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The dynamic risk assessment of typhoon disasters is an important decision-making basis for disaster response in the event of a major typhoon. Its goal is to dynamically predict the expected loss and disaster risk level caused by a typhoon so as to provide a basis for disaster risk early warning and emergency response. The traditional risk assessment model mainly fits the vulnerability curves of the hazard-affected bodies using historical disaster losses, and then establishes a disaster risk assessment model by coupling the risk of disaster factors, exposure, and vulnerability. However, the vulnerability curves generated by this method have problems of regional applicability, particularly in small-scale regions with small sample sizes available for fitting, leading to insufficient generalizability of the model. In addition, such models are complex and require phased hazard and vulnerability of the hazard-affected bodies research. Moreover, when employing the 3-element coupling process, it is difficult to consider other risk factors in the disaster system, such as hazard-formative environment and disaster prevention and mitigation capability. With the development of information technology, the availability of disaster risk factor data has been significantly improved, affording conditions for the fusion and application of disaster risk multi-source data. In recent years, many data-driven machine-learning models have been used to establish disaster risk assessment models. These models have the advantage that they can use large sample to improve the adaptability of the model, whereby the modeling process can consider more risk factors, the concepts of hazard and vulnerability are diluted, and the steps of model building are simplified. The integrated learning algorithm can not only improve the prediction accuracy, but more importantly, can be used to effectively evaluate the contribution value of the index to the final evaluation result. At present, China has established a six-level disaster reporting system at the national, provincial, municipal, county, township, and village levels, forming a long-term, high-precision database of disaster event cases since 2009, providing rich disaster loss information for the data fusion of risk elements. This study was based on 108 typhoon cases affecting five provinces in southeast China during 2009-2022. Nearly 4,000 county-level typhoon disaster loss samples were used to establish a dynamic typhoon risk assessment sample database that integrates 30 types of multi-source risk factor indicators. Six typhoon disaster risk assessment models were developed using the random forest algorithm to evaluate the affected population, emergency relocation population, crop-affected areas, collapsed and severely damaged houses, direct economic losses, and comprehensive risk level. Through the verification of actual disaster situations and model results, the overall accuracy of the disaster risk assessment results was found to be greater than 80%, indicating that the model has good generalizability and can be used for actual disaster assessment work. The experimental comparison shows that increasing the training sample size by 1-2 orders of magnitude can improve the accuracy of the model assessment by 3%-14%, indicating that the accumulation of disaster risk big data is of great significance in the study of disaster risk assessment. This study is expected to constitute a scientific reference for the quantitative analysis of the multiple impact factors of typhoon disaster damage and explore technical ideas for the application of disaster big data in risk management.

ObjectiveThis study aimed at conducting retrospective analysis of the clinical symptoms and genetic mutations in 20 children with Gitelman syndrome treated at the Affiliated Children′s Hospital of Nanjing Medical University from August 2015 to November 2022 and also explored the molecular mechanism of the pathogenic high-frequency mutation D486N in the Chinese population.MethodsWe collected the clinical manifestations, growth and development status, laboratory examination results, and SLC12A3 gene variations of the patients. We distinguished the wild-type and mutant SLC12A3 genes overexpressed in human embryonic kidney 293T cells (HEK293T). We used protein immunoblotting to detect the expression level of NCC, and used immunofluorescence techniques to examine the subcellular localization of NCC. In addition, we investigated the impact of the high-frequency SLC12A3 gene mutation D486N on NCC protein expression and localization.ResultsIn the 20 patients with Gitelman syndrome, all of them had hypokalemia. We indemnified twenty-six SLC12A3 gene mutations, 13 of which are missense mutation, 1 of which synonymous mutation, 1 nonsense mutation, 4 frameshift mutation, and 7 splicing site mutation. Among them, four mutations (p.T235K, c.1096-1G > A, p.A464A, and c.2660+1_2660+2insT) were novel mutations.ConclusionsWe found the preliminary evidence that the high-frequency mutation D486N in the Chinese population affected the expression of total and membrane-bound NCC protein and influenced the membrane localization of NCC protein. The findings of this study provides experimental evidence for genetic counseling, diagnosis, and treatment of Gitelman syndrome.

