 1963. It was 57, 15, and 22 cm/year in the periods of 1954–1963, 1963–1986, and 1986–2023, respectively. The concentrations of plutonium isotopes (²³⁹Pu: up to 2.7 fg/g) are slightly lower than those of the Belukha ice core, Siberian Altai, Russia, and almost the same as the Miaoergou glacier, eastern Tien Shan, China. Contrary to this latter ice core profile, the Puruogangri plutonium profile reflects that the Chinese weapon test started in 1966. This is confirmed by the tritium time series as well. ²⁴⁰Pu/²³⁹Pu atomic ratios vary between 0.14 and 0.23, with an average of 0.177 ± 0.024. The overall obtained local fallout of ²³⁹Pu and ²⁴⁰Pu is 13.2 and 9.0 Bq/m² (4.0 and 1.1 ng/m²), respectively. Full article

Variance-driven decomposition based on the singular spectrum analysis of the European Project for Ice Coring in Antarctica (EPICA) δD, CO₂, and CH₄ records allowed a novel quantitative structural interpretation of all glacial/interglacial cycles and glacial terminations of the last 800 kyr. This bottom-up approach used the response components of EPICA stacked records to reconstruct the envelope of the thermal response through a physical interference model. The aim was to improve understanding of the intensity, amplitude, and asymmetry features of 73 marine isotope stages/substages (MISs) and seven glacial terminations. The Antarctic stack record can be described by a variance-weighted superposition of ten thermal waves of different origins (mid-term oscillation, orbitals, and suborbitals) that stochastically interfere at a given time according to their relative differences in frequency, amplitude, and polarity. Interglacial/glacial stages resulted from constructive interference and bipolar amplification of warming/cooling responses, respectively. The low-intensity MISs (including 90% of substages) and the unbiased-dated terminations fell in the low-interference regions, where dominant destructive patterns minimize the thermal envelope. The positive skewness of the EPICA stack resulted from constructive interference with a strong bias in the warming direction, especially after the Mid-Brunhes Event. Duration analysis of short eccentricity hemicycles exhibited an intrinsic unexpectedly prolonged mean cooling in the nominal solution (5.8 kyr) and its EPICA response as well (8.6 kyr), along with an interference-induced asymmetry (21.1 kyr). The overall effect has led to the saw-tooth shape of glacial cycles, which was strongly induced by interference. Full article

Adaptive locomotion requires the integration of cognitive and motor processes and is challenged in neurological disorders. Dual-task (DT) training may improve cognitive–motor coordination, but its feasibility across heterogeneous clinical populations is uncertain. This pilot study aimed to understand if the effects of a secondary motor or cognitive task added to a walking task depend on the functional walking abilities of the subjects. We enrolled 30 participants with neurological disorders not related to traumatic events, 5 for each one of the following groups: healthy young subjects (HeY), healthy control subjects (HeC), subjects with stroke (ictus, IC), Parkinson’s disease (PD), multiple sclerosis (MS), and Long-COVID sequelae (LC). Spatiotemporal gait parameters were recorded using a wearable inertial magnetic unit, and subjective workload was assessed with the visual analog scale (VAS) and NASA-Task Load Index. Regression models revealed strong baseline–DT coupling for stride duration (slopes 1.11–1.37; R² 0.85–0.97), stride length (slopes 0.93–0.94; R² 0.86–0.93), walking speed (slopes 0.87–0.98; R² 0.78–0.93), and gait ratio (stance/swing, slopes 0.38–0.60; R² 0.21–0.52). Mixed-effects analyses identified significant group effects for walking speed (F(5) = 7.218, p < 0.001), stride length (F(5) = 4.834, p = 0.001), gait cycle duration (F(5) = 5.630–5.664, p < 0.001), Walking Quality (F(5) = 4.340–4.373, p = 0.001), and propulsion index (F(5) = 5.668–6.843, p < 0.001). The incongruent DT condition was the most sensitive in differentiating clinical groups. NASA-TLX indicated higher perceived workload in IC and MS compared with non-clinical groups. The protocol was completed by all participants without adverse events, supporting the feasibility of the procedure in this pilot sample. Its predictable scaling across baseline gait metrics supports its use as a personalized rehabilitation tool for diverse neurological populations. (ClinicalTrials.gov NCT07254377). Full article

Between the 15th and 17th centuries, as the Northern Hemisphere entered the Little Ice Age, the scale and frequency of hailstorms increased. In Ming Dynasty China, following the Han Dynasty’s “Interaction Between Heaven and Mankind” doctrine and the pre-Qin Confucian classic Zuo Zhuan’s interpretation that “when a sage rules, there is no hail,” linked these disasters to the moral conduct of the emperor. Others took a more agnostic, naturalistic approach, but in both cases, scapegoating was largely avoided. Building on existing Western scholarship on the link between witch hunts and hail, this paper will use Chinese classical interpretations, historical records of hail events from the Ming Dynasty, and the reactions of emperors and Confucian scholars as a point of reference. It aims to compare and contrast the different understandings and responses to hail disasters in Ming China and Europe. Full article

In nanometer integrated-circuit (IC) manufacturing, advanced technology scaling has intensified the effects of process variations on circuit reliability and performance. Random fluctuations in parameters such as threshold voltage, channel length, and oxide thickness further degrade design margins and increase the likelihood of functional failures. These variations often lead to rare circuit failure events, underscoring the importance of accurate yield estimation and robust design methodologies. Conventional Monte Carlo yield estimation is computationally infeasible as millions of simulations are required to capture failure events with extremely low probability. This paper presents a novel reliability-based circuit design optimization framework that leverages deep transfer learning to improve the efficiency of repeated yield analysis in optimization iterations. Based on pre-trained neural network models from prior design knowledge, we utilize model fine-tuning to accelerate importance sampling (IS) for yield estimation. To improve estimation accuracy, adversarial perturbations are introduced to calibrate uncertainty near the model decision boundary. Moreover, we propose a cascaded batch Bayesian optimization (CBBO) framework that incorporates a smart initialization strategy and a localized penalty mechanism, guiding the search process toward high-yield regions while satisfying nominal performance constraints. Experimental validation on SRAM circuits and amplifiers reveals that CBBO achieves a computational speedup of 2.02×–4.63× over state-of-the-art (SOTA) methods, without compromising accuracy and robustness. Full article