Search Results (161)

The Threshold Pressure Gradient (TPG) phenomenon exerts a profound influence on fluid flow dynamics in heavy oil reservoirs. However, the discrepancies between the True Threshold Pressure Gradient (TTPG) and Pseudo-Threshold Pressure Gradient (PTPG) significantly impede accurate residual oil evaluation and rational field development planning. This study proposes a dual-exponential conversion model that effectively bridges the discrepancy between TTPG and PTPG, achieving an average deviation of 12.77–17.89% between calculated and measured TTPG values. Nonlinear seepage simulations demonstrate that TTPG induces distinct flow barrier effects, driving residual oil accumulation within low-permeability interlayers and the formation of well-defined “dead oil zones.” In contrast, the linear approximation inherent in PTPG overestimates flow initiation resistance, resulting in a 47% reduction in recovery efficiency and widespread residual oil enrichment. By developing a TTPG–PTPG conversion model and incorporating genuine nonlinear seepage characteristics into simulations, this study effectively mitigates the systematic errors arising from the linear PTPG assumption, thereby providing a scientific basis for accurately predicting residual oil distribution and enhancing oil recovery efficiency. Full article

To elucidate the photosynthetic physiological mechanisms influencing alfalfa (Medicago sativa L.) yield and quality under varying planting densities, the cultivar ‘Zhongmu No.1’ was used as experimental material. The effects of different row spacing (R1, R2, R3) and seeding rate (S1, S2, S3, S4, S5) combinations on chlorophyll content (ChlM), nitrogen flavonol index (NFI), chlorophyll fluorescence parameters, forage quality, and hay yield were systematically analyzed. Results showed that alfalfa under R1S3 treatment achieved peak values for ChIM, NFI, EE, and hay yield, whereas R1S4 treatment yielded the highest Fv/Fm and CP content. Redundancy analysis further indicated that yield was most strongly associated with ChlM, NFI, Y (II), and qP. Y (II), and qP significantly influenced alfalfa forage quality, exerting negative effects on ADF and NDF, while demonstrating positive effects on CP and EE. In conclusion, narrow row spacing (15 cm) with moderate seeding rates (22.5–30 kg·hm⁻²) optimizes photosynthetic performance while concurrently enhancing both productivity and forage quality in alfalfa cultivated, establishing a theoretical foundation for photosynthetic regulation in high-quality and high-yield alfalfa cultivation. Full article

Landslides are a common geological hazard in mountainous areas, causing significant damage to ecosystems and production activities. Near-natural ecological restoration is considered an effective strategy for post-landslide recovery. To investigate the impact of near-natural restoration strategies on the recovery of plant communities and soil in landslide-affected areas, we selected landslide plots in Lantian County at 1, 6, and 11 years post-landslide as study sites, surveyed plots undergoing near-natural restoration and adjacent undisturbed control plots (CK), and collected and analyzed data on plant communities and soil properties. The results indicate that vegetation succession followed a path from “human intervention to natural competition”: species richness peaked at 1 year post-landslide (D_m = 4.2). By 11 years, dominant species prevailed, with tree species decreasing to 4.1 ± 0.3, while herbaceous diversity increased by 200% (from 4 to 12 species). Soil recovery showed significant temporal effects: total nitrogen (TN) and dehydrogenase activity (DHA) exhibited the greatest increases after 1 year post-landslide (132% and 232%, respectively), and by 11 years, the available nitrogen (AN) in restored plots recovered to 98% of the CK levels. Correlations between plant and soil characteristics strengthened over time: at 1 year, only 6–9 pairs showed significant correlations (p < 0.05), increasing to 21–23 pairs at 11 years. Near-natural restoration drives system recovery through the “selection of native species via competition and activation of microbial functional groups”. The 6–11-year period post-landslide is a critical window for structural optimization, and we recommend phased dynamic regulation to balance biodiversity and ecological functions. Full article

