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Simple Summary: Low-pressure systems frequently occur during the summer in coastal areas and can be detrimental to commercial poultry houses. The effects of air temperature and humidity vary across different periods. Throughout the generation of low-pressure systems, landfall, and disappearance, air temperature and humidity changes can interfere with the housing environment. However, farmers often overlook the impact of low-pressure systems on large-scale poultry houses, which may impair the production of laying hens. This study investigated the effects of the different low-pressure systems on the housing environment and egg production in large-scale poultry houses in China. The results indicated that a single low-pressure system reduced the laying performance, whereas a sustained low-pressure system mitigated the impact on egg production. This study aimed to determine the effect of low-pressure systems on the environment and the laying performance of large-scale poultry houses during the summer and to provide a basis for farmers to adjust their environmental control strategies under extreme weather conditions. Low-pressure systems (LPSs) are among the most critical weather systems, producing excessive precipitation that causes air temperatures to drop and rise considerably. Acute temperature changes directly affect poultry feed intake (FI) and laying performance. To explore the effects of LPSs on hens, the parameters of air temperature, relative humidity, egg production, and feed utilization efficiency were evaluated during different LPSs in three houses. Results indicated that about 2.8 ± 0.7 d, 2.4 ± 0.5 d, and 2.4 ± 0.5 d before the LPS landfall in houses 1, 2, and 3, respectively, the indoor air temperature started to decrease, with the average decreases being 1.7 °C ± 0.4 °C, 2.4 °C ± 0.6 °C, and 1.8 °C ± 0.4 °C, respectively. Significant differences were observed between different LPSs for reducing indoor air temperature (p < 0.05) in the three houses. In house 1, the egg production rates (EPRs) were decreased by 6.6% and 1.1% when LPSs 1 and 2 landed. The average egg weight (AEW) and FI during the LPS landfall were significantly higher than those before the LPS landfall (p < 0.01). Under successive LPSs landfall in the three houses, the EPRs initially reduced by 3.9%, 4.0%, and 0.5%, respectively, but the second LPS event increased the EPRs by 1.8%, 5.3%, and 1.0%, respectively. Furthermore, the LPS landfall increased the feed conversion ratio (FCRe) in the three houses, all above 2.00. In conclusion, LPSs can reduce heat stress, lower the EPRs, and lead to higher FI, FCRe, and AEW. [ABSTRACT FROM AUTHOR]

Addressing the issue of significant speed fluctuations in permanent magnet synchronous motors (PMSM) under load, this paper proposes an active disturbance rejection control strategy based on an improved particle swarm optimization (PSO) algorithm. Initially, the speed of the PMSM is considered as the comprehensive optimization objective, and an active disturbance rejection control (ADRC) model for the PMSM is established by integrating the ADRC with vector control. Subsequently, an adaptive PSO algorithm incorporating genetic algorithms is proposed. This algorithm uses chaotic initialization for uniform particle distribution, introduces adaptive inertia weight and dynamic cognitive factors to enhance search efficiency, and integrates the crossover and mutation modules from genetic algorithms, optimizing mutations using a Gaussian probability function. Simulation results demonstrated that: (1) under identical external load conditions, the proposed ADRC strategy ensured smaller speed fluctuations and a smoother waveform for the PMSM, and (2) compared to the traditional PSO algorithm, the proposed method reduced the speed fluctuation after external load by approximately 26%. [ABSTRACT FROM AUTHOR]

This paper presents the design of a 40 × 40 micro-light-emitting (micro-LED) test array based on a 20 mm × 20 mm substrate. A study of the relationship between luminous brightness, driving current, and driving voltage revealed that the data voltages of the red, green, and blue micro-LED array from 0 to 255 grey levels are 0.31 V, 0.29 V, and 0.30 V, respectively, under the condition that the target brightness of the white field is 1000 nits and the color temperature is 9300 K. The brightness range of the red micro-LED array is 64.8–101.2%, the brightness range of the green micro-LED array is 66.5–102.8%, and the brightness range of the blue micro-LED array is 53.5–129.2%. In order to overcome the luminance nonuniformity, a grey level depth of 12 -bit is required. A 10T3C pixel driver circuit based on low-temperature polysilicon (LTPS) with a depth of 12 bits greyscale is designed and fabricated into the micro-LED display. A brightness uniformity of 84.1–97.1% can be achieved by brightness correction combined with a 12-bit greyscale depth system for micro-LED display. This provides a valuable reference point for subsequent improvements in the quality of micro-LED displays. [ABSTRACT FROM AUTHOR]

In this paper, a three-layer structure of silver particle (AgNP)-dielectric-metal is proposed and constructed based on the characteristics of AgNPs that can excite LSPR (Localized Surface Plasmon Resonance) in free space. In order to overcome the problem of AgNPs easily oxidizing in the air, this paper synthesizes AgNPs using the improved Tollens method and effectively suppresses the coffee-ring effect by changing the solution evaporation conditions, so that the distribution of AgNPs in the deposition area is relatively uniform. The structure proposed in this paper takes advantage of the flexibility of nanoparticle application. The AgNPs deposited on the dielectric layer can effectively localize energy and regulate the LSPR of the device well. The structure can not only achieve precise regulation of the LSPR resonance peak of AgNPs but also can be used as a SERS substrate. [ABSTRACT FROM AUTHOR]

The formation of soot and NOx in ammonia/ethylene flames with varying ammonia ratios was investigated through experimental and numerical analysis. The spatial distribution of the soot volume fraction and NOx concentrations along the flame central line were measured, and the mechanism of soot and NOx formation during ammonia/ethylene co-combustion was analyzed using CHEMKIN 17.0. The experimental results indicated that the soot volume fraction decreases with an increase in ammonia ratio, with the soot peak concentration occurring in the upper region of the flame. The distribution of NOx is complex. In the initial part of the flame, a higher concentration of NOx is generated, and the lower the ammonia ratio, the higher the concentration of NOx. As the combustion process progresses, the concentration of NOx initially decreases and then subsequently increases rapidly, with higher ammonia ratios leading to higher concentrations of NOx. The addition of ammonia results in a decrease in CH3, C2H2, and C3H3, and an increase in CN concentration. This leads to a transformation of carbon atoms within the combustion system, reducing the available carbon for soot formation and suppressing its generation. A higher ammonia ratio increases the likelihood that NH3 will be oxidized to N2, as well as increasing the probability that any generated NO will undergo reduction to N2 through the action of the free radicals NH2 and NH. [ABSTRACT FROM AUTHOR]

Assessing the functional traits and ecological stoichiometric characteristics of dominant species across different life forms within plant communities in karst environments and investigating the inherent connection between them can provide insights into how species adjust their functional attributes in response to habitat heterogeneity. This approach offers a more comprehensive understanding of ecosystem processes and functions in contrast to examination of the taxonomic diversity of species. This study examines the relationship between the functional characteristics of dominant species in plant communities of various life forms in karst environments, focusing on deciduous leaf–soil ecological stoichiometry. The investigation relies on community science surveys, as well as the determination and calculation of plant functional traits and ecological stoichiometries, in plant communities of various life forms in Guizhou (a province of China). The findings of our study revealed considerable variability in the functional trait characteristics of dominant species across different plant-community life forms. Specifically, strong positive correlations were observed among plant height (PLH), leaf area (LA), leaf dry matter content (LDMC), and specific leaf area (SLA) in the dominant species. Additionally, our results indicated no significant differences in leaf ecological stoichiometry among different life forms. However, we did observe significant differences and strong positive correlations between soil N:P, withered material C:N, and apomictic C:P. Furthermore, our study found that plant height (PLH), leaf area (LA), and specific leaf area (SLA) were particularly sensitive to the ecological stoichiometry of soil and apomixis. The results of our study suggest that the functional traits of diverse plant-community life forms in karst regions are capable of adapting to environmental changes through various expressions and survival strategies. The development of various plant-community life forms in karst areas is particularly vulnerable to phosphorus limitation, and the potential for litter decomposition and soil nutrient mineralization is comparatively weaker. The functional traits of various plant-community life forms in karst regions exhibit greater sensitivity to both the soil's C:N ratio and the C:N ratio of apomictic material. Habitat variations may influence the ecological stoichiometric characteristics of the plant leaf–apomictic soil continuum. [ABSTRACT FROM AUTHOR]

