Search Results (34,316)

Due to the susceptibility of LiDAR echo signals to various noise interferences, which severely affect their detection quality and accuracy, this paper proposes a joint denoising method combining Variational Mode Decomposition (VMD), Crested Porcupine Optimizer (CPO), and Improved Wavelet Thresholding (IWT), named VMD-CPO-IWT. The parameter-adaptive CPO optimization algorithm is employed to optimize the key parameters of VMD (decomposition level k, quadratic penalty factor α), effectively solving the challenge of determining the optimal parameter combination in the VMD algorithm. Based on the probability density function (PDF), the Wasserstein distance is used as a similarity metric to screen intrinsic mode functions. Subsequently, the IWT is applied to obtain the optimal wavelet threshold, which compensates for the shortcomings of traditional threshold methods while further suppressing both low-frequency and high-frequency noise in the signal, ultimately yielding the denoising result. Experimental results demonstrate that for both simulated signals and actual LiDAR echo signals, the VMD-CPO-IWT method outperforms Neighcoeff-db4 wavelet denoising (WT-db4), EMD combined with detrended fluctuation analysis denoising (EMD-DFA), and VMD combined with Whale Optimization Algorithm (VMD-WOA) in terms of improving the Signal-to-Noise Ratio (SNR) and reducing the Root Mean Square Error (RMSE). For the actual LiDAR echo signal at a detection range of 25 m, the SNR is improved by 13.64 dB, and the RMSE is reduced by 62.6%. This method provides an efficient and practical solution for denoising LiDAR echo signals. Full article

In this study, a carbon felt (CF)-based ternary composite anode was developed through the decoration of nickel cobaltite (NiCo₂O₄) nano-needles and subsequent in situ electropolymerization of polypyrrole (PPy). The structural and electrochemical properties of the modified electrodes were systematically characterized. The CF/NiCo₂O₄/PPy anode demonstrated significantly enhanced bioelectrochemical activity, achieving a peak current density of 96.0 A/m² and a steady-state current density of 28.9 A/m², which were 4.85 and 5.90 times higher than those of bare carbon felt, respectively. Geobacteriaceae is a type of electrogenic bacteria. It was hardly detected on the bare CF substrate; however, in the ternary CF/NiCo2O4/PPy electrode, the relative abundance of Geobacteriaceae significantly increased to 43%. Moreover, the composite electrode exhibited superior charge storage performance, with a total charge (Q_t) of 32,509.0 C/m² and a stored charge (Q_s) of 3609.0 C/m² measured under a 1000 s charging/discharging period. The MFC configured with the CF/NiCo₂O₄/PPy anode reached a maximum power density of 1901.25 mW/m² at an external resistance of 200 Ω, nearly six times that of the unmodified CF-based MFC. These improvements are attributed to the synergistic interaction between the pseudocapacitive NiCo₂O₄ and conductive PPy, which collectively facilitate electron transfer, promote microbial colonization, and enhance interfacial redox kinetics. This work provides an effective strategy for designing high-performance MFC electrodes with dual functionality in energy storage and power delivery. Full article

As a novel class of thin films, thin-film metallic glasses (TFMGs) hold broad application prospects in biomedicine, electronic components, etc. In this study, CuZr TFMGs were deposited at room temperature using a medium-frequency magnetron sputtering (MFMS) technique. The effects of bias voltage on the microstructure and properties of the films were systematically investigated. The results indicate that the CuZr system exhibits excellent glass-forming ability (GFA), with films possessing a smooth surface. As bias voltage increases, cross-sectional morphology transitions from a glassy morphology to a dimple-like structure. The high bias voltage induces reduced dimple size and significantly increased density. At a bias voltage of −50 V, the hardness of CuZr film reaches a maximum of 9.6 GPa. This hardness is approximately five times and twice that of pure Cu and Zr films, respectively. Compared with Zr film, CuZr TFMGs exhibit a significantly reduced friction coefficient while maintaining a low wear rate. All CuZr films demonstrate excellent electrical conductivity and hydrophobicity, providing the basis for future potential applications. Full article

A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis incorporating ligand-receptor docking alignment and molecular dynamic (MD) simulations was conducted to elucidate the potent inhibitory effects of a series of benzamide derivatives on histone deacetylase 1 (HDAC1). A comparison between ligand-based (LB) and receptor-based (RB) 3D-QSAR models using molecular docking alignment produced statistically significant results. Steric and electrostatic contour maps provided insights into the interactions surrounding the benzamide ring, revealing that an increase in electron density enhances inhibitory activity. Furthermore, MD simulations were employed to investigate protein-ligand interactions in greater detail, yielding outcomes consistent with those from 3D-QSAR and molecular docking studies. This integrated approach of molecular docking, 3D-QSAR, and energy decomposition analysis derived from MD simulations, provides a valuable framework for the rational design of more potent HDAC1 inhibitors, facilitating the synthesis of highly effective anti-tumor compounds based on benzamide scaffolds. Full article

