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One of the most serious diseases affecting dairy cattle, causing significant losses both in breeding and economy, is mastitis, an inflammation of the mammary gland. Due to the economic importance of this issue, many research teams are striving to develop an easy-to-apply and, most importantly, effective method to prevent mastitis. The use of traditional methods for mastitis detecting and treating, as well as improvement in hygienic conditions, have not yielded the expected results in combating this disease combating. Currently, the main task is to find the tools that would allow for the rapid detection of mastitis and the improvement of udder health in cows while maintaining high milk production, which is essential for the profitability of dairy cattle farming. Accurate and rapid diagnostic tools, with the simultaneous capability of identifying pathogens, may help to reduce losses. Sufficient sensitivity and specificity for tests are required to minimize the number of false-positive and false-negative cases. Efforts are also being made to determine the optimal threshold value for detecting the disease at its earliest possible stage. The estimation of somatic cell count (SCC) as a phenotypic indicator of mastitis is widely used. A more precise parameter for accurately describing udder health is the differential somatic cell count (DSCC). The well-known California Mastitis Test (CMT) is an inexpensive, easy, and rapid method for mastitis detection useful on farms. The latest diagnostic methods for mastitis utilize tests based on the activity of N-acetyl-β-d-glucosaminidase (NAGase) or lactate dehydrogenase (LDH) as well as the determination of acute phase proteins (APPs) in blood serum and milk (such as haptoglobin, serum amyloid A, fibrinogen, and ceruloplasmin). Research also focuses on the genomic improvement of mastitis resistance in successive generations, and for this purpose, many quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs) have been identified. In recent years, immunotherapy has become an increasingly common area of research, including vaccinations, T/B cell immunotherapy, RNA immunotherapy, epigenetic immunotherapy, stem cell therapy, and native secretory factors. An important aspect of the control of mastitis is the implementation of strategies that focus primarily on preventing the disease through appropriate breeding and farm management practices. In the forthcoming years, a significant challenge will be the development of universal diagnostic and therapeutic strategies that can be effectively implemented as alternatives to antibiotic therapy. Future research should prioritize the advancement of preventive and therapeutic techniques, such as immunotherapies, bacteriocins, herbal therapy, and nanoparticle technology. [ABSTRACT FROM AUTHOR]

The accurate analysis of human dynamic behavior is very important for overcoming the limitations of movement diversity and behavioral adaptability. In this paper, a wearable device-based human dynamic behavior recognition method is proposed. The method collects acceleration and angular velocity data through a six-axis sensor to identify information containing specific behavior characteristics in a time series. A human movement data acquisition platform, the DMP attitude solution algorithm, and the threshold algorithm are used for processing. In this experiment, ten volunteers wore wearable sensors on their bilateral forearms, upper arms, thighs, calves, and waist, and movement data for standing, walking, and jumping were collected in school corridors and laboratory environments to verify the effectiveness of this wearable human movement recognition method. The results show that the recognition accuracy for standing, walking, and jumping reaches 98.33%, 96.67%, and 94.60%, respectively, and the average recognition rate is 96.53%. Compared with similar methods, this method not only improves the recognition accuracy but also simplifies the recognition algorithm and effectively saves computing resources. This research is expected to provide a new perspective for the recognition of human dynamic behavior and promote the wider application of wearable technology in the field of daily living assistance and health management. [ABSTRACT FROM AUTHOR]

Glacial lake outburst floods (GLOF) hazards in alpine areas are increasing. The effects of climate change on GLOF hazards are unclear. This study examined 37 glacial lakes and climate data from 15 meteorological stations and explored the correlation between climate variations at different temporal scales. The results indicate that 19 GLOFs hazards occurred in El Niño (warm) years, 8 GLOFs hazards occurred in La Niña (cold) years, 3 GLOFs hazards occurred in cold/warm or warm/cold transition years, and 7 GLOFs hazards occurred in normal years. The higher the fluctuations, the higher the probability of GLOF hazards. Climatic conditions can be divided into three categories: extreme temperature and precipitation, as represented by the Guangxie Co GLOF; extreme precipitation, as represented by the Poge Co GLOF; and extreme temperature, as represented by the Tsho Ga GLOF. [ABSTRACT FROM AUTHOR]