In ground-based infrared optical remote sensing systems, the target signal is very weak due to the dynamic strong light background and the movement of dim and small targets. To improve the limit detection capability, background suppression and target enhancement methods are required to be more suitable for this scenario. To solve this problem, we first analyze the image features in the current scene and propose a more complete point target and noise model. Then, we propose a new WY distribution function based on the Fermi–Dirac distribution function and propose an anisotropic filtering method based on this function, which further suppresses the background through the difference results of two steps. Building on the distribution function, we further designed an energy concentration accumulation strategy in nine scaled directions, through which the SNR of the target is effectively improved, and the suppression ability of the background is enhanced. In this dynamic scenario, the method can still detect targets with an average minimum SNR of 0.76. Through quantitative and qualitative experimental analysis, the proposed method has better robustness against extremely weak targets and dynamic backgrounds compared to the same type of algorithms. [ABSTRACT FROM AUTHOR]

The regularized lattice Boltzmann method (RLBM) is an improvement of the lattice Boltzmann method (LBM). The advantage of RLBM is improved accuracy without increasing computational overheads. The paper introduces the method of multi-layer grids, the multi-layer grids have different resolutions which can accurately solve problems in computational fluid dynamics (CFD) without destroying the parallelism of RLBM. Simulating fluid flow usually requires a large number of grid simulations. Therefore, it is necessary to design a parallel algorithm for RLBM based on multi-layer grids. In this paper, a load-balancing-based grid dividing algorithm and an MPI-based parallel algorithm for RLBM on multi-layer grids are proposed. The load balancing-based grid dividing algorithm ensures that the workload is evenly distributed across processes, minimizing the discrepancies in computational load. The MPI-based parallel algorithm for RLBM on multi-layer grids ensures accurate and efficient numerical simulation. Numerical simulations have verified that the proposed algorithms exhibit excellent performance in both 2D and 3D experiments, maintaining high stability and accuracy. The multi-layer grids method is significantly better than single-layer grids in terms of CPU runtime and number of grids required. Comparative analysis with the OpenMP multi-threading method on the multi-layer grid RLBM shows that the proposed algorithm in this paper achieves superior speedup and efficiency. [ABSTRACT FROM AUTHOR]

Perovskites have been largely implemented into optoelectronics as they provide several advantages such as long carrier diffusion length, high absorption coefficient, high carrier mobility, shallow defect levels and finally, high crystal quality. The brisk technological development of perovskite devices is connected to their relative simplicity, high-efficiency processing and low production cost. Significant improvement has been made in the detection performance and the photodetectors' design, especially operating in the visible (VIS) and near-infrared (NIR) regions. This paper attempts to determine the importance of those devices in the broad group of standard VIS and NIR detectors. The paper evaluates the most important parameters of perovskite detectors, including current responsivity (R), detectivity (D*) and response time (τ), compared to the standard photodiodes (PDs) available on the commercial market. The conclusions presented in this work are based on an analysis of the reported data in the vast pieces of literature. A large discrepancy is observed in the demonstrated R and D*, which may be due to two reasons: immature device technology and erroneous D* estimates. The published performance at room temperature is even higher than that reported for typical detectors. The utmost D* for perovskite detectors is three to four orders of magnitude higher than commercially available VIS PDs. Some papers report a D* close to the physical limit defined by signal fluctuations and background radiation. However, it is likely that this performance is overestimated. Finally, the paper concludes with an attempt to determine the progress of perovskite optoelectronic devices in the future. [ABSTRACT FROM AUTHOR]

The escalating concern over global warming has garnered significant international attention, with carbon emission intensity emerging as a crucial barrier to sustainable economic development across various regions. While previous studies have largely focused on annual scales, this study introduces a novel examination of Tianjin's quarterly carbon emission intensity and its influencing factors from 2012 to 2022 using quarterly data and the Logarithmic Mean Divisia Index (LMDI) model. The analysis considers the carbon emission effects of thermal power generation, the power supply structure, power intensity effects, and economic activity intensity. The results indicate a general decline in Tianjin's carbon emission intensity from 2012 to 2020, followed by an increase in 2021 and 2022. This trend, exhibiting significant seasonal fluctuations, revealed the highest carbon emission intensity in the first quarter (an average of 1.4093) and the lowest in the second quarter (an average of 1.0019). Economic activity intensity emerged as the predominant factor influencing carbon emission intensity changes, particularly notable in the second quarter (an average of −0.0374). Thermal power generation and electricity intensity effects were significant in specific seasons, while the power supply structure's impact remained relatively minor yet stable. These findings provide essential insights for formulating targeted carbon reduction strategies, underscoring the need to optimize energy structures, enhance energy efficiency, and account for the seasonal impacts of economic activity patterns on carbon emissions. [ABSTRACT FROM AUTHOR]

The thermal-controlled fracture method has been increasingly focused upon in the high-quality cutting of advanced ceramic materials due to its excellent characteristics. The successful application of this method in cutting ceramics mainly depends on the volumetric heating effect. However, most ceramics are treated using the surface heating mode. For the surface heating mode, the processing quality, including fracture trajectory and fracture quality, is far lower than the industrial application standards. This work was conducted to reveal the mechanism of this processing quality. Experiments involving cutting ceramics in single-surface heating mode indicate that the fracture trajectories of the upper and lower surfaces display a significant inconsistency, and the fracture quality is worse than that using the dual-surface heating mode. A cutting model was established to calculate the thermal stress distribution and to simulate the crack-propagation behaviors. The simulation results show good agreement with the experiment and provide the stress distribution, and are used to understand the reason for the processing quality problem. The mechanism of the trajectory deviation and uneven distribution of the fracture quality is revealed based on the simulation and calculation results. This study helps provide a deep understanding of the processing problems arising from this method and thus helps to innovate high-quality processing methods in this field. [ABSTRACT FROM AUTHOR]

Paddy field leveling is an essential step before rice transplanting. During the operation of a paddy field grader, a common issue is the wrapping of rice straw around the blades, resulting in a low rice straw burial rate. This study focused on analyzing the operating parameters of a disc spring–tooth-combined paddy field grader. A soil–straw mechanism simulation model was created using EDEM 2021 software to simulate the field operation status. Firstly, the single-factor test was carried out, with the working speed, the working depth of the disc cutter roller, and the rotation speed of the cutter roller as the factors and the straw-buried rate (SBR) and the machine forward resistance (MFR) as the test indexes, and the parameter range was optimized. The parameters were optimized by the response surface method (RSM) and machine learning algorithms. The results indicated that the genetic algorithm–back propagation (GA-BP) neural network outperformed other optimization models in terms of prediction accuracy and stability. By utilizing the GA-BP regression model and RSM model for regression fitting, two sets of optimal parameter combinations were obtained. Verification experiments were carried out using two sets of parameter combinations. Taking the average of the experimental results, the simulation results showed that the straw burial rate was 93.47% and the forward resistance was 6487 N for the parameter combinations of RSM, and the straw burial rate was 94.86% and the forward resistance was 6352 N for the parameter combinations of GA-BP; the field experiments showed that the straw burial rate was 92.86% and the forward resistance was 6518 N for the parameter combinations of RSM, and the straw burial rate was 95.17% and the forward resistance was 6249 N for the parameter combinations of GA-BP. The results demonstrated that the GA-BP prediction model exhibited better predictive capabilities compared to the traditional RSM, providing more accurate predictions of the paddy field grader's field operation performance. [ABSTRACT FROM AUTHOR]

