Search Results (250)

In deformation monitoring, the severe GNSS multipath caused by reflective surfaces can significantly degrade positioning accuracy. However, traditional multipath mitigation methods often assume strong day-to-day repeatability of residual errors, which is not always valid in complex monitoring environments. We propose a novel GNSS multipath correction approach that leverages multi-day post-fit residual data and principal component analysis to extract stable multipath signals, integrating them into an enhanced spatial repeatability multipath correction model. This method can effectively isolate true multipath errors, even under conditions of weak inter-day repeatability. Experimental results from a dam monitoring network demonstrate that the proposed method reduces the root mean square (RMS) error of single-day kinematic positioning by about 1.8 mm, 2.4 mm, and 6.7 mm in the East, North, and Up components, respectively. For static positioning solutions over 1 h, 2 h, and 4 h sessions, the RMS in East, North, and Up is reduced by approximately 40% on average. After correction, 2 h sessions achieve ~1.1 mm horizontal and ~3.0 mm vertical accuracy, while 4 h sessions reach ~0.9 mm horizontal and ~2.5 mm vertical accuracy. These improvements confirm that the proposed method effectively mitigates multipath effects and meets the high-precision requirements of deformation monitoring. Full article

There are significant scale and morphological differences between fire and smoke features in forest fire detection. This paper proposes a detection method based on dual-branch multi-scale adaptive feature fusion network (DMAFNet). In this method, convolutional neural network (CNN) and transformer are used to form a dual-branch backbone network to extract local texture and global context information, respectively. In order to overcome the difference in feature distribution and response scale between the two branches, a feature correction module (FCM) is designed. Through space and channel correction mechanisms, the adaptive alignment of two branch features is realized. The Fusion Feature Module (FFM) is further introduced to fully integrate dual-branch features based on the two-way cross-attention mechanism and effectively suppress redundant information. Finally, the Multi-Scale Fusion Attention Unit (MSFAU) is designed to enhance the multi-scale detection capability of fire targets. Experimental results show that the proposed DMAFNet has significantly improved in mAP (mean average precision) indicators compared with existing mainstream detection methods. Full article

Microorganisms (bacteria and algae) are important components of biological soil crusts, which exhibit crucial functions in promoting plant growth, maintaining soil structure, and improving soil nutrient content. To determine the effects of combined inoculation on the growth of Poa annua and sandy soils, four species of bacteria and algae were isolated and identified from biological soil crusts (during different developmental stages in a karst rocky desertification area). The soil quality was evaluated based on a soil quality index (SQI), growth indicators of Poa annua, soil physicochemical properties, and a stability analysis of aggregates. With the application of nutrient-poor sandy soils as the substrate, different treatment inoculation solutions were inoculated onto Poa annua. The results revealed that bacteria–algal co-inoculation reduces soil acidity, enhances soil nutrient content and aggregate stability, improves soil quality, and protects plant growth. Notably, compared with the single application of bacterial solution and algal solution, the combined application of bacteria–algal solution significantly improves the sandy soil quality. Full article

The rapid development of the logistics industry has underscored the urgent need for efficient and sustainable urban freight systems. As a core component of freight systems, heavy-duty trucks (HDT) have been researched regarding surface-level descriptive statistics of their heterogeneities, such as trip volume, frequency, etc., but there is a lack of in-depth analyses of the spatial interaction between freight travel and freight functional clustering, which restricts a systematic understanding of freight systems. Against this backdrop, this study develops a data-driven framework to analyze HDT behavioral heterogeneity and its spatial interactions with a freight functional zone in Shanghai. Leveraging the high-frequency trajectory data of nearly 160,000 HDTs across seven types, we construct a set of regional indicators and employ hierarchical clustering, dividing the city into six freight functional zones. Combined with the HDTs’ application scenarios, functional characteristics, and trip distributions, we further analyze the spatial interaction between the HDTs and clustered zones. The results show that HDT travel patterns are not merely responses to freight demand but complex reflections of urban industrial structures, infrastructure networks, and policy environments. By embedding vehicle behaviors within their spatial and functional contexts, this study reveals a layered freight system in which each HDT type plays a distinct role in supporting economic activities. This research provides a new perspective for deeply understanding the formation mechanisms of HDT trip distributions and offers critical evidence for promoting targeted freight management strategies. Full article

