Search Results (20,789)

This paper investigates distributed optimization-assisted output consensus for nonlinear multi-agent systems with mutually incommensurate Caputo orders, unavailable velocity-like states, bounded disturbances, measurement noise, and actuator saturation. A mixed-power exact penalty flow generates practical optimal references from local costs and intermittent neighbor broadcasts. The penalty gain and a smoothing bias bound are determined from a public interval, topology information, and certified local gradient data without prior knowledge of the aggregate optimizer. An autonomous decaying threshold provides event-triggered communication, an initial condition-independent fixed-time practical certificate for the integer-order optimizer, and exclusion of finite-time event accumulation. The physical layer is analyzed with established Caputo quadratic inequalities and agentwise Mittag–Leffler comparison. Fractional reference and command filters, a composite observer, and two-gain anti-saturation compensation form the output feedback controller, while the physical result is formulated as a finite-horizon regional verification certificate. Numerical studies include same-model and communication budget comparisons, a recent method-inspired optimizer benchmark, certificate tightening, and robustness tests for initialization, the fractional order, measurement noise, and the integration step size. Full article

Permeability prediction and hydraulic rock typing in carbonate reservoirs remain challenging because similar porosity values may correspond to markedly different flow capacities controlled by pore throat size, connectivity, and capillary accessibility. This study aims to develop an integrated workflow for permeability prediction and petrophysical–hydraulic rock typing of a heterogeneous dolomite reservoir using parameters that directly characterize the drainable pore throat network. Routine core analysis, centrifuge-derived capillary pressure curves, nuclear magnetic resonance $T_2$ spectra, electrical measurements, petrographic and SEM observations, and fractal descriptors were jointly analyzed. Capillary pressure curves were fitted with the Li–Horne model and transformed into equivalent pore throat radius distributions; characteristic radii $R_q$, Swanson and Capillary-Parachor parameters, irreducible water saturation, and fractal characteristics were calculated for subsequent regression analysis and rock typing. The conventional $k-\varphi$ relationship showed limited predictive capability, whereas models incorporating $R_{15}-R_{21}$ provided a more reliable permeability estimate. The best-performing relationship was close to $k\propto R^2\varphi$, supporting the interpretation of $R_{20}$ as a centrifuge-derived analog of the effective hydraulic radius. Comparison with FZI, Winland R35, NMR groups, and electrofacies showed that $R_{20}$-based typing produced a compact separation of samples by hydraulic quality. The proposed workflow is presented as a single-well proof of concept and requires validation in independent wells before application to field-scale geological and hydrodynamic models. Full article

The introduction of Connected and Autonomous Vehicles (CAVs) into the existing traffic system represents one of the greatest challenges of modern road traffic engineering. Beyond their role as active traffic participants, CAVs can also be regarded as mobile (floating) sensors, effectively turning the vehicle fleet itself into a distributed, city-wide and motorway-wide sensing infrastructure. The transition from fully human-driven vehicles to fully autonomous vehicles will take decades, giving rise to a prolonged mixed-traffic period in which vehicles with different levels of automation share the same road space. This paper analyses the parameters and measures used for evaluating the throughput, environmental impact, and safety of traffic networks at different CAV penetration rates. It further reviews studies that rely exclusively on data collected from CAVs acting as mobile sensors, examining data-aggregation and traffic-state-estimation methods used to reconstruct macroscopic traffic parameters such as flow, density, headway, and speed. Additionally, measures for evaluating specific use cases for CAVs including mobility-on-demand services and their cost comparison with human-driven taxi operations are also addressed. The energy and emissions implications of CAV deployment, including the added burden of sensing hardware and system-level rebound effects, are also examined. Based on the synthesis performed, a set of representative CAVs penetration rates is proposed as a standardised framework for future mixed-traffic flow evaluations. Full article

