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Abstract When the coal gangue sorting robot sorts coal gangue, the position of the target coal gangue will change due to belt slippage, deviation, and speed fluctuations of the belt conveyor. This will cause the robotic to fail in grasping or miss grasping. We have developed a solution to this problem: the IMSSP-Net two-stage network gangue image fast matching method. This method will reacquire the target gangue position information and improve the robot’s grasping precision and efficiency. In the first stage, we use SuperPoint to guarantee the scene adaptability and credibility of feature point extraction. We have enhanced Superpoint’s ability to detect feature points further by using the improved Multi-scale Retinex with Color Restoration enhancement algorithm. In the second stage, we introduce SuperGlue for feature matching to improve the robustness of the matching network. We eliminated erroneous feature matching point pairs and improved the accuracy of image matching by adopting the PROSAC algorithm. We conducted image matching comparison experiments under different object distances, scales, rotation angles, and complex conditions. The experimental platform adopts the double-manipulator truss-type coal gangue sorting robot independently developed by the team. The matching precision, recall, and matching time of the method are 98.2%, 98.3%, and 84.6ms, respectively. The method can meet the requirements of efficient and accurate matching between coal gangue recognition images and sorting images.

Objective To explore effective treatments and prognostic factors for diffuse intrinsic pontine glioma (DIPG). Methods Clinical and imaging information and survival data of 14 DIPG patients, treated with radiotherapy combined with temozolomide and nitolizumab or radiotherapy combined with ACT001, were retrospectively analysed at Beijing Tiantan Hospital, Capital Medical University from April 2021 to January 2024. The median progression free survival (PFS) and overall survival (OS) were calculated using Kaplan - Meier survival curves, and multifactorial Cox regression analysis was used to investigate the effects of different factors on PFS and OS. Results The objective response rate (ORR) was 10/14, and the median PFS and OS were 7.83 and 8.30 months, respectively. Multfactorial Cox regression analysis identified the absence of enhancement on baseline imaging as a good prognostic variable for both PFS (RR = 0.052, 95%CI: 0.006-0.416; P = 0.005) and OS (RR = 0.046, 95%CI: 0.005-0.413; P = 0.006), while male (RR = 0.085, 95%CI: 0.009-0.764; P = 0.028), older age (RR = 0.631, 95%CI: 0.423-0.942; P = 0.024), and the absence of symptoms of cranial nerve involvement at the onset (RR = 0.116, 95%CI: 0.017- 0.781; P = 0.027) were also good prognostic variables for OS. Conclusions Female, younger age at diagnosis, cranial nerve involvement at the onset, and enhancement on baseline imaging are risk factors for the survival of children with DIPG.

The advantages of fast charging speed and high efficiency of DC charging piles make the connection and cutting of electric vehicle (EV) loads relatively frequent. However, as a DC system, DC charging pile has the characteristics of low inertia and weak damping. In order to reduce the impact of EV load connection and cutting on the DC side voltage disturbance, a DC charging pile control method based on improved virtual inertia (VI) control is proposed. This paper firstly introduces VI control by analogy with virtual synchronous machines (VSM) technology. Secondly, the VI control is improved by using command filter backstepping integral sliding mode (CFBISM) control, in which the integral sliding mode (ISM) control is used to optimize the VI control to enhance the robustness of the system, and the command filter backstepping control is used to reconfigure the key parameters to avoid the computational inflation of the controller, while the ISM control is used to improve the current inner loop to further enhance the control effect. The stability of the proposed control strategy is then demonstrated by the Lyapunov stability criterion. Finally, through comparative simulation, it is verified that the DC-side voltage fluctuation can be limited within 2 V, the dynamic response speed is improved by about 0.1 s, and the perturbation of the key parameters in the steady state is limited to about 1 V, thus the superiority of the fast response speed and good robustness of the control proposed in this paper are verified by simulation.

Superhydrophobic coating is the ideal anti-icing materials, and the superhydrophobic materials can delay the formation of ice crystals or reduce the strength of ice adhesion, but the existing coating has the problems such as poor mechanical property and fast natural aging of performance parameters. The modified graphene is partially embedded into the elastomer to produce a new coating. The icing-deicing performance of the coating is tested and compared, and the surface structure and chemical composition of the coating are analyzed. The results show that the new coating has a certain ability of electric deicing. In the re-mechanical properties test, the coating showed excellent properties in strain, wear resistance and aging resistance. The graphene introduced into the coating is the key to make the coating have a certain active deicing ability. The unique active and passive dual deicing properties of the coating are different from the traditional passive coating unique properties, which not only lays the foundation for the research and development of dual-attribute anti-icing coating but also opens up a new development direction of anti-icing coating.

The battlefield changes rapidly in information warfare. The battlefield situation data presents massive and diversified characteristics, which makes it increasingly difficult to identify the operational intent of air targets based on expert experience. In combination with the current state-of-the-art intelligent methods, the Transformer model is studied and introduced into the field of air target intent recognition for the first time, and a new intent recognition method temporal-spatial transformer(TST) is designed, which can effectively mine the deep feature information in the temporal and spatial domains of battlefield situational data to improve the accuracy of air target combat intention recognition. In addition, a comparative study of the four currently advanced neural network intention recognition methods shows that TST achieved outstanding performance in all indicators and outperformed all compared neural network models. TST method not only has excellent accuracy but also extremely fast convergence rate, which allows it to quickly capture key information from battlefield situation data for intention recognition.

Recent scientific investigations have revealed the intricate mechanisms underlying bone formation, emphasizing the essential role of long non-coding RNAs (lncRNAs) as critical regulators. This process, essential for skeletal strength and functionality, involves the transformation of mesenchymal stem cells into osteoblasts and subsequent deposition of bone matrix. lncRNAs, including HOX transcript antisense RNA (HOTAIR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), differentiation antagonizing non-coding RNA (DANCR), and maternally expressed gene 3 (MEG3), have emerged as prominent players in this regulatory network. HOTAIR modulates osteoblast differentiation by interacting with chromatin-modifying enzymes, while MALAT1 regulates osteogenic differentiation through microRNA interactions. DANCR collaborates with Runx2 to fine-tune osteoblast differentiation, and MEG3 orchestrates multiple signaling pathways crucial for bone formation. Moreover, other lncRNAs such as H19, lncRNA for enhancing osteogenesis 3, rhabdomyosarcoma 2-associated transcript, urothelial cancer associated 1, taurine up-regulated gene 1, and nuclear enriched abundant transcript 1 contribute to the complex regulatory network governing osteoblast activities. Understanding the precise roles of these lncRNAs offers promising avenues for developing innovative therapeutic strategies targeting bone-related disorders like osteoporosis. Overall, this review summarizes the pivotal role of lncRNAs in bone formation, highlighting their potential as targets for future research endeavors aimed at advancing therapeutic interventions in bone diseases.

Objective In order to improve train operational efficiency, it is necessary to monitor metro traction power consumption and establish a relevant energy consumption model for prediction analysis of metro traction power consumption. Method The basic principles of grey prediction model and BP (backpropagation) neural network are introduced. Taking the traction daily electricity consumption data for a typical metro station in Tianjin in June 2021 as example, the grey correlation analysis method is used to select the influencing factors with high correlation to the daily traction power consumption of metro. Based on the GM (1,1) grey prediction model, the short-term traction daily power consumption is predicted. The selected influencing factors with high correlation, the short-term traction daily power consumption predicted by GM (1,1) grey model, and the adjacent historical traction daily power consumption data are used as input for training in BP neural network model to establish the GM-BP grey neural network model. The required short-term metro traction daily power consumption prediction data is generated. Result & Conclusion Compared with conventional GM (1,1) grey prediction model and BP neural network model, the prediction error of short-term traction daily power consumption predicted by the GM-BP grey neural network model shows significant improvement, and can be used as effective metro traction power consumption data for short-term prediction data analysis.

