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Objective： A surface evaporation concentration device were designed to concentrate thermosensitive feed liquid at low temperature under normal pressure with low energy consumption. Methods： Based on an introduction to the working principle of the device, the basic equations of the device were given. The changes of volumetric evaporation flux and energy saving ratio with flow rate of the feed liquid, feed liquid temperature, sweeping gas flow rate, sweeping gas temperature were calculated and analyzed. Designed an experimental platform and obtained a set of optimal performance parameters through experiments. Results： The results showed that when the flow rate of the feed liquid was 0.02 kg/s, the device had the highest energy saving ratio and higher volumetric evaporation flux; When the temperature of the feed liquid increased from 30 ℃ to 50 ℃, the volumetric evaporation flux increased by 224.68%, but the energy saving ratio decreased by 12.42%; When the sweeping gas flow rate increased from 0.004 kg/s to 0.006 kg/s, the volumetric evaporation flux increased by 23.45%, but the energy saving ratio decreased by 7.74%; When the temperature of the sweeping gas increased from 10 ℃ to 30 ℃, the volumetric evaporation flux decreased by 22.92%, but the energy saving ratio increased by 37.49%; An experimental device was established to test orange juice with a sugar content of 15 °Brix, the results showed that when the feed liquid temperature was 38 ℃ and the sweeping gas temperature was 26 ℃, the volumetric evaporation flux of the device could reach 219 kg/（m3·h）, and the energy saving ratio could reach 3.3.Conclusion： The heat pump assisted random filler surface evaporation device has the characteristics of low temperature concentration under atmospheric pressure and low energy consumption when concentrating thermosensitive feed liquid．

Long-range multi-purpose cluster munitions with reconnaissance, identification, strike and evaluation functions are widely used, and a large number of unexploded submunitions will be generated on the surface, which will greatly hinder the battlefield maneuver, deployment and depth attack. Due to its special visual characteristics, surface unexploded submunitions use imaging technology and deep learning technology for long-distance, large-area, non-contact rapid and accurate detection and recognition. This paper introduces the common methods of unexploded submunition detection and their advantages and disadvantages, summarizes the imaging characteristics of unexploded submunitions under different imaging technology conditions and their identification and positioning methods, analyzes the signifi-cant advantages of deep learning in the field of unexploded submunition detection and recognition. Then, a UAV-borne rapid detection, identification and positioning method based on deep learning for surface unexploded submunitions is proposed.

【Objective】This study aims to discover members of the Al-activated malate transporter ALMT gene family that may be involved in the growth and development of litchi and to investigate their biological functions.【Method】The physicochemical properties of proteins, subcellular localisation predictions, phylogeny, gene structure, conservative motifs, chromosomal positioning, promoter cis-acting elements, protein structure and expression patterns of litchi ALMT gene family members were systematically analysed using bioinformatics methods, expression of the litchi LcALMTs was analysed by qPCR.【Result】The results showed that the litchi LcALMT gene family has 16 members with CDS lengths ranging from 118 to 803 bp and isoelectric points between 5.16 and 9.07. Subcellular localisation predictions showed that the LcALMTs were all localised to the plasma membrane, and the family was divided into five subclades based on a phylogenetic tree. The number of exons of the LcALMTs ranged from 3 to 10, and four LcALMT genes did not contain any non-coding regions. Chromosomal localisation analysis revealed that LcALMTs was localised on only six of the 15 chromosomes of litchi, and mainly on chromosome 13. Conservative motif analysis revealed that litchi ALMT family members contain both ALMT and ALMT superfamily structural domains. Among the cis-acting elements, light-responsive elements accounted for the largest proportion, followed by hormone-responsive elements. Expression pattern analysis revealed that the expression of Litchi LcALMTs was highly variable in different tissues, with LcALMT5 and LcALMT15 being expressed at high levels in all tissues, the qPCR results showed that the expression level of LcALMT5 was more consistent with the results of the transcriptome.【Conclusion】There are 16 members of the litchi ALMT Gene family, which has a conservative gene structure and protein domain, and there are differences in tissue expression.

With the continuous emergence of network and information security challenges, international trade frictions and other issues, the demand for localization, independence and controllability of products is becoming more and more intense. As a result, domestic hardware and software solutions will be gradually adopted to replace foreign solutions for the key control system in the field of rail transit. This paper briefly describes the architecture of the domestic traction and network control system for the standardized subway platform, and focuses on the selection of the hardware and software, such as CPUs, embedded operating systems and graphical development software. It also details the hardware scheme, software structure, and migration and adaptation process of the software and hardware for the traction and network control system, and makes a comparative analysis on the functions and performances of the domestic operating system and VxWorks. Through a series of software functional tests such as verification of traction/electric braking characteristics and networking, conclusions are drawn that the domestic traction and network control system features excellent performance parameters, stable and reliable operation, normal traction/electric braking characteristics, network delay of the system in microseconds, and jitter of the sub-microsecond level, which meet the requirements of the standardized subway platform, and therefore it can be used for 100% localization as an equivalent substitute.

Using Tianbao banana as the test material, one strain of Fusarium was isolated, purified and identified. Different concentrations (5, 10, 15, 20 mg/mL and 25 mg/mL) of camellia saponin were used to determine the inhibitory effect on Fusarium. The weight loss rate, hardness, soluble solids, titratable acid, respiratory strength and other main quality indicators of bananas treated with different concentrations of camellia saponin (15, 20, 25 mg/mL and 30 mg/mL) at a temperature of 16 ℃ and a relative humidity of 85% under constant temperature and humidity for 25 days were determined to study the effect of camellia saponin on bananas. The results showed that the antibacterial rate of camellia saponin against Fusarium continued to increase as the concentration increased. When the concentration of camellia saponin was 20 mg/mL, the antibacterial rate could reach 86.52%, but when the concentration increased again, the antibacterial rate did not increase significantly. On this basis, the MIC and MBC values of camellia saponin against Fusarium were determined to be 5 mg/mL and 10 mg/mL, respectively. Comprehensive quality indicators showed that the 20 mg/mL concentration of camellia saponin solution had the best preservation effect on post-harvest bananas. When stored for 20 days, compared with the control group (clear water group and positive control group), the weight loss rate was reduced by 48.04% and 51.67%, respectively. Compared with the control group (clear water group), soluble solids delayed the emergence of the peak value. Titratable acid increased by 56.09% and 23.07%, and respiratory intensity increased by 65.68% and 14.82%. On the 10th day of storage, the hardness increased by 13.76% compared with the positive control group. The results of the research are expected to provide certain theoretical and technical support for the preservation of bananas by camellia saponin.

