Search Results (22,000)

Pedestrian-induced vibration is a critical serviceability concern for flexible structures such as footbridges and long-span floors. Existing human–structure interaction models commonly rely on single-degree-of-freedom simplifications and time-domain simulations, making them less suitable for frequency-domain analysis. This paper proposes a spectral analysis model for crowd-structure interaction vibration under unrestricted pedestrian traffic. The structure was formulated as a multi-degree-of-freedom modal system, whereas each pedestrian is represented by an independent spring–mass–damper system. To address the time-varying nature of moving crowds, a piecewise stationary assumption was introduced: the continuous walking path was discretized into fixed position groups, within each of which a time-invariant coupled equation of motion was established. The response spectra obtained for different position groups were combined using residence-time weighting, thereby allowing nonuniform walking speeds to be considered. The corresponding frequency response function was derived using the state–space method, and the structural acceleration power spectral density and root mean square responses were obtained by incorporating an unrestricted crowd walking load spectral model. Comparisons with field measurements from two footbridges demonstrated reasonable agreement. The resulting framework offers an efficient frequency-domain approach for vibration serviceability assessment under unrestricted pedestrian traffic. Full article

The Chinese lizard gudgeon (Saurogobio dabryi) is an economically important freshwater species within the Cyprinidae family, abundant in the middle and lower reaches of the Yangtze River and its adjacent basins. As a promising species suitable for aquaculture in China, the lack of genomic resources has rendered the genetic breeding and conservation research. Here, we present the first chromosome-level genome assembly of S. dabryi using PacBio HiFi long reads, short reads, and Hi-C sequencing data. The final assembly reaches a total size of 1.09 Gb and Hi-C scaffolding anchors 99.55% of the assembled contigs onto 25 chromosomes, with a scaffold N50 reaching 43.15 Mb. The final genome assembly shows a BUSCO completeness of 98.39%. We annotated 659.55 Mb repetitive sequences and 26,036 protein-coding genes, 99.47% of which are functionally annotated. Comparative phylogenomic analysis clarifies the phylogenetic position of Saurogobio within Gobioninae. This high-quality genome provides a critical genetic basis for exploring cyprinid phylogeny, benthic adaptive evolution, genetic improvement, and conservation efforts of S. dabryi. Full article

This article presents a review and comparative analysis of converter architectures for electrolyzer systems, covering alternating current (AC) -grid-connected, direct-current (DC) -grid-connected, and renewable-energy-connected systems, as well as isolated and non-isolated configurations. The study classifies and compares key converter topologies based on engineering criteria, including voltage gain, efficiency, device count, control complexity, and implementation feasibility. Furthermore, the relationships among converter structures, power-source characteristics, and electrolyzer-system requirements are analyzed to reveal system-level engineering trade-offs. The analysis demonstrates that converter suitability depends on the combined requirements of the power source, galvanic isolation, electrolyzer characteristics, operating conditions, and application-specific engineering priorities. In addition, wide-bandgap semiconductor devices and electrolyzer operating characteristics are discussed as important factors in converter selection, particularly for improving converter efficiency, reducing current ripple, increasing power density, and supporting dynamic operation. This article therefore provides a systematic framework for converter classification and selection according to power-source characteristics, electrolyzer requirements, and application power levels. Full article

