Chang'an University

Chiral sulfoxaflor is widely present in environmental matrices; however, the health hazards of this neonicotinoid-like pollutant remain poorly understood. This study investigated the nicotinic acetylcholine receptor (nAChR)-mediated neurotoxicity of sulfoxaflor at the enantiomeric level and elucidated the distinct roles of its two chiral centers. Results showed that the toxic response of nAChR to sulfoxaflor exhibits significant enantioselectivity and the affinity of α7 nAChR with (R,S)-/(S,S)-sulfoxaflor (－35.34/－34.84 kcal mol−1) is higher than those of their antipodes (－22.08/－22.76 kcal mol−1). The conjugations of (R,S)-/(S,S)-sulfoxaflor in agonistic mode at the orthosteric site induces crucial residues (e.g., Trp-147, Tyr-186, Leu-117) to shift toward the binding position (RMSF: 0.0968 nm to 0.3959/0.3801 nm), which disturbs the intrinsic conformational flexibility of α7 nAChR (random coil: 18.16–23.65 %/22.15 %), prompting (R,S)-/(S,S)-sulfoxaflor to exhibit enhanced activated efficacy. Furthermore, chirality at the sulfur atom plays a key role in the electrostatic contribution (ΔGele) to be different (－23.55/－22.3/－11.39/－12.73 kcal mol−1), rendering sulfoxaflor a higher enantioselective neurotoxicant. This study could pave away for untangling the health hazards associated with sulfoxaflor and prompt the legislature to develop environmental regulations for pollutants containing multiple chiral centers.

The interplay between the surface nanostructure and the mechanical vibration in governing nanodroplet impact dynamics remains poorly understood in fluid mechanics. This study systematically investigates the impact dynamics of nanodroplets on vertically vibrating nanopillar-arrayed surfaces, revealing the amplitude-frequency decoupling phenomena on nanostructured surfaces through molecular dynamics simulation. Our results demonstrate an amplitude-dominated phase transition threshold mechanism in droplet bouncing dynamics. When the applied amplitude exceeds a dimensionless critical threshold A*crit, which is correlated with surface solid fraction ϕs, the complete rebound occurs independently of the frequency. Notably, in the subcritical amplitude regime (A* < Acrit*), droplet bouncing exhibits pronounced frequency dependence. Specifically, the droplet bouncing only occurs at the low- and high-frequency regimes, while the intermediate frequency would suppress rebound probability. Importantly, we present a theoretical derivation of the spreading time ts and the maximum spreading factor βmax via a vibration-coupled energy framework, resolving the competition among the vibrational energy, interfacial energy, and viscous dissipation. This work advances the fundamental understanding of the fluid–structure–vibration interactions and provides strategies for anti-icing, thermal management, and energy harvesting applications.

Natural polymer‐based hydrogel electrolytes, though biocompatible and cost‐effective, often exhibit poor mechanical strength and ionic conductivity, limiting their use in high‐performance energy storage. Phos‐XK, a novel hydrogel electrolyte derived from xanthan gum (XG) and konjac glucomannan (KGM), has been developed via physical cross‐linking and targeted phosphorylation. Specifically, physical cross‐linking forms a robust 3D network that provides a stable structural foundation. Building on this, the phosphorylation process introduces phosphate monoesters (MPE) and diesters (DPE) in a precisely controlled ratio. MPE groups enhance ionic conductivity by facilitating Zn²⁺ desolvation and ion migration, while DPE strengthens mechanical integrity through enhanced cross‐linking. These distinct roles of MPE and DPE are confirmed through both theoretical calculations and experimental results. Optimizing the phosphorylation ratio achieves a balance between mechanical strength (2.524 MPa) and ionic conductivity (20.72 mS cm⁻¹), resulting in remarkable electrochemical performance, including an extended cycle life exceeding 3000 h and a high Coulombic efficiency of 99.45% in Zn//Cu batteries. Moreover, Phos‐XK is biocompatible and biodegradable, ideal for sustainable energy storage. This work highlights the potential of bio‐based materials to overcome the limitations of traditional hydrogel electrolytes and stresses the importance of molecular engineering in achieving high‐performance, eco‐friendly energy storage.

