A failure criterion for shale considering the anisotropy and hydration based on the shear slide failure model

A failure criterion fully considering the anisotropy and hydration of shale is essential for shale formation stability evaluation.Thus,a novel failure criterion for hydration shale is developed by using Jaeger’s shear failure criterion to describe the anisotropy and using the shear strength reduction caused by clay minerals hydration to evaluate the hydration.This failure criterion is defined with four parameters in Jaeger’s shear failure criterion(S_(1),S_(2),a andφ),three hydration parameters(k,ω_(sh)andσ_(s))and two material size parameters(d and l0).The physical meanings and determining procedures of these parameters are described.The accuracy and applicability of this failure criterion are examined using the published experimental data,showing a cohesive agreement between the predicted values and the testing results,R^(2)=0.916 and AAREP(average absolute relative error percentage)of 9.260%.The error(|D_(p)|)is then discussed considering the effects ofβ(angle between bedding plane versus axial loading),moisture content and confining pressure,presenting that|Dp|increases whenβis closer to 30°,and|D_(p)|decreases with decreasing moisture content and with increasing confining pressure.Moreover,|D_(p)|is demonstrated as being sensitive to S1and being steady with decrease in the data set whenβis 0°,30°,45°and 90°.

Investigation of Electrical Parameters of Fresh Water and Produced Mixed Injection in High-Salinity Reservoirs

Assuming a reservoir with a typical salt-lake background in the Qaidam Basin as a testbed,in this study the var-iation law of the rock electrical parameters has been determined through water displacement experiments with different salinities.As made evident by the results,the saturation index increases with the degree of water injec-tion.When the salinity of the injected water is lower than 80000 ppm,the resistivity of the rock samplefirst decreases,then it remains almost constant in an intermediate stage,andfinally it grows,thereby giving rise to a‘U’profile behavior.As the salinity decreases,the water saturation corresponding to the inflection point of the resistivity becomes lower,thereby leading to a wider‘U’type range and a higher terminal resistivity.For dif-ferent samples,higher initial resistivity of the sample in the oil-bearing state,and higher resistivity after low-sali-nity water washing are obtained when a thicker lithology is considered.

Genome sequencing provides potential strategies for drug discovery and synthesis

Medicinal plants are renowned for their abundant production of secondary metabolites,which exhibit notable pharmacological activities and great potential for drug development.The biosynthesis of secondary metabolites is highly intricate and influenced by various intrinsic and extrinsic factors,resulting in substantial species diversity and content variation.Consequently,precise regulation of secondary metabolite synthesis is of utmost importance.In recent years,genome sequencing has emerged as a valuable tool for investigating the synthesis and regulation of secondary metabolites in medicinal plants,facilitated by the widespread use of high-throughput sequencing technologies.This review highlights the latest advancements in genome sequencing within this field and presents several strategies for studying secondary metabolites.Specifically,the article elucidates how genome sequencing can unravel the pathways for secondary metabolite synthesis in medicinal plants,offering insights into the functions and regulatory mechanisms of participating enzymes.Comparative analyses of plant genomes allow identification of shared pathways of metabolite synthesis among species,thereby providing novel avenues for obtaining cost-effective biosynthetic intermediates.By examining individual genomic variations,genes or gene clusters associated with the synthesis of specific compounds can be discovered,indicating potential targets and directions for drug development and the exploration of alternative compound sources.Moreover,the advent of gene-editing technology has enabled the precise modifications of medicinal plant genomes.Optimization of specific secondary metabolite synthesis pathways becomes thus feasible,enabling the precise editing of target genes to regulate secondary metabolite production within cells.These findings serve as valuable references and lessons for future drug development endeavors,conservation of rare resources,and the exploration of new resources.

