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At present, tomato transplanting in facility agriculture is mainly manual operation. In an attempt to resolve the problems of high labor intensity and low efficiency of manual operation, this paper designs a clip stem automatic transplanting and seedling picking device based on the yolov5 algorithm. First of all, through the study of the characteristics of tomato seedlings of different seedling ages, the age of tomato seedlings suitable for transplanting was obtained. Secondly, the improved yolov5 algorithm was used to determine the position and shape of tomato seedlings. By adding a lightweight upsampling operator (CARAFE) and an improved loss function, the feature extraction ability and detection speed of tomato seedling stems were improved. The accuracy of the improved yolov5 algorithm reached 92.6%, and mAP_0.5 reached 95.4%. Finally, the seedling verification test was carried out with tomato seedlings of about 40 days old. The test results show that the damage rate of the device is 7.2%, and the success rate is not less than 90.3%. This study can provide a reference for research into automatic transplanting machines.

Background: Myocardial Infarction (MI) and severe mental disorders (SMDs) are two types of highly prevalent and complex disorders and seem to have a relatively high possibility of mortality. However, the contributions of common and rare genetic variants to their comorbidity arestill unclear. Methods: We conducted a combined genome-wide association study (GWAS) and exome-wide association study (EWAS) approach. Results: Using gene-based and gene-set association analyses based on the results of GWAS, we found the common genetic underpinnings of nine genes (GIGYF2, KCNJ13, PCCB, STAG1, HLA-C, HLA-B, FURIN, FES, and SMG6) and nine pathways significantly shared between MI and SMDs. Through Mendelian randomization analysis, we found that twenty-seven genes were potential causal genes for SMDs and MI. Based on the exome sequencing data of MI and SMDs patients from the UK Biobank, we found that MUC2 was exome-wide significant in the two diseases. The gene-set analyses of the exome-wide association study indicated that pathways related to insulin processing androgen catabolic process and angiotensin receptor binding may be involved in the comorbidity between SMDs and MI. We also found that six candidate genes were reported to interact with known therapeutic drugs based on the drug–gene interaction information in DGIdb. Conclusions: Altogether, this study revealed the overlap of common and rare genetic underpinning between SMDs and MI and may provide useful insights for their mechanism study and therapeutic investigations.

As an important member of innate immunity, macrophages show remarkable plasticity and heterogeneity, and play an important role in immune regulation, tissue development, homeostasis of the internal environment and injury repair. However, the excessive activation of macrophages is closely related to the occurrence and development of many diseases. The prenylated flavonoid structure is one of the characteristic structures isolated from Sophora flavescens, with anti-inflammatory, anti-tumor, anti-allergy and other effects. In this study, the effects of (2R)-3β,7,4′-trihydroxy-5-methoxy-8-prenylflavanone (TMP), a prenylated dihydroflavonol, on the polarization and phagocytosis of macrophages were systematically studied. In LPS-induced M1-type macrophages, TMP dose-dependently inhibited the expression of COX-2, iNOS and the secretion of NO, IL-1β, IL-6 and IL-18, showing an inhibitory effect on M1 polarization. Further experiments revealed that it was related to the inhibition of TLR4-related AKT/mTOR, MAPK and NF-κB signaling pathways; in IL-4-induced M2-type macrophages, TMP down-regulated the expression of M2-related Arg1, IL-10, TGF-β, CD206 and CD163, as well as the phosphorylation levels of AKT1 and STAT6. For macrophages in a physiological state, it was very important for cells to return from a stress state to a phenotypic stability in the M0 state. These results indicated that TMP negatively regulated the M1/M2 polarization of macrophages, and made them tend to M0 homeostasis, which might provide new theoretical and data support for explaining the anti-inflammatory immunoregulatory activity of Sophora flavescens.

Understanding the relationship between climate, snow cover, and vegetation Net Primary Productivity (NPP) in the Tibetan Plateau (TP) is crucial. However, the role of snow cover in influencing the NPP remains unclear. This study investigates the connection between the NPP and snow phenology (SP) across the TP from 2011 to 2020. Interannual trends were assessed using the Theil–Sen non-parametric regression approach combined with the Mann–Kendall test. Additionally, the pathways through which snow cover affects the NPP, considering various environmental factors, were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Approximately 10.72% of the TP showed a significant decrease in the NPP, accompanied by advancing trends in the Snow Onset Date (SOD) and Snow End Date (SED), as well as a gradual decrease in the Snow Cover Duration (SCD). The PLS-SEM results reveal that precipitation and soil temperature significantly influenced the NPP, with total effects of 0.309 and 0.206 in the SCD structural equation. Temperature had a relatively strong indirect effect on the NPP through its influence on the SOD and SCD, contributing 16% and 10% to the total effect, respectively. Neglecting the mediating effect of SP underestimates the environmental impact on the NPP. This study highlights how environmental factors influence the NPP through snow cover changes as the biomass increases, thereby enhancing our understanding of SP’s impact on the TP.

With the rapid development of mobile edge computing (MEC) and wireless power transfer (WPT) technologies, the MEC-WPT system makes it possible to provide high-quality data processing services for end users. However, in a real-world WPT-MEC system, the channel gain decreases with the transmission distance, leading to “double near and far effect” in the joint transmission of wireless energy and data, which affects the quality of the data processing service for end users. Consequently, it is essential to design a reasonable system model to overcome the “double near and far effect” and make reasonable scheduling of multi-dimensional resources such as energy, communication and computing to guarantee high-quality data processing services. First, this paper designs a relay collaboration WPT-MEC resource scheduling model to improve wireless energy utilization efficiency. The optimization goal is to minimize the normalization of the total communication delay and total energy consumption while meeting multiple resource constraints. Second, this paper imports a BK-means algorithm to complete the end terminals cluster to guarantee effective energy reception and adapts the whale optimization algorithm with adaptive mechanism (AWOA) for mobile vehicle path-planning to reduce energy waste. Third, this paper proposes an immune differential enhanced deep deterministic policy gradient (IDDPG) algorithm to realize efficient resource scheduling of multiple resources and minimize the optimization goal. Finally, simulation experiments are carried out on different data, and the simulation results prove the validity of the designed scheduling model and proposed IDDPG.

Dam seepage significantly poses a serious threat to both the reservoir safety and the ecological health of the surrounding area. Characterizing and quantifying seepage zones is essential for effective risk mitigation and reinforcement measures. In this study, Electrical Resistivity Tomography (ERT) was applied to detect seepage on a reservoir dam. The ERT survey included three survey lines along the dam. The results indicated low resistivity in seepage zones, showing a distribution extending to the deep section in the middle of the dam and shallow section on both sides of the dam. The reservoir water came out to the ground surface in the downstream from seepage zones. Five seepage models were constructed to quantify seepage based on geological information. The models were further modeled based on the ERT results. Simulated results revealed the annual seepage of the reservoir is 78,880.16 m3. However, 75.5% of the total seepage is contributed by a region representing 50% of the dam. This concentrated seepage should draw the attention of future safety monitoring and reinforcement efforts. This study combines geophysics, geological, and numerical simulation to quantify dam seepage. This allows for the development of more scientifically sound solutions for preventing seepage and improving drainage ability in reservoir dams.