In the complex and harsh environment of agriculture, rolling bearings, as the key transmission components in agricultural machinery, are very prone to failure, so research on the intelligent fault diagnosis of agricultural machinery components is critical. Therefore, this paper proposes a new method based on SVD-EDS-GST and ResNet-Vision Transformer (ResViT) for the fault diagnosis of rolling bearings in agricultural machines. Firstly, an experimental platform for rolling bearing failure in agricultural machinery is built, and one-dimensional vibration signals are obtained using acceleration sensors. Next, the signal is preprocessed for noise reduction using singular value decomposition (SVD) combined with the energy difference spectrum (EDS) to solve for the interference of complex noise and redundant components in the vibration signal. Secondly, generalized S-transform (GST) is used to process vibration signals into images. Then, the ResViT model is proposed, where the ResNet34 network is used to replace the image chunking mechanism in the original Vision Transformer model for feature extraction. Finally, an improved Vision Transformer (ViT) is utilized to synthesize global and local information for fault classification. The experimental results show that the proposed method's average accuracy in rolling bearing fault classification for agricultural machinery reaches 99.08%. In addition, compared with SVD-EDS-GST-CNN, SVD-EDS-GST-LSTM, STFT-ViT, GST-ViT, and SVD-EDS-GST-ViT, the accuracy rate was improved by 3.5%, 3.84%, 4.8%, 8.02%, and 0.56%, and the standard deviation was also minimized. [ABSTRACT FROM AUTHOR]

This study proposes a model for the quantitative evaluation of the life-cycle carbon footprints of large sporting events and the uncertainties related to them. The model was used to analyze the case of a mega sporting event in Beijing, China. First, the quantitative model for the evaluation of the carbon footprints of mega sporting events includes a preparation stage, a holding stage, and an end stage. These stages consider the energy and resources used for construction, operation, transportation, catering, and accommodation. Second, this study proposes a prediction model using model-based and simulation-based methods to address the difficulty of obtaining traffic activity. Third, a semi-quantitative method that combines a data quality indicator and stochastic simulation is adopted for the uncertainty analysis of mega sporting events. Finally, a case study is used to indicate that the preparation stage of a mega sporting event accounts for the highest CO2 emissions at 92.1%, followed by 7.5% in the holding stage and 0.4% in the end stage. The total life-cycle CO2 emissions of a sustainable scenario of a mega sporting event in Beijing amount to 205,080.3 t CO2e, and the per capita CO2 emissions during the event's holding stage amount to 0.26 t CO2e/person. The uncertainty in the input parameters is 0.0617, indicating that the uncertainty of the model is low, and the reliability of the results is high. [ABSTRACT FROM AUTHOR]

Fusarium graminearum, a devastating fungal pathogen, causes great economic losses to crop yields worldwide. The present study investigated the potential of Streptomyces pratensis S10 to alleviate F. graminearum stress in wheat seedlings based on plant growth-promoting and resistance-inducing assays. The bioassays revealed that S10 exhibited multiple plant growth-promoting properties, including the production of siderophores, 1-aminocyclopropane-1-carboxylic acid deaminase (ACC), and indole-3-acetic acid (IAA), phosphate solubilization, and nitrogen fixation. Meanwhile, the pot experiment demonstrated that S10 improved wheat plant development, substantially enhancing wheat height, weight, root activity, and chlorophyll content. Consistently, genome mining identified abundant genes associated with plant growth promotion. S10 induced resistance against F. graminearum in wheat seedlings. The disease incidence and disease index reduced by nearly 52% and 65% in S10 pretreated wheat seedlings, respectively, compared with those infected with F. graminearum only in the non-contact inoculation assay. Moreover, S10 enhanced callose deposition and reactive oxygen species (ROS) accumulation and induced the activities of CAT, SOD, POD, PAL, and PPO. Furthermore, the quantitative real-time PCR (qRT-PCR) results indicated that S10 pretreatment increased the expression of SA- (PR1.1, PR2, PR5, and PAL1) and JA/ET-related genes (PR3, PR4a, PR9, and PDF1.2) in wheat seedlings upon F. graminearum infection. In summary, S. pratensis S10 could be an integrated biological agent and biofertilizer in wheat seedling blight management and plant productivity enhancement. [ABSTRACT FROM AUTHOR]

Risk management in electronic component selection is crucial for ensuring inherent system quality dependability in aerospace equipment research and development (R&D). Therefore, it is of great significance to conduct rapid and accurate risk assessment research of electronic components based on engineering practice. This article utilizes the extreme gradient boosting (XGBoost) algorithm and domain knowledge to assess electronic component selection risk. Firstly, an innovative risk assessment system is established for electronic component selection based on business materials analysis and investigation by questionnaire. Then, the values of factors in the system are quantified based on domain knowledge and empirical formulae. Finally, an XGBoost-based risk assessment model is constructed that can explore learning strategies and develop latent features by integrating multiple decision trees. The model is compared against the random forest (RF), support vector machine (SVM) and decision tree (DT) algorithms. Accuracy, precision, recall, and F1 score are used as evaluation indexes. The results obtained from the above algorithms illustrate the effectiveness of the proposed method in electronic component selection risk assessment. [ABSTRACT FROM AUTHOR]

This study advances our understanding of the Jiangnan Orogenic Belt by integrating high-precision geochronological data with interpretations of sedimentary and tectonic environments. Specifically, it addresses the controversy over the geological significance, origins, and tectonic significance of the Shengong Unconfomity: at the base of the Luojiamen Formation. This paper shows that the formation developed over four stages with the primary source of detritus lying in a volcanic arc to the south. The study also reassesses the "unconformity" between the Luojiamen Formation of the Heshangzhen Group and the Zhangcun Formation of the Shuangxiwu Group, concluding that it does not demarcate the end of the orogenic collision between the Cathaysia and Yangtze blocks. [ABSTRACT FROM AUTHOR]

This paper studies the design problem of fault detection (FD) observer for unmanned marine vehicles (UMVs) based on the T-S fuzzy model. Firstly, T-S fuzzy systems are used to approximate the nonlinear dynamics in UMVs. Secondly, to improve the FD performance of UMVs, a new H ∞ / H _ performance index, which depends on the membership functions, is defined. Then, based on the membership-function-dependent H ∞ / H _ performance index, a new fuzzy FD observer strategy, where the fuzzy submodels are not all required to be with the same H _ performance index, is developed to detect the sensor fault in UMVs; the corresponding synthesis conditions of the FD observer are derived based on the Lyapunov theory. Different from the conventional FD strategies, in the proposed membership-function-dependent FD method, the fuzzy submodels—which the system always works on—can have a larger H _ performance index, such that the performance of the FD can be improved. In the end, an example is given to show the effectiveness of the presented method. [ABSTRACT FROM AUTHOR]

