Objective:To investigate the differences between meditation and resting states using infrared thermal imaging(IRTI)to determine facial temperature distribution features during meditation and annotate the patterns of f...Objective:To investigate the differences between meditation and resting states using infrared thermal imaging(IRTI)to determine facial temperature distribution features during meditation and annotate the patterns of facial temperature changes during meditation from the perspective of traditional Chinese medicine facial diagnosis.Methods:Each participant performed 10 min meditation and 10 min resting but in different sequences.A concentration test was set as the task load,followed by a meditation/resting or resting/meditation session,during which the participants'facial temperatures were observed using IRTI.Participants were scored on the Big Five Inventory(BFI)and Mindful Attention Awareness Scale(MAAS).Results:Forehead temperatures decreased more during meditation than during the resting state.The chin temperature increased only during meditation(P<.0001).For the subjects with meditation experience,there were significant differences in the temperatures of the left forehead(P<.01),right forehead(P<.01)and chin(P<.05)between the meditation and resting state at the 10~(th)min.In the nontask state,the BFI-Extraversion showed a negative correlation with the temperature of the left forehead(R=-0.41,P=.03).In the post-task state,the temperature of the left forehead was negatively correlated with scores on the MAAS(R=-0.42,P=.02).Conclusion:Using IRTI to study meditation offers a practical solution to the challenges in meditation research.The results indicate that an increase in chin temperature may be a representative feature of a meditation state,and forehead temperature is also a potential indicator.展开更多
Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a nove...Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.展开更多
As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crud...As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.展开更多
Deepsea mining has been proposed since the 1960s to alleviate the lack of resources on land.Vertical hydraulic transport of collected ores from the seabed to the sea surface is considered the most promising method for...Deepsea mining has been proposed since the 1960s to alleviate the lack of resources on land.Vertical hydraulic transport of collected ores from the seabed to the sea surface is considered the most promising method for industrial applications.In the present study,an indoor model test of the vertical hydraulic transport of particles was conducted.A noncontact optical method has been proposed to measure the local characteristics of the particles inside a vertical pipe,including the local concentration and particle velocity.The hydraulic gradient of ore transport was evaluated with various particle size distributions,particle densities,feeding concentrations and mixture flow velocities.During transport,the local concentration is larger than the feeding concentration,whereas the particle velocity is less than the mixture velocity.The qualitative effects of the local concentration and local fluid velocity on the particle velocity and slip velocity were investigated.The local fluid velocity contributes significantly to particle velocity and slip velocity,whereas the effect of the local concentration is marginal.A higher feeding concentration and mixture flow velocity result in an increased hydraulic gradient.The effect of the particle size gradation is slight,whereas the particle density plays a crucial role in the transport.展开更多
Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is...Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.展开更多
First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism...First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.展开更多
Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calcu...Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.展开更多
Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical ener...Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.展开更多
Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq ...Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.展开更多
To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and obj...To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.展开更多
To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fer...To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.展开更多
Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirm...Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.展开更多
This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the at...This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.展开更多
Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital i...Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.展开更多
