Enrichment of Geogenic Organoiodine Compounds in Alluvial-Lacustrine Aquifers: Molecular Constraints by Organic Matter.

Organoiodine compounds (OICs) are the dominant iodine species in groundwater systems. However, molecular mechanisms underlying the geochemical formation of geogenic OICs-contaminated groundwater remain unclear. Based upon multitarget field monitoring in combination with ultrahigh-resolution molecular characterization of organic components for alluvial-lacustrine aquifers, we identified a total of 939 OICs in groundwater under reducing and circumneutral pH conditions. In comparison to those in water-soluble organic matter (WSOM) in sediments, the OICs in dissolved organic matter (DOM) in groundwater typically contain fewer polycyclic aromatics and polyphenol compounds but more highly unsaturated compounds. Consequently, there were two major sources of geogenic OICs in groundwater: the migration of the OICs from aquifer sediments and abiotic reduction of iodate coupled with DOM iodination under reducing conditions. DOM iodination occurs primarily through the incorporation of reactive iodine that is generated by iodate reduction into highly unsaturated compounds, preferably containing hydrophilic functional groups as binding sites. It leads to elevation of the concentration of the OICs up to 183 µg/L in groundwater. This research provides new insights into the constraints of DOM molecular composition on the mobilization and enrichment of OICs in alluvial-lacustrine aquifers and thus improves our understanding of the genesis of geogenic iodine-contaminated groundwater systems.

Enhanced grey wolf algorithm for automatic tuning of an ensemble neural network in predicting PCF optical properties.

The structural characteristics of photonic crystal fibers (PCFs) determine their optical properties. This paper introduces an enhanced Grey Wolf Optimization algorithm termed ACD-GWO, which proposes adaptive strategies, chaotic mapping and dimension-based approaches and integrates them into the Grey Wolf Optimization framework. The aim is to achieve efficient automatic adjustment of hyperparameters and architecture for ensemble neural networks. The resulting ensemble neural network demonstrates accurate and rapid prediction of optical properties in PCFs, including effective refractive index, effective mode area, dispersion, and confinement loss, based on the PCF's structural characteristics. Compared to random forest and feedforward neural network models, the ensemble neural network achieves higher accuracy with a mean squared error of 3.78 × 10-6. Additionally, the computational time is significantly reduced, with only 2.27 minutes required for training and 0.08 seconds for prediction, which is much faster than numerical simulation software. This will provide new possibilities for optical device design and performance optimization, driving cutting-edge research and practical applications in the field of optics.

A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.

In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly.

Highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle.

One of the primary challenges for autonomous vehicle (AV) is planning a collision-free path in dynamic environment. It is a tricky task for achieving high-performance obstacle avoidance with velocity-varying obstacle. To solve this problem, a highly smooth and parameter independent obstacle avoidance method for autonomous vehicle with velocity-varying obstacle (HSPI-OAM) is presented in this work. The proposed method uses the virtual collision point model to accurately design the desired acceleration, which makes the obtained path highly smooth. At the same time, the method gets rid of the dependence on parameter adjustment and has strong adaptability to different environments. The simulation is implemented on the Matlab-Carsim co-simulation platform, and the simulation results show that the path planned by HSPI-OAM has good performance for obstacle with acceleration.

Reliability and validity study of the Chinese version of the Cerebellar Cognitive Affective Syndrome Scale in patients with cerebellar injury.

