Search Results (51)

In slab continuous casting, the internal hydrodynamics of the submerged entry nozzle (SEN) play a determining role in mold flow stability and product quality, particularly when external electromagnetic flow-control technologies are not employed. This study analyzes a novel bifurcated SEN design intended to promote stable, highly symmetric outlet jets under asymmetric inlet flow conditions produced by typical flow-control devices. The proposed configuration combines three geometric modifications: a square-section bore, a flow-divider bottom wall derived from a rotated mountain-type geometry, and two bell-shaped protrusions that act as flow modulators positioned immediately above the outlet ports. The hydrodynamic behavior inside the nozzle was investigated using complementary experimental and numerical approaches. Physical modeling was conducted in a scaled water model using particle image velocimetry (PIV) to characterize time-averaged velocity fields and flow fluctuations. In parallel, three-dimensional large-eddy simulations (LESs) were performed to resolve transient flow structures and quantify jet characteristics at the nozzle exits. Both approaches show consistent results. The combined action of the flow modulators and the flow-divider bottom wall robustly induces the formation of two nearly identical counter-rotating vortices in the lower region of the SEN. This flow structure suppresses stagnation and recirculation zones near the outlet ports, mitigates inlet-induced asymmetries, and enhances flow evacuation efficiency. Quantitative analysis of the outlet jets indicates a significant reduction in angular dispersion and a flow-rate imbalance below 0.2%, markedly lower than that observed in conventional SEN configurations. The results demonstrate that appropriate internal geometric design can effectively stabilize SEN hydrodynamics without active control systems, offering a feasible and scalable strategy for improving mold flow stability in industrial continuous casting operations. Full article

Battery-powered edge systems must operate under tight energy budgets while facing growing computational demand from rapidly evolving edge workloads. Field-programmable gate arrays (FPGAs) offer middle ground when optimized for energy, especially flash-based FPGAs due to inherent low-power characteristics. Microchip flash-based SoC FPGAs further expose ultra-low-power (LP) modes including fabric Flash*Freeze (F*F), processor sleep and selectable standby clocks. Combining these modes with HW/SW partitioning and clock-frequency scaling can reduce energy for low-duty-cycle workloads; however, selecting an energy-efficient operating point in this multidimensional design space is non-trivial. This work explores the design space by measuring and analyzing LP modes across three architectural approaches (SW, co-design, and HW) under frequency scaling on a Microchip Smartfusion2 platform, using a low-duty-cycle heart-rate monitoring workload. Measurements indicate that, for low-duty-cycle workloads, total energy is dominated by the idle phase and is minimized by combining fabric-F*F with processor sleep. The results further show that main-clock downscaling reduces active-phase current but has limited impact on idle consumption once F*F and sleep are applied, while standby-clock selection trades idle current against LP entry/exit latency. Event-rate scaling further shows that the energy-optimal operating point can shift with duty cycle. We provide measurement-based guidelines for duty-cycle-aware energy-efficient operating point selection in similar flash-based SoC platforms. Full article

This study investigates the machinability of Continuous Fiber-Reinforced Thermoplastic Composite (CFRTP) produced via Material Extrusion (MEX) additive manufacturing, focusing on drilling as a critical post-processing step in hybrid manufacturing. CFRTP components, fabricated from 3K carbon fibers and a PLA matrix, were subjected to systematic drilling tests under varying cutting speeds (50–110 m/min) and feed rates (0.06–0.24 mm/rev). Thrust force (Fz) and torque (Mz) were recorded using a high-precision dynamometer to evaluate the influence of cutting parameters on mechanical loads and damage mechanisms. Results indicate that increasing the feed rate significantly increases Fz and Mz, promoting fiber pull-out, delamination, and edge deformation, particularly at hole entry and exit regions. Conversely, higher cutting speeds reduce Fz and Mz due to thermal softening of the PLA matrix, enabling more controlled fiber–matrix interaction. Microscopic analyses revealed that damage severity correlates strongly with mechanical load levels. While high feed rates caused pronounced surface irregularities and matrix smearing, low feed rates combined with high cutting speeds yielded smoother hole morphology and preserved fiber–matrix integrity. The study concludes that optimal drilling conditions for CFRTP materials involve low feed rates and high cutting speeds, minimizing mechanical loads and suppressing damage formation. These findings provide a scientific basis for precision finishing strategies in hybrid manufacturing, enhancing dimensional accuracy and structural reliability of CFRTP components for advanced engineering applications. Full article

