Search Results (3,192)

Physically active individuals demonstrate enhanced immune competence. Efficient execution of effector function relies on chemokine receptor-regulated immune cell trafficking along chemokine gradients to sites of inflammation, infection, tumors, or tissue damage. This study investigates the impact of acute high-intensity interval training (HIIT) on chemokine receptor expression in leukocytes. Sixteen healthy participants completed a single HIIT session, and peripheral blood was collected before exercise (Bsl), immediately after (Ex02), and one hour later (Ex60). Surface expression of selected chemokine receptors was measured using flow cytometry on CD4⁺ T cells, γδ T cells, NK cells, and monocytes, followed by FlowSOM clustering. NK cells, CD4⁺ T cells, and γδ T cells were strongly mobilized at Ex02 and returned to or below baseline at Ex60. HIIT preferentially mobilized CX3CR1⁺ CXCR2⁺ CD56^dim NK cells, CD4⁺ T cells expressing CX3CR1^hi and CCR5⁺, and CX3CR1⁺ CD56⁺ γδ T cells, indicating mobilization of immune cells phenotypically associated with migratory and cytotoxic potential. Proportions of intermediate and non-classical monocytes increased at Ex02 and decreased at Ex60. In conclusion, HIIT induced a rapid redistribution of leukocyte subsets with chemokine receptor profiles suggesting enhanced endothelial interaction and migratory capacity toward effector tissues. Full article

We develop an informational extension of spacetime thermodynamics in which local entropy production is coupled to spacetime curvature within an effective covariant framework. Spacetime is modeled as a continuum limit of finite-capacity information registers, giving rise to a coarse-grained entropy field whose gradients define an informational flux. Within a nonminimally coupled scalar–tensor formulation, the resulting field equations imply that the local divergence of this flux is sourced by the Ricci scalar, establishing a direct relation between curvature and entropy production. The corresponding integral form links cumulative entropy generation to the integrated spacetime curvature over a causal region. In stationary limits, the framework reproduces the Bekenstein–Hawking entropy of horizons, while in homogeneous expanding cosmologies it yields monotonic entropy growth consistent with the observed arrow of time. The construction remains compatible with unitarity at the microscopic level and with holographic entropy bounds in the stationary limit. Numerical solutions in flat FLRW backgrounds are used as consistency checks of the coupled evolution equations and confirm the expected curvature–entropy behavior across cosmological epochs. Overall, the results provide a thermodynamically consistent interpretation of curvature as a geometric source of irreversible information flow, without modifying the underlying gravitational field equations. Full article

For battery-powered Smart Road components deployed in locations without access to the electrical grid, limited energy availability represents a major challenge to long-term autonomous operation. While photovoltaic panels are the most commonly used energy-harvesting solution, their effectiveness depends strongly on environmental and climatic conditions and may be insufficient in shaded areas or in highly dynamic road environments. Road infrastructure, however, inherently provides additional and largely underutilized energy sources, among which thermoelectric energy generated by temperature gradients within the road structure is particularly promising. This review addresses the problem of identifying viable alternatives or complements to photovoltaic energy harvesting by focusing on thermoelectric transducers as a potential power source for Smart Road applications. The objective of the article is to provide a comprehensive overview of the physical principles underlying thermoelectric transducers, the different architectures of thermoelectric modules, and their practical applicability in road transportation systems. Particular attention is devoted to implementation approaches that do not interfere with traffic flow or compromise road safety, as well as to existing applications of thermoelectric energy harvesting in transportation infrastructure. In addition, the review discusses the potential and limitations of concentrated thermoelectric transducers for increasing power density. By synthesizing current research results, this work evaluates the feasibility, advantages, and challenges of thermoelectric energy harvesting to extend the operational lifetime of autonomous Smart Road components and identifies directions for future research. Full article