高职教育:育人环境与环境育人

高职院校要实现高质量发展,就必须优化育人环境、强化环境育人。育人环境是教育生态的系统映射,不仅反映了宏观环境系统与教育的交互关系,也反映了微观环境系统对教育的深刻影响;环境育人则是育人体系的物化结果,在物质基础之外还承载着课程、科研、实践、文化、网络、心理、管理、服务、资助、组织等诸多育人体系的"审美创造",并通过"审美移情"的心理机制,最终作用于"人"的培养。对于职业教育而言,校、企构成了育人的两大主体,而企业文化体现了职业环境的核心特征,要发挥企业育人的主体作用,还须导入企业文化,充分挖掘其环境育人的主体价值。

Machine Learning−based Weather Support for the 2022 Winter Olympics

1.A key support for the 2022 Winter Olympics The XXIV Olympic Winter Games are scheduled to take place from 4 to 22 February 2022,followed by the Paralympic Games from 4 to 13 March,in Beijing and towns in the neighboring Hebei Province,China.Weather plays an extremely important role in the outcome of the games(Chen et al.,2018).It can not only cause a difference between a medal or not,but affect the safety of athletes.Success of the Winter Olympics will greatly depend on weather conditions at the outdoor competition venues,dealing with many weather elements including the snow surface temperature,apparent temperature,gust wind speed,snow,visibility,etc.To ensure that the scheduled games go smoothly,it is imperative to have hourly or even every 10-minutely forecasts as well as updated weather-related risk assessments at the venues for the next 240 hours.So far,the Beijing/Hebei Meteorological Observatory has already started intelligent weather forecasting at 3-km resolution based on the results of numerical weather prediction(NWP)models.However,these experiments have suggested that the current forecasting techniques are incapable of capturing the complex mountain weather variations around some venues.The forecasting capability of NWP is constrained partly by limited knowledge of the local weather mechanisms.

Recent progress in porous organic polymers and their application for CO_(2) capture

Carbon capture,storage,and utilization(CCSU)is recognized as an effective method to reduce the excessive emission of CO_(2).Absorption by amine aqueous solutions is considered highly efficient for CO_(2) capture from the flue gas because of the large CO_(2) capture capacity and high selectivity.However,it is often limited by the equipment corrosion and the high desorption energy consumption,and adsorption of CO_(2) using solid adsorbents has been receiving more attention in recent years due to its simplicity and high efficiency.More recently,a great number of porous organic polymers(POPs)have been designed and constructed for CO_(2) capture,and they are proven promising solid adsorbents for CO_(2) capture due to their high Brunauer-Emmett-Teller(BET)surface area(SBET),adjustable pore size and easy functionalization.In particular,they usually have rigid skeleton,permanent porosity,and good physiochemical stability.In this review,we have a detailed review for the different POPs developed in recent years,not only the design strategy,but also the special structure for CO_(2) capture.The outlook of the opportunities and challenges of the POPs is also proposed.

Integrated energy corridor:a comprehensive proposal of the low-carbon transition for China Energy Group

New energy is considered to be an indispensable means to significantly reduce carbon emissions and to achieve the temperature-control goals defined by the Paris Climate Accord.Despite the bright future,the inherent characteristics,including volatility,intermittency and uneven seasonal and geographical distributions,and the rapid growth of installations make it increasingly difficult to connect green electricity to grids.This becomes a dominating bottleneck for the low-carbon transition of China Energy Group(CE).This paper aims to help with the implementation of the new-energy development plan and to define the low-carbon energy-transition path for CE.Based on the current industry structure of CE,Shenhua Engineering Technology Co.,Ltd proposes the concept of an‘integrated energy corridor’.The integrated energy corridor represents a comprehensive energy-transmission channel with coal,green electricity,green hydrogen,green oxygen and other green energy products such as transmission media,railways,pipelines and power grids as transmission means and thermal power,coal chemical plants,cities,etc.along the route as new-energy consumers and regulators.The integrated energy corridor can support the rapid development of new-energy assets and the low-carbon transition of CE.

Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory

Unmanned Aerial Vehicle(UAV)swarms have been foreseen to play an important role in military applications in the future,wherein they will be frequently subjected to different disturbances and destructions such as attacks and equipment faults.Therefore,a sophisticated robustness evaluation mechanism is of considerable importance for the reliable functioning of the UAV swarms.However,their complex characteristics and irregular dynamic evolution make them extremely challenging and uncertain to evaluate the robustness of such a system.In this paper,a complex network theory-based robustness evaluation method for a UAV swarming system is proposed.This method takes into account the dynamic evolution of UAV swarms,including dynamic reconfiguration and information correlation.The paper analyzes and models the aforementioned dynamic evolution and establishes a comprehensive robustness metric and two evaluation strategies.The robustness evaluation method and algorithms considering dynamic reconfiguration and information correlation are developed.Finally,the validity of the proposed method is verified by conducting a case study analysis.The results can further provide some guidance and reference for the robust design,mission planning and decision-making of UAV swarms.