Investigating the seeding mechanism of precision seeders is of great significance for improving the quality of cotton sowing operations. This paper designs a rotary type-hole cotton precision mulching dibbler. The main factors influencing the entry of cotton seeds into the seed wheel holes during the seeding process are then theoretically analyzed. Following this, an accurate discrete element model of coated cotton seeds is established and combined with a discrete element method (DEM) and multi-body dynamics (MBD)-coupled simulation model of the seed drill for seed picking and planting. Simulation experiments on the seeding performance of the precision dibbler were performed to study the influence of the seed wheel structure and motion parameters on the picking and planting performance under different speeds. The optimal parameter combination for the seed wheel is obtained through optimization experiments, and a precision dibbler is manufactured for bench testing. The bench test results are consistent with the simulation test results. At the precision dibbler rotation speed of 16 r/min, the qualified index reaches a maximum value of 93.28%, the skip sowing index increases with the precision dibbler rotation speed, and the re-sowing index decreases as the speed increases. These optimization results significantly improved seeding precision and efficiency and are of great significance for the reliability and effectiveness of cotton sowing operations.

As a key prerequisite for the promotion of withdrawal from rural homesteads (WRH), farmers’ willingness to withdraw has long attracted extensive attention. This study proposes an analytical framework for understanding rural households’ WRH intentions integrating farmer differentiation and environmental cognition (EC), and identifies the influencing factors, using surveyed data of 842 rural households collected in two pilot villages in Hubei Province. Binary logistic regression was applied to explore the impact of factors and the influencing mechanism. The results show that both farmer differentiation and EC have a significant impact on their willingness to withdraw from homesteads. Most factors are positively related to villagers’ preference for WRH, except the age of household head, share of agricultural income in annual household income, and satisfaction with existing rural infrastructure. The findings emphasize the combined roles of farmer differentiation and EC in shaping the willingness of WRH, providing a basis for other regions to benefit from the experiences in pilot areas and thus better implement the policy.

The inactivated quadrivalent influenza vaccine (IIV4) and the 23-valent pneumococcal polysaccharide vaccine (PPSV23) have been administered for years and could be administered concomitantly if necessary. However, the immunogenicity and safety of the concomitant administration of these two vaccines have not been well documented, especially in the Chinese population. In this study, 480 participants aged 60 years and older were randomly assigned to the concomitant administration group (C group) or the separate administration group (S group) to receive IIV4 and PPSV23 either concomitantly or separately. Blood samples were collected before and 28 days after each vaccination. The antibodies against four influenza virus strains and twenty-three pneumococcus serotypes were tested. The results showed that the geometric mean titer (GMT) ratios (C group to S group) for the four influenza strains ranged from 0.72 to 0.95, with the lower limits of the 95% confidence intervals (CIs) ranging from 0.51 to 0.75, and the geometric mean concentration (GMC) ratios for the 23 pneumococcal serotypes ranged from 0.80 to 1.00, with the lower limits of 95% CIs ranging from 0.67 to 0.86. All values met the predefined criteria for non-inferiority. The incidence of adverse events was 0.63% in the C group and 1.56% in the S group. No serious adverse events were observed. In conclusion, the immunogenicity of the concomitant administration of IIV4 and PPSV23 was non-inferior to that of the separate administration, and the safety profile was favorable in adults aged 60 years and older in China.

Inflammatory processes in the brain can exert important neuroprotective functions. However, in neurological and psychiatric disorders, it is often detrimental due to chronic microglial over-activation and the dysregulation of cytokines and chemokines. Growing evidence indicates the emerging yet prominent pathophysiological role of neuroinflammation in the development and progression of these disorders. Despite recent advances, there is still a pressing need for effective therapies, and targeting neuroinflammation is a promising approach. Therefore, in this study, we investigated the anti-neuroinflammatory potential of a marketed and quantified proprietary herbal extract of Ginkgo biloba leaves called EGb 761 (10–500 µg/mL) in BV2 microglial cells stimulated by LPS (10 ng/mL). Our results demonstrate significant inhibition of LPS-induced expression and release of cytokines tumor necrosis factor-α (TNF-α) and Interleukin 6 (IL-6) and chemokines C-X-C motif chemokine ligand 2 (CXCL2), CXCL10, c-c motif chemokine ligand 2 (CCL2) and CCL3 in BV2 microglial cells. The observed effects are possibly mediated by the mitogen-activated protein kinases (MAPK), p38 MAPK and ERK1/2, as well as the protein kinase C (PKC) and the nuclear factor (NF)-κB signaling cascades. The findings of this in vitro study highlight the anti-inflammatory properties of EGb 761 and its therapeutic potential, making it an emerging candidate for the treatment of neuroinflammatory diseases and warranting further research in pre-clinical and clinical settings.

Trametes lactinea polysaccharides have a high medicinal value; however, we still know little about the structure and bioactivity of intracellular and extracellular polysaccharides in the mycelial liquid fermentation of T. lactinea. This study analyzed the structures of intracellular (IP-1, IP-2, and IP-3) and extracellular (EP-1 and EP-2) polysaccharide components isolated from T. lactinea liquid fermentation, as well as investigated their antioxidant, antibacterial, and immunomodulatory properties. The results showed that IP-3 was the only component with a triple-helix structure, while the other four components did not possess this structure. IP3 has a higher molecular weight, flavonoid, and total phenolic content compared to other components. Both intracellular and extracellular polysaccharide components exhibited strong scavenging abilities against ABTS and DPPH radicals. The components showed limited antibacterial effects against four types of bacteria (Staphylococcus aureus, Bacillus subtilis, Erwinia carotovora, and Escherichia coli), and were found to be non-toxic to RAW264.7 cells, even promoting cell proliferation. Furthermore, within a specific concentration range, all components enhanced the phagocytic activity of RAW264.7 cells, increased the secretion of NO, TNF-α, and IL-6, and demonstrated concentration-dependent effects, with IP-3 displaying the most potent immunomodulatory activity. This study shows a high potential for the development and utilization of polysaccharides derived from the liquid fermentation of T. lactinea mycelium.

The Lengjimanda plate is situated in the middle section of the Da Hinggan mountains, in the eastern section of the Tianshan Xingmeng orogenic belt. To determine the formation age of the volcanic rocks in the Longjiang formation in this area, to explore their origin and tectonic background, and to reconstruct the geodynamic evolution of the region, this study conducted petrological, zircon U–Pb geochronological, geochemical, and isotopic analyses of the volcanic rocks in the Longjiang formation. The Longjiang formation’s volcanic rocks are primarily composed of trachyandesite, trachyte trachydacite, and andesite, which are intermediate basic volcanic rocks. They are enriched in large-ion lithophile elements, are depleted in high-field-strength elements, are significantly fractionated between light and heavy rare earth elements, and exhibit a moderate negative Eu anomaly in most samples. The results of the LA–ICP–MS zircon U–Pb dating indicate that the volcanic rocks in this group were formed in the Early Cretaceous period at 129.1 ± 0.82 Ma. The zircon εHf(t) ranges from +1.13 to +43.77, the tDM2 ranges from +655 to +1427 Ma, the initial Sr ratio (87Sr/86Sr)i ranges from 0.7030 to 0.7036, and the εNd(t) ranges from +2.1 to +6.6. Based on the geochemical compositions and isotopic characteristics of the rocks, the initial magma of the volcanic rocks in the Longjiang formation originated from the partial melting of basaltic crustal materials, with a source material inferred to be depleted mantle-derived young crustal. These rocks were formed in a superimposed post-collisional and continental arc environment, possibly associated with the Mongol-Okhotsk Ocean closure and the oblique subduction of the Pacific plate. This study addresses a research gap regarding the volcanic rocks of the Longjiang formation in this area. Its findings can be applied to exploration and prospecting in the region.

