Search Results (1,265)

To elucidate the hydraulic transport characteristics of coarse-particle slurry in deep-sea mining vertical lifting pipelines and the governing effects of key operating parameters, a bidirectionally coupled CFD-DEM model was established, in which seawater was treated as the continuous phase and ore particles were treated as the discrete phase, while particle–fluid momentum exchange and particle–particle/particle–wall collisions were explicitly accounted for. The effects of inlet velocity, feed concentration, particle size, and particle shape on local particle concentration, local particle flow rate, and particle volume fraction distribution were systematically investigated. The results show that increasing the inlet velocity markedly reduces local particle concentration, increases the local particle flow rate, and promotes a faster transition of the solid–liquid two-phase flow toward a uniformly mixed state. Increasing the feed concentration enhances the conveying capacity, but simultaneously increases the risk of particle aggregation. The effect of particle size on local concentration is non-monotonic: the local concentration is relatively high at approximately 20 mm, whereas smaller particles exhibit better flow uniformity. The effect of particle shape is mainly manifested under low-velocity and high-concentration conditions, and gradually weakens with increasing inlet velocity. The present results provide a theoretical basis for parameter optimization of deep-sea mining vertical lifting systems. Full article

Resistivity is a key parameter in shale reservoir characterization. Diverse micro-pore types and complex conduction mechanisms in shale result in poor accuracy when applying existed conductivity models. Establishing a high-precision conductivity response model requires comprehensive consideration of the pore structure and clay-bound water conduction. The primary novelty of this work lies in replacing macroscopic empirical fitting parameters with a mechanistic, multi-dimensional fractal framework. We develop a novel conductivity response characterization model that explicitly couples multi-dimensional fractal pore structure theory with clay-bound water conduction. Experimental data verification demonstrates the new model’s superior characterization accuracy. Results indicate three distinct zones in the shale conductivity-pore water conductivity relationship: a nonlinear zone, a transition zone, and a linear zone. A higher cation exchange rate on clay surfaces leads to an increase in the nonlinear characteristics of the conductivity for both the shale and the pore water in low-salinity regions. An increase in the values of the conduction path fractal dimension, pore morphology fractal dimension, and pore fractal dimension all contribute to reduced shale conductivity. While sharing clay-induced conductivity terms with conventional dual-water and shale volume models, the new model offers advantages in operational simplicity and parameter accessibility. This research provides a physically rigorous and highly accessible approach for conductivity-based reservoir parameter calculation, offering new technical perspectives for complex shale oil/gas evaluation. Full article

With the increasing number and enhanced sensing capabilities of satellites, the volume of satellite imagery has substantially surpassed the available bandwidth of satellite-to-ground links. Recently, with the adoption of commercial on-board GPUs, Learned Image Compression (LIC) offers the potential to mitigate this bottleneck by virtue of its superior rate–distortion performance over traditional codecs. However, existing LIC solutions operate in isolation on single satellites and underutilize the overlapping observations, which limits further gains in compression performance. In this paper, we propose Distributed Latent Representation Clustering (DLRC), which represents the first attempt to integrate real-time multi-satellite observation redundancy elimination into LIC. DLRC first introduces a local latent representation clustering mechanism. It discretizes the latent representation of LIC into compact cluster signatures on each satellite with lightweight computational overhead. Subsequently, DLRC presents a global cluster signature synchronization strategy. By exchanging signatures with negligible communication overhead, it enables multiple satellites to identify globally redundant local observations on a per-signature basis. By coding and downlinking only the latent representation corresponding to globally unique signatures, DLRC achieves non-redundant downlink in a training-free paradigm while remaining compatible with existing LIC architectures. Through extensive experiments, we demonstrate that DLRC achieves efficient bits per pixel reduction compared to independent LIC solutions while maintaining comparable reconstruction quality. Full article

