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

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

The 3D perception system functions as one of the core components for the safe operation of autonomous-rail rapid tram. Addressing the limitations of LiDAR systems used for autonomous-rail rapid tram in complex urban environments, such as challenges in perceiving distant objects, insensitivity to color, and potential failure, this paper proposes a pure-vision monocular 3D perception system for autonomous-rail rapid tram. Comprising data preprocessing, model training and model deployment, this vision-based scheme with a full coverage from data collection to on-board deployment enables the 3D perception of obstacles around autonomous-rail rapid tram, thereby improving the operational reliability in complex urban environments. The test results based on the autonomous-rail rapid transit dataset and Waymo open dataset show that the system can effectively perceive the complex road scenes in autonomous-rail rapid transit, achieving a final 3D average precision (AP) of 0.53, reasoning a single-frame of image about 56 ms, and meeting the real-time requirements of autonomous-rail rapid tram for the obstacle perception algorithm.

In the driverless transport and operation system of surface mine, the roadside perception system is used to assist driverless vehicles by providing road condition information. The driverless system currently applied in mine trucks realizes roadside perception based on the multi-sensor fusion technology, consisting of cameras, laser radars and millimeter wave radars. However, this system has several drawbacks, such as high system cost, a complicated structure and poor robustness. In this regard, this paper proposes a roadside perception approach based on an improved DeepSORT algorithm. This approach involves using cameras to acquire image data on vehicles and pedestrians in the mine, which are accurately identified by the YOLOv5s algorithm. Then, the improved DeepSORT algorithm tracks the identified objects in real-time, enabling statistical analysis to provide various functions, including vehicle traffic statistics, abnormal parking detection and pedestrian intrusion detection. The proposed approach was tested at the No. 8 intersection of Xiwan Surface Mine of Shaanxi Shenyan Coal Co., Ltd. The results show that using a single sensor approach can effectively achieve the recognition and tracking of vehicles and pedestrians at mine intersection, reduce the complexity of the roadside perception system and save costs compared to the roadside perception technology based on multi-sensor fusion.

Objective To observe the effect of abdominal hollowing exercise (AHE) through real-time ultrasound imaging feedback on transverse abdominis (TrA) muscle activation and diastasis recti abdominis (DRA) after postpartum. Methods From December 2021 to July 2022, 62 patients with DRA more than 20 mm treated in the Third Affiliated Hospital of Guangzhou Medical University were selected and randomly divided into experimental group and control group. The real-time ultrasound imaging feedback for AHE was performed in experimental group, and conventional feedback for AHE was given in control group. The treatment lasted for four weeks in both groups. Before treatment and after 2 weeks and 4 weeks of treatment, the abdominal circumference (AC) was measured, and the abdominal muscle thickness and inter-recti distance(IRD) were measured by high-frequency ultrasound to calculate AC difference and the activation degree of TrA muscle. Results Compared with those in control group, the activation degree of TrA muscle significantly increased, and AC reduced in experimental group after 2 weeks of treatment (P＜0.05). Compared with those in control group, in experimental group, IRD became smaller ［（18.02±4.82）mm vs (20.36±4.13）mm, P＜0.05］, and the static TrA muscle thickness ［(3.21±0.59)mm vs (2.91±0.51)mm, P＜0.05］ and the dynamic TrA muscle thickness ［(5.16±0.86)mm vs (4.54±0.70)mm, P＜0.05］ significantly increased after 4 weeks of treatment. Conclusions AHE based on real-time ultrasound feedback can promote the activation of TrA muscle and an increase in thickness of TrA muscle, which may be conducive to the recovery of the postpartum patients with diastasis recti abdominis.

Thermal energy storage by using phase change materials (PCMs) is a kind of technology with mature development, simple process and high thermal energy storage density. Its basic homothermal heat storage and release process can reduce the loss of energy quality and has broad application prospects. Focusing on the key materials involved in phase change thermal energy storage technology, this paper introduced the advantages and disadvantages of various phase change materials under different application conditions, and summarized the applications of phase change thermal energy storage materials in waste heat recovery and utilization, solar thermal conversion storage, battery thermal management, building energy conservation and so on. In addition, the research progress in preventing the leakage of PCMs during the phase change process, improving the thermal conductivity of PCMs, and reducing the supercooling and corrosion effects of PCMs were summarized. Considering that the application of thermal energy storage by using PCMs contributes to the goals of energy conservation and carbon reduction, it is necessary to continue the research and development of thermal energy storage materials and continuously improve the comprehensive properties of thermal energy storage materials.