Hydrophobic surfaces have attracted great attention due to their ability to repel water, and metallic surfaces are particularly significant as they have several benefits, for example they self-clean and do not corrode in marine environments, but also have several applications in the aircraft, building and automobile industries. Tungsten is an ideal material for metallic surfaces due to its remarkable mechanical properties. However, conventional micromachining methods of micro- or nanostructures, including mechanical fabrication and laser and wet etching are incapable of balancing functionality, consistency and cost. Inspired by the etching process of silicon, deep etching of bulk tungsten has been developed to achieve versatile microstructures with the advantages of high efficiency, large scale and low cost. In this article, fabrication methods of tungsten-based hydrophobic surfaces using an ICP deep etching process were proposed. Micro- or hierarchical structure arrays with controllable sidewall profiles were fabricated by optimizing etching parameters, which then exhibited hydrophobicity with contact angles of up to 131.8°.

Accurate diagnostic techniques and effective therapeutic methods are required to treat H. pylori. The application of chicken single-chain variable fragment (scFv) antibodies may diagnose and treat H. pylori. This study used the phage display technique to construct a chicken-derived immune scFv antibody library against H. pylori. Total RNA was extracted from the spleens of five immunized chickens and reverse transcribed into cDNA. A fragment of scFv was produced by overlap extension PCR and cloned into a pHEN2 phagemid vector. After the package with the M13KO7 helper phage, the recombinant HpaA protein was used as a target antigen to validate the screening ability of our antibody library by bio-panning. The dilution counting results showed that the size of the primary antibody library was estimated to be 1 × 109 cfu/mL. PCR analysis of 47 clones from the library revealed that about 100% of the clones were positive with scFv fragments, and there were no identical sequences, indicating the good diversity of the antibody library. After three rounds of bio-panning, high-affinity antibodies against recombinant HpaA protein were successfully obtained. The selected antibody specifically recognized HpaA protein in nine different H. pylori strains, confirming the screening ability of our library. The chicken immune scFv antibody library against H. pylori was successfully constructed, and the antibody library’s screening ability was validated by selecting specific scFv antibodies against recombinant HpaA and clinical strains. It provided a simple and rapid method to obtain antibodies against H. pylori for diagnosis or treatment.

Chronic inflammation is driven by proinflammatory cytokines such as interleukin 6 (IL-6), tumor necrosis factor-α (TNF-α), and chemokines, such as c-c motif chemokine ligand 2 (CCL2), CCL3, C-X-C motif chemokine ligand 2 (CXCL2), and CXCL10. Inflammatory processes of the central nervous system (CNS) play an important role in the pathogenesis of various neurological and psychiatric disorders like Alzheimer’s disease, Parkinson’s disease, and depression. Therefore, identifying novel anti-inflammatory drugs may be beneficial for treating disorders with a neuroinflammatory background. The G-protein-coupled receptor 55 (GPR55) gained interest due to its role in inflammatory processes and possible involvement in different disorders. This study aims to identify the anti-inflammatory effects of the coumarin-based compound KIT C, acting as an antagonist with inverse agonistic activity at GPR55, in lipopolysaccharide (LPS)-stimulated BV2 microglial cells in comparison to the commercial GPR55 agonist O-1602 and antagonist ML-193. All compounds significantly suppressed IL-6, TNF-α, CCL2, CCL3, CXCL2, and CXCL10 expression and release in LPS-treated BV2 microglial cells. The anti-inflammatory effects of the compounds are partially explained by modulation of the phosphorylation of p38 mitogen-activated protein kinase (MAPK), p42/44 MAPK (ERK 1/2), protein kinase C (PKC) pathways, and the transcription factor nuclear factor (NF)-κB, respectively. Due to its potent anti-inflammatory properties, KIT C is a promising compound for further research and potential use in inflammatory-related disorders.

Broccoli is a rich source of diverse bioactive compounds, but how their contents are influenced by different growing seasons and variations in broccoli head sizes remains elusive. To address this question, we quantified sixteen known bioactive compounds and seven minerals in broccoli with varying head sizes obtained in two different growing seasons. Our results suggest that the contents of vitamin C, total phenols, carotenoids, and glucoraphanin were significantly higher in samples from the summer–autumn season, showing increases of 157.46%, 34.74%, 51.80%, and 17.78%, respectively, compared with those from the winter–spring season. Moreover, chlorogenic acid is a phenolic compound with relatively high contents among the six detected, while beta-sitosterol is the sterol with relatively high contents. Further, principal component analysis was conducted to rank the comprehensive scores of the profiles of phenolic compounds, phytosterols, and minerals, demonstrating that the broccoli samples grown during the summer–autumn season achieved the highest composite scores. Our results indicate that broccoli heads from the summer–autumn season are richer in a combination of bioactive compounds and minerals than those from the winter–spring season based on the composite score. This study extends our understanding of the nutrition profiles in broccoli and also lays the foundation for breeding broccoli varieties with improved nutrition quality.

As a strong interference source for the all-time optical imaging surveillance of maritime targets, sea surface glare is difficult to mitigate accurately because of its time-varying characteristics due to lighting conditions and seawater fluctuations. In this paper, we propose an adaptive suppression approach to sea surface glare, which establishes a geographic polarization suppression model based on real-time information regarding geographic positioning and the orientation information of the floating platform, and also combines dynamic polarization control and pixel normalization to achieve adaptive suppression of sea surface glare. Experimental results show that this approach can mitigate the influence of rapidly changing glare effectively, and the SSIM indexes between the images without glare and those with glare suppression of the same scenes exceed 0.8, which is suitable for all-time glare suppression on the sea surface under natural lighting conditions.

Investigating the mathematical and geometric principles embedded in ancient classic architecture is a significant tradition in the history of architectural development. Drawing inspiration from the modular design and creative ideology based on the geometric proportions of squareness and roundness in ancient Chinese architecture, we propose a new mode of squareness and roundness composition based on scale proportion specifically for the design of multi-story buildings. Taking Yingxian Wooden Pagoda as the case study, we not only re-evaluate the modular system and proportional rules followed in the design of the entire pagoda, but also reveal the technical approaches and geometric rules for effectively controlling the form of multi-story buildings. In particular, the mode of squareness and roundness composition based on scale proportion, utilizing a modular grid combined with squareness and roundness drawings as decision-making tools, can control the scale and proportion of buildings across different design dimensions and organically coordinate the design of multi-story buildings’ plans and elevations. Thus, it can achieve an effective balance of multi-story architectural forms. This study has potential applications in the creation of traditional multi-story buildings and heritage restoration projects, and offers valuable insights for future research on ancient multi-story buildings.

The tracking of carbon and aerosol co-emissions is essential for environmental management. Satellite-based atmospheric synoptic observation networks provide large-scale and multifaceted data to help resolve emission behaviors. This study employs a comprehensive analysis of atmospheric dynamics, combustion byproducts, and aerosol characteristics around power plants. Strong correlations between Aerosol Optical Depth (AOD) at 500 nm and the column-averaged dry-air mole fraction of carbon dioxide (XCO2) were observed, revealing synchronous peaks in their emission patterns. The investigation into combustion completeness utilized metrics such as the ratio of carbon monoxide (CO)/XCO2 and Black Carbon Extinction (BCEXT)/Total Aerosol Extinction (TOTEXT). Discrepancies in these ratios across cases suggest variations in combustion efficiency and aerosol characteristics. Nitrogen dioxide (NO2) distributions closely mirrored XCO2, indicating consistent emission patterns, while variations in sulfur dioxide (SO2) distributions implied differences in sulfide content in the coal used. The influence of coal composition on AOD/XCO2 ratios was evident, with sulfide content contributing to variations besides combustion efficiency. This multifactorial analysis underscores the complex interplay of combustion completeness, aerosol composition, and coal components in shaping the air quality around power stations. The findings highlight the need for a nuanced understanding of these factors for effective air quality management.

