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Accurate photovoltaic （PV） output power forecasting plays a crucial role in ensuring the secure and stable operation of distribution networks. In light of this， the paper proposes a short-term PV power forecasting method using cosine similarity and a hybrid TSO （tuna swarm optimization） and BP （back propagation） neural network. Firstly， the cosine similarity algorithm is utilized to identify historical data with strong resemblance to the forecast day as training samples. Subsequently， the TSO algorithm is employed to search for optimal initial weights and thresholds for the BP neural network. The TSO-BP model is then trained for short-term PV power forecasting. Finally， the TSO-BP model is applied to predict PV output power under both stable and fluctuating weather conditions. Simulation results indicate that， the proposed method， compared to traditional forecasting methods， achieves higher accuracy in predictions for both steady and fluctuating weather scenarios.

Voltage instability, power imbalance, and unreliability are caused mainly by equipment failure in the distribution system, so it is important to accurately and quickly assess the status of distribution network equipment. However, it is challenging to detect equipment failures, the traditional XGBoost algorithm is unsuitable because some evaluation indices are incompetent to quantify. To address these issues, we propose a fast evaluation method for the state of electrical distribution equipment based on fuzzy decision-making. Firstly, key indices are selected from the multi-source equipment information. Secondly, this paper constructs the mapping between key indices and equipment status scores by combining the fuzzy iterative method and the XGBoost algorithm. Finally, the proposed assessment model is confirmed by using the distribution transformers as an example. The result shows that the proposed multi-source information assessment method can quickly and accurately determine the operation status of electrical distribution equipment, and the proposed method has better accuracy than the traditional method.

Objective To evaluate the psychological intervention combined with Traditional Chinese Medicine Ta stain therapy in nursing of patients with diabetic foot ulcer. Methods Totally 64 patients with diabetic foot ulcer were randomly divided into the control group and the observation group, with 32 cases in each group. All patients received local dressing change in addition to the comprehensive treatment such as blood glucose control and infection prevention. Patients in the observation group were given psychological intervention combined with wet compress of Traditional Chinese Medicine. The condition of swelling relief and wound repair were evaluated after intervention, and the degree of pain was measured by using Visual Analogue Scale (VAS). Results The total effective rates of swelling relief and wound repair in the observation group were higher than those in the control group(P＜0. 05). The VAS score was decreased in both two groups after intervention, and VAS score in the observation group was lower than that in the control group(P＜0. 01). Conclusion The psychological intervention combined with wet compress of Traditional Chinese Medicine is effective to improve the swelling relief and wound repair, and reduce the pain of patients with diabetic foot ulcer. (目的 探讨心理干预联合中药塌渍技术在糖尿病足溃疡患者护理中的应用效果。方法 采用随机数字表法将64例糖尿病足溃疡患者分为对照组和观察组, 各32例。两组患者在积极控制血糖和抗感染的基础上, 给予局部换药; 观察组增加中药塌渍治疗, 并强化患者心理干预。评估患者红肿伤口消肿情况和破溃伤口修复情况, 采用视觉模拟评分(VAS)评估患者足部疼痛感, 评价干预效果。结果 红肿伤口消肿和破溃伤口修复评价结果显示, 观察组干预效果均优于对照组, 差异有统计学意义(P＜0. 05)。干预后, 两组VAS量表评分均较干预前下降, 且观察组VAS量表评分低于对照组, 差异有统计学意义(P＜0. 01)。结论 在常规护理的基础上, 心理干预联合中药塌渍技术能有效促进糖尿病足溃疡患者红肿伤口消肿和破溃伤口的修复, 缓解足部疼痛感。)

Objective To investigate the effect of humanistic nursing interventions on anxiety and depression of patients with diabetic foot. Methods A total of 100 patients with diabetic foot were randomly divided into the control group and observation group, with 50 cases in each group. All patients received comprehensive treatment of diabetes and routine care, and those in the observation group were given humanistic nursing interventions. The Self-rating Anxiety Scale and Self-rating Depression Scale were used to measure the negative emotions of patients. Results The SAS and SDS scores were significantly decreased after intervention, and SAS and SDS scores in the observation group were lower than those in the control group (P＜0. 01). Conclusion The humanistic nursing intervention is effective to relieve the anxiety and depression of patients with diabetic foot. It may help to enhance patient’s positive coping style and quality of life. (目的 运用人文关怀护理干预缓解糖尿病足患者焦虑抑郁情绪。方法 选取于2022年1月—2023年4月医院收治的糖尿病足患者100例为研究对象, 随机分组为对照组和观察组, 各50例。对照组接受常规治疗和护理, 观察组在对照组基础上增加人文关怀护理。采用焦虑自评量表(SAS)和抑郁自评量表(SDS)评估患者焦虑抑郁情绪。结果 干预后, 两组SAS和SDS量表评分均较干预前下降, 且观察组SAS和SDS量表评分低于对照组, 差异有统计学意义(P＜0. 01)。结论 人文关怀护理能有效改善糖尿病足患者焦虑抑郁情绪, 增强积极应对方式, 从而有利于改善生活质量。)

