Search Results (5,904)

The rapid evolution of data-driven enterprises demands scalable and intelligent systems capable of managing substantial volumes of heterogeneous data in real time. However, traditional systems lack a holistic approach to managing distributed data engineering, real-time analytics, and intelligent decision-making. To address these limitations, this paper proposes a Cognitive Lakehouse Framework that integrates distributed data processing, transformer-based deep learning, real-time analytics, and autonomous decision intelligence. Data are gathered from high-velocity, heterogeneous streams using Apache Kafka. Subsequently, data are processed using the hybrid batch/streaming paradigm, implemented via Apache Spark and Apache Flink, providing low latency and scalability. For data storage, a unified lakehouse layer is created using Delta Lake and Apache Iceberg, both of which support ACID transactions and schema evolution. In addition, transformer-based Deep Learning (DL) algorithms are utilized to capture temporal dependencies for predictive analytics, anomaly detection, and adaptive learning. Model lifecycle management is handled by MLflow, while ClickHouse and Apache Druid are used for real-time analytics. The architecture uses microservices and an event-driven approach on Kubernetes, and the workflow is automated with Apache Airflow. The performance assessment is conducted using TPC-H, TPC-DS, and real-time stream data to measure latency, throughput, and accuracy. Data quality, security, and compliance are provided by governance layers consisting of Apache Ranger and Apache Atlas. Experimental results show that significant gains can be made in terms of performance, with an accuracy of 98.5%, a query response time of 120 ms, a peak throughput of 85,000 records/s, and an end-to-end latency of 95 ms. Full article

Brachymystax lenok tsinlingensis is an endangered salmonid endemic to China. Traditional trapping methods frequently fail to detect this rare fish in low-density mountain streams, hampering evidence-based conservation. Here, we employed environmental DNA quantitative PCR (eDNA-qPCR) with species-specific primers to assess the spatial biomass distribution of this species in the Zhouzhi Heihe River. Concurrently, we surveyed plankton, benthic macroinvertebrates, and physicochemical water parameters. eDNA detected the target species at 12 of 14 sites, with reliable quantification achieved at 9 sites, suggesting that the method may be more effective than conventional trapping for detecting this species under the studied low-density conditions. eDNA-derived relative biomass exhibited pronounced spatial heterogeneity, ranging from 6.0 × 10⁻⁴ to 1.5 × 10⁻² g/cm³. Water depth showed a significant positive association with biomass (r = 0.5347), whereas phytoplankton Shannon diversity (a measure of species richness and evenness) was significantly negatively correlated (r = −0.5447). Flow velocity displayed a negative trend that did not reach statistical significance (r = −0.5009). Plankton and benthic communities indicated overall ecological conditions but did not directly explain the observed spatial variation in fish biomass. These findings indicate that the spatial pattern of B. lenok tsinlingensis is primarily shaped by local physical habitat structure, with deeper, hydraulically more complex channel units serving as key microhabitats. eDNA-qPCR thus represents an effective, low-disturbance monitoring tool for this endangered cold-water fish and provides a scientific basis for targeted habitat protection and restoration. Full article

This study investigates the use of mussel shells (MSs), a biogenic by-product of the food industry, as a partial replacement for ground granulated blast furnace slag (GBFS) in alkali-activated mortars. Given their high CaCO₃ content, MSs represent a sustainable secondary raw material that reduces both waste disposal burden and reliance on natural resources, while offering a low-carbon alternative to conventional cement-based binders. Alkali-activated mussel shell/slag mortars (AAMSs) were produced with MS replacement ratios of 0%, 5%, 10%, 15%, and 20% by mass of GBFS. Sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) were used as alkaline activators. Fresh specimens were cured at 60 °C for 48 h. The experimental program included workability, compressive and flexural strength, water absorption, porosity, density, capillarity, ultrasonic pulse velocity (UPV), and freeze–thaw (F-T) resistance tests. Increasing MS content slightly reduced flowability and mechanical strength, while increasing water absorption, porosity, and capillarity. The M0 series achieved the highest 28-day compressive strength (54.06 MPa), while M15 exhibited the highest flexural strength (5.23 MPa). Following F-T cycling, the 5% and 10% MS series demonstrated the best compressive strength (30 MPa). The 10% MS exhibits a relatively balanced overall performance, providing the best balance between mechanical performance, F-T resistance, and microstructural stability, as confirmed by scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDS) analyses showing elevated Ca/Si ratios and the formation of Ca-rich crystalline phases. Full article