To address low nitrogen use efficiency (NUE) derived from excessive fertilization in cotton production in the Yellow River Basin, a field study was conducted to evaluate the effects of two planting densities and six nitrogen (N) rate levels. Key results show that a N rate of 225 kg ha⁻¹ optimized root length density and root biomass density. High planting density (105,000 plants ha⁻¹) improved the population-level root traits, photosynthetic radiation interception, and boll number per unit area, though it reduced individual plant root development. Total dry matter peaked at 225 kg ha⁻¹ N, and density increased reproductive dry matter by 7.5–11.9%. Higher N rates reduced reproductive partitioning and root–shoot ratio. While the maximum seed cotton yield (SCY) was 225 kg ha⁻¹, near-maximum yield was achieved at 150 kg ha⁻¹. NUE declined with increasing N, but densification improved agronomic NUE and partial factor productivity by 1.5–6.6% and 3.3–39.3%, respectively. Under the “densification with N reduction” mode, combining a planting density of 105,000 plants·ha⁻¹ with an N rate of 150 kg·ha⁻¹ achieved conventional yield. At the same density, an N rate of 225 kg·ha⁻¹ not only enabled high yield and maintained relatively high NUE but also showed better adaptability to the simplified cultivation mode in Yellow River Basin cotton-growing regions. Full article

Source water reservoirs in the lower reaches of the Yangtze River are increasingly threatened by algal contamination, driven by fluctuations in upstream water quality. To ensure stable reservoir operation and protect downstream drinking water sources, physical enclosures are widely used. However, most algal pollution in reservoirs consists of microalgae (diameters < 100 μm), and conventional algae barriers are effective primarily against visible algal blooms but perform poorly against microscopic algal clusters. To address this limitation, we developed a composite microfiltration physical enclosure system by integrating a microfiltration membrane, supported by a mechanical layer, onto physical enclosures. The algal removal performance of this system was evaluated from lab-scale tests to field-scale applications. Results demonstrated that the composite membrane exhibited excellent interception efficiency against algal aggregates, with algae density in the filtered water reduced by over 80%. The composite enclosure effectively filters multiple algae species, significantly reducing the risk of algae entering downstream water treatment plants, thereby alleviating the burden of traditional processes and reducing operating costs. Full article

This paper investigates the estimation of the stress–strength reliability parameter $\rho =P(X\le Y)$, where stress (X) and strength $\left(Y\right)$ are independently modeled by geometric distributions. Objective Bayesian approaches are employed by developing Jeffreys, reference, and probability-matching priors for $\rho$, and their effects on the resulting Bayes estimates are examined. Posterior inference is carried out using the random-walk Metropolis–Hastings algorithm. The performance of the proposed Bayesian estimators is assessed through extensive Monte Carlo simulations based on average estimates, root mean squared errors, and frequentist coverage probabilities of the highest posterior density credible intervals. Furthermore, the applicability of the methodology is demonstrated using two real data sets. Full article

The pressure arch effect limits the influence range of excavation on the surrounding rock, reduces the geological pressure on underground structures, and serves as an important indicator for evaluating the stability of underground engineering. By accounting for the energy transfer process in surrounding rock during the tunnel-induced pressure arch formation, this paper proposes a novel approach for determining the range of the pressure arch around tunnels—the energy density difference (EDD) method. Numerical analysis is conducted to evaluate the effects of tunnel span, internal friction angle, and lateral pressure coefficient on post-excavation energy density fields and pressure arch zones in tunnels. Comparative studies with three existing approaches confirm the EDD method’s efficacy in identifying the arch zones of tunnel-surrounding rock. Critically, the proposed approach addresses the controversy regarding the determination of the deviation degree of principal stress vectors and provides a physically meaningful interpretation of the formation and evolution mechanisms of pressure arches. Full article