In the intelligent driving system of transport vehicles in open-pit mines, the data fusion of camera and LiDAR plays a vital role in the detection, recognition and tracking of obstacles. Aiming at the problem of camera and LiDAR spatial coordinate unity, that is establishing the correspondence between 2D coordinate system of image and 3D coordinate system of point cloud, this paper proposes a camera and LiDAR calibration method based on chessboard calibration board. Firstly, Zhang Zhengyou Calibration Method is used to calibrate the camera internal parameters, and the internal parameter matrix and distortion coefficient are obtained.Then the camera and LiDAR respectively extract the corner coordinates of the calibration plate edge, and multiple groups of the three-dimensional coordinates of point cloud and two-dimensional coordinates of the image are obtained. Based on multiple groups of feature point pairs, the external parameter matrix is obtained by EPnP algorithm. In order to verify the calibration accuracy, this paper projects the point cloud on the image plane and compares its point pair accuracy. Experimental results show that, this method can obtain the position and pose relationship between cameras and LiDAR, and the projection error is less than 3 pixels, which solved the problem of camera and LiDAR space calibration of transport vehicles in open-pit mines.

Currently, a variety of commercial software has been introduced from abroad into the oil & gas engineering design industry, which has a certain impact on the development cost and output process of the traditional engineering design industry. Hence, it is urgent to seek for high-efficiency application of the software. Besides, the domestic commercial process software is developed relatively slowly and not applied massively in the engineering design industry.So, the application status of foreign commercial process software was summarized systematically based on a variety of mainstream commercial software for relevant process design in the upstream-midstream and downstream projects of oil &gas engineering. The product characteristics, development trend and related impact on the industry were also expounded.Meanwhile, the product characteristics and development trend of domestic commercial process software were summarized,with comparative analysis on the advantages and disadvantages of the domestic commercial process software. On this basis, the application and efficiency improvement strategies were proposed for the foreign commercial process software,including the consideration and suggestions on the development of domestic commercial process software, so as to provide reference for the development, application and evolution of industrial process software for engineering design.

Quantum-based sensing and measurement technology is a disruptive technology that can realize fine detection of the gravity and magnetic fields in deep Earth, and it has become a key development direction for geophysical exploration equipment worldwide. This study focuses on the frontier technologies for the quantum-based high-precision measurement of Earth’s gravity and magnetic fields, summarizes the development status of quantum-based geophysical exploration equipment, and analyzes demand for the superconducting quantum-based electromagnetic detection system, magnetic vector gradient detection system, superconducting gravity detection system, and cold-atom absolute-gravity exploration system during deep resource exploration. Moreover, the international trend of quantum-based high-precision measurement technology as well as the development opportunities and challenges in this field are analyzed. To improve the core technology research, complete localization, and exploration application of quantumbased geophysical exploration equipment in China, we propose the development goals, technical system, key tasks, and strategic planning for a new generation of quantum-based high-precision deep geophysical exploration equipment. This aims to achieve breakthroughs in superconducting quantum chips and high-sensitivity sensors, establish a collaboration model for the independent development of China’s quantum-based geophysical exploration equipment, promote the high-quality development of deep exploration equipment, and provide strategic support for solving major problems associated with deep mineral resource exploration and revealing of Earth’s deep structure.

Aiming at the problems of poor detection effect and low tracking stability of multi-type vehicles in complex mining environment due to the similarity of operating vehicles and background images, this paper proposes a multi-category and multi-target real-time detection and tracking algorithm for operating vehicles in complex mining environments. The model framework is constructed based on the lightweight backbone network YOLO combined with the multi-scale feature fusion module. The model uses DIoU as loss function, uses K-means clustering to regress the size of candidate frame, and learns image features through the lightweight backbone network. On this basis, the features of multi-category work vehicle targets are used as similarity metric, combined with Mahalanobis distance metric and cosine metric that characterize motion information for cascading matching, and IoU matching and Kalman filtering are connected in series to confirm the trajectory and the real-time tracking of multiple work vehicles. Experimental results show that the average vehicle detection accuracy of the algorithm mAP@ 0.5-0.95 is 58.40%, the multi-target tracking accuracy reaches 82.60%, and the image processing time per frame is 26.5 ms, which can effectively perform real-time detection and tracking of working vehicles.

