Search Results (1,500)

Pulmonary hypertension (PH) is a heterogeneous clinical syndrome in which similar haemodynamic abnormalities may arise from distinct vascular, cardiac, pulmonary, thromboembolic, and molecular mechanisms. This complexity limits the ability of conventional classifications and risk scores to fully capture individual disease trajectories and treatment responses. Artificial intelligence (AI) offers a framework for integrating clinical data, electrocardiography, multimodal imaging, invasive haemodynamics, biomarkers, and multi-omics information across the PH care pathway. This review summarises current applications of machine learning and deep learning in early detection, diagnostic referral, right-ventricular and pulmonary vascular phenotyping, molecular endotyping, risk stratification, and therapeutic decision support. Available studies show promising results for AI-assisted electrocardiographic screening, automated echocardiographic and cardiac magnetic resonance analysis, computed tomography (CT)-based phenotyping, and multimodal prognostic modelling. True multi-omics integration in PH remains limited to discovery studies and has not yet yielded externally validated endotype or treatment-response classifiers. Evidence maturity is task-dependent: screening and phenotyping span several PH groups, whereas validated risk tools, molecular endotyping, and pathway-directed therapy remain predominantly PAH-based, particularly in idiopathic/heritable PAH. However, most evidence remains retrospective, derives from selected referral populations, and lacks robust external or prospective validation. No AI-based model currently supports routine drug selection or autonomous clinical decision-making. Future progress will require harmonised multicentre datasets and standardised acquisition protocols, transparent and interpretable models, and prospective studies demonstrating meaningful clinical benefit. AI should therefore be viewed as an emerging decision-support tool that may strengthen precision medicine in PH while complementing clinical expertise across diagnosis, phenotyping, risk assessment, and therapeutic stratification pathways. Full article

The prototypical complex-forming reactions of OH + CO and OH + SO are critical elementary processes in atmospheric chemistry and combustion systems. The vibrational mode-specific quasi-classical trajectory (QCT) investigations for these two reactions were performed on full-dimensional globally accurate potential energy surfaces (PESs). Integral cross-sections (ICS), differential cross-sections (DCS), and product energy distributions for different vibrational excitation modes were calculated and analyzed. Although both exothermic oxygen-transfer reactions share similar topological features in their PES profiles, their energy landscapes exhibit pronounced differences, giving rise to entirely distinct dynamic and kinetic behaviors. This work will advance our understanding of how PES topology, collision energy, and mode-specific vibrational excitation jointly govern reactivity and energy dissipation in radical oxidation processes involving carbon- and sulfur-containing oxides. Full article

Background: Early post-transplant albuminuria is associated with adverse graft and cardiovascular outcomes and may reflect ischemia–reperfusion injury-induced damage to the glomerular filtration barrier. However, evidence for safe adjunctive interventions targeting these early pathophysiological processes remains limited. Methods: In this single-center prospective cohort study with historical controls, adult kidney transplant recipients transplanted between January 2020 and September 2022 served as controls, while consecutive recipients transplanted from October 2022 onward received adjunctive silymarin (900 mg/day for 30 days) in addition to standard immunosuppression. The principal renal outcome was UACR assessed during the first 3 months post-transplant. A ≥25% reduction in UACR between Months 1 and 3 was additionally evaluated as an exploratory responder outcome. Secondary outcomes included estimated glomerular filtration rate (eGFR), lipid profile parameters, tacrolimus exposure, and safety. Results: A total of 136 patients (78 silymarin-treated and 58 controls) were included. UACR was consistently lower in the silymarin group at months 1–3. In multivariable analysis, silymarin treatment was independently associated with lower UACR at month 3. In an exploratory responder analysis, a ≥25% reduction in UACR between Months 1 and 3 occurred more frequently in silymarin-treated patients (OR 3.28, 95% CI 1.38–7.79; p = 0.007). eGFR trajectories were similar between groups. No consistent independent effects on lipid parameters were observed after adjustment. Tacrolimus exposure and adverse event rates were comparable between groups. Conclusions: Short-term silymarin exposure initiated early after kidney transplantation was associated with lower UACR during the first three post-transplant months. These findings support a potential targeted effect on early glomerular injury and suggest that silymarin may represent a safe adjunctive strategy to modulate early post-transplant risk. Full article