New luminescent coatings are increasingly being used in highway tunnels to address inadequate internal lighting conditions. However, there is currently a lack of scientifically reliable methods to evaluate the effectiveness of these paints in improving lighting conditions, reducing driver psychological stress, and quantifying these impacts. This study utilized new luminescent coatings to improve tunnel lighting conditions, conducting real-vehicle tests to measure drivers’ physiological parameters including pupil diameter and heart rate. It examined the mechanisms through which variations in lighting conditions within highway tunnels affect the psychological workload of drivers. A hierarchical analysis–fuzzy comprehensive evaluation (AHP-FCE) method was adopted to develop a quantitative evaluation system for highway tunnel driving psychological load. The results indicate that variations in tunnel lighting substantially influence the psychological workload experienced by drivers during operation. The new luminescent coatings effectively enhanced tunnel lighting conditions, increasing average brightness and illuminance by 37.71% and 40.95%, respectively. Following lighting improvements, pupil diameter variation rates during tunnel entry and exit phases decreased by 35.37% and 10.06%, respectively, while heart rate variation rates decreased by 12.50% and 4.36%. Quantitative analysis of driver mental load revealed a comprehensive score of 0.6230 before lighting enhancement, which decreased to 0.2702 after improvements. This research introduces an innovative integrative framework that combines physiological parameter monitoring with the AHP-FCE method to quantitatively assess the psychological workload experienced by drivers in tunnel environments. This approach addresses a significant gap in the literature concerning the quantitative relationship between tunnel lighting optimization and drivers’ psychological workload responses. Full article

Adeno-associated viruses (AAVs) are a leading vector for gene therapy, yet their clinical utility is limited by the lack of robust quality control methods to distinguish between empty (AAV_empty), partially loaded (AAV_partial), and fully DNA loaded (AAV_full) capsids. Current analytical techniques provide partial insights but remain limited in sensitivity, throughput, or resolution. Here we present a multimodal plasmonic nanopore sensor that integrates optical trapping with electrical resistive-pulse sensing to characterize AAV9 capsids at the single-particle level in tens of μL sample volumes and fM range concentrations. As a model system, we employed AAV9 capsids not loaded with DNA, capsids loaded with a self-complementary 4.7 kbp DNA (AAV_scDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAV_ssDNA). Ground-truth validation was performed with analytical ultracentrifugation (AUC). Nanosensor data were acquired concurrently for optical step changes (occurring at AAV trapping and un-trapping) both in transmittance and reflectance geometries, and electrical nanopore resistive pulse signatures, making for a total of five data dimensions. The acquired data was then filtered and clustered by Gaussian mixture models (GMMs), accompanied by spectral clustering stability analysis, to successfully separate between AAV species based on their DNA load status (AAV_empty, AAV_partial, AAV_full) and DNA load type (AAV_scDNA versus AAV_ssDNA). The motivation for quantifying the AAV_empty and AAV_partial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAV_scDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAV_scDNA and AAV_ssDNA despite their identical masses. In contrast, AUC could not differentiate between AAV_scDNA and AAV_ssDNA. An equimolar mixture of AAV_scDNA, AAV_ssDNA and AAV_empty was also measured with the sensor, and the results showed the expected population fractions, supporting the capacity of the method to differentiate AAV load status in heterogeneous solutions. In addition, less common optical and electrical signal signatures were identified in the acquired data, which were attributed to debris, rapid entry re-entry to the optical trap, or weak optical trap exits, representing critical artifacts to recognize for correct interpretation of the data. Together, these findings establish plasmonic nanopore sensing as a promising platform for quantifying AAV DNA loading status and genome type with the potential to extend ultra-sensitive single-particle characterization beyond the capabilities of existing methods. Full article