ObjectiveTo explore the effect of home visit based on empowerment education on psychotic symptoms， self-management ability and well-being of schizophrenia patients in home rehabilitation.MethodsA total of 87 cases of schizophrenia patients who met the diagnostic criteria of International Classification of Diseases， tenth edition （ICD-10） and were recovering at home in Caiba town， Yibin city from January to July 2021 were selected by random sampling method as research subjects. They were divided into experimental group （n=43） and control group （n=44） according to the random number table method. The two groups received routine family visits， and the experimental group received family visits based on empowerment education. The intervention cycle of the two groups was 6 months. Before and after the intervention， the severity of psychotic symptoms， self-management ability and well-being of the patients in the two groups were assessed with the Brief Psychiatric Rating Scale （BPRS）， the Schizophrenia Self-Management Instrument Scale （SSMIS） and the Index of Well-Being Scale （IWB）.ResultsAfter intervention， the intra group comparison showed that the BPRS score in the experimental group was lower than that before the intervention （t=4.550， P

ObjectiveTo investigate the contamination status and dietary exposure risk of 3 perfluorinated substances and 2 chlorine substituted perfluoroalkyl ether sulfonate acids in fresh vegetables planted in the vicinity of typical fluorine chemical industry parks located in Guangdong province.MethodsNinety six vegetables were collected from the vicinity of 3 typical fluorine chemical industry parks and local markets in 2019. The concentrations of 3 perfluorinated substances ［perfluorooctane sulfonate acid （PFOS）， perfluorooctanoic acid （PFOA）， perfluorohexanesulfonic acid （PFHxS）］ and 2 chlorine substituted perfluoroalkyl ether sulfonate acids （6：2 Cl-PFESA and 8：2 Cl-PFESA） in fresh vegetables were detected using isotope dilution method by UPLC-QqQ-MS， and the point estimate was employed to estimate the levels of dietary exposure from fresh vegetables.ResultsPFOS and PFOA were detected in all samples， while chlorine substituted perfluoroalkyl ether sulfonates were detected in 2 leafy vegetable samples. The sum of average concentration of PFASs and Cl-PFESAs in vegetable samples was 0.792 ng/g fw （fresh weight， fw）， and it was two-fold higher compared the samples around the fluorine chemical industrial with the samples from local markets. The average concentration of 5 chemicals （1.11 ng/g fw） was the highest in leafy vegetables. The results of dietary exposure assessment indicated that the exposure levels of 3 perfluorinated compounds by consumption of fresh vegetables which planted surrounding fluorine chemical industry parks were 0.185-2.35 ng/kg·BW. The hazard indexes （HI） of PFOS and PFOA were greater than 1. The exposure level of chlorine substituted perfluoroalkyl ether sulfonate acids were lower.ConclusionThe exposures of PFOS and PFOA of local general population exceeded the established thresholds for the adult residents. The risks of 2 chlorine substituted perfluoroalkyl ether sulfonate acids exposure from vegetables were low， which still need to be concerned.

The Chingshui geothermal field stands out as the most significant geothermal field in Taiwan. Understanding the sustainability of geothermal energy is important for its long-term use. In the present study, a numerical model Chingshui reservoir based on geological conditions is developed by using a thermal-hydraulic-mechanical (THM) model in the COMSOL to evaluate the depth’s effect of the production well on the different binary cycles. The thermodynamic cycles of two configurations, namely the organic Rankine cycle (ORC) and transcritical Rankine cycle (TRC), are established by using MATLAB and coupled with the Chingshui reservoir through the COMSOL Livelink module. The study focuses on different well depths’ effects on the cycle performance. The results show the system efficiencies of the ORC and TRC under different well depths were 5.77% and 13.76%, and 9.64% and 16.31%, respectively.

Speech recognition technology is a key component of the intelligent voice interaction system. In recent years, this technology has developed rapidly and is widely used in automotive electronics, consumer electronics, medical and other fields. This paper analyzes the development status of speech technology in the field of automotive field, introduces the development process of this technology in detail, focuses on the demand and application of speech recognition technology in the field of rail transit.Aiming at the problem that the display interactive content of different models of rail transit is changeable and needs to be customized and developed, the research on speech recognition technology based on time-delay neural network is carried out and a speech recognition system for train display based on intelligent computing platform is developed. The system can flexibly build models according to the interaction requirements of different display platforms and the processing performance of intelligent hardware platforms, and optimize the interaction keywords on the basis of the general model to improve the recognition rate. Finally, the test is completed in the voice interaction system of autonomous-rail rapid tram display in different scenes and noisy conditions and the word recognition rate reaches more than 85%. It also lays the foundation for the application of intelligent voice technology in other rail transit vehicles.