The widespread use of location-based services (LBSs) has led to the continuous collection of user location and trajectory data, increasing the risk of privacy leakage and creating a persistent tradeoff between privacy protection and data utility. To address this problem in discrete location query scenarios, this paper proposes a single-point location privacy protection method based on Q-R tree retrieval and differential privacy, termed QRDPP. QRDPP combines the adaptive spatial partitioning capability of a Q-tree with the minimum bounding rectangle (MBR)-based indexing capability of an R-tree. It applies an improved geometric privacy budget allocation strategy to leaf nodes and an arithmetic allocation strategy to non-leaf nodes, followed by Laplace perturbation of the corresponding location data and node information. For continuous trajectory query scenarios, this paper proposes a spatiotemporal generalization and differential privacy method, termed STG-DPTP, to address inadequate temporal protection, inappropriate generalization, and trajectory distortion. STG-DPTP performs hierarchical spatiotemporal clustering, separately models temporal and spatial distributions using Gaussian kernel density estimation, dynamically optimizes bandwidth parameters through Bayesian optimization, selects representative candidate subsets using the exponential mechanism, and generates protected trajectories through constrained sampling. Experiments on the GeoLife dataset evaluate the proposed methods in terms of query accuracy, computational efficiency, spatial trajectory similarity, reconstruction error, adversarial uncertainty, and temporal preservation. The results show that QRDPP improves the utility and efficiency of privacy-preserving spatial queries, while STG-DPTP better preserves the spatial distribution, trajectory structure, and temporal characteristics of the original data under the adopted differential privacy framework. Full article

High penetration of wind and photovoltaic generation reshapes power system net-load profiles and increases the computational burden of repeatedly solving security-constrained unit commitment problems under multiple renewable scenarios. This paper proposes a fast schedule generation method based on historical schedule transfer. A library is constructed by pairing feasible unit commitment schedules with their corresponding 24 h net-load trajectories. For a target day, hour-wise, standardized net-load trajectories are compared using Euclidean distance, and the Top-K most similar historical schedules are selected as candidates. Each candidate is verified under the target-day operating conditions. When no candidate satisfies the feasibility or economic requirements, a limited-perturbation model is applied to repair the retrieved schedule with minimal changes in unit statuses. Case studies show that the proposed method effectively transfers historical commitment patterns, maintains operational feasibility and near-optimal economic performance, and reduces the computational effort required for unit commitment schedule generation. Full article

Chinese hamster ovary (CHO) cells are the principal platform for manufacturing recombinant biopharmaceuticals, but sustained production can exceed the protein-folding capacity of the endoplasmic reticulum (ER). Binding immunoglobulin protein (BiP/GRP78), encoded by Hspa5, is a major ER chaperone that supports folding and modulates unfolded protein response (UPR) signaling, yet increasing BiP abundance has produced beneficial or inhibitory outcomes depending on the recombinant product. Here, we introduced an additional Chinese hamster Hspa5 coding sequence under the constitutive EEF1A1 promoter into a CHO line producing a dulaglutide analogue comprising a modified GLP-1 peptide fused to human IgG4 Fc and compared the resulting stable DUL-BiP population with an empty-vector DUL-Neo control. At constant 37 °C, the two populations showed similar viable cell density and viability trajectories, whereas DUL-BiP cells continued extracellular GLP-1–Fc accumulation for approximately two days after accumulation in DUL-Neo cells had slowed and reached a 40% higher final titer in this experiment. Two independent temperature-shift experiments showed the same direction of the final-titer difference, although the increases were smaller and were accompanied by reduced peak viable cell density. Semi-quantitative immunoblot analysis of samples from the constant-temperature experiment showed a comparatively stable total BiP signal in DUL-BiP cells and a pronounced late increase in DUL-Neo cells, together with temporal changes in cleaved ATF6, eIF2α phosphorylation, and CHOP in both populations. Intracellular GLP-1–Fc did not progressively accumulate. Because the immunoblot time courses were derived from one biological fed-batch experiment, they are interpreted descriptively rather than as independent quantitative biological replicates. Stable constitutive expression of host-derived BiP was therefore associated with prolonged late-stage GLP-1–Fc accumulation in the producer population examined. These kinetics are compatible with a model in which the timing of ER chaperone supply influences the maintenance of productive output, while the underlying mechanism and generality to other producer populations or recombinant products remain to be established. Full article