Objective To explore the feasibility of establishing a computer-aided diagnostic model of multi-stained pathological images in patients with non-inflammatory aortic medial degeneration(MD). Methods In this study, pathological sections of aortic surgical specimens for non-inflammatory lesions from patients with thoracic aortic aneurysms and dissections were retrospectively collected at the Beijing Anzhen Hospital, Capital Medical University from July to December 2018. The lesions were scanned under ×400 magnification as whole slide images(WSI) and then annotated by two pathologists. The annotated WSI images were randomly split into training and test sets in a 6:1 ratio. SE-EmbraceNet was used to train the data to construct a multi-classification model for MD of multi-stained pathology images, including intralamellar mucoid extracellular matrix accumulation (MEMA-I), translamellar mucoid extracellular matrix accumulation (MEMA-T), elastic fiber fragmentation and/or loss(EFFL) and smooth muscle cell nuclei loss (SMCNL). The classification effect of the model was evaluated based on the test set data, and the results were expressed in terms of accuracy, sensitivity, precision, and the F1 value. Results Totally 530 pathological slides of non-inflammatory aortic lesion surgical specimens from patients with aortic aneurysm and dissection were included. Extracted 5265 sets of images, each containing 5 stained pathological images of the same lesion site: HE staining, special staining (elastic fiber/VanGieson, Masson, Alcian blue/periodic acid Schiff) and smooth muscle actin staining. There were 4513 sets of training images, including 987 SMCNL, 2013 EFFL, 1337 MEMA-I, and 176 MEMA-T; and 752 test images including 166 SMCNL, 335 EFFL, 222 MEMA-I, and 29 MEMA-T. The overall performance of the model in the test set showed good results, with an accuracy of 96.54%(726/752). The model had the best classification performance for EFFL, with accuracy, sensitivity, precision, and F1 value all ≥98.51%. The model also had a great classification ability for SMCNL, with all evaluated indexes≥97.59%. Conclusion The multi-stained pathology image-based MD classification model constructed in this study has high classification accuracy and good generalization ability, which has the potential to be applied to assist in the diagnosis of the non-inflammatory aortic lesion.

Objective: This study aimed to find out the best parameters of moistening leaves in redrying. Methods: Based on the BO1 module of upper leaves in Ganzhou, the effects of hot air temperature, drum speed, water addition and steam valve opening on aroma components of primary and secondary leaves were investigated, and the optimum parameters of leaf moistening process were screened by comprehensive balance method based on the style of sweet and coke in Ganzhou. Results: The content of aroma components increased after one-time leaf wetting and decreased after two-time leaf wetting, but slightly increased, compared with that before leaf wetting. The hot air temperature in the first moistening leaf had a significant effect on the contents of solanone and furfuryl alcohol, while the hot air temperature in the second moistening leaf had a significant effect on the content of phenylacetaldehyde. Conclusion: The optimum process conditions of twice moistening leaves during tobacco redrying were hot air temperature 135 ℃, roller speed 10 r/min and water addition 3.5 kg/100 kg. Hot air temperature 145 ℃, roller speed 9 r/min, steam valve opening 50%.

Ethernet circuit based on IEEE 802.3 has been widely used in the field of rail transit. Open systems interconnection (OSI) model divides Ethernet into seven layers, of which the physical layer (PHY) belongs to the first layer, which is mainly responsible for converting Ethernet signals into specific electrical signals and transmitting them to Ethernet cables, and plays a very important role in the interconnection between different network interfaces. In order to improve the reliability of train network system based on Ethernet and improve the quality of train communication, this paper designs and studies the physical layer circuit of train Ethernet, including PHY chip filtering and impedance matching, the application of different xMII (medium independent interface) interfaces, EMC protection, factors in the consistency test of network interface and PCB layout and wiring rules, and designs an Ethernet physical layer circuit according to the research results. The application results show that the designed circuit is suitable for the field of train Ethernet communication, and has strong EMC protection ability and high reliability.

【Objective】Acid invertase (SAI) plays an important role in litchi sugar metabolism. The litchi LcSAI promoter is cloned and analyzed in order to provide a theoretical basis for the research on the function of LcSAI in regulating litchi sugar metabolism.【Method】With the pulp of Feizixiao litchi as test material, according to the litchi genome sequence information, the 1 500 bp promoter sequence upstream of LcSAI gene was cloned. At the same time, the transcription start sites, cis-acting elements and CpG islands in the promoter sequences were predicted and analyzed by bioinformatics tools.【Result】A 1 514 bp LcSAI promoter sequence was cloned. In addition to a large number of promoter core elements such as TATA-box and enhancer element CAAT-box, promoter cis-acting elements also had light-responsive cis-elements, hormone response elements, anaerobic inducible response elements, and MYB binding sites, MYC binding sites and some cis-acting elements of unknown function. There may be three core promoter regions in the LcSAI promoter sequence. TheLcSAI promoter region did not predict CpG islands that met the defined conditions.【Conclusion】The LcSAI gene promoter is related to adversity stress. It is predicted that LcSAI plays an important role in the physiological process of litchi resisting adversity stress.

Based on the microseismic monitoring data, the time-frequency characteristics of the rockburst events induced by mining in 13200 working face of Gengcun Coal Mine of Henan Energy and Chemical Industry Group Co., Ltd. and microseismic events before the rockburst events are analyzed by using fast fourier transform, wavelet packet transform and Hilbert-Huang transform. The results show that the main frequency of rockburst is within 10 Hz, and the main frequency of the microseismic event waveform before rockburst is within 100 Hz. The highest energy distribution frequency band is within 5 when rockburst occurs. The highest energy distribution frequency band of the previous three microseismic events waveforms is about 10. The instantaneous energy of the six microseismic event waveforms before rockburst is not high, indicating that there is a silent period of energy before rockburst occurs. Based on the time-frequency characteristics of rockburst events and microseismic events before rockburst, the precursor characteristics of rockburst are obtained. The main frequency of the microseismic event waveform is within 100 Hz, the highest energy distribution frequency band is within 10, and the instantaneous energy is less than 1-5.