Soybean is one of the important crops in China. Soymilk, a traditional neutral plant-based protein drink, is rich in high quality proteins. Although soybean milk is rich in nutrients, its marketing among consumers, es...Soybean is one of the important crops in China. Soymilk, a traditional neutral plant-based protein drink, is rich in high quality proteins. Although soybean milk is rich in nutrients, its marketing among consumers, especially those in Western countries who are used to peaceful flavor, has been limited due to the adverse flavor impact brought by its special composition. In recent years, with the increasing attention to the nutritional value of soymilk, the flavor of soymilk has become a popular research object for scholars at home and abroad. The flavor components of soymilk are mainly volatile small molecular compounds produced by enzymatic reactions catalyzed by lipoxygenase(LOX). After formation, they interact with protein macromolecules to form the overall flavor of soymilk. At present, there are many methods to control the off-odor of soymilk at home and abroad, including physical heating methods, chemical methods, biological enzymatic digestion methods, mask methods, and a variety of breeding methods. These methods effectively reduce the off-odor of soymilk, but all of them have shortcomings. Currently, the sensory characteristics of the beany odor in soymilk are evaluated mainly by traditional human sensory scoring along with the assistance of modern instrument analysis of volatile flavor substances using headspace solid phase microextraction(SPME) gas chromatography coupled with-mass spectrometry(GC-MS). This paper summarized the research results of volatile flavor substances in soymilk in recent years and the sensory evaluation methods of soymilk at home and abroad, and looked forward to the future development direction, hoping to provide some theoretical bases and reference detection methods for solving the problem of soymilk flavor in the future.展开更多
The dynamic model of a bistable laminated composite shell simply supported by four corners is further developed to investigate the resonance responses and chaotic behaviors.The existence of the 1:1 resonance relations...The dynamic model of a bistable laminated composite shell simply supported by four corners is further developed to investigate the resonance responses and chaotic behaviors.The existence of the 1:1 resonance relationship between two order vibration modes of the system is verified.The resonance response of this class of bistable structures in the dynamic snap-through mode is investigated,and the four-dimensional(4D)nonlinear modulation equations are derived based on the 1:1 internal resonance relationship by means of the multiple scales method.The Hopf bifurcation and instability interval of the amplitude frequency and force amplitude curves are analyzed.The discussion focuses on investigating the effects of key parameters,e.g.,excitation amplitude,damping coefficient,and detuning parameters,on the resonance responses.The numerical simulations show that the foundation excitation and the degree of coupling between the vibration modes exert a substantial effect on the chaotic dynamics of the system.Furthermore,the significant motions under particular excitation conditions are visualized by bifurcation diagrams,time histories,phase portraits,three-dimensional(3D)phase portraits,and Poincare maps.Finally,the vibration experiment is carried out to study the amplitude frequency responses and bifurcation characteristics for the bistable laminated composite shell,yielding results that are qualitatively consistent with the theoretical results.展开更多
Contingent self-esteem captures the fragile nature of self-esteem and is often regarded as suboptimal to psychological functioning.Self-compassion is another important self-related concept assumed to promote mental he...Contingent self-esteem captures the fragile nature of self-esteem and is often regarded as suboptimal to psychological functioning.Self-compassion is another important self-related concept assumed to promote mental health and well-being.However,research on the relation of self-compassion to contingent self-esteem is lacking.Two studies were conducted to explore the role of selfcompassion,either as a personal characteristic or an induced mindset,in influencing the effects of contingent self-esteem on well-being.Study 1 recruited 256 Chinese college students(30.4%male,mean age=21.72 years)who filled out measures of contingent self-esteem,self-compassion,and well-being.The results found that self-compassion moderated the effect of contingent self-esteem on well-being.In Study 2,a sample of 90 Chinese college students(34%male,mean age=18.39 years)were randomly assigned to either a control or self-compassion group.They completed baseline trait measures of contingent self-esteem,self-compassion,and self-esteem.Then,they were led to have a 12-min break(control group)or listen to a 12-min self-compassion audio(self-compassion group),followed by a social stress task and outcome measures.The results demonstrated the effectiveness of the brief self-compassion training and its moderating role in influencing the effects of contingent self-esteem on negative affects after the social stress task.This research provides implications that to equip with a self-compassionate mindset could lower the risk of the impairment of well-being associated with elements of contingent selfesteem,which involves a fragile sense of self-worth.It may also provide insights into the development of an“optimal selfesteem”and the improvement of well-being.展开更多