Finite-volume gravity currents frequently encounter bottom obstacles, particularly in underwater environments such as lakes and oceans. However, how obstacle–current interactions reorganize Lagrangian transport pathways and ultimately determine the fate of fluid elements over the full current life cycle remains unclear. Using large-eddy simulations, we focus on a low-volume lock-exchange gravity current impinging on an isolated two-dimensional triangular obstacle. Fluid-element trajectories are tracked from collapse through propagation, obstacle interaction, and final dilution and decay, and are classified using K-means clustering into five transport modes linked to characteristic flow structures. We find that increasing obstacle slenderness strengthens upstream reflection and reduces downstream overflow, thereby shifting the fate of tracer particles from downstream delivery toward upstream retention. In addition, the obstacle standoff distance controls the dynamical state of the current at impact, producing systematic yet non-monotonic changes in the fractional population of the transport modes. This study establishes an explicit correspondence between evolving flow structures and clustered Lagrangian pathways. Comparative cases with varying geometric configuration, density contrast, flow depth, and release volume indicate that the identified transport patterns are reasonably robust. Therefore, the present results provide a fate-oriented predictive framework and theoretical basis for the transport of finite-volume gravity currents near obstacles, with important implications for engineering applications. Full article

Automated multiplex immunohistochemistry (IHC) and in situ hybridization (ISH) require staining platforms that combine stable reagent exchange, low-volume operation, process observability, and protocol flexibility. Existing autostainers are often rigid and costly, whereas microfluidic and sensing solutions remain largely component-specific rather than system-oriented. This study proposes and partially validates a layered cyber-physical architecture for multiplex histological staining. The architecture integrates five functional layers—biochemical workflow, fluidic processing, capacitive sensing, protocol-driven control, and software-based process representation—within a unified formal framework and is supported at the subsystem level by experimental characterization of its fluidic and sensing layers. Fluidic experiments on a slot-type microfluidic chamber identified a practical operating window in which upper-feed operation, moderate calibrated flow conditions, and low chamber angles between 10° and 40° provide stable filling and acceptable drainage. The differential slot-line capacitive sensing subsystem detected liquid volumes as low as 0.5 µL, with stable threshold-based interpretation at a practical detection threshold of approximately 5 fF after digital filtering. The control and software layers are specified at the architectural and formal model level; their hardware implementation and closed-loop validation remain subjects of future work. Together, the reported results demonstrate that controlled reagent transport and sensing-based process observability are jointly feasible within the proposed modular framework, establishing a conceptual and experimental foundation for scalable, flexible, and resource-efficient multiplex IHC/ISH systems. Full article

Organic Rankine Cycles (ORCs) are widely recognized as an effective solution for Waste heat recovery (WHR). However, the design and optimization of these systems must address the tradeoff between computational efficiency and the need to capture complex component behavior. This requires moving beyond purely energetic 0D modeling approaches to account for constructional, spatial, and operational constraints. This work presents a novel modeling framework with a specific focus on the expansion device. Radial inflow turbine stages are selected for their capability to achieve high pressure ratios while maintaining compactness and high efficiency. Heat exchangers follow a generic one-dimensional counterflow configuration, with a shell-and-tube geometry adopted for sizing purposes. The turbine stages are modeled by resolving several internal sections in order to capture local thermofluid dynamic conditions. The framework predicts turbine efficiency and incorporates a newly developed formulation for shock-induced losses, improving performance prediction under trans-sonic flow conditions. After validation against experimental data, the model is applied to a WHR system integrated with an internal combustion engine fueled by biofuels. The results highlight the existence of optimal operating conditions arising from competing physical mechanisms. The analysis also shows the transition from single-stage to two-stage turbine configurations at high pressure ratios and emphasizes the role of real gas effects in determining stage performance and optimal expansion distribution. The results of simulations carried out for three different working fluids (ethanol, toluene, and R1234ze(E)) highlight that the available mechanical power ranges from 10 to 22 kW for single-stage turbine configurations and from 24 to 36 kW for two-stage configurations, with total system volumes varying between approximately 600 and 9000 L. Among the working fluids considered here, ethanol provides the best overall performance for the present case study. Overall, the proposed approach provides a reliable and computationally efficient tool for the preliminary design and optimization of ORC-based WHR systems. Full article

