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Organic solvent reverse osmosis (OSRO) is an emerging and promising technology for the separation of organic mixtures, which is realized by differential transport rates of organics through polymer membranes. However, the solvent transport characteristics and separation mechanism within OSRO systems remain unclear. Herein, we investigate the solvent transport behavior in polymer membranes with intrinsic microporosity by combining nonequilibrium molecular dynamics simulations with solvent permeation examinations. The results indicate that organic molecules permeate through the micropores in a clustered state driven by both pressure and concentration gradients. The selectivity of solvents is co‐determined by their sorption and diffusion in the swollen polymer membranes with a microporous character. The sorption selectivity is predominant in the overall selectivity toward polar ethyl ether/n‐butanol separation, whereas diffusion selectivity is more critical in nonpolar 1,3,5‐triisopropylbenzene/toluene separation. Generally, this work provides valuable insights into the development of next‐generation OSRO membranes for solvent separation. [ABSTRACT FROM AUTHOR]

Prescribed burning is commonly used to maintain forest ecosystem functions and reduce the risk of future wildfires. Although many studies have investigated the response of microbial community to wildfires in forest ecosystems, the effects of prescribed burnings on soil microbial community structure are less studied. It is also unclear that how post-fire soil physiochemical properties changes affected soil microbial communities. Here, we studied the impacts of prescribed burning on soil microbiome in three typical temperate forests of northern China by collecting soil physicochemical and high-throughput sequencing for 16S rRNA and 18S rRNA was applied to analyze the diversity and community composition of soil microbes (bacteria and fungi). Compared with pre-fire condition, prescribed burning significantly decreased Chao1 index and altered soil bacterial communities (P < 0.05), whereas it had no significant effect on fungal diversity and community structure of the (P > 0.05). Planctomycetes and Actinobacteria made the greatest contributions to the bacterial community dissimilarity between the pre-fire and post-fire conditions. The main variables influencing the post-fire soil microbial community structure are soil pH, available phosphorus, total nitrogen, and the ratio of soil total carbon to soil total nitrogen, which could account for 73.5% of the variation in the microbial community structure in these stands. Our findings demonstrated a great discrepancy in the responses of bacteria and fungi to prescribed burning. Prescribed burning altered the soil microbial structure by modifying the physicochemical properties. Our results pointed that it is essential to evaluate the impact of prescribed burnings on forest ecosystem functions. These findings provide an important baseline for assessing post-fire microbial recovery in the region and offer critical guidance for restoration efforts. [ABSTRACT FROM AUTHOR]

Prescribed burning is commonly used to maintain forest ecosystem functions and reduce the risk of future wildfires. Although many studies have investigated the response of microbial community to wildfires in forest ecosystems, the effects of prescribed burnings on soil microbial community structure are less studied. It is also unclear that how post-fire soil physiochemical properties changes affected soil microbial communities. Here, we studied the impacts of prescribed burning on soil microbiome in three typical temperate forests of northern China by collecting soil physicochemical and high-throughput sequencing for 16S rRNA and 18S rRNA was applied to analyze the diversity and community composition of soil microbes (bacteria and fungi). Compared with pre-fire condition, prescribed burning significantly decreased Chao1 index and altered soil bacterial communities (P < 0.05), whereas it had no significant effect on fungal diversity and community structure of the (P > 0.05). Planctomycetes and Actinobacteria made the greatest contributions to the bacterial community dissimilarity between the pre-fire and post-fire conditions. The main variables influencing the post-fire soil microbial community structure are soil pH, available phosphorus, total nitrogen, and the ratio of soil total carbon to soil total nitrogen, which could account for 73.5% of the variation in the microbial community structure in these stands. Our findings demonstrated a great discrepancy in the responses of bacteria and fungi to prescribed burning. Prescribed burning altered the soil microbial structure by modifying the physicochemical properties. Our results pointed that it is essential to evaluate the impact of prescribed burnings on forest ecosystem functions. These findings provide an important baseline for assessing post-fire microbial recovery in the region and offer critical guidance for restoration efforts. [ABSTRACT FROM AUTHOR]

As an important global food crop, rice is damaged by a variety of piercing–sucking pests. Identifying a broad-spectrum promoter induced by the physical signal of sucking pests and applying it to transgenic breeding to mitigate the damage caused by different sucking pests will significantly improve the efficiency of our breeding. This study compared the transcriptome changes in two rice varieties under needle-wounding stress to investigate their differential responses to mechanical damage. The results showed that the insect-susceptible variety TN1 exhibited more differentially expressed genes (DEGs) and greater changes in expression levels after needle treatment, indicating a more active internal gene regulatory network. GO and KEGG enrichment analysis further revealed that TN1 not only exhibited changes in genes related to the extracellular environment, but also mobilized more genes associated with stress response and defense. By screening the differentially expressed genes, we identified two promoters (P1 and P2) with inducible expression characteristics in both the resistant and susceptible rice varieties. These promoters were able to effectively drive the expression of the insect resistance gene OsLecRK1* and enhance the resistance of transgenic plants against the brown planthopper. This study provides promoter resources for the development of insect-resistant transgenic crops. [ABSTRACT FROM AUTHOR]

The movement of submerged flexible vegetation leads to an increase in resistance to the stream flow. In this study, a formula that can directly calculate the drag force on a highly flexible submerged vegetation, called Ceratophyllum, by using the vegetation swaying characteristics and the flow field information in a steady‐uniform open‐channel flow is derived. The drag force on submerged flexible vegetation is characterized by the time‐averaged flow velocity, turbulence intensity, and the additional force arising from the vegetation swaying. Based on the results of the numerical models in the previous studies (Wang et al., 2022a, 2022b, https://doi.org/10.1017/jfm.2022.598, https://doi.org/10.1017/jfm.2022.899), the drag coefficient is determined. It is revealed that the drag coefficient is influenced by a combination of factors, including the flow conditions, and the distribution and movement characteristics of vegetation. The drag coefficient decreases with an increase in velocity and is approximately linearly related to the cubic power of the bulk flow velocity. In the case of an inter‐plant spacing of 0.5 times the initial plant height, the drag coefficient ranges from 10.72 to 2.11, as the Reynolds number varies from 20,000 to 50,000. Besides, the vegetation distribution density and the relative submergence influence the drag coefficient. In this context, the drag coefficient decreases linearly with an increase in the inter‐plant spacing. For the Reynolds number equaling 50,000, the drag coefficient ranges from 2.11 to 2.02, when the inter‐plant spacing varies from 0.5 to 2 times the plant height, and from 2.47 to 1.79, when the flow depth varies from 1.5 to 3 times the plant height. Key Points: A formula for the drag force on submerged flexible vegetation in an open‐channel flow is proposedThe drag coefficient is inversely proportional to and linearly varying with the cubic power of the bulk flow velocityThe drag coefficient decreases with an increase in the inter‐plant spacing and the submergence depth [ABSTRACT FROM AUTHOR]