Temperament has been associated with reproductive success in beef cattle, with excitable animals often exhibiting reduced fertility. This study evaluated whether acclimating heifers to human handling during an ovulation synchronization protocol improves temperament and pregnancy rates to timed artificial insemination (TAI). A total of 622 Bos taurus yearling beef heifers across five locations and two breeding seasons (eight herd-year observations) were stratified according to reproductive maturity and temperament and were assigned to either acclimation (TRT; n = 307) or control (CTRL; n = 315). Acclimated heifers were moved through handling facilities without restraint prior to each protocol event (days 0, 7, and 10). Temperament was assessed using chute score (CS) and exit velocity (EV), and plasma cortisol was measured in a subset of animals. Acclimated heifers had lower CS on days 7 and 10 (p = 0.011 and p = 0.010, respectively) and greater pregnancy rates to TAI compared with control heifers (54.5% vs. 45.2%; p = 0.018). Exit velocity and cortisol concentrations did not differ between treatments (p ≥ 0.13). These results indicate that acclimation during handling events can improve behavioral responses and pregnancy rates to TAI with modest additional handling time (a mean of 17 s per heifer; no more than 18 min per location/day), providing a practical and scalable strategy for beef producers. Full article

Canned motor pumps are widely utilized due to their distinct advantage of a completely leakage-free structure. Among them, an integrated impeller–rotor configuration is employed in the axial-flux canned motor pump, resulting in a shorter axial length and higher power density. This novel configuration allows for easy integration into space-constrained systems, such as electric vehicles, aerospace applications, and liquid-cooled servers. However, research on the internal flow characteristics of these pumps remains scarce. To address this gap, the present study investigates the internal flow across various flow rates. Numerical simulations are validated against experimental data. The average error remains below 2%. The pump achieves a peak efficiency of 68.6% at the design condition, but experiences efficiency drops of 15.0 and 25.2 percentage points under 0.5Q_d and 1.5Q_d, respectively. Results demonstrate that flow rates significantly govern internal characteristics. These include pressure, velocity, and entropy distributions, along with vortex structures and pressure fluctuations. Notably, operating at off-design conditions can intensify the internal pressure fluctuations by up to a factor of 29.4. Entropy analysis identifies major losses on blade suction sides and diffusers. These findings provide crucial hydrodynamic guidelines for low-noise thermal management systems in electric vehicles and ensuring high-reliability cooling loops in aerospace and liquid-cooled servers. Full article

Icing phenomena on wind turbine blades and components are a major problem, causing downtimes that increase maintenance costs, reducing the blade’s lifespan, or in severe cases, even leading to component damage. A nanofiber-based bi-layer liquid-infused surface (BLIS) coating was prepared and characterized, combining good adhesion to wind turbine blades with low ice adhesion. The BLIS coating was produced by a new method combining electrospinning and a heat treatment step, containing a poly ethyl-2-cyanoacrylate (PECA)-based adhesive layer, a slippery layer of poly vinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) copolymer, and an infiltrated perfluoropolyether lubricant. Thermogravimetric analysis (TGA) was used to ensure the thermal stability of the polymers in the nanofiber coating layers and to optimize the heat treatment process of the layers. Microstructural changes were studied by scanning electron microscopy (SEM) and surface roughness measurements. Contact angle measurements and sliding velocity tests on wind turbine blade segments at icing conditions of 0 °C and +5 °C indicate that the water sliding properties of the BLIS coating were improved compared to uncoated blades. In addition, coated blade segments showed a 50% lower ice adhesion strength than uncoated blades. Full article

Dense granular materials under low confining stress and low shear velocity—conditions relevant to low-pressure powder handling, near-surface transport, and the upper layers of stored bulk solids—remain insufficiently characterized at the microstructural level. We perform three-dimensional discrete element method (DEM) simulations of annular shear of monodisperse glass spheres at σ = 1 kPa and v = 0.01 m/s, corresponding to an inertial number I ≈ 1.06 × 10⁻³ at the quasi-static limit of the dense flow regime. The steady-state friction coefficient stabilizes at μ_ss ≈ 0.78, consistent with the quasi-static limit of the μ(I) framework. The solid volume fraction decreases monotonically from φ ≈ 0.50 at the base to φ ≈ 0.35 near the top, while the tangential velocity decays exponentially with depth (decay length δ_s ≈ 10 mm). Particle trajectory tracking reveals a sharp kinematic transition near z ≈ 5–6 mm separating a quasi-rigid basal layer (z ≲ 5 mm) from an upper shear-active zone (z ≳ 6 mm). The contact force distribution follows an exponential decay P($f$/$⟨f⟩$) ∝ exp(−β·$f$/$⟨f⟩$) with β ≈ 0.45, with strong force chains selectively concentrated in the upper zone. Together, these four microstructural descriptors co-locate within a single transition band, providing quantitative benchmarks for material characterization and constitutive modelling at the lower boundary of dense flow. Full article

