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In diplomacy and statecraft studies, it has been established that the invisible yet omnipresent language interpreters often assume a critical role at international meetings of politicians and diplomats. In contrast to interpreting in everyday settings, interpreting in political and diplomatic settings is high-profile and exclusive for two main reasons. On the one hand, political events and diplomatic missions often involve high-ranking and high-power officials from the field of politics and diplomacy, usually heads of the state, ministers, and military commanders. On the other hand, the impact of these communicative events is far-reaching, extending to peace negotiations, conflict resolutions, and post-conflict peace-building efforts. The outcome of these operations is highly visible and substantive to vulnerable groups and mobile populations, including but not limited to child victims, war-afflicted adults, and displaced and stateless populations.

This paper aims to study the safe haven attribute of the Japanese yen under domestic and U.S. economic and policy uncertainty (EPU). Because of the existence of structural changes, a bootstrap rolling window subsample causality test is used to enhance the credibility of the results. The empirical results confirm that the exchange rate returns (RER) and Japanese EPU are correlated in specific periods when major economic or political events occur. In most crisis periods, the Japanese EPU has positive effects on RER, and the yen appreciates when the EPU is increasing. In addition, the RER of the yen and U.S. EPU are both negatively and positively connected. This finding confirms the hedging function of the yen in certain periods. The reason for this relationship is that Japan’s low interest rates make the yen the primary funding currency in speculative carrying trade strategies, and thus, it tends to appreciate during crisis periods regardless of the origins of the EPU shocks. Therefore, the yen can be held as a safe haven currency unless the government intervenes artificially.

Abstract Background Effective conservation and utilization of farm animals are fundamental for realizing sustainable increases in food production. In situ and ex situ conservation are the two main strategies that are currently used to protect the genetic integrity of Chinese domestic chicken breeds. However, genomic diversity and population structure have not been compared in these conserved populations. Results Three hundred and sixty-one individuals from three Chinese domestic chicken breeds were collected from populations conserved in situ and ex situ and genotyped using genotyping-by-sequencing (GBS). First, we used different parameters based on heterozygosity, genomic inbreeding, and linkage disequilibrium to estimate the genomic diversity of these populations, and applied principal component analysis (PCA), neighbor-joining tree, and ADMIXTURE to analyze population structure. We found that the small ex situ conserved populations, which have been maintained in controlled environments, retained less genetic diversity than the in situ conserved populations. In addition, genetic differentiation was detected between the in situ and ex situ conserved populations of the same breed. Next, we analyzed signatures of selection using three statistical methods (fixation index (FST), nucleotide diversity (Pi), and cross-population extended haplotype homozygosity (XP-EHH) to study the genetic footprints that underlie the differentiation between in situ and ex situ conserved populations. We concluded that, in these small populations, differentiation might be caused by genetic drift or by mutations from the original populations. The differentiation observed in the population of Beijing You chicken probably reflects adaptation to environmental changes in temperature and humidity that the animals faced when they were moved from their place of origin to the new site for ex situ conservation. Conclusions Conservation programs of three Chinese domestic chicken breeds have maintained their genomic diversity to a sustainable degree. The small ex situ conserved populations, which are maintained in controlled environments, retain less genetic diversity than populations conserved in situ. In addition, the transfer of populations from their place of origin to another site for conservation purposes results in genetic differentiation, which may be caused by genetic drift or adaptation. This study provides a basis for further optimization of in situ and ex situ conservation programs for domestic chicken breeds in China.