Objective: Solved the problems of poor motion stability and accuracy in the food sorting process of parallel robots. Methods: Based on the analysis of the three degree of freedom food sorting robot system, a method proposed which combined polynomial interpolation and improve multi-objective particle swarm optimization algorithm for Delta robot trajectory optimization. As a parallel robot, the optimization of the shortest operation time, lowest energy consumption, and minimal motion impact were taken as multiple objectives. The improved multi-objective particle swarm optimization algorithm was applied to optimize the polynomial interpolation method, and its performance was validated. Results: The planning trajectory of the proposed planning method in the experiment was smoother and more efficient compared to conventional methods. In the actual selection of Camellia oleifera fruits, the accuracy was ＞99.00%, and the average screening time was 0.620 s. Conclusion: The trajectory planning optimization method proposed in the experiment has improved the sorting efficiency, accuracy, and stability of the Camellia oleifera fruit sorting robot.

Objective·To investigate the early efficiency and safety of endovascular therapy (EVT) for patients with acute mild ischemic stroke with large vessel occlusion (LVO-MIS).Methods·A total of 31 patients with LVO-MIS who received emergency EVT-assisted standard medical treatment at the Green Channel of Stroke in Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine from June 2016 to October 2022 were retrospectively included as endovascular therapy group (EVT group), and 32 LVO-MIS patients who only received standard medical treatment in the same period were selected as the control group. General clinical data and parameters related to EVT of the two groups were collected. The primary outcome was early efficacy, that is, the NIHSS at seventh day after treatment (d7NIHSS) score decreased by ≥3 points or directly to 0 points from baseline NIHSS score. Secondary outcomes included successful revascularization of blood vessels and early neurological deterioration (END), and safety outcomes included symptomatic intracranial hemorrhage (sICH) and mortality. The primary and secondary outcomes of the two groups of patients were analyzed to evaluate the early efficiency of EVT, and the safety evaluation indicators of the two groups of patients were analyzed to evaluate the safety of EVT. Kruskal-Wallis H test was used to analyze the NIHSS scores of 24 patients in the EVT group who underwent EVT before and after treatment.Results·There was no statistically significant difference in the general clinical data between the two groups, as well as parameters related to EVT such as occlusion site, and onset-to-admission time. The baseline NIHSS score of the EVT group [5.0 (3.0, 5.0) points] was higher than that of the control group [3.5 (2.0, 5.0) points] (P=0.001), and their d7NIHSS score [1.0 (0, 3.0) points] was lower than that of the control group [2.0 (1.0, 5.8) points] (P=0.040). A total of 24 patients (38.1%) in the two groups achieved early efficacy, including 16 cases in the EVT group and 8 cases in the control group; and the early efficacy rate of the EVT group was higher than that of the control group (χ2=4.729, P=0.030). The END rate in the EVT group was lower than that in the control group (χ2=6.097, P=0.014), and there were 29 cases (93.5%) in the EVT group of patients whose blood vessels were successfully reopened. There was no statistically significant difference in sICH rate and mortality rate between the two groups. In the EVT group, there was a statistically significant difference (H=16.997, P=0.000) among the baseline NIHSS scores [5.0 (3.0, 5.0) points] of 24 patients, postoperative 24hNIHSS score [2.0 (0.3, 3.8) points] and d7NIHSS scores [1.0 (0, 2.8) points].Conclusion·EVT is safe and effective in treating LVO-MIS, and the early efficacy rate of EVT is superior to standard medicine treatment, with a lower rate of END and no increased risk of sICH.

Text complexity is an important construct in the study of English reading instruction in the context of globalization and in the field of applied linguistics, and the main purpose of its study is to match learners with reading texts that are appropriate to their language level in order to improve learning outcomes. Focusing on text complexity, in addition to focusing on lexical and syntactic dimensions, discourse complexity features are added to explore the application in the construction of text complexity hierarchy models based on feature optimization to be examined. In this study, with the text processing software developed by Kyle’s team, we used BNCbaby as the reference corpus to extract fine-grained indicators such as vocabulary, syntax and discourse complexity, and used principal component analysis to optimize the indicators by dimensionality reduction and determine the principal component features used to build the model. Different classification algorithms are used to construct separate models and compare their performance. Models constructed based on common traditional readability formulas and other single-dimensional features have significant advantages over models constructed from feature sets. In addition, the feature set and modeling method have good grading ability for other domestic textbook datasets and good performance in grading prediction for several different datasets, with strong generalization and generalization ability. This study integrates multivariate linguistic features with neural networks to construct a text complexity grading model, which provides a new path for text complexity research. The research results not only have certain theoretical significance for text complexity research, but also have high application value in the field of applied linguistics, which can provide references for the selection of students’ reading materials, the writing and adaptation of teaching materials, and the planning and test design of reading courses.