Visual simultaneous localization and mapping (VSLAM) is pivotal for intelligent mobile robots. VSLAM systems can be used to identify scenes by obtaining massive amounts of redundant texture information from the environment. However, VSLAM faces a major challenge in dynamic low-light environments, in which the extraction of feature points is often difficult, leading to tracking failure with mobile robots. Therefore, we developed a method to improve the feature point extraction method used for VSLAM. We first used the contrast limited adaptive histogram equalization (CLAHE) method to increase the contrast in low-light images, allowing for the extraction of more feature points. Second, in order to increase the effectiveness of the extracted feature points, the redundant feature points were removed. We developed three conditions to filter the feature points. Finally, the proposed method was tested on popular datasets (e.g., TUM and OpenLORIS-Scene), and the results were compared with those of several traditional methods. The results of the experiments showed that the proposed method is feasible and highly robust in dynamic low-light environments. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) is one of the major causes of insulation accidents in oil-immersed transformers, generating a large number of signals that represent the health status of the transformer. In particular, acoustic signals can be detected by sensors to locate the source of the partial discharge. However, the array, type, and quantity of sensors play a crucial role in the research on the localization of partial discharge sources within transformers. Hence, this paper proposes a novel sensor array for the specific localization of PD sources using COMSOL Multiphysics software 6.1 to establish a three-dimensional model of the oil-immersed transformer and the different defect types of two-dimensional models. "Electric-force-acoustic" multiphysics field simulations were conducted to model ultrasonic signals of different types of PD by setting up detection points to collect acoustic signals at different types and temperatures instead of physical sensors. Subsequently, simulated waveforms and acoustic spatial distribution maps were acquired in the software. These simulation results were then combined with the time difference of arrival (TDOA) algorithm to solve a system of equations, ultimately yielding the position of the discharge source. Calculated positions were compared with the actual positions using an error iterative algorithm method, with an average spatial error about 1.3 cm, which falls within an acceptable range for fault diagnosis in transformers, validating the accuracy of the proposed method. Therefore, the presented sensor array and computational localization method offer a reliable theoretical basis for fault diagnosis techniques in transformers. [ABSTRACT FROM AUTHOR]

The Arctic is one of the most important regions in the world's oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift. [ABSTRACT FROM AUTHOR]

In this paper, the effect of waste rock-wool dosage on the workability, mechanical strength, abrasion resistance, toughness and hydration products of PVA and steel fiber-reinforced mortars was investigated. The results showed that the fluidity of the mortar gradually decreased with the increase in the dosage of waste rock wool, with a maximum reduction of 10% at a dosage of 20%. The higher the dosage of waste rock wool, the greater the reduction in compressive strength. The effect of waste rock wool on strength reduction decreases with increasing age. When the dosage of waste rock wool was 10%, the 28 days of flexural and compressive strengths were reduced by 4.73% and 10.59%, respectively. As the dosage of waste rock wool increased, the flexural-to-compressive ratio increased, and at 20%, the maximum value of 28 days of flexural-to-compressive ratio was 0.210, which was increased by 28.05%. At a 5% dosage, the abraded volume was reduced from 500 mm3 to 376 mm3—a reduction of 24.8%. Waste rock wool only affects the hydration process and does not cause a change in the type of hydration products. It promotes the hydration of the cementitious material system at low dosages and exhibits an inhibitory effect at high dosages. [ABSTRACT FROM AUTHOR]

The KR resistance curve for hydraulic crack propagation in a concrete beam was determined and discussed. A semi-analytical method was introduced to calculate the hydraulic crack propagation in concrete. A series of concrete beams with various hydraulic pressures and initial crack depths were tested, and the hydraulic crack propagation in these beams was calculated. The calculated P-CMOD curves were first verified, and then the calculated KR resistance curve for hydraulic crack propagation was determined. Based on the test results and calculation results, the following conclusions can be drawn: The proposed analysis method can accurately predict the hydraulic crack propagation process in concrete. The KR resistance to hydraulic crack propagation in concrete decreases with the increase in hydraulic pressure but is less influenced by the initial crack depth of the test beams. In addition, the concrete beams collapse immediately under hydraulic fracturing once the KIw curve reaches the KR resistance curve. This indicates that the failure of concrete structures under hydraulic fracturing occurs immediately once the driving force of crack propagation, dominated by the hydraulic pressure in the crack, becomes significant. [ABSTRACT FROM AUTHOR]

The interactions between economic development, environmental sustainability, population growth, and urbanization are vital in assessing the ecological dynamics of urban agglomerations. This study explores the relationship between economic development, environmental sustainability, population growth, and urbanization within the Xia-Zhang-Quan urban agglomeration in Fujian Province from 1989 to 2022. Utilizing Landsat remote sensing images, we calculated the Remote Sensing Ecological Index (RSEI) to evaluate changes in ecological quality. The results show that the average RSEI values for 1989, 2000, 2010, and 2022 were 0.5829, 0.5607, 0.5827, and 0.6195, respectively, indicating an initial decline followed by a significant increase, culminating in an overall upward trend. The spatial distribution of RSEI classification shows that the study area has the largest proportion of mainly "good" ecological quality. The proportion of areas with "excellent" ecological environmental quality has increased (13.41% in 1989 and 25.12% in 2022), while those with "general" quality has decreased (28.03% in 1989 and 21.21% in 2022). Over the past three decades, Xiamen experienced substantial ecological degradation (RSEI change of −0.0897), Zhangzhou showed marked improvement (RSEI change of 0.0519), and Quanzhou exhibited slight deterioration (RSEI change of −0.0396). Central urban areas typically had poorer ecological conditions but showed signs of improvement, whereas non-central urban regions demonstrated significant environmental enhancement. The factor detector analysis identified land use as the dominant factor influencing ecological environmental quality, with precipitation having a relatively minor impact. Interaction analysis revealed that all other factors demonstrated bi-variable enhancement or nonlinear enhancement, suggesting that the interactive effects of these factors are greater than the effects of individual factors alone. Land use consistently showed solid explanatory power. Temperature also exhibited significant influence in 2022 when interacting with other factors. Due to urban planning that can plan for land use, these findings suggest that effective urban planning can harmonize economic development with ecological protection within the Xia-Zhang-Quan urban agglomeration. [ABSTRACT FROM AUTHOR]

The aim of manufacturing large aerospace parts for the three-dimensional scanning field demands high precision and efficiency. However, it may be more challenging to meet the full coverage of the measurement problems for large aerospace parts with the scanning range of traditional three-dimensional scanning methods. This paper establishes a dynamic posturing scanning measurement system for large aerospace parts with a six-degree-of-freedom posturing platform and a six-degree-of-freedom industrial robot linkage. It establishes a mathematical model of dynamic three-dimensional scanning posturing. It proposes a platform attitude adjustment strategy based on the field of view angle of a 3D scanner during the adjustment of a six-degree-of-freedom platform. The dynamic scanning path planning is carried out using the three-dimensional spatial decomposition method, and the vector coordinates of the critical points at the edges of the missing areas of the scan are used to re-scan the missing areas to establish the dynamic scanning paths of large aerospace parts. It is experimentally verified that the system can realize the dynamic scanning of complex curved large aerospace parts. The experimental results show that the measurement efficiency is improved by more than 75%, and the point cloud coverage of the scanning reconstruction is improved by 18% for large aerospace components with complex surfaces. [ABSTRACT FROM AUTHOR]