Abstract Sepsis is a severe disease characterized by high mortality rates. Our aim was to develop an early prognostic indicator of adverse outcomes in sepsis, utilizing easily accessible routine blood tests. A retrospective analysis of sepsis patients from the MIMIC-IV database was conducted. We performed univariate and multivariate regression analyses to identify independent risk factors associated with in-hospital mortality within 28 days. Logistic regression was utilized to combine the neutrophil-to-lymphocyte ratio (NLR) and the neutrophil-to-platelet ratio (NPR) into a composite score, denoted as NLR_NPR. We used ROC curves to compare the prognostic performance of the models and Kaplan–Meier survival curves to assess the 28 day survival rate. Subgroup analysis was performed to evaluate the applicability of NLR_NPR in different subpopulations based on specific characteristics. This study included a total of 1263 sepsis patients, of whom 179 died within 28 days of hospitalization, while 1084 survived beyond 28 days. Multivariate regression analysis identified age, respiratory rate, neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-platelet ratio (NPR), hypertension, and sequential organ failure assessment (SOFA) score as independent risk factors for 28 day mortality in septic patients (P

Introduction: Sessile plants engage in trade-offs between growth and defense capacity in response to fluctuating environmental cues. MYB is an important transcription factor that plays many important roles in controlling plant growth and defense. However, the mechanism behind how it keeps a balance between these two physiological processes is still largely unknown. Objectives: Our work focuses on the dissection of the molecular mechanism by which GhMYB33 regulates plant growth and defense. Methods: The CRISPR/Cas9 technique was used to generate mutants for deciphering GhMYB33 functions. Yeast two-hybrid, luciferase complementary imaging, and co-immunoprecipitation assays were used to prove that proteins interact with each other. We used the electrophoretic mobility shift assay, yeast one-hybrid, and luciferase activity assays to analyze GhMYB33 acting as a promoter. A β-glucuronidase fusion reporter and 5′ RNA ligase mediated amplification of cDNA ends analysis showed that ghr-miR319c directedly cleaved the GhMYB33 mRNA. Results: Overexpressing miR319c-resistant GhMYB33 (rGhMYB33) promoted plant growth, accompanied by a significant decline in resistance against Verticillium dahliae. Conversely, its knockout mutant, ghmyb33, demonstrated growth restriction and concomitant augmentation of V. dahliae resistance. GhMYB33 was found to couple with the DELLA protein GhGAI1 and bind to the specific cis-elements of GhSPL9 and GhDFR1 promoters, thereby modulating internode elongation and plant resistance in V. dahliae infection. The ghr-miR319c was discovered to target and suppress GhMYB33 expression. The overexpression of ghr-miR319c led to enhanced plant resistance and a simultaneous reduction in plant height. Conclusion: Our findings demonstrate that GhMYB33 encodes a hub protein and controls the expression of GhSPL9 and GhDFR1, implicating a pivotal role for the miR319c-MYB33 module to regulate the trade-offs between plant growth and defense.

In order to ensure the safety of eVTOL, safety analysis of thermal runaway problem of lithium battery is needed. Due to insufficient failure data, a safety assessment method based on evidence theory and interval analysis is proposed. Firstly, a fault tree model for system is constructed. Secondly, for the imprecise failure rate of bottom events in fault tree analysis, the failure probability interval of bottom event is calculated by using the evidence theory, and combining with the importance analysis to address the problem of inaccurate failure rate of bottom events in fault tree analysis. The evidence theory is used to calculate the probability interval of failure of bottom events and combine it with interval theory to calculate the top events of the fault tree. Finally, the importance analysis is used to find out the basic events that have the greatest impact on the top events. The proposed method is used to analyze the safety of the eVTOL′s battery thermal runaway and calculate the importance of each bottom event, so as to provide a basis for reducing the system failure probability and improving the system safety level.

In high-penetration wind power generation systems， accurately assessing the support potential for virtual inertia of energy storage and fully releasing its energy reserves to render the systems active in grid frequency regulation are crucial for ensuring the systems’ frequency safety and stability. To achieve this， a dynamic frequency response model for wind-storage power generation systems to calculate the system’s time of safe frequency rise and fall and the extreme values of frequency deviation. Next， considering the constraints on the safe operating condition of the state of charge （SOC） during energy storage， the virtual inertia of energy storage during the time of safe frequency rise and fall is quantitatively evaluated. Moreover， an active frequency support technology for energy storage based on fixed-frequency control is introduced， aiming to fully exploit the frequency support capability of energy storage during the frequency drop and recovery periods. Finally， a simulation model of high-penetration wind power generation systems is constructed for validation. Under the proposed control strategy， energy storage can provide effective inertia support and offer sustained frequency response， thereby significantly enhancing the systems’ frequency stability.

Objective To explore the surgical techniques and experiences in the treatment of Peyronie's disease using electric rotary grinding of tunica albuginea plaques followed by graft repair with tunica vaginalis or bovine pericardium under a microscope. Methods A retrospective cohort study was performed on 21 patients with severe penile curvature due to Peyronie's disease admitted in our department from January 2021 and May 2023. All of them underwent microscopic electric rotary grinding of tunica albuginea plaques followed by graft repair surgery. Short-term and mid-term outcomes were observed. Results For the 21 enrolled patients, 12 (57.1%) underwent repair using unilateral tunica vaginalis, 3 (14.3%) underwent repair using bilateral tunica vaginalis, and 6 (28.6%) underwent repair using bovine pericardium. The operation time was 170~385 (average 272±69) min, and the average postoperative follow-up duration was 3~24 (average 12.1±7.2) months. Seventeen patients (81.0%) had their penis fully extended, while 4 patients (19.0%) had slight dorsal curvature, which was less than 10°. All patients were satisfied with the shape of their penis during erection. The change in penile length was +(1.1±0.5) cm, and 9 patients (42.9%) reported early postoperative penile head numbness, which spontaneously resolved after an average duration of 3.2±1.9 months. All patients were able to successfully engage in sexual activity, with an average penile erection hardness score of 3.8. The overall satisfaction rate was 90.5% postoperatively. Conclusion Meticulous dissection of Buck's fascia under a microscope is advantageous in reliably preserving dorsal neurovascular structures. Application of an electric grinding drill for plaque ablation allows for more precise release of the tunica. Graft repair of tunica albuginea defects with testicular tunica vaginalis or bovine pericardium for Peyronie's disease yields overall favorable clinical outcomes and obtains high satisfaction. It is worthy of promotion in clinical practice.

Currently, there is a high latency problem in the transmission of video surveillance data in coal mines, and the main cause of video transmission delay is encoding delay. In order to solve the above problems, a intelligent monitoring video transmission method for coal mines based on media supplemental enhancement information(SEI) without video encoding is proposed. This method caches a copy of the compressed video frame obtained by demultiplexing the video stream, and decodes the compressed video frame to obtain the decoded video frame. The method stores the AI model analysis results in the decoded video frame through SEI, writes the custom SEI into the network extraction layer unit corresponding to the compressed video frame copy of the decoded video frame based on the timestamp correspondence. The method multiplexes the compressed video frame copy to achieve real-time transmission of coal mine intelligent monitoring videos. Experimental testing of this method is conducted on a 24 core CPU. The results show that for videos with a resolution of 1280×720, the overall CPU utilization rate for video processing using this method decreases from 24.7% to 36.3% when using traditional methods to 20.3% to 23.9%. The end-to-end delay decreases from 1946 ms to 345 ms. For videos with a resolution of 1920×1080, the overall CPU utilization rate for video processing using this method decreases from 29.2% to 41.8% using traditional methods to 18.5% to 26.3%. The end-to-end latency decreases from 6204 ms to 479 ms. This method reduces the transmission delay of coal mine intelligent monitoring videos by avoiding the video encoding process, saves CPU or GPU resources required for video encoding, and reduces the hardware cost of the intelligent video monitoring system.