Reported herein is the development of assays for the spectrophotometric quantification of biocatalytic silicon−oxygen bond hydrolysis. Central to these assays are a series of chromogenic substrates that release highly absorbing phenoxy anions upon cleavage of the sessile bond. These substrates were tested with silicatein, an enzyme from a marine sponge that is known to catalyse the hydrolysis and condensation of silyl ethers. It was found that, of the substrates tested, tert-butyldimethyl(2-methyl-4-nitrophenoxy)silane provided the best assay performance, as evidenced by the highest ratio of enzyme catalysed reaction rate compared with the background (uncatalysed) reaction. These substrates were also found to be suitable for detailed enzyme kinetics measurements, as demonstrated by their use to determine the Michaelis−Menten kinetic parameters for silicatein.

Inflammation processes of the central nervous system (CNS) play a vital role in the pathogenesis of several neurological and psychiatric disorders like depression. These processes are characterized by the activation of glia cells, such as microglia. Clinical studies showed a decrease in symptoms associated with the mentioned diseases after the treatment with anti-inflammatory drugs. Therefore, the investigation of novel anti-inflammatory drugs could hold substantial potential in the treatment of disorders with a neuroinflammatory background. In this in vitro study, we report the anti-inflammatory effects of a novel hexacyclic peptide-peptoid hybrid in lipopolysaccharide (LPS)-stimulated BV2 microglial cells. The macrocyclic compound X15856 significantly suppressed Interleukin 6 (IL-6), tumor necrosis factor-α (TNF-α), c-c motif chemokine ligand 2 (CCL2), CCL3, C-X-C motif chemokine ligand 2 (CXCL2), and CXCL10 expression and release in LPS-treated BV2 microglial cells. The anti-inflammatory effects of the compound are partially explained by the modulation of the phosphorylation of p38 mitogen-activated protein kinases (MAPK), p42/44 MAPK (ERK 1/2), protein kinase C (PKC), and the nuclear factor (NF)-κB, respectively. Due to its remarkable anti-inflammatory properties, this compound emerges as an encouraging option for additional research and potential utilization in disorders influenced by inflammation, such as depression.

The global population is progressively entering an aging phase, with population aging likely to emerge as one of the most-significant social trends of the 21st Century, impacting nearly all societal domains. Addressing the challenge of assisting vulnerable groups such as the elderly and disabled in carrying or transporting objects has become a critical issue in this field. We developed a mobile Internet of Things (IoT) device leveraging Ultra-Wideband (UWB) technology in this context. This research directly benefits vulnerable groups, including the elderly, disabled individuals, pregnant women, and children. Additionally, it provides valuable references for decision-makers, engineers, and researchers to address real-world challenges. The focus of this research is on implementing UWB technology for precise mobile IoT device localization and following, while integrating an autonomous following system, a robotic arm system, an ultrasonic obstacle-avoidance system, and an automatic leveling control system into a comprehensive experimental platform. To counteract the potential UWB signal fluctuations and high noise interference in complex environments, we propose a hybrid filtering-weighted fusion back propagation (HFWF-BP) neural network localization algorithm. This algorithm combines the characteristics of Gaussian, median, and mean filtering, utilizing a weighted fusion back propagation (WF-BP) neural network, and, ultimately, employs the Chan algorithm to achieve optimal estimation values. Through deployment and experimentation on the device, the proposed algorithm’s data preprocessing effectively eliminates errors under multi-factor interference, significantly enhancing the precision and anti-interference capabilities of the localization and following processes.

Trametes lactinea is a macrofungus commonly found on broadleaf tree felling piles with rich bioactivity, and its main active substances are polysaccharides, which have a certain medicinal value. Few studies have been conducted on the simultaneous study of intracellular and extracellular polysaccharides of fermented mycelia in liquid culture. In this study, T. lactinea collected from Eucalyptus stumps was subjected to liquid fermentation culturing and the extraction of intracellular and extracellular polysaccharides from the mycelium was optimized using unidirectional and orthogonal test methods. The intracellular and extracellular crude polysaccharides were isolated and purified, and polysaccharide fractions were obtained and assayed for their chemical composition. The main findings of this study are as follows: (1) The optimal conditions for the extraction of intracellular polysaccharides from T. lactinea mycelium were a material–liquid ratio of 1:40, an extraction temperature of 100 °C, a time of 5 h, and four repeats, wherein the polysaccharide extraction rate reached 5.1%. The optimal extraction conditions for the extracellular polysaccharides were a concentration ratio of 5:1, a concentration temperature of 70 °C, an ethanol concentration of 100.0%, and an alcohol settling time of 12 h. The polysaccharides could thus be extracted up to 0.63 mg/mL. (2) The intracellular and extracellular crude polysaccharides of T. lactinea mycelium were successfully isolated and purified, resulting in three homogeneous fractions of intracellular polysaccharides (IP-1, IP-2, and IP-3) and two homogeneous fractions of extracellular polysaccharides (EP-1 and EP-2). (3) The polysaccharide chemical composition resulted in the highest total sugar content of EP-1. IP-3 had the highest uronic acid content. The results of the monosaccharide composition analysis showed that the mycelial intracellular polysaccharides IP-1, IP-2, and IP-3 were all highest in glucose. Both IP-2 and IP-3 contained guluronic acid and glucuronic acid. Mannose was the most abundant extracellular polysaccharide in both EP-1 and EP-2. This study provides theoretical and technical bases for the comprehensive development and utilization of T. lactinea polysaccharides.

The instability of the winding-cushion structure is one of the primary causes of transformer failures. Insulation cushion compression and offset are the predominant forms leading to structural instability. Therefore, this paper, using the SFSZ7-31500/110 transformer as an example, first derives the theoretical formula for mechanical stress calculation. It clarifies the key influencing parameters of the winding-cushion block structure on the axial bending stress of the winding. Subsequently, an electromagnetic force finite element calculation model is established to obtain the axial force distribution in the winding and the distribution of unbalanced displacement during short-circuit processes. Based on the force and offset distribution, a specific cushion block compression and offset test platform is constructed. By setting different cushion block variables, the effects of cushion block unbalanced height and cushion block offset on the winding’s bending elastic modulus are determined. Finally, a simulation model for stress calculation of the winding-cushion block structure is established, revealing the influence pattern of cushion block compression and offset instability on the axial strength of the winding. The results of this study indicate that the greater the uneven cushion block height, the lower the axial strength of the winding. Under the same cushion block offset angle, winding structures with non-uniform cushion block offsets exhibit the worst axial stability. When the offset angles are 30°, 45°, and 60°, the maximum axial bending stress of the winding increases by 1.73%, 3.46%, and 7.82%, respectively. Increasing the offset angle exacerbates the decrease in the axial strength of the winding up to a certain extent. The findings in this study have significant implications for enhancing a transformer’s short-circuit resistance.