Track component defect detection has long faced the problem of scarcity of defect samples. In the case of insufficient defect samples, the existing deep learning methods are prone to overfitting the model, and the generalization performance is poor, making it difficult to meet the actual track inspection requirements. To this end, this paper proposes a cascaded track component defect detection method which combines instance segmentation, fine-grained image classification and traditional image processing. Firstly, an improved fast instance segmentation network is proposed to locate fasteners and defective rails. Secondly, in view of the scarcity of defective fastener samples, a method of mask analysis and quantitative comparison of fastener contour lengths is proposed to realize the low-sample condition. At the same time, in view of the problem that the categories of rail defects are complex and subtle and easy to mix, a two-stage defect detection network of "instance segmentation + fine-grained image classification" is proposed, and label smoothing technology is introduced to improve model adaptability and classification accuracy. Experimental results show that, in the case of scarce samples, the defect detection method proposed in this paper has an accuracy rate of 95.7% for fastener breakage and loss detection, and 98% and 95% for rail defect detection rate and defect sub-classification, respectively. It meets the demand for track component defect detection.

BackgroundInert matrix fuel (IMF) can efficiently convert plutonium and long-lived minor actinides used for preventing the proliferation of nuclear weapons and improving spent fuel disposal, hence has been becoming a hot research topic in recent years. The sol-gel method has the advantage of uniform elemental distribution of the products and the wet operation process is less likely to produce radioactive dust, therefore, it has been used to prepare zirconium-based IMF in the research.PurposeThis study aims to prepare a colloidal solution with good dispersive properties and to obtain IMF microspheres with good sphericity, uniform size, and homogeneous elemental distribution.MethodsFirst of all, ThxZr1-xO2 inert matrix fuel was prepared by an external gelation process, and the sol-gel viscosity was used as the main gelation index. Then, the variation tendency of sol viscosity with c(NH4+)/c(NO3-) was investigated for different metal ions concentrations and different temperatures. Finally, the statistical distributions of colloidal particle sizes were obtained for different metal ions and reaction temperatures by laser particle sizing tests, and the X-ray diffraction (XRD) was used to study the structure of IMF after heat treatment at different temperatures.ResultsThe results showed that the complex gelation parameters and properties can be categorized and quantified using gelation field diagrams. In addition, ThxZr1-xO2 IMF kernels with uniform element distribution, good sphericity, and integral appearance were obtained by optimizing the process parameters. Zirconia showed low solubility behavior in the thorium-oxide system, leading to the generation of a biphasic structure.ConclusionsThe results of this study indicate that zirconium-based spherical IMF microspheres with good performance can be prepared by external gelation method.

Insufficient data, lack of expertise in AI application development, and weak device computing capabilities have severely restricted the rapid engineering implementation of rail transit intelligent products. In order to solve these problems, this paper proposes an AI open platform for rail transit. It builds connection between model training, edge computing and cloud-edge collaboration, and provides full-process AI application development solutions. In the cloud, this platform builds an AI development tool chain including data annotation, algorithm design, model training and application generation. It also provides an efficient model inference framework at the edge. Data collection and model deployment are implemented through the cloud-edge collaboration mechanism. Since unmanned mining trucks use autonomous driving technology similar to rail transit, this paper takes the visual perception application of unmanned mining trucks as an example for verification. The result shows that using AI open platform for application development can effectively reduce application development and deployment time, from 3~4 months normal period to present 1 month.The mean average precision of the visual detection model for stones, mining truck and other targets reaches 0.988, achieving excellent perceptual performance.

In order to promote the safety access system of mining equipment in China to adapt to the development of mine safety management, through combing the current operation mode and existing shortcomings of MA/KA management, the paper studies the safety access system of mining equipment in major mining areas of the world and common analysis with MA/KA. The paper researches production license system and certification system of industrial products in China, and focuses on comparative analysis and learns from special equipment, fire products, railway products, environmental sign products safety access management, key points for safety access system reform of mine equipment. On this basis, this paper explores the reform ideas of the transition to administrative licensing management, national certification and system owners.