Abstract Background Although the accumulation of whole-genome sequencing (WGS) data has accelerated the identification of mutations underlying complex traits, its impact on the accuracy of genomic predictions is limited. Reliable genotyping data and pre-selected beneficial loci can be used to improve prediction accuracy. Previously, we reported a low-coverage sequencing genotyping method that yielded 11.3 million highly accurate single-nucleotide polymorphisms (SNPs) in pigs. Here, we introduce a method termed selective linkage disequilibrium pruning (SLDP), which refines the set of SNPs that show a large gain during prediction of complex traits using whole-genome SNP data. Results We used the SLDP method to identify and select markers among millions of SNPs based on genome-wide association study (GWAS) prior information. We evaluated the performance of SLDP with respect to three real traits and six simulated traits with varying genetic architectures using two representative models (genomic best linear unbiased prediction and BayesR) on samples from 3579 Duroc boars. SLDP was determined by testing 180 combinations of two core parameters (GWAS P-value thresholds and linkage disequilibrium r2). The parameters for each trait were optimized in the training population by five fold cross-validation and then tested in the validation population. Similar to previous GWAS prior-based methods, the performance of SLDP was mainly affected by the genetic architecture of the traits analyzed. Specifically, SLDP performed better for traits controlled by major quantitative trait loci (QTL) or a small number of quantitative trait nucleotides (QTN). Compared with two commercial SNP chips, genotyping-by-sequencing data, and an unselected whole-genome SNP panel, the SLDP strategy led to significant improvements in prediction accuracy, which ranged from 0.84 to 3.22% for real traits controlled by major or moderate QTL and from 1.23 to 11.47% for simulated traits controlled by a small number of QTN. Conclusions The SLDP marker selection method can be incorporated into mainstream prediction models to yield accuracy improvements for traits with a relatively simple genetic architecture, however, it has no significant advantage for traits not controlled by major QTL. The main factors that affect its performance are the genetic architecture of traits and the reliability of GWAS prior information. Our findings can facilitate the application of WGS-based genomic selection.

After several stages of development, China has made great achievements in rural energy. However, the low-efficiency and high-pollution solid fuels that characterize the main source of energy consumption in rural areas remain unchanged. Under the constraints of achieving the carbon neutrality goal in 2060, the existing energy system needs to be transformed to create a sustainable energy system in order to further enhance the economy of rural areas in China. To accelerate the transition of rural energy, this paper answers the following questions based on rural energy consumption characteristics and policies, literature analysis: Why is the rural energy transition important for China at national and rural levels? How the rural energy transition can contribute to the development of rural areas? What are the challenges to implementing the rural energy transition? The paper concludes that China’s rural areas can achieve both economic and ecological development through rational use of its vast space and natural resources, which will be valued upwards of 450 billion CNY and 800 Mt CO2eq respectively. Rural energy transition will face a number of challenges from infrastructure, socio-cultural, and program development. Accordingly, Therefore, there is a need to strengthen infrastructure, raise public awareness and deepen the tripartite cooperation between government, enterprises and farmers to deal with the above problems.

With the gradual increase in demand for new energy, new types of energy storage devices have rapidly developed in recent years. Currently, new energy batteries led by lithium-ion batteries have begun to be applied in the automotive field. However, lithium-ion batteries suffer from issues such as low energy density, slow charging rates, and short operational lifespans. To mitigate and address the drawbacks of lithium-ion batteries, researchers have begun developing supercapacitors. This article first categorizes and compares some common energy storage devices, concluding that supercapacitors have significant advantages in charging rates and stability. Then, based on the dimensionality of nanomaterials, it categorizes and compares electrode materials used in supercapacitors, discussing three ways of constructing electrodes using 1D, 2D, and 1D-2D combined materials. Through classification, comparison, and discussion, it ultimately concludes that growing nanomaterials on a millimeter-scale structural substrate effectively increases material specific surface area and stability, thereby greatly enhancing the performance of supercapacitors.

Morels ranks first among the world’s four famous bacteria.Morels is a kind of rare edible and medicinal fungi that can be cultivated artificially in recent years. It has a variety of nutrients, has rich cultural deposits and a long history in Europe and China, and has high value in edible and medicinal health care. Morels is widely distributed, the growth environment conditions are harsh, the number is relatively rare, the individual is small, the price is higher, and there is a higher status in fungi, with the shape like the belly named. At present, the development and utilization of morels has not reached to a good level. This paper expounds the nutritional composition, edible value and medicinal value of mochella as a whole to further deepen people’s cognition and understanding of mochella. And summarizes the development status and existing problems of mochella industry, in order to provide more theoretical reference for mochella in medical care and product development.

To address the challenges faced by vehicles during actual operation when passing through traffic lights or intersections, where rapid changes in operating conditions can lead to a decrease in SCR efficiency and an increase in NOx emissions, this study focuses on defining characteristic position scenarios and analyzing the NOx emission characteristics of vehicles when passing through these scenarios based on real-time vehicle conditions. Through the analysis of several specific events, several road condition factors and driver behavior factors that may contribute to increased NOx emissions at characteristic position scenarios are identified. The findings indicate that when vehicles pass through traffic lights and intersections, the main causes of increased NOx emissions are low SCR temperature resulting from prolonged idling or engine shutdown, and high exhaust NOx emissions resulting from sudden excessive fuel injection. The driver behaviors associated with these situations primarily include coasting when approaching intersections, frequent stop-start behaviour due to traffic congestion or road crowding, choosing to shut off the engine for fuel efficiency during prolonged traffic congestion, and aggressive acceleration by stepping on the accelerator when the green light is about to turn red.