Porous covalent organic frameworks (COFs) have been widely used for the efficient removal of iodine from solution due to their abundance of electron-rich sites. In this study, two kinds of ketoenamine-based COFs, TpBD-(OMe)2 and TpBD-Me2, are successfully synthesized via Schiff base reaction under solvothermal conditions using 1, 3, 5-triformylphoroglucinol as aldehyde monomer, o-tolidine and o-dianisidine as amino monomers. The ability of TpBD-(OMe)2 and TpBD-Me2 to adsorb iodine in cyclohexane or aqueous solutions has been quantitatively analyzed and interpreted in terms of adsorption sites. TpBD-Me2 possesses two adsorption sites, -NH- and -C=O, and exhibits an adsorption capacity of 681.67 mg/g in cyclohexane, with an initial adsorption rate of 0.6 g/mol/min with respect to COF unit cell. The adsorption capacity of TpBD-(OMe)2 can be as high as 728.77 mg/g, and the initial adsorption rate of TpBD-(OMe)2 can reach 1.2 g/mol/min in the presence of oxygen atoms between the methyl group and the benzene ring. Compared with TpBD-Me2, the higher adsorption capacity and adsorption rate of TpBD-(OMe)2 towards iodine are not only reflected in organic solvents, but also in aqueous solutions. It is proven through X-ray photoelectron spectroscopy and Raman spectroscopy that iodine exists in the form of I2, I3−, and I5− within TpBD-(OMe)2 and TpBD-Me2 after adsorption. This work not only expands the application of COFs in the field of iodine adsorption, but also provides research ideas and important an experimental basis for the optimization of iodine adsorption sites.

The aim of this study was to find out how different postharvest temperatures and MeJA treatments affected the quality of table grapes, their antioxidant properties, and the amount of hydrogen peroxide and malondialdehyde they contained. For the investigation, postharvest Shine Muscat table grapes were treated with low and high temperatures and MeJA at concentrations of 10 and 100 μmol/L. The results indicated that treating grape berries with MeJA at concentrations of 10 and 100 μmol/L effectively reduced weight loss and mitigated the increase in soluble solid content while also mitigating the decrease in berry firmness and titratable acidity. Consequently, this treatment preserved the sensory and nutritional qualities of the berries and extended their shelf life. Meanwhile, the application of MeJA at a concentration of 10 μmol/L demonstrated superior effectiveness compared to the 100 μmol/L concentration and resulted in a significant enhancement of antioxidant activities by increasing levels of superoxide dismutase, catalase, ascorbate peroxidase, and polyphenol oxidase. Furthermore, the levels of hydrogen peroxide and malondialdehyde in the samples increased for all treatments throughout the storage period. Nevertheless, the levels of hydrogen peroxide and malondialdehyde generation following MeJA treatment remained much lower compared to samples treated at room temperature and low temperature. Therefore, the postharvest application of MeJA at a concentration of 10 μmol/L could play a critical role as a stimulator of fruit quality as well as enhance physicochemical parameters and antioxidant activities for extending the shelf life of grapes during storage.

Wireless broadband transmission channels usually have time-domain-sparse properties, and the reconstruction of these channels using a greedy search-based orthogonal matching pursuit (OMP) algorithm can effectively improve channel estimation performance while decreasing the length of the reference signal. In this research, the improved OMP and SOMP algorithms for compressed-sensing (CS)-based channel estimation are proposed for single-carrier frequency domain equalization (SC-FDE) systems, which, in comparison with conventional algorithms, calculate the path gain after obtaining the path delay and updating the observation matrices. The reliability of the communication system is further enhanced because the channel path gain is calculated using longer observation vectors, which lowers the Cramér–Rao lower bound (CRLB) and results in better channel estimation performance. The developed method can also be applied to time-domain-synchronous OFDM (TDS-OFDM) systems, and it is applicable to the improvement of other matching pursuit algorithms.

The Saima alkaline rock-hosted niobium–tantalum deposit (hereafter referred to as the Saima Deposit) is situated in the Liaodong Peninsula, which constitutes the eastern segment of the northern margin of the North China Craton. The rock types of the Saima Deposit include phonolite, nepheline syenite, and aegirine nepheline syenite, which hosts niobium–tantalum ore bodies. In this study, the primary niobium-bearing minerals identified include loparite, betafite, and fersmite. The Saima pluton is characterized as a potassium-rich, low-sodium, and peraluminous alkaline pluton. Trace element characteristics reveal that the metallization-associated syenite is enriched in large-ion lithophile elements (LILEs) such as K and Rb but is relatively depleted in high-field strength elements (HFSEs). As indicated by the rare earth element (REE) profile, the Saima pluton exhibits a high total REE content (∑REE), dominance of light REEs (LREEs), and scarcity of heavy REEs (HREEs). The Sr-Nd-Pd isotopic data suggest that aegirine nepheline syenite and nepheline syenite share consistent isotopic signatures, indicating a common origin. The Saima alkaline pluton displays elevated ISr values ranging from 0.70712 to 0.70832 coupled with low εNd(t) values between −12.84 and −11.86 and two-stage model ages (tDM2) from 1967 to 2047 Ma. These findings indicate that the metallogenic materials for the Saima Deposit derive from both an enriched mantle source and some crustal components. The lithium (Li) isotopic fractionation observed during the genesis of the Saima pluton could be attributed to the differential diffusion rates of 6Li and 7Li under non-equilibrium fluid–rock interactions.

When a transformer suffers a permanent fault, it will suffer a short-circuit impulse again after reclosing. If the previous vibration of the winding is not attenuated completely and the winding is subjected to a secondary impulse within a short time, the secondary vibration response will have a superposition. The aim of this study was to analyze the effect of the anti-short-circuit ability of operational transformers subjected to a secondary short-circuit current impulse. In this paper, a model is established for calculating axial vibration in transformer windings and effects on the vibration response of windings under different closing phase angles and short-circuit intervals are analyzed. The results show that the vibration acceleration of windings is a V-shaped variation at phase angles from 0° to 180°, reaching the maximum values at 0° and 180° and reaching the minimum value at 90°. When the transformer recloses on a permanent short circuit, due to the superposition effect, the vibration acceleration amplitude of the secondary impulse will be greater than that of the primary impulse, but as the reclosing interval increases, the superposition effect decreases continuously. When the interval is 600 ms, the superposition effect for the vibration acceleration of the secondary impulse attenuates to 83.3%. The superposition effect is not significant after 600 ms. The research provides a theoretical reference for transformer closing-control strategies.

This research addresses the challenges of visually impaired individuals’ independent travel by avoiding obstacles. The study proposes a distance estimation method for uncontrolled three-dimensional environments to aid navigation towards labeled target objects. Utilizing a monocular camera, the method captures cuboid objects (e.g., fences, pillars) for near-front distance estimation. A Field of View (FOV) model calculates the camera’s angle and arbitrary pitch relative to the target Point of Interest (POI) within the image. Experimental results demonstrate the method’s proficiency in detecting distances between objects and the source camera, employing the FOV and Point of View (POV) principles. The approach achieves a mean absolute percentage error (MAPE) of 6.18% and 6.24% on YOLOv4-tiny and YOLOv4, respectively, within 10 m. The distance model only contributes a maximum error of 4% due to POV simplification, affected by target object characteristics, height, and selected POV. The proposed distance estimation method shows promise in drone racing navigation, EV autopilot, and aiding visually impaired individuals. It offers valuable insights into dynamic 3D environment distance estimation, advancing computer vision and autonomous systems.