Multi-parametric industrial time-series forecasting is important for predictive monitoring, soft sensing, and decision support in complex process industries. This study proposes a process-informed hybrid ARX-residual deep sequence architecture for short-horizon multi-output forecasting of fluid catalytic cracking unit (FCCU) product yields. The model combines a frozen linear ARX branch with causal temporal convolution, a three-layer GRU, causal self-attention, additive attention pooling, residual gating, and a consistency-regularized multi-output objective. Experiments were performed on an open simulated FCCU benchmark containing 20,160 one-minute observations from seven normal and disturbed operating scenarios. The leakage-controlled pipeline uses scenario-wise chronological splitting, train-only median imputation and standardization, exclusion of fault-timing metadata and direct algebraic target components, and 30 min causal windows for five-minute-ahead forecasting. Across ten prespecified random seeds, the proposed model achieved a historical-test RMSE of 0.022809 $\pm$ 0.000116, compared with 0.022751 for ARX-like Ridge. Dependence-aware statistical analyses did not establish a consistent statistical advantage for either model across the evaluated runs. Rolling-origin evaluation likewise showed similar point accuracy, while leave-one-scenario-out evaluation revealed severe extrapolation failure for the unseen pressure-drop scenario. The results support the reproducibility of the proposed architecture and the importance of the ARX-based dynamic structure, but they do not establish the statistical superiority of the full deep residual architecture. Independent industrial data or newly prespecified simulation trajectories are required for confirmatory external validation. Full article

In some scenarios, motorsport simulators have been used to enable the controlled acquisition of dense telemetry with high similarity to real-world data, reducing cost when assessing driving performance. However, although popular, performance analyses traditionally treat human control as deterministic and overlook the stochasticity of driving behavior. In fact, existing coaching methods which improve driving performance have to deal with two distinct outcomes: a driver who restructures his race control strategy and a driver who merely repeats it faster. This article presents a Behavior-First framework for interpretable driver behavior analysis that separates them. We characterize control signals with two information-theoretic descriptors: Jensen–Shannon divergence, which quantifies distributional distance from a proficiency-matched reference and whose square root satisfies the triangle inequality, and Permutation Entropy to measure the ordinal complexity of the input sequence. A deterministic, physics-informed heuristic layer then identifies kinematic performance gaps and emits structured tokens that a Large Language Model translates into natural-language coaching narratives. We evaluated the framework in an exploratory case study. The three beginners who received generated coaching messages and the single uncoached comparison participant exhibited different lap-time and information-theoretic trajectories. Because the groups were small and non-randomized, these observations describe within-driver evolution and do not estimate a causal coaching effect. Full article

Parent–child interaction frequency may vary during the transition into kindergarten and across activity content, but whether persistent or repeated low-frequency interaction is associated with preschool children’s emotional-behavioral and neurodevelopmental outcomes remains unclear. We examined whether three-wave overall and content-domain trajectories, together with cumulative low-level exposure at the overall, content-domain, and activity levels, were associated with final-follow-up outcomes. Among 526 children enrolled at baseline, 419 completed all three waves. Low exposure was defined as a score below the wave-specific 25th percentile, and adjusted logistic regression models estimated associations. Compared with the persistently normal trajectory, the persistently low overall trajectory was associated with higher odds of abnormal total emotional and behavioral difficulties (aOR = 3.46, 95% CI 1.01–11.86); each additional low-exposure wave was also associated with higher odds (aOR = 1.54, 95% CI 1.02–2.33), with similar findings for conduct problems. Nominal content-domain associations were concentrated in story-reading and environmental interaction trajectories, while nominal activity-level associations involved reading/picture-book viewing, learning about nature/animals/plants, and physical activity. Neurodevelopmental associations were fewer and less stable. By jointly characterizing temporal pattern, repeated low exposure, and activity content, this study illustrates the value of repeated and content-specific assessment alongside a single overall interaction measure. These dimensions may inform assessment in parenting support and early-childhood services, but intervention evidence is required before causal or activity-specific recommendations can be made. Full article

This study examines whether fertility-related employment penalties differ across countries at different stages of demographic transition, using Kenya and South Africa as comparative case studies. Using nationally representative Demographic and Health Survey (DHS) data, the analysis employs an instrumental-variable approach that exploits exogenous variation in fertility generated by twin births, with the sex composition of the first two children used as a supplementary robustness instrument. A Principal Component Analysis (PCA)-based Economic Independence Index is also employed as an alternative outcome measure to capture broader dimensions of economic autonomy. The results show that higher fertility significantly reduces women’s paid employment participation and broader measures of economic autonomy. Instrumental-variable estimates exceed ordinary least squares estimates, suggesting that conventional models underestimate the economic costs of childbearing. Fertility-related employment penalties are remarkably similar across Kenya and South Africa despite their different demographic transition trajectories, providing little evidence that lower-fertility contexts experience weaker employment penalties. The adverse effects are strongest among women with higher parity and lower educational attainment, highlighting important life-course heterogeneity. The study contributes comparative causal evidence on fertility-related employment penalties across two Sub-Saharan African countries using a common quasi-experimental identification strategy. The findings have implications for Sustainable Development Goal (SDG) 5 (Gender Equality) and SDG 8 (Decent Work and Economic Growth) by demonstrating that demographic change alone is unlikely to improve women’s labour-market outcomes. Instead, policies that reduce childcare constraints and strengthen women’s labour-force participation may help mitigate fertility-related employment penalties and promote more inclusive and sustainable development. Full article