Particle density (ρs) and bulk density (ρb) are key factors in the calculation of total soil porosity. However, direct measurements of ρs and ρb are labour‐intensive, time‐consuming, and sometimes impractical. Pedotransfer functions (PTFs) provide alternative methods for indirect estimation of ρs and ρb. In this paper, the accuracy of typical 12 ρs and 9 ρb PTFs was evaluated using easily measurable soil properties (sand, silt, clay, and soil organic matter (SOM) content) from granitic residual soils collected from six study areas in subtropical China, and the accuracy of PTFs constructed based on multiple linear stepwise regression (MSR) and machine‐learned algorithms (backpropagation neural network, k‐nearest neighbour algorithms, random forests, support vector machines, and gradient boosted decision trees) was compared to determine the accuracy of PTFs. The results show that typical PTFs have poor accuracy (R2adjusted < 0.020) and are not applicable to the indirect estimation of ρs and ρb in granitic residual soils. The PTFs constructed by machine learning algorithms all performed better than MSR, with the highest estimation accuracy of the PTFs constructed by the random forest algorithm, with R2adjusted values of 0.923 and 0.933 for the ρs and ρb PTFs, respectively, and root‐mean‐square error of 0.020 g·cm−3 and 0.023 g·cm−3, respectively. Compared with MSR, the random forest algorithm has greater accuracy and eliminates the restriction of PTFs on predictors, which provides support for understanding the changing rules of ρs and ρb in granite residual soils in subtropical regions, evaluating soil quality and improving soil structure. [ABSTRACT FROM AUTHOR]

Transparent TiO2 photoanodes offer promise for new solar technology due to their high light transmittance, but the persistently inadequate solar conversion efficiency continues to pose obstacles for practical application. This research utilized n-butyl titanate and black P25 TiO2 (B-P25) to construct transparent TiO2 photoanodes for quantum dot sensitized solar cells (QDSSCs). The B-P25 presents rich oxygen vacancies after reduction, along with the generation of more pore structures in the TiO2 photoanode films, facilitating the transport of photogenerated charge carriers in the photoanode films. Therefore, the photoelectric conversion efficiency (PCE) is significantly enhanced from 1.77% to 5.04%, with an increase in the short-circuit current density in the J–V curve from 8.10 to 17.67 mA cm−2. This study demonstrates that B-P25 prepared using the reduction method can effectively fabricate photoanodes with high photovoltaic performance, which improves the optical properties and solar cell efficiency of QDSSCs. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are small, non-coding RNAs that are expressed in a tissue- and temporal-specific manner during development. They have been found to be highly conserved during the evolution of different species. miRNAs regulate the expression of several genes in various organisms, with some regulating the expression of multiple genes with similar or completely unrelated functions. Frequent disease and insect pest infestations severely limit agricultural development. Thus, cultivating resistant crops via miRNA-directed gene regulation in plants, insects, and pathogens is an important aspect of modern breeding practices. To strengthen the application of miRNAs in sustainable agriculture, plant endogenous or exogenous miRNAs have been used for plant breeding. Consequently, the development of biological pesticides based on miRNAs has become an important avenue for future pest control methods. However, selecting the appropriate miRNA according to the desired target traits in the target organism is key to successfully using this technology for pest control. This review summarizes the progress in research on miRNAs in plants and other species involved in regulating plant disease and pest resistance pathways. We also discuss the molecular mechanisms of relevant target genes to provide new ideas for future research on pest and disease resistance and breeding in plants. [ABSTRACT FROM AUTHOR]

Underwater images often exhibit color distortion and low contrast due to the scattering and absorption of light as it travels through water. Changes in lighting conditions further complicate the restoration and enhancement of these images. Improving the quality of underwater images is crucial for advancements in fields such as marine biology research, underwater measurement, and environmental monitoring. This paper proposes an underwater image restoration method based on the Image Formation Model (IFM), utilizing the Walsh–Hadamard transform and attenuation coefficient estimation. Traditional methods rely on dark channel prior and maximum intensity prior to estimate background light (BL) and transmission maps (TMs), often performing poorly in various underwater environments. Our method uses image blur to estimate BL and depth maps and derives three-channel attenuation coefficients using the gray-world theory to obtain a more accurate TM. Experimental results on real underwater images show that our method effectively eliminates color deviation and contrast distortion while preserving image details, significantly outperforming other IFM-based restoration techniques. Compared to the closest competing algorithms, our method achieves better UIQM and UCIQE scores. [ABSTRACT FROM AUTHOR]

Pansharpening refers to the process of fusing multispectral (MS) images with panchromatic (PAN) images to obtain high-resolution multispectral (HRMS) images. However, due to the low correlation and similarity between MS and PAN images, as well as inaccuracies in spatial information injection, HRMS images often suffer from significant spectral and spatial distortions. To address these issues, a pansharpening method based on multimodal texture correction and adaptive edge detail fusion is proposed in this paper. To obtain a texture-corrected ( T C ) image that is highly correlated and similar to the MS image, the target-adaptive CNN-based pansharpening (A-PNN) method is introduced. By constructing a multimodal texture correction model, intensity, gradient, and A-PNN-based deep plug-and-play correction constraints are established between the T C and source images. Additionally, an adaptive degradation filter algorithm is proposed to ensure the accuracy of these constraints. Since the T C image obtained can effectively replace the PAN image and considering that the MS image contains valuable spatial information, an adaptive edge detail fusion algorithm is also proposed. This algorithm adaptively extracts detailed information from the T C and MS images to apply edge protection. Given the limited spatial information in the MS image, its spatial information is proportionally enhanced before the adaptive fusion. The fused spatial information is then injected into the upsampled multispectral (UPMS) image to produce the final HRMS image. Extensive experimental results demonstrated that compared with other methods, the proposed algorithm achieved superior results in terms of both subjective visual effects and objective evaluation metrics. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence indicates that PSAT1 not only reprogrammed metabolic function but also exhibits "moonlighting" functions in promoting tumor malignancy. However, the underlying molecular mechanisms of PSAT1 promoting ER-negative breast cancer cell migration need further investigation. Methods: Briefly, the PSAT1 and ITGA2 expression in cells and tissues was detected using qRT-PCR, immunofluorescence staining and western blot assay. The effect of PSAT1 and ITGA2 was verified both in vitro and in vivo. RNA-seq analysis explored a series of differently expressed genes. The regulation between SP1 and ITGA2 was investigated by ChIP analysis. Results: We reported PSAT1 was highly expressed in ER-breast cancer tissues and tumor cells and positively correlated with metastasis. Moreover, RNA-seq analysis explored a series of differently expressed genes, including ITGA2, in PSAT1 overexpressed cells. Mechanistically, PSAT1 facilitated breast cancer metastasis via the p-AKT/SP1/ITGA2 axis. We further elucidated that PSAT1 promoted the entry of SP1 into the nucleus through the upregulation of p-AKT and confirmed ITGA2 is a target of SP1. In addition, enhanced cell migration was remarkably reversed by ITGA2 depletion or p-AKT inhibitor treatment. Conclusion: This study clarified the mechanism of PSAT1 in promoting ER-negative breast cancer metastasis, which may provide mechanistic clues for attenuating breast cancer metastasis. [ABSTRACT FROM AUTHOR]

Scene recognition has been the foundation of research in computer vision fields. Because scene images typically are composed of specific regions distributed in some layout, so modeling layouts of various scenes is a key clue for scene recognition. Existing methods usually require an additional stream to detect regions for subsequent modeling, which accumulate errors and may miss important information. Meanwhile, they use manual features to model relations between regions, which weakens the representation ability of layouts. In this paper, we propose a single-stream adaptive scene layout modeling approach based on a layout modeling module (LMM), which constructs layouts without additional detection streams and adaptively captures the relations to take advantage of graph attention network. LMM is directly concatenated to a convolutional neural network, where each pixel of the activation maps of the last convolutional layer is defined as a region that is the initial input node of the LMM. LMM first models the layout of each region, and then uses all regions with layout information to model the entire scene. Layout relations are encoded as edges, which are automatically analyzed according to region co-occurrence and relative position. Our work can be understood as optimizing features of the activation maps from a scene layout modeling perspective for scene recognition. Experimental results on MIT67, SUN397, and Places365 show that our single-stream model achieves competitive performance. [ABSTRACT FROM AUTHOR]