This paper establishes a microchannel model based on the pore scale distribution characteristics of natural cores from Daqing Oilfield. It considers the deformation and flow characteristics of the dispersed and continuous phases in the heterogeneous system， builds a flow model by the phase field method， and solves it by the finite element method. The paper also simulates the generation of dispersed phase particles in the microchannel， realizes particle sorting， and studies the effect of the matching coefficient and pore-throat ratio on the plugging performance of particles in the microscopic pore-throat structure. The results show that when the particles are elastically plugged in the microscopic pore-throat structure， the pressure at the entrance of the pore throat changes periodically with the migration of the particles through the pore throat. The optimal matching coefficient between the particles and the pore throat is ［1.0， 1.4）. In this interval， the particles can be temporarily plugged at the entrance of the pore throat and recover their original shape after deformation and migration through the pore throat. When the pore diameter is the same， a larger matching coefficient and pore-throat ratio indicate greater pressure of particles through the pore throat， and larger particle size reflects a smaller critical value of particles through the pore throat.

Ultra high pressure common rail system can realize adjustable injection rate by controlling the relationship between fuel injection and pressurization timing, and then affect the fuel injection characteristics of diesel engine. In order to ascertain the effect law and its formation mechanism of the fuel injection and pressurization pulse width on the fuel injection characteristics of ultra high pressure common rail system, on the basis of introducing the mathematical model of the system, the simulation model of ultra high pressure common rail system was established, and the accuracy of the model was verified by performance experiment, the effect of fuel injection and pressurization pulse width on the fuel injection characteristics of the system under different common rail pressure were analyzed. The results show that with the increase of fuel injection pulse width, the shape of fuel injection rate curve is similar to saddle shape and the proportion of large fuel injection rate range in the whole injection process increases gradually. At the same time, the fuel injection opening delay remains unchanged, but the fuel injection closing delay increases significantly when the fuel injection pulse width is small (0.6~1 ms), while it remains basically unchanged when the fuel injection pulse width is large (1~1.4 ms). With the increase of pressurization pulse width, the shape of fuel injection rate curve is similar to saddle shape and remains unchanged under the condition of small injection pulse width, while the fuel injection rate curve shape may appear similar to the "inverted saddle-shaped" under the condition of large injection pulse width, this is due to the rapid decrease of pressurization pressure caused by the closing of the solenoid valve control signal in the pressure-amplifier device before the end of fuel injection.

Acid-fracturing technologies have become conventional measures to increase production in the field of petroleum engineering， and they are widely used in carbonate rock， tight sandstone， and volcanic rock reservoirs. However， relevant research mainly focuses on specific blocks， and there is a lack of a systematic and comprehensive summary of relevant research progress. This paper comprehensively investigated the latest progress of acid-fracturing technologies in China and abroad， systematically concluded the research achievements including the hot acid-fracturing technologies， difficulties and measures of acid-fracturing simulation in different reservoirs， acid-fracturing mechanism， and factors affecting acid-fracturing， and pointed out the development trend and existing problems of acid-fracturing technologies. Differentiated multi-staged acid-fracturing technology， volume acid-fracturing technology， and fracture height control acid-fracturing technology are hot acid-fracturing technologies in recent years. There are certain differences in the difficulties of acid-fracturing simulation in different reservoirs. Therefore， it is necessary to formulate corresponding acid-fracturing technology policies according to reservoir characteristics. The acid-fracturing mechanism can be analyzed through theoretical calculation and experiments. Theoretical calculation is the basis of acid-fracturing technology research，and experiments can provide important guidance for the research on acid-fracturing mechanisms and the determination of process parameters. Acid-fracturing technologies are affected by both geological and engineering factors. Geological factors are the basis of acid-fracturing technology policies， and engineering factors are the key to improving acid-fracturing effects. At present， acid-fracturing technologies are developing in four directions： deep and ultra-deep acid-fracturing layers， accurate acid-fracturing objects， expanded acid-fracturing scope， and controllable acid-fracturing technologies. It is suggested to strengthen the research on acid-fracturing theories， continuously improve the process and equipment， and establish the implementation template of typical acid-fracturing technologies， so as to guide the implementation of acid-fracturing technologies.

The study of pedestrian catchment areas for metro stations serves as the foundation for addressing issues such as-passenger flow forecasting, land use planning around stations, and transportation link facility planning. This study aims to investigate how various factors related to pedestrians, the environment, and the characteristics of metro stations affect the areas where pedestrians are attracted to. The goal is to gain insights into design strategies and policy interventions that can enhance the appeal of metro stations. The present study considers the metro stations in the Chengdu area as the primary research objects. A framework for examining the connection between the built environment and the pedestrian catchment area of a subway station through the use of a hybrid gradient decision tree approach has been used. The study examines the pedestrian catchment areas of these stations and confirms the presence of a nonlinear relationship between pedestrian catchment areas and variables at these stations. There exists a negative correlation, within specific thresholds, between the number of companies, bus stops, and road network density with the catchment area of passengers. Concurrently, there is a positive correlation between the distances to the city center and the catchment area. Furthermore, this framework, which accounts for spatial heterogeneity, showed significant goodness-of-fit and predictive capability, aspects that were overlooked in earlier research. As a result, these research findings can serve as a key foundation for advancing the theoretical framework and statistical proof to facilitate land planning and development near metro stations, predicting passenger flow, and designing essential connecting amenities in the vicinity of such facilities.