Determining background aerosol optical depth threshold value (BAOD) is critical to aerosol type identification and air pollution control. This study presents a statistical method to select the best BAOD threshold value using the VIIRS DB AOD products at 1 × 1 degree resolution from 2012 to 2019 as a major testbed. A series of multiple lognormal distributions with 1 to 5 peaks are firstly applied to fit the AOD histogram at each grid point, and the distribution with the highest correlation coefficient (R) gives preliminary estimations of BAOD, which is defined as either the intersection point of the first two normal distribution curves when having multiple peaks, or the midpoint between the peak AOD and the first AOD with non-zero probability when the mono peak is the best fit. Then, the lowest 1st to 100th percentile AOD distributions are compared with the preliminary BAOD distribution on a global scale. The final BAOD is obtained from the best cutoff percentile AOD distributions with the lowest bias compared with preliminary BAOD. Results show that the lowest 30th percentile AOD is the best estimation of BAOD for different AOD datasets and different seasons. Analysis of aerosol chemical information from MERRA-2 further supports this selection. Based on the BAOD, we updated the VIIRS aerosol type classification scheme, and the results show that the updated scheme is able to achieve reliable detection of aerosol type change in low aerosol loading conditions. [ABSTRACT FROM AUTHOR]

Background: Magnesium (Mg) is an essential element and participates in many metabolic pathways. Many studies have found a certain negative correlation between magnesium and blood glucose parameters, but the dose–response relationship between them is still a relatively narrow research field. We aim to explore the dose–response relationship between plasma and dietary Mg and type 2 diabetes (T2DM) among childbearing women in a nationally representative sample. And we will also initially explore the threshold of dietary and plasma magnesium in the prevention of T2DM and their consistency. Methods: A total of 2912 18–44 year-old childbearing women were recruited from the China Adult Chronic Disease and Nutrition Surveillance (2015). Multivariate logistic regression was used to explore the dose–response relationship between plasma and dietary Mg and glucose parameters. The threshold effect between Mg and T2DM was explored by a restricted cubic spline regression. Results: It was found that when plasma Mg was increased by 0.041 mmol/L, the risk of T2DM, impaired fasting glucose (IFG), and HbA1c-hyperglycemia was reduced by 18%, 19%, and 18%, respectively. The possible threshold value for plasma Mg to prevent the risk of T2DM was 0.87 mmol/L. Through the quality control of the sample dietary survey data, 2469 cases were finally included for dietary analysis. And the possible threshold value for dietary Mg to prevent the risk of T2DM was 408 mg/d. Taking the recommended dietary Mg intake of 330 mg/d as the reference group, when the Mg intake reached 408 mg/d, the risk of T2DM was significantly reduced. And the average plasma Mg level of the people whose dietary intake reached 408 mg/d was 0.87 mmol/L. Conclusions: These results indicate that dietary Mg and plasma Mg have good consistency on the threshold effect of glucose parameters in women of childbearing age. [ABSTRACT FROM AUTHOR]

Background: Endometrial proliferative lesions (EPL) usually refer to endometrial hyperplasia (EH) and endometrial cancer (EC). Among patients with premenopausal EPL who wish to preserve their fertility, only those with EH and early-stage EC have the possibility to undergo fertility preservation therapy. However, there is currently a lack of specific and reliable screening criteria and models for identifying these patients. Methods: This study utilized a retrospective diagnostic study design. The training set included medical record information that met the criteria between August 2017 and October 2022, while the validation set consisted of medical record information that met the criteria from November 2022 to May 2023. The endometrial pathological test served as the gold standard. The serum anti-Mullerian hormone (AMH) level before endometrial sampling and a regression model were employed to predict EPL. Results: The study included a total of 1209 patients with PCOS (1119 in the control group and 90 in the endometrial proliferative lesion group) and 5366 women without PCOS (5249 in the control group and 117 in the proliferative lesion group). In the case of PCOS patients aged 20–39 years, the most effective screening threshold for AMH was found to be a serum AMH level of ≤5.39 ng/mL. The model used for this group was logit(p) = −2.562 − 0.430 × AMH + 0.127 × BMI + 1.512 × hypertension + 0.956 × diabetes −1.145 × regular menstruation. On the other hand, for non-PCOS women aged 20–39 years, the optimal screening threshold for AMH was determined to be a serum AMH value of ≤2.18 ng/mL. The model used for this group was logit(p) = −3.778 − 0.823 × AMH + 0.176 × BMI + 2.660 × diabetes −1.527 × regular menstruation −1.117 × dysmenorrhea. It is important to note that all of these findings have successfully passed internal verification. Conclusion: For PCOS and non-PCOS women aged 20–39 years, the serum AMH test and related multiple regression models were obtained for the warning of EPL. [ABSTRACT FROM AUTHOR]