The primary objective of the current study is to establish and validate for the first time a method to determine and quantify praziquantel (PZQ) and its main degradation products loaded in poly(methyl methacrylate–co-2-(diethylamino)ethyl methacrylate) P(MMA-co-DEAEMA) microparticles. A high-performance liquid chromatography (HPLC) approach was developed and validated in accordance with the United States Pharmacopeia (USP) guidelines, addressing parameters such as accuracy, linearity, solution stability, precision, specificity, robustness, sensitivity, and system suitability. The method employed a gradient mobile phase consisting of ultrapure water and acetonitrile, flowing at a rate of 1 mL/minute over a Phenomenex Kinetex^® C18 column (5 µm, 100 Å, 250 × 4.6 mm) maintained at 35 °C. Detection was performed at the wavelength of 210 nm using a DAD/UV detector. Samples of the active pharmaceutical ingredient (API) praziquantel, microencapsulated praziquantel, placebo, and a mixture of related substances (A, B, and C) were prepared with 0.5% formic acid in water/ethanol, 45:55 v/v as the diluent, and injected at 20 °C. The method demonstrated a limit of quantification (LOQ) of 0.20 µg/mL for praziquantel and related substances. The method exhibited an excellent linear response, with all correlation coefficients (R²) values exceeding 0.998, which is well above the recommended specified limit of R² > 0.995. Percent recoveries fell within the acceptable range of (95.0–105.0%), and all results indicated a percentage of relative standard deviation (%RSD) ≤ 2.0, indicating a robust methodology. Thus, the proposed HPLC technique proved to be selective, accurate, sensitive, and consistent in analyzing both the material content and its main degradation products. Full article

The Jurassic lacustrine oil shale in southwest China has become a primary production layer due to its high yield and substantial reserves. However, influenced by the lacustrine environment, the vertical profile of the lacustrine shale reservoir shows alternating deposits of shale and carbonate rock. This complex lithological combination results in significant heterogeneity in reservoir types, reservoir distribution, and internal structure. Currently, research on micro-pore structure and hydrocarbon storage mechanisms in lacustrine shales is insufficient, necessitating the elucidation of their micro-characteristics to support future exploration and development. This research focuses on the Da’anzhai Member of Jurassic Ziliujing Formation. Various techniques—including organic geochemical analysis, X-ray diffraction, physical property testing, gradient centrifugation, and gradient drying NMR monitoring—were employed to investigate the micro-pore structure and fluid storage mechanisms of the lacustrine shale reservoir. The following insights were gained from this research. The organic matter pores (OMP) and inorganic pores (IP) developed within the Da’anzhai lacustrine shale reservoir together create the storage space for shale oil, while micro-fractures further enhance the reservoir’s storage capacity and flow performance. Lacustrine shale oil exists in three storage states: mobile oil, bound oil, and adsorbed oil. Mobile oil is primarily located within the micro-fractures and large pores (greater than 350 nm) of the shale reservoir and is the main target for industrial extraction. Bound oil is mainly found in the meso-pores, micropores, and narrow pore structures between rock grains (30 nm to 350 nm), and, theoretically, could potentially be developed through engineering methods such as hydraulic fracturing. Adsorbed oil, due to its close binding with organic matter and clay mineral surfaces, is difficult to release effectively using conventional techniques. The OM abundance, the mineral composition of lacustrine shale, and the pore structure all influence the storage states of shale oil. While a high TOC value increases the amount of mobile oil, the strong adsorption properties of kerogen and organic matter lead to the accumulation of adsorbed oil, which inhibits oil flow. Clay minerals further restrict oil flow by enhancing adsorption, while brittle minerals facilitate the movement of mobile oil by expanding pore space. Based on fractal geometry theory and multi-scale testing results, the large pores in the Da’anzhai lacustrine shale have a high fractal dimension and exhibit complex shapes. However, as pore complexity increases, the amount of adsorbed oil rises significantly, which in turn reduces the proportion of movable oil. Full article