Purpose – This study aims to analyze the factors, evaluation techniques of the durability of existing railwayengineering.Design/methodology/approach – China has built a railway network of over 150,000 km. Ensuring t...Purpose – This study aims to analyze the factors, evaluation techniques of the durability of existing railwayengineering.Design/methodology/approach – China has built a railway network of over 150,000 km. Ensuring thesafety of the existing railway engineering is of great significance for maintaining normal railway operationorder. However, railway engineering is a strip structure that crosses multiple complex environments. Andrailway engineering will withstand high-frequency impact loads from trains. The above factors have led todifferences in the deterioration characteristics and maintenance strategies of railway engineering compared toconventional concrete structures. Therefore, it is very important to analyze the key factors that affect thedurability of railway structures and propose technologies for durability evaluation.Findings – The factors that affect the durability and reliability of railway engineering are mainly divided intothree categories: material factors, environmental factors and load factors. Among them, material factors alsoinclude influencing factors, such as raw materials, mix proportions and so on. Environmental factors varydepending on the service environment of railway engineering, and the durability and deterioration of concretehave different failure mechanisms. Load factors include static load and train dynamic load. The on-site rapiddetection methods for five common diseases in railway engineering are also proposed in this paper. Thesemethods can quickly evaluate the durability of existing railway engineering concrete.Originality/value – The research can provide some new evaluation techniques and methods for thedurability of existing railway engineering.展开更多
Magnesium alloy is one of the lightest metal structural materials.The weight is further reduced through the hollow structure.However,the hollow structure is easily damaged during processing.In order to maintain the ho...Magnesium alloy is one of the lightest metal structural materials.The weight is further reduced through the hollow structure.However,the hollow structure is easily damaged during processing.In order to maintain the hollow structure and to transfer the stresses during the high temperature deformation,the sand mandrel is proposed.In this paper,the hollow AZ31 magnesium alloy three-channel joint is studied by hot extrusion forming.Sand as one of solid granule medium is used to fill the hollow magnesium alloy.The extrusion temperatures are 230℃ and 300℃,respectively.The process parameters(die angle,temperature,bottom thickness,sidewall thickness,edge-to-middle ratio in bottom,bottom shape)of the hollow magnesium alloy are analyzed based on the results of experiments and the finite element method.The results are shown that the formability of the hollow magnesium alloy will be much better when the ratio of sidewall thickness to the bottom thickness is 1:1.5.Also when edge-to-middle ratio in bottom is about 1:1.5,a better forming product can be received.The best bottom shape in these experiments will be convex based on the forming results.The grain will be refined obviously after the extrusion.Also the microstructures will be shown as streamlines.And these lines will be well agreement with the mold in the corner.展开更多
Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Sma...Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(x2021-JYB-XJSJJ-032)Beijing Municipal Commission of Education,Double First-class,High-caliber Talents Grant(1000041510156)。
文摘Objective:To investigate the differences between meditation and resting states using infrared thermal imaging(IRTI)to determine facial temperature distribution features during meditation and annotate the patterns of facial temperature changes during meditation from the perspective of traditional Chinese medicine facial diagnosis.Methods:Each participant performed 10 min meditation and 10 min resting but in different sequences.A concentration test was set as the task load,followed by a meditation/resting or resting/meditation session,during which the participants'facial temperatures were observed using IRTI.Participants were scored on the Big Five Inventory(BFI)and Mindful Attention Awareness Scale(MAAS).Results:Forehead temperatures decreased more during meditation than during the resting state.The chin temperature increased only during meditation(P<.0001).For the subjects with meditation experience,there were significant differences in the temperatures of the left forehead(P<.01),right forehead(P<.01)and chin(P<.05)between the meditation and resting state at the 10~(th)min.In the nontask state,the BFI-Extraversion showed a negative correlation with the temperature of the left forehead(R=-0.41,P=.03).In the post-task state,the temperature of the left forehead was negatively correlated with scores on the MAAS(R=-0.42,P=.02).Conclusion:Using IRTI to study meditation offers a practical solution to the challenges in meditation research.The results indicate that an increase in chin temperature may be a representative feature of a meditation state,and forehead temperature is also a potential indicator.