[ Objective ] This study aims to explore the protective mechanism of exogenous silicon on water metabolism and photosynthesis of Cucurbita pepo L. seedlings under salt stress , and to provide theoretical reference for salt resistance of C . pepo L.. [ Methods ] Using “ Hanlu 7042 ” C . pepo L. variety as the test material and hydroponic experiment , four treatments were set : Control , silicon treatment ( 0.3 mmol / L Na 2 SiO 3 · 9H 2 O ), salt stress ( 150 mmol / L NaCl ), salt stress+silicon treatment ( 0.3 mmol / L Na 2 SiO 3 · 9H 2 O+150 mmol / L NaCl ) . After 10 days of treatment , root morphology and activity , leaf water con- tent and water potential , photosynthetic parameters , chlorophyll content , chlorophyll fluorescence param- eters , and expression of aquaporin genes were determined. [ Results ] Salt stress inhibited the growth of C . pepo L. seedling roots , and decreased root activity , leaf water content , and leaf water potential and tran- spiration. Salt stress also affected the photosynthetic system , net photosynthetic rate , stomatal conduct- ance , chlorophyll content , and PSⅡ photochemical efficiency. Exogenous silicon improved the root mor- phology and activity of C . pepo L. seedlings under salt stress , also improved plant water status , and leaf water content , leaf water potential , and transpiration by promoting the expression of genes PIP1 ; 2 , PIP1 ; 3 , PIP1 ; 5 , PIP1 ; 7 , PIP2 ; 1 , PIP2 ; 4 , PIP2 ; 6 , and PIP2 ; 8 , PIP2 ; 9 and PIP2 ; 12 . The exogenous silicon also increased the stomatal conductance , chlorophyll content , net photosynthetic rate , PSⅡ maximum photochemical efficiency , PSⅡ actual photochemical efficiency , and photochemical quenching coefficient , decreased intercellular carbon dioxide concentration and non-photochemical quench- ing coefficient , enhanced the photosynthesis of seedlings under salt stress. [ Conclusion ] 0.3 mmol / L sili- con could improve the water metabolism and photosynthesis of C . pepo L. seedlings under salt stress , and thus enhance the ability of C . pepo L. seedlings to resist salt stress.

Virtual power plants （VPPs） represent a tangible implementation in the construction of modern power systems. Addressing the current challenges of limited applicable technical standards and a lag in the development of a standardized system for VPPs， this paper， based on the collection and organization of relevant standards， conducts a comprehensive analysis of the standardization status across various facets of VPPs， including basic general standards， planning and construction， operation and maintenance， supporting technologies， and energy efficiency assessments. Adopting both top-down and bottom-up approaches of system engineering and guided by the principles of directive， coordinating， systematic， and open VPP standard system construction， a system architecture has been designed. The architecture encompasses 15 subcategories and 52 standard series. Furthermore， based on a future demand analysis， key layout recommendations have been proposed to provide reference for the establishment and revision of VPP standards.

Based on the MODIS (moderate-resolution imaging spectroradiometer) AOD (aerosol optical depth) and MEIC (multi-resolution emission inventory for China) in Northeast China from 2003 to 2022, the spatial distribution and interannual trend of AOD in Northeast China are analyzed. Effects of meteorological factors and anthropogenic emissions on AOD changes in Northeast China are discussed. Results show that the AOD maximum in central Liaoning is 0.6, followed by an average AOD of 0.4 in western Jilin and 0.3 in Heilongjiang. The average AOD in Northeast China is lower than that in north China, Yangtze River Delta and other frequent pollution areas. High AOD occurs in spring and summer in Northeast China, and it decreases spatially in autumn while increases in winter. The summer AOD in Liaoning is significantly higher than that in other regions, when the average value in central Liaoning and the Bohai Rim increases to 0.6. The highest values of AOD in different seasons occur in Liaoning, followed by Jilin and Heilongjiang. The increase of AOD in summer is mainly related to environmental humidity, and adverse meteorological conditions and local emissions have certain effects on near-surface atmospheric extinction in winter. The annual occurrence frequency of AOD in the range of [0.1, 0.2) and [0.2, 0.3) in Liaoning is up to 50%, the annual occurrence frequency of AOD in the range of [0.1, 0.2) in Jilin and Heilongjiang is up to 25%-30%, and the annual occurrence frequency of extreme clean condition in Heilongjiang is up to 15%. Affected by dust events in spring, the occurrence frequency of AOD [0.2, 0.3) and AOD [0.3, 0.4) in Northeast China is 25%. The regional average value of AOD in Northeast China is higher in 2003 and 2014, which is mainly influenced by boundary layer meteorological elements and anthropogenic emission of SO2, PM2.5, organic carbon (OC) and NO2. In Northeast China, AOD is negatively correlated with boundary layer height and average wind speed, and positively correlated with anthropogenic emissions. The correlation coefficient between AOD and anthropogenic emissions of SO2, PM2.5 and OC is the highest in Liaoning. From 2003 to 2022, AOD in Liaoning shows a weak negative growth trend (about-0.1 per decade), while the AOD in Jilin and Heilongjiang shows little change trend. From the perspective of seasonal interannual trend, there is a transition from a negative increasing trend in spring to a positive increasing trend in summer before 2012. After 2013, the summer AOD in Northeast China shows a negative growth trend (-0.3 per decade), which confirms that the contribution of summer aerosol to atmospheric extinction in Northeast China is decreasing in the past 10 years.

With the continuous development of communication technology and the accelerated arrival of enterprise digitization, the telecom business support system is also evolving and changing. In order to realize the goal of high-quality, high-efficiency and sustainable evolution, telecom operators need to establish an effective and adaptive to the market demand of business support system hierarchical evolution target system. Based on the analysis of the basic characteristics of the current telecom business support system and the demand of operation services, a framework of L-PS-M (level-process-system-measurement) hierarchical evolution target system for telecom operation service support was proposed. The framework firstly constructed a three-dimensional cube mapping structure formed by the three dimensional factors of end-to-end business process, system support capability, and hierarchical goal. Secondly, a subdivided implementation path of the operation service support system was given. Thirdly, telecom carriers could carry out the planning and optimization of the system support capability according to the actual demand in a targeted way through the implementation path, so as to improve the efficiency of the operation and system production, and further clarified the evolution of the business support system, which was applicable to telecom operations. It further clarified the evolution direction of the business support system.

Carbendazim and acetamidine are pesticides that widely used to control pests and diseases in oilseed rape. In this paper, a rapid, accurate and reliable method was proposed for the detection of carbendazim and acetamidine with SERS microfluidic chip technology. Ag-ps(Polystyrene microspheres) microsphere SERS substrate was prepared by spin coating and magnetron sputtering deposition of Ag. The enhancement factor of prepared SERS substrate was 2.4 × 1010. The SERS detection working curves were well fitted and the linear parameters R2 were 0.987 and 0.994, respectively. The limit of detection was 0.01 mg/mL. The use of SERS microfluidic chip to detect carbendazim and acetamidine is expected to provide a way for the detection of pesticide residues in crops, which has broad application prospects in the field of food safety.