Rice is a globally important food crop, and it is crucial to accurately and conveniently obtain information on rice fields, understand their spatial patterns, and grasp their dynamic changes to address food security challenges. In this study, Chongqing's Yongchuan District was selected as the research area. By utilizing UAVs (Unmanned Aerial Vehicles) to collect multi-spectral remote sensing data during three seasons, the phenological characteristics of rice fields were analyzed using the NDVI (Normalized Difference Vegetation Index). Based on Sentinel data with a resolution of 10 m, the NDVI difference method was used to extract rice fields between 2019 and 2023. Furthermore, the reasons for changes in rice fields over the five years were also analyzed. First, a simulation model of the rice harvesting period was constructed using data from 32 sampling points through multiple regression analysis. Based on the model, the study area was classified into six categories, and the necessary data for each region were identified. Next, the NDVI values for the pre-harvest and post-harvest periods of rice fields, as well as the differences between them, were calculated for various regions. Additionally, every year, 35 samples of rice fields were chosen from high-resolution images provided by Google. The thresholds for extracting rice fields were determined by statistically analyzing the difference in NDVI values within the sample area. By utilizing these thresholds, rice fields corresponding to six harvesting regions were extracted separately. The rice fields extracted from different regions were merged to obtain the rice fields for the study area from 2019 to 2023, and the accuracy of the extraction results was verified. Then, based on five years of rice fields in the study area, we analyzed them from both temporal and spatial perspectives. In the temporal analysis, a transition matrix of rice field changes and the calculation of the rice fields' dynamic degree were utilized to examine the temporal changes. The spatial changes were analyzed by incorporating DEM (Digital Elevation Model) data. Finally, a logistic regression model was employed to investigate the causes of both temporal and spatial changes in the rice fields. The study results indicated the following: (1) The simulation model of the rice harvesting period can quickly and accurately determine the best period of remote sensing images needed to extract rice fields. (2) The confusion matrix shows the effectiveness of the NDVI difference method in extracting rice fields. (3) The total area of rice fields in the study area did not change much each year, but there were still significant spatial adjustments. Over the five years, the spatial distribution of gained rice fields was relatively uniform, while the lost rice fields showed obvious regional differences. In combination with the analysis of altitude, it tended to grow in lower areas. (4) The logistic regression analysis revealed that gained rice fields tended to be found in regions with convenient irrigation, flat terrain, lower altitude, and proximity to residential areas. Conversely, lost rice fields were typically located in areas with inconvenient irrigation, long distance from residential areas, low population, and negative topography. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization and profound socioeconomic changes, the influx of people from various social strata into cities has led to the phenomenon of residential segregation. Currently, the international community has accumulated profound theoretical foundations and rich practical experiences in the study of residential segregation. This research, primarily based on the WOS literature database, sorts and summarizes relevant studies on residential segregation in recent years (focusing on publications from 2020 to 2024), emphasizing the following four key aspects: (1) tracing the evolution of the theory of residential segregation and analytical methods; (2) analyzing the main characteristics of urban residential segregation; (3) exploring the driving mechanisms and effects of urban residential segregation; and (4) summarizing research trends and providing future perspectives. This study aids urban planners in more accurately identifying areas and characteristics of residential segregation, optimizing urban layouts, and providing richer and more in-depth theoretical support and practical guidance for the field of urban planning science. [ABSTRACT FROM AUTHOR]

To construct a nonlinear fractional-order neural network reflecting the complex environment of the real world, this paper considers the common factors such as uncertainties, perturbations, and delays that affect the stability of the network system. In particular, not only does the activation function include multiple time delays, but the memristive connection weights also consider transmission delays. Stemming from the characteristics of neural networks, two different types of discontinuous controllers with state information and sign functions are devised to effectuate network synchronization objectives. Combining the finite-time convergence criterion and the theory of fractional-order calculus, Mittag-Leffler synchronization conditions for fractional-order multi-delayed memristive neural networks (FMMNNs) are derived, and the upper bound of the setting time can be confirmed. Unlike previous jobs, this article focuses on applying different inequality techniques in the synchronous analysis process, rather than comparison principles to manage the multi-delay effects. In addition, this study removes the restrictive requirement that the activation function has a zero value at the switching jumps, and the discontinuous control protocol in this paper makes the networks achieve synchronization over a finite time, with some advantages in terms of the convergence speed. [ABSTRACT FROM AUTHOR]

To uncover the reservoir characteristics and enrichment law of coal-measure gas in Julu sag, Hebei Province, and achieve co-exploration and co-mining, it is necessary to conduct a comprehensive analysis. In this study, we investigated the characteristics of coal-measure gas accumulation in the Taiyuan Formation and Shanxi Formation in the Julu area. This was achieved by collecting data on coal-measure source rocks and organic geochemistry, which were then combined with regional geological conditions. This study indicates that the coal seams and shales of Shanxi Formation and Taiyuan Formation in the study area serve as the primary source rocks. The predominant macerals found in coal rock are vitrinite. Furthermore, the organic matter type present in shale is primarily categorized as type II2, with the organic matter maturity falling within the immature–mature stage. Based on the simulation results of tectonic-burial history, thermal evolution history, and hydrocarbon generation history in the study area, it is evident that the coal-measure source rocks experienced their first peak of hydrocarbon generation during the Mesozoic era as a result of deep metamorphism. Subsequently, the area experienced uplift and erosion, leading to the release of coal-bearing natural gas. Since the Paleogene period, the coal-bearing source rocks have undergone sedimentary burial and entered the secondary hydrocarbon generation stage, resulting in significant production of oil and gas. Based on the analysis of gas content, buried depth, source rock thickness, and sealing conditions in the study area, it is evident that the potential of coal-measure gas resources in the study area is primarily comprised of shale gas with supplementary coalbed methane. It can be inferred that the deeper areas within the study area hold greater exploration prospects. [ABSTRACT FROM AUTHOR]

The massive integration of distributed renewable energy sources and nonlinear power electronic equipment has given rise to power quality issues such as waveform distortion, voltage instability, and increased harmonic components. Nowadays, the pollution of power quality is becoming increasingly severe, posing a potential threat to the security of the power grid and the stable operation of electrical equipment. Due to the presence of significant noise interference in the collected signals, existing methods still face issues such as low accuracy in disturbance identification and high computational complexity. To address these problems, this paper proposes a hybrid data-driven strategy that can significantly improve the accuracy and speed of identification. Firstly, the wavelet packet transform (WPT) method is employed to denoise the power disturbance signals. Subsequently, the local mean decomposition (LMD) algorithm is used to adaptively decompose the nonlinear and complex time series into multiple product function components. Feature extraction of the disturbance signals is then achieved by calculating entropy values after local mean decomposition, and a feature matrix is constructed from the entropy values of each component for analysis in disturbance identification. Finally, an extreme learning machine (ELM) is employed for the identification and classification of transient power disturbance signals. The verification of numerical examples demonstrates the feasibility and effectiveness of the proposed method in this paper. [ABSTRACT FROM AUTHOR]

For injured and after-stroke patients who temporarily lose their hand's grasping abilities, assisting them in regaining their index finger mobility is very important in the rehabilitation process. In this paper, a finger rehabilitation device based on one degree-of-freedom (DOF) linkage mechanism is designed, aiming to lead the index finger through the flexion–extension trajectory during grasping tasks. Two types of one-DOF mechanisms, a four-bar linkage and a Watt-I six-bar linkage, are synthesized for the task trajectory. Various algorithms such as PSO, GA, and GA–BFGS are adopted and compared for the synthesis of these two types of mechanisms, among which the Watt-I six-bar linkage obtained with GA–BFGS shows the optimal performance in accuracy. Clinical biomechanical data are utilized to perform static analyses of the mechanisms, and the feasibility of the Watt-I six-bar linkage models is tested, compared, and demonstrated. Finally, the prototype of the six-bar linkage as well as a wearable exoskeleton finger rehabilitation device are designed to show how they are applied in the finger rehabilitation scenario. [ABSTRACT FROM AUTHOR]