Pulmonary drug delivery via microspheres has gained growing interest as a noninvasive method for therapy. However, drug delivery through the lungs via inhalation faces great challenges due to the natural defense mechanisms of the respiratory tract, such as the removal or deactivation of drugs. This study aims to develop a natural polymer-based microsphere system with a diameter of around 3 μm for encapsulating pulmonary drugs and facilitating their delivery to the deep lungs. Pectin was chosen as the foundational material due to its biocompatibility and degradability in physiological environments. Electrospray was used to produce the pectin-based hydrogel microspheres, and Design-Expert software was used to optimize the production process for microsphere size and uniformity. The optimized conditions were determined to be as follows: pectin/PEO ratio of 3:1, voltage of 14.4 kV, distance of 18.2 cm, and flow rate of 0.95 mL/h. The stability and responsiveness of the pectin-based hydrogel microspheres can be altered through coatings such as gelatin. Furthermore, the potential of the microspheres for pulmonary drug delivery (i.e., their responsiveness to the deep lung environment) was investigated. Successfully coated microspheres with 0.75% gelatin in 0.3 M mannitol exhibited improved stability while retaining high responsiveness in the simulated lung fluid (Gamble’s solution). A gelatin-coated pectin-based microsphere system was developed, which could potentially be used for targeted drug delivery to reach the deep lungs and rapid release of the drug.

Oil agents produced from the degreasing treatment of synthetic fibers are typical pollutants in wastewater from printing and dyeing, which may cause large-scale environmental pollution without proper treatment. Purifying oily dye wastewater (DTY) at a low cost is a key problem at present. In this study, biochar microspheres with oil removal ability were prepared and derived from waste bamboo chips using the hydrothermal method. The structure of the biochar microsphere was regulated by activation and modification processes. Biochar microspheres were characterized, and their adsorption behaviors for oily dye wastewater were explored. The results show that the adsorption efficiency of biochar microspheres for oily dye wastewater (DTY) was improved significantly after secondary pyrolysis and the lauric acid grafting reaction. The maximum COD removal quantity of biochar microspheres for DTY was 889 mg/g with a removal rate of 86.06% in 30 min. In addition, the kinetics showed that chemisorption was the main adsorption manner. Considering the low cost of raw materials, the application of biochar microspheres could decrease the cost of oily wastewater treatment and avoid environmental pollution.

Campylobacter is among the four main causes of gastroenteritis worldwide. Most reported Campylobacter infections are caused by C. jejuni and C. coli. However, other emerging Campylobacter pathogens have been recognized as important pathogens in humans and animals. A novel bacterial strain, PS10T, was isolated from the gastric mucous of pigs in 2022 in Beijing, China. The cell was Gram-negative, microaerobic, motile, and negative for catalase, oxidase, and urease. Phylogenetic and phylogenomic analyses based on the 16S rRNA gene and core genome indicated that this isolate belongs to the genus Campylobacter. There were low dDDH relatedness and ANI values shared within this strain and its closest species C. mucosalis below the cut-off values generally recognized for isolates of the same species. The draft genome size of PS10T is 2,240,910 bp in length with a percentage of DNA G+C contents of 37.72%. Comparing the phenotypic and phylogenetic features among this isolate and its related organisms, strain PS10T represents a novel species within the genus Campylobacter, for which the name Campylobacter gastrosuis sp. nov. (Type strain PS10T = GDMCC 1.3686T = JCM 35849T) is proposed.

Beamspace MIMO-NOMA is an effective way to improve spectral efficiency. This paper focuses on a downlink non-orthogonal multiple access (NOMA) transmission scheme for a beamspace multiple-input multiple-output (MIMO) system. To increase the sum rate, we jointly optimize precoding and power allocation, which presents a non-convex problem. To solve this difficulty, we employ an alternating algorithm to optimize the precoding and power allocation. Regarding the precoding subproblem, we demonstrate that the original optimization problem can be transformed into an unconstrained optimization problem. Drawing inspiration from fraction programming (FP), we reconstruct the problem and derive a closed-form expression of the optimization variable. In addition, we effectively reduce the complexity of precoding by utilizing Neumann series expansion (NSE). For the power allocation subproblem, we adopt a dynamic power allocation scheme that considers both the intra-beam power optimization and the inter-beam power optimization. Simulation results show that the energy efficiency of the proposed beamspace MIMO-NOMA is significantly better than other conventional schemes.

A person’s present mental state is closely associated with the frequency and temporal domain features of spontaneous electroencephalogram (EEG) impulses, which directly reflect neurophysiological signals of brain activity. EEG signals are employed in this study to measure the mental workload of drivers while they are operating a vehicle. A technique based on the quantum genetic algorithm (QGA) is suggested for improving the kernel function parameters of the multi-class support vector machine (MSVM). The performance of the algorithm based on the quantum genetic algorithm is found to be superior to that of other ways when other methods and the quantum genetic algorithm are evaluated for the parameter optimization of kernel function via simulation. A multi-classification support vector machine based on the quantum genetic algorithm (QGA-MSVM) is applied to identify the mental workload of oceanauts through the collection and feature extraction of EEG signals during driving simulation operation experiments in a sea basin area, a seamount area, and a hydrothermal area. Even with a limited data set, QGA-MSVM is able to accurately identify the cognitive burden experienced by ocean sailors, with an overall accuracy of 91.8%.

To ascertain the Early-to-Middle Jurassic tectonic setting in the central Great Xing’an Range, this study investigated the Early and Middle Jurassic granitoids exposed in the Chaihe area in the central Great Xing’an Range based on isotopic chronology and petrogeochemistry. The results of this study show that the Early and Middle Jurassic granitoids have emplacement ages of 179–172 Ma. Moreover, the Early and Middle Jurassic granitoids are high-K calc-alkaline unfractionated I-type granitoids and high-K calc-alkaline fractionated I-type granitoids, respectively. The magma sources of the Early and Middle Jurassic granitoids both originated from the partial melting of newly accreted lower crustal basaltic rocks. Meanwhile, the Middle Jurassic magma sources were mixed with mantle-derived materials or ocean-floor sediments formed by the dehydration and metasomatism of subducted slabs. The Early and Middle Jurassic granitoids in the study area were formed in the subduction environment of the oceanic crust, in which the Mongol-Okhotsk oceanic plate was subducted southward beneath the Eerguna and Xing’an blocks. Moreover, the Siberian plate began to collide and converge with northeast China during the Middle Jurassic.

To further examine the effectiveness of the ascending and descending sections of the new round-trip drifting sounding system in forecasting high-impact weather such as heavy rainfall, in this study, three assimilation experiments were designed for a rainstorm in eastern China using WRF (Weather Research and Forecast) and WRFDA-3DVAR. Then, the reasons for the improvement in the effects of forecasting rainfall after assimilation were analyzed from various perspectives. The results showed that the assimilation of round-trip drifting sounding data can increase the accuracy of regions of heavy precipitation and improve the effectiveness of rainstorm forecasting. The quality of the wind field improved after the assimilation of the round-trip drifting sounding data, which improved the conditions of moisture transport, resulting in increased humidity in the lower layer, which accumulated more unstable energy for the development of storms. In addition, the enhanced low-level convergence after the assimilation of the new sounding data created a strong upward motion, which was more conducive to triggering heavy rainfall, thus improving the ability to forecast such heavy rainfall.