Logistic regression and neural networks have developed rapidly in recent years, and the poor diet of people in modern society has led to the emergence of various diseases in which drug-resistant bacterial infections occur during treatment, so this paper proposes logistic regression to analyze risk factors and preventive control of multi-drug-resistant bacterial infections. A logistic regression model was established to determine the magnitude of the effect of each factor on the dependent variable based on the standardized values, and the prevalence was recoded in the prediction stage, with the screened indicators serving as factors and covariates. The number of neurons in the input and output layers is determined, and the weights are continuously adjusted in iterations to calculate the average error rate between the actual number of morbidities and the predicted values. The gradient explosion and dispersion problems of in-depth analysis are solved by selecting the maximum probability for classification. The error values were calculated by using the cost function, adjusting the model parameters, comparing the errors between predicted and observed values, and updating the weights with the hidden layer error values, thus improving the accuracy of the model for analyzing risk factors of multi-drug resistant bacterial infections and preventing and controlling the deterioration of the disease. The analysis of the results showed that the logistic regression analysis method, using the area of the ROC curve as a discriminant, yielded an AUC of 0.831 in this study, which combined with the neural network model to predict multi-drug resistant bacteria infections with a higher accuracy of 85.6%, identify the potential risk of multi-drug resistant bacteria occurrence, and prevent the aggravation of the infection.

In the coal mine, underground working places are scattered, transportation routes are complex, and there are many bends and intersections in the roadway. Based on the above characteristics and the needs of intelligent construction of coal mines, the intelligent management system of trackless rubber-tyred vehicles in coal mines is studied from the aspects of demand analysis, system architecture and key technologies. Through demand analysis, it is concluded that the intelligent management system of mine trackless rubber-tyred vehicles should have the functions of precise positioning of mine vehicles, real-time collection of mine vehicle working conditions information, mine vehicle mobile communication, mine vehicle intelligent navigation, real-time monitoring and control of mine vehicle status and mine vehicle anti-collision warning. The key technologies of the system are introduced in detail. The application of UWB positioning technology in mine trackless rubber-tyred vehicle positioning is analyzed. It is suggested that the mobile communication technology of mine vehicles should adopt WiFi and 4G/5G technology. The characteristics of common path-planning technology are discussed. It is concluded that the mine trackless rubber-tyred vehicle navigation technology should adopt the path planning algorithm based on graph search with high maturity. The mine trackless rubber-tyred vehicle navigation and track playback technology should be combined with GIS technology. The traffic light control technology of mine vehicles is studied. The intersection model and single-vehicle passing lane model are proposed. The vehicle anti-collision warning technology is studied. According to the position of pedestrians and vehicles and the relative direction and distance between them and the UWB base station, the anti-collision early warning principle under the two modes of the same base station and the cross-base station is analyzed. The experimental results show that the mine vehicle communication based on UWB, mine vehicle path planning and vehicle track playback based on A* algorithm, traffic light control, anti-collision early warning and other functions can meet the application requirements.

The complex working environment of mine leads to the degradation of the infrared image. The existing infrared image enhancement algorithm is easy to lose the scene details or causes the target edge blur while improving the signal-to-noise ratio and contrast. In order to solve the above problems, a mine infrared image enhancement algorithm based on dual domain decomposition coupling improved Gaussian Laplacian (ILoG) factor and contrast limited adaptive histogram equalization (CLAHE) (ILoG-CLAHE) is proposed. Firstly, the dual domain decomposition model is used to decompose the mine infrared image into a detailed sub-images containing high-frequency information and a basic sub-images containing low-frequency information. Secondly, the CLAHE algorithm is used to improve the brightness, contrast and definition of the basic sub-images to highlight the general features of the monitoring scene. The constructed ILoG operator is used to suppress noise and sharpen edges of detail sub-images and eliminate gradient inversion. Thirdly, the reconstructed image with improved image quality is obtained through the basic sub-image and detail sub-image after reconstruction processing. Finally, a Gamma correction function of gray level redistribution is designed to adjust the brightness of the reconstructed image. The mine infrared-enhanced image is obtained. The performance of the algorithm is analyzed by subjective vision and objective indicators. The results show that the overall visual effect and objective index of the mine infrared image enhanced by the mine infrared image enhancement algorithm based on dual domain and ILoG-CLAHE have been greatly improved. The comprehensive enhancement performance and robustness are better. Compared with the original mine infrared image and the six comparison algorithms, the comprehensive evaluation index values of this algorithm are increased by 0.28, 0.11, 0.23, 0.38, 0.57, 0.04, and 0.10 respectively. The six algorithms include CLAHE algorithm, bilateral filtering(BF) decomposition and CLAHE enhancement of basic sub-images (BF-CLAHE) algorithm, BF decomposition and Gamma transform (BF-Gamma) algorithm, guided filtering and Gamma transform (GF-Gamma) algorithm, adaptive histogram equalization(AHE) coupled Laplacian transform (AHE-LP) algorithm, and un-sharp mask(UM) based layer fusion (LF-UM) algorithm. The brightness, clarity and contrast of images are greatly improved, and noise suppression and edge sharpening are realized. It shows that the algorithm is suitable for the enhancement of infrared images in the complex working environment of mine.

