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The existing deep learning based foreign object detection models for conveyor belts are relatively large and difficult to deploy on edge devices. There are errors and omissions in detecting foreign objects of different sizes and small objects. In order to solve the above problems, a foreign object detection method for coal mine conveyor belts based on improved YOLOv8 is proposed. The depthwise separable convolution, squeeze-and-excitation (SE) networks are used to reconstruct the Bottleneck of the C2f module in the YOLOv8 backbone network as a DSBlock, which improves the detection performance while keeping the model lightweight. To enhance the capability to obtain information from objects of different sizes, an efficient channel attention (ECA) mechanism is introduced. The input layer of ECA is subjected to adaptive average pooling and adaptive maximum pooling operations to obtain a cross channel interactive MECA module, which enhances the global visual information of the module and further improves the precision of foreign object recognition. The method modifies the 3 detection heads of YOLOv8 to 4 lightweight small object detection heads to enhance sensitivity to small objects and effectively reduce the missed and false detection rates of small object foreign objects. The experimental results show that the improved YOLOv8 achieves a precision of 91.69%, mAP@50 reached 92.27%, an increase of 3.09% and 4.07% respectively compared to YOLOv8. The detection speed of improved YOLOv8 reaches 73.92 frames/s, which can fully meet the demand for real-time detection of foreign objects on conveyor belts in coal mines. The improved YOLOv8 outperforms mainstream object detection algorithms such as SSD, Faster-RCNN, YOLOv5, and YOLOv7-tiny in terms of precision, mAP@50, number of parameters, weight size, and number of floating point operations.

The intrinsic characteristics of the monolithic crystal detector are spatially inconsistent, which leads to the position dependence of the detector on the energy response of the γ-ray as well as the peak shift of the response spectrum of the detector, that is, the “position-energy” shift. The “position-energy” shift will cause the energy resolution of the detector to deteriorate and affect the energy linearity of the detector. Thus, a crucial challenge in enhancing the position consistency of detector energy response, improving energy resolution, and ensuring accurate isotope identification is the reduction or elimination of this “position-energy” offset. The “position-energy” response correction method is proposed in this paper to improve the position consistency of detector energy response. Firstly, Monte Carlo simulation is used to model monolithic LaBr3(Ce) crystal detectors of different sizes. Secondly, the effective detection region of the detector model is evenly divided into 25 blocks, then the spectral peak position of each incident region is extracted, and the spectral peak correction function matrix of 25 incident regions and the center position is established. Finally, 25 incident regional peaks are modified according to the modified function matrix, so that the spectral peaks in each region are consistent with the peaks in the center, and the modified spectral responses of the detector are obtained. The simulation results show that this method can effectively solve the “position-energy” migration problem of monolithic crystal detectors of different sizes and improve the peak consistency of each detector region. The energy resolution of the 662 keV characteristic peak of the Cs-137 point source can be improved from 4.5% to 3.9%, and the linear deviation of energy can be reduced from 2.1% to 1.2%.

Abstract Accurately determining the solubility of ethane in oil‐based mud is crucial for assessing the severity of gas kicks and implementing appropriate well control procedures. The key factors influencing the solubility of ethane gas in oil‐based drilling fluids include the content of base oil, pressure, temperature, and the viscosity of the drilling fluid. This study aims to test the solubility of high‐purity ethane in oil‐based mud under simulated downhole conditions in a 5000 m deep well. The test covers a temperature range of 40–140°C and a partial pressure range of 0.17–5.92 MPa. The effects of temperature, pressure, base oil content, and drilling fluid viscosity on the solubility of ethane are analyzed using various experimental data processing methods. The results show that the variation in ethane solubility with pressure and temperature is nearly linear within the specified ranges. Furthermore, the impact of pressure (1.24–2.78%/MPa) on solubility is approximately 50 times greater than that of temperature (−0.013 to −0.049%/°C) in oil‐based drilling mud. Additionally, ethane's solubility decreases as the drilling fluid's viscosity increases. The ethane solubility in 80% and 90% oil‐based muds is roughly 1.6 times and 2.0 times higher than in 70% oil‐based mud under the same testing conditions. Models for predicting ethane solubility have been developed using screening procedures and statistical regression. These models can be incorporated into gas–liquid flow models to analyze flow behavior during gas kicks.

Objective To analyze micronutrient levels in three types of female patients with diffuse hair loss. Methods The clinical data of 299 female patients with diffuse alopecia from January 2018 to June 2021 in the Department of Dermatology of Daping Hospital were analyzed retrospectively. Results The level of serum 25-hydroxyvitamin D in patients with diffuse alopecia was significantly lower than that in the control group, and had no impact to the type of diffuse alopecia. The concentration of serum zinc in patients with diffuse alopecia areata was also significantly lower than that in the control group. When ferritin ≤50 ng/mol was taken as the threshold of iron deficiency and 25-hydroxyvitamin D≤20 ng/mol, as the indicator level of serum 25-hydroxyvitamin D deficiency, the proportion of serum 25-hydroxyvitamin D and serum ferritin deficiency in all the three types of diffuse hair loss patients was higher than that in the control group(P＜0.05). So, lack of iron and serum 25-hydroxyvitamin D were belived to be related to the occurrence of diffuse alopecia of women. Conclusions Iron metabolism disorder and serum 25-hydroxyvitamin D level play a key role in female diffuse alopecia, while the effects of copper and zinc on hair growth and hair loss cycle are not well identified yet.

Whispering gallery mode (WGM) resonators, as an integral component of integrated photonics, have attracted considerable attention due to their high Q factor, small footprint, and small mode volume, making them widely applied as microlasers. In this work, Nd:GGG crystal was prepared into a Nd:GGG film with thickness of 1.8 μm through ion implantation-enhanced etching (IIEE) technique, and subsequently, the Nd:GGG film was partened by focused ion beam (FIB) technology to generate a microdisk with diameter of 20 μm. For high-power microcavity lasers, heat generation during laser operation was inevitable. We placed the microdisk on a silica holder and a silica wafer, respectively. The microdisk placed on the silica holder and silica wafer exhibited laser thresholds of 32 μW and 17 μW, respectively. Moreover, due to different heat dissipation conditions, the microdisk placed on the silica holder exhibited a mode shift of 0.13 nm/mW, while the microdisk placed on the silica wafer showed a more stable laser output state with a mode shift of 0.02626 nm/mW.

The L-band digital aeronautical communication system (LDACS) is one of the essential infrastructures for future aviation broadband communication. To address the problem of interference from adjacent high-power distance measuring equipment (DME) signals, a joint orthogonal projection interference suppression and single-snapshot sparse decomposition direction of arrival (DOA) estimation method is proposed. Firstly, the DME interference is suppressed by using the subspace projection, and then a pseudo-covariance matrix is constructed by using single-snapshot data. High-order power of the pseudo-covariance matrix is calculated, followed by singular value decomposition and sparse solution obtained using constraints to estimate the desired target. The proposed method in this paper reduces the impact of noise by utilizing high-order pseudo-covariance matrix, enabling accurate estimation of the DOA of OFDM signals with only a single snapshot. Simulation results show that the estimation accuracy by using ISS-HOP-L1-SVD algorithm is better than that via ISS-HOP-MUSIC algorithm. This method can effectively suppress DME interference and improve the performance of the OFDM receiver.