Background: The limitations of prostate-specific antigen (PSA) in diagnosing prostate cancer (PCa) necessitate the exploration of novel biomarkers. Recent studies suggest a potential link between coagulation markers, particularly fibrinogen and D-dimer, and PCa. Methods: A retrospective single-center analysis on 466 biopsy-undergone patients was conducted, categorized into PCa and benign prostatic hyperplasia (BPH) groups. Baseline and coagulation parameter levels were analyzed. Utilizing a Mendelian randomization (MR) approach, we investigated the causative relationship between D-dimer and PCa risk. Results: Individuals with PCa, compared with those with BPH, exhibited significantly higher D-dimer levels (P <.001), total PSA (P <.001), and PSA density (P <.001). Fibrinogen levels did not exhibit significant differences (P =.505). The MR analysis suggested a probable causal link between elevated D-dimer levels and an increased risk of PCa (odds ratio: 1.81, 95% confidence interval: 1.48-2.21, P = 7.4 × 10−9). Conclusions: This research highlights D-dimer as a potential biomarker for diagnosing PCa, supported by clinical and MR analyses. The study paves the way for future large-scale, multi-center research to corroborate these findings and further explore the relationship between coagulation markers and PCa mechanisms. [ABSTRACT FROM AUTHOR]

Although TiO2 has been widely used as the illumination anode in quantum dot sensitized solar cells (QDSSCs), its inherent low photovoltaic conversion efficiency remains a challenge. This study designed and prepared black rutile phase TiO2 (B-R TiO2) using sodium borohydride as a reducing agent, and utilized it as a photoanode in quantum dot-sensitized solar cells (QDSSCs). The findings illustrated that the modification of rutile phase TiO2 through the reduction method led to changes in its surface structure which in turn affects its band structure and optical absorption properties. The increase in surface oxygen vacancy concentration resulted in an enhancement of light absorption intensity, leading to an enhanced photovoltaic conversion efficiency. Subsequently, when employed as a photoanode in QDSSCs, the photovoltaic conversion efficiency (PCE) increased from an initial 1.77% to 4.27%. X-ray photoelectron spectroscopy (XPS) analysis revealed a significant increase in the oxygen vacancy (Ov) content after reduction, resulting in a rise in short-circuit current density from the original 8.10 (mA/cm2) to 15.33 (mA/cm2) as observed in the J-V curve. In conclusion, the study demonstrated the effectiveness of the reduction method in modifying the black rutile phase TiO2, resulting in improved optical properties and improved solar cell efficiency in quantum dot-sensitized solar cells. [ABSTRACT FROM AUTHOR]

In this paper, a novel radial spatial power combiner based on the WRD650 standard double‐ridge waveguide has been proposed. The combiner exhibits a significant increase in operating bandwidth due to the utilization of the upper ridge taper and the lower ridge extension. The principle prototype is designed, processed, and tested. The test results show that the overall return loss of the dual‐ridge waveguide power combiner is better than −10 dB at the input port, and the insertion loss at each output port is better than −2 dB in the 6–18 GHz band, and the maximum phase difference at each port does not exceed 11°. Due to the limitations of the processing accuracy, the final overall synthesis efficiency is higher than 70%. [ABSTRACT FROM AUTHOR]

The problem of weight degradation is inevitable in particle filtering algorithms, and the resampling approach is an important method to reduce the particle degradation phenomenon. To solve the problem of particle diversity loss in existing resampling methods, this paper proposes a new digital twin-based resampling algorithm to improve the accuracy of particle filter estimation based on the traditional resampling algorithm. The digital twin-based resampling algorithm continuously improves the resampling process through the data interaction between the data model and the physical model, and realizes the real-time correction capability of particle weights that traditional resampling methods do not have. The new algorithm calibration rules are divided according to the size of particle weights, with particles of large weights retained and particles of small weights selectively processed. Compared with the traditional resampling algorithm, the new resampling algorithm reduces the mean square error of the particle filter estimation results by 16.62 % , 16.49 % , and 13.86 % , and improves the computing speed by 7.67 % , 2.25 % , and 7.54 % , respectively, in the simulation experiments of nonlinear systems with univariate unsteady state growth model. The algorithm is experimentally demonstrated to accurately track a person in motion in an indoor building in a non-rigid target tracking application, which illustrates the effectiveness and reasonableness of the digital twin-based resampling algorithm. [ABSTRACT FROM AUTHOR]

Improper management of sugarcane cultivation may cause severe soil erosion, especially in lateritic red soil hilly areas. Crop straw return to the field can effectively improve the soil structure, but there is a lack of evaluation studies of the soil and water conservation benefits of sugarcane leaf mixing and return to the field, and the underlying regulatory mechanism has rarely been described. Thus, we conducted a series of simulated rainfall experiments to investigate the impact of returning different mixed sugarcane leaf weights (0, 3, 6, 9, 12 and 15 t/ha) to the field on erodible lateritic red soil slopes that support sugarcane production under various slopes (5°, 10°, 15° and 20°) in different rainfall events (60 and 120 mm/h). The results indicated that returning sugarcane leaves into farmland could effectively regulate the process of runoff and sediment production on lateritic red soil slopes, and the optimal mixing amount was 9 t/ha. Under a low rainfall intensity, the erosion process was mainly affected by the slope, and the benefits of applying the sugarcane leaf mixing treatment to the slope to reduce runoff and sediment could reach 13.37–53.04% and 23.86–77.55%, respectively. However, under a high rainfall intensity, the sugarcane leaf mixing amount was the main influencing factor, the benefits for reducing runoff and sediment could reach 4.64–38.72% and 30.87–93.14%, respectively. The sugarcane leaf mixing amount exhibited a linear relationship with the Reynolds number (R2 > 0.63), whereas the runoff velocity (R2 > 0.96), Froude number (R2 > 0.94) and drag coefficient (R2 > 0.85) exhibited well‐fitting exponential function relationship with it. This study provides a reference for future endeavours regarding the inhibition mechanisms of sugarcane leaves mixed and returned to the field for decreasing slope erosion. [ABSTRACT FROM AUTHOR]

The three spacecraft of the space gravitational wave antenna employ heterodyne interferometry to mitigate the effects of Doppler shift. Constrained by laser relative intensity noise (RIN) and the sampling frequency constraints of phase readout circuits, the widespread adoption of fixed offset frequencies effectively regulates the frequency of heterodyne interferometric beat notes within a reasonable frequency domain of [5 MHz, 25 MHz]. In this work, a high-precision fitness genetic algorithm for heterodyne interferometry is utilized to generate the initial offset frequency distribution scheme. To address issues with unreasonable switching times and offset frequency settings in the initial scheme for partial frequency domains, optimization strategies are proposed from three aspects: frequency domain selection extension, switch times control, and numerical low frequency. Results demonstrate that the optimization of frequency domain selection extension narrows the reasonable frequency domain to [5 MHz, 15 MHz] and [7 MHz, 17 MHz]. Optimization of switch times control ensures that switching times of offset frequency distribution scheme generated under the settings of [6 MHz, 17 MHz] and wider frequency domains can be controlled within a reasonable range of 6 to 13 times. Fixed offset frequency settings are generally reduced by 24.3% after low-frequency optimization. This methodology and result can provide a reliable reference for Program Taiji and even related space gravitational wave antenna projects. [ABSTRACT FROM AUTHOR]