Climate-induced natural hazards can result in disruptions and failures of railway routes which are associated with high economic costs. Hence, the mechanisms of climate impacts posing a threat to rail transport must be identified, analysed and localised in railway networks. This study aims at assessing heavy rainfall hazards on the railway network of the federal state Nordrhein-Westfalen (NRW) in Germany and presents a GIS-based flooding indicator. A rule-based classification and aggregation approach with a hazard matrix was developed using potential flooding depths and flow velocities, resulting in five hazard classes. The approach was applied to the railway network in NRW for two heavy rainfall scenarios (N₁₀₀, N_ext). The results show that the clear majority of route kilometres are classified as at least moderate hazard in both precipitation scenarios considered (N_ext 81%, N₁₀₀ 72%). On railway routes in low mountain range regions, more sections are assigned higher hazard classes than in flat landscapes. The plausibility of the indicator was explored through scenario, structural and conceptual parameter analyses, which support robustness of the results. The maps can serve as a tool for making qualitative statements on the potential impact on the German railway network and localising these impacts spatially. Full article

Background: In youth football, sprint performance depends on the capacity to produce and orient force horizontally during acceleration. Resisted sprinting may preferentially target the force end of the sprint force–velocity profile, whereas free sprinting may favour velocity-oriented adaptations. Purpose: To compare the effects of resisted versus non-resisted sprint training on sprint performance and sprint force–velocity variables in youth footballers, while monitoring countermovement jump (CMJ) as a secondary outcome. Methods: This parallel-group randomised controlled trial included 44 players from two age categories (U14, n = 21; Youth, n = 23). Within each category, players were randomly allocated to resisted sprint training (RST; U14 n = 11, Youth n = 12) or non-resisted sprint training (NRST; U14 n = 10, Youth n = 11). Both groups completed two supervised sessions per week for six weeks. Outcomes were CMJ and sprint-derived variables including maximal theoretical horizontal force (F0), maximal theoretical velocity (V0), maximal power (Pmax), measured maximal sprint velocity (Vmax), peak ratio of horizontal force (RFpeak), decrease in RF with increasing velocity (DRF), and force–velocity slope (FV). Results: CMJ remained essentially unchanged in both age categories. Sprint performance improved over time, with the pattern of adaptation generally favouring RST for force-oriented sprint mechanical variables (F0, Pmax and RFpeak), whereas improvements in Vmax were observed in both groups. In the Youth category, the FV slope differed between groups post-test (p = 0.002). Overall, resisted sprint training tended to produce larger improvements in acceleration-oriented mechanical qualities, while non-resisted sprint training was associated with more velocity-oriented adaptations. Conclusions: Low-volume resisted sprint training using a sled load of ~20% body mass was associated with more favourable adaptations in force-oriented sprint mechanical variables, whereas non-resisted sprint training tended to favour velocity-oriented characteristics. CMJ performance remained unchanged in both groups. These findings should be interpreted cautiously given the small age-stratified subgroup sizes and the single-club nature of the study. Trial registration: This study was retrospectively registered at ClinicalTrials.gov (NCT07418892). Full article

Accurate tire–soil traction prediction is critical for agricultural and off-road vehicle design, yet rigorous comparisons of advanced discretization strategies under controlled-slip conditions remain limited. This study compares MM-ALE and Hybrid FE-SPH (H-SPH) discretization in LS-DYNA for SRTT (225/60R16) traction prediction on sandy loam (0.4% gravimetric moisture content) across 5–40% slip ratios. A CT-scan-based tire model using Yeoh visco-hyperelastic rubber (Material_2) was validated against experimental data, achieving CORA scores of 0.989 (radial deflection), 0.999 (loaded radius), 0.947 (footprint area), and 0.985 (contact pressure), outperforming the Mooney–Rivlin formulation (Material_1; CORA = 0.618). Soil moisture content (0.4%, 8%, 14%) was included as a design variable through a Latin Hypercube Sampling framework. Both methods reproduced a monotonic increase in traction; inter-method differences ranged from 29 to 36% at low slip, converging to a 7.8% coefficient of variation at 40% slip. A 27-run full-factorial DOE-I identified normal load as the dominant traction driver (90.1%), followed by velocity (8.6%) and inflation pressure (1.3%). An LHS-based DOE-II revealed moisture content as the primary driver of traction coefficient (67.5%), via a non-monotonic cohesion mechanism peaking at 8% gravimetric moisture. H-SPH reduced runtime by 38% versus MM-ALE. The validated framework provides reusable traction prediction protocols for variable conditions. Full article