Objective To investigate the nutritional status of patients undergoing concurrent chemoradiotherapy for malignant tumor and its influencing factors. Methods A self-designed questionnaire was used to collect related clinical data of the patients who underwent concurrent chemoradiotherapy for malignant tumor in Beijing Cancer Hospital from March to May, 2019. Patient-generated Subjective Global Assessment (PG-SGA) was used to investigate the nutritional status of these patients and related influencing factors. Results A total of 150 usable questionnaires were collected. The median PG-SGA score was 6.0 (3.0,11.0) for all 150 patients. Among these 150 patients, 56 (37.3%) had severe malnutrition and 49 (32.7%) had moderate malnutrition. The univariate analysis showed that old age, esophageal cancer or head and neck cancer, stage Ⅳ tumor, more than 15 sessions of radiotherapy, more than 4 sessions of chemotherapy, and paclitaxel+platinum regimen or platinum monotherapy were influencing factors for malnutrition in these patients (Z=-3.839--2.087,P

Abstract Using data from the World Values Survey (1990–2012), this article attempts to describe and analyze the changing trends in public values during social transformations in China. It is found that public attitudes toward authority tend to be increasingly favorable over time, values in the private sphere tend to be more open, while postmaterialist values show a trend of first rising and then falling. The most salient feature of the cohort effect is that the generations born after the reform and opening-up in 1978 identify more closely with the value of respect for authority, while their recognition of postmaterialist values tends to decline. The change in values is related to China's modernization process, global cultural diffusion, and important historical events and is also deeply influenced by the two-way interaction between tradition and modernity.

BackgroundU3Si2 is regarded as one of the most promising accident-tolerant nuclear fuels for light water reactors and is expected to replace the UO2 nuclear fuel in the future. Currently, spark plasma sintering (SPS) is an advanced technique for preparing U3Si2 pellets; however, the influence of SPS parameters on the performance of the pellets is unclear.PurposeThis study aims to investigate the effects of different sintering parameters (temperature and pressure) on the mechanical and thermal properties of the U3Si2 pellets prepared using SPS technology.MethodsThe thermal diffusivity of U3Si2 pellets was measured using a laser flash apparatus, and the thermal conductivity of the pellets was calculated. The mechanical properties of the pellets, including hardness, Young's modulus, and fracture toughness, were measured using nanoindenter. Thereafter, the influence of different sintering temperatures in the range of 1 000~1 300 ℃ and pressures in the range of 30~90 MPa on the mechanical and thermal properties of U3Si2 pellets were carefully examined.ResultsThe measurement results show that the thermal conductivity of the as-synthesized pellets increases linearly with temperature in the range 27~700 ℃. Moreover, increasing the sintering temperature and pressure improves the thermal conductivity of the U3Si2 pellets. The hardness and Young's modulus of the pellets increase with an increase in sintering temperature. They also exhibit a trend of first increasing and then stabilizing with increasing pressure, and tend to fully stabilize at 60 MPa. Moreover, the fracture toughness of the pellets decreases with the increase of sintering temperature and increases with increasing pressure.ConclusionsBased on the above results, optimized SPS parameters for the U3Si2 pellets are proposed, and this study provides a reference for the preparation of high-performance U3Si2 pellets.

Abstract Background Although Traditional Chinese Medicine (TCM) has been used for treating asthma for centuries, the understanding of its mechanism of action is still limited. Thus, the purpose of this study was to explore the possible therapeutic effects, and underlying mechanism of baicalein in the treatment of asthma. Methods Freely availabled atabases (e.g. OMIM, TTD, Genecards, BATMAN-TCM, STITCH 5.0, SEA, SwissTargetPrediction) and software (e.g. Ligplot 2.2.5 and PyMoL) were used for disease drug target prediction and molecular docking by network pharmacology. The efficacy and mechanism of action of baicalein in the treatment of asthma were validated using an ovalbumin (OVA)-induced asthma mouse model and molecular biology techniques. Results A total of 1655 asthma-related genes and 161 baicalein-related targets were identified from public databases. Utilizing common databases and software for network pharmacology and molecular docking analysis, seven potential target proteins for the therapeutic effects of baicalein on asthma were selected, including v-akt murine thymoma viral oncogene homolog 1 (AKT1), vascular endothelial growth factor A (VEGFA), epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC), mitogen-activated protein kinase 3 (MAPK3), matrix metallopeptidase 9 (MMP9), and MAPK1. In vivo, baicalein treatment via intraperitoneal injection at a dose of 50 mg/kg significantly reduced airway inflammation, collagen deposition, smooth muscle thickness, lung interleukin (IL)-4 and IL-13 levels, peripheral blood immunoglobulin (Ig)E levels, as well as the count and ratio of eosinophils in bronchoalveolar lavage fluid (BALF) in an OVA-induced asthma mouse model. Further validation by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blotting analysis revealed that the VEGF and EGFR signaling pathways involving VEGFA, MAPK1, MAPK3, and EGFR were inhibited by baicalein in the asthma mouse model. Conclusion Baicalein attenuates airway inflammation and airway remodeling through inhibition of VEGF and EGFR signaling pathways in an OVA-induced asthma mouse model. This will provide a new basis for the development of baicalein as a treatment for asthma and highlights the potential of network pharmacology and molecular docking in drug discovery and development.

The RGB image of coal foreign objects lacks target space and edge information, the color and texture between the object to be detected and the background are similar, the contrast is low, and there are overlapping and occlusion phenomena among the objects to be detected, resulting in insufficient feature extraction of coal foreign objects, and the existing foreign object detection methods are difficult to achieve ideal results. In order to solve the above problems, a coal foreign object detection method based on cross modal attention fusion is proposed. By introducing Depth images to construct a dual feature pyramid network (DFPN) for RGB images and Depth images, a shallow feature extraction strategy is adopted to extract low-level features of Depth images. Basic features such as deep edges and deep textures are used to assist deep features of RGB images, effectively obtaining complementary information between the two features. It thereby enriches the spatial and edge information of foreign object features and improves detection precision. A cross modal attention fusion module (CAFM) based on coordinate attention and improved spatial attention is constructed to synergistically optimize and fuse RGB features and Depth features. It enhances the network's attention to the visible parts of occluded foreign objects in the feature map, and improves the precision of occluded foreign object detection. Finally, regional convolutional neural network (R-CNN) is used to output the classification, regression, and segmentation results of coal foreign objects. The experimental results show that in terms of detection precision, the average segmentation precision AP of the proposed method is 3.9% higher than the better Mask transformer in the two-stage model. In terms of detection efficiency, the proposed method has a single frame detection time of 110.5 ms, which can meet the real-time requirements of foreign object detection. The coal foreign object detection method based on cross modal attention fusion can assist color, shape, and texture features with spatial features. It accurately recognizes the differences between coal foreign objects and between coal foreign objects and conveyor belts, effectively improves the detection precision of complex feature foreign objects. It reduces false alarms and missed detections, and achieves precise detection and pixel level segmentation of coal foreign objects under complex features.

Abstract Early metastasis is the primary factor in the very poor prognosis of pancreatic ductal adenocarcinoma (PDAC), with liver metastasis being the most common form of distant metastasis in PDAC. To investigate the mechanism of PDAC liver metastasis, we found that PDAC cells can promote the formation of pre-metastatic niches (PMNs) through exosomes to facilitate liver metastasis in the early stage. In our study, hepatic stellate cells (HSCs) were treated with PDAC-derived exosomes (PDAC-exo), and the activation of HSCs was detected. A novel transfer RNA-derived fragment, the tRF-GluCTC-0005 was obtained by small RNA sequencing from serum exosomes of PDAC patients. Bioinformatics analysis and RNA pull-down assays revealed the interaction between WDR1 and tRF-GluCTC-0005. A KPC transgenic mouse model and an AAV-mediated sh-WDR1 mouse model were used to detect the mechanism of liver metastasis in vivo. Finally, the dual luciferase reporter assay, protein mutation truncation assay, Co-IP assay, and flow cytometry assay were used to explore the molecular mechanism in HSCs activation and PMNs formation. We found that the tRF-GluCTC-0005 in exosomes binds to the 3’ untranslated region of the mRNA of the WDRl in HSCs and increases mRNA stability. The N-terminals of WDR1 bind to the YAP protein directly, inhibit YAP phosphorylation, and promote the expression of YAP transcription factors. The tRF-GluCTC-0005 in PDAC-exo significantly recruits myeloid-derived suppressor cells (MDSCs) in the liver, creating a PMNs immunosuppressive microenvironment and further advancing liver metastasis from PDAC. Our results suggest that the key of PDAC liver metastasis is the activation of HSCs through upregulation of WDR1 by tRF-GluCTC-0005 in exosomes, which mediates the infiltration of MDSCs to form PMNs.