This paper discusses a class of inhomogeneous fractional differential equations with boundary conditions. At the same time, we apply it to the database network encryption model. In this paper, the fractional differential equation algorithm segments the big data in the cloud environment, and the homomorphic algorithm is used for encryption. We encrypt the algorithms and store them in the database, respectively. When the model is queried, the corresponding ciphertext data in the database can be matched according to the type of query statement. The experimental simulation realizes the information retrieval and statistics in the case of full ciphertext on the server-side.

The anodic oxidation treatment on aluminum alloy using HEDP (hydroxyethylidene diphosphonic acid) as the electrolyte additive could significantly improve the corrosion resistance of the parts and be helpful for their use in marine conditions. The optimum process parameters of HEDP anodic oxidation were determined by orthogonal test and single factor test: a HEDP concentration of 0.3 mol/L, a temperature of 20～30 ℃, a current density of 0.83 A/dm2, and an oxidation time of 60 min. Moreover, the influences of various process parameters on the film microstructure were analyzed. Based on the morphology of the anodic oxide coating prepared using the optimum process parameters, the thickness of blocking layer was obtained, which was further compared with the thickness of sulfuric acid anodic blocking layer.

The separation equipment will continuously produce a small amount of solid sediment during operation, which needs to be cleaned regularly. At present, the conventional cleaning method is to use the section single-stage cleaning mode to connect multiple separation equipment in parallel. In view of the disadvantages of large amount of raw materials and total time, a cascade cleaning method is proposed in this paper, and the optimization comparison between single-stage cleaning and cascade cleaning is carried out through calculation. Taking the 10 stage cascade cleaning as an example, the optimization results show that compared with the conventional cleaning method, the use of raw material is saved by 75.9% and the cleaning time is saved by 89.3%. Therefore, the cascade mode cleaning can greatly reduce the use of raw materials and effectively shorten the total cleaning time, which is significantly better than the single-stage mode cleaning.

Along with the gradual normalization of coordinated cross-mining of multiple mineral resources, the safety situation of natural gas wells has become increasingly serious. Taking coal-gas cross-mining in the Ordos Basin as the research object, this paper proposed an anti-collision early warning method based on vibration wave monitoring prevent the occurrence of collision accidents between roadheader and gas well. Through the steel pipe percussion vibration test and coal mine excavation vibration test, the attenuation law of vibration waves in the steel pipe and coal rock is studied, and the formula for calculating the distance from the roadheader to the natural gas well is deduced according to the vibration attenuation law. The results show that the attenuation coefficients of vibration waves in steel pipes and coal rocks are different, but the attenuation laws are basically the same, both conforming to the exponential attenuation law, with the vibration waves first decaying rapidly and then slowly. It provides a reference for the realization of surface monitoring of the distance from the roadheader to the natural gas well, preventing collision and predicting early warning.

Objective To investigate the clinical value of neutrophil/lymphocyte ratio (NLR) and neutrophil/high-density lipoprotein cholesterol ratio (NHR) for carotid atherosclerosis (CAS) in patients with end-stage renal disease (ESRD). Methods A total of 220 ESRD patients [glomerular filtration rate < 15 mL/(min·1.73 m2)] admitted in our department from January 2017 to January 2021 were recruited in this study. According to the results of neck color Doppler ultrasound, they were divided into CAS group (n=80) and non-CAS group (n=140). Their general data, results of blood routine test, biochemical indexes and hs-CRP level were collected, and then NLR, NHR, monocyte to high-density lipoprotein cholesterol ratio (MHR), and platelet to lymphocyte ratio (PLR) were calculated. Results The CAS group had significant older age, higher NLR, NHR, PLR and MHR, and lower hemoglobin, albumin and HDL levels when compared with the non-CAS group (P < 0.05). Multivariate logistic regression analysis showed that older age (OR=1.067, 95%CI: 1.035~1.099, P < 0.001), elevated NLR (OR=1.295, 95%CI: 1.066~1.574, P=0.009), and increased NHR (OR=2.143, 95%CI: 1.620~2.834, P < 0.001) were risk factors for CAS, and risen hemoglobin (OR=0.945, 95%CI: 0.923~0.967, P < 0.001) were protective factors for CAS in ESRD patients. ROC curve analysis indicated that NLR (AUC=0.759, 95%CI: 0.696~0.82, P < 0.000 1), NHR (AUC=0.755, 95%CI: 0.691~0.820, P < 0.000 1) and their combination (AUC=0.793, 95%CI: 0.733~0.853, P < 0.000 1) had certain predictive values for CAS in ESRD patients. Conclusion NLR and NHR, as inflammatory indexes, are independent risk factors for CAS in ESRD patients. Their combination might have better predictive value for CAS in these patients.