In view of the problems of constant speed and single carbon emission calculation method in the distribution model of fresh agricultural products in the transportation link of agricultural supply chain, combined with the time-varying characteristics of road network and the new multi vehicle carbon emission calculation method, this study put forward the distribution route optimization model of fresh agricultural products with four optimization objectives, which were the distribution distance, multi vehicle carbon emission, goods loss and vehicle fixed cost. In this model, the calculation of fuel consumption and carbon emission in the model would be affected by many factors, among which the load is the most important factor: Firstly, the average fuel consumption per 100 km of different trucks was calculated, then the CO2 emission factors of various trucks were calculated according to the carbon balance principle, and finally the average value of the results of each truck was taken as the carbon emission factor of the vehicle. According to those characteristics of the model, an improved double strategies co-evolutionary ant colony system (DC-ACS) was proposed. In this study, the main method was used to transform the problem into a solvable single objective problem. Then, the ant colony algorithm combined the coevolution mechanism, adaptive pheromone update strategy and local search mechanism were used to improve the solution effect of the algorithm. Finally, an appropriate fitness calculation method and stagnation avoidance strategy were designed to enhance the ability of the algorithm to jump out of local optimization. The C105 example of Solomon dataset was solved by using the improved ant colony algorithm. The optimal solutions on the four optimization objectives were 937.94 km, 4961.48 CNY, 4081.78 CNY and 7500.87 CNY respectively, which proved the effectiveness of the model proposed in this study. Based on the effectiveness of the model, the experimental results showed that the total distribution cost of the improved ant colony algorithm reduced by more than 14% on average compared with the basic ant colony algorithm on the four optimization objectives, which proved that the improved ant colony algorithm had more advantages. The improved ant colony algorithm was used to solve large-scale examples with different distributions: centralized, random and mixed. The optimal total costs were 19939.53 CNY, 24095 CNY and 24397.58 CNY, respectively. To sum up, the proposed model and algorithm could provide a good reference for the urban distribution path decision-making of cold chain logistics enterprises, a new idea to improve the distribution path optimization model and optimization method of smart agricultural supply chain, and a reference for enterprises to further expand their scale.

The problem existing in the transformation of deep learning algorithm to engineering application is analyzed. Combining with the characteristics and development trends of army intelligent ammunition, the missile-borne image processing heterogeneous accelerate system for deep learning is put forward based on the research of compression, quantitative and hardware heterogeneous acceleration, realizing heterogeneous hardware design. The DNNDK is used to compress and quantify the Yolo v3 model. The weight and parameter compression rate are more than 90% and 80%, realizing the lightweight design of Yolo v3. Based on the DPU hardware acceleration architecture, the algorithm is transplanted to the missile-borne embedded platform, and its power consumption and detection efficiency meet the requirements of missile-borne image processing.

Colorectal cancer (CRC) is one of the most common malignant tumors in the world, which is also the main death cause of cancer patients. Surgery, radiotherapy and chemotherapy can improve the prognosis of CRC patients. However, late recurrence and distant metastatic diseases cannot be cured, which will result in poor prognosis. With the cross penetration of molecular biology, oncology and immunology, the immunotherapy has made a huge breakthrough and has become an important means of tumor therapy. This article summarizes the immunotherapy of metastatic CRC at home and abroad in recent years.

In order to solve the problems that orders are widely distributed, scheduling of distribution vehicle needs a lot of manpower,and high cost of chicken distribution in large-scale poultry enterprise, in this research, combined with the idea of solving vehicle routing optimization problem, a chicken distribution vehicle scheduling optimization model based on order location clustering was proposed. By introducing the K-means clustering algorithm, a distribution unit division method based on order location was implemented, an automated order location clustering process based on the elbow rule and contour coefficient method to realize the autonomous division of order distribution units was designed. On the basis of the divided groups of orders, the optimal delivery cost was taken as the objective function to establish a chicken delivery vehicle scheduling optimization model, and the model was solved with an improved genetic algorithm.The actual order data of a poultry company in Beijing was used to compare the results of the overall scheduling optimization in the case of orders without clustering and the scheduling optimization in the case of with clustering grouping. The results showed that the model in the case of orders with clustering could reduce the average daily mileage of delivery vehicles by 69% compared with orders without clustering, it could be seen that the optimization of order grouping with clustering algorithm was more suitable for vehicle scheduling scenarios with a large actual order position span and a large number of orders. Based on the above research, a vehicle scheduling optimization service system was developed, functions such as automatic order clustering, delivery vehicle scheduling optimization were realized, and model service application programming interface was customized.The practical application results of the model showed that, the average total mileage per day decreased by 5.04% compared with manual routing, the manual routing time took 20 to 30 minutes per day, and the average time for the model to complete the routing was 14.49 s. The goal of providing intelligent delivery vehicle scheduling optimization services for poultry industry enterprises has been achieved, which could effectively improve the operation efficiency and reduce the distribution cost of the poultry enterprise.

Ultraviolet-visible and nuclear magnetic resonance (NMR) spectroscopy was used to investigate the effects of pH, solvent and temperature on the tautomeric equilibrium of selaginellins from Selaginella. The results demonstrated that the tautomerism of selaginellins could be catalyzed by acid, base and protic solvent. Variable-temperature 1H NMR experiments demonstrated that the tautomerism was interrupted when the temperature fell below 233 K.

The factors,which influence the stability of thin-wall perforated steel components are complex. Take the columns as an example,in the existing research,much attention has been paid to the continuous section,but little paper on noncontinuous one. According to the characteristics of the non continuous cross section,based on performance testing and finite element analysis of columns,with the method of BP neural network intelligent stability prediction,the stability prediction model of the columns is established. The predict results are compared with the test data,and the error is less than 2%,which is more accurate than the finite element analysis results. It is very promising that the intelligent prediction method has applied in the structure engineering.