In this work, Cu₂CoSnS₄ (CCTS) thin films were deposited on glass substrates by thermal evaporation and investigated for photovoltaic applications. The influence of substrate temperature, varied from 25 °C to 200 °C, on the structural, morphological, and optical properties of the films was experimentally studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), and photoluminescence (PL) measurements. XRD analysis confirmed the formation of crystalline CCTS with a stannite structure and a preferential orientation along the (112) plane. SEM observations revealed rough and non-uniform surfaces accompanied by an increase in grain size with increasing substrate temperature. Room-temperature PL measurements indicated a band-gap energy of approximately 1.3 eV, suitable for photovoltaic applications, and confirmed the presence of secondary phases in the p-type stannite CCTS films. Despite the promising photovoltaic properties of CCTS, numerical studies on CCTS-based solar cells remain scarce in the literature. In this context, a numerical study of the CCTS-based solar structure grown on glass was also performed using SCAPS-1D, showing good agreement with experimental photovoltaic results and validating the simulation model. Replacing the glass substrate with silicon improved the device efficiency to 5.77%. Further optimization of the series and shunt resistances significantly enhanced the photovoltaic performance, achieving a power conversion efficiency of 16.77%, with FF = 52.94%, V_oc = 0.89 V and J_sc = 35.19 mA/cm². Full article

Riparian land use and land cover (LULC) exerts scale- and season-dependent controls on surface water quality, yet its influence in regulated agricultural–urban rivers is poorly characterized. We combined seasonal t-tests, one-way ANOVA, and redundancy analysis (RDA) at three riparian buffer scales (500, 1000, and 2000 m) to examine discharge, dissolved oxygen (DO), temperature, turbidity, and pH at four USGS stations along the Kansas River mainstem (2019–2026). DO and temperature showed the strongest seasonal contrasts: DO was 3.1–3.7 mg/L higher in the dry season and temperature 13–15 °C higher in the wet season, a coupling central to aquatic habitat suitability. Turbidity rose significantly in the wet season, consistent with agricultural runoff and sediment mobilization, whereas discharge showed no significant seasonal difference at three of four stations, reflecting upstream reservoir regulation. Spatial ANOVA detected station-level differences only for wet-season DO ($F_{3,28}=4.91$, $p=0.007$), which was lowest at the downstream urbanized station. RDA linked agricultural cover to turbidity and urban cover to reduced wet-season DO, although permutation tests were non-significant ($p\ge 0.42$) at $n=4$ replicates. Seasonality and riparian LULC jointly shape water quality along this regulated river, and the 500 m buffer is the most spatially discriminating scale for land-cover assessment. Full article

Municipal sewage sludge contains considerable amounts of protein, making protein recovery a viable route for sludge valorization. In this work, sludge disintegration was achieved by cyclone cutting coupled with ozone oxidation, and the mixed liquor of foam standing liquid and supernatant was used as the feedstock for protein recovery via isoelectric point precipitation. Pretreatment tests showed that under 60 mg/L ozone concentration, 10 °C and 60 min, alkaline conditions enhanced sludge lysis; the mixed liquor suspended solids (MLSS) removal rate reached 87.65% at pH 9, and the protein concentration in the foam layer reached 1530.14 mg/L at pH 11, yielding a protein-rich feedstock suitable for subsequent extraction. In the isoelectric point precipitation stage, single-factor and L9(3⁴) orthogonal experiments were conducted to examine the effects of pH, temperature and centrifugal speed on extraction rate, and four ensemble learning algorithms (GBR, RF, XGBoost and CatBoost) were employed to build prediction models. The results showed that the factor influence order was pH > centrifugal speed > temperature, with pH being extremely significant (p < 0.01). Under leave-one-out cross-validation, the XGBoost model performed best (R² = 0.9243, MAE = 2.78%, RMSE = 3.52%). Response surface analysis determined the optimal parameters as pH 4.0, 5 °C and 3500 r/min, with both predicted and measured precipitation-stage extraction rates of 86.19%. Amino acid analysis indicated that essential amino acids accounted for 39.9% of the extracted protein, with good rehydration and foaming stability. Ensemble learning algorithms can reveal the multi-factor nonlinear coupling in isoelectric point precipitation, providing data support for process optimization of sludge protein recovery. Full article