BackgroundThe conversion of UF6, which is a primary nuclear product, to UF4 in fluoride molten salt phase is expected to be used in the preparation or reconstitution of nuclear fuel salt for molten salt reactors, thus simplifying the process of molten salt reactor fuel production. Determination of the concentration of the key intermediate UF3 plays an important role in obtaining the reaction parameters.PurposeThis study aims to establish a method for measuring UF3 concentration in solid fluoride molten salts.MethodsThe X-ray diffraction (XRD) was employed to test the homemade standards and obtain the internal standard curve of UF3. Firstly, the α-Al2O3 was taken as the internal standard to obtain the XRD peak height internal standard curve (R=0.986) and peak area internal standard curve of LiF-BeF2-UF3 molten salt. Then, these two internal standard curves were applied to measuring the known content of LiUF5 and UF3 solid mixed samples to compare their accuracies. Finally, measurements were conducted on rapidly cooled LiF-BeF2-UF3 solid molten salt samples and naturally cooled LiF-BeF2-UF3-LiUF5 solid molten salt samples to evaluate the stability and accuracy of the curve, and the relative error was obtained.ResultsIn the UF3 concentration range of 1.00~10.00 wt%, the correlation coefficient of the internal standard curve based on the peak area determined for of LiF-BeF2-UF3 molten salt is 0.995. Measuring results of solid mixed samples of LiUF5 and UF3 with known concentrations indicate that the peak area internal standard curve achieves better accuracy with a relative measurement error of no more than 8.7%. In addition, the results of the same content samples with different cooling methods confirm the good stability and accuracy of the proposed method with less than 5.4% relative standard deviation.ConclusionsThe established method can be used for the quantitative analysis of solid LiF-BeF2-UF3 and LiF-BeF2-UF3-LiUF5 molten salts with good measurement accuracy and repeatability.

Density is a crucial parameter for quantitatively describing the physical properties of liquids. It serves as an important indicator for scientific research, production process control, pipeline transportation, and other aspects. In oil pipeline transportation and raw material processing, the real-time online measurement of liquid density is of great significance. This paper analyzes the working principle of an online vibrating tube densitometer and derives the fitting equation for temperature, pressure, and density; it also conducts experiments with an online vibrating tube liquid densitometer and establishes a traceability chain for the experimental device. The experimental setup includes a desktop densitometer system, a multi-temperature field constant-temperature stirring system, a walk-in constant-temperature box, an automatic blowing system, and a frequency acquisition and calculation system. The uncertainty of the device’s evaluation is U = 0.08 kg/m3, k = 2. We built a set of pressure-density static test systems, statically testing the online vibrating tube’s liquid-density meter vibration frequency at different pressures; the whole set of systems can be used to assess the specific density, temperature, and pressure range of online vibrating tube liquid density meters in the experimental research to derive the standard temperature. Through the experimental research, we can accurately derive the fitting coefficients under the standard temperature, specific temperature, and pressure of online vibrating tube liquid densitometers, and calculate the fitting error of online vibrating tube liquid densitometers under different temperatures and pressures within the experimental range through fitting equations and coefficients, so as to realize the practical application of online vibrating tube liquid densitometers in engineering by utilizing straight-tube-type and curved-type online vibrating tube densitometers. A preliminary study was conducted on the effects of different densities, temperatures, and pressures on the vibrating tube system’s vibration cycle. The fit coefficient and error were calculated, and the experimental results were compared to the theoretical analysis to confirm the device’s conformity. The study verified the device’s scientific and reasonable design, and demonstrated that it is feasible to use the device for follow-up research. Using this device in subsequent experiments can verify the effects of viscosity, inlet, installation, and other factors on the online vibrating tube liquid densitometer’s metrological performance. Further experimental research on the pressure–frequency–density test system and the establishment of a wide range of temperatures and pressures within the pressure standard density test system are needed to achieve a wide range of temperatures and pressures under the standard density test.

OTULIN deficiency is a complex disease characterized by a wide range of clinical manifestations, including skin rash, joint welling, lipodystrophy to pulmonary abscess, and sepsis shock. This disease is mechanistically linked to mutations in the OTULIN gene, resulting in an immune disorder that compromises the body’s ability to effectively combat pathogens and foreign stimuli. The OTULIN gene is responsible for encoding a deubiquitinating enzyme crucial for hydrolyzing Met1-poly Ub chains, and its dysfunction leads to dysregulated immune responses. Patients with OTULIN deficiency often exhibit an increase in monocytes, including neutrophils and macrophages, along with inflammatory clinical features. The onset of symptoms typically occurs at an early age. However, individuals with OTULIN haploinsufficiency are particularly susceptible to life-threatening staphylococcal infections. Currently, the most effective treatment for patients with OTULIN biallelic mutations involves the use of TNF-blocking agents, which target the dysregulated immune response. In conclusion, OTULIN deficiency presents a complex clinical picture with diverse manifestations, attributed to mutations in the OTULIN gene. Understanding the underlying mechanisms is crucial for developing targeted therapeutic interventions to address this challenging condition. Further research into the pathophysiology of OTULIN deficiency is essential for improving clinical management and outcomes for affected individuals.

Introduction: More than two billion tons of oil reserves have been discovered in the fractured-cavity type carbonate reservoirs in Tarim Basin, which is a key field for increasing reserves and production in the future. This type of oil reservoirs is characterized by extremely high heterogeneity, and waterflood huff-puff oil displacement is generally used for secondary development of the oil reservoirs. The conventional methods are dominated by qualitative evaluation, which are insufficient to predict the oil production increase by waterflood huff-puff in various karst zones.Methods: The new method developed in this study involves four aspects, i.e., establishing a standard well database, optimally selecting the key development indicators, equivalent classification of reservoir space type, and optimally selecting the classification and evaluation methods for oil production increase by waterflood huff-puff. From the perspective of reservoir space type, the result of waterflood huff-puff oil displacement of multi-cave type reservoir (large scale) is better than that of relatively isolated cave type reservoir, followed by the fractured-vuggy type reservoir.Results and discussion: The new method shows advantages in the following aspects: 1) The differences in reservoir geological genesis and spatial structure characteristics in various karst zones are involved; 2) The difference in internal filling features of the same type of reservoir is integrally determined based on the changes in production performance; 3) The actual development characteristics of waterflood huff-puff oil displacement wells in various karst zones are systematically analyzed, and the criteria for selecting standard wells is formulated; 4) The violin plot is introduced as the main study tool for predicting and discriminating oil production increase by waterflood huff-puff displacement. Therefore, the new method is more capable of predicting the oil production increase by waterflood huff-puff in various karst zones.