A T-shaped chip-scale micromixer with built-in baffles is simulated and investigated based on ANSYS. This paper highlights on a comparative analysis of the effect of different numbers, rows, positions, angles and different Reynolds numbers (Re) of baffles on the mixing efficiency within a chip-scale micromixer. The simulation results demonstrate that: increase in the amount of baffles improved mixing of two fluids; the double rows of baffles significantly improve the mixing efficiency compared with the single rows of baffles; the position of the baffles relocates a certain distance to the outlet, which accelerates mixing of fluids in the chip-scale mixer; the mixing efficiency of baffle angle of 120° is also superior to that of 60°; the Re is between 0.1 and 2, which results in a high mixing efficiency; and the mixing efficiency slowly becomes lower when the Re is between 2 and higher mixing efficiencies with Re values between 0.1 and 2; Re between 2 and 40, the mixing efficiency slowly becomes lower; Re between 40 and 100, the mixing efficiency gradually rises.

The fluid-structure interaction problem of cylindrical flow around the cylinder is a classic problem, especially in many fields such as energy engineering, fluid dynamics, engineering structure, energy utilization and development, and environmental protection. In this article, we have heard about the simplified model and analyzed it with the help of the classical cylindrical flow model. In this paper, the flow field was pre-processed on the Workbench software platform, and the pressure distribution and eddy current phenomenon were observed by post-processing given the velocity of the flow field of 1m/s. There is a large number of thunder (2.799552×106) and the Carmen Vortex appears around the cylinder. The vortex falls off periodically, and the wake structure is relatively irregular. The maximum pressure appears at the bottom of the cylinder and the maximum deformation at the top. Then, the pressure term of the simulation results was transferred to the Ansys solver for finite element structural analysis to observe the stresses and strains of the structure under the action of fluids. Finally, the response signal is based on Variational Mode Decomposition (VMD). Its periodic signal corresponded to the flow field, and its components were analyzed in detail. The application of VMD in this area provides innovative inspiration for related fields.

In order to improve the efficiency of traffic flow and reduce the delay of arterial intersections, a coordinated signal control method based on numerical solution is proposed. Firstly, considering the factors such as the shortest green time and saturation of a single intersection, the intersection delay model is established. Secondly, the traffic capacity of the trunk line is improved by optimizing the public cycle and the green ratio of each intersection. Finally, an optimization model with minimum delay as the optimization objective is constructed, and the signal coordination of arterial intersections is realized by taking Yancheng City as an example. The results show that the coordinated control model of adjacent intersections based on the numerical method can reduce the average vehicle delay of two-way vehicles, achieve the purpose of green wave coordinated control of road sections, and improve the road traffic capacity.

The sustainable development of container rail-water intermodal transport in China faces a series of deep-seated constraints. In this paper, we quantitatively summarize the development status of container rail-water intermodal transportation in China’s ports. Next, the typical problems faced by the sustainable development of rail-water intermodal transport are analyzed from the bottom constraints and direct constraints. Finally, this paper proposes strategic ideas to promote sustainable development of rail-water intermodal transport, taking into account network layout, technical equipment, data exchange rules, and policy environment.

As the demand for fresh food products among Chinese residents grows rapidly, the development of cold chain logistics has ushered in a “golden age.” Using PEST analysis tool, this paper comprehensively analyzes the development environment of cold chain logistics in China from the four dimensions of politics, economy, society and technology, analyzes the outstanding problems existing in the development of cold chain logistics in infrastructure, standard system and information construction, and puts forward countermeasures and suggestions to promote the high-quality development of cold chain logistics from three aspects: strengthening the guidance of infrastructure, standard guarantee and technology empowerment.

Under the background of China's rapid economic development and accelerated urbanization process, the construction industry has been fully developed. However, due to the characteristics of extensive production in the construction industry, a large amount of construction waste is generated. This paper relies on the centralized resettlement project of Zhanjie Town in Gongyi City. Through the research on the key technologies such as the reuse of pile head, the reuse of steel bar head and the recycling of construction waste in engineering practice, the practical methods of construction waste recycling are analyzed, so as to better carry out the recycling of construction waste.