BackgroundOwing to its excellent mechanical properties and corrosion resistance, 304L stainless steel is widely used as the core structure material in advanced nuclear power systems.PurposeThis study aims to investigate the damage characteristics of selective laser melted (SLM) 304L stainless steel under Xe ion irradiation and compare them with that of traditionally manufactured (TM) 304 stainless steel under the same experimental conditions.MethodsSLM 304L and TM 304L alloy samples were irradiated with 5 MeV Xe ions at 550 ℃. The irradiation dose was 3.53×1015 ions·cm-2. The microstructure and nano-hardness changes of the both alloy samples before and after irradiation were characterized by transmission electron microscopy (TEM) and nanoindentation, respectively. TEM samples were prepared by focused ion beam.ResultsThe TEM images show that dislocation loops and bubbles appeared in the irradiated alloy samples. The average sizes and number densities of dislocation loops in the SLM 304L and TM 304L alloy samples are (2.13±0.53) nm and (1.94±0.46) nm, 1.48×1022 m-3 and 6.94×1022 m-3, respectively. The average sizes and number densities of Xe bubbles in the SLM 304L and TM 304L alloy samples are (3.71±1.40) nm and (1.37±0.46) nm, 3.50×1022 m-3 and 1.73×1023 m-3, respectively. The both alloy samples show the irradiation hardening after Xe ion irradiation. The irradiation hardening degrees of the SLM 304L and TM 304L alloy samples are 14% and 32%, respectively.ConclusionsThe calculation results based on the dispersed barrier hardening model (DBH) reveal that the dislocation loops and Xe bubbles caused by irradiation play an important role in irradiation hardening of the two kinds of alloys.

The research on the standard system of coal mine equipment is based on the top-level design of the standard system. Through in-depth review and analysis of the national and industry standards approved and published, the deficiency of the existing coal mine equipment standardization work is analyzed, focusing on the common characteristics of the European Union, the United States, Russia's coal mine equipment standards. In view of the existing deficiencies and the analysis of foreign standard systems for reference, the construction principles, construction dimensions and overall framework of the standard system were proposed. A standard system including basic standards of coal mine equipment, 12 sub-systems of professional equipment standards and 973 standards was established, and suggestions for standardization under the new system were put forward.

Objective To explore the associated factors for quality of life in patients with progressive supranuclear palsy (PSP). Methods A total of 218 PSP patients were included from January 2012 to December 2019. Demographic and clinical data were collected. The quality of life was evaluated by the 39⁃Item Parkinson's disease Questionnaire (PDQ⁃39). The Progressive Supranuclear Palsy Rating Scale (PSPRS) was used to assess the severity of PSP related motor and non⁃motor symptoms, while the Non⁃Motor Symptoms Scale (NMSS) was used to elevate the non⁃motor symptoms, Hamilton Depression Rating Scale⁃24 (HAMD⁃24), Hamilton Anxiety Rating Scale (HAMA), Lille Apathy Rating Scale (LARS), Frontal Assessment Battery (FAB), and Montreal Cognitive Assessment (MoCA) were used. The Pearson and partial correlation followed by the multiple linear regression were used to explore the correlates of the PDQ⁃39 score. Results Correlation analysis indicated that the PDQ⁃39 score was positively correlated with disease duration (r=0.301, P=0.000), Charlson Comorbidity Index (CCI; r=0.147, P=0.031), levodopa equivalent daily dose (LEDD; r=0.225, P=0.001), and scores for the PSPRS (r=0.551, P=0.000), NMSS (r=0.484, P=0.000), HAMD⁃24 (r=0.515, P=0.000), HAMA (r=0.439, P=0.000) and LARS (r=0.476, P=0.000), but was negatively correlated with scores of FAB (r=⁃0.325, P=0.000) and MoCA (r=⁃0.355, P=0.000). Multiple linear stepwise regression model indicated that the PDQ⁃39 score was significantly associated with female (P=0.021), longer disease duration (P=0.026), higher LEDD (P=0.008), higher PSPRS score (P=0.000), higher NMSS score (P=0.002), higher HAMD⁃24 score (P=0.004), and higher LARS score (P=0.000). Conclusions Female, longer disease duration, higher LEDD, and more severe motor and non⁃motor symptoms contribute to the reduced quality of life in patients with PSP. Our study is beneficial to the clinical management of patients with PSP.