Using global Total Electron Content (TEC) data provided by the Madrigal database, this study investigates large-scale traveling ionospheric disturbances (LSTIDs) observed in the North American and European sectors during the geomagnetic storm on March 23, 2023. A second-order polynomial fitting method was applied to filter residuals, calculate ionospheric disturbance values, and create two-dimensional TEC disturbance maps showing variations across latitude and longitude. The results indicate the observation of multiple LSTIDs originating from the Arctic in both the European and North American sectors. Intense LSTIDs were found to propagate during the daytime in these sectors. In the North American sector, LSTIDs exhibited propagation speeds ranging from 512 to 610 m/s, while in the European sector, the speeds ranged from 575 to 652 m/s. The wave propagation direction in the North American sector averaged approximately 15 degrees southeast of south, whereas in the European sector, the average direction was 15 degrees southwest of south.

There is great potential for legged robots in unstructured environments. However, model‐based approaches benefit from precise model analysis, which can be cumbersome and demand substantial domain expertise, while learning‐based methods, though promising, often necessitate prolonged training periods and may result in complex and opaque controllers. This architecture aims to mimic neural‐muscle control and sensory feedback mechanisms, enabling legged robots to adjust neural signal intensity based on proprioceptive feedback and achieve behavior responses similar to those observed in animals. Specifically, and the central pattern generator creates insect‐like gaits, the virtual motoneurons network generates continuously adjustable trajectories for omnidirectional motion and limb control. The sensorimotor integration module, event‐based finite state machine, and local reactive strategies allow robots to traverse unstructured terrains. The method is experimentally applied to a newly developed hexapod robot named RENS H2. The results indicate that the proposed method enhances the robot's locomotion diversity, enabling adaptive navigation in unstructured terrains, including overcoming steps with heights up to 66.7% of its leg length.

This study intended to investigate the hydrochemical characteristics and sources of nitrate (NO3-N) in groundwater, and to evaluate the potential health risks in the vicinity of the Jiangcungou landfill in Northwest China. To fulfill these purposes, a total of 41 groundwater sourced primarily from the phreatic aquifer were collected and analyzed. The study found that NO3-N concentrations in the area varied between 0.57 mg/L and 47.69 mg/L, with 26.67% of samples exceeded China’s drinking water threshold (20 mg/L as N) and 31.7% surpassing the WHO guideline (11.3 mg/L as N). The background level of NO3-N was estimated to be 1.11 mg/L through a probabilistic approach and was exceeded by 85.4% of the samples. Ionic ratios and land use analysis highlighted significant NO3-N contributions from domestic sewage, industrial, and agricultural sources. These findings were reinforced by principal component analysis (PCA) and the absolute principal component score-multiple linear regression (APCS–MLR) model, which attributed 40.12% of NO3-N to domestic sewage and wastewater and 7.78% to industrial and agricultural activities. Although Jiangcungou landfill is not the primary contributor, lingering leachate still affects groundwater quality, especially in nearby wells with high NO3-N concentrations. Furthermore, health risk assessments indicated significant NO3-N associated non-carcinogenic risks (HQoral > 1) for infants (63.4%), children (46.3%), females (41.5%), and males (34.1%). The Monte Carlo Simulation further supports these findings, highlighting elevated risks, especially for infants and children. This study provides important scientific support and guidance for implementing sustainable groundwater management practices and the protection of human health in affected areas.

To address the global energy crisis and mitigate environmental challenges stemming from fossil fuel dependence, advancing efficient photocatalytic water splitting technology has become a critical focus in renewable energy research. An innovative design strategy for high‐efficiency photocatalysts based on band edge alignment is established through the integration of machine learning (ML) and first‐principles computational methods, developing a high‐throughput screening framework specifically targeting 1T‐phase transition metal dichalcogenides (1T‐TMDs). Through optimized feature selection, ML models, and training protocols, the PdSSe monolayer is identified as exhibiting ideal band edge compatibility with the GeC monolayer. Subsequent density functional theory (DFT) verification confirmed exceptional agreement with ML predictions. The GeC/SPdSe Z‐scheme heterostructure achieves remarkable photocatalytic efficiency, driven by its optimally aligned band structure that enables spontaneous hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) under visible‐light irradiation. Nonadiabatic molecular dynamics (NAMD) simulations reveal that photo‐generated carriers in heterostructures follow a Z‐scheme pathway, as supported by distinct timescales of electron‐hole migration and recombination. This heterostructure architecture exhibits broadband light absorption spanning the visible to ultraviolet spectral regions, yielding a remarkable theoretical solar‐to‐hydrogen (STH) efficiency of 29.5%.