Background/Objectives: Age may influence myocardial recovery after acute myocardial infarction (AMI) beyond changes in left ventricular ejection fraction (LVEF). We investigated age-related patterns in ischemic delay, admission biomarkers, biventricular function, myocardial deformation, and exploratory patterns of prescribed heart failure guideline-directed medical therapy (HF-GDMT) classes after primary percutaneous coronary intervention (PCI). Methods: This prospective frequency-matched cohort study included 90 AMI patients treated with primary PCI, stratified into younger (25–44 years; n = 30) and older (≥45 years; n = 60) groups. Clinical data, ischemic time, cardiac biomarkers, serial echocardiography at baseline, 6, and 12 months, and HF-GDMT intensity were analyzed. Results: Older patients had longer pain-to-balloon time (720 [480–1230] vs. 540 [420–660] min; p = 0.021), higher hs-cTnI (p = 0.045), and higher NT-proBNP (4776 [3013–5952] vs. 833.5 [95.7–1939.5] pg/mL; p < 0.001). Baseline and 12-month LVEF were similar between groups. Younger patients showed greater 12-month global longitudinal strain (GLS) improvement (−3.7 [−5.1 to −1.9] vs. −2.3 [−3.0 to −1.3] percentage points; p = 0.002), despite comparable absolute GLS. In exploratory post hoc analyses, prescribed HF-GDMT drug-class count showed an association with LVEF change primarily in older patients, who also had significantly lower baseline LVEF (ρ = 0.59; p < 0.001). Conclusions: In this prospective exploratory cohort, 12-month conventional systolic recovery assessed by LVEF and absolute GLS was comparable between age groups after primary PCI. However, the older comparator group had longer ischemic delay and higher admission biomarkers reflecting cardiomyocyte injury and myocardial wall stress, while younger patients showed greater longitudinal GLS improvement over time. These findings suggest that age-stratified recovery after AMI is better characterized by ischemic timing, baseline biomarker profile, and deformation trajectory than by LVEF alone. Because infarct size was not directly quantified, admission biomarker differences should not be interpreted as evidence of larger infarcts. Full article

Grouping vehicles with similar paths is important for traffic analysis, but camera-image trajectories are distorted by perspective, and unsupervised clustering does not directly reveal how many traffic movements should be expected. This paper presents Homography-Guided Semantic Maneuver Graph Trajectory Clustering (HG-SMG-TC), a model-selection framework that uses a lightweight homography to estimate intersection structure while retaining isotropically normalized camera coordinates for clustering. Entry and exit endpoint groups are consolidated into physical approach-level groups, and their supported origin–destination relationships form a maneuver graph. Bootstrap resampling converts this structure into an interval for the expected number of observed movements, which guides clustering model selection. The method is evaluated on 67,029 vehicle trajectories from five urban intersection scenes in the Traffic Node Video Dataset, using separate target-estimation, model-selection, and independent-test recording blocks. Independent polygon-rule reference labels cover 89.6–98.4% of test trajectories. HG-SMG-TC reduces mean target-count error from 3.20 for untargeted selection and 2.53 for the point-target variant to 2.13, while achieving an adjusted Rand index of 0.734 and normalized mutual information of 0.839. The results show that the proposed semantic maneuver prior improves target alignment and provides a reproducible way to guide unsupervised trajectory clustering, while retaining explicit trade-offs across evaluation metrics. Full article