The current real-time and integrity of massive data acquisition in fully mechanized working faces are poor. The abnormal data cleaning takes a long time. The data mining delays are large. This leads to low utilization rate of fully mechanized working data and incapability to assist management in issuing decision-making instructions in real-time. In order to solve the above problems, a massive data mining and analysis platform for fully mechanized working faces is designed. The platform consists of a data source layer, a data acquisition and storage layer, a data mining layer, and a front-end application layer. The data source layer is provided with raw data by various hardware devices on the working surface. The data acquisition and storage layer uses the OPC UA gateway to collect real-time monitoring information from underground sensors, and then stores the data in the InfluxDB storage engine through the MQTT protocol and RESTful interface. The data mining layer uses the Hive data engine and Yarn resource manager to filter out abnormal data caused by workplace interference during the data acquisition process. It solves the problem of local data acquisition order disorder caused by network latency. The Spark distributed mining engine is used to explore the potential value of massive working condition data in the working face device group, improving the running speed of the data mining model. The front-end application layer utilizes visual components to associate with the back-end database. It interacts with the back-end data in real-time through AJAX technology to achieve visual display of model mining results and various monitoring data. The test results show that the platform can fully ensure the real-time and integrity of data acquisition. The cleaning efficiency is 5 times better than a standalone MySQL query engine and the mining efficiency is 4 times better than a standalone Python mining engine.

Background: A high-fat Western diet is a risk factor for obesity and steatosis. Reducing intestinal absorption of a high-fat diet (HFD) is a feasible strategy to control obesity. Sulfosuccinimidyl oleate (SSO) inhibits intestinal fatty acid transport. Therefore, the aim of this study was to investigate the effects of SSO on HFD-induced glucose and lipid metabolism in mice and its possible underlying mechanisms.Methods: Male C57/BL were fed a HFD (60% calories) for 12 weeks and were administered an oral dose of SSO (50 mg/kg/day). The expression of lipid absorption genes (CD36, MTTP, and DGAT1) and the serum levels of triglycerides (TGs), total cholesterol (TC), and free fatty acids (FFAs) were detected. Lipid distribution in the liver was detected by oil red and hematoxylin and eosin staining. In addition, serum levels of inflammatory factors, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were measured to detect side effects.Results: SSO was effective in the treatment of obesity and metabolic syndrome induced by HFD in mice. It attenuated the assembly of intestinal epithelial chylomicrons by inhibiting intestinal epithelial transport and absorption of fatty acids, thereby reducing the gene expression levels of MTTP and DGAT1, resulting in decreased plasma TG and FFA levels. At the same time, it inhibited the transport of fatty acids in the liver and improved the steatosis induced by a HFD. The results of oil red staining showed that SSO treatment can reduce lipid accumulation in the liver by 70%, with no drug-induced liver injury detected on the basis of interleukin-6, C-reactive protein, ALT, and AST levels. In addition, SSO treatment significantly improved insulin resistance, decreased fasting blood glucose levels, and improved glucose tolerance in HFD-fed mice.Conclusion: SSO is effective in the treatment of obesity and metabolic syndrome induced by a HFD in mice. SSO reduces intestinal fatty acid absorption by reducing the inhibition of intestinal CD36 expression, followed by decreased TG and FFA levels, which attenuates HFD-induced fatty liver.

Despite dehazing algorithms based on convolutional neural networks have made tremendous progress in synthetic uniform hazy datasets,they still perform poorly on real nonhomogeneous hazy images.In order to achieve fast and effective nonhomogeneous image dehazing,we propose a multi-patch and multi-scale hierarchical aggregation network (MPSHAN),which fuses multi-patch local information and multi-scale global information.Secondly,we propose a hierarchical fusion module (HFM),which not only decouples residual fusion to achieve richer non-linear feature expression,but also improves the feature fusion qua-lity at key locations through the channel attention mechanism.At the same time,dilated convolution is used on hierarchies to obtain multi-scale information,which enhances feature maps to optimize the fusion effect.In addition,in the loss function,we add frequency domain loss to restore better edge quality.The experimental results show that the proposed algorithm has good robustness on nonhomogeneous hazy images,and the average processing time of 1 200×1 600 high-resolution images is only 0.044 s.Compared with other dehazing algorithms,it achieves a better balance between image dehazing effect and running time.

This essay explores the concept of activity-based carbon neutrality as a critical component in achieving carbon emission reduction targets. With the Chinese government’s commitment to carbon sequestration by 2030 and carbon neutrality by 2060. activity-based carbon neutrality has gamed prominence as a hot topic in environmental discussions. The essay emphasizes the significance of activity-based carbon neutrality in promoting public awareness and participation in carbon reduction efforts. It highlights the existing research gap in this field and stresses the need for exploring methodologies to achieve activity-based carbon neutrality. The essay outlines the accounting standards for activity-based carbon neutrality, focusing on large-scale events and offering practical examples of carbon emission reduction measures during the preparation, execution, and conclusion phases of activities. Additionally, it introduces carbon offsetting methods such as carbon quotas and carbon credits. The article also presents a specific case study of the “Six-Five Environment Day National Event” held in Liaoning Province, which successfully achieved carbon neutrality through various initiatives. Overall, the essay encourages further investigation into activity-based carbon neutrality to enhance overall carbon reduction efforts.