Human interferences have set off a multitude of morphological responses of the lower Rhine in Germany and the Netherlands. We share insights from thirty years of studies on these responses in the Niederrhein below Xanten and the branches in the delta. Elementary analyses of the 1D Saint-Venant–Exner equations explain the downstream flattening and upstream steepening of the longitudinal bed profile due to retrogressive erosion in response to river training, bend cut-offs and sediment mining. Three reasons make a 2D approach necessary for modelling the seemingly 1D problem of large-scale morphological response: (i) transverse variations in bed sediment composition, (ii) sediment division at river bifurcations, and (iii) the possibility that non-erodible layers in bends cause either erosion or sedimentation of the longitudinal bed profile. The Pannerdense Kop and IJsselkop bifurcations are in a state of quasi-equilibrium, essentially unstable but developing slowly. Considerable spatiotemporal variations in the sediment composition of the riverbed surface pose a challenge to stabilizing the longitudinal bed profile by matching gradients in flow velocity to gradients in bed sediment composition. As these variations form a major knowledge gap, we recommend research on the state and dynamics of sediment size and layer structure in the upper metres of the riverbed. Full article

Prostate cancer remains largely refractory to immunotherapy, implying the existence of context-specific immune landscape programs that diverge between circulation and tumor. Here, we integrate bulk RNA sequencing from three cohorts (patient peripheral mononuclear cells, primary prostate tissue, and biochemical-recurrence tumors) with multiparameter flow cytometry, unsupervised UMAP/T-REX (Tracking Responders Expanding) mapping, and de novo discovery of long non-coding RNAs (lncRNAs) to characterize context-specific immunoregulation. Patient PBMCs revealed a coherent IL-1/TNF/IL-17 inflammatory architecture with strong chemotactic programs and an unexpected neutrophil-like signal despite density-gradient isolation, consistent with low-density PMN-MDSCs. In contrast, tumors broadly repressed chemokines and innate immune mediators, yet upregulated prostate cancer-associated lncRNAs, indicating local immune quiescence coupled with non-coding regulatory programs. Recurrent tumors acquired epithelial–mesenchymal transition and metabolic remodeling, accompanied by relapse-associated lncRNA signatures, whereas long-term nonrecurrent tumors preserved epithelial and stress-response networks. High-dimensional cytometry confirmed discrete, cancer-enriched myeloid clusters expressing CD47, SIRPα, PD-L1, CD73, and Galectin-9. Network analysis highlighted inflammatory hubs (CXCL2, PTGS2) in PBMCs and loss of mechanotransduction modules in tumors. Structural modeling uncovered a three-way junction and 3′ triple helix in lncRNA. Collectively, these data suggest that circulating inflammatory rewiring is associated with checkpoint-rich suppressor expansion and tumor immune quiescence, outlining integrated myeloid- and RNA-directed strategies for cancer research. Full article

The well-known shooting algorithm has produced important results in solving various linear as well as nonlinear BVPs, defined on unbounded intervals, but has become obsolete. The main difficulty lies in the numerical handling of the domain’s infiniteness. This paper presents a three-step strategy that significantly improves the traditional truncation algorithm. It consists of Chebyshev collocation, implemented as Chebfun, in conjunction with rational AAA interpolation and analytic continuation. Furthermore, and more importantly, this approach enables us to provide a thorough analysis of both possible errors in dealing with and the hidden singularities of some BVPs of real interest. A singular second-order eigenvalue problem and a fourth-order nonlinear degenerate parabolic equation, all defined on the real axis, are considered. For the latter, Chebfun provides properties-preserving solutions. Travelling wave solutions are also studied. They are highly nonlinear BVPs. The problem arises from the analysis of thin viscous film flows down an inclined plane under the competing stress due to the surface tension gradients and gravity, a long-standing concern of ours. By extending the solutions to these problems in the complex plane, we observe that the complex poles do not influence their behaviour. On the other hand, the real ones involve singularities and indicate how long solutions can be extended through continuity. Full article