Based on the application of the honeycomb in the square guide rail,analyzed the tandem honeycomb deformation stability by experiments. Found tandem honeycomb is prone to instability in the impact process for the effect of uneven strength of simple honeycomb and impact load deflection. Analysis shows that the plate, with low intensity or its sectional dimension is smaller than guide rail section, is difficult to prevent honeycomb instability. To improve the effect of connection on keep tandem honeycomb deformation stability, studied the relationship among plate sectional dimension, guide rail sectional dimension and plate deflection degree from the theoretical level: when the guide rail sectional dimension unchanged, the longer the length of connection plate is, the smaller the deflection angle of plate is, the smaller the friction between plate and guide rail is, the better the guiding function of connection plate is. Based on the conclusion, designed a new guiding plate, it is not only improves tandem honeycomb deformation stability, but also solves the honeycomb peeling.

The highly ordered porous anodic alumina was prepared by anodic oxidation technology, after being treated by AC phosphoric pore broadening, the Cu-Ni nano composite particles were deposited into anodic alumina pores by AC frequency with 50Hz in different voltages, different time and different temperatures. The spectra result shows that the coating prepared under the conditions of voltage is 12V, time is 600s, temperature is 25℃ has good solar absorption performance, the absorptivity is 0.91, emissivity is 0.18, quality factor is 4.9. The SEM and XRD analysis show that CuAl2O4/Cu-Ni composite nanorods were deposited on the surface of the composite oxide coating. After heat treatment at 600℃, the solar absorption and infrared emission of target coating have a small fluctuation and the thermal stability of the coating system is greatly improved. The existing of CuAl2O4 limits the diffusion of metal particles under high temperature environment at the interface, which prevents the Cu/Ni from being oxidized.

Objective To study and analyze the effect of applying the knowledge, attitude/belief, and practice (KAP) nursing mode in caring for patients who receive fixed orthodontic treatment. Methods A total of 112 patients who re⁃ ceived orthodontic treatment were selected as study subjects. They were randomly divided into an observation group and a control group, with 56 patients in each group. Patients in the control group were treated with conventional oral care, while those in the observation group were treated with the KAP nursing mode. The patients􀆳 awareness of the disease, treatment compliance, and orthodontic complications were compared between the two groups. Results After treatment with the KAP nursing mode, the disease cognition score was significantly higher in the observation group than in the control group (P < 0.05). Patient compliance was better in the observation group than in the control group throughout the treatment. Pa⁃ tients in the observation group were more able to return to the hospital on time than those in the control group. The orth⁃ odontic plaque index (OPI) of patients in the observation group decreased during the treatment. The OPI of patients in the observation group was significantly lower than that of patients in the control group at 6 months (t＝2.344) and 12 months (t＝3.721) after the start of the treatment (P < 0.05), and the incidence of orthodontic complications in the observation group was 7.1% (4/56), significantly lower than that in the control group (26.9% (15/56); c2＝9.728, P < 0.05). Conclu⁃ sion Application of the KAP nursing mode can effectively reduce the incidence of complications in patients with fixed orthodontics, improve the oral health of patients, and positively affect orthodontic treatment.

In view of problem that bad electromagnetic environment of coal mine underground causes phenomenon of false alarm and false power off of safety monitoring and control system, the paper analyzed kinds of underground electromagnetic interference sources and made electromagnetic interference test in areas of false alarm of safety monitoring and control system of a coal mine. The test result showed that on No.3213 working face of the mine, when parallel length of power cable and test cable in waist roadway and airway is about 150 m, interference peak-peak value of induced surge generated by starting pumps and drills is as high as 190 V, and the interference intensity is strong, which explained that strong signal interference sources produced by simultaneous starting of frequency converter and drill caused phenomenon of false alarm of gas sensor. According to the test result, it proposed corresponding anti-interference measures which solved problem of false alarm of gas sensor

In view of problems that current standard safety pins of mine car use manual operation when bolting and pulling and cannot realize automatic uncoupling, a new type of safety pin used in trip of mine car was designed. Structure, working principle, installation and characteristics of the safety pin were introduced, and design of automatic uncoupling and pulling system taking the safety pin as core was given. The actual application shows that the safety pin meets with actual application requirements of simple structure, reliable self-locking, easy to pull, low cost and less modification for structure of mine car.

In railway signaling design, the calculation of electricity consumption for railway signal equipment is very complicated. To simplify the process of electricity consumption design for railway signal equipment, this paper analyzes various calculation methods of signal load, and uses the VB6.0 programming software to compile the electricity consumption calculation software for railway signal equipment, reducing the difficulty of electricity consumption design for railway signal equipment and improving design efficiency. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the longer concentration time of juice will lead to more loss of beneficial components, a rapid concentration membrane distillation module based on sweeping gas membrane distillation was designed. The mathematical model was established to calculate and analyze the variation of concentration of the feed liquid flowing out of the membrane module and the double concentration time with the temperature of feed liquid, the inner diameter of membrane tube, the flow rate of sweeping gas (air) and the membrane pore diameter. The results show that the double concentration time of the feed liquid is 40 ~ 100 s under typical operating parameters. The relative influence coefficients of double concentration time with the temperature of feed liquid, the inner membrane tube diameter, the flow rate of air and the membrane pore diameter are 130.6%, 10.2%,9.8% and 5.9% respectively. Increasing the temperature of the feed liquid, reducing the inner diameter of membrane tube, increasing the flow rate of air and the membrane pore diameter are beneficial to reduce the double concentration time of the feed liquid. When the temperature of feed liquid is 60 t, concentration of the feed liquid flowing in the membrane module is 10%, concentration of the feed liquid flowing out the membrane module is 40%, the retention rates of vitamin C, total phenolic content and total carotenoid content in orange juice are 97.99%, 98.59% and 98.30%, respectively. The research can provide reference for the development of rapid concentration device for thermosensitive food liquid. [ABSTRACT FROM AUTHOR]

In this paper, 1 m³ climate chamber method and GC-MS were used to quantitatively analyze the content level changes of five organophosphorus flame retardants in pollution sources, and the average concentration of OPEs in the air was 110 ng/m3 based on calculation, in which tris-(2-chloroisopropyl) phosphate (TCPP) was the main pollutant. Moreover, the health risk assessment of one organophosphorus flame retardants in laminate flooring was evaluated, of which the non-carcinogenic risk and carcinogenic risk were at a low level. [ABSTRACT FROM AUTHOR]