PURPOSE: To preliminarily investigate the reliability and validity of the Chinese version of the Cerebellar Cognitive Affective Syndrome Scale (CCAS scale) in the cerebellar injury population. METHODS: In this study, 40 patients with cerebellar injury and 39 normal individuals hospitalized in a stroke center were assessed using the Chinese version of the CCAS scale A, MMSE, and PHQ2, and the results were analyzed using content validity, structural validity, internal consistency, inter- rater agreement, and test-retest reliability. RESULTS: The correlation coefficients of semantic fluency, phonemic fluency, category switching, digit span forward, digit span backward, cube, verbal recall, similarities and Go No-Go subscores in the Chinese version of the CCAS scale A were 0.586-0.831 (P ≤ 0.05) with the total score, but there was no significant correlation between the affect and the total score (P = 0.110). The total cognitive score of the Chinese version of the CCAS scale A was correlated with the (r = 0.807, P ≤ 0.01), and the total score of the Chinese version of the CCAS scale A affect was correlated with the total score of PHQ2 (r = 0.884, P ≤ 0.01). The 2 factors were extracted using principal component analysis, and the cumulative variance contribution rate was 59.633%. The factor loadings of each of the corresponding factors were > 0.5, indicating good structural validity of the Chinese version of the CCAS scale A. Cronbach α = 0.827 indicated good internal consistency, and inter-rater reliability (ICC > 0.95) and test-retest reliability (ICC = 0.717-0.895)indicated that the Chinese version of the CCAS scale A had good inter-rater reliability and test-retest reliability. CONCLUSION: The Chinese version of the CCAS scale A has good reliability and validity in the cerebellar injury population and is useful for screening cerebellar cognitive-emotional syndrome.

Deciphering the spatial heterogeneity of groundwater arsenic in Quaternary aquifers of the Central Yangtze River Basin.

Significant spatial variability of groundwater arsenic (As) concentrations in South/Southeast Asia is closely associated with sedimentogenesis and biogeochemical cycling processes. However, the role of fine-scale differences in biogeochemical processes under similar sedimentological environments in controlling the spatial heterogeneity of groundwater As concentrations is poorly understood. Within the central Yangtze Basin, dissolved organic matter (DOM) and microbial functional communities in the groundwater and solid-phase As-Fe speciation in Jianghan Plain (JHP) and Jiangbei Plain (JBP) were compared to reveal mechanisms related to the spatial heterogeneity of groundwater As concentration. The optical signatures of DOM showed that low molecular terrestrial fulvic-like with highly humified was predominant in the groundwater of JHP, while terrestrial humic-like and microbial humic-like with high molecular weight were predominant in the groundwater of JBP. The inorganic carbon isotope, microbial functional communities, and solid-phase As-Fe speciation suggest that the primary process controlling As accumulation in JHP groundwater system is the degradation of highly humified OM by methanogens, which drive the reductive dissolution of amorphous iron oxides. While in JBP groundwater systems, anaerobic methane-oxidizing microorganisms (AOM) coupled with fermentative bacteria, iron reduction bacteria (IRB), and sulfate reduction bacteria (SRB) utilize low molecular weight DOM degradation to drive biotic/abiotic reduction of Fe oxides, further facilitating the formation of carbonate associated Fe and crystalline Fe oxides, resulting in As release into groundwater. Different biogeochemical cycling processes determine the evolution of As-enriched aquifer systems, and the coupling of multiple processes involving organic matter transformation­iron cycling­sulfur cycling-methane cycling leads to heterogeneity in the spatial distribution of As concentrations in groundwater. These findings provide new perspectives to decipher the spatial variability of As concentrations in groundwater.

Cellulose-based aerogel derived N, B-co-doped porous biochar for high-performance CO2 capture and supercapacitor.

The remarkable characteristics of porous biochar have generated significant interest in various fields, such as CO2 capture and supercapacitors. The modification of aerogel-derived porous biochar through activation and heteroatomic doping can effectively enhance CO2 adsorption and improve supercapacitor performance. In this study, a novel N, B-co-doped porous biochar (NBCPB) was synthesized by carbonating and activating the N, B dual-doped cellulose aerogel. N and B atoms were doped in-situ using a modified alkali-urea method. The potassium citrate was served as both an activator and a salt template to facilitate the formation of a well-developed nanostructure. The optimized NBCPB-650-1 (where 650 corresponded to activation temperature and 1 represented mass ratio of potassium citrate activator to carbonized NBCPB-400 precursor) displayed the largest micropore volume of 0.40 cm3·g-1 and a high specific surface area of 891 m2·g-1, which contributed to an excellent CO2 adsorption capacity of 4.19 mmol·g-1 at 100 kPa and 25 °C, a high CO2/N2 selectivity, and exceptional reusability (retained >97.5 % after 10 adsorption-desorption cycles). Additionally, the NBCPB-650-1 electrode also delivered a high capacitance of 220.9 F·g-1 at 1 A·g-1. Notably, the symmetrical NBCPB-650-1 supercapacitor exhibited a high energy density of 9 Wh·kg-1 at the power density of 100 W·kg-1. This study not only presents the potential application of NBCPB-650-1 material in CO2 capture and electrochemical energy storage, but also offers a new insight into easy-to-scale production of heteroatomic-modified porous biochar.