Background/Objectives: Prehospital identification of non-ST-elevation acute coronary syndrome remains unresolved, and available risk scores incorporate troponin categorically. We compared the discriminative performance of cardiac troponin I measured in a blood sample obtained at first prehospital medical contact, analysed as a continuous variable, against the HEART, GRACE, and TIMI scores for predicting 30-day major adverse cardiac events. Methods: We conducted a prospective cohort study in 333 adults with non-traumatic chest pain suggestive of non-ST-elevation acute coronary syndrome, which was attended by two physician-staffed advanced life support units. Venous blood was drawn at first medical contact and analysed later in the laboratory; the results were not available during patient care. All three scores used this same determination as their troponin component. The primary outcome was a composite of all-cause mortality, type 1 myocardial infarction, and unplanned coronary revascularisation at 30 days. Results: The primary outcome occurred in 82 patients (24.6%). Prehospital troponin discriminated better (area under the curve 0.916, 95% CI 0.875–0.952) than TIMI (0.817), GRACE (0.767), and HEART (0.721); all comparisons were p < 0.001. An exploratory rule-out threshold of 80 ng/L identified 61 patients (18.3%) with no events (sensitivity and negative predictive value 100%, exact 95% CI 95.6–100 and 94.1–100), whereas the ≥780 ng/L stratum showed an event rate of 69.4%. Conclusions: A blood sample obtained at first prehospital medical contact carries substantial prognostic information that clinical scores discard by categorising it. Because it was analysed subsequently in the laboratory, these findings do not evaluate a real-time strategy; they support development and validation of point-of-care devices. Full article

Shear-wave time-of-flight (TOF) measurement enables controlled assessment of frequency-dependent wave propagation, but its feasibility in biological tissues remains insufficiently established. This study evaluated whether a custom shear-wave TOF device could detect frequency- and direction-dependent responses in ex vivo tissues. Three porcine liver samples and three chicken breast samples were examined. Chicken breast was measured with propagation parallel and perpendicular to visible muscle fibers. One-cycle sinusoidal excitations were applied at 40–160 Hz, with 50 acquisitions ensemble-averaged per sample–frequency measurement. TOF was estimated using Tx threshold detection and cumulative-energy-based Rx onset detection, and TOF-derived apparent shear-wave propagation speed was calculated from the Tx–Rx distance and the measured TOF. Frequency-dependent data were fitted using the Kelvin–Voigt fractional derivative model to obtain model-dependent KVFD fit parameters. Signal quality was assessed, and a preliminary descriptive comparison with HISKY EQTouch UD3000 (Wuxi Hisky Medical Technologies Co., Ltd., Wuxi, China) SWE was performed. All 63 averaged sample–frequency measurements satisfied the predefined primary-detection criteria. Mean apparent shear-wave speed was 3.145 m/s in porcine liver, 6.133 m/s in chicken breast measured parallel to the fibers, and 5.914 m/s in chicken breast measured perpendicular to the fibers, giving a parallel-to-perpendicular speed ratio of 1.037. Mean post-averaging, post-processing SNR ranged from 24.47 to 31.52 dB. The UD3000 comparison showed the same tissue ranking. The device detected frequency- and direction-dependent responses in averaged ex vivo signals, supporting its feasibility as a controlled research platform. Claims of absolute stiffness accuracy and intrinsic muscle anisotropy require independent calibration and validation. Full article