基金the National Key Research and Development Program of China(2021YFF0900800)the National Natural Science Foundation of China(61972276,62206116,62032016)+2 种基金the New Liberal Arts Reform and Practice Project of National Ministry of Education(2021170002)the Open Research Fund of the State Key Laboratory for Management and Control of Complex Systems(20210101)Tianjin University Talent Innovation Reward Program for Literature and Science Graduate Student(C1-2022-010)。
文摘Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.
基金This work was financially supported by the National Natural Science Foundation of China(52074089 and 52104064)Natural Science Foundation of Heilongjiang Province of China(LH2019E019).
文摘As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.
基金financially supported by the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City(Grant No.520LH052)the National Natural Science Foundation of China(Grant No.51909164).
文摘Deepsea mining has been proposed since the 1960s to alleviate the lack of resources on land.Vertical hydraulic transport of collected ores from the seabed to the sea surface is considered the most promising method for industrial applications.In the present study,an indoor model test of the vertical hydraulic transport of particles was conducted.A noncontact optical method has been proposed to measure the local characteristics of the particles inside a vertical pipe,including the local concentration and particle velocity.The hydraulic gradient of ore transport was evaluated with various particle size distributions,particle densities,feeding concentrations and mixture flow velocities.During transport,the local concentration is larger than the feeding concentration,whereas the particle velocity is less than the mixture velocity.The qualitative effects of the local concentration and local fluid velocity on the particle velocity and slip velocity were investigated.The local fluid velocity contributes significantly to particle velocity and slip velocity,whereas the effect of the local concentration is marginal.A higher feeding concentration and mixture flow velocity result in an increased hydraulic gradient.The effect of the particle size gradation is slight,whereas the particle density plays a crucial role in the transport.
基金The authors are grateful for financial support from the National Key Projects for Fundamental Research and Development of China(2021YFA1500803)the National Natural Science Foundation of China(51825205,52120105002,22102202,22088102,U22A20391)+1 种基金the DNL Cooperation Fund,CAS(DNL202016)the CAS Project for Young Scientists in Basic Research(YSBR-004).
文摘Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.
基金This work is supported by the 2022 National Key Research and Development Plan“Security Protection Technology for Critical Information Infrastructure of Distribution Network”(2022YFB3105100).
文摘First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.
基金funded by the National Natural Science Foundation of China(Grant No.41861134008)Muhammad Asif Khan academician workstation of Yunnan Province(Grant No.202105AF150076)+6 种基金General program of Yunnan Province Science and Technology Department(Grant No.202105AF150076)Key Project of Natural Science Foundation of Yunnan Province(Grant No.202101AS070019)Key R&D Program of Yunnan Province(Grant No.202003AC100002)General Program of basic research plan of Yunnan Province(Grant No.202001AT070059)Major scientific and technological projects of Yunnan Province:Research on Key Technologies of ecological environment monitoring and intelligent management of natural resources in Yunnan(No:202202AD080010)“Study on High-Level Hidden Landslide Identification Based on Multi-Source Data”of Key Laboratory of Early Rapid Identification,Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan Province(KLGDTC-2021-02)Guizhou Scientific and Technology Fund(QKHJ-ZK[2023]YB 193).
文摘Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.
基金supported by the National Natural Science Foundation of China(52203364,52188101,52020105010)the National Key R&D Program of China(2021YFB3800300,2022YFB3803400)+2 种基金the Strategic Priority Research Program of Chinese Academy of Science(XDA22010602)the China Postdoctoral Science Foundation(2022M713214)the China National Postdoctoral Program for Innovative Talents(BX2021321)。
文摘Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.
基金supported by Natural Science Foundation of Fujian Province (CN) (2020I0009, 2022J01596)Cooperation Project on University Industry-Education-Research of Fujian Provincial Science and Technology Plan (CN) (2022N5011)+1 种基金Lancang-Mekong Cooperation Special Fund (2017-2020)International Sci-Tech Cooperation and Communication Program of Fujian Agriculture and Forestry University (KXGH17014)。
文摘Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.
基金support of the project“State Grid Corporation Headquarters Science and Technology Program(5108-202299258A-1-0-ZB)”.