In lithium‐ion batteries, the polymer electrolyte was susceptible to mechanical damage from external stimuli or internal expansion caused, which in turn affected the performances of the batteries. The thermally reversible self‐healing gel polymer electrolyte (DASHPE) based on the Diels–Alder reaction was prepared to solve the above problems. The DASHPE electrolytes exhibited good flexibility and self‐healing ability, achieving self‐healing at 80°C for 30 min. Furthermore, the DASHPE electrolyte exhibited excellent thermal stability and could withstand temperatures above 300°C. Additionally, it had a wide electrochemical window (about 5 V) and good electrochemical performances. Serving as the electrolyte in lithium‐ion batteries, DASHPE‐2 showed an initial specific capacity of 133.11 mAh g−1 at 0.1 C. The DASHPE electrolyte was expected to be a candidate material for self‐healing battery. [ABSTRACT FROM AUTHOR]

The functional role of soil microbes in the restoration of degraded lands is greatly influenced by interactions within and between microbial communities, as well as by soil organisms at higher trophic levels (microfauna). However, little is known about how changes in connection patterns among soil microbes and their co‐existing microfauna contribute to associated changes in soil function over the ecosystem restoration process.In this study, the effects of afforestation and natural regeneration approaches on connection patterns among soil microbes and their co‐existing microfauna were assessed in ex‐arable lands on the Loess Plateau in China along a 50‐year restoration chronosequence. The relationships between soil network connections, microbial functional associations, and multiple soil functions (e.g. multifunctionality) were assessed quantitatively.Although both afforestation and natural regeneration approaches enhance connections among soil microbes and their co‐existing microfauna compared to recently abandoned sites, connection trends were opposed between these two approaches across the restoration chronosequence. Afforestation resulted in a higher number of soil microbial and microfauna species with a unimodal connection pattern, while natural regeneration resulted in a continuous increase in soil network connections over the progress of succession. These increases in soil network connections, particularly those of soil microfauna‐microbe and microbial inter‐kingdom connections, corresponded to enhanced microbial functional associations. This result is corroborated by significant correlations between microbial functional genes encoding different central functional pathways, which, in turn, were positively correlated with soil multifunctionality.Synthesis and applications. Changes in the connections among soil microbes and their co‐existing microfauna were positively associated with changes in soil multifunctionality, mediated by microbial functional associations. While in the early restoration stages, soil networks following afforestation contained more connections than those following natural regeneration, in later restoration stages, the number of connections of the afforestation network declined and was eventually surpassed by those following natural regeneration. These findings raise concerns about the ecological sustainability of afforestation measures in historic grasslands on the Loess Plateau, suggesting that natural regeneration is the preferred approach to achieve long‐term ecological restoration success. [ABSTRACT FROM AUTHOR]

Drunk-driving events often escalate into drunk-driving crashes, however, the contributing factors of this progression remain elusive. To mitigate the likelihood of crashes stemming from drunk-driving events, this paper introduces the notion of 'the severity of drunk-driving event' and examines the complex relationship between the severity and its contributing factors, considering spatiotemporal heterogeneity. The study utilizes a Geographically and Temporally Weighted Binary Logistic Regression (GTWBLR) model to conduct spatiotemporal analysis based on police-reported drunk-driving events in Beijing, China. The results show that most factors passed the non-stationary test, indicating their effects on the severity of drunk-driving event vary significantly across different spatial and temporal domains. Notably, during non-workday, drunk-driving events in northeast of Beijing are more likely to escalate into crashes. Furthermore, severe weather during winter in the northwest of Beijing is associated with high risk of drunk-driving crashes. Based on these insights, the authorities can strengthen drunk-driving checks in the northeast region of Beijing, particularly during non-workdays. And it is crucial to promptly clear accumulated snow on the roads during severe winter weather to improve road safety. These insights and recommendations are highly valuable for reducing the risk of drunk-driving crashes. [ABSTRACT FROM AUTHOR]

Traffic violation is one of the leading causes of traffic crashes. In the context of global aging, it is important to study traffic violations by elderly drivers for improving traffic safety in preparation for a worldwide aging population. In this study, a hybrid approach of Latent Class Analysis (LCA) and XGBoost based SHAP is proposed to identify hidden clusters and to understand the key contributing factors on the severity of traffic violations by elderly drivers, based on the police-reported traffic violation dataset of Beijing (China). First, LCA is applied to segment the dataset into several latent homogeneous clusters, then XGBoost based SHAP is established on each cluster to identify feature contributions and the interaction effects of the key contributing factors on the severity of traffic violations by elderly drivers. Two comparison groups were set up to analyze factors, which are responsible for the different severities of traffic violations. The results show that elderly drivers can be classified into four groups by age, urban or not, license, and season; factors such as less annual number of traffic violations, national & provincial highway, night and winter are key contributing factors for higher severity of traffic violations, which are consistent with common cognition; key contributing factors for all clusters are similar but not identical, for example, more annual number of traffic violations contribute to more severe violation for all clusters except for Cluster 2; some factors which are not key contributing factors may affect the severity of traffic violations when they are combined with other factors, for example, the combination of lower annual number of traffic violations and county & township highway contributes to more severe violation for Cluster 1. These findings can help government to formulate targeted countermeasures to decrease the severity of traffic violations by specific elderly groups and improve road service for the driving population. [ABSTRACT FROM AUTHOR]

Improper management of sugarcane cultivation may cause severe soil erosion, especially in lateritic red soil hilly areas. Crop straw return to the field can effectively improve the soil structure, but there is a lack of evaluation studies of the soil and water conservation benefits of sugarcane leaf mixing and return to the field, and the underlying regulatory mechanism has rarely been described. Thus, we conducted a series of simulated rainfall experiments to investigate the impact of returning different mixed sugarcane leaf weights (0, 3, 6, 9, 12 and 15 t/ha) to the field on erodible lateritic red soil slopes that support sugarcane production under various slopes (5°, 10°, 15° and 20°) in different rainfall events (60 and 120 mm/h). The results indicated that returning sugarcane leaves into farmland could effectively regulate the process of runoff and sediment production on lateritic red soil slopes, and the optimal mixing amount was 9 t/ha. Under a low rainfall intensity, the erosion process was mainly affected by the slope, and the benefits of applying the sugarcane leaf mixing treatment to the slope to reduce runoff and sediment could reach 13.37–53.04% and 23.86–77.55%, respectively. However, under a high rainfall intensity, the sugarcane leaf mixing amount was the main influencing factor, the benefits for reducing runoff and sediment could reach 4.64–38.72% and 30.87–93.14%, respectively. The sugarcane leaf mixing amount exhibited a linear relationship with the Reynolds number (R2 > 0.63), whereas the runoff velocity (R2 > 0.96), Froude number (R2 > 0.94) and drag coefficient (R2 > 0.85) exhibited well‐fitting exponential function relationship with it. This study provides a reference for future endeavours regarding the inhibition mechanisms of sugarcane leaves mixed and returned to the field for decreasing slope erosion. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect of quick acupuncture combined with rehabilitation therapy on motor and swallowing function of patients with stroke. Design: A retrospective study. Setting: Single center study. Participants: One hundred and twenty patients with stroke were divided into control and observation group based on the therapeutic regimen. Intervention: Control group (n = 60) only received rehabilitation therapy, and observation group (n = 60) received rehabilitation therapy combined with quick acupuncture. Acupuncture was performed once a day, and 6 times/week for 4 consecutive weeks. Main measures: The simplified Fugl-Meyer assessment scale and Barthel index were used to assess limb motor function and daily living ability. The Dysphagia Outcome Severity Scale and Swallowing Quality of Life questionnaire were conducted to estimate the dysphagia severity and life quality of patients with swallowing disorders. The therapeutic efficacy and complications after treatment were analyzed and counted. Results: After treatment, the scores of the observation group were significantly improved compared with the control group (P < 0.05). In the observation group, the therapeutic efficacy was 93% (n = 56); the complication rate was 5% (n = 3); the therapeutic efficacy of the control group was 75% (n = 45); and the complication rate was 25% (n = 15), indicating that the therapeutic efficacy of the observation group is better and the incidence of complications is lower than that of the control group. Conclusion: This study suggests that rehabilitation therapy combined with rapid acupuncture therapy has a potential therapeutic effect on the relief of swallowing and motor dysfunction after stroke. [ABSTRACT FROM AUTHOR]