The combustion characteristics of ammonia/hydrogen premixed laminar flow and the effect of hydrogen on the combustion performance of ammonia fuel were studied. First, the corresponding model of ammonia/ hydrogen premixed laminar combustion is established by using GRI3.0 mechanism, Konnov mechanism, Mei mechanism, Okafor mechanism, and Otomo mechanism respectively. Second, the simulation results are compared with the experimental results. It is found that the Mei mechanism and Okafor mechanism are more suitable for ammonia/ hydrogen premixed laminar combustion. On this basis, the effects of equivalent ratio, hydrogen ratio, and initial temperature on laminar flame velocity, maximum combustion temperature, and NO mole fraction were studied. The results show that the laminar flame velocity, the maximum combustion temperature, and the mole fraction of NO first increase and then decrease with the increase of the equivalent ratio, and the laminar flame velocity reaches the maximum when the equivalent ratio is 1.1. At the same time, with the increase of hydrogen ratio and initial temperature, the maximum combustion temperature increases first and then decreases. The mole fraction of NO increased with the increase of hydrogen ratio and initial temperature. The results show that mixing hydrogen in ammonia can improve the combustion characteristics of ammonia.

To explore the strength change law and solidification mechanism of cement solidified heavy metal lead and chromium contaminated soil, ordinary Portland cement (OPC) and magnesium phosphate cement (MPC) were used for solidification/stabilization treatment. Through the unconfined compressive strength (UCS) test, scanning electron microscopy (SEM) and the leaching toxicity test, the microscopic characteristics of the cement type, the cement content, the ion type, the ion concentration, and the age and their influence law on the strength characteristics of heavy metal contaminated soil were obtained. The UCS test shows that the compressive strength increases with the cement content and age. When OPC and MPC were used to solidify lead and chromium heavy metal contaminated soil, the compressive strength of OPC was greater than that of MPC, and when the curing age was 28 days, 20% of OPC and MPC satisfied the landfill requirements. The leaching toxicity test showed that after the solidification/stabilization of heavy metal lead and chromium contaminated soil by OPC and MPC, the leaching content of lead ions in the leaching solution conforms to the national limit. For chromium contaminated soil, the concentration was less than or equal to 5000mg/kg, which conform to the limit standard. When the concentration was 10000mg/kg, the content exceeded the limit. Therefore, heavy metal lead contaminated soil is more easily stabilized than chromium contaminated soil. Microscopic tests show that OPC solidified heavy metal contaminated soil is solidified/stabilized by heavy metal ions through hydration products, namely, ettringite and amorphous cementing materials. MPC is obtained by the hydration reaction of magnesium oxide and ammonium dihydrogen phosphate to form struvite, and heavy metal ions are encapsulated in the lattice to achieve solidification/stabilization.

The small hydropower stations have reached a new balance after years of operation. The ecological balance of the river would been broken by the dam removal and the reservoir area above the dam would disappear. Consequently, a series of changes occurred in water depth, velocity of flow, the concentration of organic and inorganic nutrients, distribution and form of organic matter, aquatic organism, etc. It is unclear what would happen for the hydrodynamic conditions, sediment characteristics and aquatic organism community structure of the reservoir area and the lower reaches after the dam removal. Therefore, it is urgent to study the impact of dam removal on the transportation and redistribution of organic debris and the potential ecological effects with benthos as indicators in the river where the small hydropower station is located.

In the new era of China’s development for higher vocational college students have new quality development requirements, especially in terms of ideological quality, college students in the new era are required to have patriotic feelings and practical action, correct overall view of world development, and conscious view of global ecological environment protection. At a higher vocational college in Anhui province for two months investigation and study of the topic, through the data analysis found that some problems existing in the college students in the new era of ideological quality development: some college students of level of concern for domestic event and domestic security is not high, and the patriotic practical actions need to be further improved; Some of them have a shallow understanding of the international situation, and the ideological quality of a few college students does not meet the requirements of The times; College students have nearly for ecological environment protection is the lack of action. It puts forward the corresponding countermeasures and Suggestions: Guiding the college students pay attention to the national development, and to the right side of thinking, actively safeguard national interests; Guiding the youth to learn to distinguish right from wrong, and form a correct global vision and the soul of thought; Through the education of higher vocational college students to learn ecological security concept of national overall security, enhance their awareness of environmental protection, ecological security and the ability to consciously maintain ecological security.

To solve the problem of traditional pollution detection methods on the prevention and control of pollution flashover of transmission line insulators,the non-contact and high-resolution hyperspectral technology is used to study the on-line pollution detection technology. At the same time,an insulator pollution level identification technology based on wavelet packet energy spectrum feature optimization is proposed to effectively extract the spectral features reflecting the pollution degree and weaken the influence of redundancy and interference information. Firstly,the spectral images of insulator samples with different pollution levels are segmented to extract the spectral mean curve of pixels in uniform pollution area. Secondly,the difference of light intensity uniformity and environmental noise of different images are preprocessed,and the differentiability among different pollution levels is improved by logarithmic transformation. Thirdly,the feature extraction of wavelet packet energy spectrum is performed on the preprocessed spectral lines. Finally,a pollution level recognition model based on the proposed features and support vector machines (SVM) is established. The experimental results show that the SVM pollution level recognition model based on wavelet energy spectrum features achieves 99.8%,and it has higher recognition accuracy than full band data or principal component analysis (PCA) feature data does.

Cutis Laxa is a rare connective tissue disease featuring inelastic and saggy skin. It is thought that plastic surgery might be the most effective treatment, while the previous pieces of literature on the surgical treatment for Cutis Laxa complained of the recurrence. We report a patient of Congenital Cutis Laxa who has received systematic and sequential treatment based on plastic surgery. The patient is content with the effect of treatment, and there are no signs of recurrence after 5 months. By referring to relevant pieces of literature, we evaluate the clinical manifestations and diagnosis of the disease. A multi-step, systematic, and sequential treatment is recommended for the treatment of Congenital Cutis Laxa.