We investigate the dynamic magnetic properties of an epitaxial Co₂₅Fe₇₅ thin film grown on a MgAl₂O₄ (001) substrate using broadband ferromagnetic resonance (VNA-FMR). The film exhibits a pronounced fourfold symmetry of the resonance field, characteristic of cubic magnetocrystalline anisotropy. By combining broadband and angular-dependent FMR measurements, we determined a spectroscopic g-factor of 2.083 ± 0.017, an effective magnetization of 1655 ± 31 kA/m, and a cubic magnetocrystalline anisotropy field of 28.25 ± 0.22 mT. Beyond the expected angular dependence of the resonance field, we experimentally demonstrated a pronounced flattening of the frequency versus magnetic field dependence for magnetic field direction located between the principal crystallographic axes. The effect, predicted by conventional ferromagnetic resonance theory but not previously investigated in detail, originates from the equilibrium rotation of the magnetization and is quantitatively described within the Stoner–Wohlfarth framework. For ${\varphi }_H$ = 34°, the resonance frequency remained nearly constant over the magnetic field interval from 6.8 to 26.2 mT at room temperature. A comparison with other (001)-oriented epitaxial magnetic films revealed that similar frequency plateaus can occur over frequencies ranging from 0.9 to 12.35 GHz and over magnetic field intervals from 0.5 to 63 mT. These findings establish a route toward microwave devices that are insensitive to fluctuations in the applied magnetic field and motivate further studies of spin-wave dynamics in this regime. Full article

Heavy metals in water are a global concern due to their persistence, toxicity, and bioaccumulation potential, highlighting the need to assess their effects on aquatic organisms. The ecotoxicity of eight potentially toxic metal nitrates (Cd (0.002 mg/L), Co (0.02 mg/L), Cr (0.02 mg/L), Cu (0.001 mg/L), Mn (0.04 mg/L), Ni (0.005 mg/L), Pb (0.002 mg/L), Zn (0.1 mg/L) up to 1000 mg/L for all metals) was assessed on the aquatic macrophyte Lemna minor, in a multilevel study. Growth responses, measured as frond number and average specific growth rate, were used to generate dose–response curves, but also to calculate EC₅₀ (Median Effective Concentration) and E_rC₅₀ (50% Effect Concentration based on growth rate) values. Based on EC₅₀, toxicity followed the order Cd > Co > Ni > Zn > Cu > Cr > Pb > Mn, while E_rC₅₀-based ranking was Cd > Ni > Co > Zn > Cu > Cr > Pb > Mn. Metals were classified as highly toxic (Cd, Ni; Co based on EC₅₀), moderately toxic (Co based on E_rC₅₀, Zn based on EC₅₀), slightly toxic (Cu, Cr; Zn based on E_rC₅₀, Pb based on EC₅₀), or practically non-toxic (Pb based on E_rC₅₀, Mn). Biochemical responses regarding photosynthetic pigments, primary metabolites, and oxidative-stress-related enzymes were investigated, revealing physiological effects for most metals. Species sensitivity distribution-based comparison indicated that L. minor sensitivity varies across metals, ranging from typical to relatively low within the broader species sensitivity distribution. Although the toxicity of potentially toxic metals to L. minor has been extensively investigated, data on ErC50 values for several of the metals investigated in the present study remain limited, highlighting the need for further ecotoxicological research. Full article

High-resolution remote sensing object detection is a fundamental task in Earth observation. However, the storage, transmission, and downstream processing of high-resolution images impose substantial bandwidth, memory, and computational burdens. Compressed sensing (CS) samples and compresses the signals simultaneously, thereby reducing data transmission and storage overhead. Unfortunately, most existing CS-based pipelines require explicit image reconstruction before downstream inference, leading to heavy computational overheads and poor scalability for high-resolution remote sensing images (RSIs). This work focuses on post-acquisition image compression and explores algorithmically, rather than from a physical hardware implementation perspective, whether explicit image reconstruction is an indispensable intermediate step prior to object detection. To this end, we propose HR²SIOD-CL, an end-to-end compressed learning (CL) framework that performs object detection directly on CS measurements of high-resolution RSIs without explicit image reconstruction. HR²SIOD-CL integrates an entropy-driven content-aware adaptive sampling strategy and a measurement-domain detection backbone for multi-scale feature extraction. Although jointly optimized during training, the adaptive sampling and detection modules can be decoupled for flexible deployment. For fair comparison, an extra lightweight reconstruction network equipped with a single-step data-consistency correction is constructed as the baseline. Extensive experiments on the NWPU VHR-10 and DIOR datasets show that across various sampling ratios, HR²SIOD-CL surpasses the reconstruction-based detection method when integrated into two-stage detectors, and achieves comparable or superior detection performance to the reconstruction-based counterparts when integrated into single-stage detectors. Meanwhile, its computational overhead and GPU memory consumption are merely 6.97% and 35.74% of those of the reconstruction-based counterpart, respectively. These results indicate that CS measurements can function as an effective intermediate representation for object detection, and explicit image reconstruction is not a prerequisite when detection is the primary objective. Full article