In-depth data on business development processes is required to understand the reasons behind productivity dynamics and economic trends. However, even basic demographic knowledge of Russian timber enterprises is often scarce, which severely limits opportunities for advanced economic research. This paper addresses this issue by introducing an open dataset on the business demographics of logging and sawn wood production companies in Asian Russia, an important center of the global forestry economy. To create an aggregated dataset containing registration and liquidation information from 1991 to 2024, we developed an approach to collect and process primary data on 9731 legal entities in the specified timber industries and Russian regions. This paper presents the periodization of the Russian timber market for the first time based on the obtained dataset. This periodization allows us to track the effects of significant changes in the business environment over the past 35 years. The analysis revealed a structural shift in 2016, due to the launch of the tax authorities’ policy of liquidating abandoned and shell companies. This led to an overestimation of the number of liquidations in official statistics. Our estimates of the liquidation rates for economically active timber companies from 2016 to 2024 are three to five times lower, highlighting the importance of using micro-level data for economic research. Our findings suggest that the crises of 2019–2020 and 2022–2024 had a greater impact on new entries than exits in the Asian Russian timber market. The largest forest companies have demonstrated resilience in the face of changes in the timber market, the pandemic crisis, and economic sanctions imposed on Russia, as evidenced by their low liquidation rates. Full article

Advances in sensor technology have significantly improved the efficiency and precision of agricultural spraying. Unmanned aerial vehicles (UAVs) are widely utilized for applying plant protection products (PPPs) and fertilizers, offering enhanced spatial control and operational flexibility. This study evaluated the performance of an autonomous UAV-based precision spraying system that applies variable rates based on zone levels defined in a prescription map. The system integrates real-time kinematic global navigation satellite system positioning with a proximity-triggered spray algorithm. Field experiments on a rice field were conducted to assess spray accuracy and fertilization efficacy with liquid fertilizer. Spray deposition patterns on water-sensitive paper showed that the graded strategy distinguished among zone levels, with the highest deposition in high-spray zones, moderate in medium zones, and minimal in no-spray zones. However, entry and exit deviations—used to measure system response delays—averaged 0.878 m and 0.955 m, respectively, indicating slight lags in spray activation and deactivation. Fertilization results showed that higher application levels significantly increased the grain-filling rate and thousand-grain weight (both p < 0.001), but had no significant effect on panicle number or grain count per panicle (p > 0.05). This suggests that increased fertilization primarily enhances grain development rather than overall plant structure. Overall, the system shows strong potential to optimize inputs and yields, though UAV path tracking errors and system response delays require further refinement to enhance spray uniformity and accuracy under real-world applications. Full article

Background/objectives: The purpose of this study was to examine the overall efficacy and treatment outcomes of CROs in the treatment of isolated deformational plagiocephaly and investigate the variables that influence treatment efficacy. Methods: This was a 10-year retrospective review of N = 27, 990 infants with Isolated Deformational Plagiocephaly (IDP) who completed Cranial Remolding Orthosis (CRO) treatment between 3 and 18 months of age. Results: There was a significant overall mean change in CVAI(S) of −3.42 ± 0.011 (p < 0.001), and a significant improvement in CVAI(S) in all age groups, even in older babies (i.e., >11 months). Up to 96% of infants aged 4–6 months at initiation of treatment achieved a “good” or “great” outcome rating, and up to 77.6% of infants over 11 months exited with a similar outcome. The following were identified as significant predictors of greater change in CVAI(S): (1) younger entry age (p < 0.001, β = 0.01), (2) larger initial CVAI(S) scores (p <0.001, β = −0.43), (3) left plagiocephaly (p < 0.001, β = −0.36), and (4) and the absence of torticollis (p < 0.001, β = −0.17). Conclusions: CROs are an effective, research-supported treatment for IDP. Pediatric health care providers and parents should be aware of the efficacy of CRO therapy across age groups and severity ratings, the risk factors that may influence CRO outcomes, and the benefits of an early referral at a young age. Full article