The main objective of the current work is to evaluate the effect of adding biochar obtained by pyrolysis of a mixture of greenhouse waste to agricultural soil, measuring its effectiveness as an amendment. A mixture of broccoli, zucchini, and tomato plant residues was pyrolyzed in a lab-scale reactor at 450 °C, obtaining a biochar yield of 35.6%. No carrier gas was used in the process. A thorough characterization of the biochar obtained was performed, including elemental and proximal analysis, density, pH, electrical conductivity, cation exchange capacity, surface area, and metal content. Since the raw material had a high percentage of ash (approximately 20%), the resulting biochar contained around 50% inorganic matter, with potassium and calcium being the major metals detected (10–11%). This biochar had a 29% fixed carbon content, a high heating value of 11.5 MJ kg⁻¹, a cation exchange capacity of 477 mmol kg⁻¹, and an electrical conductivity of 16 mS cm⁻¹.The biochar was mixed with greenhouse soil and fertilizer to form a substrate to grow bean seeds, the crop selected for the study. Different experiments were carried out, varying the biochar, fertilizer, and soil percentages. By adding 0.5% biochar to a substrate containing 1% fertilizer, the bean production was increased by 24.5%. It is worth noting that by adding only 0.5% biochar to soil, the bean production reached higher values than when adding 1% fertilizer. Biochar produced from the studied biomass improved the productivity of agricultural soils. The avoidance of selective collection by farmers as well as the non-use of carrier gas in the pyrolysis process made the implementation of the pyrolysis system in situ easier. Consequently, this research has great potential for practical application in modest agricultural areas. Full article

Exploring the interactions and coupling effects in the Population–Land–Industry–Facility (PLIF) system can help maximize resource allocation and promote the synergistic development of systems. This study constructs an index system for the PLIF system in Hebei Province, employing coupling coordination degree and spatial autocorrelation methods to investigate the spatio-temporal evolution of the system’s coordination. Furthermore, grey relational analysis is employed to examine the key factors influencing the coordination degree of the system. The results show the following: (1) The development levels of each subsystem and the overall development level of the PLIF system in Hebei Province have generally increased, but the overall level remains relatively low. (2) The PLIF system in Hebei Province exhibits a pattern of “low in the north and high in the south, high in the east and low in the west”, with most counties in a barely coordinated state and a generally high degree of coupling. (3) The main factors affecting the coordinated development of the PLIF system include population density, the proportion of the tertiary industry, and the degree of non-agriculturalization of rural labor force. The research results of this paper provide a reference for promoting the coordinated development of population, land, industry, and facilities in Hebei Province and facilitating the sustainable development of the region. Full article

As a major energy producer and consumer, China has witnessed rapid growth in carbon emissions, which are closely linked to changes in regional climate and the environment. Water, energy, and food (W-E-F) are the three most critical components of human production and daily life, and achieving the coordinated development of these three resources and connecting them with climate change through the carbon emissions generated during their utilization processes has become a key issue for realizing regional ecological sustainable development. This study constructs a dynamic two-stage network slack-based measure-data envelopment analysis (SBM-DEA) model, which integrates the water–energy–food (W-E-F) system with the climate change process to evaluate China’s comprehensive ecological efficiency from 2011 to 2022, and adopts the Dagum Gini coefficient decomposition, kernel density estimation, hierarchical clustering, and geographical detector model to analyze provincial panel data, thereby assessing efficiency patterns, regional differences, and driving mechanisms. The novelty and contributions of this study can be summarized in three aspects. First, it establishes a unified framework that incorporates the W-E-F nexus and climate change into a dynamic network SBM-DEA model, enabling a more systematic assessment of ecological efficiency. Second, it uncovers that interregional overlap effects and policy-driven factors are the dominant sources of spatial and temporal disparities in ecological efficiency. Third, it further quantifies the interactive effects among key driving factors using Geodetector, thus offering practical insights for regional coordination and policy design. The results show that China’s national ecological efficiency is at a medium level. Southern China has consistently maintained a leading position, while provinces in northwest and southwest China have remained relatively backward; the efficiency of the water–energy–food integration stage is relatively high, whereas the efficiency of the climate change stage is medium and exhibits significant temporal fluctuations. Interregional differences are the main source of efficiency gaps; ecological quality, environmental protection efforts, and population size are identified as the primary driving factors, and their interaction effects have intensified spatial heterogeneity. In addition, sub-indicator analysis reveals that the efficiency related to total wastewater, air pollutant emissions, and agricultural pollution shows good synergy, while the efficiency associated with sudden environmental change events is highly volatile and has weak correlations with other undesirable outputs. These findings deepen the understanding of the water–energy–food-climate system and provide policy implications for strengthening ecological governance and regional coordination. Full article