Understanding the detailed spatiotemporal variations in soil organic carbon (SOC) stocks is essential for assessing soil carbon sequestration potential. However, most existing studies predominantly focus on topsoil SOC stocks, leaving significant knowledge gaps regarding critical zones, depth-dependent variations, and key influencing factors associated with deeper SOC stock dynamics. This study adopted a comprehensive methodology that integrates random forest modeling, equal-area soil profile analysis, and space-for-time substitution to predict depth-specific SOC stock dynamics under climate warming in Northeast China’s forest ecosystems. By combining these techniques, the approach effectively addresses existing research limitations and provides robust projections of soil carbon changes across various depth intervals. The analysis utilized 63 comprehensive soil profiles and 12 environmental predictors encompassing climatic, topographic, biological, and soil property variables. The model’s predictive accuracy was assessed using 10-fold cross-validation with four evaluation metrics: MAE, RMSE, R², and LCCC, ensuring comprehensive performance evaluation. Validation results demonstrated the model’s robust predictive capability across all soil layers, achieving high accuracy with minimized MAE and RMSE values while maintaining elevated R² and LCCC scores. Three-dimensional spatial projections revealed distinct SOC distribution patterns, with higher stocks concentrated in central regions and lower stocks prevalent in northern areas. Under simulated warming conditions (1.5 °C, 2 °C, and 4 °C increases), both topsoil (0–30 cm) and deep-layer (100 cm) SOC stocks exhibited consistent declining trends, with the most pronounced reductions observed under the 4 °C warming scenario. Additionally, the study identified mean annual temperature (MAT) and normalized difference vegetation index (NDVI) as dominant environmental drivers controlling three-dimensional SOC spatial variability. These findings underscore the importance of depth-resolved SOC stock assessments and suggest that precise three-dimensional mapping of SOC distribution under various climate change projections can inform more effective land management strategies, ultimately enhancing regional soil carbon storage capacity in forest ecosystems. Full article

Zeugodacus cucuribitae (Coquillett) (Z. cucuribitae) is a global extremely invasive quarantine pest which has a wide host range of fruits and vegetables. At present, there are a few control measures for Z. cucuribitae, and deltamethrin and avermectin are commonly used. Among the hosts of Z. cucuribitae, Luffa acutangular, Luffa cylindrica, Sechium edule, Brassica oleracea var. botrytis, Musa nana, and Fragaria × ananassa are non-favored hosts. However, it is still not clear why these hosts are non-favored and whether there are any repellent components of Z. cucuribitae in these hosts. In this study, the components of these six hosts were collected from the literature, and the genes of odor and chemical sensation were determined from the genome of Z. cucuribitae. After the potential relationships between these components and genes were determined by molecular docking methods, the KEGG and GO enrichment analysis of these genes was conducted, and a complex network of genes vs. components vs. Kegg pathway vs. GO terms was constructed and used to select the key components for experiments. The results show that oleanolic acid (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), rotenone (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), and beta-caryophyllene oxide (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL) had a significant repellent effect on Z. cucuribitae, and three components, rotenone (1 mg/mL and 0.1 mg/mL), echinocystic acid (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), and beta-caryophyllene oxide (1 mg/mL, and 0.1 mg/mL) had significant stomach toxicity in Z. cucuribitae. Furthermore, a complex signaling pathway was built and used to predict the effect of these components on Z. cucuribitae. These components probably play roles in the neuroactive ligand–receptor interaction (ko04080) and calcium signaling (ko04020) pathways. This study provides a reference for the prevention and control of Z. cucuribitae and a scientific reference for the rapid screening and development of new pest control drugs. Full article

This study addresses the long-standing difficulty of predicting the remaining useful life (RUL) of rolling bearings from highly non-stationary vibration signals by proposing WaveAtten, a symmetry-aware deep learning framework. First, mirror-symmetric and bi-orthogonal Daubechies wavelet filters are applied to decompose each raw signal into multi-scale approximation/detail pairs, explicitly preserving the left–right symmetry that characterizes periodic mechanical responses while isolating asymmetric transient faults. Next, a bidirectional sparse-attention module reinforces this structural symmetry by selecting query–key pairs in a forward/backward balanced fashion, allowing the network to weight homologous spectral patterns and suppress non-symmetric noise. Finally, the symmetry-enhanced features—augmented with temperature and other auxiliary sensor data—are fed into a long short-term memory (LSTM) network that models the symmetric progression of degradation over time. Experiments on the IEEE PHM2012 bearing dataset showed that WaveAtten achieved superior mean squared error, mean absolute error, and R² scores compared with both classical signal-processing pipelines and state-of-the-art deep models, while ablation revealed a 6–8% performance drop when the symmetry-oriented components were removed. By systematically exploiting the intrinsic symmetry of vibration phenomena, WaveAtten offers a robust and efficient route to RUL prediction, paving the way for intelligent, condition-based maintenance of industrial machinery. Full article