Under the new development, new opportunities and new models, China attaches more importance to the green development of enterprises, green and low-carbon development is becoming more and more important in the strategic position. This paper adopts the method of case study, analyzes the relationship among the motivation, mode and performance of green innovation, divides green innovation behavior into various types, and makes a comparative study on the difference of green innovation mode and performance of typical enterprises with different characteristics in Shaoxing, Zhejiang Province. It is found that the environmental performance, financial performance and market performance brought by substantive green innovation achieve the best effect, and the financial performance brought by strategic green innovation is better, but the change of environmental performance and market performance is relatively not obvious, and the financial performance and market performance brought by irritable green innovation have no obvious change, and the environmental performance brought by environmental innovation is also average.

Background: The COVID-19 pandemic has spotlighted the face mask as an intricate object constructed through the uptake of varied and sometimes competing discourses. We investigated how the concept of face mask was discursively deployed during the first phase of the COVID-19 pandemic. By examining the different discourses surrounding the use of face masks in public domain texts, we comment on important educational opportunities for medical education. Method: We applied critical discourse methodology to look for key phrases related to face masks that can be linked to specific socio-economic and educational practices. We created an archive of 171 English and Mandarin texts spanning the period of February to July 2020 to explore how discourses in Canada related to discourses of mask use in China, where the pandemic was first observed. We analyzed how the uptake of discourses related to masks was rationalized during the first phase of the pandemic and identified practices/processes that were made possible. Results: While the face mask was initially constructed as personal protective equipment, it quickly became a discursive object for rights and freedoms, an icon for personal expression of political views and social identities, and a symbol of stigma that reinforced illness, deviance, anonymity, or fear. Conclusion: Discourses related to face masks have been observed in public and institutional responses to the pandemic in the first wave. Finding from this research reinforce the need for medical schools to incorporate a broader socio-political appreciation of the role of masks in healthcare when training for pandemic responses.

This study examines the effects of the Education Welfare Priority Zone Program (ewpzp) on how elementary school students adjust to school in South Korea. Principal stratification and propensity score approaches were employed on a sample of 1,237 students. The results suggest that recipients of Priority Support (ps, a customised care programme offered to ewpzp students with special needs) reported increases in their perceptions of teacher interest. Teacher interest directly and indirectly improved the students’ class attitudes and social skills. Second, non-ps students in ewpzp schools showed appreciable improvement. Suggestions for improving ewpzp implementation are also made based on these findings.

Abstract Background Goat, one of the first domesticated livestock, is a worldwide important species both culturally and economically. The current goat reference genome, known as ARS1, is reported as the first nonhuman genome assembly using 69× PacBio sequencing. However, ARS1 suffers from incomplete X chromosome and highly fragmented Y chromosome scaffolds. Results Here, we present a very high-quality de novo genome assembly, Saanen_v1, from a male Saanen dairy goat, with the first goat Y chromosome scaffold based on 117× PacBio long-read sequencing and 118× Hi-C data. Saanen_v1 displays a high level of completeness thanks to the presence of centromeric and telomeric repeats at the proximal and distal ends of two-thirds of the autosomes, and a much reduced number of gaps (169 vs. 773). The completeness and accuracy of the Saanen_v1 genome assembly are also evidenced by more assembled sequences on the chromosomes (2.63 Gb for Saanen_v1 vs. 2.58 Gb for ARS1), a slightly increased mapping ratio for transcriptomic data, and more genes anchored to chromosomes. The eight putative large assembly errors (1 to ~ 7 Mb each) found in ARS1 were amended, and for the first time, the substitution rate of this ruminant Y chromosome was estimated. Furthermore, sequence improvement in Saanen_v1, compared with ARS1, enables us to assign the likely correct positions for 4.4% of the single nucleotide polymorphism (SNP) probes in the widely used GoatSNP50 chip. Conclusions The updated goat genome assembly including both sex chromosomes (X and Y) and the autosomes with high-resolution quality will serve as a valuable resource for goat genetic research and applications.

Based on discrete element method (DEM), three kinds of soil–rock mixture (SRM) models with different coarse particle contents were established and triaxial compression tests were carried out. The results show that the force chains in the particle system playing the main bearing role need more lateral supports, which results in the contact with a higher coordination number and often bear larger contact force. The relationship between the contact’s carrying capacity and the coordination number can be fit by a quadric surface. Taking the fit quadric surface as the capacity function, the network-flow model of force transfer can be constructed to quantify the force transfer ability of a contact network. By connecting the maximum flow in the network with the hardening parameter of the unified hardening model, the stress–strain relationship of SRM can be predicted to some extent, which lays a basis for formulating micro–macro constitutive model for granular materials.