Background/Objectives: Spontaneous intracranial hypotension (SIH) is caused by spinal cerebrospinal fluid (CSF) leakage and is typically diagnosed by clinical presentation and characteristic MRI signs; however, objective tools for monitoring physiological changes and treatment response remain limited. Cine phase-contrast MRI (PC-MRI) enables noninvasive quantification of aqueductal CSF dynamics, yet reliable analysis is challenging since the cerebral aqueduct is extremely small and susceptible to low contrast, partial volume effects, and ROI-dependent measurement variability—particularly in SIH where CSF pulsatility is often reduced. Methods: We propose an end-to-end automated framework that integrates (1) a cascade localization–segmentation strategy, consisting of Tiny YOLOv4 detection followed by MultiResUNet segmentation on a YOLOv4-derived cropped ROI; (2) physiology-informed pulsatility-based segmentation (PUBS) to refine anatomical masks into functional flow ROIs; and (3) one-dimensional convolutional neural networks (1D-CNNs) to extract exploratory waveform morphology features from 32-phase cardiac-cycle velocity waveforms. The study includes 39 participants, yielding 59 cine PC-MRI examinations: 11 controls, 28 Pre-treatment SIH scans and 20 Post-treatment Recovery scans. Results: The cascade model significantly improves segmentation robustness compared with a full-image baseline, achieving higher Dice scores and markedly lower boundary errors across cohorts (e.g., Pre-treatment SIH HD95: 1.66 ± 0.74 px vs. 15.37 ± 44.98 px). PUBS refinement reduces quantification deviation from expert manual references in SIH (mean relative error: 7.4% to 5.6%) and improves diagnostic performance for multiple hemodynamic parameters (e.g., downward mean flow AUC: 0.747 to 0.792). For waveform morphology analysis, the end-to-end 1D-CNN classifier was evaluated using repeated-seed participant-level grouped LOOCV. The repeated-seed ensemble prediction showed modest out-of-sample discrimination between Normal controls and Pre-treatment SIH scans, with an AUC of 0.646, a bootstrap 95% confidence interval of 0.455–0.826, and a permutation-test p-value of 0.072. Separately, exploratory analysis of the final baseline-trained 1D-CNN latent space showed marked, apparent Normal-versus-SIH separability and an intermediate recovery distribution in PCA space, suggesting that aqueductal waveform morphology may encode SIH-related physiological information. Conclusions: These findings suggest that SIH-related information may be reflected not only in flow magnitude but also in aqueductal CSF waveform morphology. However, the modest and statistically non-significant out-of-sample performance of the end-to-end 1D-CNN classifier indicates that morphology-based AI features should currently be regarded as exploratory biomarker candidates rather than validated stand-alone diagnostic tools. Larger independent cohorts are required to confirm their reproducibility, physiological meaning, and clinical utility. Full article

In this study, three-dimensional P- and S-wave velocity structures and P- and S-wave velocity ratio variations in the crust and upper mantle beneath the Marmara Region and the Sea of Marmara were modeled using the Poisson tomography method in the field of Seismology. Within this scope, P- and S-wave arrival times from a total of 23,672 earthquakes that occurred in the region between 2011 and 2023 were evaluated, and an inversion procedure based on body-wave arrival times was applied. The obtained results indicate that the northern branch of the North Anatolian Fault Zone is the most active segment among its three main branches. In addition, a low-velocity zone characterized by seismic gap features extending from the southern parts of Marmara toward Istanbul was identified. Within these seismic gap zones, P- and S-wave velocities decrease sharply across regions exhibiting strong velocity gradients. It was determined that this low-velocity structure cuts across the North Anatolian Fault, which branches into three segments within the Sea of Marmara, and continues at depths of approximately 15–25 km. Earthquakes were observed to concentrate particularly in areas with high-velocity ratio variations and within transition zones from low to high values. Due to the complex tectonic and stratigraphic structure of the Marmara Region, these low-velocity seismic gap zones within the crust may be associated with segments capable of generating large earthquakes in the future. Therefore, a detailed investigation of the crustal structure of the region provides important insights for understanding regional earthquake hazards. Full article