Influence of education level on MMSE and MoCA scores of elderly inpatients.

OBJECTIVE: The purpose of this study was to investigate the influence of education level on MMSE and MoCA scores of elderly inpatients. METHOD: This is a cross-sectional study. A total of 260 elderly inpatients were evaluated by the MMSE and MoCA sequentially. RESULTS: The total MMSE scores were highly correlated with the total MoCA scores (r = 0.7629, p < 0.0001), and were correlated with the length of education (r = 0.2723, p < 0.0001). The total MoCA scores were also correlated with the length of education (r = 0.3323, p < 0.0001). Meanwhile, MoCA was also used to reevaluate the elderly inpatients with normal MMSE scores at different education levels. There were no significant differences at different education levels (χ2=1.351, p = 0.5090). Finally, we analyzed the diagnostic consistency of MMSE and MoCA at different education levels, and the results showed that education level was closely related to the consistency of the diagnoses based on the MMSE and MoCA (χ2=10.23, p = 0.0368). CONCLUSIONS: In general, the results of both the MMSE and MoCA were influenced by education level, and this effect was more obvious for the MoCA. However, in the cognitive assessment of elderly patients, the ability to identify impairment with the MoCA is obviously superior to that with the MMSE.

A preliminary study of the Saint Louis University Mental Status examination (SLUMS) for the assessment of cognition in moderate to severe traumatic brain injury patients.

OBJECTIVES: To compare the sensitivity and specificity of the Saint Louis University Mental Status (SLUMS) examination, the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) in adults with moderate to severe traumatic brain injury (TBI). METHODS: In this cross-sectional study, 98 patients with moderate to severe TBI and 30 matched controls were evaluated. All participants were assessed using the MMSE, the MoCA and the SLUMS examination. RESULTS: The SLUMS, MoCA and MMSE scores of the TBI group were significantly lower than those of the control group, indicating that the cognitive function of patients with TBI was significantly impaired. The receiver operating characteristic (ROC) curve analysis indicated that the areas under the curve for the SLUMS examination, the MoCA and the MMSE were all greater than 0.8. There were no significant differences among the instruments, indicating that all three were equally effective for diagnosing cognitive impairment in patients with moderate to severe TBI. According to the ROC curve analysis, the optimal cutoff values for the SLUMS examination, the MoCA and the MMSE were 24.5, 21.5 and 28.5, respectively. At that cutoff value, the sensitivity and specificity of the SLUMS examination were well balanced, with both exceeding 80%. CONCLUSIONS: The SLUMS examination is better suited than the MMSE or the MoCA for assessing cognitive function in patients with moderate to severe TBI.

The Influence of Presentation Frames of Visualization Information for Safety on Situational Awareness under a Three-Level User-Interface Design.

To explore the influence of the construction and presentation frames of visualization information for safety (VIS) on people's situation awareness (SA), we designed a three-level user interface (UI) of VIS based on the three-stage SA theory, including perception (SA1), comprehension (SA2), and projection (SA3). Then, 166 subjects were recruited and divided into three groups to participate in the experiment, in which SA was measured by the situation-present-assessment method (SPAM) and situation-awareness-rating technique (SART), and eye-movement data were recorded. The results show that the level-3 UI design could effectively improve the subjects' SA levels. Although the increase in VIS displayed caused by the higher UI level led to a decrease in the perception-stage score of SA, the level-3 UI fully considered the three stages of human information processing, and helped improve the SA of the subjects; the overall SA score measured using the SART method was not significant, but the result was consistent with the SPAM. There was a framing effect on the presentation of VIS, and subjects perceived different degrees of risk under different presentation frames; that is, less risk under the positive frame, more risk under the negative frame, and a higher level of SA under the positive frame compared with the negative frame. To some extent, the nearest-neighbor-index (NNI) algorithm could be utilized to quantify subjects' eye-tracking fixation mode. While the frames were guided by the high-level interface and the positive presentation frame, the distribution of the subjects' gaze points was more discrete; they could grasp the relevant information more comprehensively and had a relatively high level of SA. To some extent, this study can provide a reference for the design and optimization of the VIS presentation interface.