In the context of the “dual carbon” strategy， this paper addresses the optimization of wind-solar-energy storage capacity configuration in microgrids by proposing a dual-layer optimization model. With the overarching objective of maximizing net profit throughout the microgrid's planned lifecycle and considerations related to constraints on carbon emission quotas and transformer capacity on the source side， the model aims to reduce electricity purchasing of main grid and lower the overall carbon footprint of the system. On the load side， demand response is introduced， and users are guided to modify their electricity consumption patterns under time-of-use pricing， leading to an optimized load curve and improved economic efficiency for the microgrid. The dual-layer optimization model is solved using LINGO， a nonlinear programming tool. Through case studies， the planning outcomes considering different proportions of transferable and unloadable loads， as well as varying constraints on carbon emission quotas and transformer capacities. The results demonstrate the effectiveness of the proposed model.

Abstract An improved model predictive control (MPC) with Luenberger state observer is proposed in this article for LC‐coupling hybrid active power filter (LC‐HAPF). Traditionally, the implementation of MPC for LC‐HAPF requires additional sensors to measure coupling capacitor voltage, thereby increases the system cost and reduces reliability. The existence of one‐step sampling delay in practice will also affect the final compensation performance. To relax these problems, both continuous and discrete models are deduced first. Then, the Luenberger observer is utilized based on the discrete model to mitigate the steady‐state error without additional sensors. In addition, the sampling delay compensation is provided by improving the prediction horizon. Finally, the effectiveness of the improved MPC for LC‐HAPF is verified by experiment results, indicating that the proposed method has fast dynamic response and low steady‐state error.

NHX proteins are transmembrane antiporters belonging to the cation/proton antiporter gene family, with a conserved Na+ (K+)/H+ exchange (PF00999) protein domain. NHXs play a prominent role in plant growth, development, and defense. However, the role of NHX gene family in potato (Solanum tuberosum L.) is yet to be known. In this study, we conducted a genome-wide analysis of the potato NHX gene family. A total of 25 StNHX family members were identified to be unevenly distributed on 10 chromosomes. The proteins ranged in length from 252 to 1,153 amino acids, with molecular masses ranging from 27516.32 to 127860.87 kD, and isoelectric points (pI) ranging from 4.96 to 9.3. Analyses of gene structures and conserved motifs indicated that StNHX genes in the same phylogenetic cluster are conserved. Phylogenetic analysis divided the StNHX genes into three subfamilies (Classes I, II, and III). Synteny analysis indicated that StNHX gene family Class III of NHX and all Arabidopsis thaliana NHXs shared a close evolutionary relationship. Analysis of cis-acting elements in the upstream 1,500 bp promoter region of potato NHX genes showed that these genes could be regulated by light, stress, and hormones such as abscisic acid and gibberellic acid. Protein-protein interaction network analysis indicated that StNHX proteins may participate in the regulation of potato growth and stress response. Besides, To determine a potential role of these genes in tissue development and drought response, we analyzed the RNA-seq data of different DM potato tissues. The results showed that NHX genes exhibited distinct tissue-specific expression patterns. We further examined the expression patterns of StNHX in different tissues (leaves, roots, shoots, tubers, stolons, and flowers) during the flowering stage in ‘Jizhangshu NO.8.’ potato. The qRT-PCR results further confirmed the importance of StNHX genes in potato plant growth and development. We further analyzed the RNA-seq data (DM potato) under different abiotic stresses (salt, drought, and heat), and found that the expression of StNHX genes was induced under abiotic stress. qRT-PCR analysis of shoots and roots of ‘Jizhangshu NO.8.’ potato treated for 0, 6, 12, and 24 h with 15% PEG6000 confirmed that the 25 StNHX genes are involved in the response to drought stress in potato. The results of this study may be useful for selecting appropriate candidate genes for the breeding of new drought-tolerant potato varieties. Furthermore, this study lays a foundation for prospective analysis of StNHX gene functions.

The basic region/leucine zipper (bZIP) transcription factors play important roles in plant development and responses to abiotic and biotic stresses. OsbZIP53 regulates resistance to Magnaporthe oryzae in rice by analyzing APIP5-RNAi transgenic plants. To further investigate the biological functions of OsbZIP53, we generated osbzip53 mutants using CRISPR/Cas9 editing and also constructed OsbZIP53 over-expression transgenic plants. Comprehensive analysis of phenotypical, physiological, and transcriptional data showed that knocking-out OsbZIP53 not only improved disease resistance by inducing a hypersensitivity response in plants, but also regulated the immune response through the salicylic acid pathway. Specifically, disrupting OsbZIP53 increased H2O2 accumulation by promoting reactive oxygen species generation through up-regulation of several respiratory burst oxidase homologs (Osrboh genes) and weakened H2O2 degradation by directly targeting OsMYBS1. In addition, the growth of osbzip53 mutants was seriously impaired, while OsbZIP53 over-expression lines displayed a similar phenotype to the wild type, suggesting that OsbZIP53 has a balancing effect on rice immune response and growth.

The efficiency of the underground drainage system in coal mines directly affects the production safety and economic benefits of coal mines. The existing multi-level relay drainage system in mines does not fully consider the peak and valley features of electricity bills and the safety constraints of the drainage system required by the Coal Mine Water Prevention and Control Regulations. It is difficult to achieve integrated safe and economic operation of the entire system. In order to solve the above problems, based on the avoiding peaks and filling valley strategy and dynamic programming method, an optimization strategy for multi-level relay drainage system in mines under the time of use electricity price is proposed. By considering the multi-level series structure, water inflow, and drainage capacity of water pumps, a mathematical model of a multi-level relay drainage system in coal mines is established. Based on the strategy of avoiding peaks and filling valleys, with the lowest electricity cost as the objective function and constraints such as water level in water tanks, drainage capacity of water pumps, and coal mine safety requirements, a multi-level relay drainage system optimization problem based on time of use electricity price is constructed. The solution algorithm based on dynamic programming method is provided. Taking the 4-level drainage system of a certain mine as an example for simulation analysis, the results show that this strategy can effectively control the underground water level and ensure that the water level is at a reasonable height. When the electricity price is high, the number of drainage pumps opened is very small or zero, and the water tank is in a high water level state. When the electricity price is low, the number of drainage pumps opened is larger, and the water tank is in a low water level state. This strategy can improve economic benefits while ensuring the production efficiency and safety of coal mines.

In order to solve the problem that the selection of key process parameters of a flexible soldering robot depends on manual experience, the empirical model of its THT assembly process parameters is established with the response surface method and the reliability of the model is verified. On this basis, the multi-parameter relative sensitivity of the key process parameters is analyzed through the Monte-Carlo simulation, and their single-parameter sensitivity curve is drawn. Then, based on the sensitivity analysis, the stability region division method is designed, and the stability region of process parameters for soldering quality comprehensive score is obtained. The optimal region of process parameters of the soldering robot are acquired by compressing the stability region: soldering temperature from 350-368 ℃, soldering time from 1.31-1.48 s and solder feeding volume from 1.5-2.0 mm3. The average value of the soldering quality comprehensive score within the optimal region of process parameters is 90.2 points.