Sepsis is a common and deadly syndrome that despite all the progress in its control, the death rate caused by it is high. Sepsis is a serious problem that needs immediate attention and treatment. This infection, especially if it is caused by bacteria resistant to several drugs, causes high mortality. About two-thirds of sepsis cases occur in hospitalized patients. Several factors such as increasing the age of the population, increasing the duration of chronic diseases, high consumption of antibiotics and corticosteroids, use of mechanical devices and intravascular devices play a role in increasing its incidence. We herein demonstrate the biogenic procedure for the in situ immobilizing gold nanoparticles over lignin (Lig)-modified Fe3O4 magnetic nanoparticles mediated by Cydonia leaf extract (Fe3O4@Lig-Ag NPs) and its catalytic activity on the acetylation of alcohols using acetic anhydride and subsequent biological performances. The successful synthesis of Fe3O4@Lig-Ag NPs was assessed using an array of advanced techniques like field emission scanning electron microscopy, fourier transformed infrared spectroscopy, transmission electron microscopy EDX, elemental mapping, vibrating-sample magnetometer, and X-ray diffraction. Cecal ligation and puncture was used for inducing the sepsis model in rats. Several doses of Fe3O4@Lig-Ag NPs (45, 15, and 5 µg/kg) on oxidant–antioxidant, inflammatory mediators mRNA such as IL-1 and TNF-α, and its effects on the levels of expression were assessed in the kidney, liver, duodenum, lung, and stomach. When septic rats kidney, liver, duodenum, lung, and stomach were compared with those of the control group, it was found that Fe3O4@Lig-Ag NPs dose-dependent administration raised glutathione levels and superoxide dismutase activity and significantly reduced the levels of malondialdehyde. The Fe3O4@Lig-Ag NPs (45 µg/kg) indicated greater anti-oxidative effects than the 5 and 15 µg/kg doses for all the assessed parameters. In addition, the expression of TNF-α mRNA in the CLP + 45 µg/kg group was decreased in comparison with the control group. Fe3O4@Lig-Ag NPs reduced oxidative stress by enhancing the free radicals scavenging effects and supporting endogenous antioxidants. The Fe3O4@Lig-Ag NPs potent antioxidant property may be related to the cytokine cascade suppression during sepsis. The above findings offer that Fe3O4@Lig-Ag NPs administration may indicate a modern treatment for the inhibition of liver, kidney, lung, duodenum, and stomach tissues damage caused by septic conditions.

Magnesium alloy as the most potential light structural material, has the advantages of high specific strength, specific stiffness and easy recycling, which contributes to the realization of lightweight in the industrial field. Compared with the traditional manufacturing technologies, the new and advanced manufacturing technology of additive manufacturing represent for high manufacturing efficiency, excellent performance, and forming complex structures. The technology of additive manufacturing for magnesium alloy, which has broad application prospects in the industrial field, is urgently required to be studied. In this paper, the recent studies of the three major additive manufacturing technologies for magnesium alloy: selective laser melting, wire+arc additive manufacturing, and friction stir additive manufacturing were summarized and analyzed from the aspects of forming characteristic, defect control, and features of microstructure and property.Finally, the developments in shape and performance control of the additive manufacturing technology for magnesium alloy: simulation analysis, process control, and heat source regulation were discussed.

[Objective] The water use characteristics of plants and their responses to environmental changes in a tunnel construction area at the eastern margin of Qinghai-Xizang Plateau were studied in order to provide a reference for soil and water conservation in this ecologically fragile region influenced by both nature and human activity. [Methods] The δ2H and δ18O values of xylem water of typical plants and potential water sources in different months from 2020 to 2021 in a tunnel construction area with an altitude of 3 230 m were measured. The MixSIAR model was used to calculate the proportion of plants absorbing water from each potential water source. The proportional similarity index (PS index) between every two plants was calculated to compare the water competition relationship between different species. [Results] Shallow soil water (0—40 cm) was the main water source for Festuca rubra, Picea likiangensis var. balfouriana, and Quercus spinosa. Populus szechuanica mainly absorbed middle and deep (40—200 cm) soil water. The uptake proportions from shallow soil water by plants in August and October 2021 were significantly lower than during the same period in 2020. For P. likiangensis var. balfouriana, there were significant positive and negative correlations (p

[Objective] The structure and sustainability of livelihood factors and their coupling coordination under different grazing intensities were studied in order to provide a scientific basis for optimizing the livelihood strategies of farming households, increasing their economic income, and realizing rural revitalization. [Methods] Taking the typical district of loess hilly area as an example, based on the sustainable livelihood framework, constructing the evaluation index system from multiple livelihood elements, combining the survey data of farmers and mathematical modeling, a comprehensive study was conducted on the sustainability of livelihoods of farmers with different grazing intensities and their coupled and coordinated development. [Results] ① Grazing intensity enhanced the sustainability of farmers’ livelihood capital, but there were significant differences in the effects on the sustainability of livelihood environment, livelihood strategies, and livelihood outcomes. ② Livelihood sustainability was highest under moderate grazing intensity, and livelihood capital, livelihood environment, livelihood strategy, and livelihood outcome sustainability increased by 37.86%, 3.83%, 9.92% and 30.45%, respectively, compared with non-grazing farmers. ③ The coupling coordination development characteristics followed the order of moderately grazing farmers > lightly grazing farmers > heavily grazing farmers > non-grazing farmers. Farmers’ livelihood coupling degree was higher than the coordination degree, indicating that the livelihood system of grazing farmers in the loess hilly region had a strong inter-role intensity, and that good coupling and synergistic development within the system had not yet formed. Therefore, it will still be necessary to further strengthen the transformation and upgrading of farmers’ livelihoods to improve their livelihood sustainability in the future. [Conclusion] Moderate grazing can increase livelihood capital and optimize livelihood strategy for farming households in the loess hilly region, and increase the livelihood sustainability and economic income of farming households.

The influence of thermal inertia of the furnace refractory on the peak regulation characteristics of a 300 MW circulating fluidized bed boiler (CFB) was studied by using a numerical calculation method. Based on the actual operation conditions of the boiler, the calculation results reveal that the thermal inertia of refractory is affected by its thermal conductivity and the thickness. Specifically, the thermal inertia of refractory decreases with the increasing thermal conductivity and decreasing refractory thickness. As a consequence, the time that required for the refractory to reach heat equilibrium decreases from 5 812 s to 3 426 s if the thermal conductivity of refractory increases from 1 W/(m⋅K) to 15 W/(m⋅K), while it increases from 3 267 s to 7 771 s if the thickness of refractory material increases from 30 mm to 90 mm. Practically in the presence of the traditional refractory in the CFB dense phase zone, the time required to achieve heat equilibrium state becomes 82, 65 and 60 min when the load of this CFB boiler rises from 50% to 100% with a rate of 1%/min, 2%/min and 3%/min. For a refractory with higher thermal conductivity, the equilibrium response time will be reduced to 65, 46 and 40 min, correspondingly. According to the calculation results, a formula for the heat absorption rate of refractory material was obtained. In addition, the influencing coefficient of the thermal inertia of refractory on coal feeding was also defined and calculated.

Aiming at the small imaging, complex background and crowded distribution of remote sensing image targets, a remote sensing image target detection algorithm (HQ-S2ANet) based on perceptual extension and anchor frame optimal matching is proposed by using the rotating target detection method S2ANet as a baseline network. Firstly, a cooperative attention(SEA) module is built to capture the relationship among the feature pixels when extending the model perception area to realize the relationship modeling between the target and the global. Secondly, the feature pyramid (FPN) feature fusion process is improved to form a perceptual extension feature pyramid module (HQFPN), which guarantees the low-level detail position information in the down sampling process when extending the perception area to enhance the model information capturing capability. Finally, a high-quality anchor frame is used to detect the target by using the high quality anchor frame as the baseline network. The high-quality anchor frame matching method (MaxIoUAssigner_HQ) is used to control the anchor frame truth value assignment by using a constant factor to ensure the recall rate while preventing the generation of low-quality anchor frame matching. The experimental results show that, under the DOTA dataset, the average accuracy(mAP) of HQ-S2ANet is improved by 3.1%, the parameters number increased by only 2.61M and the average recall(recall) is improved by 1.6% compared with the S2ANet algorithm, and the present algorithm effectively enhances the detection capability of the remote sensing image target.