A comprehensive review was conducted on the historical development, construction scheme, and training strategy of the machine learning potential. This novel technique approximates the potential energy surface of molecular system at the level of first-principle calculations and has been successfully applied in the molecular modelling of combustion and explosion for energetic materials, including nitramine compounds (RDX, CL-20, and ICM-102), oxidizers (AP) and high-energy particles (Al, B). In addition, the representative applications of machine learning potential on the combustion of hydrocarbon fuels were also introduced. Furthermore, the challenges and future development perspectives of machine learning potential in energetic materials were discussed. It is well demonstrated that machine learning potentials, particularly deep potential models, are highly accurate and efficient. The data-driven approach makes it feasible to empower the simulation of million atoms with a great accuracy as first-principle calculations. In the final remark, the key challenges for the further development of machine learning potentials are discussed; (1) sampling issue for a complex potential energy surface under extreme conditions; (2) accuracy problem in the training dataset. With 91 references. [ABSTRACT FROM AUTHOR]

PPG-5-CETETH-20 is a multifunctional raw material. It has a wide range of application in skin care and hair care products. The purpose of this study was to evaluate the performance of PPG-5-CETETH-20 in shampoos and conditioners. The results showed that, PPG-5-CETETH-20 could improve the combability, softness and smoothness of hair. In additional, it could improve foam stability and fine bubbles therein, without any influence on the transparency of the products. [ABSTRACT FROM AUTHOR]

Pedestrian object detection and tracking have attracted much attention in the computer vision field. An improved multi-pedestrian tracking model is proposed, which improves the basic framework of Deep SORT and integrates Mask R-CNN to realize the detection, tracking and pose estimation f pedestrian. The anchor boxes with the more suitable aspect ratio for pedestrian target are adopted, which replace the anchor boxes of RPN to speed up the model and improve performance without complex calculation. In addition, attention mechanism is introduced into the deep residual network, i. e., the lightweight SKNet is used to choose the best convolution kernel adaptively to improve the feature representation for target detection. The histogram of gradient feature combined with color information is adopted instead of the convolution feature, which improves appearance feature association matching in the Deep SORT model so as to track pedestrian targets effectively under occlusion. The impact of various improvements on the model are verified through ablation studies, and the proposed model is compared with the current mainstream model. Experimental results show that the improved models are effective, which improves MOTA of NSH by 6% on the MOT16 tracking data set. The test performance of our proposal on the public datasets is superior to that of the compared models. The proposed model can still rack pedestrian targets effectively when the background moves or pedestrian targets are occluded. [ABSTRACT FROM AUTHOR]

Stock price prediction has always been a focal topic in financial research and quantitative investment. Currently, most deep learning models for stock price prediction are based on batch learning settings, which require prior knowledge of the training dataset. These models are not scalable for real-time data stream prediction, and their performance decreases when the data distribution dynamically changes. To address the issue of poor prediction accuracy for non-stationary stock price data in existing research, this paper proposes an online stock price prediction model (Increformer) based on incremental learning and continuous attention mechanism. By leveraging continuous self-attention mechanism to capture the temporal dependencies among feature variables and employing continuous normalization mechanism to handle non-stationary data, the model enhances prediction accuracy through the incremental training strategy based on elastic weighting consolidation to acquire new knowledge from the data stream. Five public datasets are selected from the stock index and individual stock price sequences in the stock market for experiments. Experimental results demonstrate that Increformer effectively extracts temporal information and feature dimension correlation from the data, thus improving the prediction performance of stock prices. Additionally, ablation experiments are conducted to evaluate the effects and necessity of the continuous normalization mechanism, continuous attention mechanism, and incremental training strategy, thereby verifying the accuracy and generalizability of the proposed model. Increformer can effectively capture the trends and fluctuations of stock price series.

Fiber Bragg Grating (FBG) pressure sensor has the advantages of underwater passive, corrosion resistance, light weight, low cost and anti-electromagnetic interference, which has been widely used. This paper first briefly introduces the basic principle of FBG pressure sensing. It then summarizes the development status of FBG writing technology, pressure sensing and sensitizing technology, and temperature compensation technology. Next, it summarizes the application progress of FBG pressure sensor in the fields of ocean depth, lake level measurement, oil and gas pipeline pressure measurement, and rock and soil pressure monitoring in recent years. Finally, the FBG pressure sensing technology is prospected.

Currently, the situation of global food security is complicated and severe, and diet-derived chronic diseases are sweeping the world. Meanwhile, the views of “health-centered”, “nutritional diversity”, and “Food is Medicine” have become the general consensus. Using agricultural biodiversity to explore a new generation of crops that are both high-yield and nutritious has become an international trend, and Huangjing (i. e., Polygonati rhizoma) has notable characteristics and advantages. To fully unleash the potentials of Huangjing, this study systematically summarizes its history as both food and medicine, material basis of nutrition and efficacy as forest grain, as well as resource distribution and food production potentials. Huangjing does not contain starch, but rich in nutrients such as fructans with a complex structure, easy degradation, and energy, which is vital for serving life and health. Huangjing is suitable for in-forest planting or intercropping with maize and does not take up the farmland or compete for forest land. It has enormous production capacities and is crucial for ensuring food security. Huangjing is suitable for planting and processing in thousands of households, with good economic benefits, and is of great significance for achieving common prosperity. However, the Huangjing industry of China currently faces multiple challenges in terms of basic research, application technologies, as well as cultural heritage and policy support. Therefore, it is necessary to strengthen research on the basic sciences and application technologies of the industry. Meanwhile, we suggest to incorporate Huangjing production into the policy and funding guarantee system for woody grain and oil, integrate Huangjing application into the healthcare and population health planning, and regard the Huangjing industry as an important carrier for rural revitalization and common prosperity, thus to establish a complete innovation and application system covering the entire industrial chain.