In 3.5 wt% NaCl solution used to simulate seawater, the individual (self-corrosion) and coupled (galvanic) corrosion behaviors of TA22 titanium alloy and 304 stainless steel were systematically investigated at 25 °C, 35 °C, 45 °C and 55 °C. Post-corrosion surfaces were characterized by scanning electron microscopy (SEM), three-dimensional profilometry and X-ray photoelectron spectroscopy (XPS). The results demonstrated that elevating temperature decreased the compactness and protective quality of the passive film on both alloys, as indicated by increasing donor densities and positive shifts in flat-band potentials. Distinct pitting corrosion occurred on 304 SS above 45 °C. Upon galvanic coupling, the passive film on TA22 was modified in both structure and composition, exhibiting a decreased TiO₂ content and increased lower valence oxides (Ti₂O₃, TiO). The galvanic effect intensified with temperature, leading to progressively aggravated corrosion of 304 SS, characterized by increased pit density, diameter, and depth compared to its self-corrosion state. Full article

Ammonia borane (AB) is recognized as a highly promising material for hydrogen storage owing to its exceptional safety and high hydrogen density, enabling controllable hydrogen release at room temperature through catalytic hydrolysis. The development of efficient catalysts to accelerate this process remains a critical research challenge. In this work, carbon nanotube (CNT)-supported Co-MoO₃ nanoparticles were synthesized through reduction with sodium borohydride. The catalyst with a Co/MoO₃ molar ratio of 1.0:0.1 (denoted as Co₁Mo_0.1/CNTs) showed optimal performance in AB hydrolysis, with a turnover frequency (TOF) of 19.15 mol_H2 mol_cat⁻¹ min⁻¹ and an activation energy (E_a) of 26.41 kJ mol⁻¹. The superior performance of the Co₁Mo_0.1/CNTs catalyst can be ascribed to the efficient proton-transfer promotion by carboxylated carbon nanotubes and the synergistic catalytic effect between Co and Mo in the system. This study offers a viable pathway for constructing high-efficiency noble metal-free catalysts for hydrogen production from AB hydrolysis. Full article

The stochastic and undetermined nature of longwall coal mining results from the complex interaction between geological-mining and technical-organizational factors. This interaction causes variability in key parameters of the production process. This article presents three stochastic models developed on the basis of probability density functions, which describe selected process parameters. These mathematical functions serve as the foundation for effective stochastic models, enabling analysis of complex mining operations. The methodology employed in the study involves empirical data collection, statistical analysis, and stochastic simulation, carried out under both laboratory and field conditions. The results include empirical probability functions for output, delays, and crew-dependent productivity, offering insights into process variability and its impact on performance. Each method is characterized by its theoretical foundations, algorithmic structure, and application areas. The models have been validated through statistical tests and operational field data and can be applied as decision-support tools in both scientific research and industrial management. Given the extensive nature of the described methods, the article provides a comprehensive reference list for readers interested in further exploration and practical implementation in mining engineering. Full article

Background/Objectives: Dyslipidemia is one of the major problems of long-term management in people living with human immunodeficiency virus (HIV) (PLH) as a risk factor for cardiovascular diseases. Lipoprotein lipase (LPL) is anchored on the surface of the capillary endothelial cells and plays a pivotal role in triglyceride metabolism by catabolizing dietary chylomicrons and very low-density lipoprotein synthesized in the liver. However, the details of the mechanisms in the era of integrase strand transfer inhibitor-based antiretroviral therapy have not yet been clarified. Methods: This study was a cross-sectional, single-center, non-interventional study evaluating the underlying factors associated with dyslipidemia, insulin resistance or secretion, and changes in the body composition of PLH. Results: Among PLH (n = 48), lower LPL (<60.8 ng/mL) and older age independently predicted antilipemic drug (ALD) necessity. A comparison of ALD-naïve PLH (n = 33) and age- and sex-matched non-HIV controls (n = 33) showed that PLH were significantly associated with lower high-density lipoprotein cholesterol (HDL-C) and higher HOMA-β. LPL was also the independent predictor of HDL-C < 40 mg/dL in PLH (adjusted odds ratio = 0.901, p = 0.044). Furthermore, LPL < 65.3 ng/mL predicted HDL-C < 40 mg/dL with 100% sensitivity and 60.9% specificity. Low levels of HIV-RNA were detected in the high HOMA-β group. Conclusions: In Japanese individuals, compared to non-HIV controls, PLH has low HDL-C and LPL. The measurement of LPL may confer the risk assessment and decision-making with relevance to ALD in PLH. Additionally, the effectiveness of HIV antiviral therapy and glucose tolerance may interact with each other. Full article