Time series analysis is a method of key importance for systems of various hierarchies' economic security studies. This article's main goal is to develop an economic security rapid indicators system, introducing threshold values and utilizing indices with a one-month sampling period, and its approbation during Russia's economic security operational monitoring. In order to develop such a system, the authors accumulated economic security world experience including reliability, visibility and tree structure principles. The authors' monitoring system includes four spheres: real economy, social, monetary and foreign economic, each of which contains three indicators. In order to organize economic security monitoring, it is proposed to use the index method, which converts indicators into a dimensionless form with integral values in subsequent calculations. Based on integral indices values, the economic security generalized index is synthesized, which can be used to analyze a system's development trends. We present economic security normalized indicators and integral indices dynamics for the years 2020–2022, which show two crises dynamics. The first is due the COVID-19 pandemic, while the second is associated with economic sanctions against Russia, implemented in 2022. The proposed economic security operational monitoring indicators system can be used effectively in the government's practical tasks in order to ensure the required level of economic security. This is especially true for rapid diagnosis of crisis phenomena in countries and individual regions. [ABSTRACT FROM AUTHOR]

Cloud computing is a prominent approach for complex scientific and business workflow applications in the pay-as-you-go model. Workflow scheduling poses a challenge in cloud computing due to its widespread applications in physics, astronomy, bioinformatics, and healthcare, etc. Resource allocation for workflow scheduling is problematic due to the computationally intensive nature of the workflow, the interdependence of tasks, and the heterogeneity of cloud resources. During resource allocation, the time and cost of execution are significant issues in the cloud-computing environment, which can potentially degrade the service quality that is provided to end users. This study proposes a method focusing on makespan, average utilization, and cost. The authors propose a task's dynamic priority for workflow scheduling using MONWS, which uses the min-max algorithm to minimize the finish time and maximize resource utilization by calculating the dynamic threshold value for scheduling tasks on virtual machines. When the experimental results were compared to existing algorithms, MONWS achieved a 35% improvement in makespan, an 8% increase in maximum average cloud utilization, and a 4% decrease in cost. [ABSTRACT FROM AUTHOR]

The critical damage point of the red-bed soft rock percolation phenomenon can be described as the percolation threshold. At present, there are insufficient theoretical and experimental studies on the percolation phenomenon and threshold of red-bed soft rock. In combination with theoretical analysis, compression experiment and numerical simulation, the percolation threshold and destruction of red-bed soft rock are studied in this paper. The theoretical percolation threshold of red-bed soft rock was obtained by constructing a renormalization group model of soft rock. Based on damage mechanics theory, rock damage characterization and strain equivalent hypothesis, a constitutive model of red-bed soft rock percolation damage was obtained. The percolation threshold of red-bed soft rock was determined by compression test and a damage constitutive model, which verified the rationality of the theoretical percolation threshold, and we numerically simulated the percolation of red-bed soft rock under triaxial compression. The results showed that the percolation threshold increases as the confining pressure rises, but decreases significantly with the action of water. In this study, the critical failure conditions and percolation characteristics of red-bed soft rock under different conditions were obtained. The relationship between percolation and soft rock failure was revealed, providing a new direction for studying the unstable failure of red-bed soft rock. [ABSTRACT FROM AUTHOR]

Alloy 718 for forged parts can form a wide range of microstructures through a variety of thermo-mechanical processes, depending on the number of remelting processes, temperature and holding time of homogenization annealing, cogging and the number of forging steps depending on the forming characteristics. In industrial practice, these processing steps are tailored to achieve specific mechanical and microstructural properties in the final product. In the present work, we investigate the dependence of the threshold of stress intensity factor range ΔKth on associated microstructural elements, namely grain size and distribution. For this purpose, a series of tests with different starting microstructures were performed at the falling stress intensity factor range, ΔK, and a load ratio of R = 0.1 to evaluate the different threshold values. Fracture initiation and crack propagation were analyzed afterward using scanning electron microscopy of the resulting fracture surfaces. In order to obtain comparable initial conditions, all specimens were brought to the same strength level by means of a two-stage aging heat treatment. In the future, this knowledge shall be used in the context of simulation-aided product development for estimating local fatigue crack propagation properties of simulated microstructures obtained from forging and heat treatment modeling. [ABSTRACT FROM AUTHOR]