This paper aims to fuzzify the width problem of classical approximation theory. New concepts of fuzzy Kolmogorov n-width and fuzzy linear n-width are introduced on the basis of α-fuzzy distance which is induced by the fuzzy norm. Furthermore, the relationship between the classical widths in linear normed space and the fuzzy widths in fuzzy linear normed space is discussed. Finally, the exact asymptotic orders of the fuzzy Kolmogorov n-width and fuzzy linear n-width corresponding to a given fuzzy norm in finite-dimensional space and Sobolev space are estimated.

The performance of traditional model-based constant false-alarm ratio (CFAR) detection algorithms can suffer in complex environments, particularly in scenarios involving multiple targets (MT) and clutter edges (CE) due to an imprecise estimation of background noise power level. Furthermore, the fixed threshold mechanism that is commonly used in the single-input single-output neural network can result in performance degradation due to changes in the scene. To overcome these challenges and limitations, this paper proposes a novel approach, a single-input dual-output network detector (SIDOND) using data-driven deep neural networks (DNN). One output is used for signal property information (SPI)-based estimation of the detection sufficient statistic, while the other is utilized to establish a dynamic-intelligent threshold mechanism based on the threshold impact factor (TIF), where the TIF is a simplified description of the target and background environment information. Experimental results demonstrate that SIDOND is more robust and performs better than model-based and single-output network detectors. Moreover, the visual explanation technique is employed to explain the working of SIDOND.

Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for skin and soft tissue infections with multi-resistance to many antibiotics. It is thus imperative to explore alternative antimicrobial treatments to ensure future treatment options. Nisin (NIS), an antibacterial peptide produced by Lactococcus lactis, was selected to combine with Oxacillin (OX), to evaluate the antimicrobial effect and potential mechanism against MRSA. The synergistic antimicrobial effect of OX and NIS was verified by Minimal Inhibitory Concentration (MIC) assays, checkerboard analysis, time-kill curve, biofilm producing ability, and mice skin infection model in vivo. For the potential synergistic antimicrobial mechanism, the microstructure and integrity change of MRSA cells were determined by Scanning and Transmission Electron Microscope (SEM and TEM), intracellular alkaline phosphatase activity and propidium iodide staining were assayed; And transcription of mecA, main gene of MRSA resistant to OX, were detected by qRT-PCR. The results showed NIS could restore the sensitivity of MRSA to OX and inhibit biofilm production; OX + NIS can make MRSA cell deform; NIS may recover OX sensitivity by inhibiting the transcription of mecA. In vivo, mice skin infection models indicate that OX + NIS can substantially alleviate MRSA infections. As a safe commercially available biological compound, NIS and the combination of antibiotics are worth developing as new anti-MRSA biomaterials.

The process of intelligent multi-objective parametric optimization design for mirrors is discussed in detail in this paper, with the error of the mirror surface shape and the total mass being examined as the optimization objectives. The establishment of complex objective functions for solving the optimization problem of the mirror surface shape error was realized, and manual modification of the model was avoided. Moreover, combining this with a non-dominated sorting genetic algorithm (NSGA) helped the Pareto front move towards an ideal optimal set of solutions. To verify the effectiveness of the proposed method, an aluminum alloy mirror with an aperture of 140 mm was taken as an example. The Pareto optimal solution set of the mass and surface shape error under 1 g gravity was obtained for finding the required solution and satisfying the optimization goal. In addition, this method is applicable to other complex structural design problems.

Complex terrain conditions of wind farms, the large weight and the long size of wind turbine equipment, the high economic requirements of transportation on roads, and a shortage of relevant standards and codes lead to difficulty in road design and route selection of wind farms. In addition, frequent excavations and landfills in wind farm construction have seriously destroyed vegetation cover and soil structure on the primary surface, resulting in a large amount of water and soil loss and ecological damage to the wind farm. In view of the above problems, this paper reviews the relevant research status of the wind farm road route selection method, circular curve, longitudinal section design index, and water and soil loss problems, and summarizes them. Several calculation models for circular curve widening, the recommendation of a minimum radius under different restrictions, calculation models for longitudinal slope and vertical curve, and recommended values are listed. The causes of water and soil losses in wind farms are discussed and the characteristics of the diversity of erosion and the uneven distribution of time and space are put forward. Prediction models of wind farm water and soil loss and comprehensive prevention measures are given. The existing problems in the road design field of wind farms are put forward and the future development direction in this field is forecasted.

Offline handwritten Chinese recognition is an important research area of pattern recognition, including offline handwritten Chinese character recognition (offline HCCR) and offline handwritten Chinese text recognition (offline HCTR), which are closely related to daily life. With new deep learning techniques and the combination with other domain knowledge, offline handwritten Chinese recognition has gained breakthroughs in methods and performance in recent years. However, there have yet to be articles that provide a technical review of this field since 2016. In light of this, this paper reviews the research progress and challenges of offline handwritten Chinese recognition based on traditional techniques, deep learning methods, methods combining deep learning with traditional techniques, and knowledge from other areas from 2016 to 2022. Firstly, it introduces the research background and status of handwritten Chinese recognition, standard datasets, and evaluation metrics. Secondly, a comprehensive summary and analysis of offline HCCR and offline HCTR approaches during the last seven years is provided, along with an explanation of their concepts, specifics, and performances. Finally, the main research problems in this field over the past few years are presented. The challenges still exist in offline handwritten Chinese recognition are discussed, aiming to inspire future research work.

Primary school mathematics is one of the most important subjects in primary school learning, and basic mathematical competencies are an important component of the response to academic achievement. Improving students’ basic competence in mathematics is one of the important goals of teaching mathematics in primary schools. Research has shown that experiential learning has an impact on basic competencies in mathematics, attitudes toward mathematics, and self-efficacy in mathematics. Therefore, this study explores the structural model that fits the relationship between experiential learning and basic competencies in mathematics using a linear model. This study uses a sample of 263 primary school students to explore the influential relationships between learning engagement, mathematical attitudes, mathematical self-efficacy, and basic mathematical competencies after experiential learning. The study revealed that the model had a good fit, with learning engagement, mathematical attitudes, and mathematical self-efficacy all having significant effects on basic mathematical competencies; in addition, behavioral engagement had insignificant effects on mathematical attitudes and mathematical self-efficacy. This study can infer through one year of experiential learning and based on the structural model developed that experiential learning in mathematics can increase students’ learning engagement in mathematics learning and positively influence mathematical attitudes and mathematical self-efficacy, thus positively influencing students’ performance in basic mathematical competencies.

Since there is a frequency offset between each adjacent antenna of FDA radar, there exists angle-range two-dimensional dependence in the transmitter. For bistatic FDA-multiple input multiple output (MIMO) radar, range-direction of departure (DOD)-direction of arrival (DOA) information is coupled in transmitting the steering vector. How to decouple the three information has become the focus of research. Aiming at the issue of target parameter estimation of bistatic FDA-MIMO radar, a real-valued parameter estimation algorithm based on high-order-singular value decomposition (HOSVD) is developed. Firstly, for decoupling DOD and range in transmitter, it is necessary to divide the transmitter into subarrays. Then, the forward–backward averaging and unitary transformation techniques are utilized to convert complex-valued data into real-valued data. The signal subspace is obtained by HOSVD, and the two-dimensional spatial spectral function is constructed. Secondly, the dimension of spatial spectrum is reduced by the Lagrange algorithm, so that it is only related to DOA, and the DOA estimation is obtained. Then the frequency increment between subarrays is used to decouple the DOD and range information, and eliminate the phase ambiguity at the same time. Finally, the DOD and range estimation automatically matched with DOA estimation are obtained. The proposed algorithm uses the multidimensional structure of high-dimensional data to promote performance. Meanwhile, the proposed real-valued tensor-based method can effectively cut down the computing time. Simulation results verify the high efficiency of the developed method.