Research on the risk of runway excursion events is mostly based on accident statistics. Analysis is rarely conducted from flight data and flight operation characteristics. Therefore，based on the QAR（quick access recorder）data，the risk analysis for runway excursion is performed. The QAR data is divided into three categories：flight status，operation instructions and information，so as to analyze the status of the aircraft in the three stages of takeoff run，landing and landing run. Through the operating characteristics reflected by the QAR data，combined with the SOP（standard operating procedures），the operations that exceed the normal data and do not conform to the standard operations can be deduced，and the risk factors affecting the normal flight are obtained. Based on the 2-4 model of behavior safety，the risk assessment index system of runway excursion can be established. Based on the causative mechanism of an accident，focusing on the analysis of operational characteristics and human factors，the risk prevention and control measures for overshoot runway excursion are proposed. The results show that，a risk im pact indicator system can be established from three dimensions：operation，data，and environment. This can reduce the impact of indicator factors on runway excursion events. Countermeasures and suggestions are proposed from the perspectives of personnel，aircraft，environment，and management，which can effectively reduce the probability of runway excursion events.

Carbon-based materials strongly pertain to citizens’ daily life due to their versatile derivatives such as diamond, graphite, fullerenes, carbon nanotube, single-layer graphene, and amorphous carbon (a-C). Compared to other families, a-C exhibits reconfigurable electrical properties by triggering its sp2–sp3 transition and vice versa, which can be readily fabricated by conventional film deposition technologies. For above reasons, a-C has been adopted as a promising memristive material and has given birth to several physical and theoretical prototypes. To further help researchers comprehend the physics behind a-C-based memristors and push forward their development, here we first reviewed the classification of a-C-based materials associated with their respective electrical and thermal properties. Subsequently, several a-C -based memristors with different architectures were presented, followed by their respective memristive principles. We also elucidated the state-of-the-art modeling strategies of a-C memristors, and their practical applications on neuromorphic fields were also described. The possible scenarios to further mitigate the physical performances of a-C memristors were eventually discussed, and their future prospect to rival with other memristors was also envisioned.

Abstract In this paper, an open‐circuit fault‐tolerant topology of LC‐coupling hybrid active power filter (LC‐HAPF) and its control strategy are proposed at the switch level, which can greatly improve the reliability of the system. The proposed structure has a contactor between the midpoint of each bridge arm and the negative bus of the dc‐link capacitor. When a single‐phase fault occurs, the proposed LC‐HAPF can be reconstructed into a three‐phase four‐switch system to compensate for the harmonic and reactive power, while the power quality compensation effect is hardly affected. When a two‐phase fault occurs, the operation of the normal bridge arm is not affected, and the two faulty bridge arms can suppress harmonic current and compensate for a fixed reactive power through the passive filters. When the bridge arms all fail, the whole device acts as a passive filter to suppress the harmonic current of the load and to compensate for reactive power as well. Finally, the effectiveness of the proposed topology and its control strategy is verified by simulation and experiment results.

In order to reduce the cement consumption during the production of autoclaved aerated concrete (AAC) made from circulating fluidized bed ash (CFBA), this paper investigated the effects of lime replacements for cement on gas-forming volume, bulk density, water absorption and compressive strength of AAC. The results show that the volume of gas formed in AAC during the pre-curing stage decreased as the lime content increased from 3 wt% to 22 wt%. After autoclaving cured for 7 h, the bulk density and water absorption of AAC increased with increasing the lime content. The compressive strength of AAC gradually increased from 3.0 MPa to 3.6 MPa as the lime content increased to 16 wt%. More defined tobermorite crystals formed as the lime content increases to 19 wt%, contributing much to the strength enhancement of AAC, whereas the lime content beyond 16 wt% adversely affected the microstructure of AAC.

Freshly squeezed fruit and vegetable juice， freshly ground coffee， new tea and other freshly made beverages are very popular among consumers. However， due to the loose quality control of raw materials and non-standard processing operation， the risk of microbial contamination exists in the freshly made beverages. This paper summarizes the status of microbiological pollution in the present system beverage and the current situation of industry supervision， analyzes the causes of microbiological pollution in the process of the present system beverage， finds out the key control points and proposes the intervention measures， in order to promote the healthy development of the present system beverage industry.

This paper takes three colleges and universities in a province as an example, designs relevant questionnaires and distributes them, and analyzes the collected data by using statistical methods such as independent samples t-test and ANOVA one-way ANOVA. The paper analyzes the data collected using statistical methods such as independent sample T-tests and ANOVA to infer the overall situation of the current level of emotional identification with Marxist theory among Chinese college students. The data was examined in detail to determine the variations in the emotional recognition of Marxist theory among college students based on their gender, ethnicity, and professional classification. The results show that more than 50% of college students understand Marxism and strongly identify with it. The overall mean score of affective identification is 35.324, which is a good status for identification. In terms of different genders, the P-values of value identity, knowledge identity, social identity, and behavioral identity are less than 0.1, and there are significant differences. Emotional identity does not have significant differences in different ethnicities (P = 0.382 > 0.05) and different majors (P = 0.426 > 0.05).

To reduce the emission of fine particulate matter (PM) from gasoline engines, a gasoline particulate filter (GPF) filtration model that considers the fractal characteristics of both particulate matter and filters is designed and its filtration characteristics are analyzed based on several GPF filtration models. Based on the GPF filtration mechanism, a new mathematical model of fiber efficiency filtration is established after correcting the classical filtration formula based on correcting the particle size of particles and considering the relationship between the porosity of the fiber filter and the fractal dimension of the filter. Simulation of the filtration efficiency of the established mathematical filtration model is carried out to obtain visual filtration efficiency curves. The filtration efficiency and pressure drop of the model are analyzed, and the effects of parameters such as particle fractal dimension, filter fractal dimension, filter thickness, flow rate, and fiber diameter on filtration efficiency are also comprehensively analyzed. The results show that when the fractal dimension of particles is in the range of 1.8-2.8, the most penetrating particle size decreases with the increase of the fractal dimension of particles. When the particle size is small, the effect of fractal dimension on filtration efficiency is not obvious. When the particle size is larger than the most penetrating particle range, the larger the fractal dimension, the filtration efficiency increases obviously. Considering the relationship between the fractal dimension of the filter body and the porosity and the influence of each on the filtration efficiency, the optimal fractal dimension of the filter body should be between 1.82 and 1.925, and the thickness of the filter has some influence on the filtration efficiency. The slower the gas flow rate is, the better the trapping effect will be. However, considering the problem of automobile emission, a lower exhaust speed can be chosen. Increasing the fiber diameter can improve the trapping efficiency of the model, but will reduce the porosity of the trapping collective. Therefore, the fiber diameter should not be too large under the combined action.

This research delves into the innovative application of topological number theory to reform English language teaching methodologies in higher education. We introduce and assess a novel approach to English teaching in colleges and universities, inspired by the principles of topological number theory. Our methodology leverages a unique model for recognizing handwritten English based on visual topological cognition, applying the insights of topological cognition theory to enhance English language instruction. The empirical analysis reveals a low word error rate of just 9.42% for our model, outperforming traditional models like the CRNN, which exhibits a 15.12% error rate. In a 10-week instructional experiment, students taught using the topological approach demonstrated significant improvements across all dimensions of English learning compared to their peers in a control group. The findings underscore the substantial potential of topological number theory in elevating English language teaching in colleges, offering significant benefits in teaching effectiveness and student motivation.