Maintenance of autonomic homeostasis is continuously calibrated by sensory fibers of the vagus nerve and sympathetic chain that convey compound action potentials (CAPs) to the central nervous system. Lipopolysaccharide (LPS) intravenous challenge reliably elicits a robust inflammatory response that can resemble systemic inflammation and acute endotoxemia. Here, we administered LPS intravenously in nine healthy subjects while recording ventral cervical magnetoneurography (vcMNG)-derived CAPs at the rostral Right Nodose Ganglion (RNG) and the caudal Right Carotid Artery (RCA) with optically pumped magnetometers (OPM). We observed vcMNG RNG and RCA neural firing rates that tracked changes in TNF-α levels in the systemic circulation. Further, endotype subgroups based on high and low IL-6 responders segregate RNG CAP frequency (at 30-120 min) and based on high and low IL-10 response discriminate RCA CAP frequency (at 0-30 min). These vcMNG tools may enhance understanding and management of the neuroimmune axis that can guide personalized treatment based on an individuals distinct endophenotype.

Colorectal cancer (CRC) is one of the main alimentary tract system malignancies affecting people worldwide. Adenomatous polyps are precursors of CRC, and therefore, preventing the development of these lesions may also prevent subsequent malignancy. However, the adenoma detection rate (ADR), a measure of the ability of a colonoscopist to identify and remove precancerous colorectal polyps, varies significantly among endoscopists. Here, we attempt to use a convolutional neural network (CNN) to generate a unique computer-aided diagnosis (CAD) system by exploring in detail the multiple-scale performance of deep neural networks. We applied this system to 3,375 hand-labeled images from the screening colonoscopies of 1,197 patients; of whom, 3,045 were assigned to the training dataset and 330 to the testing dataset. The images were diagnosed simply as either an adenomatous or non-adenomatous polyp. When applied to the testing dataset, our CNN-CAD system achieved a mean average precision of 89.5%. We conclude that the proposed framework could increase the ADR and decrease the incidence of interval CRCs, although further validation through large multicenter trials is required.

Objective To investigate the expression of substance P (SP) and its receptor, neurokinin-1 receptor (NK-1R), in nasopharyngeal carcinoma (NPC) tissues and their correlation with the clinicopathological parameters of the patients. Methods Real-time fluorescence quantitative PCR (RT-qPCR) and Western blotting were used to detect the expression of SP and NK-1R mRNAs in the specimen of tumor tissues of NPC patients and normal tissues from patients with deviated nasal septum, and their protein expression and distribution in the tissues were observed using immunohistochemistry. Chi-square test was used to analyze the correlation of the expression of SP and NK-1R with the clinicopathological characteristics of the patients. CCK8 and Transwell assays were used to evaluate the effects of SP on the proliferation and invasion of HNE1 cells. Results The mRNA levels of SP and NK-1R were significantly increased in NPC tissues (7.96±1.75 and 7.12±1.54, respectively) as compared with the normal tissues (1.05±0.34, 1.04±0.2; P < 0.01); the protein expression of SP and NK-1R were also significantly upregulated in the NPC tissues (1.18±0.27 and 0.81±0.17, respectively) in comparison with the normal tissues (0.56±0.06, 0.48±0.05; P < 0.01). The positive expression rate of SP and NK-1R in the NPC tissues was 64% and 68%, respectively, significantly higher than the rates in normal tissues (11% and 22%, respectively; P < 0.01). The positive expression rates of SP and NK-1R were significantly higher in stage Ⅲ and stage Ⅳ NPC cases than in stage Ⅰ-Ⅱ cases (P < 0.05). Exogenous SP significantly enhanced the proliferation (P < 0.05) and invasion (P < 0.01) of HNE1 cells in vitro. Conclusion SP and NK-1R are over-expressed in NPC tissues, and their expression levels are correlated with the TNM stages of NPC, suggesting their value as potential new targets for diagnosis and treatment of NPC.

At present, most of the research on aero-engine gas path analysis is based on the steady-state process of the engine, but the steady-state data is usually difficult to obtain, and some fault features can only be displayed in the transient working state, so the transition state data which is relatively easy to obtain can be used to evaluate the health state of the engine more comprehensively. In the case of a small number of gas path sensors, a large number of health parameters are analyzed by using the sequential operating points method, which can increase the available information and reduce the systematic error of parameter estimation introduced by the average effect of the multiple working points method. An indirect recursive Newton Raphson method is proposed to enhance the non-dominated sorting differential evolution algorithm to solve the problem of computational convergence in the estimation of large deviation performance degradation health parameters of engines. The results show that this method can effectively and accurately estimate a large number of health parameters in a large deviation range by using engine transition state data under the condition of limited number of gas path sensors.

In the field of gas isotope separation, it is necessary to accurately measure the gas flow in the system. To meet the design requirements, the accuracy of 0.1 mg/s even needs to be achieved at some key positions. In order to control the flow accurately, the principle of “sound velocity orifice plate” in gas hydrodynamics has been widely used in the field of gas isotope separation. Based on the physical principle of sound velocity orifice plate, this paper introduces several commonly used orifice calibration methods, and sorts out the basic application direction, so as to facilitate the majority of scientific researchers to use directly in the process of experimental research and engineering design, etc.