This study aims to investigate the mechanism by which the total flavones of Rhododendron (TFR) protect against cerebral ischemic injury through the endothelial-derived H₂S-mediated regulation of RhoA phosphorylation at the Ser188 and Rho kinase 2 (ROCK₂) phosphorylation at Thr436. For experimental design, mouse or rat cerebrovascular endothelial cells (ECs) were cultured with or without neurons and subjected to hypoxia/reoxygenation (H/R) injury. The vasodilation of the cerebral basilar artery was assessed. Cerebral ischemia/reperfusion (I/R) injury was induced in mice by bilateral carotid artery ligation, followed by Morris water maze and open field behavioral assessments. The protein levels of cystathionine-γ-lyase (CSE), 3-mercaptopyruvate sulfurtransferase (3-MST), RhoA, ROCK₂, p-RhoA (RhoA phosphorylated at Ser188), and p-ROCK₂ (ROCK₂ phosphorylated at Thr436) were quantified. Additionally, the activities of RhoA and ROCK₂ were measured. Notably, TFR significantly inhibited H/R-induced H₂S reduction and suppressed the increased expression and activity of RhoA and ROCK₂ in ECs, effects attenuated by CSE or 3-MST knockout. Moreover, TFR-mediated cerebrovascular dilation was reduced by RhoA or ROCK₂ inhibitors, while the protective effect of TFR against cerebral I/R injury in mice was markedly attenuated by the heterozygous knockout of ROCK₂. In the ECs-co-cultured neurons, the inhibition of TFR on H/R-induced neuronal injury and decrease in H₂S level in the co-culture was attenuated by the knockout of CSE or 3-MST in the ECs. TFR notably inhibited the H/R-induced upregulation of neuronal RhoA, ROCK₂, and p-ROCK₂ protein levels, as well as the activities of RhoA and ROCK₂, while reversing the decrease in p-RhoA. However, the knockout of CSE or 3-MST in the ECs significantly attenuated the inhibition of TFR on these increases. Furthermore, 3-MST knockout in ECs attenuated the TFR-mediated suppression of p-RhoA reduction. Additionally, CSE or 3-MST knockout in ECs exacerbated H/R-induced neuronal injury, reduced H₂S level in the co-culture system, and increased RhoA activity and ROCK₂ expression in neurons. In summary, TFR protected against ischemic cerebral injury by endothelial-derived H₂S promoting the phosphorylation of RhoA at Ser188 but inhibited the phosphorylation of ROCK₂ at Thr436 to inhibit the RhoA-ROCK₂ pathway in neurons. Full article

Wound infections remain significant challenges for current tissue adhesives, primarily due to their poor adhesion in moist environments, slow bonding, cytotoxicity, and limited antibacterial properties. Slightly acidic electrolyzed water (SAEW), a potent disinfectant, suffers from limited stability due to chlorine loss. This study developed a novel SAEW-based hydrogel (SAEW-gel) by combining SAEW with chitosan and β-glycerol disodium phosphate to improve its stability and therapeutic potential. SAEW-gel demonstrated high water absorption, long-term water retention, and enhanced antibacterial activity against S. aureus and E. coli compared to SAEW alone. It maintained germicidal efficacy after prolonged storage and significantly accelerated wound healing in a rat model, achieving a 95.41% healing rate by the 12th day of treatment. Mechanistically, SAEW-gel reduced inflammatory cell infiltration, promoted granulation and collagen formation, and regulated inflammatory markers (IL-6, IL-1β, TNF-α, MPO, HYP). These findings highlight SAEW-gel as a promising biomaterial for treating infectious wounds and support its potential for future clinical application. Full article