Object detection as a hot field in computer vision, usually requires a large number of labeled images for model training, which will cost a lot of manpower and material resources. At the same time, due to the inherent longtailed distribution of data in the real world, the number of samples of most objects is relatively small, such as many uncommon diseases, etc., and it is difficult to obtain a large number of labeled images. In this regard, few-shot object detection only needs to provide a small amount of annotation information to detect objects of interest. This paper makes a detailed review of few- shot object detection methods. Firstly, the development of general target detection and its existing problems are reviewed, the concept of few- shot object detection is introduced, and other tasks related to few-shot object detection are differentiated and explained. Then, two classical paradigms based on transfer learning and meta-learning for existing few-shot object detection are introduced. According to the improvement strategies of different methods, few-shot object detection is divided into four types: attention mechanism, graph convolutional neural network, metric learning and data augmentation. The public datasets and evaluation metrics used in these methods are explained. Advantages, disadvantages, applicable scenarios of different methods, and performance on different datasets are compared and analyzed. Finally, the practical application fields and future research trends of few-shot object detection are discussed. [ABSTRACT FROM AUTHOR]

In order to reduce the energy consumption of the reaction, the magnesium alloy samples were immersed directly into three conversion solutions and reacted for 9 hours at 60 ℃ and pH=12.0 used the chelating agent-assisted method by adding three chelating agents, ethylenediaminetetraacetic acid tetrasodium (EDTA-4Na), sodium citrate (SC) and potassium sodium tartrate (PST) to aluminum nitrate (Al(NO3)3) solution, and Mg-Al layered double hydroxides (LDHs) films doped with different chelating agents can be prepared on the surface of magnesium alloys. The microstructure, phase composition, and corrosion resistance of each LDHs film were analyzed by SEM, XRD, FT-IR, etc. The results show that the chelating agent-assisted method can successfully prepare LDHs films with typical layered structure on the surface of magnesium alloys under normal pressure and 60 ℃ environment; and three kinds of Mg-Al LDHs films obtained can effectively improve the corrosion resistance of magnesium alloys. Then, by comparing the structural properties of three different LDHs film layers, it is found that the Mg-Al-PST LDHs film prepared by adding PST has the highest density and the largest thickness, reaching up to 1.4 μm. The improvement effect of three coatings on the corrosion resistance of magnesium alloys is as follows: Mg-Al-PST LDHs > Mg-Al-SC LDHs > Mg-Al-EDTA LDHs; The magnesium alloy covered with the Mg-Al-PST LDHs film compared to the blank magnesium alloy, the corrosion current density decreases by about two orders of magnitude, and the total corrosion resistance increases by about one order of magnitude. And based on the analysis of the structure and properties of the obtained LDHs films, it can be seen that the chelating agent-assisted method can prepare Mg-Al LDHs films with better corrosion resistance in-situ on the surface of magnesium alloys under the lower energy consumption condition. The reason may be that the carboxyl group in the chelating agent can accelerate the deposition of Al3+ on the magnesium substrate and promote the substitution of some Mg2+ in Mg (OH)2 by Al3+ to form LDHs.

To solve the problem of obstacle avoidance and path planning of tetrahedral tumbling robots in the triangular grid map, a path planning method based on the A* algorithm for tetrahedral tumbling robots is proposed. Based on the robot motion principle, it is analyzed that the motion trajectory of the robot is the triangular grid. The robot position and orientation representation method is proposed with the triangular grid map, and then the robot path planning method based on the A* algorithm is proposed. Matlab software is used to simulate and calculate the path planning process of the tetrahedral robot, which verifies the feasibility and correctness of the proposed method. It has laid an important foundation for robotic land exploration in deep space patrol.

This paper introduces the main active ingredients of plant extracts, expounds the application of plant extracts in aquatic products, puts forward the existing problems and future research direction, and provides a theoretical basis for the application and development of plant-derived active substances in aquatic products. [ABSTRACT FROM AUTHOR]

Crown width is a critical variable in reflecting the individual tree growth status and in developing forest growth and yield models. With the crown width base model as reference, we developed the crown width quantile regression models for different quantiles (0.50, 0.90, 0.93, 0.95, 0.96, 0.99) based on the data of 2763 Korean pines in 66 permanent plots from the 10-55 years old plantations in Dabiangou forest farm, mountainous areas of eastern Liaoning Province. We used the reparameterization method by introducing the single tree competition index (Rd) and used the dummy variable method by introducing stand density and forest layer variables. We then selected optimal quantile of maximum crown width in the stand by comparing our model developed routine to the traditional methods. The final crown width linear mixed effect quantile regression model was developed based on the optimal quantile at the plot level. The influence of each variable on crown width was analyzed to reflect the difference of crown width among individual trees in the stand. The models with different stand densities and forest layers had significant difference based on F statistical test: the Ra2 of the model increased by 0.0104, the root mean square error decreased by 0.0115 and the mean square error reduction was 7.4%, after the variables of forest layer, forest density, and competition being incorporated into the basic model. The developed quantile regression model performed better than that of the ordinary least square method in simulating the maximum crown width of a single tree in the forest stand. The selected best quantile of the quantile regression model for the upper forest layer and lower forest layer was 0.96 and 0.93, respectively. The linear quantile regression model with the mixed effect was superior to the traditional quantile regression model in Akaike, Bayesion and HQ information criterion and other evaluation parameters, the standard error for the parameters of estimates was significantly reduced, and the introduced mixed effect well explained differences among different plots. For the upper forest layer and lower forest layer, the maximum crown width decreased with increasing stand density, increased with increasing relative diameters. The influence of stand density on the crown width of the lower forest layer was greater than that of the upper forest layer. The crown width would increase first and then decrease with the increases of DBH when the stand density was large enough. The mixed effect of the quantile regression model developed here could significantly improve the fitting stability of the model. The sustainable development of Korean pine plantation in the mountainous area of eastern Liaoning Province should be realized by adjusting stand density and moderate tending and thinning in the future. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to establish a method for the Preparation of matrix reference material for carbaryl residues in Chinese yam flour. Methods: Yam powder containing menafyl was prepared by homogenized, freeze-dried, ground, sifted, mixed and packaged. A liquid chromatography-series mass spectrometer was used for detection, and the isotope internal standard curve method was used for quantification. Through the process of equalization stability evaluation, cooperative setting and uncertainty evaluation, the matrix reference material of the expected yam powder was obtained. Results: The property value and expanded uncertainty of carbaryl was (1.04±0.10) mg/kg (k=2). Conclusion: It could be used for food laboratory method verification, quality control and other activities.