Targeted degradation technologies, primarily referring to targeted protein degradation, have emerged as promising drug discovery strategies. In contrast to traditional “occupancy-driven” inhibition approaches, these technologies ingeniously leverage the cell’s endogenous degradation mechanisms to achieve specific elimination of disease-causing targets. Autophagy, a highly conserved cellular clearance pathway, possesses broad substrate recognition capabilities, enabling degradation of not only individual proteins but also protein aggregates, damaged organelles, and invading pathogens. Given these characteristics, researchers are actively exploring the application of autophagy mechanisms in targeted degradation technologies. Herein, we summarize recent advances in autophagy-dependent degradation approaches, including autophagosome tethering compounds (ATTEC), autophagy-targeting chimeras (AUTAC), autophagy-targeting Chimera (AUTOTAC), chaperone-mediated autophagy (CMA)-based methods, nanotechnology-based strategies, and the newly introduced autophagy-induced antibody (AUTAB) technique, highlighting their mechanisms, advantages, and potential applications in treating tumors, neurodegenerative diseases, and other challenging conditions. Full article

2,3,5-Trimethylpyrazine (TMP) is an alkyl pyrazine with broad application prospects in the fields of food additives and medicine. L-threonine-3-dehydrogenase (TDH) is a key enzyme in the biosynthesis pathway of TMP. To explore the efficient and environmentally friendly production method of TMP, we constructed recombinant strains overexpressing the BlTDH gene and its mutant BlTDH (N157A) using Bacillus licheniformis YC7. The TMP yield of recombinant strains with pHT01-BlTDH (N157A) reached 15.35 ± 1.51 mg/L, which was significantly higher than that of strains with pHT01-BlTDH (9.86 ± 1.24 mg/L) and strains with vector pHT01 (2.35 ± 0.58 mg/L). To further increase the TMP yield of strain YC7/pHT01-BlTDH (N157A), the fermentation process was optimized by single-factor experiments, and the response surface test was conducted using the Box–Behnken design. The results revealed that the substrate ratio, IPTG concentration and fermentation time had significant effects on the yield of TMP, and the degree of influence was substrate ratio > fermentation time > IPTG concentration. The optimization results of response surface indicated that the optimal fermentation conditions were as follows: substrate ratio of 1:2, IPTG concentration of 1.0 mM, and fermentation time of 4 d. Under these conditions, the TMP yield reached 44.52 ± 0.21 mg/L, which was around 0.005 mg/L different from the predicted value (45.515 mg/L), and increased by 29.17 mg/L compared with the initial condition. The optimization of fermentation conditions significantly increased the yield of TMP produced by recombinant strains, which provided a theoretical basis and strain resources for industrial production of TMP. Full article

On the one hand, the dynamic characteristics of gas-heat flow in the IES (integrated energy system) are important in achieving multi-energy coupling, improving system scheduling flexibility, and increasing energy regulation potential. On the other hand, the uncertainty of new energy causes fluctuations in the interactive power between the upper TG (transmission grid) and the lower IES, and its coupling characteristics weaken the autonomy of each system. Therefore, this paper proposes a robust two-stage scheduling strategy for TG-IES, considering gas-heat dynamic characteristics. Firstly, according to the characteristic equation of gas-heat energy flow, the dynamic model of the gas-heat network is established and applied to system scheduling. Secondly, aiming at the uncertainty problem, a TG-IES two-stage robust model is constructed, and the ATC (analytical target cascading) method and the C&CG (column and constraint generation) algorithm are combined to realize the distributed solution of the non-convex coupling model. Finally, the effectiveness of the model and strategy is verified by using the IEEE-39 system as TG and the IEEE39 Grid-20 Gas Grid-6 Heat Network system as IES. The simulation results show that using a two-stage robust model and considering the dynamic characteristics of gas and heat can effectively reduce system operating costs and improve the environmental friendliness of system scheduling. Full article

Long non-coding RNAs (lncRNAs) could alter the tumor immune microenvironment and regulate the expression of immune checkpoints (ICPs) by regulating target genes in tumors. However, only a few lncRNAs have precise functions in immunity and potential for predicting ICP inhibitors (ICI) response. Here, we developed a computational multi-step framework that leverages interaction network-based analysis to identify cancer- and immune-context ICP-related lncRNAs (NetLnc). Based on bulk and single-cell RNA sequencing data, these lncRNAs were significantly correlated with immune cell infiltration and immune expression signature. Specific hub ICP-related lncRNAs such as BANCR, MIAT, and SNHG15 could predict three- and five-year prognosis of melanoma in independent datasets. We also validated that some NetLnc-based predictions could better effectively predict ICI response compared to single molecules using three kinds of machine learning algorithms following independent datasets. Taken together, this study presents the use of a network-based framework to efficiently select ICP-related lncRNAs, which contributes to a comprehensive understanding of lncRNA functions and accelerates the discovery of lncRNA-based biomarkers in ICI treatment. Full article