The surge in information technology has catalyzed a pivotal shift towards innovative English teaching methodologies in higher education, garnering significant attention in educational research. This study introduces wavelet packet decomposition as a novel approach to both the innovation and evaluation of English teaching methods in colleges and universities, aiming to enhance teaching efficacy and scientific rigor. By employing wavelet packet decomposition for data analysis and utilizing a cloud-based evaluation model for teaching assessments, we investigate the impact of a new teaching mode at College M. Results reveal that students exposed to this innovative teaching strategy outperformed their counterparts in the control group on English cognitive tests, particularly in foundational areas such as grammar, where the experimental group achieved an impressive average success rate of 86.73%, compared to the 25%-50% range of the control group. These findings highlight the substantial benefits of the innovative teaching mode in elevating students’ English learning outcomes, particularly in grasping basic concepts. Furthermore, integrating a cloud evaluation model offers a comprehensive and scientific framework for assessing teaching effectiveness. This research validates the efficacy of the novel teaching model and introduces an innovative evaluation methodology for English education in tertiary institutions.

This study focuses on applying intelligent translation systems in assisting high-quality English writing in the Internet era. The study analyzes statistical machine translation techniques, especially N-gram language modeling and word alignment techniques, and their crucial role in translation quality improvement. In English writing, the intelligent translation system significantly improves the quality of students’ Writing through word block translation. By analyzing 320 students, the mean value of self-efficacy in writing skills of students in the high-quality writing group was 3.78, significantly higher than that of the low-quality group, which was 2.82. After the experiment, 0.57 students indicated that they would improve their English writing vocabulary with the aid of the Intelligent Translation System, which showed the potential of the Intelligent Translation System to enhance students’ interest in and autonomy in Writing. Average distribution analysis shows that word block usage positively correlates with writing performance, with an R Square value of 0.6726. The intelligent translation system improves students’ English writing and enhances their self-efficacy, which is of great significance to English teaching.

This paper analyzes the intelligent networked fleet formation mechanism under adaptive cruise control (CACC). By constructing a communication architecture system including network layer, coordination layer, control layer and physical layer, and based on environment sensing technology and 5G network, a layered control structure for autonomous driving vehicles is established. In the study, the inter-vehicle distance control strategy is proposed, and combined with the theory of metacellular automata, the study constructs an intelligent networked fleet model, which adopts the full speed difference model and adaptive cruise control vehicle following model. The simulation analysis is carried out through the actual data of a section of G6 Beijing-Tibet Expressway, and the simulation environment is a two-lane highway of 3000m, considering different CAV vehicle penetration rates (0% to 100%). The results show that with the increase of CAV penetration, the traffic flow and the congestion significantly improved. The intelligent Connected Vehicles fleet performs well in the obstacle avoidance task, effectively reducing unnecessary lane changes and shortening the congestion time compared to the conventional system, with the distance error controlled within 1m. This study shows that the intelligent connected vehicles-connected fleet has significant advantages in improving traffic flow’s operational efficiency and safety.

With the gradual increase in the demand for parametric human 3D models, the requirements for the accuracy of modeling and the quality of generation are getting higher and higher. In this paper, the human body structure model is constructed by 3D human posture estimation and spatio-temporal graph convolutional network, and after normalizing the data of the human body base, the 3D human body model based on the human body base is generated by combining the free deformation method, and the local light model is used to make the human body model more three-dimensional and real. In addition, the quality of 3D animation production is investigated by combining blind quality evaluation and validation analysis of the human body-based 3D model. The 3D human body modeling simulation error assessment has an error assessment root-means-square error that falls within 1.5%. In the validation analysis of model generation quality, the quality evaluation model proposed in this paper has a quality correlation coefficient and prediction accuracy of 0.9456 and 0.9454 on the dataset, respectively, and the performance of the ablation experiments and generalization experiments is stable. The mean value of the error between the animation production character generation effect and the actual testers is not more than 10mm.Combined with the research in this paper, it effectively improves the accuracy of human body modeling and provides an evaluation method for the quality of human 3D animation production and generation, which is of practical significance for its development.

To cultivate more application-oriented talents needed in the market, this paper puts forward a series of innovative development strategies for the integration of industry and education for the government, schools, and enterprises. The indicators used to determine whether the integration of industry and education is good or bad are relatively complicated because it is a long-term and complex teaching mode. In this paper, we use hierarchical analysis to construct a reasonable and clear evaluation index framework and use the convolutional neural network algorithm to calculate the weight value of each index, to comprehensively reflect the impact of the mechanism of industry-teaching integration on students, schools, and enterprises. According to the results of the evaluation system, the weights of the indicator “school running form” and the indicator “employment rate of graduates” reach 0.71 and 0.43 respectively, which fully indicates that the mechanism of integration of industry and education promotes the transformation of several courses in the school, and also helps students to solve the problem of employment. Employment Problems. In addition, the global weight value of the indicator “training cost of new employees” is only 0.01, which greatly reduces the recruitment and training cost of enterprises through the integration of industry and education. Therefore, the convolutional neural network adopted in this paper can effectively calculate the weight value and judge that the innovative development strategy of industry-teaching integration is of great help to all three parties.

In this paper, we first investigate the peroxidase enzyme during millet storage, deeply analyze the characteristics of different types of grain bins during millet storage, and then summarize the peroxidase properties. Secondly, to extract the feature vector of the molecule, a descriptor was introduced, and on machine learning, SVM was used to construct a model of catalytic site MCD-MFEs and multiple catalytic sites SMAD-MFEs. Then, experimental materials were selected, experimental methods and measurement methods were determined, and an example analysis of machine learning-based enzymes during millet storage was performed, specifically from two aspects: model analysis and the study of peroxidase during millet storage. The results showed that the activity of millet peroxidase decreased by 92.2mg H2O2g−1, 90.4mg H2O2g−1, and 85.7mg H2O2g−1 for conventional, nitrogen-filled storage at 22°C. The activity of millet peroxidase decreased by 102.2mg H2O2g−, 98.8g H2O2g−, and 95.1mg H2O2g− The rate of reduction in peroxidase activity of millet stored in nitrogen-filled storage was not significantly different. This study was conducted to understand the enzyme change pattern during millet storage to provide a more intuitive and realistic reference for individual households to store grain.

Under the background of the shortage of traditional energy and the increasingly serious environmental problems, this paper proposes a bi-level optimization configuration method for microgrids based on stepped carbon trading and price-based demand response. The stepped carbon trading mechanism is introduced into the planning model to clarify the impact of construction processes on land carbon emissions. Simultaneously, price-based demand response during system operation is introduced, guiding users to change the electricity consumption strategies to promote the consumption of renewable energy. Then, a bi-level optimal configuration framework is constructed. The upper level is optimized to allocate the capacity of the microgrid, with the lowest annual equivalent comprehensive cost as the objective function. The lower level is optimized for microgrid operation, with the minimum sum of the microgrid operation cost and carbon emission cost as the objective function. In view of the advantages of enhanced whale optimization algorithm (E-WOA) in solving multi-dimensional feature selection problems, E-WOA and CPLEX solver are combined to solve the bi-level optimization model for the first time. Simulation results show that after introducing a stepped carbon trading mechanism, the system carbon emissions decreased by 23.09%. Considering price-based demand response under the premise of introducing a stepped carbon trading mechanism, the total cost decreased by 3.57% and the carbon emissions decreased by 19.83%.