Based on the ERG (Existence, Relatedness and Growth) theory, a scale was developed to evaluate the professional needs of psychological counsellors in China and its related factors were explored. A total of 209 counsellors participated in the study and completed two online questionnaires. The majority of participants were female (n = 163, 78%). The average age of participants is 41.00 (SD = 8.66). The results showed that the existence needs ($\bar{x}$ x ¯ = 4.49, SD = 0.60), relatedness needs ($\bar{x}$ x ¯ = 4.20, SD = 0.65) and growth needs ($\bar{x}$ x ¯ = 4.66, SD = 0.50) of counsellors were all at a high level. Work setting, marital status and regular supervision had a significant influence on the professional needs of counsellors. Counsellors working in private practice had more existence and growth needs compared to those working in institutions. Counsellors, who were married, had more existence and relatedness needs than those who were single. Counsellors without regular supervision had more existence, relatedness and growth needs. [ABSTRACT FROM AUTHOR]

10‐Hydroxycamptothecin (HCPT) is a widely used clinical anticancer drug but has a significant side effect profile. Melatonin has a beneficial impact on the chemotherapy of different cancer cells and reproductive processes, but the effect and underlying molecular mechanism of melatonin's involvement in the HCPT‐induced side effects in cells, especially in the testicular cells, are poorly understood. In this study, we found that melatonin therapy significantly restored HCPT‐induced testicular cell damage and did not affect the antitumor effect of HCPT. Further analysis found that melatonin therapy suppressed HCPT‐induced DNA damage associated with ataxia‐telangiectasia mutated‐ and Rad3‐related and CHK1 phosphorylation levels in the testis. Changes in apoptosis‐associated protein levels (Bax, Bcl‐2, p53, and Cleaved caspase‐3) and in reactive oxygen species‐associated proteins (Nrf2 and Keap1) and index (malondialdehyde and glutathione) suggested that melatonin treatment relieved HCPT‐induced cell apoptosis and oxidative damage, respectively. Mechanistically, melatonin‐activated autophagy proteins (ATG7, Beclin1, and LC3bII/I) may induce p62‐dependent autophagy to degrade Keap1, eliciting Nrf2 from Keap1‐Nrf2 interaction to promote antioxidant enzyme expression such as HO‐1, which would salvage HCPT‐induced ROS production and mitochondrial dysfunction. Collectively, this study reveals that melatonin therapy may protect testicular cells from HCPT‐induced damage via the activation of autophagy, which alleviates oxidative stress, mitochondrial dysfunction, and cell apoptosis. [ABSTRACT FROM AUTHOR]

Background: Sevoflurane is a superior agent for maintaining anesthesia during surgical procedures. However, the neurotoxic mechanisms of clinical concentration remain poorly understood. Sevoflurane can interfere with the normal function of neurons and synapses and impair cognitive function by acting on α5‐GABAAR. Methods: Using MWM test, we evaluated cognitive abilities in mice following 1 h of anesthesia with 2.7%–3% sevoflurane. Based on hippocampal transcriptome analysis, we analyzed the differential genes and IL‐6 24 h post‐anesthesia. Western blot and RT‐PCR were performed to measure the levels of α5‐GABAAR, Radixin, P‐ERM, P‐Radixin, Gephyrin, IL‐6, and ROCK. The spatial distribution and expression of α5‐GABAAR on neuronal somata were analyzed using histological and three‐dimensional imaging techniques. Results: MWM test indicated that partial long‐term learning and memory impairment. Combining molecular biology and histological analysis, our studies have demonstrated that sevoflurane induces immunosuppression, characterized by reduced IL‐6 expression levels, and that enhanced Radixin dephosphorylation undermines the microstructural stability of α5‐GABAAR, leading to its dissociation from synaptic exterior and resulting in a disordered distribution in α5‐GABAAR expression within neuronal cell bodies. On the synaptic cleft, the expression level of α5‐GABAAR remained unchanged, the spatial distribution became more compact, with an increased fluorescence intensity per voxel. On the extra‐synaptic space, the expression level of α5‐GABAAR decreased within unchanged spatial distribution, accompanied by an increased fluorescence intensity per voxel. Conclusion: Dysregulated α5‐GABAAR expression and distribution contributes to sevoflurane‐induced partial long‐term learning and memory impairment, which lays the foundation for elucidating the underlying mechanisms in future studies. [ABSTRACT FROM AUTHOR]

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A method of preparing SiO2‐BNNSs hybrid material by surface modification of boron nitride nanosheets (BNNSs) with SiO2 was proposed to improve the dispersion of BNNSs in the coatings. Then, phosphate ceramic coatings with BNNSs and SiO2‐BNNSs were prepared on stainless steel (304) by spraying. Characterization of BNNSs and SiO2‐BNNSs by X‐ray diffraction, Fourier transform‐infrared, Raman, and scanning electron microscopy proved the success of hybridization. The surface morphology and mechanical properties were conducted to characterize the protective performance of the coating. Simultaneously, the phase composition and electrochemical properties of the coatings after high‐temperature oxidation were studied. The results showed that ceramic coatings had low surface energy with a contact angle of 102.41° when.4 wt.% SiO2‐BNNSs was added. Compared with BNNSs coating, the mechanical properties of SiO2‐BNNSs coating were significantly enhanced, the hardness of.4 wt.%SiO2‐BNNSs coating was as high as 170 HV, and the interface bonding strength was 12.24 MPa. For the oxidation corrosion resistance,.4 wt.% SiO2‐BNNSs coating under oxidation at 400°C for 50 h had the minimum corrosion current density and maximum impedance, which were.864 μA/cm2 and 177 kΩ/cm2, respectively, this indicated that SiO2‐BNNSs coating could still maintain excellent oxidation corrosion resistance under high‐temperature conditions for a long time. [ABSTRACT FROM AUTHOR]

The underwater optical imaging environment presents unique challenges due to its complexity. This paper addresses the limitations of existing algorithms in handling underwater images captured in artificial light scenes. We proposed an underwater artificial light optimization algorithm to preprocess images with uneven lighting, mitigating the effects of light distortion. Furthermore, we proposed a novel underwater image enhancement algorithm based the Multiscale Fusion Generative Adversarial Network, named UMSGAN, to address the issues of low contrast and color distortion. UMSGAN uses the generative adversarial network as the underlying framework and first extracts information from the degraded image through three parallel branches separately, and adds residual dense blocks in each branch to learn deeper features. Subsequently, the features extracted from the three branches are fused and the detailed information of the image is recovered by the reconstruction module, named RM. Finally, multiple loss functions are linearly superimposed, and the adversarial network is trained iteratively to obtain the enhanced underwater images. The algorithm is designed to accommodate various underwater scenes, providing both color correction and detail enhancement. We conducted a comprehensive evaluation of the proposed algorithm, considering both qualitative and quantitative aspects. The experimental results demonstrate the effectiveness of our approach on a diverse underwater image dataset. The proposed algorithm exhibits superior performance in terms of enhancing underwater image quality, achieving significant improvements in contrast, color accuracy, and detail preservation. The proposed methodology exhibits promising results, offering potential applications in various domains such as underwater photography, marine exploration, and underwater surveillance. [ABSTRACT FROM AUTHOR]