This paper proposes a feature-driven topology reconfiguration framework to enhance the resilience of Industrial Internet of Things (IIoT) systems against heterogeneous attacks. By dynamically partitioning IIoT into subnetworks based on localized attack features and reconstructing each subnetwork with tailored topologies, our framework significantly improves connectivity and communication efficiency. Evaluations on a real-world dataset (Tech-Routers-RF) characterizing IIoT topologies with 2113 nodes show that under diverse attack scenarios, connectivity and communication efficiency improve by more than 70% and 50%, respectively. Leveraging information entropy to quantify the trade-off between structural diversity and connection predictability, our work bridges adaptive network design with real-world attack dynamics, offering a scalable solution for securing large-scale IIoT deployments. Full article

Designing bifunctional catalysts for efficient hydroisomerization of phenanthrene to alkyl-adamantane is a great challenge for producing high-density fuels. Herein, a bifunctional Pt catalyst was fabricated by developing hierarchical H-MSY-T zeolites with an NOA-co strategy. The influence of different mesopore template agents on the hierarchical structure of H-MSY-T zeolite was investigated. Effective regulation of pore structure and acid distribution of zeolites was achieved by adjusting the templating agents. The block copolymer P123 promoted the formation of mesoporous structures via self-assembly with a large mesopore centered at 8 nm. Large mesoporous structure and suitable distribution of Bronsted acid boosted the hydroisomerization of phenanthrene. The highest alkyl-adamantane yield of 45.9 wt% was achieved on the Pt/MSY-P1 catalyst and a reaction network of hydroisomerization was proposed. This work provides guidance to design highly selective bifunctional catalysts for the one-step hydroconversion of tricyclic aromatic hydrocarbons into high-density fuels. Full article

The pyrolysis carbon black (CBp) from waste tires contains zinc, iron, and other metal elements, which have high recycling value. This study proposes a simple method of recovering zinc and iron from waste tire-derived CBp to synthesize hydrotalcite-type adsorbents for the treatment of anodic dye wastewater. Firstly, zinc-aluminum hydrotalcite (LDH) and zinc-iron aluminum hydrotalcite (FeLDH) were obtained by leaching the zinc and iron ions from CBp with an acid solution. As compared with LDH, FeLDH shows increased laminate metal ion arrangement density and layer spacing. By calcining the LDH and FeLDH at 500 °C, zinc aluminum oxides (LDO) and zinc iron aluminum oxides (FeLDO) were then prepared and applied for the adsorption of dye methyl orange (MO). The results demonstrate that the maximum adsorption capacity of LDO and FeLDO are 304.9 and 609.8 mg g⁻¹ at pH of 4.0, respectively. The adsorption processes of both LDO and FeLDO are consistent with the Langmuir adsorption isotherm and the proposed second-order kinetic model. The adsorption regeneration performance and adsorption mechanism of LDO and FeLDO were also investigated in detail. Regeneration experiments show that after three cycles, the removal rate of MO by LDO remains above 80%, while that of FeLDO only remains around 64% in the first cycle after regeneration. This work would provide a new pathway to realize the high-value metal recycling of waste tire-derived CBp and solve the contamination of dye wastewater. Full article

In response to the growing threats posed by frequent wildfires to ecological environments and human safety, this study presents the development of a lightweight, spaceborne, multispectral, uncooled infrared remote sensing camera specifically designed for wildfire monitoring. To address the low wildfire detection sensitivity of VOx uncooled infrared instruments, a multi-point precision temperature control technique and a spatiotemporal stacking method are implemented. Furthermore, a compact design and assembly approach endows the camera with low weight, small size, and low power consumption, making it highly suitable for satellite deployment. The test results demonstrate that the camera weighs less than 1.5 kg, consumes under 1.5 W of power, and achieves a sensitivity below 0.2 K, comparable to current spaceborne cooled infrared remote sensing cameras. The remote sensing camera has successfully detected various wildfires and thermal events. This study provides an innovative instrument for remote sensing wildfire monitoring. Full article