The atomic magnetometer (AM), operating within the spin-exchange relaxation-free (SERF) regime, boasts numerous advantageous qualities, including ultrahigh sensitivity, exceptional spatial resolution, and minimal power consumption. Consequently, it emerges as a promising alternative to superconducting quantum interference devices in biomagnetic measurement applications. This paper details the development of a fully integrated SERF AM system comprising a compact sensor head and corresponding control electronics. Utilizing a 4 mm × 4 mm × 4 mm cubic vapor cell, we have successfully integrated the compact sensor into a 9 ${\mathrm{cm}}^3$ volume employing a single-beam scheme facilitated by a polarization-maintaining fiber. The in-house control electronics encompass essential components, such as the laser driver, coil driver, vapor-cell temperature controller, and transimpedance amplifier. As a result, the fully integrated SERF AM achieves a sensitivity of 25 $\mathrm{fT}/{\mathrm{Hz}}^{1/2}$@5∼100 Hz, accompanied by a bandwidth of 193 Hz, meeting the necessary criteria for magnetocardiography (MCG) and magnetoencephalography (MEG) measurements. Furthermore, the fully integrated SERF AM successfully records typical MCG and alpha rhythm MEG signals, showcasing immense potential for biomagnetic imaging applications. Full article

Tidal inundation dynamics are a principal driver of hydrological and biogeochemical processes in coastal ecosystems, controlling the exchange of carbon, nutrients, and sediments between wetlands and estuaries. In this study, we assessed the utility of L-band radar imagery in deriving tidal wetland inundated volume estimates (pixel-wise water depths), which provide a more robust characterization of wetland–estuary exchange processes than the lateral inundation state estimates. Inundation state products derived using L-band radar were combined with digital elevation models (DEMs) and synthetic tide gauging to estimate the volume of inundation. Synthetic tide gauges, models of water level produced from combined short-term field measurements and long-term monitoring stations were employed to provide calibration and validation for satellite observations for times outside of the water level sensor monitoring period (August–December 2018). Ten synthetic gauges were established across the Charles H. Wheeler Wildlife Management Area (Connecticut, USA) in a regular grid and were used to validate the radar-based inundation state and inundated volume products. To generate volumetric inundation estimates from inundation state products, we employed two bathymetric fill approaches using a DEM to constrain water surface elevations. The first approach assumed a constant water elevation fill for all inundated pixels, while the second introduced a maximum water depth constraint. While both approaches showed strong correlations with synthetic gauges, the depth constraint approach was more accurate, increasing R² from 0.87 to 0.98 and lowering RMSE from 0.79 m to 0.02 m. In this study, PALSAR-1/2 served as a proxy for the recently launched NISAR mission. Future research is planned to leverage the improved temporal sampling of the NISAR data record, combined with in-marsh water level observations (May 2025–present) and synthetic gauge estimates to improve wetland–estuary volumetric exchange characterization, which we demonstrate can be accurately estimated when paired with high-quality DEMs. Full article

Poland ranks among the world’s leading exporters of goose meat and edible offal, yet domestic consumption remains minimal, revealing a structural imbalance between production and internal demand. This study aims to provide a comprehensive economic assessment of Poland’s foreign trade in goose meat and offal during 2020–2024, examining export specialization, price dynamics, and market resilience. Using official data from the Central Statistical Office (GUS), Eurostat, UN Comtrade, and the National Bank of Poland (NBP), trade flows were disaggregated by CN product codes, destination countries, and unit prices to identify key structural patterns. Results indicate that export volumes remained largely limited by price responsiveness despite sharp price increases and exchange rate fluctuations, confirming stable foreign demand. Exports were heavily concentrated in Germany, which absorbed over 70% of the total trade value, while domestic consumption stayed below 0.5 kg per capita annually. These findings demonstrate both the competitiveness and the fragility of Poland’s export-oriented trade model, characterized by dependence on a single market and limited domestic integration. The study concludes that long-term food system resilience requires diversification of export destinations, stimulation of domestic demand, and stronger alignment with sustainability goals. A forthcoming second part will address environmental impacts and consumer awareness. Full article