Surrogate safety assessment in motorcycle-dominated mixed traffic requires screening methods that distinguish threshold-sensitive event prevalence from stable site, time, and interaction patterns. This study develops a TTC–THW-based site–time–interaction framework for engineering screening using 13.342 h of video from six Hanoi arterials, comprising 371,864 vehicles, 2,977,401 validated leader–follower observations, and 180,722 TTC-defined events. Primary window-level inference uses 799 complete non-overlapping 60 s windows; 3181 overlapping windows are retained only for sensitivity analysis. Increasing the TTC reference from 1.5 to 2.4 s raised the flagged-observation proportion from 12.04% to 17.99%, without changing the site ordering. A one-standard-deviation increase in median THW was associated with a 13.81% lower expected TTC-defined event rate per following exposure in the primary model (IRR=0.8619, 95% CI 0.8433–0.8809), with similar estimates under overlapping-window and AR(1) GEE specifications. Follower-clustered event models showed stable vehicle-pair contrasts across TTC-defined criticality cut-points of 0.6, 0.8, and 1.0 s; the MC–Car odds ratios were 1.440, 1.352, and 1.273, respectively, relative to Car–Car. Alternative THW boundaries and empirical tertiles retained the main temporal-compression contrasts. Downsampling from 7.5 to approximately 3.75 Hz reduced absolute event counts by about 30.6–30.7% but left comparative site rankings unchanged. The framework therefore provides trajectory-based interaction screening rather than crash-risk prediction or independently validated near-crash classification. Full article

Accurate cloud segmentation from ground-based fisheye camera imagery is essential for solar irradiance forecasting and photovoltaic system optimization. Traditional computer vision approaches, such as HSV thresholding and K-means clustering, face significant limitations when applied globally to sky images due to the spectral similarity between cloud regions and sky areas under varying atmospheric conditions. This study presents a hybrid methodology that leverages YOLOv8 instance segmentation to provide contextual cloud regions followed by refined HSV thresholding within these detected areas. The approach incorporates solar trajectory modeling using pvlib for accurate sun disk detection and exclusion, preventing false cloud classification. The methodology was developed and validated at the CIESOL using Mobotix Q71 fisheye cameras, and later tested in Antofagasta (Chile) and Huelva (Spain). The YOLOv8l-seg model achieved a mask precision of 0.821 and box mAP@0.5 of 0.680 on validation data. The results show a promising correlation with radiometric measurements such as clearness index $k_t$ and diffuse fraction $k_d$ in preliminary validation cases. While YOLOv8 demonstrates good cross-site generalization, HSV thresholding requires camera-specific calibration for optimal performance. The method addresses the context-dependency limitations of traditional algorithms, though computational performance and broader validation remain areas for future work. Full article

Coastal green tides may alter nearshore bioaerosols through coupled marine, atmospheric, and meteorological processes, yet their effects on airborne microbial communities remain poorly resolved. Atmospheric samples were collected in Aoshan Bay, Qingdao, China, during five phases of the Ulva prolifera green tide in 2019 (pre-bloom, 19 April; early bloom, 15 June; middle bloom, 15 July; late bloom, 6 August; post-bloom, 30 August); seawater samples were collected at one nearshore site on each of the five sampling dates, with microbial sequencing performed for the middle-bloom (15 July) and late-bloom (6 August) phases. Bacterial and fungal communities were characterized; although bioaerosols may also contain microalgae and viruses, this study profiled only the bacterial and fungal fractions, using bacterial 16S rRNA gene (V3-V4 region) and fungal internal transcribed spacer (ITS2) amplicon sequencing and evaluated together with meteorological variables, air-pollutant concentrations, and 72-h backward air-mass trajectories. Proteobacteria dominated the airborne bacterial assemblages (81.28–97.83%), with Sphingomonas as the most abundant genus (47.85–89.84%). Basidiomycota and Ascomycota dominated the fungal assemblages, whereas Cryptococcus and Alternaria were the major fungal genera. Community richness and composition varied across bloom phases. Chytridiomycota was undetected before the bloom (0%), appeared after bloom onset, and reached its highest relative abundance during the middle phase (8.19%). Spatial patterns indicated joint terrestrial and marine influences, although bacterial communities in seawater and air remained highly dissimilar. Temperature, relative humidity, particulate matter, ozone, and air-mass origin were associated with changes in microbial diversity and composition. These findings provide an observational baseline for coastal bioaerosol dynamics during a macroalgal green tide, extending the HAB–bioaerosol literature—which has focused predominantly on cyanobacterial blooms—to a large green macroalga. Bacteria and fungi showed contrasting environmental responses: bacterial richness increased with temperature, whereas fungal diversity declined. Greater compositional similarity between seawater and air for fungi than for bacteria suggests differential environmental filtering at the air–sea interface and implies that multiple source pathways—direct aerosolization, sea-surface release, and in-situ atmospheric production—may differentially shape the two domains. Given the single-date-per-phase sampling design, the absence of sequenced laboratory contamination controls, and the lack of absolute abundance data, these results should be regarded as preliminary and hypothesis-generating, underscoring the need for ASV-level source tracking, controlled chamber experiments, and replicated multi-year designs in future assessments of bloom–atmosphere interactions. Full article