Eliminating poverty and exploiting natural resources are sustainable development goals for modern society, especially for developing countries or regions. To achieve these targets, development-oriented eco-tourism planning and design can empower rural areas with rich available natural resources to eventually achieve the aforementioned goals. Pro-Poor Tourism (PPT), an initiative proposed by the UK's Department for International Development in 1999, is regarded as an effective pathway that benefits, through tourism, the underprivileged population living in poor areas. For the purpose of attracting the participation and increasing the income of the poor population, we conducted research, in the present study, on possible models of development-oriented poverty reduction via ecotourism in forest zones. We then proposed several development paths for PPT industries in Lechang city, Guangdong province, southern China, by utilizing the literature review method and conceptual analyses and comprehensively adopting the PPT strategy. The results indicated that: 1) four stakeholders [(i.e., government departments, tourism enterprises, rural communities, and non-profit social organizations (NGOs)] are responsible for engaging the poor population, alleviating poverty, and protecting the environment in different ways. Specifically, government departments are expected to play a leading role in setting up platforms and supervising the situation, tourism can maximize its usage of various ecological resources rationally and sustainably, and the rural communities and NGOs are recommended to serve as an organic unit, working together to push forward certain PPT tasks and form practical development models. 2) In consideration of the availability of three featured types of ecological resources (i.e., natural forests, high mountain tea, and characteristic vegetables and fruits) in Lechang city, the present study put forward a compound development model of ecological tourism consisting of the above three featured agro-forestry resources.Furthermore, we proposed three possible pathways suitable for the industrial development of Lechang city; that is, (i) "leisure agriculture + characteristic forest fruit industry + e-commercial tourism industry," (ii) "understory leisure industry + understory economic industry + initial processing of forest products," and (iii) "forest eco-tourism + characteristic forest planting + natural ecological education." In conclusion, our study suggests that the rational utilization of the PPT strategy and the effective integration of government departments, tourism enterprises, rural communities, and NGOs could facilitate subsequent tasks. The study also emphasized that achieving the anticipated three goals (i.e., comprehensive development of economy, comprehensive development of poor communities, as well as poor population and ecological sustainability) might largely rely on the full consideration of benefits for the economy, society, and the environment during the process of development-oriented poverty reduction via eco-tourism by the four stakeholders.

Air pollution is a serious problem in China, and the control measures are incomplete.By conducting a comparative study of domestic and foreign emission standards of volatile organic compounds(VOCs) and learning the content of foreign standards, we can provide ideas for China's environmental management and reduce the harm of VOCs to human health and ecological environment via strengthening management and control.Through a comparative research on the definition, hazard attributes, control measures and other aspects of VOCs between China and developed countries, several suggestions are put forward for the management and control of VOCs in China:strengthening top-level design;scientific screening to increase industrial pollution control;establishing refined standard system;implementing risk management;considering photochemical reaction and harmful properties, strengthening source prevention.

Chronic obstructive pulmonary disease (COPD) is a common obstructive respiratory disease characterized by persistent respiratory symptoms and limited airflow due to airway obstruction. The present study investigates the distribution characteristics of respiratory tract flora in both frequent and infrequent exacerbators of COPD. The 16S sequencing technique was adopted to differentiate the inherent differences of respiratory tract flora between frequent exacerbators and infrequent exacerbators. Additionally, cell counting kit 8 (CCK8), lactate dehydrogenase (LDH) test, flow cytometry, enzyme-linked immunosorbent assay (ELISA), and western blot were carried out in human bronchial epithelial cells cultured in vitro and the regulatory effects of differential flora were verified. The results revealed that the observed species index, Chao1 index, and the ACE estimator of COPD frequent exacerbators were markedly higher than those of COPD infrequent exacerbators. The top five strains of COPD frequent exacerbators included g_Streptococcus (15.565%), g_Prevotella (10.683%), g_Veillonella (6.980%), g_Haemophilus (5.601%), and g_Neisseria (4.631%). Veillonella parvula generated obvious cytotoxicity and substantially reduced the activity of human bronchial epithelial cells (p < 0.01). Furthermore, the results of flow cytometry indicated that the proportion of human bronchial epithelial cells in both the S phase and G2 phase decreased following Veillonella parvula treatment indicated that Veillonella parvula inhibited cell proliferation. Meanwhile, being treated using Veillonella parvula, the expressions of interleukin-1 (IL-1), IL-6, Tumor Necrosis Factor α (TNF-α), and p-nuclear factor kappa B (NF-κB) of the cells were increased markedly (p < 0.01). Taken together, the current research demonstrated that the relative abundance of Veillonella in COPD frequent exacerbators was higher than that of infrequent exacerbators. Veillonella parvula activated the inflammatory pathway, ultimately destroyed the cell viability, and greatly impaired the activity of human bronchial epithelial cells, thereby inhibiting cell proliferation.