In the assessment of environmental radiation risk, 137Cs and 129/131I, as high-yield fission products, are crucial indicators in the radioactive effluent of nuclear power plants. Due to the strong mobility and bioavailability of Cs+ and I- in the groundwater-soil system, their diffusion behaviors attracted much attention. In this work, the shallow soil samples under the long-distance effluent pipeline of a proposed nuclear power plant in China were used to study the diffusion behaviors of stable analogue (133Cs and 127I) of radioisotopes. The experimental data were fitted by Pycharm, which shows that the shallow soil at different sampling sites retards Cs+ through the adsorption process. The effective diffusion coefficient of Cs+ ranges from 3.87×10-11 m2/s to 4.31×10-11 m2/s, the range of effective diffusion coefficient of I- is 1.97×10-11 m2/s to 2.61×10-11 m2/s, illustrating the diffusion of Cs+ and I- are normal diffusion. The through time of Cs+ ranges from 29.24 d to 34.48 d, and the solid-liquid distribution coefficient (Kd) ranges from 3.34×10-2 L/g to 4.27×10-2 L/g. On the contrary, the average through time of I- is 0.30 d, which is much less than that of Cs+, and the solid-liquid distribution coefficient (Kd) of I- tends to be zero (1.75×10-4-2.72×10-7 L/g), indicating that the weakly adsorbed 129/131I is difficult to be fixed by soil, and illustrating a faster diffusion of I- than Cs+. The diffusion coefficient of Cs+ and I- in SK02 soil is the largest, which indicating that the migration rate of Cs+ and I- is faster in SK02. The differences of Cs+ and I- diffusion behaviors are affected by soil adsorption. Illite, biotite and montmorillonite in soil can provide stong affinity adsorption sites for Cs+, on the contrary, it is difficult to provide effective adsorption sites for I-. Since the main components of the soil samples are quartz, plagioclase and anorthite, when the concentration of Cs+ is higher than the capacity of strong affinity sites, a small amount of clay minerals in the soil will no longer control the diffusion of Cs+. In the meantime, the negative charge of the soil surface can attract Cs+ and reject I-, so in the long-term diffusion process, the surface charge is the dominant factor that controlling the diffusion behavior of Cs+ and I- in this area.

Accurate forecasting of short-term power load for industrial sectors plays a pivotal role in ensuring the safe and economic operation of regional power grids. To address this critical need， a short-term power load forecasting model in industries based on correlation analysis and convolutional neural network （CNN） is proposed. First， the k-means clustering algorithm is optimized， and the raw data of industry load and external influencing factors are clustered to improve the accuracy of the subsequent correlation analysis. Then， an improved correlation analysis method based on normalized mutual information （NMI） is proposed to quantitatively assess the correlation between various external influencing factors and industrial loads. Last， a load forecasting network considering the correlation of external influencing factors based on the CNN is designed， which can be used for the short-term power load forecasting of industrial sectors after training. The results of a controlled experiment demonstrate the superiority of the proposed model in terms of both accuracy and stability when it comes to short-term power load forecasting for industrial sectors.

Load forecasting of building air conditioning is of great significance for improving the accuracy of power load forecasting of buildings and regional distribution networks. In order to improve the load forecasting accuracy of building air conditioning， a load forecasting method based on multi-stage attention mechanism is proposed. First， the attention module of influencing factors is constructed to fully consider the importance difference of different influencing factors for load forecasting of building air conditioning. Second， the LSTM network model is used to extract the implicit features of influencing factors in each hour. Finally， the temporal attention module is constructed to differentiate the implicit features of the influencing factors in different hours according to the importance of building air conditioning load forecasting to obtain the results of the air conditioning load forecasting. The example results show that the construction of the influencing factor attention module and the temporal attention module are both conducive to improving the model’s ability to fit the building air-conditioning load， thus effectively improving the load prediction accuracy of building air-conditioning.

Cross - border mining is a difficult and hot topic in the current supervision of oil and gas mines. Based on the judgement and interpretation of superficial and surface engineering, such as well sites, station sites, oil wells, gas wells, metering plants, gas gathering stations, gathering and transportation stations, patrol roads, and oil and gas pipelines within a single mining right, this study proposed for the first time that the combined information of superficial and surface engineering allow for quickly clarifying the accumulation and flow direction of oil and gas and accurately identifying and determining the production sites belonging to the same mining right and the cross - border sites. This method has been applied to a certain oil field as the test area and has been proved effective. [ABSTRACT FROM AUTHOR]

It is of extreme significance to evaluate the health risks of various risk factors exposed to people as the reclaimed water reuse has been increasingly practised. In this study, fluorescence quantitative qPCR was used to test varied viruses including adenovirus (AdV), enterovirus (EV), and rotavirus (RV) in the reclaimed water of three urban waste-water treatment plants in Qingdao City. Thereby, on the basis of the testing results, health risk assessment of virus in the reclaimed wastewater was carried out with the help of the dose-response model and referring to the "four-step " method of the risk assessment proposed by the USEPA. Results of the assessment showed that above-mentioned samples were positive for AdV, the detected concentration being ND~924.44 copies/L, and neither EV nor RV was detected; as far as the tertiary treatment effluent of WWTP-2 phase (1st project) and the tertiary treatment effluent effluent of WWTP-2 phase (4th project) were reused applying in urban greening, putting off street dust, landscaping, household greening, flushing toilets, etc., AdV will cause certain health risks to both professionals and non-professionals, and the infection risk of professional personnel was higher than that of non-professional personnel. In terms of the referred different reuse ways, the health risk to professionals was following the order: urban greening≈putting off road dust≈landscaping > household greening > flushing toilets; on the other hand, the health risk to non-professionals following the descending order: urban greening > putting off road dust > landscaping > household greening > flush toilets. Hopefully, the assessment would provide theoretical supports for risk control in the process of local reclaimed water reuse. [ABSTRACT FROM AUTHOR]

For the difficulties in the construction of the directional drilling along the coal seam adjacent to the goaf under the influence of mining, such as the difficulty in hole formation and the inability of conventional measures to implement hydraulic fracturing, this paper takes the hydraulic fracturing drilling in the goaf adjacent to the 2# coal seam of Huangling No.2 Coal Mine as the research object, and puts forward the drilling layout idea of “entering the roof before entering the coal seam”. The comprehensive determination method of main key parameters is obtained, and the minimum value of opening point to coal point （Ｌ value） is 71.6 m; the stepwise release packer and matching in-hole fracturing tool combination suitable for the integral hydraulic fracturing of directional drilling are determined. The engineering practice has been carried out in the affected area of mining in the 209 working face, and the directional drilling and overall hydraulic fracturing construction of three “first entering the roof and then entering the coal seam” boreholes have been successfully implemented. The directional drilling length is 240-270 m, the rock hole section （Ｌ ｖａｌｕｅ） is 105-117 m, the single-hole fracturing section length is 126-165 m, the pumping pressure is 15.2-19.0MPa, and the fracturing fluid consumption is 248-315 m3. The measured influence radius of hydraulic fracturing is 36-54 m. The average gas drainage concentration and volume of fracturing boreholes has increased by 4-16 times and 3-8 times compared with that before fracturing. The gas drainage volume of pre-pumping boreholes in the fracturing area is twice that of the unfractured site, and the number of boreholes with gas drainage concentration greater than 60% is 5.1 times that of the unfractured area.