Single metal catalysts with different active components (La, Sm, Ce) and La loadings (5%, 10%, 15%) were prepared. Oxydehydrogenation of C2H6 with CO2 over the above catalysts was studied by catalyst activity experiments and characterization tests. The results indicate that the homogeneous reaction of CO2/C2H6 is the coupling of ethane pyrolysis and hydrogenolysis. Dehydrogenation has better selectivity than reforming on La/Sm/Ce-based catalysts; Sm exhibits the best catalytic activity due to carbon deposition resistance and many oxygen vacancies. C2H6 conversion on 10% Sm/SiO2 is 42.75% at 700 °C, but C2H4 selectivity is lowest. Because of the existence of $\mathrm{Ce}^{4+}$, Ce has the best C2H4 selectivity; it has potential to modify the catalyst, but its catalytic activity is lowest. La shows the best catalytic performance. The activation energy on 10% La/SiO2 is 83.99 kJ/mol, C2H4 selectivity is 96.84% at 700 °C, and its optimum loading is between 10% and 15%.

With the improvement of automation degree of coal mine mechanical and electrical equipments, such as conveyors, crushers, mining motors, inverters, and a large number of non-linear loads, cause large reactive power consumption, power factor of coal mine power grid, power supply quality and stability, and bring greater influence to coal mine safety production and economic benefits. As a new generation of high voltage dynamic reactive power compensator, SVG (Static Var Generator) has fast response and compound functions, such as compensating reactive power, suppressing harmonic and imbalance with FC(Filter Capacitor), which plays a good role in improving the power quality of coal mine. This paper designs the system parameters of SVG in coal mine and introduces its application.

This article takes the knowledge module of part sketch surveying in Mechanical Drawing as an example to explore the BOPPPS teaching mode and the “cloud on screen” remote learning application that combines MOOC, virtual technology, and smart classroom. Based on the six teaching links in the BOPPPS teaching mode, the case implementation process is analyzed and summarized. Practice has shown that in the project-based teaching process, the use of a new teaching mode that combines the BOPPPS teaching mode and information based teaching methods can effectively improve the remote teaching level of teachers and the remote learning effect of students.

Offering reference for sustainable researches of psychological warning field by analyzing hotspots in it in the latest decade. 589 literatures relevant to psychological warning conformed to standard, were extracted keywords. Cooccurrence matrix and lexical matrix were exported by using python software, and the correlations among high frequency keywords were received by analyzing the combination between social network and semantic network which also drew the semantic network graph. The hierarchical clustering function was used to draw the high frequency keywords clustering analysis diagram, and the Eucidean range model was used to draw the two-dimensional scale analysis graph. The combination between co-word analysis and knowledge graph revealed, explored, and summarized the current research hotspots and their relationships in the field of psychological warning. Hotspots research showed the necessity of researches in the psychological warning field. The construction of psychological warning evaluation system and the analysis of key elements of psychological warning should be attached importance.

In order to comprehensively improve the digital level of soil and water conservation in Anji County, it is necessary to realize the "one map management" of soil and water conservation by the information sharing and interaction among multiple government departments. With the new generation of information technologies such as big data, digital twin, artificial intelligence and virtual reality, use "11143" as the construction framework, improve the data warehouse of soil and water conservation to achieve "one map management" of the whole life cycle of production and construction projects; monitor soil erosion in real time through satellite remote sensing data and provide early warning and forecasting; and dock with the national "double carbon" strategy to build a carbon sink management system for soil and water conservation. It is expected to be built into a water and soil conservation wisdom management platform that meets multiple business application scenarios such as supervision of production and construction projects, dynamic monitoring and comprehensive management of soil erosion, wisdom decision making and application, and industry promotion services.

Various experiments about obedience and disobedience to authority have been taken place in the past decades. However, it is a brand new task for academics where genders and types of authorities are on cross analysis. Are female more likely to obey to educated professionals or severe dominators? Will genders affect people’s attitudes to the governors? In this work, an experiment is designed based on Milgram’s original experiment of obedience, in order to answer the answers previously mentioned. Different reactions from different genders will be tested when they are facing prestige or dominance authorities separately. The method of testing level of obedience is altered from the original electric shock experiment taken by Milgram to a new method of using hot sauce to measure participants’ obedience to authorities. The hypothesis in existence suggested that females will show a higher level of obedience to dominance authorities rather than prestige authorities, and their obedience to dominant authorities will be relatively high comparing to males, while males will show a higher level of obedience to prestige authorities than dominant authorities, and showing relatively high obedience to prestigious authorities. This work aims to show a new way to understand gender difference in behaviors, and wish to open a gate of behaviour study and gender cognition study.