Repeated non-equidistant unmanned aerial vehicle (UAV) inspections of slope-road cracks require measurements from different distances, poses, and image scales to remain comparable and sufficiently precise for engineering-state decisions. Existing studies rarely integrate cross-view physical conversion, measurement uncertainty, and a project-defined minimum detectable change. We develop an engineering-detectability framework that defines cross-period criteria for crack width and displacement and derives equivalent widths for ideal, representative non-standard, and arbitrary viewpoints. First-order error propagation and reliability allocation convert the minimum detectable change into accuracy requirements for range, field of view, and normalized image coordinates. Crack-boundary coordinates and localization uncertainties provide a common interface for interchangeable detection and photogrammetric modules. Validation combines a controlled fixed-camera sequence with a close-range field-camera multiview test of seven physical openings under local coplanarity. All six determinate stages in the controlled sequence agreed with the digital image correlation (DIC) comparison, while one borderline stage required review. Across the seven openings, the four-view means gave a mean absolute error (MAE) of 0.196 mm and a root mean square error (RMSE) of 0.270 mm, with cross-view coefficients of variation (CVs) of 0.33–4.93%. An illustrative error budget demonstrates reverse screening of system configurations from project thresholds. The framework therefore connects viewpoint-equivalent measurements, uncertainty constraints, and engineering-state decisions in an auditable chain. Full article

Quantitative EEG features such as frontal alpha asymmetry, spectral ratios and signal-complexity measures are often presented as interpretable biomarkers of emotion. Such claims require the markers to generalize across individuals, yet common evaluation protocols allow overlapping epochs and recordings from the same participants to appear in both training and test sets. We re-evaluated qEEG-based valence and arousal recognition on DEAP and DREAMER under trial-grouped, participant-independent, within-participant and cross-dataset protocols. Epoch-pooled evaluation on DEAP gave ROC-AUC values of 0.689 for valence and 0.711 for arousal, whereas participant-independent evaluation of the same features and model returned 0.493 and 0.447. Grouping epochs by trial accounted for about 0.06 of that difference and separating participants for a further 0.13 to 0.17. The same features identified participants with accuracy of 0.998 on DEAP and 0.891 on DREAMER, and a predictor that used no EEG, assigning each trial its participant’s training-set positive rate, accounted for 42 to 84 percent of the above-chance discrimination of the epoch-pooled model. Emotion-related effects were reproducible within participants on DEAP but close to zero on DREAMER, and their direction reversed for about 40 percent of features across participants. In a matched participant-level comparison using a single fixed estimator in both arms, training on a participant’s own data improved DEAP valence by 0.092 AUC (95% CI 0.029 to 0.157, Holm-adjusted $p=0.042$) and gave no reliable benefit for DEAP arousal or for either DREAMER target. Across the channels shared by the two datasets, per-feature arousal effect sizes correlated moderately, although no individual feature reached false-discovery-rate significance in both datasets. Pooled qEEG emotion-recognition scores can therefore reflect participant-specific recording structure rather than transferable affective information. Population-level claims require participant-independent evaluation, while personalization should be considered only where stable within-person effects are demonstrated. Full article