C31H28N2O2, triclinic, P1‾$P\overline{1}$ (no. 2), a = 9.0809(9) Å, b = 9.2626(9) Å, c = 14.8540(15) Å, α = 93.574(8)°, β = 98.554(8)°, γ = 99.558(8)°, V = 99.558(8) Å3, Z = 2, Rgt(F) = 0.0541, wRref(F2) = 0.1424, T = 293(2) K.

The existing research on ventilation control for long-distance heading face is mostly limited to the frequency conversion of local ventilation fans themselves. There is few research on the on-demand wind supply direction for long-distance heading face. In order to solve the above problem, a design scheme for an intelligent regulation and control system for local ventilation in long-distance heading face is proposed. The system consists of an underground monitoring system, a ventilation anomaly control system, and a ground workstation. The underground monitoring system achieves early warning of abnormal working conditions of local ventilation fans, dynamic analysis of air leakage inside the air ducts, and dynamic prediction of actual supply and demand air volume by real-time monitoring of underground ventilation fans, air ducts, and working surfaces. The ventilation anomaly control system identifies underground abnormal ventilation parameters, develops risk collaborative disposal strategies for different parameters and levels, and displays the specific distribution of parameters such as gas concentration in the heading face in real-time. The ground workstation excavates the potential laws between the air flow status of the heading face and the parameters of the air duct, forming an air flow-air duct control model. Real time control of the air duct is achieved based on the distribution status of the air flow in the heading face. At the same time, the workstation establishes a variable frequency predictive air regulation model that matches the theoretical air supply, actual air supply, and actual air demand. Based on the variable frequency air regulation model and real-time ventilation parameters, the operating frequency of the fan is determined. The on-demand air supply is achieved through intelligent variable frequency of the fan. In abnormal ventilation situations, based on the prediction of gas emission and the limit capacity of air venting gas, supplemented by drilling gas extraction to control the concentration of gas in the working face, the ventilation safety guarantee for the long-distance heading face is achieved. Taking the 23303 heading face of Zhuanlongwan Coal Mine as an example, numerical simulation of air flow is conducted to study the distribution status of air flow in the face. It provides a basis for adjusting the layout of wind speed sensors in the heading face. The paper proposes two different ventilation linkage control methods, namely variable frequency wind regulation under normal conditions and regulating exhaust air under abnormal conditions. The operating frequency of the fan is determined through supply and demand matching analysis under normal conditions to achieve intelligent variable frequency air regulation of the fan. In case of abnormal ventilation, four regulation and exhaust rules are adopted to ensure the ventilation safety of long-distance heading faces, while achieving the effect of energy conservation and emission reduction. A comprehensive evaluation system for the health indicators of the local ventilation system has been constructed. Through a comprehensive evaluation model and health index, real-time health 'physical examination' of the local ventilation system is achieved, and the risk levels of different indicators are quantitatively displayed to ensure that the local ventilation system is in a healthy state.

In this work, a non-targeted metabolomic study was performed on the ultrafine whole pulp of Lactobacillus-fermented Chimonobambusa quadrangularis shoot using ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). Based on the variable importance in projection (VIP) > 1 and P < 0.05 in t-test, 361, 392 and 398 differential metabolites were selected in raw (control) versus Limosilactobacillus reuteri (LR) fermented samples, control versus Lactobacillus plantarum (LP) fermented samples, and control and LR + LP (LRP) fermented samples in the positive ion mode; and 268, 304 and 321 differential metabolites in the negative ion mode, respectively. The major differential metabolites were lipids and lipid-like compounds, organic acids and their derivatives, organic heterocyclic compounds, and benzenes including histamine, D-mannan, indole-3-lactic acid, DL-4-hydroxyphenyl lactate, ornithine, and proline. Four significant metabolic pathways were identified by Kyoto Encyclopedia of Genes and Genomes metabolic pathway enrichment analysis, namely purine metabolism, pyrimidine metabolism and phenylalanine metabolism and citric acid cycle. This study provides theoretical support for the development of fermented bamboo shoot products.

The aim of this study was to explore the changes in pH and pepsin concentrations in oral lavage fluid of rabbit reflux model. A total of 18 New Zealand rabbits were randomly divided into two groups. The lower esophageal sphincters (LESs) of the rabbits in the experimental group (EG) were dilated by balloon after the LESs were localized by manometry. The pH levels of the throat and the lower esophagus were monitored 1 week before and 2 weeks after inflation. Oral lavage fluid was collected 1 week before, and 2 and 8 weeks after inflation. The pH monitoring showed that the percentage of reflux time, the number of reflux events, and the longest time of reflux after the dilation (AE) in the EG were significantly higher than before the dilation (P < 0.01). The pepsin concentrations at 2 and 8 weeks AE in the EG were significantly higher than that before and that in the control group (P < 0.05). Based on receiver operating characteristic curve analysis, the best diagnostic threshold value was 30.3 ng/ml. The reflux model constructed by balloon inflation of the LES in rabbits is characterized by a decrease in throat pH and an increase in salivary pepsin concentration.

The functional reconstruction of large maxillofacial defects is a major issue in oral and maxillofacial surgery, and autologous bone transplantation is the main method. However, bone is readily absorbed following an autologous bone transplant. Even with vascular anastomosis, spontaneous osteoporosis of transplanted bone is still serious, which affects dental implantation and functional recovery. Therefore, osteoporosis of the grafted bone has become one of the main complications of jaw reconstruction, and there is no preventive measure. The problem that autologous bone with sufficient blood supply cannot avoid osteoporosis suggests that systemic factors such as nerves, which have been neglected in traditional methods, may regulate the internal environment of the transplanted bone. Based on previous studies on the regulation of mesenchymal stem cells by the neural microenvironment, we initiated a new surgical procedure for innervated and vascularized iliac bone flaps based on animal model and cadaver studies. In the innervated and vascularized iliac bone flap, vascular microanastomosis was performed in conjunction with microneuronal anastomosis between the simultaneously harvested ilioinguinal nerve (which innervates the iliac bone and is usually sacrificed and neglected in the conventional vascularized iliac bone flap) and the inferior alveolar nerve proximally and with the mental nerve distally. By conducting clinical retrospective studies and prospective randomized controlled trials, we proved that the novel method of simultaneous innervated iliac bone transplantation can not only prevent bone resorption but also restore the sensation of adjacent soft tissues such as the lip. This may solve the key problems of sensory loss and osteoporosis after mandibular reconstruction, ensure the success of dental implant dentures, and put forward the new concept of "blood supply + innervation" bi-system bone transplantation.

In this study, headspace-solid-phase microextraction extraction combined with gas chromatography-orbitrap-mass spectrometry (HS-SPME-GC-Orbitrap-MS) was used to establish a method for the simultaneous determination of five aldehydes and ketones and four furans in fruit wines. The method was validated on model wine, goji berry wine, blueberry wine and hawthorn wine. The limits of detection (LODs) for all target compounds ranged from 0.004 to 6.300 μg/L, and the limits of quantification (LOQs) were between 0.01 and 21.00 μg/L. The recoveries of all analytes in spiked wine samples were between 81% and 120% and the relative standard deviations (RSDs) for precision were equal to or less than 19.08%. This method is accurate and can meet the requirements for the quantification of aldehydes, ketones and furans in fruit wines.