The authors study the problem of compressive target detection in a single‐frequency network (SFN)‐based multistatic passive radar system (MS‐PRS) consisting of multiple illuminators of opportunity (IOs) and one receiver. Firstly, a generalised likelihood ratio test (GLRT)‐based SFN‐based compressive subspace detector (SFN‐CSD) is derived by exploiting the sparsity of the target echoes for the case of known noise variance. When the noise variance is unknown, an SFN‐based unknown‐noise (UN) compressive subspace detector is proposed, referred to as the SFN‐UNCSD. Moreover, closed‐form expressions of the probability of false alarm and detection of the proposed detectors are deriived. It is proved that the SNF‐UNCSD has a constant false alarm rate (CFAR) property. Finally, numerical simulations are conducted to verify the theoretical analysis and illustrate the performance of the proposed detector relative to several benchmark detectors. [ABSTRACT FROM AUTHOR]

High-precision temperature control of large-area blackbodies has a pivotal role in temperature calibration and thermal imaging correction. Meanwhile, it is necessary to correct the temperature difference between the radiating (surface of use) and back surfaces (where the temperature sensor is installed) of the blackbody during the testing phase. Moreover, large-area blackbodies are usually composed of multiple temperature control channels, and manual correction in this scenario is error-prone and inefficient. At present, there is no method that can achieve temperature-automated calibration for a large-area blackbody radiation source. Therefore, this article is dedicated to achieving temperature-automated calibration for a large-area blackbody radiation source. First, utilizing two calibrated infrared thermometers, the optimal temperature measurement location was determined using a focusing algorithm. Then, a three-axis movement system was used to obtain the true temperature at the same measurement location on a large-area blackbody surface from different channels. This temperature was subtracted from the blackbody's back surface. The temperature difference was calculated employing a weighted algorithm to derive the parameters for calibration. Finally, regarding experimental verification, the consistency error of the temperature measurement point was reduced by 85.4%, the temperature uniformity of the surface source was improved by 40.4%, and the average temperature measurement deviation decreased by 43.8%. In addition, this system demonstrated the characteristics of strong environmental adaptability that was able to perform temperature calibration under the working conditions of a blackbody surface temperature from 100 K to 573 K, which decreased the calibration time by 9.82 times. [ABSTRACT FROM AUTHOR]

Ultra-compact spectrometers are becoming increasingly popular for their promising applications in biomedical analysis, environmental monitoring, and food safety. In this work, we report a single-pixel-photodetector spectrometer with a spectral range from 480 nm to 820 nm, based on the AlGaAs/GaAs p-graded-n junction with a voltage-tunable optical response. To reconstruct the optical spectrum, we propose a tailored method called Neural Spectral Fields (NSF) that leverages the unique wavelength and bias-dependent responsivity matrix. Our spectrometer achieves a high spectral wavelength accuracy of up to 0.30 nm and a spectral resolution of up to 10 nm. Additionally, we demonstrate the high spectral imaging performance of the device. The compatibility of our demonstration with the standard III-V process greatly accelerates the commercialization of miniaturized spectrometers. The miniaturization of spectrometers to a submillimeter-scale footprint opens opportunities for applications in hyperspectral imaging and lab-on-a-chip systems. Here, the authors report a high-performance single-pixel photodetector spectrometer based on the III-V semiconductor p-graded-n junction, featuring a voltage-tunable optical response. [ABSTRACT FROM AUTHOR]

Rare precipitation events with return periods of multiple decades to hundreds of years are particularly damaging to natural and societal systems. Projections of such rare, damaging precipitation events in the future climate are, however, subject to large inter‐model variations. We show that a substantial portion of these differences can be ascribed to the projected warming uncertainty, and can be robustly reduced by using the warming observed during recent decades as an observational constraint, implemented either by directly constraining the projections with the observed warming or by conditioning them on constrained warming projections, as verified by extensive model‐based cross‐validation. The temperature constraint reduces >40% of the warming‐induced uncertainty in the projected intensification of future rare daily precipitation events for a climate that is 2°C warmer than preindustrial across most regions. This uncertainty reduction together with validation of the reliability of the projections should permit more confident adaptation planning at regional levels. Plain Language Summary: Very rare extreme precipitation events are particularly damaging to natural and societal systems. Projections of such rare, damaging precipitation events in the future climate vary substantially among climate models. Reducing this uncertainty will aid adaptation planning. We show here that the projected range of future rare precipitation intensification is strongly affected by the projected range of global warming, especially for regions where the intensification is dominated by increases in atmospheric moisture. We verify that using the past global warming trend as an observational constraint can eliminate more than 40% of the warming‐induced uncertainty in the intensification of future rare precipitation events at 2°C warmer above preindustrial across most global land regions. This narrowing of the possible range of future rare precipitation intensification at regional scales can greatly benefit adaptation planning. Key Points: Projections of future rare precipitation intensification exhibit substantial differences among climate modelsA substantial portion of the inter‐model differences can be traced to the projected global warming uncertaintyUsing the past global warming trend as an observational constraint can eliminate >40% of the warming‐induced uncertainty [ABSTRACT FROM AUTHOR]

Background: Heart failure (HF) is the last stage in the progression of various cardiovascular diseases. Although it is documented that CD151 contributes to regulate the myocardial infarction, the function of CD151 on HF and involved mechanisms are still unclear. Method and results: In the present study, we found that the recombinant adeno-associated virus (rAAV)-mediated endothelial cell-specific knockdown of CD151-transfected mice improved transverse aortic constriction (TAC)-induced cardiac function, attenuated myocardial hypertrophy and fibrosis, and increased coronary perfusion, whereas overexpression of the CD151 protein aggravated cardiac dysfunction and showed the opposite effects. In vitro, the cardiomyocytes hypertrophy induced by PE were significantly improved, while the proliferation and migration of cardiac fibroblasts (CFs) were significantly reduced, when co-cultured with the CD151-silenced endothelial cells (ECs). To further explore the mechanisms, the exosomes from the CD151-silenced ECs were taken by cardiomyocyte (CMs) and CFs, verified the intercellular communication. And the protective effects of CD151-silenced ECs were inhibited when exosome inhibitor (GW4869) was added. Additionally, a quantitative proteomics method was used to identify potential proteins in CD151-silenced EC exosomes. We found that the suppression of CD151 could regulate the PPAR signaling pathway via exosomes. Conclusion: Our observations suggest that the downregulation of CD151 is an important positive regulator of cardiac function of heart failure, which can regulate exosome-stored proteins to play a role in the cellular interaction on the CMs and CFs. Modulating the exosome levels of ECs by reducing CD151 expression may offer novel therapeutic strategies and targets for HF treatment. [ABSTRACT FROM AUTHOR]

This paper uses the Entropy Weight Method‐Grey Relational Analysis (EWM‐GRA) and Covariance Base Structural Equations Model (CB‐SEM) to study the relationships between driving habits and efficiency. EWM‐GRA ranks 12 indicators in terms of their relevance of lane‐changing and driving efficiency. Based on this, a CB‐SEM‐based framework to describe the relevance between driving habits and lane‐changing is established, focusing on the effects of lane‐changing and car‐following behaviour. To validate the established framework, NGSIM trajectory data is used as measurement variables to describe latent variables. Several hypotheses about the relationships between the latent variables in this framework are proposed, and they are verified using trajectory data. The results show that driving habits have a direct impact on efficiency, and this impact becomes more significant when associated with lane‐change behaviour. [ABSTRACT FROM AUTHOR]