Background The solid fuel thorium element molten salt reactors (MSR) have attracted more attention recent years. A3-3 graphite is chosen as the fuel matrix for MSR, thus its irradiation behavior and mechanical property is very important before the application. Purpose The study aims to observe the irradiation defects and hardness of A3-3 matrix graphite after ion irradiation by slow positron beam and nano-indentation, respectively. Methods The matrix graphite of fuel elements was irradiated with 1 MeV Xe ions to fluence of 5.8×1014 ions·cm-2 and 2.9×1015 ions·cm-2 respectively at room temperature. The slow positron beam and nano-indentation were employed to investigate the effect of Xe ions irradiation on vacancy defects and hardness of matrix graphite. The changes in irradiation induced defects distribution with depth and fluence were analyzed according to the obtained positron annihilation S parameters versus positron incidence energy or depth curves, compared to SRIM (Stopping and Range of Ions in Matter) calculation. Results Results from slow positron beam measurement show that 1 MeV Xe ions irradiation in matrix graphite introduces a damage layer with depth of about 600 nm, and the damage peak locates at about 250~350 nm in depth, consisted with SRIM simulation. The S parameters in irradiation samples increase significantly compared to virgin sample, which suggests that a high concentration of vacancy-type defects appeared within irradiation damage layer. In addition, the S parameters increase with the irradiation fluence, which shows that the concentration or size of vacancy-type defects increases. The nano-indentation results show that the hardness of irradiated graphite matrix is enhanced. Conclusions The enhanced hardness of A3-3 matrix graphite after ion irradiation is ascribed to the pinning of basal plane dislocation by the high concentration of vacancy type defects introduced by irradiation, consisted with the slow positron beam analysis. Slow positron beam is a very sensitive tool to study the irradiation defects.

BackgroundThe additive manufacturing (AM) technology is expected to apply to the field of advanced nuclear energy because of its unrivalled design freedom and short lead times. However, the irradiation resistance of the AM materials needs to be studied. One of the key scientific problems is the irradiation hardening behavior of the AM materials under irradiation environment. As a candidate nuclear material, 316L stainless steel (SS) produced by selective laser melting (SLM, a very important AM technology of metals) is selected as the study object.PurposeThis study aims to investigate the irradiation hardening behavior and the irradiation defects evolution of the SLM 316L SS as function of temperature.MethodsThe SLM 316L SS was irradiated by 500 keV helium ions at different irradiation temperatures (from 350 °C to 800 °C) to explore the temperature effect of hardening behavior. The irradiation dose of each sample was 1.5×1016 ions·cm-2. The irradiation hardening and irradiation defects were characterized by nanoindentation and transmission electron microscopy (TEM) respectively. The contribution of helium bubbles and dislocation loops to irradiation hardening was calculated using the dispersed barrier hardening (DBH) model.ResultsThe results of the nanoindentation test show that the irradiation hardening degree of SLM 316L SS decreases from 71.65% at 350 °C to 23.62% at the highest temperature, suggesting an obvious irradiation hardening recovery with the temperatures increasing. The observation of TEM indicates that helium bubbles and dislocation loops are the main micro defects caused by the ion irradiation. The evolution trend of the two types of irradiation defects with temperature is the same whilst the helium bubble's contribution to the irradiation hardening is slightly higher than that of dislocation loops except at the highest temperature. With the increase of temperature, the average number density of the two defects decreases steadily with the increase of diameter, but the helium bubbles have the higher temperature sensitivity. The calculated values by the DBH model are in agreement with the experimental values obtained by nanoindentation testing.ConclusionsThe irradiation hardening of SLM 316L SS decreases with increasing temperature, and helium bubbles and dislocation loops are closely related to the irradiation hardening behavior. The higher temperature sensitivity of helium bubbles may be a very important reason for the high temperature recovery of irradiation hardening. With the increase of temperature, the decrease of irradiation defects induced by the enhancement of defects' diffusion ability is the main mechanism of the recovery of the hardening behavior of SLM 316L SS at high temperature.