Starting from the analysis of the distribution of objects in distress and the probability of ideal discovery, the correction factors affecting aerial search, the width of the scan and the searchable range are comprehensively interpreted, and the actual discovery probability, success probability, inclusive probability and cumulative success probability are comprehensively sorted out. It provides effective means and support for the determination of the scope of search and rescue in aviation search and rescue operations and the analysis of the probability of successful search.

With the rapid development of China’s electric power industry, the cost management of electric power projects, which is closely related to the power grid transmission and substation projects, has become more and more important. Do a good investment feasibility analysis of power projects. Optimize power engineering design. Reasonable determination of power project cost and effective control of power project cost are the main problems to be solved by the project cost management of power grid transmission and transformation projects. In this paper, DCN-BIM model is established based on DCN algorithm as the theory. A detailed calculation and analysis of the influencing factors and stage share of the cost management of power grid transmission and substation projects is carried out. Through calculation, it can be seen that the share of power products in the project cost is about 15.43% due to their special characteristics. The lowest cost share in the project cost is the project tender. Its share is only 10.03%. The highest cost share is for equipment materials. Its cost share is as high as 51.34%. The design phase accounted for 23% of the cost. The lowest cost share in the bidding phase was only 21%.

ObjectiveTo construct an evaluation index system for the development of district-level disease prevention and control centers according to the requirements of the modernization of Shanghai’s disease control system and public health work practices， and to comprehensively assess the construction and development of district-level disease prevention and control institutions.MethodsAccording to the national and municipal requirements for the development of disease prevention and control institutions， an index framework was proposed through literature search and expert interviews. 39 representative experts in the field of public health at the national， provincial， and municipal （district） levels were selected to participate in the consultation and construction of the index system. The authority coefficient， the coefficient of variation， etc. were used to carry out quality control and determination of each index on the Delphi method.ResultsThe questionnaire response rate was 100%， the expert authority coefficient was 0.86，the degree of familiarity was 0.79， and the judgment basis was 0.92. The coefficients of variation of the necessary indicators in the index system were all

The shipping industry, which undertakes over 90% of global trade and transportation, has rich digital scenarios. Empowering the shipping industry through smart port construction and integrating ports with virtual–real integration to form a smart port digital base has become an industry consensus. This study defines the smart ports and the virtual – real integration technology system, and analyzes the demand of port operation for virtual – reality integration technology from five aspects: operation planning, activity implementation, equipment operation and maintenance, safety and emergency response, and energy conservation. It also summarizes maps of six virtual – real integration technologies and their application scenarios in smart ports, the technologies being system simulation, extended reality, information-physical system, digital twin, parallel system, and metaverse. After sorting out the development idea and examining scientific issues, a system framework is proposed for the high-quality development of smart ports driven by virtual–real integration technologies, covering the development positioning of technology systems, key technology development directions, and research directions in key fields. Suggestions for development are proposed from the perspectives of deepening application, policy incentives, technological demonstration, and talent cultivation, thereby providing a reference for the engineering application of the virtual–real integration technology system in smart ports.

Objective To screen the risk factors of intracranial infection in patients with severe traumatic brain injury (sTBI) and establish a Nomogram model based on these risk factors. Methods A total of 130 patients with sTBI admitted to The Second Affiliated Hospital of Shandong First Medical University from January 2021 to June 2022 were enrolled. They were divided into a group with intracranial infection (n = 27) and a group without intracranial infection (n = 103) according to whether complicated with intracranial infection. To analyze the risk factors of intracranial infection in patients with sTBI by univariate and multivariate stepwise Logistic regression, and construct a Nomogram model based on the risk factors to draw receiver operating characteristic (ROC) curve and calibration curve of this model and perform Hosmer⁃Lemeshow goodness of fit test. Results The proportion of diabetes (χ2 = 5.356, P = 0.021), open traumatic brain injury (χ2 = 4.248, P = 0.039), cerebrospinal fluid (CBF) leakage (adjusted χ2 = 4.731, P = 0.030), surgical treatment (χ2 = 8.284, P = 0.004), severe infection (adjusted χ2 = 6.479, P = 0.011), tracheal intubation (χ2 = 6.487, P = 0.011) and tracheotomy (χ2 = 4.072, P = 0.044) in intracranial infection group were higher than those in non ⁃ intracranial infection group. Logistic regression analysis showed diabetes (OR = 2.748, 95%CI: 1.417-8.654; P = 0.047), CBF leakage (OR = 4.483, 95%CI: 1.852-8.341; P = 0.031), surgical treatment (OR = 1.941, 95%CI: 1.483-8.842; P = 0.031) and severe infection (OR = 1.614, 95%CI: 1.113-5.682; P = 0.041) were risk factors for sTBI complicated with intracranial infection. The area under the curve (AUC) of ROC curve was 0.758 (95%CI: 0.641-0.875, P = 0.001), and the optimal cut⁃off value for predicting sTBI complicated with intracranial infection was 175. The calibration curve showed good consistency between the predicted probability and the actual probability, while the Hosmer⁃Lemeshow goodness of fit test showed no statistically significant difference (χ2 = 4.613, P = 4.412), indicating the Nomogram model has good differentiation, calibration and stability. Conclusions Diabetes, CBF leakage, surgical treatment and severe infection can increase the risk of sTBI complicated with intracranial infection. The Nomogram model can better predict the risk of sTBI complicated with intracranial infection.

Based on a literature review and policy analysis, this study investigates the evolution of China's railway investment and financing, planning, and development in the context of its market-oriented reform. The relationship between railway and multi-level spatial development is divided into specific periods. The features of different stages are summarized from the perspective of railway financing structure, route arrangement, station location, and their spatial effects. This study contributes to our understanding of the changing multi-level governance of railway development in China in the long run and the rationale of the pattern of high-speed rail network development in the country. With the establishment of China's market-oriented economy and its integration into economic globalization, the central and local governments have different interests and objectives in railway development, which have affected railway investment and financing structure, route arrangement, and station location, and finally resulted in different spatial effects of railway development. Since the establishment of the People's Republic of China, the relationship could be divided into four periods: i) railway services adapted to national economic and spatial development (1949-1978), ii) railway services lagged behind national economic and spatial development (1978-2004), iii) railway construction followed national economic and spatial development (2004-2013), and iv) railway construction led national economic and spatial development (2013-present). The main body of railway development, construction mode, and spatial effects were significantly varied across different periods. In the planned economy period, railway planning construction adapted to national strategic policies and social and economic needs. As China's institution of the market economy was established and urbanization and industrialization developed rapidly, railway construction was hindered by funding constraints, resulting in a significant gap between railway services supply and the increasing national transportation demand. Consequently, railway construction has gradually fallen behind national economic and spatial development. However, there are differences in the national and local interests between the central and local governments in planning and developing railway networks, which have driven the evolution of railway construction toward a multi-level construction mode. This mode centers around the national backbone network, dominated by the central government, and aims to promote the construction of national development corridors and urban agglomerations. The planning for metropolitan areas has been facilitated via inter-city rail networks, led by provincial and municipal governments. In this process, conventional railways are gradually being replaced by high-speed railways (HSR), which have become the priority of railway development. Subsequently, development has shifted from the construction of conventional railways to meet regional transportation and population flow needs toward the planning and construction of HSR that lead multiscale spatial restructuring. In the context of rapid expansion of high-speed rail development, some spatial problems emerged, such as negative impacts of HSR development on small and middle-sized cities, low land use efficiency in station areas, and weak functional connections between station areas and central cities. Therefore, to promote the coordinated development of urban agglomerations and metropolitan areas, it is necessary to develop station areas based on local and regional conditions and enhance the interaction of high-speed rail effects at different scales.