BackgroundThe study of irradiated samples is of considerable importance. Owing to these samples being radioactive, the applicability of conventional characterization methods is limited. Because of the high sensitivity of 3He detectors to neutrons, the small-angle neutron scattering (SANS) technique is nearly unaffected by radiation such as gamma, beta rays, and sample preparation is simple.PurposeThis study aims to develop a device for SANS measurement of nanostructures in radioactive samples.MethodsThe shielding thickness of the device was optimized through Monte Carlo simulations. Experimental efficiency and safety of the device were improved by combining remote-control functionality and automated sample switching among up to 12 samples loaded simultaneously. Finally, the device was used to carry out a SANS experiment for characterizing the radioactive A508-III steel sample.ResultsThe optimized thickness of the lead shielding layer of the device is 7.5 cm, the corresponding maximum dose rate of the measurable radioactive sample is 1.4 mSv·h-1. The results of successful SANS experiment on a A508-III steel irradiation surveillance specimen indicate that low-dose, long-term irradiation has a minimal impact on the nanostructure of pressure vessel steel.ConclusionsThe device and associated technical methods can be applied for nanostructure characterization of radioactive samples.

The preparation of a new type of adsorbent and its combined treatment of phosphorus and fluorine wastewater were studied. Using dolomite as raw material, after calcination and carbonation, the composition and morphology of the products were characterized by XRD, XRF, SEM, FTIR, etc. The effects of environmental parameters such as reaction time, initial phosphorus and fluorine concentration, solid-liquid ratio, pH value on the combined treatment of phosphorus and fluorine were investigated. The results show that with the increase of solid-liquid ratio, the residual fluoride concentration tends to be stable after decreasing. The removal kinetic of fluoride ions follows the pseudo-second-order model (R² > 0. 967). The initial pH value of the solution has no significant effect on the experimental results. The Langmuir isotherm adsorption model can better describe the fluoride removal process. The mechanism of calcination-carbonation dolomite (CCD) combined treatment of phosphorus and fluorine is as follows: CCD reacts with phosphorus to form hydroxyapatite, and then OH- is replaced by F- to transform into fluoroapatite; at the same time, the dissolved Ca2+ and Mg2+ from CCD react with F- to form corresponding products. [ABSTRACT FROM AUTHOR]

Accurate in-situ crustal stress data are essential for excavation support design and long-term stability analysis of underground projects. We tested the main shaft of the Shaling Gold Mine for crustal stress using hydraulic fracturing technology, and the crustal stress state of 20 measurement points was obtained. The Brazilian test, uniaxial compression test, and acoustic emission test of the cores were conducted indoors to obtain the rock’s spatial inhomogeneity and strength distribution. We analyzed the relationship between the inhomogeneity of the rock and the hydraulic fracturing results. The analysis results show that the magnitude of the principal stress increases nearly linearly with the measurement depth, with the maximum horizontal principal stress value ranging from 20.78 to 45.2 MPa and the minimum principal stress value from 14.94 to 35.33 MPa. The average direction of the maximum horizontal principal stress is NW 65°. The inhomogeneity of each layer of the cores varies, and the inhomogeneity coefficient of the metagabbro is from 0.1 to 0.3. The number of acoustic emission signals under each intensity of the rock is basically the same, and the dispersion of the rock is small. The non-homogeneity coefficient of granite is up to 1.0, dominated by the acoustic emission signals generated by the intense-phase rupture at the late loading stage. The non-homogeneity of the rock affects the direction of expansion of the hydraulic fracture, and the angle\begin{document}$\varphi $\end{document}between the expansion direction and the maximum horizontal principal stress affects the measurement results of the horizontal maximum and minimum principal stresses and has a more significant effect on the horizontal minimum principal stress. The relationship between hydraulic fracture measurements and rock properties was analyzed, which is helpful for accurately detecting the distribution of stress fields in inhomogeneous strata.

To improve the positioning accuracy of the followers in leader-follower cooperative navigation algorithm for multi-USVs based on distance measurement, this algorithm integrates the distance measurements between the followers into the traditional leader-follow structure, reconstructs the equations of state and measurements in this system, calculating positions through extended Kalman filter. Simulation results shows that the algorithm added distance measurements between the followers compared with the traditional algorithm can restrain the errors diffuse effectively and improve positioning accuracy of the followers.

Objective To analyze the clinical characteristics of patients in makeshift COVID-19 hospital and discuss how to establish and optimize the transfer system for a large number of critical cases. Methods From April 10 to May 24 of 2022, 659 patients with COVID-19 who needed to be transferred due to emergency in makeshift hospital located in National Convention and Exhibition Center were included, and their basic information, including the age, gender, underlying diseases and reasons for transfer, were analyzed. According to the key elements of the transfer process, a fast and efficient transfer system was established. Results Among the 659 transferred patients, 131 patients had respiratory system related diseases whose mean age was 58.47(95%CI: 55.62~61.33), with a male to female ratio of 1∶0.37(95/36). There were 528 patients had non-respiratory system diseases, whose mean age was 52.57(95%CI: 50.87~54.28), with a male to female ratio of 1∶1.01 (263/265). The types of diseases of the transferred patients mainly were 86 cases of endocrine diseases, 69 cases of cardiovascular system diseases, 34 cases of fever, 38 cases of nervous system diseases, 36 cases of tumor diseases, 34 cases of trauma, 32 cases of digestive system diseases and 199 cases of other diseases. Conclusion The effective treatment of patients in critical condition in makeshift hospital depends on the linkage mechanism run effectively, and the establishment of a fast, smooth, efficient and safe transport system can improve the treatment level of critical cases in large makeshift hospital.