Horizontal nystagmus is still commonly interpreted at the bedside through a pragmatic peripheral-versus-central dichotomy. Although this heuristic is often clinically useful, it may be misleading because distributed brainstem–cerebellar disorders can generate peripheral-appearing phenotypes. This paper presents a narrative clinical–conceptual review proposing that a substantial subset of horizontal nystagmus patterns may be understood more coherently as expressions of dysfunction within a coupled vestibulo-ocular integrative network rather than as direct signatures of a single lesion site. Within this framework, two core dynamical domains are separated conceptually: a vestibular nuclei (VN)-centered velocity-storage process and an NPH-centered gaze-holding integrator. These processes are proposed to operate under cerebellar regulatory influence, with the nodulus–uvula (NU) acting as a plausible regulator of storage gain, temporal persistence, adaptation stability, and oscillatory behavior. Clinically, the velocity-storage domain is expressed through low-frequency vestibulo-ocular reflex behavior and optokinetic after-nystagmus-related dynamics, whereas the gaze-holding domain is expressed through eccentric gaze stability, gaze-evoked nystagmus, and post-saccadic drift. This framework carries a clinically relevant implication: horizontal nystagmus phenotypes may be interpreted more effectively by asking which functional process is predominantly abnormal—gaze holding, storage-related vestibular persistence, or cerebellar regulatory stability—rather than by relying solely on a binary peripheral–central label. On this basis, we outline a clinician-facing workflow linking gaze dependence, periodicity, direction reversals, head-shaking behavior, and Alexander-law mismatch to operational bedside criteria and candidate quantitative readouts. The proposed model is intended as a clinical–conceptual framework rather than a deterministic localization tool. Its main value lies in organizing discordant vestibular findings, strengthening the mechanistic interpretation of bedside and instrumented observations, and identifying testable directions for future validation studies in acute dizziness and ocular motor disorders. Full article

Industrial waste heat recovery is an important approach for improving energy utilization efficiency and reducing environmental impacts. Thermoelectric devices can directly convert waste heat into electricity, but their practical application is limited by relatively low output power. Active water cooling can enhance the power generation performance of thermoelectric devices, but the pumping power may reduce the net output power. In this study, a water-cooling thermoelectric device is investigated under constant heat input conditions using three-dimensional numerical simulations and a semi-analytical prediction model. The effects of cooling water inlet temperature and flow rate on the thermal response, electrical output, heat transfer behavior, and net output power are systematically analyzed. The results show that increasing the cooling water flow rate increases the gross electrical power but also increases pumping power, resulting in an optimal flow rate of approximately 3 m/s to maximize the net output power. At inlet temperatures of 24 °C, 28 °C, and 32 °C, the maximum net output powers are 51.46 W, 49.89 W, and 48.68 W, respectively. A prediction model for cooling water input conditions is further developed based on energy balance and convective heat transfer correlations, and the predicted velocities agree with the numerical results with relative errors below 2%. Full article

This study presents a transient computational fluid dynamics (CFD) analysis of dielectric flow behaviour and debris transport in micro-EDM milling, considering the effects of dielectric properties, inter-electrode gap (IEG) size (20–30 µm), and tool rotational speed (400–850 rpm). Four dielectric media, nitrogen gas, deionized water, HEDMA111 EDM oil, and sunflower seed oil, were investigated using a two-dimensional FEM-based model coupled with particle tracking simulations to evaluate debris mobility within the machining region. The results demonstrate that dielectric properties, particularly viscosity, strongly influence hydrodynamic behaviour and particle transport within the IEG. Under the adopted equal mass flow rate condition, nitrogen gas exhibited the highest flow velocities and the fastest debris evacuation due to the combined effects of its low viscosity and the resulting higher inlet velocity. Deionized water and HEDMA111 oil exhibit comparable intermediate behaviour, indicating that moderate viscosity variations within liquid dielectrics do not significantly alter the overall flow regime. In contrast, sunflower seed oil generates the most damped flow conditions, with reduced velocities and prolonged particle residence due to increased viscous resistance. Variations in IEG size produce only minor changes in evacuation efficiency compared with the dominant influence of dielectric properties, while tool rotational speed primarily affects velocity magnitude without altering qualitative transport behaviour. Full article