Chinese fir (Cunninghamia lanceolata) is a kind of evergreen coniferous tree species, the expansion of its pure forest area and multiple generations of continuous planting has led to a decline of stand quality and woodland fertility. To further investigate the relationship between leaf, litter, and soil stoichiometry, microbial community status, and microbial resource limitation of Chinese fir after continuous planting. We studied the C, N, and P stoichiometries of leaf, litter, and soil from successive rotations of Chinese fir plantations. In addition to this, soil microbial biomass C, N, and P, extracellular enzymes, as well as the soil microbial community composition, were determined. The continuous planting of Chinese fir significantly increased the leaf N and P contents and decreased the C content of litter, and the soil C:N and C:P ratios, thus leading to a soil stoichiometric imbalance. The continuous planting of Chinese fir plantations significantly increased the soil microbial biomass. Compared with the first-generation plantations, the N and P contents of the second- and third-generation plantations increased by 37.11%, 21.83% and 46.28%, 73.38%, respectively, thus alleviating the restriction of microbial N and P. Under continuous planting, the extracellular enzyme activities of N (NAG + LAP) and P (AP) were significantly decreased, and those of the second- and third-generation plantations were significantly decreased by 7.05%, 9.43% and 11.79%, 48.94%, respectively, compared with those of the first-generation plantations, resulting in an increase of 7.85 and 3.19% in carbon-use efficiency. The fungi:bacteria (F:B) ratio of the soil microbial community was elevated in successive plantations. The least squares pathway model (PLS-PM) indicated that the stoichiometric ratio of ecological enzymes had an indirect negative effect on CUE, and was the strongest predictor. This study showed that the successive plantation of Chinese fir resulted in a leaf, litter, and soil stoichiometric imbalance, further affecting community composition and resource limitation of soil microorganisms.

Neuroinflammation and oxidative stress are conditions leading to neurological and neuropsychiatric disorders. Natural compounds exerting anti-inflammatory and anti-oxidative effects, such as Licochalcone A, a bioactive flavonoid present in a traditional Chinese herb (licorice), might be beneficial for the treatment of those disorders. Therefore, this study aimed to investigate the anti-inflammatory and anti-oxidative effects of Licochalcone A in LPS-activated primary rat microglia. Licochalcone A dose-dependently prevented LPS-induced PGE2 release by inhibiting the arachidonic acid (AA)/cylcooxygenase (COX) pathway decreasing phospholipase A2, COX-1, and COX-2 protein levels. Furthermore, LPS-induced levels of the cytokines IL-6 and TNFα were reduced by Licochalcone A, which also inhibited the phosphorylation and, thus, activation of the mitogen-activated protein kinases (MAPK) p38 MAPK and Erk 1/2. With the reduction of 8-iso-PGF2α, a sensitive marker for oxidative stress, anti-oxidative effects of Licochalcone A were demonstrated. Our data demonstrate that Licochalcone A can affect microglial activation by interfering in important inflammatory pathways. These in vitro findings further demonstrate the potential value of Licochalcone A as a therapeutic option for the prevention of microglial dysfunction related to neuroinflammatory diseases. Future research should continue to investigate the effects of Licochalcone A in different disease models with a focus on its anti-oxidative and anti-neuroinflammatory properties.

Dissolved organic carbon (DOC) in inland waters (rivers, reservoirs, lakes, and small ponds) plays a significant role in the global carbon cycle and affects global climate change. In addition, DOC is also a vital indicator of the water environment due to its multiple physical, chemical, and ecological roles. Lakes and ponds of small sizes are abundant on a global and regional scale, and a large increase in ponds is expected with global agricultural land expansion. However, the DOC characteristics of ponds in agricultural watersheds are still unclear, posing a challenge to better understanding the carbon cycle of inland waters. In this study, we explored the DOC variability and their influencing factors in ponds draining different landscapes in a typical agricultural watershed to address the issue. The field measurements over a year showed the DOC concentration varied among ponds draining different landscapes. Specifically, the mean DOC concentrations in the natural pond, sewage pond, aquaculture pond, and irrigation pond were (6.17 ± 1.49) mg/L, (12.08 ± 2.92) mg/L, (9.36 ± 2.92) mg/L, and (8.91 ± 2.71) mg/L, respectively. Meanwhile, monthly measurements found the DOC varied across sampling dates. The DOC variability was positively correlated with nutrients, primary production, and precipitation, suggesting anthropogenic loadings, an internal production rate, and hydrological regime that regulated the substantial variability of DOC in these ponds at the watershed scale. Further, large pollutant discharge and high primary production led to peak DOC occurring in the sewage pond. Our results implied that more attention should be paid to ponds in agricultural watersheds to better understand the roles of inland waters in the global carbon cycle.

Previous studies have shown that spermidine (Spd) can improve tolerance to high temperature stress in tomato seedlings. To further understand how Spd regulates the molecular components of high temperature stress signaling pathways, we performed a genome-wide transcriptome analysis in tomato seedlings treated with high temperature and/or exogenous Spd. The results demonstrate that, under high temperature conditions, Spd significantly alleviated the inhibition of plant growth, as well as improving the net photosynthetic rate and pigment contents. The transcriptome analysis revealed thousands of differentially expressed genes (DEGs) in response to high temperature with or without Spd treatment. Half of the genes were induced by high temperature, part of the genes were induced by high temperature with exogenous Spd, and some were induced by the coordinated effect of high temperature and Spd. A GO analysis indicated that genes involved in cellular processes, metabolic processes, and nucleotide binding in the sample were subjected to high temperature. Some DEGs were also involved in plant physiological processes. These results suggest potential genes and molecular pathways were involved in the exogenous Spd-mediated tolerance to high temperature stress in tomato plants. A JA signaling test was designed, which indicated that MYC2 and JAS1 in heat-resistant materials were both increased, through quantitative RT-PCR.

Dust detection is essential for environmental protection, climate change assessment, and human health issues. Based on the Fengyun-4A (FY-4A)/Advance Geostationary Radiation Imager (AGRI) images, this paper aimed to examine the performances of two classic dust detection algorithms (i.e., the brightness temperature difference (BTD) and normalized difference dust index (NDDI) thresholding algorithms) as well as two dust products (i.e., the infrared differential dust index (IDDI) and Dust Score products (DST) developed by the China Meteorological Administration). Results show that a threshold below −0.4 for BTD (11–12 µm) is appropriate for dust identification over China and that there is no fixed threshold for NDDI due to its limitations in distinguishing dust from bare ground. The IDDI and DST products presented similar results, where they are capable of detecting dust over all study areas only for daytime. A validation of these four dust detection algorithms has also been conducted with ground-based particulate matter (PM10) concentration measurements for the spring (March to May) of 2021. Results show that the average probability of correct detection (POCD) for BTD, NDDI, IDDI, and DST were 56.15%, 39.39%, 48.22%, and 46.75%, respectively. Overall, BTD performed the best on dust detection over China with its relative higher accuracy followed by IDDI and DST in the spring of 2021. A single threshold for NDDI led to a lower accuracy than those for others. Additionally, we integrated the BTD and IDDI algorithms for verification. The POFD after integration was only 56.17%, and the fusion algorithm had certain advantages over the single algorithm verification.