Few-shot action recognition is a challenging problem aimed at learning a model capable of adapting to recognize new categories using only a few labeled videos. Recently, some works use attention mechanisms to focus on relevant regions to obtain discriminative representations. Despite the significant progress, these methods still cannot attain outstanding performance due to insufficient examples and a scarcity of additional supplementary information. In this paper, we propose a novel Semantic-guided Spatio-temporal Attention (SGSTA) approach for few-shot action recognition. The main idea of SGSTA is to exploit the semantic information contained in the text embedding of labels to guide attention to more accurately capture the rich spatio-temporal context in videos when visual content is insufficient. Specifically, SGSTA comprises two essential components: a visual-text alignment module and a semantic-guided spatio-temporal attention module. The former is used to align visual features and text embeddings to eliminate semantic gaps between them. The latter is further divided into spatial attention and temporal attention. Firstly, a semantic-guided spatial attention is applied on the frame feature map to focus on semantically relevant spatial regions. Then, a semantic-guided temporal attention is used to encode the semantically enhanced temporal context with a temporal Transformer. Finally, use the spatio-temporally contextual representation obtained to learn relationship matching between support and query sequences. In this way, SGSTA can fully utilize rich semantic priors in label embeddings to improve class-specific discriminability and achieve accurate few-shot recognition. Comprehensive experiments on four challenging benchmarks demonstrate that the proposed SGSTA is effective and achieves competitive performance over existing state-of-the-art methods under various settings. [ABSTRACT FROM AUTHOR]

Road crashes cause significant traffic delay and bring unnecessary financial losses. This study investigates the impact of contributing factors on the level of delay caused by crashes (LDC) using Texas crash data. To capture the unobserved heterogeneity, a latent class analysis (LCA) was first used to segment the whole dataset into several homogeneous clusters. Then, XGBoost based SHAP was developed on each cluster to identify the main contributing factors hidden in the latent classes. The interaction effects between the contributing factors were subsequently analyzed, including the effects between high importance features and between high and low importance features. The LCA results indicate that season is the main factor producing heterogeneity, hence the data were divided into four clusters. The main contributing factors and the interaction effects are different among the four clusters, as shown by the XGBoost based SHAP algorithm. For example, Sunrise_Sunset, Peak_hours and Crossing are the main contributing factors in Fall and Winter crash, whereas Traffic_Signal, Workday and Junction are the main contributing factors in Summer and Spring crash. The interaction effects of Highway and Zone are different in Fall and Winter crash. This study can provide insightful information for regulators to develop targeted policies in different seasons. [ABSTRACT FROM AUTHOR]

Traffic crashes cause serious traffic delay and have some unobserved heterogeneity in different areas. Using Texas accident data in 2020, this article aims to predict the level of delay caused by crashes (LDC) accurately and efficiently and discuss the difference between metropolitan and non-metropolitan areas. A framework based on Random Forests (RF) and LightGBM (LGBM) is developed to measure the association between LDC and its possible risk factors. At first, the most relevant variables in different areas were recognised through recursive feature elimination based on logistic regression. Then, LDC were forecasted by classifiers after grid search hyper parameters. To resolve data imbalance, two threshold moving methods of maximisation G-mean and F1-score were used. Finally, SHapley Additive explanation was employed to interpret the best model. The results indicate that the improved RF performs better in metropolitan areas and the improved LGBM performs better in non-metropolitan areas. In addition, Highway, spring and sunrise are the main risk factors of higher LDC in the two areas. And excessive wind speed and temperature in metropolitan areas can lead to higher LDC while in non-metropolitan areas it is pressure and apparent temperature. [ABSTRACT FROM AUTHOR]

Background: Anterior cruciate ligament injury is a common knee joint injury. Anterior cruciate ligament reconstruction is a common surgical treatment to treat anterior cruciate ligament injury. It may have certain advantages to retain the ligament stump during the operation, but the results of systematic evaluation on whether to retain the ligament stump are different. The conclusion is still controversial, and the quality needs to be strictly evaluated. Objective: To evaluate the methodological quality, risk of bias, reporting quality and evidence quality of the systematic review of remnant preservation in anterior cruciate ligament reconstruction, and to provide reference for clinical work. Methods: We systematically searched the system evaluations in 8 electronic databases, the languages were limited to Chinese and English, and the time limit was from the establishment of the database to June 2023. Two reviewers independently screened literature and extracted data. The methodological quality, risk of bias, reporting quality and quality of evidence were evaluated by AMSTAR-2, ROBIS, PRISMA and GRADE tools. Results: A total of 14 systematic reviews were included. The evaluation of results showed that the methodological quality of the included systematic reviews was relatively low, of which 5 were low quality and 9 were critically low quality. A small number of systematic reviews were low risk of bias. The system evaluation reports are relatively complete, but the lack of program registration is a common problem. A total of 111 pieces of clinical evidence were extracted from the included 14 systematic reviews. The quality of evidence was generally low, with only 7 pieces of high-quality evidence, 45 pieces of medium-quality evidence, and the rest were low and very low-quality evidence. Among the reasons for relegation, imprecision is the most common, followed by inconsistency and indirectness. The existing evidence shows that patients after anterior cruciate ligament reconstruction with remnant preservation have certain advantages in knee joint function, joint stability and proprioception recovery, which may be a more effective surgical method. However, it may also increase the incidence of postoperative complications and adverse reactions. Conclusion: Compared with Standard Technique, Remnant Preservation in Anterior Cruciate Ligament Reconstruction has more advantages in restoring joint function and stability and proprioception. But the potential risks should also be considered by surgeons. At present, the quality of evidence is generally low, and the reliability of the conclusion is insufficient. It still needs to be verified and further in-depth research is needed. [ABSTRACT FROM AUTHOR]

The growth of large‐scale bilayer graphene (bi‐graphene) is significantly important for graphene‐based device fabrications. Chemical vapor deposition is usually used for the synthesis of high‐quality and large‐scale thin films including various monolayers and bilayers. However, a major challenge for bi‐graphene growth is the so‐called limited underlayer coverage, i.e., the faster growth of the top layer than the underlayer. Herein, using the circumfluence chemical vapor deposition, it is demonstrated that the underlayer growth can be greatly enhanced via optimizing the streamline, and high‐quality AB‐stacking sub‐millimeter bi‐graphene with underlayer coverage over 93% is achieved successfully. Raman spectroscopy and selected area electron diffraction confirm the high crystalline quality and uniformity of the as‐grown bilayers. The as‐fabricated field‐effect transistor using the bi‐graphene as the channel layer exhibits typical semiconductor transfer characteristics and a nonzero bandgap which is required for device applications. It is suggested that the optimized streamline design largely allows a reduction of difference in the edge growth kinetics between the top and bottom layers. Thus, in this work, a promising technical route is presented for the growth of large‐scale bi‐graphene with high underlayer coverage, beneficial for the development of functional graphene devices. [ABSTRACT FROM AUTHOR]