The aging of electrical insulation material or a system is a main issue for designers of high-voltage (HV) machines. Precise determination of the life cycle of electrical insulation is one way of improving the efficiency of electrical machines involved in the production and transmission of electrical energy. Much effort has been devoted to preparing statistical or physical methods of Electrical Insulating System (EIS) life time estimation in the real operation of electrical machinery. The main aim of this paper is to introduce a new physical-statistical model of thermal aging respecting the threshold value. This model is based on thermal aging model and the main difference between this model and previously published models is taking into account the threshold value of degradation factor. The complete design of this model is presented in this paper, including functions defining the threshold value of the effect of the degradation factor depending on the temperature. Proposed model was verified by accelerated thermal aging test at selected temperatures (160, 170, 180 °C) and time intervals (0, 120, 240 h) on a commonly used transformer board. The breakdown voltage was set as an indicating parameter of the level of thermal aging and was measured according to standard IEC 60243-1. Collected data from these measurements were used for threshold value determination (431.23 K) and verification of proposed physical-statistical model of thermal aging respecting the threshold value. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate sarcopenia and locomotive syndrome in Korean elderly patients, analyze the closely related factors, and determine the threshold for distinguishing participants with sarcopenia, locomotive syndrome, and non-disease. To this end, we enrolled 210 subjects aged 65 years or more and classified them into the sarcopenia ( n = 36) and locomotive syndrome ( n = 164) groups; a control group was also included ( n = 10). We evaluated the characteristics of these patients using the Timed Up and Go (TUG) test and Berg Balance Scale (BBS) and performed statistical analysis. Our findings showed statistically significant differences between the groups, leading to the derivation of a significant threshold value. The threshold value of the TUG test between the control and locomotive syndrome groups was 9.47 s; the threshold value of the BBS was 54 points, respectively. The threshold value of the TUG test between the locomotive syndrome and sarcopenia groups was 10.27 s, and the threshold value of the BBS was 50 points, respectively. These findings suggest that sarcopenia is closely related to locomotive syndrome, and that sarcopenia and locomotive syndrome can be identified using a physical therapy diagnostic evaluation tool.

The paper proposes an approach to assessing the allowed signal-to-noise ratio (SNR) for light detection and ranging (LiDAR) of unmanned autonomous vehicles based on the predetermined probability of false alarms under various intentional and unintentional influencing factors. The focus of this study is on the relevant issue of the safe use of LiDAR data and measurement systems within the "smart city" infrastructure. The research team analyzed and systematized various external impacts on the LiDAR systems, as well as the state-of-the-art approaches to improving their security and resilience. It has been established that the current works on the analysis of external influences on the LiDARs and methods for their mitigation focus mainly on physical (hardware) approaches (proposing most often other types of modulation and optical signal frequencies), and less often software approaches, through the use of additional anomaly detection techniques and data integrity verification systems, as well as improving the efficiency of data filtering in the cloud point. In addition, the sources analyzed in this paper do not offer methodological support for the design of the LiDAR in the very early stages of their creation, taking into account a priori assessment of the allowed SNR threshold and probability of detecting a reflected pulse and the requirements to minimize the probability of "missing" an object when scanning with no a priori assessments of the detection probability characteristics of the LiDAR. The authors propose a synthetic approach as a mathematical tool for designing a resilient LiDAR system. The approach is based on the physics of infrared radiation, the Bayesian theory, and the Neyman–Pearson criterion. It features the use of a predetermined threshold for false alarms, the probability of interference in the analytics, and the characteristics of the LiDAR's receivers. The result is the analytical solution to the problem of calculating the allowed SNR while stabilizing the level of "false alarms" in terms of background noise caused by a given type of interference. The work presents modelling results for the "false alarm" probability values depending on the selected optimality criterion. The efficiency of the proposed approach has been proven by the simulation results of the received optical power of the LiDAR's signal based on the calculated SNR threshold and noise values. [ABSTRACT FROM AUTHOR]