Open-source bioprinting can broaden access to biofabrication, enabling existing systems to perform high-resolution tissue manufacturing. However, most of these focus on low cost, easy assembly, or specific biomaterial ink rather than making a robust standardized and modularized multifunction platform. In this study, we present CrystalCells, a user-friendly modular open-source bioprinting system centered on the TridentExtruder, a high-performance syringe extruder with extrusion/retraction capability and tool-free automated syringe coupling. The system enables the automated exchange of syringe, temperature-controlling, microscope, and pipette modules. Repeated syringe return-and-pickup cycles showed repositioning errors within ±20 μm, while the extruder generated pressures above 950 kPa and exhibited lower elastic deformation than the Replistruder 4 under the same pressure conditions. CrystalCells supported the extrusion of pre-crosslinked alginate, FRESH printing, and dual-biomaterial inks printing with automated exchange. A microscope module resolved stained HeLa cells and enabled layer-by-layer imaging for defect detection during printing. A thermoelectric module maintained the syringe barrel below 6 °C during the printing of an alginate–collagen biomaterial ink at 23 °C (room temperature), and a pipette module transferred 2–10 μL volumes with errors within ±0.5 μL. These results show that CrystalCells is an open-source modular biofabrication platform integrating printing, imaging, temperature control, and liquid handling within a single workflow. Full article

To investigate the influence of working fluid composition on the thermo-hydraulic performance of plate heat exchangers (PHEs) under single-phase sensible heat transfer conditions, a three-dimensional steady-state numerical model was developed for a transverse corrugated channel with a chevron angle of 60°. The governing equations were solved using the finite volume method implemented in ANSYS Fluent, in conjunction with the standard k–ε turbulence model. The analysis considered pure refrigerants R134a and R245fa, as well as their mixtures with mass ratios of 0.2, 0.5, and 0.8, with thermophysical properties assumed to be temperature-independent constants. The results indicate that as the mass fraction of R134a decreases from 1.0 to 0, the heat transfer coefficient (h) decreases from 1025 to 815 W/(m²·K), primarily attributed to the combined effects of reduced thermal conductivity and increased viscosity. Among the investigated cases, the R134a/R245fa mixture with a mass ratio of 0.8 provides the most favorable performance trade-off, exhibiting a heat transfer coefficient only 3.0% lower than that of pure R134a while achieving a 12.5% reduction in flow resistance compared with pure R245fa. Furthermore, the heat transfer coefficient is found to be weakly affected by heat flux in the range of 8000–20,000 W/m²; in contrast, increasing the mass flow rate from 0.001 to 0.005 kg/s enhances heat transfer coefficient by 65.1%, accompanied by a significant increase in pressure drop. Comparisons with established single-phase correlations for corrugated channels show average deviations of 6.5% for the Nusselt number and 3.8% for the friction factor. The present study provides useful guidance for working fluid selection and operational optimization of PHEs in applications dominated by sensible heat transfer, such as specific stages of heat pump cycles and medium-temperature waste heat recovery. Full article

This study proposes a machine learning framework tailored to the institutional characteristics of Taiwan’s stock market, aiming to enhance forecasting accuracy for the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The model employs the Radius Neighbors Regressor with a dynamic radius-based similarity measure and integrates domain-specific features including technical indicators, volume–price relationships, and Qualified Foreign Institutional Investor (QFII) activity. A custom 60-day input window with a 20-day forecast horizon is applied to capture medium-term market dynamics. The framework was evaluated through extensive backtesting and real-world validation with the TAIEX Futures. The results demonstrate that the model achieves a peak directional accuracy of 85.1% under optimal parameter settings. Moreover, trading simulations confirm its practical viability, yielding a cumulative return on investment (ROI) of approximately 1600% during the short-term evaluation period (2023–2025) and nearly 2000% in the long-term evaluation (2019–2025), even after accounting for transaction costs and stop-loss mechanisms. These findings indicate that combining historical pattern similarity with institutional investor behavior substantially improves predictive power and profitability. Nevertheless, the framework remains constrained by its reliance on Taiwan-specific institutional features and historical trading data, limiting generalizability. Future research should extend applications to other markets while incorporating macroeconomic variables, corporate fundamentals, and news-driven signals to enhance adaptability. Full article