In this work, the melt polycondensation method was used to synthesize aliphatic polyesters from 1,12-dodecanediol and aliphatic diacids with even carbon atoms. Gel permeation chromatography, hydrogen-1 nuclear magnetic resonance (1H NMR), infrared spectroscopy, differential scanning calorimetry, wide-angle X-ray diffraction, thermogravimetric analysis, tensile test, dynamic mechanical analysis, and rotational rheometer were used for characterization. All polyesters had high weight average molecular weight (> 60,000 g/mol). Poly(1,12-dodecylene adipate) had the lowest weight average molecular weight (66,360 g/mol) and poor thermal stability. Four polyesters had very flexible molecular chains and shared a crystalline structure with polyethylene. Poly(1,12-dodecylene octanedioate) and poly(1,12-dodecylene sebacate) had tensile strength of 20.8 MPa and 25.3 MPa, respectively, and elongation at break of 255% and 254%, respectively, meaning that their tensile properties were similar to those of polyethylene. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the numerical solution of the second kind of Volterra integral equation with a highly oscillatory Fourier kernel. Based on the calculation of the modified moments, we propose four collocation methods to solve the equations: direct linear interpolation, direct higher order interpolation, direct Hermite interpolation and piecewise Hermite interpolation. These four methods are simple to construct and can quickly compute highly oscillatory integrals involving Fourier functions. We present the corresponding error analysis and it is easy to see that, in some cases, our proposed method has a fast convergence rate in solving such equations. In some cases, our proposed methods have significant advantages over the existing methods. Some numerical experiments demonstrating the efficiency of the four methods are also presented. [ABSTRACT FROM AUTHOR]

The development and functional perfection of urban areas have led to increasingly severe fire risks in recent decades. Previous urban fire risk assessment methods relied on subjective judgment, rough data collection, simple linear statistical methods, etc. These drawbacks can lead to low robustness of evaluation and inadequate generalization ability. To resolve these problems, this paper selects the indicator and regression models based on the high-resolution data of the spatial distribution characteristics of Longquanyi distinct in Chengdu, China. and proposes an integrated machine learning algorithm for fire risk assessment. Firstly, the kernel density analysis is used to map the fourteen urban characteristics related to fire risks. The contributions of these indicators (characteristics) to fire risk and its corresponding index are determined by Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGBoost). Then, the spatial correlation of fire risks is determined through Moran's I, and the spatial distribution pattern of indicator weights is clarified through the raster coefficient space analysis. Finally, with these selected indicators, we test the regression performance with a backpropagation neural network (BPNN) algorithm and a geographically weighted regression (GWR) model. The results indicate that numerical variables are more suitable than dummy variables for estimating micro-scale fire risks. The main factors with a high contribution are all numerical variables, including roads, gas pipelines, GDP, hazardous chemical enterprises, petrol and charging stations, cultural heritage protection units, assembly occupancies, and high-rise buildings. The machine learning algorithm integrating RF and BPNN shows the best performance (R2 = 0.97), followed by the RF-GWR integrated algorithm (R2 = 0.87). Compared with previous methods, this algorithm reduces the subjectivity of the traditional assessment models and shows the ability to automatically obtain the key indicators of urban fire risks. Hence, this new approach provides us with a more robust tool for assessing the future fire safety level in urban areas. [ABSTRACT FROM AUTHOR]

Background: Exosomes are a new class of molecular entities in the metastatic microenvironment, which can mediate bidirectional communication between cells. While exosomes-mediated interactions between tumor cells and other cell populations in the tumor microenvironment have attracted most attention, little is known about the significance of exosomes in mediating the interaction between non-stemness cancer cells and cancer stem cells during cancer progression. Methods: The structure, sequence and downstream target miRNAs of lncRNA Mir100hg were predicted by online web resources. The bioinformatics prediction results were validated with experimental verification: exosome tracing, electron microscopy, Luciferase assay, metabolomics sequencing and mouse tail vein model of pulmonary metastasis. A complex regulatory network of "cancer stem cells-exosomal lncRNA-non-stem cancer cells" was constructed. Results: This study demonstrates firstly that lncRNA Mir100hg is upregulated in lung cancer stem cell LLC-SD (Lung cancer stem cells) and can be delivered to non-stemness cancer cells LLC (Lewis lung cancer cells) via exosomes. In LLC, Mir100hg targets miR-15a-5p and miR-31-5p which leads to the increase of the global glycolytic activity of lung cancer cells and consequently, the enhancement of their metastatic capability. Conclusion: We delineated a complex regulatory network that utilized by cancer stem cells to transfer their high metastatic activity to the low-metastatic non-stemness cancer cells through exosomal Mir100hg, thereby providing new mechanistic insights into the communication between two heterogeneous tumor cells. EX9vzfLURWcPee8x9snm8i Video Abstract [ABSTRACT FROM AUTHOR]

Diamond/SiC (Dia/SiC) composites possess excellent properties, such as high thermal conductivity and low thermal expansion coefficient. In addition, they are suitable as electronic packaging materials. This study mainly optimized the diamond particle size packing and liquid-phase silicon infiltration processes and investigated a method to prevent the adhesion of the product to molten silicon. Based on the Dinger–Funk particle stacking theory, a multiscale diamond ratio optimization model was established, and the volume ratio of diamond particles with sizes of D20, D50, and D90 was optimized as 1:3:6. The method of pressureless silicon infiltration and the formulas of the composites were investigated. The influences of bedding powder on phase composition and microstructure were studied using X-ray diffraction and scanning electron microscopy, and the optimal parameters were obtained. The porosity of the preform was controlled by regulating the feeding amount through constant volume molding. Dia/SiC-8 exhibited the highest density of 2.73 g/cm3 and the lowest porosity of 0.6%. To avoid adhesion between the sample and buried powder with the bedding silicon powder, a mixed powder of α-Si3N4 and silicon was used as the buried powder and the related mechanisms of action were discussed. [ABSTRACT FROM AUTHOR]

The main goal of this study is to investigate the unobserved heterogeneity in VRU-MV crash data and to determine the relatively important contributing factors of injury severity. For this end, a latent class analysis (LCA) coupled with random parameters logit model (LCA-RPL) is developed to segment the VRU-MV crashes into relatively homogeneous clusters and to explore the differences among clusters. The random-forest-based SHapley Additive exPlanation (RF-SHAP) approach is used to explore the relative importance of the contributing factors for injury severity in each cluster. The results show that, vulnerable group (VG), intersection or not (ION) and road type (RT) clearly distinguish the crash clusters. Moto-vehicle type and functional zone have significant impact on the injury severity among all clusters. Several variables (e.g. ION, crash type [CT], season and RT) demonstrate a significant effect in a specific sub-cluster model. Results of this study provide specific and insightful countermeasures that target the contributing factors in each cluster for mitigating VRU-MV crash injury severity. [ABSTRACT FROM AUTHOR]

Polylactic acid (PLA) is a kind of bio-based and biodegradable polyester and has shown promise in a variety of fields, but its wider application is limited due to its brittle property. Therefore, in order to improve the ductility of PLA, we synthesized bio-based and biodegradable poly(butylene adipate-copolybutylene furandicarboxylate) (PBAF70) and blended with PLA. The blend's structure, mechanical properties, thermal properties, crystallization properties, and rheological properties were characterized. The results reveal that when the amount of PBAF70 varies from 0 to 30 wt%, the elongation at break increases from 5.7 to 222%, indicating that PBAF70 enhanced the ductility of PLA. At the same time, XRD results showed that stretching-induced crystallization occurred in PBAF70 during the stretching process. The strongly electronegative oxygen atoms in the furan ring may increase the interaction and the compatibility between PBAF70 and PLA. Therefore, the glass transition temperature of PBAF70 is not obvious in the DSC curves of the blends, and the rheological results show that the complex viscosity of the blends is greater than that of PLA. Due to the addition of PBAF70, PLA can only crystallize at a higher temperature, and the addition of PBAF70 hinders the cold crystallization of PLA. It can be seen from SEM that the cross section of the blend is rough, while the PLA is smooth. When the amount of PBAF70 was the same as that of PBAT, the elongation at break of PLA/PBAF70 was better than PLA/PBAT. [ABSTRACT FROM AUTHOR]