Lead (Pb) and cadmium (Cd) ions have serious negative impacts on human health and the ecological environment due to toxicity, persistence and nonbiodegradability. Among various trace Pb and Cd ions detection technologies, electrochemical analysis is considered as one of the most promising methods. The deposition of Bi nanoparticles on delaminated Ti₃C₂T_x (DL-Ti₃C₂T_x) develops a sensor with good conductivity and performance. Square wave anodic stripping voltammetry (SWASV) technology was applied to simultaneously deposit Bi on DL-Ti₃C₂T_x/GCE and achieve the rapid detection of Pb and Cd ions. The Bi nanoparticles effectively improved the sensitivity of Bi/DL-Ti₃C₂T_x/GCE sensors to detect Pb and Cd ions. The preparation conditions of the Bi/DL-Ti₃C₂T_x/GCE were optimized, including DL-Ti₃C₂T_x droplet amount, solution pH, Bi³⁺ concentration, deposition time and deposition potential, to improve the detection ability. The Bi/DL-Ti₃C₂T_x/GCE sensor has detection limits of 1.73 and 1.06 μg/L for Pb and Cd ions, respectively (S/N > 3). This electrochemical sensor is easy, sensitive and selective to apply in actual water samples for trace Pb and Cd ions detection. Full article

Incorporating a 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide-based derivative (1,4-bis(diphenoxyphosphoryl)piperazine, DIDOPO) in combination with modified calcium sulfate whiskers (MCSWs) improved the flame retardancy, thermal stability, and rheological properties of a polyethylene oxide (PEO) composite. The synergistic flame-retardant effect of DIDOPO and MCSW on the PEO system was investigated. After introducing 5 wt.% MCSW and 10 wt.% DIDOPO into PEO, the UL-94 rating of the composite reached V-0, and the limiting oxygen index was increased to 26.5%. Additionally, the peak and average heat release rates and total heat release of the PEO/10% DIDOPO/5% MCSW composite decreased by 38.9%, 22%, and 20.07%, respectively. The results of a thermogravimetric analysis (TGA) revealed that PEO/10% DIDOPO/5% MCSW displayed an improved initial thermal stability and rate of char formation compared to those of the PEO matrix. The results of TGA/Fourier transform infrared analysis indicated that the composites exhibited phosphorus-containing groups during thermal degradation, based on the characteristic absorption peaks, and increased amounts of gas-phase volatiles. The morphologies and structures of the residues indicated that the PEO/10% DIDOPO/5% MCSW blend was less stable than PEO during combustion. The MCSW mixture formed a denser, more continuous carbon layer on the composite surface during combustion. The rheological behavior indicated that the high complex viscosity and moduli of PEO/10% DIDOPO/5% MCSW promoted the cross-linking network structure of the condensed phase during combustion. MCSW exhibited an excellent flame retardancy and improved thermal stability, which are potentially promising for use in fire safety applications. Full article

Drought stress is a crucial factor limiting plant survival and growth, especially during the seedling establishment stage. A deep understanding of different plants’ responses to drought stress and their drought resistance is of great significance for vegetation restoration under drought conditions. This study selected one-year-old seedlings of Winter Jasmine (Jasminum nudiflorum), Oleander (Nerium oleander), Privet (Ligustrum lucidum), and Redleaf Photinia (Photinia × fraseri) as research objects. Through pot experiments, we investigated the physiological and biochemical responses of these shrubs under different levels of drought stress (control, mild, moderate, and severe drought stress, corresponding to 75%, 60%, 45%, and 30% of field maximum water holding capacity) to comprehensively assess their drought resistance capabilities. The research results indicated that as the level of drought stress increased, significant changes (p < 0.05) occurred in the physiological and biochemical indicators of all four plant species. The chlorophyll content (Chla+b) of Winter Jasmine and Redleaf Photinia gradually decreased with the intensification of stress, while the Chla+b of Oleander showed the most significant decline under moderate stress and Privet was most affected under mild stress. The proline (Pro) and soluble sugar (SS) contents of all four plants exhibited an upward trend, suggesting that the plants coped with drought stress by accumulating these osmoregulatory substances. Drought stress led to damage to plant cell membranes, manifested by an increase in malondialdehyde content (MDA), with Winter Jasmine showing the most pronounced increase. The activities of peroxidase (POD) and superoxide dismutase (SOD) in the four plant species responded differently to drought stress: the POD activity of Oleander and Redleaf Photinia increased with the deepening of stress, while that of Winter Jasmine and Privet decreased. A comprehensive evaluation of the drought tolerance of the four plant species was performed using principal component analysis and affiliation function value methods. The drought tolerance of the four shrubs, from strongest to weakest, was as follows: Redleaf Photinia > Oleander > Privet > Winter Jasmine. This finding provides valuable insights for plant selection in ecological slope protection projects, and Redleaf Photinia and Oleander can be promoted for use in vegetation restoration work under drought conditions. Full article