Due to the limitations of configuration scenarios， energy storage capacity configuration takes long time and the net profit value of energy storage capacity is small. Research on energy storage capacity configuration method for power system based on an improved particle swarm optimization （PSO） is proposed. First， the power system energy storage capacity is determined， and the storage capacity configuration constraints are analyzed in respect of the remaining power， charging and discharging efficiency， and reliability of the energy storage system； then， with the objective of maximum net revenue of storage capacity configuration， an economy model of the power system is constructed， and the improved particle swarm algorithm is introduced to solve the model and complete the configuration of the power system energy storage capacity. The experimental results show that the proposed method takes shorter configuration time while owning higher net energy storage capacity revenue， which verifies the application performance of the method.

The offshore RMB exchange rate is affected by the supply and demand relationship in the international market, investor sentiment, market liquidity, and other factors, while the onshore RMB exchange rate is mainly affected by government regulation and intervention. Therefore, the offshore RMB exchange rate may be a better reflection of the market’s macroeconomic expectations and risk appetite for China. Stock index futures are mainly affected by macroeconomic factors, so studying the correlation between the offshore RMB exchange rate and stock index futures is helpful for risk management, hedging, and price discovery. In this study, we selected the offshore RMB exchange rate, the volume of stock index futures, and the absolute rate of return as variables of investor sentiment. Through the Granger causality test, impulse response function, and variance decomposition, we studied the correlation between the rate of return of stock index futures and the rate of return of the offshore RMB exchange rate. Furthermore, we constructed a GARCH conditional volatility model. It was concluded that the trading volume and the absolute rate of return of stock index futures could explain the price fluctuations of stock index futures very well. A change in the offshore RMB exchange rate yield causes a change in the yield of stock index futures. Policymakers need to pay close attention to changes in the offshore RMB exchange rate in order to better grasp market trends and manage risks accordingly.

In order to study the development law of water conducting fracture zone in coal seam mining in A’ai Mining Area, Xinjiang, 1013 working face of a coal mine is selected as the research object. The development height of water conducting fracture zone in coal seam mining is analyzed by the combination of numerical simulation, underground segmented water pressure detection and theoretical calculation. The results show that the stress concentration phenomenon appears around the working face after coal seam mining, and the stress is mainly distributed on the coal pillar 0-20 m away from the coal wall. A pressure relief zone is formed in the roof rock mass above the goaf, and the maximum pressure relief zone is located at the center line of the goaf. With the increase of mining distance, the stress gradually increases, and the development height of water conducting fracture zone gradually increases. The maximum development height of water conducting fracture zone obtained by numerical calculation is 53.50 m, and the fracture mining ratio is 16.72. The development height of water conducting fracture zone in 1013 working face is detected by underground segmented water pressure method. The maximum height of water conducting fracture zone is 50.08 m and the fracture mining ratio is 15.65 times. According to the empirical formula, the development height of water conducting fracture zone is 42.30 m and 45.78 m respectively, and the fracture mining ratio is 13.22 times and 14.31 times respectively. The development height of water conducting fracture zone obtained by the three methods is close, which proves that the results are reliable.

Individual identification is one of the research hotspots in the practice of forensic science， and the judgment is usually built on the comparison of the unique biological characteristics of the individual， such as fingerprints， iris and DNA. With the dramatic increase in the number of cases related to video image investigations， there is an increasing need for the technology to identify individuals based on the macroscopic comparison of facial appearance biometrics. At present， with the introduction of computer three-dimensional （3D） modeling and 3D superimposition comparison technology， considerable progress has been made in individual identification methods based on macroscopic comparison of facial appearance biometrics. This paper reviews individual facial appearance biometric methods based on macroscopical comparison, comprehensively analyzes the advantages and limitations of different methods, and puts forward recommendations and prospects for subsequent research.