Carotid free⁃floating thrombus (CFFT) is significantly associated with ischemic stroke. Thrombosis occludes the artery or falls off, leading to massive cerebral infarction or multiple embolism. In severe cases, cerebral hernia or even death may occur. The diagnosis of CFFT is gradually based on CT angiography (CTA). Early identification can help in etiological treatment. This article reviews the progress of the diagnosis and treatment of CFFT, in order to improve chinical diagnosis and treatment.

Wind power generation has uncertainty due to the high fluctuation of wind speed. In traditional wind power prediction models, the uncertainty is measured by normal distribution with zero mean and constant variance. However, the variance may vary with time, which means the variance has heteroscedasticity. To improve the prediction accuracy, this paper proposes a new integrated probabilistic wind power prediction model for wind farm considering heteroscedasticity based on online least absolute shrinkage and selection operator and vector autoregression (LASSO VAR) and the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model. First, online LASSO VAR is used to forecast power output. Then, heteroscedasticity of residuals is validated by autoregressive conditional heteroskedasticity test. Considering heteroscedasticity, the news impact curve and dynamic significance line verify that positive and negative residuals affect future volatility asymmetrically. Thus, the EGARCH model is used to forecast the residuals to obtain the conditional variance of point prediction results. Finally, the probabilistic result of total power output is obtained by summing the power output of turbines in the wind farm considering the correlation of the active wind power of wind turbines. This method is applied to forecast the power output of a wind farm in East China and is proved effective in improving the prediction accuracy.

Abstract Background Blood–brain barrier (BBB) is a crucial but dynamic structure that functions as a gatekeeper for the central nervous system (CNS). Managing sufficient substances across the BBB is a major challenge, especially in the development of therapeutics for CNS disorders. Methods To achieve an efficient, fast and safe strategy for BBB opening, an acoustofluidic transwell (AFT) was developed for reversible disruption of the BBB. The proposed AFT was consisted of a transwell insert where the BBB model was established, and a surface acoustic wave (SAW) transducer realized using open-source electronics based on printed circuit board techniques. Results In the AFT device, the SAW produced acousto-mechanical stimulations to the BBB model resulting in decreased transendothelial electrical resistance in a dose dependent manner, indicating the disruption of the BBB. Moreover, SAW stimulation enhanced transendothelial permeability to sodium fluorescein and FITC-dextran with various molecular weight in the AFT device. Further study indicated BBB opening was mainly attributed to the apparent stretching of intercellular spaces. An in vivo study using a zebrafish model demonstrated SAW exposure promoted penetration of sodium fluorescein to the CNS. Conclusions In summary, AFT effectively disrupts the BBB under the SAW stimulation, which is promising as a new drug delivery methodology for neurodegenerative diseases. Graphical Abstract

Objective To improve the early management of penile amputation injury by analyzing and summarizing our microreplantation experience of 4 cases of complete penile amputation. Methods Clinical data of 4 patients with complete penile amputation admitted to our hospital from March 2018 to October 2022 were collected, and their related clinical features, microsurgical procedures, post-operative treatment and follow-up outcomes were retrospectively analyzed. Results Meticulous anatomical microreplantation was successfully performed on all the 4 patients. Two of them received successfully bilateral penile dorsal arteries anastomosis, and the other two got only one dorsal artery anastomosis. All patients completed anastomosis of deep dorsal penile vein, and 3 of them had superficial dorsal vein anastomosis. Anastomosis of 4~6 dorsal nerves on both sides of the back of the penis were completed in all the patients. The operation time ranged from 6.5 to 7.5 h, with an average of 6.9 h. The warm ischemia period was 1~4 h, averagely 1.9 h. During the follow-up, 3 cases obtained successful penis replantation, although 2 of them had partial necrosis of foreskin, which healed naturally after 2~3 months. These 3 patients had normal urinations after operation, and had an erectile hardness score of 3~4 in 3~6 months after operation, with satisfactory self-reported recoveries. Conclusion For the patients with short warm ischemia period after complete penile amputation, microreplantation should be carried out as soon as possible in order to obtain satisfactory appearance and functional recovery of the penis.

In vivo magnetic resonance vessel size imaging at 7 T high field was used to explore the changes in cerebral vascular plasticity after spinal cord hemisection injury in rats. Region of interest (ROI) analysis showed that four weeks after injury, mean vessel diameter (mVD), microvascular density (Density) and vessel size index (VSI) values were significantly increased in the contralateral side compared with the ipsilateral pyramid of the injury site, suggesting angiogenesis or vascular activation in the white matter region of the contralateral corticospinal tract (CST). Immunofluorescence results showed that the intensity of staining for platelet endothelial cell adhesion molecule 1 (CD31) and glial fibrillary acidic protein (GFAP) also increased significantly in the contralateral pyramid four weeks after injury. These results suggested that magnetic resonance vessel size imaging could provide valuable information on neovascularization in brain after spinal cord injury and may be a novel tool to diagnose brain vascular pathologies in spinal cord injury patients.

With the development of China’s economy, the application of industrial radiation flaw detection technology is becoming more and more widespread, and the radiation monitoring and protection of flaw detection work has become an important topic in the field of radiation safety and protection. This paper uses pyroelectric technology to track X-ray radiation levels in the environment. It also chooses the scale curve method for calibrating the pyroelectric dosimeter and figures out the scale factor at the same time. The neutron and photon dimensions are used to evaluate the personal dose equivalent. The applicable range of pyroelectric dosimeters is calculated and the method is applied for radiation dose monitoring in industrial X-ray flaw detection rooms. Concrete wall shielding is used to determine the design parameters of the flaw detection room and the location of the distribution points to improve the shielding capacity of the flaw detection room and control the radiation intensity. The monitoring value of the operation position of the flaw detection room of Leshan Leboiler Enterprises in 2018 was 258.2, which was 73 higher than that of 2019. The results of the on-site monitoring of the absorbed dose rate of the ambient air in the flaw detection room showed that the average absorbed rate ranged from 0.015 to 0.546 μSv/h, which was lower than the standard of 2.5 μSv/h, and the shielding capacity of the flaw detection room was better, and the intensity of the radiation could be effectively controlled.

With the rapid development of the economy, the influence of digital marketing on consumer buying behavior is becoming more and more important. This paper first introduces the consumer purchase behavior regression model (SICAS) for digital marketing. Secondly, a locally weighted linear regression model based on SGD is constructed using nonparametric linear regression, local weighting, and stochastic gradient descent algorithms. This model is used to regression analyze the factors affecting consumer purchase behavior and identify the important factors that affect consumer purchase decisions. Finally, the insights of a digital marketing approach to enhance consumer buying behavior are given. People who buy goods offline account for 30.7%, while the remaining 69.3% choose online shopping. With the development of the digital market economy, online purchases will become mainstream. The reliability coefficient is in the range of 0.851-0.949, the KMO is 0.924, the Bartlett value is 759.766, and the significance is P < 0.05. The variables’ high reliability and correlation make them suitable for factor analysis. The coefficients between the factors and consumer purchase decisions were 0.774, 0.805, 0.832, 0.332, and 0.894 (P < 0.01). The model R2 was 0.868 and F = 225.968 (p

Driven by the current teaching management situation, teaching administrators at all levels generally hope to build a more complete teaching data operation center and data analysis system by using advanced information technology to provide teaching management personnel with a more comprehensive historical data analysis function. In the graph and improvement of the educating administration facts evaluation machine in this paper, the information warehouse and facts mining science used in the gadget are deeply studied. First of all, the troubles in the current instructing administration machine are analyzed in a centered manner, the technical framework of the entire teaching management data analysis system is designed and planned, and the various components of the framework are described and described in detail according to actual needs. Then, after the comparative evaluation of the facts warehouse and records mining strategies extensively used in more than a few fields in the present fields, the more than a few classical algorithms that can be utilized to the educating administration information evaluation device is improved, and the algorithms and algorithms are used to analyze the course grades and employment of the graduated alumni respectively, and the decision tree model is established, and finally the algorithm efficiency comparison chart is concluded that the improved C4.5 algorithm is better than the other three algorithms in terms of accuracy and time efficiency, and shows good classification performance.