In view of the low efficiency and slow development of fruit and vegetable picking in China, the picking sequence and obstacle avoidance of clustered crabapples were studied with them as the picking target. The multi-objective picking sequence of crabapples was planned, and the adaptive pheromone factor, heuristic function, and volatile factor were used to improve the ant colony (ACO) algorithm, so as to improve the convergence speed, adaptability, and global search ability of the algorithm. In order to avoid the collision between the robotic arm and the branches of the fruit tree, the three-dimensional reconstruction of the fruit tree was carried out, the shape and position information of the obstacle branch was determined, the artificial potential field was fused with the RRT, the search orientation of the RRT algorithm was enhanced, the inflection point was reduced, and the convergence speed was improved. The results showed that the average success rate of picking was 89.58%, and the robotic arm did not collide with the branches according to the planned picking sequence during the picking process, so as to achieve the picking purpose and picking effect. Full article

Coke (AC) was modified and activated with sodium hydroxide (NaOH) and potassium hydroxide (KOH) to produce AC-Na and AC-K, respectively, and applied as a persulfate (PS) activator to promote phenol (Ph) removal in water. Under the given experimental conditions, compared to AC/PS (Ph removal effect was 77.09%), the Ph removal effects were 94.46% and 88.73% for AC-K/PS and AC-Na/PS, respectively. AC-K proved to be a more effective activator than AC-Na and was used for all the subsequent experiments. When PS/phenol molar ratio was 6.26:1:00, the initial system pH was 7 and the system temperature was 25 °C; the AC-K/PS system could effectively remove Ph (98.75%) from the simulated wastewater. After that, the stability of AC-K was verified. Electron paramagnetic resonance (EPR) and quenching analysis confirmed the hydroxyl free radical (•OH) to be predominant within this system. EPR combined with X-ray photoelectron spectroscopy (XPS), Fourier-transformed infrared (FTIR) spectroscopy, and Raman spectroscopy indicated that the sulfate radical (SO₄^•−) and •OH were generated due to the defects in AC-K, thereby enhancing the PS activation potency of AC-K. Additionally, the radical quenching experiments showed that the superoxide (O₂⁻) radical is a key intermediate product promoting SO₄^•− and •OH, which aided Ph removal. Both radical (SO₄^•− and •OH) and non-radical (¹O₂) pathways were found to co-exist during the removal process. The Ph removal rate of the AC-K/PS system could still reach 29.50%, even after four repeated cycles. These results demonstrate that the unique AC-K/PS system has a potential removal effect on organic pollutants in water. Full article

Illegal, unreported, and unregulated (IUU) fishing significantly threatens marine ecosystems, disrupts the ecological balance of the oceans, and poses serious challenges to global fisheries management. This contribution presents the efficacy of China’s summer fishing moratorium using BeiDou vessel monitoring system (VMS) data from 2805 fishing vessels in the East China Sea and Yellow Sea, integrated with a deep learning framework for spatiotemporal analysis. A preprocessing protocol addressing multidimensional noise in raw VMS datasets was developed, incorporating velocity normalization and gap filling to ensure data reliability. The CNN-BiLSTM hybrid model emerged as optimal for fishing behavior classification, achieving 89.98% accuracy and an 87.72% F1 score through synergistic spatiotemporal feature extraction. Spatial analysis revealed significant policy-driven reductions in fishing intensity during the moratorium (May–August), with hotspot areas suppressed to sporadic coastal distributions. However, concentrated vessel activity in Zhejiang’s nearshore waters suggested potential illegal fishing. Post-moratorium, fishing hotspots expanded explosively, peaking in October and clustering in Yushan, Zhoushan, and Yangtze River estuary fishing grounds. Quarterly patterns identified autumn–winter 2021 as peak fishing seasons, with hotspots covering >80% of East China Sea grounds. The framework enables real-time fishing state detection and adaptive spatial management via dynamic closure policies. The findings underscore the need for strengthened surveillance during moratoriums and post-ban catch regulation to mitigate overfishing risks. Full article