Wi-Fi networks used in smart grids are essential for enabling communication between smart meters and data aggregation units. A key challenge, however, is the ability to hide the existence and traffic patterns of these communications, so that sensitive information exchanges cannot be easily detected or intercepted. Unfortunately, most existing solutions do not provide support for traffic prioritization and steganographic channel encryption. In this paper, we propose a novel covert channel with Quality of Service (QoS) and encryption support for smart grid environments based on the IEEE 802.11 standard. We introduce an original steganographic approach that leverages the backoff mechanism, the Enhanced Distributed Channel Access (EDCA) function, frame aggregation, and the StegoPaddingCipher algorithm. This design ensures QoS-aware traffic handling while enhancing security through encryption of the transmitted covert data. The proposed protocol was implemented and evaluated using the ns-3 simulator, where it achieved excellent performance results. The system maintained high efficiency even under heavily saturated network conditions with additional background traffic generated by other nodes. The proposed covert channel offers an innovative and secure method for transmitting substantial volumes of QoS-related data within smart grid environments. Full article

Preterm birth interrupts critical phases of lung development and is associated with long-term alterations in respiratory structure and function. While bronchopulmonary dysplasia (BPD) has traditionally been considered the principal determinant of adverse outcomes, accumulating evidence indicates that prematurity per se contributes substantially to persistent pulmonary impairment. Lung function trajectories in preterm-born children frequently track along lower percentiles from infancy into adolescence and early adulthood, with limited catch-up growth and increased vulnerability to chronic airflow limitation. Assessment of lung function requires a developmentally tailored approach, as feasibility and interpretability vary across age groups. In infancy, non-volitional techniques such as tidal breathing flow-volume loop analysis and raised-volume rapid thoracoabdominal compression allow early evaluation of respiratory mechanics. During toddlerhood, methodological limitations persist, although emerging technologies may expand feasibility. In preschool children, impulse oscillometry enables detection of small airway dysfunction, often preceding spirometric abnormalities. From school age onward, spirometry, body plethysmography, diffusing capacity, and multiple breath washout provide complementary information on obstructive, restrictive, and gas-exchange impairments. Longitudinal studies demonstrate that reduced lung function is not confined to children with BPD and may predispose to early-onset chronic obstructive pulmonary disease-like phenotypes. Early identification of abnormal trajectories and modifiable risk factors supports structured long-term follow-up and preventive strategies. Standardization of age-specific assessment protocols and harmonization of reference values are essential to improve risk stratification and optimize long-term respiratory outcomes in this vulnerable population. Full article

The object of the study is a single heated carbonaceous particle of relatively small size, 0.003 to 0.01 m. Main hypothesis: The formation of soot particles and black carbon particles is caused by the thermochemical destruction of dry organic matter of forest fuel and the mechanical fragmentation of coke residue. The aim of the study is to conduct numerical simulations of heat and mass transfer in a single heated carbonaceous particle, taking into account the soot formation process and assessing its fragmentation with regard to heat exchange with the external environment in a 2D setting. As part of this study, a new model of heat and mass transfer in a pyrolyzed carbonaceous particle was developed, taking into account its step-by-step fragmentation (fragmentation tree model with four secondary particle formations from the initial particle). The calculations resulted in the distributions of temperature and volume fractions of phases in the carbonaceous particle across various scenarios. Scenarios of surface fires (initial temperatures of 900 K and 1000 K), crown fires (1100 K), and a firestorm (1200 K) for typical vegetation (pine, spruce, birch) are considered. Cubic carbonaceous particles are considered in the approximation of a 2D mathematical model. To describe heat and mass transfer in the structure of the carbonaceous particle, a differential equation of thermal conductivity with corresponding initial and boundary conditions of the third type is used, taking into account the gross reaction in the kinetic scheme of pyrolysis and soot formation. Differential analogues of partial differential equations are solved using the finite difference method of second-order approximation. Options for using the developed mathematical model and probabilistic fragmentation criterion for assessing aerosol emissions are proposed. Recommendations: The suggested mathematical model must be incorporated with mathematical models of forest fire plume and aerosol transport in the upper layers of the atmosphere. Moreover, probabilistic criteria for health assessment must be developed for the practical use of the suggested mathematical model. Full article