Tobacco companies a fast-moving consumer goods wholesale enterprises in the storage, procurement, logistics, and distribution of all aspects of the close relationship with warehouse management. This paper takes RFID technology as the theoretical basis and explains the introduction. It finds that FRID is composed of a reader, electronic tag, antenna, and local server as its main components. Then, it proposes to apply RFID technology to manufacturing enterprises and describes the application mode of the relevant manufacturing enterprise system based on RFID. At the same time, based on RFID algorithms and technology, the system of the tobacco enterprise was tested and analyzed, completing the function test and performance test. In the performance test, RFID and PLC technology and industrial Ethernet automatic control system to do the data comparison found that RFID in the system with the increase of the user command response time is still very flexible, to do in more than 18000/s. Subsequently, with the support of RFID, the application in tobacco production was experimentally analyzed to verify the practicality of RFID manufacturing technology in the tobacco production process.

With the development of the times, traditional innovation and entrepreneurship education exist in the backwardness of education concept and learning concept. This paper proposes a model for entrepreneurship innovation that incorporates multi-source data fusion technology. From both online and offline sources, we obtain multi-source data about the education and teaching methods of the entrepreneurship innovation education concept in higher vocational colleges and universities. In the process of multi-source data fusion, data is preprocessed to improve its quality and efficiency during data fusion. Using the least squares method to complete the multi-source data fusion operation, combined with the concept of entrepreneurship innovation education, co-designed a data fusion-driven innovative entrepreneurship education teaching model that integrates interactive and targeted teaching methods. The model underwent validation and analysis. The data show that after some time of adopting the targeted teaching method to teach students innovative and entrepreneurial concepts, the difference between the mean value of the level of creative and entrepreneurial concepts of the students in the experimental group mean value (43.79) and the control group mean value (43.79) is 4.55. The sig value is 0.019

This study investigates the role of non-electrical protective devices in forecasting hazards for large 300Mvar class phase shifter units, which face overvoltage and overcurrent stresses under severe faults, distorting their internal magnetic fields. Utilizing migration learning, the research extracts target and auxiliary data to train autoencoders with sparse constraints. A deep learning-based DSAE-BP online recognition network is constructed using a backpropagation neural network. This network predicts potential safety hazards in large-scale phase-regulating units by analyzing data signals from connected sensors. Experimental results show delay time errors of less than 20ms and ripple rates between 1.40%-1.65% across varied current and voltage conditions, demonstrating the device’s accuracy and stability in fault prediction.

In innovative sports, integrating new-generation technologies is revolutionizing how we approach and analyze athletic performance. Our research focuses on developing a sophisticated middle and long-distance running system that harnesses the power of modern communication tech, including LoRa connectivity and 5G edge computing. By applying the IMF method, we effectively minimize data noise, enhancing the fidelity of sports signal analysis. Our system’s prowess is evident in its low latency (2.97 ms at 100 nodes), high accuracy (rating of 6.8), and impeccable anti-collision capabilities during competitive events. In practical tests over 1000 meters, it dramatically reduced timing errors to a mere fraction of manual methods, demonstrating its precision and potential to transform physical training and education. This innovation stands as a beacon for the future of sports, driving the integration of technology and athletics.

As the growth of automated detection technology, traditional manual detection has gradually been replaced. To improve the effectiveness of defect detection, a HPLC/dual mode portable sorting device with deep learning and image processing is raised for apparent defect detection. The product image is segmented using flood filled mean shift method, and defect detection is achieved using Yolo v3 algorithm. An LME2918 chip is the main component of the communication module in the portable device. Based on experimental data, image segmentation accuracy can range from 80% to 100%, and image matching accuracy can range from 85% to 95%. Under the power line carrier mode, the average success rate of apparent defect detection in portable sorting devices can reach 85%, and the change in success rate is not significant, indicating that the detection is relatively stable; Under wireless communication mode, the average success rate can reach 83%, and the change in success rate is relatively obvious, because wireless communication is easily affected by the external environment. The experimental data shows that the defect detection effect of the HPLC/dual mode portable sorting device based on deep learning and image processing meets the design requirements.

Exploring effective logistics machinery and equipment fault diagnosis and prediction technology to achieve efficient and stable operation of logistics machinery and equipment. In this paper, starting from the logistics machinery and equipment fault diagnosis technology, we optimize the hyperparameters of the recurrent gate unit neural network by using the improved second-order oscillatory particle swarm algorithm and then construct the IPSO-GRU logistics machinery and equipment fault prediction model. The IPSO-GRU model is used to test the prediction effect of the hydraulic lift table and logistics hoist by using the historical data of the hydraulic lift table as training data. The prediction accuracy of the IPSO-GRU model was improved by 6% compared with BP neural network. From the prediction results of the logistic hoist, only 6 out of 250 data samples failed to achieve accurate prediction. This shows that the IPSO-GRU model can effectively achieve the prediction of logistics machinery and equipment fault diagnosis and also provides a proven method for predictive maintenance of logistics equipment.

This paper selects the evaluation indexes that fit with the teaching mode and evaluation objectives of university innovation and entrepreneurship education in the new media environment. The limitations of the existing evaluation indexes are analyzed and combined with the characteristics of students’ physical and mental development and cognitive level; the indexes are screened and integrated, and a new evaluation system is constructed. Based on the improved particle swarm algorithm, the BP neural network is optimized to establish the evaluation model of students’ innovation ability and improve the defects of the particle swarm algorithm, covering the selection of the network topology, the number of neurons in each layer, the setting of the parameters of the improved particle swarm algorithm, and the dynamic adjustment of the weights and thresholds, so as to build the evaluation model. Analyzing the influencing factors of college innovation and entrepreneurship education in terms of college factors and individual factors, 45.7% of students want college innovation and entrepreneurship education courses to focus on entrepreneurial opportunities or environment analysis in the teaching process, 41.4% of students feel average in terms of teaching resources, and more than 50% of college students are conservative in the direction of employment or entrepreneurship in terms of personal factors. Comprehensive analysis shows that the influencing factors, such as inflexible teaching methods, unsound curriculum systems, imperfect practice platforms, and college students’ own ideological awareness, are very significant and worth noting.

The purpose of exploring the new theoretical system of college education development is to improve college students’ quality in all aspects. This paper constructs a new theoretical system of college education development based on the new theory of college education development--”three comprehensive education” theory. The fuzzy credibility measure and credibility distribution are used to explain the fuzzy processing theory, and the uncertainty index of the fuzzy processing model is optimized based on the cross-rhombus search algorithm to improve the search speed of the fuzzy processing model. Data experimental analysis is conducted for the fuzzy ICDS multi-optimization principle. Regarding search speed, the average search speed improvement of the algorithm in this paper relative to the CD algorithm saves about 1.37 to 4.69 points per block. It improves classification accuracy by 12.02% and 7.65% compared to the best fuzzy and GFCM algorithms, respectively. This shows that using the fuzzy ICDS multi-optimization principle can help analyze the effectiveness of the “three holistic education” theory in constructing the education development system and provide a reference for planning and implementing the new education development system.