Background: Picture My Participation (PMP) intended to measure participation, defined as attendance and involvement in everyday situations, of children with disabilities, particularly in low- and middle-income settings. Objectives: To explore structural validity of PMP by identifying possible subcomponents in the attendance scale and examining internal consistency of the total score and each subcomponent. Method: A picture-supported interview was conducted with 182 children, 7–18 years, with and without intellectual disability (ID). Frequency of attendance in 20 activities was rated on a four-point Likert scale (never, seldom, sometimes and always). Results: An exploratory principal component analysis extracted four subcomponents: (1) organised activities, (2) social activities and taking care of others, (3) family life activities and 4) personal care and development activities. Internal consistency for the total scale (alpha = 0.85) and the first two subcomponents (alpha = 0.72 and 0.75) was acceptable. The two last subcomponents alpha values were 0.57 and 0.49. Conclusion: The four possible subcomponents of PMP can be used to provide information about possible domains in which participation and participation restrictions exist. This study provided further psychometric evidence about PMP as a measure of participation. The stability and the utility of these subcomponents needed further exploration.

Rock quality designation (RQD) is widely adopted as a fundamental tool in characterizing rock masses since it was devised in 1964. Since the conventional RQD calculation is limited due to its dependence on the selected threshold, previous research introduced generalized RQD to adequately reflect the anisotropy and scale effect of RQD. However, the influence of the joint development inside rock mass on generalized RQD remains unclear. The objective of this work is to investigate characteristics of the generalized RQD in view of different development degrees of discontinuities in rock mass, including spacing (density) and trace length. Three-dimensional fracture network modelling is employed to simulate the actual rock mass of open-pit iron mine in China. Virtual scanlines are set to obtain RQD values in different directions. The results primarily show that the generalized RQD should be introduced to calculate the RQD with different thresholds to fully reflect the anisotropy of rock mass. The optimal threshold can be obtained based on an anisotropic coefficient, which is defined by (RQDmax-RQDmin). It is also indicated that the fracture spacing has a great influence on both the anisotropy of RQD and the selection of the optimal threshold. The optimal threshold of the generalized RQD increases with the increase in the fracture spacing. In addition, the scale effect of RQD in different models is discussed by changing the length of the scanlines. The longer the scanlines we set, the more stable RQD value can be obtained in the model. It is recommended to fit much longer scanline to get realistic RQD in heavily fractured rock mass.

BackgroundThe Uranium dioxide (UO2) is currently the most widely used nuclear fuel for commercial nuclear reactors. However, the Fukushima Daiichi nuclear disaster revealed the primary safety risks of this fuel in an accident, so various international programs were launched to develop accident tolerant fuel (ATF), a new generation of fuel system developed to enhance the capability of nuclear fuel assemblies in severe accidents.PurposeThis study aims to improve the thermal conductivity of fuel pellets by adding a second material to the UO2 matrix, an important research direction for ATF.MethodsFirst of all, large-grain UO2 particles were used as raw materials, and the high-density large grain UO2-SiC composite fuel pellets were obtained by Spark Plasma Sintering (SPS) sintering process at lower sintering temperature. Then, the properties, such as microstructure and chemical composition, of the composite fuel pellets were characterized by using metallographic microscope (MM), scanning electron microscope (SEM), X-ray diffraction (XRD) and energy dispersive spectrometer (EDS). Finally, the high-temperature oxidation resistance in air environment was studied.ResultsThe results show that the UO2-SiC interfacial reaction can be avoided by the SPS sintering at lower temperature, and the density of the prepared pellets is more than 95% theoretical density (TD). Compared with traditional UO2 fuel pellets and SPS sintered UO2-SiC pellets using conventional UO2 powders, the thermal conductivity of large-grain composite fuel pellets is significantly improved. Oxidation tests results indicate that the oxidation weight gain of the composite fuel pellets is significantly weaker than that of traditional pellets when the temperature is lower than 350 ℃. However, when the temperature reaches 350 ℃, the oxidation of UO2 cannot be further prevented by SiC.ConclusionsThis study provides reference for improving the thermal conductivity of UO2 matrix by adding a second phase with high thermal conductivity.

Electronic transformers and merging units are the core components of smart substation. The performance and accuracy of these indicators have a decisive impact on the following measures: protection, measurement and control, and digital energy metering. However, selection or acceptance, regular testing and other aspects of the measures taken or means have not yet reached a perfect, comprehensive and accurate level. This paper presents a merging unit tester traceability device with table source integrated separable structure characteristics, both for electronic transformer calibrator and the merging unit tester traceability. It can also directly calibrate the electronic transformer and the merging unit error.