文摘To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.
基金supported by Special key project of technological innovation and application development in Yongchuan District,Chongqing(2021yc-cxfz20002)the special funds of central government for guiding local science and technology developmentthe funds for the platform projects of professional technology innovation(CSTC2018ZYCXPT0006).
文摘To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.
基金supported by the National Key R&D Program of China(2021YFB3301100)Beijing University of Chemical Technology Interdisciplinary Program(XK2023-07).
文摘Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.
基金the National Natural Science Foundation of China(Grant No.42174047 and No.42174036)the National Science Foundation Project for Outstanding Youth(No.42104034).
文摘This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.
文摘Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.
基金Supported by the Youth Fund Project of the National Natural Science Foundation of China(32001570)the Post-doctorate Program Funding in Heilongjiang Province(LBH-Z19118)the Academic Backbone'Project of Northeast Agricultural University(20XG11)。
文摘Soybean is one of the important crops in China. Soymilk, a traditional neutral plant-based protein drink, is rich in high quality proteins. Although soybean milk is rich in nutrients, its marketing among consumers, especially those in Western countries who are used to peaceful flavor, has been limited due to the adverse flavor impact brought by its special composition. In recent years, with the increasing attention to the nutritional value of soymilk, the flavor of soymilk has become a popular research object for scholars at home and abroad. The flavor components of soymilk are mainly volatile small molecular compounds produced by enzymatic reactions catalyzed by lipoxygenase(LOX). After formation, they interact with protein macromolecules to form the overall flavor of soymilk. At present, there are many methods to control the off-odor of soymilk at home and abroad, including physical heating methods, chemical methods, biological enzymatic digestion methods, mask methods, and a variety of breeding methods. These methods effectively reduce the off-odor of soymilk, but all of them have shortcomings. Currently, the sensory characteristics of the beany odor in soymilk are evaluated mainly by traditional human sensory scoring along with the assistance of modern instrument analysis of volatile flavor substances using headspace solid phase microextraction(SPME) gas chromatography coupled with-mass spectrometry(GC-MS). This paper summarized the research results of volatile flavor substances in soymilk in recent years and the sensory evaluation methods of soymilk at home and abroad, and looked forward to the future development direction, hoping to provide some theoretical bases and reference detection methods for solving the problem of soymilk flavor in the future.
基金Project supported by the National Natural Science Foundation of China(Nos.12293000,12293001,11988102,12172006,and 12202011)。
文摘The dynamic model of a bistable laminated composite shell simply supported by four corners is further developed to investigate the resonance responses and chaotic behaviors.The existence of the 1:1 resonance relationship between two order vibration modes of the system is verified.The resonance response of this class of bistable structures in the dynamic snap-through mode is investigated,and the four-dimensional(4D)nonlinear modulation equations are derived based on the 1:1 internal resonance relationship by means of the multiple scales method.The Hopf bifurcation and instability interval of the amplitude frequency and force amplitude curves are analyzed.The discussion focuses on investigating the effects of key parameters,e.g.,excitation amplitude,damping coefficient,and detuning parameters,on the resonance responses.The numerical simulations show that the foundation excitation and the degree of coupling between the vibration modes exert a substantial effect on the chaotic dynamics of the system.Furthermore,the significant motions under particular excitation conditions are visualized by bifurcation diagrams,time histories,phase portraits,three-dimensional(3D)phase portraits,and Poincare maps.Finally,the vibration experiment is carried out to study the amplitude frequency responses and bifurcation characteristics for the bistable laminated composite shell,yielding results that are qualitatively consistent with the theoretical results.
基金the Jilin Science and Technology Department 20200201280JC,and Shanghai special fund for ideological and political work in Shanghai University of International Business and Economics.