The COVID-19 pandemic highlighted the need for a scientific framework that enables quantitative assessment and control of airborne infection risks in indoor environments. This study identifies limitations in the traditional Wells–Riley model—specifically its assumptions of perfect mixing and steady-state conditions—and addresses these shortcomings by adopting the REHVA (Federation of European Heating, Ventilation and Air Conditioning Associations) infection risk assessment model. We propose a five-tier risk classification system (Monitor, Caution, Alert, High Risk, Critical) based on two key metrics: the probability of infection (Pₙ) and the event reproduction number (R_event). Unlike the classical model, our approach integrates airborne virus removal mechanisms—such as natural decay, gravitational settling, and filtration—with occupant dynamics to reflect realistic contagion scenarios. Simulations were conducted across 10 representative indoor settings—such as classrooms, hospital waiting rooms, public transit, and restaurants—considering ventilation rates and activity-specific viral emission patterns. The results quantify how environmental variables (ventilation, occupancy, time) impact each setting’s infection risk level. Our findings indicate that static mitigation measures such as mask-wearing or physical distancing are insufficient without dynamic, model-based risk evaluation. We emphasize the importance of incorporating real-time crowd density, occupancy duration, and movement trajectories into risk scoring. To support this, we propose integrating computer vision (CCTV-based crowd detection) and entry/exit counting sensors within a live airborne risk assessment framework. This integrated system would enable proactive, science-driven epidemic control strategies, supporting real-time adaptive interventions in indoor spaces. The proposed platform could serve as a practical tool for early warning and management during future airborne disease outbreaks. Full article

The icebreaking process of water-exiting vehicles involves complex nonlinear interactions as well as multi-physical field coupling effects among ice, solids, and fluids, which poses enormous challenges for numerical calculations. Addressing the low solution accuracy of traditional grid methods in simulating large deformation and destruction of ice layers, a numerical model was established based on the FEM-SPH-SALE coupling algorithm to study the dynamic characteristics of the water-exiting vehicle on the icebreaking process. The FEM-SPH adaptive algorithm was used to simulate the damage performance of ice, and its feasibility was verified through the four-point bending test and vehicle breaking ice experiment. The S-ALE algorithm was used to simulate the process of fluid/structure interaction, and its accuracy was verified through the wedge-body water-entry test and simulation. On this basis, numerical simulations were performed for different ice thicknesses and initial velocities of vehicles. The results show that the motion characteristics of the vehicle undergoes a sudden change during the ice-breaking. The head and middle section of the vehicle are subject to greater stress, which is related to the transmission of stress waves and inertial effect. The velocity loss rate of the vehicle and the maximum stress increase with the thickness of ice. The higher the initial velocity of the vehicle, the larger the acceleration and maximum stress in the process of the vehicle breaking ice. The acceleration peak is sensitive to the variation in the vehicle’s initial velocity but insensitive to the thickness of the ice. Full article

Carbon fibre reinforced composite (CFRP) laminates are widely used in high-tech industries. However, their assembly often requires a drilling process that can create defects. Therefore, studies on the drill tip angle have sought to minimize the surface area affected by these defects and improve the internal hole quality. In this work, drilling was carried out under dry conditions at a constant cutting speed for four different feed rates in the epoxy–carbon-based thermosetting laminate (EPX-C). Two carbide drills with point angles of 118° and 140° were used. The results showed the occurrence of chipping-type delaminations on both the hole entry and exit surfaces, with the latter being more severely affected. The delamination factor values obtained indicated that the 118° drill performed better than the 140° drill. The results were also compared with those obtained in a previous study using drills with angles of 60° and 130°. Although the values were higher, they followed the same trend of reduction with increasing feed. In terms of surface finish, the average roughness (Ra) values obtained with the 140° drill were better at the lowest feed rate. Full article