In order to finely detect the distribution range of shallow coal mined-out areas, a low-frequency focused factor is introduced into the phase shift method, and a low-frequency focused phase shift method is proposed, which has the advantage of extracting low-frequency dispersion energy on a short receivor array.The synthetic test results show that the low-frequency focused phase shift method significantly improves the focus of the dispersion energy at the low frequency, extends the range of frequency bands that can be picked up, and increases the detection depth.Meanwhile, the method shortens the spread length required to calculate the dispersion energy, ensuring that the MASW method has a high lateral resolution.The real data in the shallow coal mined-out area shows that using the low-frequency focused phase shift method in the dispersion energy extraction, the MASW method obtains high-precision horizontal slices of the shear wave velocity and identifies the extent of the mined-out area, the location of the security pillar and its geometry.It confirms the effectiveness of the low-frequency focused phase shift method to improve the lateral resolution of MASW and the feasibility to detect the shallow coal mined-out area finely.

Aiming at the problem of insufficient adaptability to the new elements of the new power system in the current distribution network investment method, this paper innovatively proposes a distribution network investment method based on the new power system. By constructing a source-grid-load-storage-side investment calculation model, the investment in the new power system can be accurately calculated. First, the distributed power investment is calculated from the two aspects of new construction and renovation. Secondly, construct the grid investment demand and grid investment capacity measurement model, and obtain the grid side investment model by weighted summation. Then, a model for calculating the scale of investment that can be saved due to demand-side response is constructed, and the cost of demand response is subtracted to obtain a model for calculating the scale of investment that can be saved on the load side. Finally, the energy storage side investment calculation model is constructed from the power supply side, grid side, user-side energy storage investment, and energy storage investment benefit. The research results are applied to the empirical area, and scientific guidance is provided to realize the precise investment in the area.

The effects of aging treatment on microstructure and properties of Al-Zr-Sc(-Er) alloys were investigated by TEM, STEM, hardness tests and electric conductivity tests systematically. Results show that the aging response speed, peak hardness and thermal stability of Al-Zr-Sc alloys are significantly improved by increasing Sc content, and increasing Zr content improves hardness and thermal stability, while decreasing the electric conductivity. Adding Er in Al-Zr-Sc alloys improves the aging response speed and promotes the precipitation of Zr and Sc. Hardness and electrical conductivity of alloy are improved, owing to the formation of Al3(Er, Sc, Zr) phases with core-double shell structure. For experimental alloys, one-stage aging at 300℃ provides the higher hardness but lower electric conductivity; one-stage aging at 400℃ can increase the aging response speed and electrical conductivity but decrease hardness; two-stage aging at 300℃/24 h+400℃ can lead to better match of conductivity, tensile strength and heat resistance.

Diabetic foot ulcers (DFU) are chronic, refractory wounds caused by diabetic neuropathy, vascular disease, and bacterial infection, and have become one of the most serious and persistent complications of diabetes mellitus because of their high incidence and difficulty in healing. Its malignancy results from a complex microenvironment that includes a series of unfriendly physiological states secondary to hyperglycemia, such as recurrent infections, excessive oxidative stress, persistent inflammation, and ischemia and hypoxia. However, current common clinical treatments, such as antibiotic therapy, insulin therapy, surgical debridement, and conventional wound dressings all have drawbacks, and suboptimal outcomes exacerbate the financial and physical burdens of diabetic patients. Therefore, development of new, effective and affordable treatments for DFU represents a top priority to improve the quality of life of diabetic patients. In recent years, nanozymes-based diabetic wound therapy systems have been attracting extensive interest by integrating the unique advantages of nanomaterials and natural enzymes. Compared with natural enzymes, nanozymes possess more stable catalytic activity, lower production cost and greater maneuverability. Remarkably, many nanozymes possess multienzyme activities that can cascade multiple enzyme-catalyzed reactions simultaneously throughout the recovery process of DFU. Additionally, their favorable photothermal-acoustic properties can be exploited for further enhancement of the therapeutic effects. In this review we first describe the characteristic pathological microenvironment of DFU, then discuss the therapeutic mechanisms and applications of nanozymes in DFU healing, and finally, highlight the challenges and perspectives of nanozyme development for DFU treatment.

The amorphous Ni-P/Al2O3 composite coatings with high P content were deposited using the bi-directional pulse electrodeposition. The micrographic morphology and chemical composition of the coatings were examined using the scanning electron microscope (SEM) and energy dispersive spectroscopy (EDS) analysis. Also, the phase structure of the coating was characterized using the X-ray diffraction (XRD). By analyzing the electrochemical test results of the coatings, the corrosion resistances of different types of deposits were evaluated. The results show that compared to the direct current (DC) plating, the P content in the Ni-P alloy coatings increases to 12.06%(mass fraction) by bi-directional pulse electrodeposition, which facilitates the formation of the amorphous Ni-P alloy coatings. The PC plating can produce a finer and denser Ni-P/Al2O3 composite coatings with more compact crystallization than that deposited by DC. The Ni-P alloy coatings deposited by the pulse electrodeposition has a better corrosion resistance, and adding composite particles of Al2O3 can further contribute to improving the corrosion resistance of the amorphous Ni-P alloy coatings.