Soil salinization is a global agro-ecological problem and a major factor impeding agricultural development. Planting salt-tolerant plants to improve saline soils offers both ecological and economic benefits. Currently, there are few studies addressing the combined effects of salt and alkali stress. Quinoa is known for its salinity tolerance. However, research has predominantly focused on the effects of salinity stress on quinoa's morphology and physiology, with its molecular mechanisms remaining unclear. To better understand quinoa's response mechanisms to salinity and alkali stress, we employed RNA-seq technology to analyze transcriptomes under these conditions. We identified 1833 differentially expressed genes (DEGs) under salt stress and 2233 DEGs under alkali stress. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations revealed that quinoa responds to salt and alkali stress through similar mechanisms. Both stresses promoted sucrose synthesis, starch synthesis and catabolism, which increased the osmotic potential of quinoa leaves. Additionally, there was a regulation of the down-regulated expression of the abscisic acid receptor PYR/PYL and the up-regulated expression of the serine/threonine protein kinase (PP2C) gene in the ABA signaling pathway. Contrasting with salt tolerance, the mechanism specific to quinoa's alkalinity tolerance involves the up-regulation of the citric acid cycle via an active γ-aminobutyric acid (GABA) branch, enhancing quinoa's energy metabolism. In summary, our transcriptome analysis revealed key regulatory mechanisms in quinoa's response to saline and alkaline stress. This study deepens the understanding of quinoa's stress response mechanisms and provides theoretical references for the biological improvement of salinized soils. [ABSTRACT FROM AUTHOR]

Soil pollution by heavy metals is a serious environmental concern globally. Hexavalent (VI) chromium (Cr) is one of the main pollutants causing groundwater and soil heavy metal pollution. Miscanthus sinensis is a C4 perennial grass species with a high level of heavy metal tolerance. This species can effectively remove Cr from soils and maintain desirable biomass production under Cr stress. This research aimed to characterize and compare Cr accumulation in 58 genotypes of M. sinensis and to develop Expressed Sequence Tag–Simple Sequence Repeat (EST-SSR) markers associated with Cr tolerance. The results show that the pattern of translocation of Cr in plants differed among the 58 M. sinensis genotypes following treatment of 200 mg/L of Cr6+; however, in most genotypes, the Cr was primarily accumulated in roots. A total of 43,367 EST-SSRs were identified, and 88 EST-SSR primer pairs corresponding to candidate genes involved in Cr accumulation in M. sinensis were selected for validation. Subsequently, 170 polymorphic loci generated from 24 validated EST-SSRs were used for the population structure and marker–trait association analysis. Based on a general linear model (GLM), a total of 46 associations were identified (p < 0.05), with 14 EST-SSRs markers associated with target traits. Among them, four genes related to ABC transporters, wall-associated receptor kinases, as well as two high-affinity sulfate transporters (ST), were identified under Cr stress (p < 0.05). The results of this study help to accelerate the screening across M. sinensis genotypes for desirable traits under Cr stress and provide a platform for M. sinensis genetic improvement and molecular-marker-assisted breeding. [ABSTRACT FROM AUTHOR]

With the global rise in the prevalence of diabetes, diabetic patients need innovative footwear designs to reduce the risk of foot ulcers. This study examined the mechanical properties of diabetic shoe midsoles featuring auxetic lattice structures. Through the construction of finite element models and simulation, this research compared the biomechanical parameter differences in the plantar regions of the metatarsal head, midfoot, and hindfoot when wearing two types of auxetic midsoles with internal angles of 60° and 75° and a non-auxetic midsole with an internal angle of 90° under both walking and running conditions. Compared to the non-auxetic midsole, the auxetic midsoles significantly reduced the peak plantar pressure and optimized the pressure distribution across various plantar regions. Notably, the auxetic 60° midsole reduced the peak plantar pressure by 19.68–55.25% and 16.19–54.39% compared to the non-auxetic 90° midsole during walking and running, respectively. This study also verified that the auxetic midsoles exhibited greater adaptability and compliance to the plantar foot shape, contributing to reductions in plantar pressure in comparisons of deformation values and plantar contact areas across the different midsoles. Auxetic midsoles manufactured using 3D printing technology have significant potential to prevent diabetic foot ulcers and maintain human foot health. This research integrates insights and techniques from materials science and ergonomics, offering a new direction for footwear design. [ABSTRACT FROM AUTHOR]

In order to further optimize the performance of PMMA (Polymethyl Methacrylate) repair mortar. In this paper, fly ash, talcum powder and wollastonite powder are used as fillers to modify the PMMA repair mortar. The effects of these three fillers on the working performance, mechanical performance and durability of PMMA repair mortar were explored. The study shows that the three fillers have good effect on the bond strength of the repair mortar, in which the fly ash has the best effect on the mechanical performance. The mechanical properties of PMMA repair mortar were best when the amount of fly ash was 60 phr (parts per hundred, representing the amount of the material added per hundred parts of PMMA). At this time, the 28 d compressive strength was 71.26 MPa and the 28 d flexural strength was 28.09 MPa, which increased by 13.31% and 15.33%, respectively. Wollastonite powder had the least negative effect on the setting time of the PMMA repair mortar. When the dosage of wollastonite powder was increased to 100 phr, the setting time was only extended from 65 min to 94 min. When the talc dosage was 60 phr, the best improvement in salt freezing resistance was achieved. After 100 cycles of salt freezing, the mass loss rate and strength loss rate decreased to 0.159% and 4.97%, respectively, which were 75.1% and 37.7% higher than that of the control group. The addition of all three fillers reduced the porosity and the proportion of harmful pores in the mortar. This study contributes to a comprehensive understanding how different types of fillers affect PMMA repair mortars, and it also provides theoretical support for the further development of low-temperature rapid repair mortars. [ABSTRACT FROM AUTHOR]

To elucidate the atomic mechanisms of the chemical mechanical polishing (CMP) of silicon carbide (SiC), molecular dynamics simulations based on a reactive force field were used to study the sliding process of silica (SiO2) abrasive particles on SiC substrates in an aqueous H2O2 solution. During the CMP process, the formation of Si-O-Si interfacial bridge bonds and the insertion of O atoms at the surface can lead to the breakage of Si-C bonds and even the complete removal of SiC atoms. Furthermore, the removal of C atoms is more difficult than the removal of Si atoms. It is found that the removal of Si atoms largely influences the removal of C atoms. The removal of Si atoms can destroy the lattice structure of the substrate surface, leading the neighboring C atoms to be bumped or even completely removed. Our research shows that the material removal during SiC CMP is a comprehensive result of different atomic-level removal mechanisms, where the formation of Si-O-Si interfacial bridge bonds is widespread throughout the SiC polishing process. The Si-O-Si interfacial bridge bonds are the main removal mechanisms for SiC atoms. This study provides a new idea for improving the SiC removal process and studying the mechanism during CMP. [ABSTRACT FROM AUTHOR]