Quantifying groundwater storage in karst aquifers remains challenging because of their heterogeneous structure and the scarcity of direct observations. This study proposes a pragmatic approach for characterizing storage and water availability in karst systems at the regional scale using long-term hydrographs from 16 Swiss karst springs and rivers. We distinguish between seasonal storage, associated with recharge events, and low-water storage, which sustains discharge during periods without significant recharge. Seasonal storage was estimated at approximately 30–70 mm for most investigated systems, while total storage reached up to about 140 to 180 mm at some sites, based on recharge–discharge modelling. Low-water storage was estimated to be on the order of 200 mm across most investigated systems, despite differences in hydrogeological settings. Analysis of low-water recession curves showed that most natural springs analyzed in this study followed a similar master recession curve, with low-water conditions defined as beginning at a specific transition discharge of 11.25 L s⁻¹ km⁻². This similarity provides the basis for a regional drought index that estimates the volume of remaining groundwater storage and forecasts discharge several weeks in advance. The results also support a conceptual model in which epikarstic, epiphreatic, and deeper storage compartments attenuate short-term discharge variability while sustaining low-water discharge over prolonged periods. Comparison with non-karst catchments shows that karst hydrogeological systems dampen peak flows but sustain baseflow through distinct storage reservoirs. This approach delivers quantitative indicators to assess drought, manage groundwater, and foresee water shortages in karst regions. Future work will test its validity outside the Swiss dataset. Despite discussed uncertainties in discharge measurements and catchment delineation, results demonstrate that dedicated hydrograph-based analyses can yield robust and transferable insights into karst groundwater storage at regional scales. Full article

Shoreline determination is fundamental to coastal research, spatial planning, and legal boundary delineation but remains challenging in low-relief coastal areas where small sea-level variations can produce substantial horizontal shoreline displacements. This study compares shoreline determination methods based on tide gauge (TG) observations, LiDAR data, Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical satellite imagery using the low-relief coast of Pärnu Bay, Estonia, as a case study. The comparison was based on shorelines derived from Sentinel-1 and Sentinel-2 imagery acquired on selected common acquisition dates within the 2015–2025 study period, rather than on a temporally continuous annual dataset, and compared with temporally matched LiDAR-derived shorelines extracted from a Digital Terrain Model (DTM) generated from a 2021 LiDAR survey. The LiDAR-derived shorelines were extracted using the mean sea level (MSL) observed at the Pärnu and Häädemeeste TGs at the satellite overpass time, while the satellite-derived shorelines were additionally validated against RTK GNSS measurements. The results demonstrate that the evaluated methods produce substantially different shoreline positions. Sentinel-2-derived shorelines generally corresponded more closely to the temporally matched LiDAR-derived shorelines than Sentinel-1-derived shorelines and most accurately represented the instantaneous land–water boundary during field validation. These findings demonstrate that different shoreline determination methods represent different shoreline definitions. Consequently, shoreline datasets should be interpreted according to their intended purpose rather than treated as directly interchangeable. Full article

Digital transformation can expand manufacturing firms’ capacity for interorganizational collaboration, but digitalization does not automatically translate into coupled open innovation. Drawing on dynamic capability theory and social comparison theory, this study examines the association between digital transformation and coupled open innovation, evaluates absorptive, adaptive, and innovative capabilities as parallel capability-related pathways, and investigates the external executive pay gap as a boundary condition. The analysis uses 12,791 firm-year observations from 2199 Chinese A-share listed manufacturing firms during 2011–2022. Digital transformation is measured from annual-report disclosures, while coupled open innovation is operationalized as joint patent applications with external co-applicants. Firm and year fixed-effects regressions with firm-clustered standard errors are complemented by Poisson pseudo-maximum-likelihood and negative-binomial count models and firm-cluster bootstrap mediation analyses. Digital transformation is positively associated with coupled open innovation across the linear and count specifications. In the simultaneous parallel-mediator model, the indirect associations through the absorptive-, adaptive-, and innovative-capability proxies are statistically distinguishable from zero, although the innovative-capability association is substantively small. The linear interaction specification indicates a stronger Digital–COI association at higher observed levels of the external executive pay gap, while the exploratory conditional-indirect analysis suggests selective moderation through the innovative-capability pathway rather than a uniform pattern across all three capability pathways. The results clarify how digital resources, organizational capabilities, and executive compensation context relate to formal collaborative innovation and the organizational and economic sustainability of manufacturing firms. Full article