In this mixed-method investigation, the researchers delved into the intricate dynamics underlying Chinese postgraduates' procrastination behavior, academic engagement, and self-confidence, unveiling a multifaceted interplay among these factors. Quantitative findings revealed an intermediate-high level of procrastination, particularly in relation to writing assignments, exam preparations, and weekly reading tasks, while attendance tasks and general school activities elicited lower procrastination levels. Further analysis elucidated a substantial negative correlation between procrastination behaviors and both academic engagement and self-confidence, indicating the pernicious influence of this pervasive phenomenon on students' academic experiences. Qualitative insights garnered through thematic analysis explicated the complex reasons behind procrastination, including being overwhelmed by intricate tasks, lack of genuine interest, competitive milieu, insecurities, distractions, cultural and familial pressures, and struggles with time management, prioritization, and perfectionism. Furthermore, inadequate mentorship and anxiety surrounding future career prospects emerged as significant contributors to procrastination. Evidently, this detrimental factor not only impeded postgraduates' academic immersion but also eroded their self-confidence, exacerbating the detrimental repercussions on their scholarly performance. Thus, the findings underscore the imperative for targeted interventions, encompassing mentorship, time management skills, and emotional support, to mitigate the deleterious effects of procrastination on Chinese postgraduates' academic engagement and self-confidence.

Nickel/diamond composite coatings were prepared on the basis of a new high speed electroplating bath. The influence of additives, plating parameters and diamond concentration on internal stress was investigated in order to find the solution to decrease the stress introduced by high current density; the micro morphology of the coatings were observed by SEM. The bath and depositing parameters were optimized that thick nickel/diamond composite coatings with low internal stress can be high speed electroplated with a high cathode current density of 30A/dm2. The results show that when plated with bath composition and parameters as follows: sodium dodecyl sulfate 0.5g/L, ammonium acetate 3g/L, sodium citrate 1.5g/L, diamond particles 30g/L; pH value 3-4, temperature 50℃, the composite coatings prepared in high speed have the lowest internal stress.

According to the mathematical model of the split-cylinder resonator method, it is impossible to establish a simple equation between the intermediate variables and the relative dielectric constant or the loss tangent. Instead, the measured relative dielectric constant and the loss tangent must be calculated numerically by iterative programming. When evaluating uncertainty according to the Guide to the Expression of Uncertainty in Measurement (GUM), it is impossible to obtain the sensitivity coefficient of each intermediate. Therefore, the reliability of uncertainty evaluation is greatly reduced. ISO/TS15530 states that the most effective method for estimating uncertainty is computer simulation, and more specifically, a Monte Carlo simulation. In this study, Three typical samples with different relative dielectric constant and loss tangent were measured, respectively. The probability density function of each intermediate variable was given, according to which the Monte Carlo simulations were performed by MATLAB programming. Moreover, some of the simulation results are compared with those of the previous literature, and the results show that the measurement uncertainty evaluated by the GUM method was slightly larger, indicating that it was a little bit conservative to assume that each intermediate variable is completely uncorrelated in the GUM method.

Under the conditions of giving the length of the rocker CD,swinging angle φ and advance-to return-time ratio K（extreme position angle θ）,in order to design crank-rocker mechanism with the maximum value of minimum transmission angle γmin,the supplementary angle β（be used to determine the position angle of the rotation center A of crank） is introduced,the function relation of minimum transmission angle γminand the supplementary angle β is established.Then the maximum value of minimum transmission angle γmincan be obtained by utilizing procedure of Matlab.At the same time,in view of the different K value,the mechanism of type selection is classified.Then,points out the typeⅠ and Ⅱmechanism can be used to design and typeⅠ mechanism is better in force-passing property when K ∈（1,3）.When K∈[3,+ ∞),if type Ⅱ mechanism is used to carry on the design,which will not be able to meet the requirement of the rocker swinging angle,if typeⅠ mechanism is used,which has low efficiency and is not conductive to transmission of the mechanism.