Cells of higher organisms express numerous cell surface proteins, and their spectrum and level of expression are directly related to cells’ functions. The technology of mass cell selection based on the surface protein expression levels may be highly important both for basic research and cell therapy applications. We have previously developed a method of magnetic selection of cells differing in surface marker expression levels, which we term here MACS-MEL (Magnetic-Assisted Cell Selection by Marker Expression Levels). The method demonstrated its effectiveness in the artificial model system, namely retrovirally transduced NIH 3T3 cells. However, whether it was also applicable to complex natural cell populations remained unclear. In the current study, we validated the MACS-MEL approach by separating mouse bone marrow (BM) cells into fractions according to the expression of pan-hematopoietic marker CD45. In the basic protocol, two-stage fractionation of CD45⁺ cells from BM was performed using selection of cells consecutively with 2 μL and 8 μL of anti-CD45 magnetic beads, resulting in isolation of CD45^high and CD45^int cell populations. To explore in full the potential of the method, the extended protocol was also tested, where a third selection stage with 30 μL of anti-CD45 beads was added. The isolated cell fractions were analyzed by flow cytometry for CD45 expression, as well for CD11b, Gr-1, CD117, CD115 and CD19 markers, while their in vitro progenitor function was assessed by quantitating colony-forming units (CFUs) in methyl cellulose. The results of analysis demonstrate that the isolated cell fractions significantly differed both in their surface phenotypes and CFU potential. In particular, cell fractions with progressively reduced CD45 expression were characterized by decreasing expression of myeloid differentiation markers CD11b and Gr-1, as well as B-lymphoid marker CD19. The expression of stem/progenitor cell marker CD117, on the contrary, significantly increased. The CFU frequency also strongly correlated with decrease in CD45 expression, while the differentiation potential of CFUs differed substantially in various cell fractions. In general, our results demonstrate that less differentiated hematopoietic cells in mouse BM studied using in vitro tests are characterized by lower CD45 expression levels, in full accordance with data obtained in human system. Successful validation of the MACS-MEL in a BM system, characterized by existence of multiple cell types and high phenotypic and functional heterogeneity, demonstrated the effectiveness, simplicity and affordability of this method. The MACS-MEL approach can be applied for mass selection of cells based on differential marker expression and may yield cell subsets suitable for advanced cell therapy applications. Full article

Electrochemical sensor arrays that perform simultaneous multi-technique (SMT) measurements within a shared electrolyte are essential for continuous, multi-analyte detection in microfluidic platforms for environmental and healthcare monitoring. This review examines the potentiostat architectures and electrode geometries relevant to SMT operation. Traditional single channel and multi-electrode potentiostat topologies are surveyed, and their suitability for multi-cell shared-electrolyte environments is evaluated. Additionally, crosstalk mechanisms in shared electrolytes are classified into chemical, electrical, and a newly identified category termed stability-based interference, which arises from conflicting feedback loops in conventional grounded working electrode instrumentation. A survey of existing multi-cell platforms reveals that most reported systems either avoid true SMT operation or address crosstalk primarily through electrode geometry without systematic evaluation of instrumentation effects. Based on this analysis, we introduce an instrumentation and electrode geometry co-design framework that provides a unified design pathway toward continuous multi-analyte microfluidic sensors for wearable and point-of-care applications. Full article

The increasing penetration of renewable energy has significantly intensified the demand for flexible operation of thermal power plants, making dynamic simulation an essential tool for understanding transient behaviors and developing advanced operational strategies for circulating fluidized bed (CFB) power plants. This review critically examines the existing dynamic modeling approaches for industrial-scale CFB power plants, with particular emphasis on their applicability to flexibility studies. Existing CFB flue-gas side models are systematically classified into three categories: 3D physics-based CFD models, behavioral/data-driven models, and semi-empirical mechanistic models. Their characteristics are critically compared in terms of spatial and temporal scales, empirical dependence, model generality, computational and implementation burden, and applicability to CFB flexibility studies. Dynamic modeling of the steam–water cycle is also reviewed, showing that it has reached a relatively mature stage owing to well-established thermo-hydraulic theories and standardized modeling platforms. The current research bottleneck is therefore identified as the dynamic coupling between the flue-gas side and the steam–water cycle for integrated CFB whole-plant simulation. Based on the comparative analysis, semi-empirical mechanistic models are identified as a particularly suitable framework for industrial-scale CFB flexibility studies requiring minute-to-hour transient simulation, physical interpretability, and whole-plant coupling. Finally, future research directions are discussed, highlighting how integrated dynamic models can support CFB flexibility-enhancement technologies and the development of new-generation coal-fired power plants. Full article