The rational design of high-performance catalysts for the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) is essential for the development of clean and renewable energy technologies, particularly in fuel cells and metal-air batteries. Two-dimensional (2D) covalent organic frameworks (COFs) possess numerous hollow sites, which contribute to the stable anchoring of transition metal (TM) atoms and become promising supports for single atom catalysts (SACs). Herein, the OER and ORR catalytic performance of a series of SACs based on TQBQ-COFs were systematically investigated through density functional theory (DFT) calculations, with particular emphasis on the role of the coordination environment in modulating catalytic activity. The results reveal that Rh/TQBQ exhibits the most effective OER catalytic performance, with an overpotential of 0.34 V, while Au/TQBQ demonstrates superior ORR catalytic performance with an overpotential of 0.50 V. A critical mechanistic insight lies in the distinct role of boundary oxygen atoms in TQBQ, which perturb the adsorption energetics of reaction intermediates, thereby circumventing conventional scaling relationships governing OER and ORR pathways. Furthermore, we established the adsorption energy of TM atoms (Ead) as a robust descriptor for predicting catalytic activity, enabling a streamlined screening strategy for SAC design. This study emphasizes the significance of the coordination environment in determining the performance of catalysts and offers a new perspective on the design of novel and effective OER/ORR COFs-based SACs. Full article

With the rapid acceleration of global urbanization, the impact of land use/cover change (LUCC) on the environment and ecosystems has become increasingly prominent, particularly in terms of air quality, which has emerged as a significant issue demanding attention. Focusing on the coastal city of Lianyungang, the spatiotemporal dynamics of land use/cover changes were explored by utilizing land use dynamic degree and land use transfer matrix methods. By integrating a comprehensive historical dataset, multiple linear regression analysis was used to analyze the driving mechanism of land use conversion and to explore the effect of LUCC on the variations in PM₁₀ levels. The results showed an overall decreasing trend in PM₁₀ levels over the 24-year period from 2000 to 2023, with distinct seasonal fluctuations, showing higher concentrations in winter and lower concentrations in summer. The impact of land use on PM₁₀ variations can be categorized into three stages: initial (2000–2006), transitional (2007–2013), and deepening development (2014–2022). Notably, during the third stage, with the involvement of policy interventions and industrial upgrading, a strong negative correlation of −0.97 was identified between urban land expansion and the decrease in PM₁₀ levels. The correlation between LUCC and PM₁₀ levels was insignificant over shorter periods, but the analysis of data from 2000 to 2022 revealed a significant positive correlation of 0.77, emphasizing the importance of adopting a long-term perspective to accurately assess the impact of LUCC on air quality. This research provides valuable insights into the implications of LUCC on air quality during urbanization and establishes a scientific foundation for developing air pollution management strategies in Lianyungang and similar regions. Full article

Ecosystem water use efficiency (WUE) is a key indicator of the coupling between carbon and water cycles. With the increasing frequency of extreme climate events, WUE may also show trends of extremization. Understanding the dominant drivers behind extreme WUE variations is crucial for assessing the impact of climate variability on WUE. We investigate the main drivers and regional sensitivity of extreme WUE variations across seven geographical regions in China. The results reveal that extreme WUE variations are collectively influenced by gross primary productivity (GPP) and evapotranspiration (ET) (43.72%). GPP controls extreme WUE variations in 36.00% of the areas, while ET controls 20.17%. Furthermore, as the climate shifts from arid to humid regions, the area where GPP dominates extreme WUE variations increases, while the area dominated by ET decreases, suggesting a relationship with precipitation. Ridge regression analysis shows that vapor pressure deficit (VPD) is the primary driver of interannual WUE variation in China, with an average relative contribution of 38.64% and an absolute contribution of 0.025 gC·m⁻²·mm⁻¹·a⁻¹. We studied the changes in WUE and its driving mechanisms during extreme disaster events, providing a perspective focused on extreme conditions. In the future, these results may help regulate the carbon–water cycle in different regions, such as by guiding vegetation planting and land use planning based on the spatial characteristics of the dominant factors influencing extreme WUE variations to improve vegetation WUE. Full article

This paper addresses the bipartite consensus problem of signed directed multi-agent systems (MASs) subject to actuator faults. This problem plays a crucial role in various real-world systems where agents exhibit both cooperative and competitive interactions, such as autonomous vehicle fleets, smart grids, and robotic networks. To address this, unlike most existing works, an intermediate observer is designed using newly introduced intermediate variables, enabling simultaneous estimation of both agent states and faults. Furthermore, a distributed adaptive observer is developed to help followers estimate the leader’s state, overcoming limitations of prior bounded-input assumptions. Finally, simulation results demonstrate the method’s effectiveness, showing that consensus tracking errors converge to zero under under various fault scenarios and input uncertainties. Full article