This article reports a case of nevus trichilemmocysticus. The patient, a 48-year-old man, presented with multiple filiform keratoses and nodules. Physical examination identified multiple subcutaneous papules and nodules on the scalp, filiform keratoses on the face and bilateral ears, in addition to linear blackheads on trunk and limbs. The patient also exhibited hair loss and hypoplastic tooth. Histopathology revealed trichilemmal cyst. Nevus trichilemmocysticus is a rare organoid nevus. We reviewed literature in order to raise the awareness of the syndrome.

Objective·To explore the changes of pelvic floor structure in the early and middle pregnant women with the history of cervical incompetence (CIC) by ultrasound.Methods·The pregnant women during early and middle trimesters were collected from Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine from August 2022 to January 2023. All the pregnant women had only one history of premature delivery, abortion or induced labor in the middle trimester, and were divided into CIC group and control group according to whether having the history of CIC in the previous pregnancy. Age, body mass index (BMI), gestational age, the prevalence of funneling of internal urethral orifice and the prevalence of urinary incontinence were compared between the two groups. Two-dimensional, three-dimensional, and four-dimensional pelvic floor ultrasound was used to measure the pelvic floor structures of the women in the states of resting, pelvic floor muscle contraction (PFMC) and Valsalva maneuver (VM). The parameters of pelvic floor structure included bladder neck position, urethral inclination angle, urethral rotation angle, posterior angle of bladder, bladder neck mobility, cervix position, position of ampulla of rectum, area of urogenital hiatus (HA), hiatal transverse diameter, and hiatal anteroposterior diameter. General linear regression model was used to correct the influence of confounders and to analyze the association between the history of CIC and the different indexes of pelvic floor structure.Results·A total of 76 pregnant women in early and middle trimesters were collected, including 39 women in the CIC group and 37 women in the control group. There was no significant difference in the age between the two groups, while BMI and gestational age in the CIC group were significantly greater than those of the control group, and the differences were significant (both P 0.05); at the state of VM, HA (P=0.016) and hiatal anteroposterior diameter (P=0.014) increased in the CIC group, while other parameters did not change significantly. It was found that the CIC history was associated with HA (P=0.038) and hiatal anteroposterior diameter (P=0.049) at VM after adjusting gestational age and BMI by the general linear regression model. The incidence rates of funneling of internal urethral orific in the CIC group and the control group were 10.25% and 0, respectively; the incidence rates of stress incontinence were 23.07% and 13.51%, respectively. Neither of the differences were significant (both P>0.05).Conclusion·In the pregnant women with the history of CIC, HA and hiatal anteroposterior diameter at VM increase, and the morphological change of the levator ani hiatus is more obvious with the increase of the vertical axis.

Abstract Background Isolated congenital bilateral absence of vas deferens (iCBAVD) in men results in obstructive azoospermia and is mainly caused by pathogenic variants in cystic fibrosis transmembrane conductance regulator (CFTR) or adhesion G protein‐coupled receptor G2 (ADGRG2). Methods The next‐generation sequencing (NGS) was used to screen the mutations in the proband, and Sanger sequencings were performed to validate the compound heterozygous variant of CFTR in his family members. Protein structure simulation was performed to discover the potential pathological mechanism. Results This study reported novel compound heterozygous CFTR mutations (NM:000492.4, Intron: 5T; c.3965_3969dupTTGGG: p.R1325Gfs*5) in two brothers with obstructive azoospermia. The compound heterozygous CFTR mutations were first screened out by NGS in an infertile male patient who exhibited iCBAVD from a nonconsanguineous Chinese family. Histological analysis of the testicular biopsy from this patient revealed normal spermatogenesis and mature spermatozoa were observed in the seminiferous tubules. Surprisingly, the same compound heterozygous CFTR mutations were also observed in his brothers who also exhibited iCBAVD, with their parents being a heterozygous carrier for the mutations, as verified by Sanger sequencing. Protein structure simulation revealed that these mutations potentially led to impaired ATP‐binding ability of CFTR. Conclusion We identified novel compound heterozygous CFTR mutations in two brothers and summarized the literature regarding CFTR mutation and male infertility. Our study may contribute to the genetic diagnosis of iCBAVD and future genetic counseling.

Plant growth regulators (PGRs) are defined as naturally occurring or artificially synthesized compounds. The functions of PGRs mainly include accelerating or delaying seed germination, breaking plant dormancy, stimulating or reducing bud elongation, inducing flowering and fruiting, and affecting the aging process. The application of PGRs has effectively promoted the growth of plants. However, the application concentration of PGRs is more than one millionth. The large amount of abuse and misuse of PGRs in the process of use not only reduces the yield of crops, but also exacerbates their residues in the environment, especially in agricultural products such as fruits and vegetables. So, they are detected in many environmental media like fruits, vegetables, and water. In addition, most PGRs are toxic, and some of them will undergo adsorption, desorption, hydrolysis, photolysis, microbial degradation, and other environmental behaviors after entering the soil. The decomposition products produced by this process are more toxic.In order to comprehensively understand the current status of PGRs pretreatment, analysis and test method, the common pretreatment methods of solid phase extraction and liquid-liquid extraction for typical PGRs in solid substrates such as fruits and vegetables, fertilizers and soil, and in liquid substrates such as water, edible oil and nutrient solution are summarized in this paper, as well as the analysis and testing techniques such as high-performance liquid chromatography (HPLC) and ultra-high performance liquid chromatography (UPLC). Moreover, to reduce the detection limit, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) is also frequently used. At the same time, considering the strong natural attenuation ability of PGRs and the high toxicity of their intermediates, the advantages, disadvantages and applicability of different testing techniques are systematically summarized, taking into account the special structure and nature of PGRs, in order to fully understand the current status of pretreatment and analytical testing of PGRs and provide literature support for subsequent research on analytical testing, migration transformation, pollution evaluation and treatment of PGRs.Due to many impurities in the sample that can interfere with the detection, the appropriate pretreatment method can improve the accuracy of the test results. However, the sample pretreatment process accounts for more than 70% of the total analysis and test work, and about 50% of the error in the final test results comes from pretreatment. Therefore, establishing a fast, simple, and stable pretreatment method can effectively improve the efficiency and accuracy of analysis and detection. At present, the forms of environmental media detected for PGRs are mainly divided into two types: solid matrix samples (such as fruits, vegetables, fertilizers and soil, etc.) and liquid matrix samples (water, oil and nutrient solution, etc.). The related pretreatment methods are also mostly targeted at these two different forms of environmental media.Solid substrates involving PGRs mainly include fruits and vegetables, fertilizers and soil. Among them, fruits and vegetables are the most frequently detected solid substrates of PGRs, and some PGRs have also been detected in fertilizers, soil and other substrates. The pretreatment process of solid matrix samples can be divided into two parts: extraction and purification. Among them, solid phase extraction is the most commonly used extraction technology, and QuEChERS method is the most widely used purification method.Water, edible oil, and nutrient solution are the most frequently detected liquid substrates of PGRs. At present, liquid-liquid extraction is the most commonly used extraction method for liquid matrix. For the selection of extractants, the octanol-water partition coefficient of PGRs such as gibberellic acid and ethephon is less than 1, which is a strong polar compound and can be extracted by hydrophilic organic solvents such as methanol, ethanol and acetone; the polarity of most other PGRs such as forchlorfenuron and paclobutrazol is relatively weak, but it still belongs to the category of strong polarity compared with other kinds of compounds such as benzene and chloroethane (n-octanol-water partition coefficient>10). Therefore, the extractant can not only use methanol, but also use polar organic solvents such as ethyl acetate and chloroform that are insoluble in water. Although liquid-liquid extraction requires a lot of extractants, the high-water solubility of most PGRs makes them often directly detected by HPLC-MS/MS, which eliminates the complex pretreatment steps such as extraction and purification. In addition, because some PGRs have poor chromatographic characteristics or are not easily detected, the derivatization is also required to convert the components into derivatives suitable for analysis.Analytical and testing technologies mainly include gas chromatography (GC), gas chromatography-mass spectrometry (GC-MS), HPLC/UPLC, HPLC-MS/MS, ion chromatography (IC), spectrophotometry (SP), capillary electrophoresis (CE), enzyme-linked immunosorbent assay (ELISA) and electrochemical sensor method.At present, the solubility of most PGRs in water (20℃) is 0.50-10g/L, and the octanol-water partition coefficient of most PGRs is 0-4, with strong hydrophilicity. Therefore, HPLC-MS/MS are applicable to the detection of almost all PGRs. However, HPLC-MS/MS are often used to detect the residues of PGRs in fruits and vegetables, followed by soil and fertilizer, while there are few related studies in natural water. This may be due to the rapid natural decay rate of PGRs in the natural environment, resulting in extremely small amounts of residues in natural water bodies such as surface water and groundwater that cannot be directly detected.GC has the advantages of low cost and easy maintenance, and GC-MS has become a conventional testing technology. However, GC-MS are greatly affected by sample matrix interference and require high pretreatment methods. In addition, due to the influence of the physical and chemical properties of different PGRs (such as abscisic acid and indole acetic acid with a boiling point over 400℃, or forchlorfenuron and cinnamic acid with hydroxyl and carboxyl groups), most PGRs have poor gas chromatographic characteristics and are not easily detected.The order of detection limits of PGRs is GC>HPLC>chromatography-mass spectrometry, and the lowest instrumental detection limit of chromatography-mass spectrometry is 10-5mg/kg. However, the higher solubility and the larger natural attenuation rate of most PGRs lead to the lower detection concentrations in complex environmental substrates such as soil and water, so there is still an urgent need to solve the problem of analytical testing of trace PGRs and its intermediates.In future, PGRs analysis and test method will focus on the analysis and detection of trace PGRs and their intermediates, as well as the development of new materials and technology-based methodologies.