This study investigated the application of Covariant Hamiltonian Optimization for Motion Planning (CHOMP) in the MATLAB programming environment to an industrially relevant Universal Robots UR5e six-DOF manipulator. The parameters were set to be equal to those of the standard MoveIt2 CHOMP plugin, and the obstacle cost was computed directly in MATLAB using the Robotics System Toolbox’s forward kinematics function to obtain the end-effector position at each trajectory waypoint, which was then evaluated against a piecewise potential field defined over three spherical obstacles in the workspace. We executed five distinct picking task examples and one task over thirty trials, together with a sensitivity analysis over the weight parameter defining the optimization smoothness (i.e., weight/gamma). The mixed empirical results exposed major drawbacks of vanilla CHOMP under our parameter configuration. We achieved a collision-free result for only two of the five tasks, T-03 and T-05, with T-03 converging quickly in five iterations (0.16 s) and T-05 requiring 156 iterations and hitting the planning timeout limit of 10 s. Three tasks did not yield any collision-free result under the 10 s time limit. One of those three tasks, T-01, when running 30 random trial simulations after adding a tiny amount of noise to the start/end poses, yielded 0%, so all trials timed out on its planning 200-iteration limit with an invalid collision result. We analyzed the movement profile (position, velocity, and acceleration over time) of the trajectories generated during the experiments. Several examples exceed the UR5e velocity limit (180 deg/s) and the UR5e acceleration limit (400 deg/s²) by an order of magnitude, and peak values on T-02 reached up to 4731.92 deg/s². With these chosen parameters, basic CHOMP is not industrially suitable for the UR5e robot or for the implementation of the empirical evaluation of CHOMP discussed in this paper. We also identified the modes of failure of basic CHOMP under these parameters and discuss relevant changes. Full article

The development of bioactive hybrid coatings for biomedical implants requires materials exhibiting suitable thermal stability, bioactivity, and biocompatibility. In this study, hybrid organic–inorganic sol–gel coatings based on silica (SiO₂) and polyethylene glycol (PEG, 24 wt%) were functionalized with different concentrations of caffeic acid (CafA 5, 10, and 15 wt%) and deposited onto AISI 304 and AISI 316 stainless steel substrates by dip-coating without surface pre-treatment. The proposed approach enabled the formation of homogeneous hybrid coatings on untreated stainless steel substrates through a simple and scalable deposition process. A thermal analysis demonstrated the stability of the hybrid network and the effective integration of the organic and inorganic phases. Bioactivity was evaluated by in vitro immersion in simulated body fluid (SBF), while SEM observations revealed the formation of mineral deposits on the coating surface, and an EDX analysis confirmed the presence of calcium and phosphorus within the deposited layer. The formation of crystalline hydroxyapatite (HA) was subsequently confirmed by X-ray diffraction (XRD), confirming that all investigated formulations retained their ability to induce apatite formation after SBF immersion. In addition, in vitro biocompatibility assays confirmed that the developed materials exhibited concentration-dependent cytocompatibility, with the cellular response being influenced by the amount of incorporated CafA. Overall, the results demonstrate that the proposed hybrid materials combine thermal stability, bioactivity, and cytocompatibility, highlighting their potential as bioactive coatings for biomedical applications. Full article