Global warming has an impact on building performance, and it is very important to explore the optimization of building performance under future climate change conditions. The study generates 2050s typical meteorological year (TMY) data of different cities (Harbin, Beijing, Shanghai, Shenzhen) representing the future climate. Taking energy consumption, thermal comfort, and initial investment cost as the objective function, the Back Propagation (BP) neural network and non-dominated sorting genetic algorithm (NSGA-Ⅱ) were used to optimize the key parameters of the building envelope of representative cities in different climate regions of China and to obtain the Pareto curve. The final solution is obtained by the weighted sum method (WSM). The results show that, except for the type of windows, the optimal configuration of the building envelope in each city is different. Compared with the results of reference buildings, the final results of each city reduces energy consumption by 14.5~24.0 % and improves thermal comfort by 23.8~34 % when the initial investment cost increases by 27.0~35.3 %. The method proposed in this paper has reference significance for the optimization of building envelope in different climatic regions of China under the future climate.

In this paper, taking a typical office building in Chengdu as an example, the coupling relationship between the radiation properties (short-wave absorption coefficient and long-wave emission coefficient) of the external surface materials of the wall and the insulation types and the insulation performance is studied by using software simulation method. The results show that the internal insulation wall is beneficial to reduce the heating load while the external insulation wall is beneficial to reduce the cooling load. And the external surface material's radiative properties hardly affect the wall insulation type choice. Still, in the case of Chengdu office buildings, interior insulated walls are more conducive to year-round building energy efficiency. In summer, the radiation characteristics of the outer surface material will affect the choice of the best heat transfer coefficient (U-value) of the wall. When the short-wave radiation absorption coefficient is small, the wall with good insulation performance will appear anti-energy-saving phenomenon. Therefore, it is recommended that the regions with high cooling loads fully consider the influence of the external surface material's radiation properties on the wall's thermal performance in the design of the thermal performance of the wall.

The traditional automatic monitoring method of salt spray concentration has a weak anti-interference ability, which affects the monitoring accuracy. Therefore, a remote automatic monitoring method of atmospheric salt fog concentration based on optical sensor is designed. Determine the optical power loss of salt fog remote monitoring in atmospheric environment, and obtain the relationship between optical power loss and salt density, environmental humidity. Based on optical sensing, a quartz rod monitoring and early warning model under high salt fog environment is established to increase the surface area of the quartz rod, thus improving the anti-interference ability of the remote automatic monitoring device. The simulation experiment verifies that the monitoring method has higher monitoring accuracy and can be applied in real life.

Macvlan and IPvlan modes allow the host physical Network Interface Card (NIC) to create several virtual sub interfaces, which can meet the containers communication requirements across different network segment in complex application scenarios. The paper describes the architecture characteristics of these two modes in depth and builds container overlay network in single machine and multi machine environments. Around the key network indicators such as round-trip time (RTT), bandwidth and jitter, Ping and Iperf tools are used to test and analyse the end-to-end container communication performance. The experimental results show that IPvlan mode has better network performance and provides a comprehensive and rich application scenario for the container overlay network.

This paper examines the causal relationship between interest rate differential (IRD) and international short-term capital flow (SCF) to determine whether such a relationship in China supports the Mundell-Fleming model. With structural changes existing, we find that long-run relationship using full-sample data is unstable, suggesting that causality test is not reliable. Consequently, we use a time-varying rolling-window approach to revisiting the dynamic causal relationship, and the results show that IRD has both positive and negative impacts on SCF in several sub-periods, but SCF has no effect on IRD in China. When China suffers external and internal shocks, SCF should not be curbed only by adjusting IRD. Therefore, it is critical for policymakers to pay attention to specific backgrounds (e.g. economic situation, monetary policies) and further employ interest rate and fiscal policies in reducing negative influence from SCF on the Chinese economy.