In the process of isotope separation in cascade, some separation working fluids will have chemical reactions in the cascade, and a small amount of solid materials will be continuously produced and deposited in the separation equipment. With the increase of sediment, the separation performance of separation equipment will be gradually affected, and then the production and operation of cascade will be affected. Therefore, the sediment needs to be cleaned regularly. In this paper, a numerical method is proposed to calculate the distribution of different gaseous substances in the cascade. On the premise that the cleaning parameters of a single machine are known, the linear iterative algorithm is used to describe the distribution of various gaseous substances in the cascade based on the mass conservation between cascade stages, and the calculation convergence is achieved through the total mass conservation. The results of the numerical example show that the algorithm can converge stably under different cascade regimes.

Based on a semirigid tricarboxylate ligand 5-((4-carboxyphenoxy)methyl)benzene-1,3-dioic acid (H3L), a new Pb(II)-based coordination polymer formulated as [Pb(HL)(H2O)](H2O) (1) was synthesized under solvothermal conditions and characterized by single-crystal X-ray structural analysis, power X-ray diffraction, and elemental analysis. Compound 1 is a two-dimensional layered structure formed by the connection of the one-dimensional Pb(II)-based secondary building unit chains with the partly deprotonated HL ligands, which are further extended into three-dimensional supermolecular structures through the H-bonds. Furthermore, the size of the as-prepared 1 could be downsized into the nano region through a simple ultrasonic method. Finally, the antilung cancer activities of 1 and the nanosized 1 have been probed via the MTT assay against three human lung cancer cell lines (A549, H1299, and PC9).

In view of problems of dispersive design data and difficult knowledge sharing existed in current shearer design, an innovation design service platform of shearer was developed. The platform utilizes key technologies such as dedicated web crawler based on Python, 3D model web page display based on WebGL and parametric CAD/CAE integrated design based on component technology to provide functions of specific innovation design information capture, 3D model web page display of shearer components, remote parametric CAD modeling and remote parametric CAE analysis for designers. The platform provides a lot of innovative knowledge and innovative resource services, which helps to break thinking pattern of shearer designers and can effectively improve innovation design ability of shearer designers and shorten design period of shearer.

The present study deals with a microwave-assisted oxidation roasting oxide–sulphide zinc ore technology of with addition of manganese dioxide. Effects of roasting parameters such as MnO2 addition level, roasting temperature, and holding time are studied by using the Central Composite Design (CCD). Meanwhile, zinc calcines are characterized by phase compositions analyses(XRD), structure characteristics of minerals (FT-IR), micro-area chemical analyses (SEM-EDAX) and elemental valence bonding analyses (XPS), which prove to be in accordance with the CCD results. The optimum roasting conditions are decided as MnO2 addition level being 85.14 %, roasting temperature 680 °C, and holding time 41 mins, and oxidation degree of zinc can reach 88.22 %. Besides, when MnO2 addition level reaches a certain value, zinc will aggregate in a form of ZnMn2O4, one battery material.

In view of problems that existing knowledge expression methods are difficult to fully and effectively express innovative design knowledge of shearer, and knowledge expression of existing special knowledge base is not comprehensive enough and its retrieval efficiency is not high, in order to realize reuse of innovative design knowledge and experience of shearer, inspire ability of knowledge analogy transfer by designers, a multi-level and multi-granularity knowledge innovative design expression method of shearer was proposed. Six attributes are extracted including parameter, structure, function, principle, effect and domain. The attributes are described by knowledge with different abstract granularity, each granularity corresponds to abstraction levels of concept layer, semantic relationship layer and instance layer. Knowledge items are generated through feature attribute description, and multi-level and multi-granularity innovative design knowledge base of shearer is constructed. Through ontology reasoning and semantic extension, knowledge of different levels and different granularities is retrieved from local knowledge base and Internet resources, thus realizes multi-level and multi-granularity expression of innovative design knowledge of the shearer. The feasibility of the method was verified by improved structure design of shearer drum.

Demand for germanium (Ge) is rapidly growing in recent years in various fields including semiconductors, aerospace, and solar cells. However, the Ge resources are very limited in the world. Hence, in this work, microwave-assisted leaching and conventional leaching methods are employed for the leaching of Ge from the Ge-rich lignite ash (GA). The effects of leaching temperature, leaching time, initial acid concentration, oxidizing agent amount, and stirring speed on leaching of Ge were investigated and microwave-assisted and conventional methods of leaching were compared. Here, HCl solution is used as a leaching agent, and MnO2 is used as an oxidizing agent. From the results, the leaching rate of Ge was found to be 89.49% in the microwave-assisted method, and 83.62% in the conventional leaching method. The optimal conditions for microwave-assisted method include a leaching temperature of 65°C, a leaching time of 90 min, an oxidizing agent amount of 10 g/l, an initial acid concentration of 10 mol/l, and a stirring speed of 250 rpm. The leaching rate of Ge significantly improved in the microwave-assisted method as compared to the conventional method. Therefore, the microwave-assisted method is a suitable method for the leaching of Ge from the GA and is a novel way for the efficient utilization of Ge concentrate.