The present study analyzes the cyclic crack propagation behavior in an austenitic steel processed by electron beam powder bed fusion (PBF-EB). The threshold value of crack growth as well as the crack growth behavior in the Paris regime were studied. In contrast to other austenitic steels, the building direction during PBF-EB did not affect the crack propagation rate, i.e., the crack growth rates perpendicular and parallel to the building direction were similar due to the isotropic microstructure characterized by equiaxed grains. Furthermore, the influence of significantly different building parameters was studied and, thereby, different energy inputs causing locally varying manganese content. Crack growth behavior was not affected by these changes. Even a compositional gradation within the same specimen, i.e., crack growth through an interface of areas with high and areas with low manganese content, did not lead to a significant change of the crack growth rate. Thus, the steel studied is characterized by a quite robust cyclic crack growth behavior independent from building direction and hardly affected by typical parameter deviations in the PBF-EB process. [ABSTRACT FROM AUTHOR]

This paper proposes a measurement of risk (MOR) method to recognize risky driving behavior based on the trajectory data extracted from surveillance videos. Three types of risky driving behavior are studied in this paper, i.e., speed-unstable driving, serpentine driving, and risky car-following driving. The risky driving behavior recognition model contains an MOR-based risk evaluation model and an MOR threshold selection method. An MOR-based risk evaluation model is established for three types of risky driving behavior based on driving features to quantify collision risk. Then, we propose two methods, i.e., the distribution-based method and the boxplot-based method, to determine the threshold value of the MOR to recognize risky driving behavior. Finally, the trajectory data extracted from UAV videos are used to validate the proposed model. The impact of vehicle types is also taken into consideration in the model. The results show that there are significant differences between threshold values for cars and heavy trucks when performing speed-unstable driving and risky car-following driving. In addition, the difference between the proportion of recognized risky driving behavior in the testing dataset compared with that in the training dataset is limited to less than 3.5%. The recognition accuracy of risky driving behavior with the boxplot- and distribution-based methods are, respectively, 91% and 86%, indicating the validation of the proposed model. The proposed model can be widely applied to risky driving behavior recognition in video-based surveillance systems.

The purpose of this study is to identify factors that can change the environmental friendliness of individuals in the context of climate change issues in terms of values, beliefs, controllability, concern, attitude, intention, and behavior through a survey experiment, and to test the hypothesis that providing information about the amount of carbon dioxide (CO2) emissions attributable to an individual with its threshold value motivates him/her to reduce that amount using statistical analyses (the Mann–Whitney test) and multivariate regressions (the ordered logit model). It is crucial to change the behavior of individuals as well as organizations to reduce the emissions of CO2 for solving climate change issues, because the aggregate amount of individual CO2 emissions is too large to ignore. We conducted a survey experiment to detect factors affecting the environmental friendliness of individuals. Subjects of the experiment were 102 students at Shiga University in Japan. They were randomly provided with communication opportunities, information about individual or group CO2 emissions, and information about their threshold value. The finding is that provision of information about the amount of individual and group CO2 emissions may be able to improve that person's environmental friendliness in terms of values, beliefs, concern, attitude, intention, and behavior. [ABSTRACT FROM AUTHOR]

The wind power ramp event includes large fluctuations in wind power within a short period of time. To maintain grid stability, defining, identifying, and predicting the wind power ramp event is inevitable. Therefore, a comprehensive assessment method of wind power ramp events that combines the generalized information of the source, grid, and load sides is proposed. In this method, we put forward a channel self-selected multi-layer coefficient correction model (CSMCC) and wind power ramp threshold, according to the allowable value of a grid frequency change. Additionally, the availability of data-driven modeling methods is verified by performing autocorrelation analysis. Finally, the comprehensive evaluation method, which combines the back propagation (BP) neural network, supports the vector machine and CSMCC model is proved to be effective. This paper has a certain reference significance for basic research on large-scale wind power safety and efficient utilization. [ABSTRACT FROM AUTHOR]

Image thresholding is one of the fastest and most effective methods of detecting objects in infrared images. This paper proposes an infrared image thresholding method based on the functional approximation of the histogram. The one-dimensional histogram of the image is approximated to the transient response of a first-order linear circuit. The threshold value for the image segmentation is formulated using combinational analogues of standard operators and principles from the concept of the transient behavior of the first-order linear circuit. The proposed method is tested on infrared images gathered from the standard databases and the experimental results are compared with the existing state-of-the-art infrared image thresholding methods. We realized through the experimental results that our method is well suited to perform infrared image thresholding. [ABSTRACT FROM AUTHOR]