Increasing the accuracy of age-at-death estimation using two skeletal-characteristic stages can enhance confidence in biological identification using forensic science. Transition analysis and the inverse prediction method with a Bayesian approach was proposed in this study to estimate age from skeletal characteristics measured as binary variables. The Bayesian approach with adaptive rejection sampling was employed to derive the posterior distributions of the transition model parameters and the age classification threshold in order to reverse the age-at-death estimation from a binary predictor. The posterior odds ratio was proposed to assess the value of observed evidence for the age estimation. Subsequently, the efficiency of our proposed method, measured by the percentage of correct classification, was evaluated by Monte Carlo simulation and compared with the Maximum Likelihood Estimation with the inverse prediction method. The simulation results supported the advantages of our proposed method, especially when using small sample sizes. In an application involving chest X-ray images with two chest plate ossification stages, the results showed that our method could identify suitable features of the chest plate, providing good age-prediction performance with a high percentage of accuracy. Full article

We introduce a new class of split inverse problems, termed the Split Pseudomonotone Equilibrium Problem with Multiple Output Sets, which generalizes classical equilibrium formulations to accommodate multiple decision outputs and pseudomonotonicity. To solve this problem, we propose a novel iterative method that employs an inertial technique and self-adaptive step sizes to improve the convergence properties. Under suitable conditions, we establish the convergence of the method and provide a detailed theoretical analysis. The proposed framework is then applied to medical diagnosis classification tasks, considering diabetes, chronic kidney disease, heart disease, and breast cancer datasets where decision-making involves heterogeneous data. Numerical tests reveal the algorithm’s strength and effectiveness, underscoring its potential for wider use in optimization-based classification and decision-making systems. Full article

The rapid development of the low-altitude economy is reshaping tourism activities, infrastructure provision, and landscape resource use, yet national-scale research on low-altitude tourism bases remains limited. Using data on 1247 bases in China, this study applies average nearest-neighbor analysis, kernel density estimation, and spatial inequality measures to characterize multi-scale patterns. The study further employs an optimal parameters-based geographical detector within a geographical nature framework to identify influencing factors and interactions. The results reveal significant clustering and regional inequality, with a pronounced east–west divide along the Heihe–Tengchong Line. A diamond-shaped core bounded by Beijing, Hangzhou, Chengdu, and Sanya, together with its 200 km buffer zone, contains 89.17% of all bases. Domestic tourism revenue, the number of low-altitude industry enterprises, general aviation airports, national tourist resorts, and domestic tourist arrivals constitute the leading factors, although the dominant factor combinations vary across base types. Factor interactions are dominated by two-factor and nonlinear enhancement. The three natures form a coupled pathway: first nature provides environmental suitability, second nature transforms resource potential into marketable tourism products, and third nature regulates implementation. General aviation infrastructure acts as an operational interface linking environmental conditions, tourism demand, industrial support, and policy arrangements. The findings provide a basis for differentiated regional zoning and type-specific facility planning, thereby informing the sustainable development of low-altitude tourism. Full article

Accurate characterization of local ship motion remains challenging because conventional AIS trajectory analysis primarily relies on global or averaged motion descriptors that overlook short-term navigation dynamics. This research introduces a fractal micromovement representation framework that identifies localized motion episodes and transforms them into symbolic descriptors suitable for structural trajectory analysis. The framework combines sliding-window Higuchi fractal analysis, quantile-based episode detection, temporal aggregation, and symbolic encoding of the resulting micromovement episodes. To formalize local motion dynamics, each micro-episode is transformed into a symbolic fractal code that reflects the topological structure of the geometric complexity of the vessel’s trajectory. Application of the proposed framework to experimental trajectory data demonstrates its ability to localize intervals of elevated trajectory complexity and transform them into compact symbolic representations suitable for structural comparison. Quantitative sensitivity analysis and comparison with an independent kinematic reference further characterize the stability and operational correspondence of the fractal representation. The framework is intended for retrospective trajectory analysis, while behavioral recognition, anomaly detection, forecasting, and integration with higher-precision navigation data are considered prospective applications. Full article