To solve the problem of array detection performance in environments with mesoscale eddies, this study utilizes the Gaussian eddy model to describe the sound speed structure disturbed by eddies. Through numerical simulations, the corresponding sound field is obtained, and the transmission loss influenced by the eddy is analyzed. Furthermore, to investigate the relation between the array gain and spatial correlation in the eddy environments, the differences in vertical correlation at different positions and their effects on the vertical array gain of conventional beamforming (CBF) are studied. When the source is around the eddy center, the conclusions drawn are as follows: (1) The presence of an eddy changes the turning-point depth and the sound field distribution, significantly affecting the direct sound region and the first convergence zone, while having a minor impact on the first shadow zone. (2) In different eddy-induced environments, the first convergence zone maintains a high vertical correlation, but the vertical correlation of the direct sound region is greatly influenced by the eddy. (3) The array gain of CBF is consistent with the vertical correlation. When the correlation between each element of the sound field is great, the array gain increases with the number of array elements. [ABSTRACT FROM AUTHOR]

The emergence of carbapenem-resistant Gram-negative pathogens presents a clinical challenge in infection treatment, prompting the repurposing of existing drugs as an essential strategy to address this crisis. Although the anticancer drug 5-fluorouracil (5-FU) has been recognized for its antibacterial properties, its mechanisms are not fully understood. Here, we found that the minimal inhibitory concentration (MIC) of 5-FU against Escherichia coli was 32–64 µg/mL, including strains carrying blaNDM-5, which confers resistance to carbapenems. We further elucidated the antibacterial mechanism of 5-FU against E. coli by using genetic and biochemical analyses. We revealed that the mutation of uracil phosphoribosyltransferase-encoding gene upp increased the MIC of 5-FU against E. coli by 32-fold, indicating the role of the upp gene in 5-FU resistance. Additionally, transcriptomic analysis of E. coli treated with 5-FU at 8 µg/mL and 32 µg/mL identified 602 and 1082 differentially expressed genes involved in carbon and nucleic acid metabolism, DNA replication, and repair pathways. The biochemical assays showed that 5-FU induced bacterial DNA damage, significantly increased intracellular ATP levels and the NAD+/NADH ratio, and promoted reactive oxygen species (ROS) production. These findings suggested that 5-FU may exert antibacterial effects on E. coli through multiple pathways, laying the groundwork for its further development as a therapeutic candidate against carbapenem-resistant bacterial infections. [ABSTRACT FROM AUTHOR]

It is crucial to discover novel antimicrobial drugs to combat resistance. This study investigated the antibacterial properties of halicin (SU3327), an AI-identified anti-diabetic drug, against 13 kinds of common clinical pathogens of animal origin, including multidrug-resistant strains. Employing minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assessments, halicin demonstrated a broad-spectrum antibacterial effect. Time-killing assays revealed its concentration-dependent bactericidal activity against Escherichia coli ATCC 25922 (E. coli ATCC 25922), Staphylococcus aureus ATCC 29213 (S. aureus ATCC 29213), and Actinobacillus pleuropneumoniae S6 (APP S6) after 4 h of treatment at concentrations above the MIC. Halicin exhibited longer post-antibiotic effects (PAEs) and sub-MIC effects (PA-SMEs) for E. coli 25922, S. aureus 29213, and APP S6 compared to ceftiofur and ciprofloxacin, the commonly used veterinary antimicrobial agents, indicating sustained antibacterial action. Additionally, the results of consecutive passaging experiments over 40 d at sub-inhibitory concentrations showed that bacteria exhibited difficulty in developing resistance to halicin. Toxicology studies confirmed that halicin exhibited low acute toxicity, being non-mutagenic, non-reproductive-toxic, and non-genotoxic. Blood biochemical results suggested that halicin has no significant impact on hematological parameters, liver function, and kidney function. Furthermore, halicin effectively treated respiratory A. pleuropneumoniae infections in murine models. These results underscore the potential of halicin as a new antibacterial agent with applications against clinically relevant pathogens in veterinary medicine. [ABSTRACT FROM AUTHOR]

Brown-rot fungus is one of the important medicinal mushrooms, which include some species within the genus Fomitopsis. This study identified wild macrofungi collected from a broad-leaved tree in Liaoning Province as Fomitopsis palustris using both morphological and molecular methods. To elucidate the potential medicinal and economic value of F. palustris, we conducted single-factor and orthogonal tests to optimize its mycelium culture conditions. Subsequently, we completed liquid culture and domestic cultivation based on these findings. Furthermore, crude polysaccharides were extracted from the cultivated fruiting bodies of F. palustris and their antioxidant activity was evaluated using chemical methods and cell-based models. The results showed that the optimal culture conditions for F. palustris mycelium were glucose as the carbon source, yeast extract powder as the nitrogen source, pH 6.0, and a temperature of 35 °C. Moreover, temperature was found to have the most significant impact on mycelial growth. The liquid strains were fermented for 6 days and then inoculated into a cultivation substrate composed of broadleaf sawdust, resulting in mature fruiting bodies in approximately 60 days. The crude polysaccharides extracted from the cultivated fruiting bodies of F. palustris (FPPs) possess in vitro scavenging abilities against DPPH radicals and OH radicals, as well as a certain ferric-reducing antioxidant power. Additionally, FPPs effectively mitigated H2O2-induced oxidative stress in RAW264.7cells by enhancing the intracellular activity of antioxidant enzymes such as SOD and CAT, scavenging excess ROS, and reducing MDA levels. This study provides preliminarily evidence of the potential medicinal and economic value of F. palustris and offers initial data for the future development and utilization of this species. [ABSTRACT FROM AUTHOR]

HSG (high-sulfur gas) reservoirs are prevalent globally, yet their exploitation is hindered by elevated levels of hydrogen sulfide. A decrease in temperature and pressure may result in the formation of sulfur deposits, thereby exerting a notable influence on gas production. Test instruments are susceptible to significant corrosion due to the presence of hydrogen sulfide, resulting in challenges in obtaining bottom hole temperature and pressure test data. Consequently, a WTD (wellbore temperature distribution) model incorporating sulfur precipitation was developed based on PPP (physical property parameter), heat transfer, and GSTP (gas–solid two-phase) flow models. The comparison of a 2.53% temperature error and a 4.80% pressure error with actual field test data indicates that the established model exhibits high accuracy. An analysis is conducted on the impact of various factors, such as production, sulfur layer thickness, reservoir temperature, and reservoir pressure, on the distribution of the wellbore temperature field and pressure field. Increased gas production leads to higher wellhead temperatures. The presence of sulfur deposits reduces the flow area and wellhead pressure. A 40% concentration of hydrogen sulfide results in a 2 MPa pressure drop compared to a 20% concentration. Decreased reservoir pressure and temperature facilitate the formation of sulfur deposits at the wellhead. [ABSTRACT FROM AUTHOR]

With the continuous improvement in production efficiency and quality of life, the requirements of electrical equipment for power quality are also increasing. Accurate detection of various power quality disturbances is an effective measure to improve power quality. However, in practical applications, the dataset is often contaminated by noise, and when the dataset is not sufficient, the computational complexity is too high. Similarly, in the recognition process of artificial neural networks, the local optimum often occurs, which ultimately leads to low recognition accuracy for the trained model. Therefore, this article proposes a power quality disturbance classification strategy based on the variational mode decomposition (VMD) and improved support vector machine (SVM) algorithms. Firstly, the VMD algorithm is used for preprocessing disturbance denoising. Next, based on the analysis of typical fault characteristics, a multi-SVM model is used for disturbance classification identification. In order to improve the recognition accuracy, the improved Grey Wolf Optimization (IGWO) algorithm is used to optimize the penalty factor and kernel function parameters of the SVM model. The results of the final case study show that the classification accuracy of the proposed method can reach over 98%, and the recognition accuracy is higher than that of the other models. [ABSTRACT FROM AUTHOR]