Environmental obligation, fuel security, and human health issues have fuelled the search for locally produced sustainable transport fuels as an alternative to liquid petroleum. This study evaluates the sustainability performance of various alternative energy sources, namely, ethanol, electricity, electricity-gasoline hybrid, and hydrogen, for Western Australian road transport using a life cycle sustainability assessment (LCSA) framework. The framework employs 11 triple bottom line (TBL) sustainability indicators and uses threshold values for benchmarking sustainability practices. A number of improvement strategies were devised based on the hotspots once the alternative energy sources failed to meet the sustainability threshold for the determined indicators. The proposed framework effectively addresses the issue of interdependencies between the three pillars of sustainability, which was an inherent weakness of previous frameworks. The results show that the environment-friendly and socially sustainable energy options, namely, ethanol-gasoline blend E55, electricity, electricity-E10 hybrid, and hydrogen, would need around 0.02, 0.14, 0.10, and 0.71 AUD/VKT of financial support, respectively, to be comparable to gasoline. Among the four assessed options, hydrogen shows the best performance for the environmental and social bottom line when renewable electricity is employed for hydrogen production. The economic sustainability of hydrogen fuel is, however, uncertain at this stage due to the high cost of hydrogen fuel cell vehicles (HFCVs). The robustness of the proposed framework warrants its application in a wide range of alternative fuel assessment scenarios locally as well as globally. [ABSTRACT FROM AUTHOR]

Aquiclude plays a critical role in the occurrence of mining-induced roof water inrush in underground coal mines. This paper proposes an assessment index for the evaluation of aquiclude stability and a threshold value of water inrush from the roof, based on a case study of roof water inrush accidents in Cuimu coal mine, China. The relation between roof water inrush and water level variation in the aquifer, and the characteristics of aquiclude deformation, were studied in this assessment. Using the developed assessment criteria, the likelihood of roof water inrush was categorized into different risk levels, which were followed by a proposal for roof water inrush control measures. The main findings of this study are: a) in Cuimu coal mine, the waterbody in the bed separation between the upper aquifer and the aquiclude directly causes the inrush, and inrush occurs after the water level declines in the aquifer; b) tension-induced horizontal strains of aquiclude can be regarded as the index to evaluate the stability of aquiclude affected by underground coal mining—roof water inrush occurs when the maximum horizontal strain reaches a threshold of 10mm/m—c) based on the critical mining height for aquiclude instability, and the different thicknesses of barrier layers, high-risk zones are identified and inrush controls are proposed. [ABSTRACT FROM AUTHOR]

This work explored the influence of gas mole fraction and activity in aqueous phase while predicting phase equilibrium conditions. In pure gas systems, such as CH4, CO2, N2 and O2, the gas mole fraction in aqueous phase as one of phase equilibrium conditions was proposed, and a simplified correlation of the gas mole fraction was established. The gas mole fraction threshold maintaining three-phase equilibrium was obtained by phase equilibrium data regression. The UNIFAC model, the predictive Soave-Redlich-Kwong equation and the Chen-Guo model were used to calculate aqueous phase activity, the fugacity of gas and hydrate phase, respectively. It showed that the predicted phase equilibrium pressures are in good agreement with published phase equilibrium experiment data, and the percentage of Absolute Average Deviation Pressures are given. The water activity, gas mole fraction in aqueous phase and the fugacity coefficient in vapor phase are discussed. [ABSTRACT FROM AUTHOR]

A new temperature stress test machine (TSTM) was developed to improve temperature control accuracy and efficiency. As there is no uniform standard for the threshold value of TSTM, quite different threshold values are used in the test, which results in the influences of the threshold value on the evaluation of thermal stresses and crack risk of concrete not being determined. To illustrate the importance of an appropriate threshold value, different threshold values were used to evaluate the influences on the thermal stresses and cracking resistance of concrete specimens under a complete restraint test with semi-adiabatic temperature development. The results show that the maximum compressive stress of a concrete specimen with a threshold value 3 με was slightly larger than that of 1.5 με when the growth rate of tensile stress of the concrete specimen with the threshold value 3 με was slightly greater than that of concrete specimen with the threshold value 1.5 με. Based on the combination of crack risk coefficient and restraint degree, a new system for evaluating the crack resistance of concrete was proposed, in which different threshold values were used to estimate their influences on the crack risk of concrete. Thus, an appropriate range of threshold values could be determined. [ABSTRACT FROM AUTHOR]