This case report describes the lingual orthodontic treatment of a 28-year-old female patient who presented with a bimaxillary protrusion malocclusion, a hyperdivergent facial pattern, mentalis strain, and a ‘gummy’ smile. To achieve favourable occlusal and facial results, the four first premolars were extracted, and micro-screws utilised to provide maximum anchorage. With the widespread application of three-dimensional technology, a digital goal-oriented treatment plan was applied for its predictability and precision. A fully customised lingual appliance system with preset torque in the anterior teeth combined with ribbon-wise arch wires was placed to prevent excessive lingual inclination of the incisors during retraction. As a result, an attractive facial profile and a well-aligned dentition with ideal intercuspation was obtained.

Multiple kernel learning(MKL) aims to find an optimal consistent kernel function.In the hierarchical multiple kernel clustering(HMKC) algorithm,the sample features are extracted layer by layer from high-dimensional space to maximize the retention of effective information,but the information interaction between layers is ignored.In this model,only the corresponding nodes in the adjacent layer will exchange information,but for other nodes,it is isolated,and if the full connection is adopted,the diversity of the final consistence matrix will be reduced.Therefore,this paper proposes a hierarchical multiple kernel K-Means(SCHMKKM) algorithm based on sparse connectivity,which controls the assignment matrix to achieve the effect of sparse connections through the sparsity rate,thereby locally fusing the features obtained by the distillation of information between layers.Finally,we perform cluster analysis on multiple data sets and compare it with the fully connected hierarchical multiple kernel K-Means(FCHMKKM) algorithm in experiment.Finally,it is proved that more discriminative information fusion is beneficial to learn a better consistent partition matrix,and the fusion strategy of sparse connection is better than the strategy of full connection.

Solitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast enhanced CT (CECT), CT perfusion imaging (CTPI), and dual- energy CT (DECT) used for differentiating benign and malignant SPNs with a multi-institutional and prospective study.

Objective To construct a Nomogram model that can accurately predict early death of metastatic colon cancer (mCC). Methods A total of 6 669 patients from the SEER database were identified using inclusion and exclusion criteria. Multivariate logistic regression was used to identify risk factors for early mortality and to construct a Nomogram. The predictive performance of the Nomogram was evaluated by C-index, calibration curve, and decision curve analysis (DCA). Results Primary tumor location, differentiation grade, T stage, M stage, bone metastases, brain metastases, CEA, tumor size, age and marital status were independent factors for early death in patients with mCC. A Nomogram was constructed based on these variables. The C-index and the calibration curve of the Nomogram showed the good predictive ability of the nomogram. DCA showed that the Nomogram had a superior clinical net benefit in predicting early death compared with TNM stage. Conclusion The developed Nomogram has good predictive ability and can help guide clinicians to identify patients with high-risk mCC for individualized diagnosis and treatment.

In order to analyze the mechanism of cutting and dust production of coal and rock driving machine, the three axis force model of coal and rock was constructed based on EDEM method, and the coal dust cutting mechanism under different cutting conditions was analyzed. The results show that the number of bonds between particles decreased periodically with the operation time of the cutting head, the cycle length is in the range of 0.2 s to 0.7 s, and the number of broken bonds between particles increases linearly with the cutting time; the average body mass and throwing velocity of particles in the process of coal cutting with cutting depth showed a distribution of cyclical fluctuations, in addition, the average particle throwing velocity of rock mass cutting is obviously larger; the cutting depth increased gradually with the increase of cutting head operating time and the average velocity of particle throwing shows an increasing trend of fluctuation from about 1.0 s; with the increase of cutting depth, the average speed of the particles increased periodically under different roof pressure conditions, and the height of cut coal has little influence on the dust generation process.

To improve the ride comfort of a light commercial vehicle, the dynamic performance of the hybrid air suspension was analyzed and optimizaed by multi-body dynamics. Through the quasi-static compression test, the dynamic model of the air spring under different air pressures was established, and then the dynamic performance of the vehicle under random and pulse input were studied through the multi-body dynamics simulation. A combined model for ride comfort simulation was established ob basis of Isight, Matlab and Adams/Car. Through performing the sensitivity analysis, the parameters that have a great impact on the ride comfort performance were determined. Finally, the ride comfort of the whole vehicle under random and impulse input is optimized through the Co-simulation platform and NSGA-Ⅱ optimization algorithm. The simulation results of ride comfort after optimization show that: under random input, the root mean square value of weighted acceleration at the driver is reduced by 13.6%, and that at the passenger is reduced by 25.6%; under pulse input, the maximum vertical acceleration at the driver is reduced by 15.9%, and that at the passenger is reduced by 29.4%, and the ride comfort of the whole vehicle is significantly improved.