This study investigates left-turn safety at urban intersections using surrogate safety measures derived from field video observations. Time-to-Collision (TTC) among motorized traffic and Post-Encroachment Time (PET) among pedestrian and motorized traffic were extracted for left-turn conflicts across five intersection types in Thessaloniki, Greece, and linked to geometric attributes, signal operations, and traffic conditions. Count-based models (Poisson, Negative Binomial) were estimated alongside machine-learning approaches (Random Forest, Gradient Boosting with Poisson loss). For PET events, the Poisson model had the best balance of parsimony and predictive accuracy, whereas the Negative Binomial model provided a superior fit for TTC events. Results indicate that PET-defined conflicts increased with pedestrian volume and the presence of shared and protected left-turn lanes, and decreased with higher opposing flow, greater average acceleration, and wider end-approach lanes. By contrast, TTC events were associated with lower average speeds, the presence of protected signal phasing for left turns, and the number of passenger cars. Machine-learning models underperformed relative to classical count models, reflecting limited sample size and the discrete event structure. The analysis indicates that the determinants of TTC and PET differ, with certain variables such as pedestrian activity and lane configuration having contrasting effects on the two surrogate safety measures. The analysis reveals that pedestrian demand and shared lane configurations significantly increase PET occurrences, whereas TTC events are more strongly associated with vehicle volumes, speeds, and signal phasing. This distinction underscores the importance of tailoring safety assessment and intervention strategies to the type of interaction being evaluated. Full article

The present study investigates the generalized dispersion of a solute in an incompressible MHD flow via a rectangular channel with injectable or suctioned walls. The mathematical model of dispersion suggests a distinct type of mass flux expressed as a fractional partial differential equation based on the time-fractional Caputo derivative. The mass flow in the model under investigation is determined by both the concentration gradient and its historical evolution. A constant external magnetic field is provided transverse to the flow direction. The analysis and discussion of the analytical solution for the advection velocity are performed in relation to the Hartmann number and the suction/injection Reynolds number. To determine the solute concentration in space and time, the unstable fractional convection–diffusion equation is analytically solved. The polynomial in the geographic variable y that has coefficients that depend on the spatial variable x and the time t is the analytical solution of the concentration. The effects of the fractional order of the Caputo derivative, Reynolds number, Hartmann number, and Peclet number on the advection–diffusion process are examined using numerical simulations of the analytical solution of the solute concentration. Full article

Riverbed topography in natural rivers commonly features sand dunes, whose morphological variations can alter the turbulent flow structure near the bed and thereby affect processes of channel scour, deposition, and sediment transport. In this study, a series of flume experiments was conducted using an acoustic Doppler velocimeter (ADV) to simulate fixed bedforms of different dune scales (ratio of wavelength to flow depth, λ/h) in a laboratory flume. Velocity measurements were taken along the water depth at the dune crest and trough for each test case. The near-bed distributions of mean flow velocity, Reynolds stress, turbulent kinetic energy (TKE), and turbulence intensity were obtained at the crest and trough under three flow conditions, allowing analysis of the vertical decay of turbulence intensity at different locations on the dune. The results show that the dune steepness (Ψ, defined as dune height over wavelength) is a key parameter controlling the near-bed flow structure. As Ψ increases, the near-bed velocity gradient, Reynolds stress, TKE, and peak turbulence intensity all increase significantly, with the peak positions shifting closer to the bed. The trough region, due to flow separation and vortex shedding, exhibits substantially higher values of all turbulence-related parameters than the crest, making it the primary zone of energy dissipation and turbulence production. This study provides experimental evidence and theoretical reference for understanding the mechanism by which sand dune morphology influences flow structure, and it offers insight for predicting riverbed evolution. Full article

To address the critical challenge of low thermoelectric conversion efficiency in high-temperature, highly turbulent waste heat recovery, a novel fish-fin convergent annular thermoelectric generator (FF-CATEG) device is proposed. An annular contraction-type thermal conduction ceramic component is designed along the axial gradient direction, with fish-fin-like fins and thermocouple annular arrays introduced on the inner and outer walls of the ceramic, respectively. Therefore, the directional transport through the cross-coupling of fluid kinetic energy and thermal energy is achieved, significantly improving the thermoelectric conversion efficiency of the proposed structure. Experimental validation demonstrates that the optimized FF-CATEG attains a maximum net output power of 6.17 W at a pipe contraction angle of 3.5° and a fin coverage of 13.44%. With a temperature difference of 320 K and a waste heat fluid velocity of 14.5 m/s, the thermoelectric conversion efficiency is enhanced to 3.97%, representing a substantial 39.3% improvement compared to the finless configuration. This study presents a new approach for recovering waste heat from turbulent flows. Full article