Water regime-nitrogen fertilizer incorporation interaction：Field study on methane and nitrous oxide emissions from a rice agroecosystem in Harbin, China

Water regime and nitrogen（N） fertilizer are two important factors impacting greenhouse gases（GHG） emission from paddy field, whereas their effects have not been well studied in cold region. In this study, we conducted a two-year field experiment to study the impacts of water regime and N fertilizer on rice yields and GHG emissions in Harbin, China, a cold region located in high latitudes. Our results showed that intermittent irrigation significantly decreased methane（CH4） emission compared with continuous flooding, however,the decrement was far lower than the global average level. The N2O emissions were very small when flooded but peaked at the beginning of the disappearance of floodwater. The N fertilizer treatments increased CH4 emissions at low level（75 kg N/ha）. But both CH4 and N2O emissions were uninfluenced at the levels of 150 kg N/ha and 225 kg N/ha. Rice yields increased under intermittent irrigation and were highest at the level of 150 kg N/ha. From our results, we recommended that the intermittent irrigation and 150 kg N/ha as the ideal water regime-nitrogen fertilizer incorporation for this area to achieve low GHG emissions without impacting rice yields.

Active dry yeast supplementation improves the growth performance,rumen fermentation, and immune response of weaned beef calves

The objective of this experiment was to investigate the potential benefits of active dry yeast(ADY)on the growth performance,rumen fermentation,nutrient digestibility,and serum parameters of weaned beef calves.Thirty Simmental crossbred male calves(body weight=86.47±4.41 kg and 70±4 d of age)were randomly divided into 2 groups:control(CON)(fed basal ration)and ADY(fed basal ration and 5 g/d ADY per calf).The dietary concentrate-to-roughage ratio was 35:65.All the calves were regularly provided rations 3 times a day at 07:00,13:00,and 19:00 and had free access to wate r.The experiment lasted for 60 d.The average daily gain of ADY group was higher(P=0.007)than that of the CON group,and the ratio of feed intake to average daily gain in the ADY group was reduced(P=0.022)as compared to the CON group.The concentration of ruminal ammonia-N was higher(P=0.023)in the CON group than that in the ADY group,but an opposite trend of microbial protein was found between the 2 groups.Also,the ruminal concentrations of propionate and butyrate were higher(P<0.05)in the ADY group than those in the CON group.Calves fed ADY exhibited higher(P<0.05)crude protein and neutral detergent fiber digestibility.Supplementation of ADY increased(P<0.05)the contents of glucose,glutathione peroxidase,superoxide dismutase,immunoglobulin A,immunoglobulin M,and interleukin 10 in the serum of calves,but an opposite trend was observed in malondialdehyde,interleukin 1 beta,and tumor necrosis factor alpha contents between the 2 groups.In conclusion,dietary supplementation with ADY could improve the growth performance,rumen fermentation,nutrient digestibility,antioxidant ability,and immune response of weaned beef calves.

Unmanned aerial vehicle swarm mission reliability modeling and evaluation method oriented to systematic and networked mission

With the development of Unmanned Aerial Vehicle(UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of future applications. Traditional single-UAV mission reliability modeling methods have been unable to meet the requirements of UAV swarm mission reliability modeling. Therefore, the UAV swarm mission reliability modeling and evaluation method is proposed. First, aimed at the interdependence among the multiple layers, a multi-layer network model of a UAV swarm is established. At the same time, based on the system having the following characteristics—using a mission chain to complete the mission and applying the connectivity of the mission network—the mission network model of a UAV swarm is established. Second, vulnerability and connectivity are selected as two indicators to reflect the reliability of the mission, and aimed at random attack and deliberate attack, vulnerability and connectivity evaluation methods are proposed. Finally, the validity and accuracy of the constructed model are verified through simulations,and the model and selected indicators can meet the reliability requirements of the UAV swarm mission. In this way, this study provides quantitative reference for UAV-swarm-related decisionmaking work and supports the development of UAV-swarm-related work.