Magnesium-based Zintl-phase compounds are outstanding among the high performance thermoelectric material candidates for their better flexibility, non-toxicity and low-cost. Recently, we have noted an experiment that synthesized a new thermoelectric...

Ecosystem service (ES)-oriented spatial optimization can contribute to regional well-being, especially for mountain ecosystems carrying multiple ES capacities. However, existing studies on mountain ecosystem services (MESs) predominantly address gradient dynamics, yet fail to incorporate landscape as a socio-ecological nexus, which hinders their practical application in spatial planning. Therefore, we proposed a spatial optimization strategy, leveraging landscape to strengthen the process from ES science to practical management in the Qinling Mountain (QLM), China. Landscape Naturalness Composite Index (LNCI) was drawn on as a continuous metric to symbolize the gradient of mountainous landscape configuration driven by social-ecological interaction. Spatiotemporal change and attribution analysis of MESs were also conducted to corroborate the final management, considering carbon sequestration (CS), modified habitat quality (HQ), and soil conservation (SC) from 1990 to 2020. We find that the three critical MESs synergistically increased over 31 years. Among them, HQ and CS increased stepwise under the context of ecological programs, but SC fluctuates dominated by rainfall. Holistically, agricultural intensification and urban development alleviated remote human-land conflicts, indicating that the improvement in MESs coincided with increases in the urban-rural population ratio and food production (FP). A mountain regulation baseline (MRB) was identified by landscape threshold, covering 44.39 % of the QLM, which can help to address a range of issues in mountain conservation. We proposed a two-tier nested zonal management framework, leveraging landscape to connect MRB and multifunctionality characterized by ES bundles. Our framework has benefits for informing adequate implications on management practices of global mountain ecosystems.

To study the influence of the evolution of pore structure and pore fluid state on the loading effect of unsaturated loess, a series of oedometer tests were carried out on intact and remoulded loess, supplemented by low‐field nuclear magnetic resonance (NMR) tests at different consolidation stages of the same specimens for the first time. The results show that the deformation of intact loess lags behind that of remoulded loess during mechanical wetting. The pore water gradually encroaches on the pore structure, which increases the debonding effect of soil and the behaviour of loess gradually converges to that of saturated loess. Under the same vertical pressure, unsaturated loess maintains a higher void ratio than saturated. The decrease in the relaxation time span predicts the compression of the pore structure and the gradual encroachment of water. Deformation caused by consolidation enhances the water retention performance of unsaturated loess. The results provide guidance for understanding the evolution of micropore fabrics in the compaction process of loess.

To investigate the temperature dependence of the modulus of LSAM-50 flexible base asphalt pavement (LSAM-50 pavement) materials, specifically SMA-13, AC-20, and LSAM-50. The effects of temperature on the modulus of LSAM-50 pavement materials were investigated, and a temperature-dependent model of resilient modulus was established. A dynamic modulus master curve was constructed based on a generalized logarithmic Sigmoidal model. The correlation between the resilient modulus and dynamic modulus was studied, and a multiple linear regression model was developed to describe the relationship between the dynamic modulus and resilient modulus, temperature, and loading frequency. The results show that the resilient modulus and dynamic modulus gradually decrease with the increase in temperature and then tend to stabilize. The resilient modulus of LSAM-50 is higher than that of SMA-13 and AC-20 in the entire temperature range, and the dynamic modulus of LSAM-50 is higher than that of SMA-13 and AC-20 in the high-temperature range. The correlation coefficients (R²) of the established resilient modulus and dynamic modulus estimation models are greater than 0.97 and 0.94, respectively.

Traditional laboratory rutting tests are performed at a constant temperature by neglecting pavement temperature variation. The mechanical properties of asphalt are susceptible to temperature variation. This sensitivity to temperature variations significantly influences the performance and durability of asphalt pavements. Following this purpose, a stepwise temperature-controlled rutting test method was proposed to investigate the rutting development of double-layer asphalt pavement (DLAP) under variable temperature. A time-hardening model was developed and employed to evaluate the rutting performance of DLAP under variable temperature. Results indicate that the rutting development of DLAP exhibits a stepwise variation when subjected to variable temperatures. Within a specific constant temperature range, rutting development can be fitted using a power function of load cycles. The rutting deformation of DLAP predominantly occurs at 20 °C; once the temperature exceeds 50 °C, the rutting development accelerates and becomes difficult to stabilize. The time-hardening model effectively captures the rutting development under variable temperature. The predicted values align closely with field values, which demonstrates the model’s feasibility in calculating rutting deformation under variable temperature. Under actual service conditions, the rutting development of DLAP follows a periodic S-shaped growth, yet this trend can still be represented by a power-law function. DLAP exhibits satisfactory durability and structural stability, effectively addressing the challenges posed by traffic loads and high temperatures in test sections.