This paper addresses integral sliding mode output feedback fault-tolerant control (FTC) of unmanned marine vessels (UMVs) with unknown premise variables and actuator faults. Due to the complexity of the marine environment, the presence of uncertainties in the yaw angle renders the premise variables in the Takagi–Sugeno (T–S) fuzzy model of UMVs unknown. Consequently, traditional integral sliding mode techniques become infeasible. To address this issue, a control strategy combining integral sliding mode based on output feedback with a compensator utilizing switching mechanisms is proposed. First, a radial basis function neural network is used to approximate the nonlinear terms in the UMV T–S fuzzy model. In addition, an integral sliding mode surface is constructed based on fault estimation information and membership function estimation. On this basis, an FTC scheme based on integral sliding mode output feedback is developed to ensure that the UMV system is asymptotically stable and satisfies the prescribed H ∞ performance index. Finally, simulation results are provided to demonstrate the effectiveness of the presented control strategy. [ABSTRACT FROM AUTHOR]

This study investigates the enhancement of wear resistance in CuCrZr rails through the plasma cladding of CuCrZr-GO coatings with a varying graphene oxide (GO) content. The microstructure, phase composition, and mechanical properties of CuCrZr coatings containing 0%, 0.2%, 0.4%, 0.6%, and 0.8% GO were examined using scanning electron microscopy (SEM), X-ray diffraction (XRD), ESD surface scanning, friction and wear tests, and hardness analysis. The findings indicated that increasing the GO content from 0% to 0.6% results in a transition in the coating microstructure from columnar to equiaxed crystals, leading to an improved density. However, at 0.8% GO, numerous porosity defects were observed. The coating containing 0.6% graphene oxide (GO) exhibited a superior performance, with a hardness of 75, a friction coefficient of approximately 0.7, and a wear mass of 2.84 mg under a 10 N load. In comparison to the CuCrZr coating lacking GO, the hardness showed an increase of around 4.8%, the friction coefficient decreased by approximately 5.1%, and the wear mass diminished by 59.4%. These findings hold significant implications for extending the operational lifespan of electromagnetic railguns. [ABSTRACT FROM AUTHOR]

This study investigates the effects of ambient illumination and negatively polarized text color on visual fatigue, exploring the issue of visual fatigue when using visual display terminals in low-illumination environments. The research methodology utilizes an experimental design to collect data on changes in pupil accommodation and blink rate through an eye tracker. Participants completed a reading task while exposed to various text colors and ambient light conditions to evaluate visual fatigue and cognitive performance. The study's findings suggest that text color significantly affects visual fatigue, with red text causing the highest level of visual fatigue and yellow text causing the lowest level of visual fatigue. Improvements in ambient lighting reduce visual fatigue, but the degree of improvement varies depending on the text color. Additionally, cognitive performance is better when using yellow and white text but worse when using red text. Yellow text is the most effective choice for reducing visual fatigue under negative polarity. Increasing ambient lighting can also improve visual fatigue in low-illumination conditions. These findings will offer valuable guidance for designing visual terminal device interfaces, especially for low-illumination or night environments, to minimize visual fatigue and improve user experience. [ABSTRACT FROM AUTHOR]

Mainstream semi-supervised learning (SSL) techniques, such as pseudo-labeling and contrastive learning, exhibit strong generalization abilities but lack theoretical understanding. Furthermore, pseudo-labeling lacks the label enhancement from high-quality neighbors, while contrastive learning ignores the supervisory guidance provided by genuine labels. To this end, we first introduce a generalized bias-variance decomposition framework to investigate them. Then, this research inspires us to propose two new techniques to refine them: neighbor-enhanced pseudo-labeling, which enhances confidence-based pseudo-labels by incorporating aggregated predictions from high-quality neighbors; label-enhanced contrastive learning, which enhances feature representation by combining enhanced pseudo-labels and ground-truth labels to construct a reliable and complete symmetric adjacency graph. Finally, we combine these two new techniques to develop an excellent SSL method called GBVSSL. GBVSSL significantly surpasses previous state-of-the-art SSL approaches in standard benchmarks, such as CIFAR-10/100, SVHN, and STL-10. On CIFAR-100 with 400, 2500, and 10,000 labeled samples, GBVSSL outperforms FlexMatch by 3.46%, 2.72%, and 2.89%, respectively. On the real-world dataset Semi-iNat 2021, GBVSSL improves the Top-1 accuracy over CCSSL by 4.38%. Moreover, GBVSSL exhibits faster convergence and enhances unbalanced SSL. Extensive ablation and qualitative studies demonstrate the effectiveness and impact of each component of GBVSSL. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) technology is widely used in integrated radar and communication systems (IRCSs). Moreover, index modulation (IM) is a reliable OFDM transmission scheme in the field of communication, which transmits information by arranging several distinguishable constellations. In this paper, we propose a sparse reconstruction-based joint signal processing scheme for integrated MIMO-OFDM-IM systems. Combining the advantages of MIMO and OFDM-IM technologies, the integrated MIMO-OFDM-IM signal design is realized through the reasonable allocation of bits and subcarriers, resulting in better intercarrier interference (ICI) resistance and a higher transmission efficiency. Taking advantage of the sparseness of OFDM-IM, an improved target parameter estimation method based on sparse signal reconstruction is explored to eliminate the influence of empty subcarriers on the matched filtering at the receiver side. In addition, an improved sequential Monte Carlo signal detection method is introduced to realize the efficient detection of communication signals. The simulation results show that the proposed integrated system is 5 dB lower in the peak sidelobe ratio (PSLR) and 1.5 × 10 5 lower in the number of complex multiplications than the latest MIMO-OFDM system and can achieve almost the same parameter estimation performance. With the same spectral efficiency, it has a lower bit error rate (BER) than existing methods. [ABSTRACT FROM AUTHOR]

In cation–anion co-doping, rare earth elements excel at regulating the electronic structure of perovskites, leading to their improved photocatalytic performance. In this regard, the impact of co-doping rare earth elements at the Ba and Ti sites in BaTiO3 on its electronic and photocatalytic properties was thoroughly investigated based on 2 × 2 × 2 supercell structures of BaTiO3 with different La concentrations of 12.5% and 25% using DFT calculations. The band structure, density of states, charge density difference, optical properties, and the redox band edge of the co-doped models mentioned above were analyzed. The results indicated that the BaTiO3 structure co-doped with 25% La at the Ti site exhibited higher absorption in the visible range and displayed a remarkable photocatalytic water-splitting performance. The introduced La dopant at the Ti site effectively reduced the energy required for electronic transitions by introducing intermediate energy levels within the bandgap. Our calculations and findings of this study provide theoretical support and reliable predictions for the exploration of BaTiO3 perovskites with superior photocatalytic performances. [ABSTRACT FROM AUTHOR]

The accuracy of cosmic ray observations by the Large High Altitude Air Shower Observatory Wide Field-of-View Cherenkov/Fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples over 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and Ångström Exponent (AE) at 440–870 nm (AE440–870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD is in the order of spring > summer > autumn = winter. The monthly average maximum of AOD440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE440–870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India regions. These results are presented for the first time, providing a detailed analysis of aerosol seasonality and origins, which have not been thoroughly documented before in this region, also enriching the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau. [ABSTRACT FROM AUTHOR]