In response to the need to optimize the performance of copper–graphite current-carrying friction materials, spark plasma sintering (SPS) technology was used to prepare copper–graphite composite materials with different graphite orientations. A self-made current-carrying friction testing machine was used to study the effect of graphite orientation on the current-carrying friction performance of copper–graphite composites. The results showed that as the graphite orientation increased, the current-carrying friction performance of the copper–graphite composites initially improved and then deteriorated. The performance was optimal when the graphite orientation of the 7.5 wt% graphite–copper composite was 90°, primarily constrained by the wear rate. The main wear mechanism was furrowing, and graphite enrichment occurred on the worn surface, where the graphite content on the wear surface was higher than that in the bulk material. The degree of enrichment varied under different wear mechanisms. The graphite content near the entry region of the friction surface was significantly lower than that near the exit region. Full article

Managing emissions and congestion in urban transportation systems is a growing challenge, particularly when traffic dynamics are influenced by real-time conditions and infrastructure constraints. This study addresses this issue by proposing a cellular automata-based model to analyze traffic emissions and flow dynamics in two-route traffic systems under one-directional flow conditions, incorporating various real-time information feedback strategies. Unlike previous studies, the proposed model integrates key components of urban infrastructure, such as lane-changing dynamics, traffic signalization, and vehicle-type heterogeneity, along with operational factors including entry rates, exit probabilities, and the number of waiting vehicles. The model aims to fill a gap in existing emission studies by capturing the dynamics of heterogeneous, multi-lane systems with integrated feedback mechanisms. These considerations provide valuable insights into traffic management and emission mitigation strategies. The analysis reveals that prioritizing information feedback from the system entrance, rather than relying on feedback from the entire system, more effectively reduces traffic emissions. Additionally, the Vehicle Number Feedback Strategy (VNFS) proved to be the most effective, reducing the number of waiting vehicles and consequently lowering CO₂ emissions. Furthermore, simulation results indicate that for entry rate values below approximately 0.4, asymmetrical lane-changing generates higher emissions, whereas symmetrical lane-changing yields elevated emissions when entry rate surpasses this threshold. Overall, this research contributes to advancing the understanding of traffic management strategies and offers actionable insights for emissions mitigation in two-route systems, with potential applications in intelligent transportation infrastructure. Full article

Travel time information has become an essential component of everyday commuting. Without such information, schedule delays would increase, leading to inevitable losses in traveler utility. In Korea, dedicated short-range communication transponders that identify vehicles have been installed along signalized arterials to collect travel time data. By matching vehicle identifications at consecutive points, travel times can be measured. However, for travel time information to be effective, two types of data processing techniques are required: outlier filtering and travel time prediction. This study proposes algorithms to address both challenges. An outlier filtering algorithm based on the median-based confidence interval was developed, taking into account the travel time characteristics on suburban arterials with frequent entry and exit points. Additionally, a travel time prediction algorithm that integrates Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNNs), referred to as LSTM-CNN, was developed to capture both long-term trends and local patterns in travel time data. The implementation of these algorithms resulted in a 2.2% reduction in error rates under congested conditions compared to current practices. At the 4 km study site, the annual benefits from this error reduction could amount to USD 135,200. Full article

The tympanic membrane forms an impenetrable barrier between the ear canal and the air-filled middle ear, protecting it from fluid, pathogens, and foreign material entry. We previously screened a phage display library and discovered peptides that mediate transport across the intact membrane. The route by which transport occurs is not certain, but possibilities include paracellular transport through loosened intercellular junctions and transcellular transport through the cells that comprise the various tympanic membrane layers. We used confocal imaging to resolve the phage’s path through the membrane. Phages were observed in puncta within the cytoplasm of tympanic membrane cells, with no evidence of phages within junctions between epithelial cells. This result indicates that transport across the membrane is transcellular and within vesicles, consistent with the transcytosis process. The trans-tympanic peptide phages display a wide range of transport efficiencies for unknown reasons. This could include variation in tympanic membrane binding, entry into the membrane, crossing the membrane, or exiting into the middle ear. To address this, we titered phages recovered from within the membrane for phages with differing transport rates. We found that differences in the transport rate were inversely related to their presence within the tympanic membrane. This suggests that differences in the transport rate primarily reflect the efficiency of an exocytotic exit from the mucosal epithelium rather than entry into, or passage across, the membrane. Full article