In this study, the feasibility of using three-dimensional (3D) printing technology to investigate the impact of macrotexture and microtexture on the skid resistance of asphalt pavement was verified. The macrotexture characteristics of the five types of real asphalt mixtures were captured, reconstructed, and printed. The comparison analysis of the skid resistance between the pavement and printed specimens was conducted, and the correlations and contribution proportions of the macrotexture and microtexture on skid resistance were also calculated. Results show that five printed asphalt mixtures present good consistency in the microtexture with a roughness of about 100 nm. The impact of thin water film on the skid resistance is insignificant for real asphalt mixtures, while it is significant for printed mixtures. The printed specimens under dry conditions show a similar British pendulum number (BPN) with the real pavement specimens under wet conditions, while the BPN under wet conditions for printed specimens are much smaller than the real ones but follows a similar variation trend. Mean profile depth (MPD) values of four printed asphalt concrete (AC) mixtures are well linearly correlated with their BPN under dry and wet conditions, especially for wet conditions with the R² of 0.91. The contribution proportion of macrotexture to the skid resistance is nearly 90% for the dry condition and about 50% for the wet condition.

Video snow removal has tremendous potential in enhancing video quality and boosting the performance of computer vision tasks. Recently, Transformers have gained attention for the self-attention mechanism. However, the memory consumption of self-attention is considerable, limiting its application in high-resolution video restoration. In this paper, we propose an efficient video desnowing spatio-temporal Transformer, which utilizes spatio-temporal sequence attention to parallelly capture intra-frame spatial information and inter-frame temporal information, with much lower memory consumption compared to standard self-attention. Additionally, we mitigate the impact of snowflake occlusion on video frame alignment by leveraging an atmospheric scattering model. Furthermore, we introduce the concept of Neural Representation for Videos (NeRV) and effectively reconstruct compressed videos after multi-resolution feature extraction using the recovery NeRV module, thereby further reducing computational consumption. Extensive experiments demonstrate that the model achieves superior performance in video snow removal while significantly reducing computational resources.

Promoted by the goal of global energy transformation and carbon neutrality, green hydrogen production technology driven by solar energy has become a key strategic direction to break through the bottleneck of energy and the environment. Traditional photocatalytic water decomposition method for hydrogen production is limited by the low kinetic efficiency of oxidation half‐reaction and dependence on high‐cost and harmful sacrifice agents, therefore it is urgent to seek a potential and sustainable alternative. In this review work, the relevant research progress of different metal sulfide photocatalysts in photocatalytic hydrogen evolution (PHE) of multilevel biomass resources and waste plastics is reviewed. First, the structure and modification strategy of metal sulfides are discussed, and the PHE mechanism and multi‐scale synergistic effect are analyzed. Second, the effective strategies of different metal sulfides in the PHE process of multilevel biomass and waste plastics are summarized. In addition, the vital industrialization potential of the technology is also evaluated from the aspects of environmental impact and economic feasibility. Finally, the development direction of material‐process‐artificial intelligence integration innovation is prospected, providing theoretical guidance and technical path from laboratory to large‐scale application.

In this study, graphene‐carbon fiber/basalt fiber (GO‐CF/BF) hybrid reinforced composites were prepared using fused deposition 3D printing technology with vacuum infiltration hot press molding process. The effects on microstructure and shape memory properties were comparatively analyzed by adding shape memory polymer (SMP) and changing the lay‐up method. The results showed that, in terms of density and porosity, the density and porosity of the composites showed a decreasing trend due to the low density and low porosity characteristics of the SMP, and the density and porosity of the composites increased with the increase of the BF content due to the large bulk density of the BFs and the poor interfacial bonding ability with the matrix. In terms of shape memory properties, the addition of SMP can increase the fixation rate and recovery rate of GO‐CF/BF hybrid reinforced composites, and with the increase of BF content, the fixation rate increases and the recovery rate decreases. In terms of flexural properties, the flexural strength of the composites gradually decreased from 675.58 to 400.45 MPa with the increase of BF content due to the low modulus and strength of BFs and the low bonding rate with the matrix.