An analysis is presented for the steady thermophoresis and photophoresis of a homogeneous dispersion of identical aerosol spheres of typical physical properties and surface characteristics. The analysis assumes a moderately small Knudsen number (less than about 0.1), such that the gas motion lies within the slip-flow regime, including thermal creep, temperature jump, thermal stress slip, and frictional slip at the particle surfaces. Under conditions of low Peclet and Reynolds numbers, the coupled momentum and energy equations are analytically solved using a unit cell approach that explicitly incorporates interparticle interactions. Closed-form expressions are derived for the mean particle migration velocities in both thermophoresis driven by a uniform temperature gradient and photophoresis induced by an incident radiation field. The results reveal that the normalized particle velocities, referenced to those of an isolated particle, generally decrease with increasing particle volume fraction, though exceptions occur for thermophoresis. While thermal stress slip and thermal creep exert no influence on the normalized thermophoretic velocity, they markedly affect the normalized photophoretic velocity, which rises with the thermal stress slip to the thermal creep coefficient ratio. For both phenomena, the normalized migration velocities increase monotonically with the particle-to-fluid thermal conductivity ratio. Full article

To address the issues of parameter setting, reliance on human experience, and the limitations of traditional model-driven control methods in handling complex nonlinear dynamics in the tin smelting industrial process, this paper proposes a data-driven control approach based on improved deep reinforcement learning (RL). Aiming to reduce the tin entrainment rate in smelting slag and CO emissions in exhaust gas, we construct a data-driven environment model with an 8-dimensional state space (including furnace temperature, pressure, gas composition, etc.) and an 8-dimensional action space (including lance parameters such as material flow, oxygen content, backpressure, etc.). We innovatively design a Dual-Action Discriminative Deep Deterministic Policy Gradient (DADDPG) algorithm. This method employs an online Actor network to simultaneously generate deterministic and exploratory random actions, with the Critic network selecting high-value actions for execution, consistently enhancing policy exploration efficiency. Combined with a composite reward function (integrating real-time Sn/CO content, their variations, and continuous penalty mechanisms for safety constraints), the approach achieves multi-objective dynamic optimization. Experiments based on real tin smelting production line data validate the environment model, with results demonstrating that the tin content in slag is reduced to between 3.5% and 4%, and CO content in exhaust gas is decreased to between 2000 and 2700 ppm. Full article

As computational fluid dynamics (CFD) has become more mainstream in production engineering workflows, new demands have been introduced that require high-quality meshes to accurately capture the complex geometries. This evolution has created the need for mesh generation frameworks that help engineers design optimized meshing structures for each new geometry. However, many simulation workflows rely on the experience and intuition of senior engineers rather than systematic frameworks. In this paper, a novel technique for determining mesh convergence is created using machine learning (ML). This method seeks to provide process engineers with a visual feedback mechanism of flow regions that require mesh refinement. The work was accomplished by creating three grid sensitivity studies on various geometries: zero-pressure-gradient flat plate, bump in channel, and axisymmetric free jet. The cases were then simulated using the Reynolds Averaged Navier-Stokes (RANS) models in OpenFOAM (v2306) and had the ML method applied post-hoc using Python (v3.12.6). To apply the method to each case, the flow field was regionalized and clustered using an unsupervised ML model. The ML clustering results were then converted into a similarity score, which compares two grid levels to inform the user whether the region of the flow had converged. To prove this framework, the similarity scores were compared to flow field probes used to determine mesh convergence at key points in the flow. The method was found to be in agreement with the flow field probes on the level of mesh refinement that created convergence. The approach was also seen to provide refinement region recommendations in regions of the flow that align with human intuition of the physics of the flow. Full article