Fresnel high-concentration photovoltaic/thermal (HCPV/T) systems operating in sandy environments are susceptible to natural lens soiling, which attenuates the effective concentrated solar input and alters electrical and thermal performance. Natural-soiling comparison tests were conducted over 0–28 d, and an SD-CNN-BiLSTM-Attention model was developed to forecast cell-center temperature and electrical power 5, 10, and 20 min ahead. At a surface soiling density of 10.760 g·m⁻², current and electrical power decreased by 38.37% and 39.28%, respectively, relative to the concurrently operated clean-reference unit; cell-center temperature and water-tank temperature rise decreased by 7.74% and 15.13%. Thermal power also showed an overall downward trend, although the magnitude was affected by relatively large measurement uncertainty. Under grouped cross-validation, temperature RMSEs were 0.473, 0.515, and 0.555 °C at 5, 10, and 20 min, corresponding to reductions of 8.34%, 21.68%, and 44.07% relative to Persistence. Electrical-power RMSEs were 0.661, 0.618, and 0.640 W, with an 18.24% reduction relative to Persistence at 20 min. Ablation analysis showed a limited contribution from surface soiling density at 5 and 10 min but a clearer contribution at 20 min. These results support electrical and thermal performance assessment and short-term operational forecasting of Fresnel HCPV/T systems in sandy environments. Full article

Background: Anthropometric body-composition assessment in youth soccer commonly relies on equations developed in different source populations and based on distinct body-composition models, potentially altering nutritional and sport-related interpretation. This study compared body-fat estimates from equations intended to report the same outcome, body fat percentage, but based on different operational models, and quantified muscle-mass outputs from anthropometric approaches targeting total-body skeletal, whole-body, and tissue-level muscle compartments in a cohort of Chilean male U-15 and U-16 players. Methods: This secondary cross-sectional method-comparison study analyzed anonymized anthropometric records collected in 2018 from 50 male players. Slaughter, Faulkner, Carter, Deurenberg, and Sloan–Siri estimates of body fat were compared, together with Poortmans, Lee, Doupe, and Kerr muscle-mass approaches. Absolute agreement among adiposity equations was evaluated using a two-way random-effects, absolute-agreement, single-measure ICC [ICC(A,1)] and Bland–Altman analyses. Muscle-mass approaches were compared with repeated-measures analysis; pairwise difference-versus-mean summaries across different muscle constructs were interpreted descriptively rather than as formal agreement tests. Sensitivity analyses excluded Deurenberg and examined a maturation-related Slaughter scenario. Results: Deurenberg yielded the highest body-fat estimate (18.97 ± 3.07%), followed by Slaughter (13.32 ± 3.35%), Faulkner (10.84 ± 1.40%), Sloan-Siri (8.01 ± 2.80%), and Carter (7.91 ± 1.49%). Global differences were large (χ²(4) = 182.96; p < 0.001; Kendall’s W = 0.915), and individual absolute agreement was low [ICC(A,1) = 0.157; bootstrap 95% CI 0.102–0.212]. Excluding Deurenberg did not remove the between-method differences (χ²(3) = 124.44; p < 0.001; W = 0.830). For muscle mass, mean estimates ranged from 25.11 ± 3.07 kg with Poortmans to 31.26 ± 4.94 kg with Doupe, with a significant method effect after Greenhouse–Geisser correction (p < 0.001). Conclusions: The adiposity equations yielded substantially different numerical estimates of the same reported outcome, body fat percentage, and showed low individual-level absolute agreement. Muscle-mass approaches also produced large numerical differences, partly expected because they target different compartments. Outputs from different equations or constructs should not be treated as numerically interchangeable. Because no criterion reference method was included, this study quantifies method dependence rather than validity and cannot identify the most accurate equation. Full article