文摘Contingent self-esteem captures the fragile nature of self-esteem and is often regarded as suboptimal to psychological functioning.Self-compassion is another important self-related concept assumed to promote mental health and well-being.However,research on the relation of self-compassion to contingent self-esteem is lacking.Two studies were conducted to explore the role of selfcompassion,either as a personal characteristic or an induced mindset,in influencing the effects of contingent self-esteem on well-being.Study 1 recruited 256 Chinese college students(30.4%male,mean age=21.72 years)who filled out measures of contingent self-esteem,self-compassion,and well-being.The results found that self-compassion moderated the effect of contingent self-esteem on well-being.In Study 2,a sample of 90 Chinese college students(34%male,mean age=18.39 years)were randomly assigned to either a control or self-compassion group.They completed baseline trait measures of contingent self-esteem,self-compassion,and self-esteem.Then,they were led to have a 12-min break(control group)or listen to a 12-min self-compassion audio(self-compassion group),followed by a social stress task and outcome measures.The results demonstrated the effectiveness of the brief self-compassion training and its moderating role in influencing the effects of contingent self-esteem on negative affects after the social stress task.This research provides implications that to equip with a self-compassionate mindset could lower the risk of the impairment of well-being associated with elements of contingent selfesteem,which involves a fragile sense of self-worth.It may also provide insights into the development of an“optimal selfesteem”and the improvement of well-being.
基金funded by the National Key Research and Development Program of China(No:2020YFC1909900)the National Natural Science Foundation of China(No:51908550)the Scientific Research Project of China Academy of Railway Sciences Group Corporation Limited(No:2021YJ173).
文摘Purpose – This study aims to analyze the factors, evaluation techniques of the durability of existing railwayengineering.Design/methodology/approach – China has built a railway network of over 150,000 km. Ensuring thesafety of the existing railway engineering is of great significance for maintaining normal railway operationorder. However, railway engineering is a strip structure that crosses multiple complex environments. Andrailway engineering will withstand high-frequency impact loads from trains. The above factors have led todifferences in the deterioration characteristics and maintenance strategies of railway engineering compared toconventional concrete structures. Therefore, it is very important to analyze the key factors that affect thedurability of railway structures and propose technologies for durability evaluation.Findings – The factors that affect the durability and reliability of railway engineering are mainly divided intothree categories: material factors, environmental factors and load factors. Among them, material factors alsoinclude influencing factors, such as raw materials, mix proportions and so on. Environmental factors varydepending on the service environment of railway engineering, and the durability and deterioration of concretehave different failure mechanisms. Load factors include static load and train dynamic load. The on-site rapiddetection methods for five common diseases in railway engineering are also proposed in this paper. Thesemethods can quickly evaluate the durability of existing railway engineering concrete.Originality/value – The research can provide some new evaluation techniques and methods for thedurability of existing railway engineering.
基金National Natural Science Foundation of China No.51905068Natural Science Foundation of Liaoning Province No.2020-HYLH-24The open research fund from the State Key Laboratory of Rolling and Automation,Northeastern University No.2020RALKFKT012。
文摘Magnesium alloy is one of the lightest metal structural materials.The weight is further reduced through the hollow structure.However,the hollow structure is easily damaged during processing.In order to maintain the hollow structure and to transfer the stresses during the high temperature deformation,the sand mandrel is proposed.In this paper,the hollow AZ31 magnesium alloy three-channel joint is studied by hot extrusion forming.Sand as one of solid granule medium is used to fill the hollow magnesium alloy.The extrusion temperatures are 230℃ and 300℃,respectively.The process parameters(die angle,temperature,bottom thickness,sidewall thickness,edge-to-middle ratio in bottom,bottom shape)of the hollow magnesium alloy are analyzed based on the results of experiments and the finite element method.The results are shown that the formability of the hollow magnesium alloy will be much better when the ratio of sidewall thickness to the bottom thickness is 1:1.5.Also when edge-to-middle ratio in bottom is about 1:1.5,a better forming product can be received.The best bottom shape in these experiments will be convex based on the forming results.The grain will be refined obviously after the extrusion.Also the microstructures will be shown as streamlines.And these lines will be well agreement with the mold in the corner.
文摘Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.