Background: While the Public Health Agency of Canada notes 19 cases from May 2019 to February 2020 relating to e-cigarette or vaping product use-associated lung injury (EVALI) in Canada, there are likely many more unreported cases, including non-hospitalized and asymptomatic cases. E-cigarette use or vaping exposes users to numerous aerosolized chemical species, some of which have proven to be deleterious to health. These chemical species can include vitamin E acetate (VEA), flavourants, base / solvents (propylene glycol or vegetable glycerin), psychoactive substances, pesticides, endotoxins, metals, and pyrolysis by-products from e-cigarette heating coils. Objectives: We aim to review current findings related to EVALI from the standpoint of known chemical species currently used in vaping products. We specifically examine the toxicological profiles of these chemical species and the mechanisms through which they cause lung injury. Methods: A comprehensive literature search was performed with MEDLINE for EVALI-related human studies that were published between January 1, 2010, and May 15, 2020. This search strategy identified 832 case reports, case series, clinical trials, and in-vitro laboratory studies. From this group, 71 records were examined in greater detail. Results and Conclusions: Although the chemical composition and toxicology of vaping products have largely been characterized, the physiological effects of the chemical interactions between various constituents of vaping products and the generation of new species remain inconclusive. Given the rapid increase in the popularity of vaping and e-cigarettes, there is a need for further research. Developing a comprehensive understanding of the chronic health effects of vaping through randomized controlled trials and physiological studies is prudent and necessary to reduce the long-term impacts on users and the health care system.

The LOF data anomaly detection method has some defects, such as the value of k has great influence on the accuracy of detection results, and the selection of k value usually adopts trial method, which consumes a lot of calculation time. Therefore, this paper proposes an anomaly detection method for LOF data based on sample parameter selection, Tagged according to the sample data set point of normal and abnormal point, the adaptive selection of k value and outlier detection, so as to improve the accuracy of data outlier detection and calculation speed, and through the example of meteorological data outliers detection showed that LOF abnormal data points based on sample parameter selection method in the detection accuracy and reliability are improved significantly.

Layered Li-rich cathode oxides can provide high specific capacity due to oxygen anion redox involving in charge compensation process during cycling, but there is a severe structural transition from layered to spinel accompanying with irreversible oxygen loss during cycling, which lead to electrochemical degradation. The current researches show that the irreversible oxygen evolution reaction of layered lithiumrich materials in the first cycle mainly comes from the surface lattice oxygen, so the surface modification by the materials with more stable structure is one of the effective ways to improve the electrochemical performance of layered lithium-rich materials. In this paper, we report a modified layered lithium-rich cathode material by surface coating of inverse spinel MnFe2O4. The inverse spinel has strong polarization effect on anion migration due to its different atoms occupying octahedral sites from layered structure and it can also modulate the Fermi level and stretching the O-O bond, thereby increasing the energy barrier for surface oxygen oxidization. Furthermore, the three-dimensional connected tunnel structure of the inverse spinel also makes the surface layer of the material have a faster lithium ion transferring rate, and a large number of lithium storable vacancies inside of it improved the Li+ intercalation efficiency, initial coulombic efficiency and rate performance. Compared with the unmodified sample, the modified material coated with 2% MnFe2O4 has superior cycle stability and outstanding rate performance. It is hoped our work would provide the knowledge for the future development of high-performance cathode materials for Li-ion batteries.

With the development of science and technology and the progress of society, various high and new technologies have increasingly shown their respective advantages. Among them, geophysical prospecting technology is a typical representative. Because it can greatly improve the speed and efficiency of engineering, and at the same time, it also plays an important role in engineering safety and prevention. Therefore, it is widely promoted and applied, especially in engineering survey work. This article studies the importance of geophysical prospecting in engineering exploration, the methods of geophysical prospecting technology, the application of geophysical prospecting technology, and the development trend of geophysical prospecting technology. How to better understand the application of geophysical prospecting technology and rationally choose working methods and methods, so as to serve the geological exploration work to the utmost extent, is an important topic that needs to be solved and studied urgently.

Volatile organic compounds (VOCs) emitted from many industrial processes, are harmful to human health and the atmsphere. Several technologies are currently used to eliminate VOCs from the environment. Among them, catalytic oxidation has been recognized as one of the most efficient and promising ways to treatment VOCs. So high performance oxidants play an dominant role in the catalytic oxidation process. In this work, we discussed many researchers’ works about preparation and effect of their catalysts, kinds of mesoporous catalysts for eliminating VOCs were reviewed, the active components of the catalysts are noble and non-noble metal oxides, which loaded in the mesochannels of mesoporous materials including silica, titania and aluminia.

In frozen regions, especially metro tunnel portal sections, which are vulnerable to an externally low-temperature atmosphere, would lead to frozen damage affecting traffic safety. To clarify how the air temperature field at tunnel portal sections varies with periodically changing atmospheric temperature, a site test was conducted on Metro Line 1 in Hohhot in the Inner Mongolia Autonomous Region, and the basic heat transfer equation and principle of energy conservation were introduced to establish a basic theoretical model, which was compared with the results from other regions. By comparison with testing results in other regions, the theoretical model was essentially consistent with the variation rules of the tested temperature. Therefore, the research could theoretically direct the heat preservation and freeze prevention of key facilities and equipment in metro tunnel portal sections in frozen regions.

Based on the boundary conditions obtained from the actual measurements during the infrastructure period of Jinghe Dongzhuang Power Station, a calculation model of the predicted bus bar hole environment was established, and a full-scale numerical simulation of the bus bar hole environment was performed based on CFD to analyze the effect of air supply velocity changes on the temperature and velocity fields in the working area. The ventilation effect is evaluated and compared by calculating the inhomogeneity coefficient and air distribution characteristic index. The study shows that an appropriate increase in air velocity can reduce the thermal impact of the internal heat source on the surrounding environment and can effectively control the air quality in the work area. Considered comprehensively, the work area has better comfort when V/V0 is slightly greater than 1. The research results have some guiding significance for the design of bus bar hole air supply system in Jinghe Dongzhuang Power Station.

Machine learning is a method generally used in defect detection of smart manufacturing. It uses data and algorithms to simulate the function of human’s brain, and the accuracy can be improved by repeated machine training. Neural networks such as convolutional neural network is an effective method used in machine learning to achieve defect detection in smart manufacturing. Through a systematic lecture review, this gives the architecture of the convolutional network and provides its model, which includes three layers: convolution layer, pooling layer and fully-connected layer, whose functions are determining the way of the neurons network connections, reducing the amount of parameters within activations by downsampling along with the spatial dimensionality of the inputs and produce class scores from the activations as well as suggesting the usage of Rectified Linear Unit to improve performance respectively, then points out two challenges of applying convolutional neural network in practical of defect detection, which is the class imbalance problem and insufficient data problem. Following these problems, three solutions namely, Objectlevel Attention Mechanism; PaDiM and SDD-CNN are discussed. In addition, this paper also identifies the topics for future study at the end.

Abstract Background The number of teats in pigs is related to a sow’s ability to rear piglets to weaning age. Several studies have identified genes and genomic regions that affect teat number in swine but few common results were reported. The objective of this study was to identify genetic factors that affect teat number in pigs, evaluate the accuracy of genomic prediction, and evaluate the contribution of significant genes and genomic regions to genomic broad-sense heritability and prediction accuracy using 41,108 autosomal single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing on 2936 Duroc boars. Results Narrow-sense heritability and dominance heritability of teat number estimated by genomic restricted maximum likelihood were 0.365 ± 0.030 and 0.035 ± 0.019, respectively. The accuracy of genomic predictions, calculated as the average correlation between the genomic best linear unbiased prediction and phenotype in a tenfold validation study, was 0.437 ± 0.064 for the model with additive and dominance effects and 0.435 ± 0.064 for the model with additive effects only. Genome-wide association studies (GWAS) using three methods of analysis identified 85 significant SNP effects for teat number on chromosomes 1, 6, 7, 10, 11, 12 and 14. The region between 102.9 and 106.0 Mb on chromosome 7, which was reported in several studies, had the most significant SNP effects in or near the PTGR2, FAM161B, LIN52, VRTN, FCF1, AREL1 and LRRC74A genes. This region accounted for 10.0% of the genomic additive heritability and 8.0% of the accuracy of prediction. The second most significant chromosome region not reported by previous GWAS was the region between 77.7 and 79.7 Mb on chromosome 11, where SNPs in the FGF14 gene had the most significant effect and accounted for 5.1% of the genomic additive heritability and 5.2% of the accuracy of prediction. The 85 significant SNPs accounted for 28.5 to 28.8% of the genomic additive heritability and 35.8 to 36.8% of the accuracy of prediction. Conclusions The three methods used for the GWAS identified 85 significant SNPs with additive effects on teat number, including SNPs in a previously reported chromosomal region and SNPs in novel chromosomal regions. Most significant SNPs with larger estimated effects also had larger contributions to the total genomic heritability and accuracy of prediction than other SNPs.

This note corrects an issue that has been identified in the article in Comptes Rendus Chimie with the above title. It was published online on 6th June 2020 in Volume 23, Issue 1, 2020, pages 33–46, https://doi.org/10.5802/crchim.4.