An adaptive collision avoidance strategy for autonomous vehicle under various road friction and speed.

When the autonomous vehicle (AV) is under various road friction and speed, emergency collision avoidance is extremely difficult. In this situation, the AV may encounter severe understeering problem, so it is hard to achieve collision avoidance, even under the control of active safety system. To tackle this problem, an adaptive collision avoidance strategy (ACAS) is proposed for AV under various road friction and speed. The adaptive performance of the ACAS is realized via three aspects. (1) An adaptive reference path planning method is proposed to provide desired evasive speed and reference path for the AV according to various road friction and reduces the turning burden of AV. (2) A predictive-based fuzzy controller is designed to realize the speed control, and it improves the tracking accuracy of various desired evasive speed. (3) A novel turning enhanced method built with a direct yaw turning controller and a torque distribution method can enhance the turning capability of AV. Finally, the proposed strategy is verified on AV via simulation experiments. The code can be found online here: https://github.com/wangjinlei-hnu/ACAS.

Reliability and validity of the Brief Assessment of Impaired Cognition (Chinese version) for stroke patients.

Objective and accurate cognitive assessment scales are essential for guiding cognitive rehabilitation following stroke. The aim of this study was to evaluate the validity and reliability of the Mandarin Chinese version of the Brief Assessment of Impaired Cognition (BASIC) in stroke patients. The English version of the BASIC scale was translated into Mandarin Chinese, and 56 stroke patients at a stroke treatment center were enrolled in the study. The Mini-Mental State Examination (MMSE) and BASIC scale were used to evaluate the patients' cognitive function, and content validity, structural validity, concurrent validity, internal consistency, interrater consistency and reliability and test-retest reliability were used to evaluate the test results. The correlation coefficients between each item of the BASIC scale and the total score were between 0.416 and 0.804 (p < 0.05). The total score on the BASIC scale was correlated with the total score on the MMSE (r = 0.479, p < 0.05). Four factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 74.932%. The factor loading of each item on the corresponding factor was > 0.5, indicating that the scale has good structural validity. Internal consistency was good (Cronbach's α = 0.821), as were interrater (ICC > 0.95) and test-retest reliability (ICC = 0.815-0.941). Therefore, the Chinese version of the BASIC scale has good reliability and validity and can assist in screening for cognitive dysfunction or dementia in stroke patients.

Research on the formation mechanism of information cocoon and individual differences among researchers based on information ecology theory.

Introduction: Choosing to only retrieve and read academic information related to their own research field is conducive to researchers' in-depth understanding of their own research issues, and also reduces the pressure of researchers' information retrieval, but may bring about the effect of information cocoon. Methods: Based on the information ecology theory, a theoretical model is built from the aspects of information people, information, information environment and information technology, and relevant data is collected through questionnaires to verify assumptions. To explore the formation path of information cocoon for scientific researchers and the differences between different types of scientific researchers. Results: Different gender, education background, identity, age and team size of scientific researchers will lead to different dimensions in the process of producing information cocoon; Community influence, information homogeneity and value identification are important factors influencing the formation of information cocoon room for scientific researchers; Community influence and information homogeneity positively affect value identification. Discussion: In the future research work, researchers should pay attention to the influence of information homogeneity, community influence and value identification.

Social Q&A communities: A multi-factor study of the influence of users' knowledge sharing behaviors.

Recently, social Q&A communities have grown increasingly popular, serving as a primary platform for people to learn and share information. Nonetheless, fewer knowledge producers in these communities are significant than knowledge consumers. Thus, promoting users' participation in knowledge sharing is a challenge for managers of social Q&A communities. Even though many scholars have studied factors influencing willingness to share knowledge, they tend to start with one theory and ignore the impact of several factors on behaviors. Thus, this manuscript presents a multi-factor model based on three dimensions of technology, cognition, and security to explore the effects of the six factors of perceived ease of use and perceived usefulness, perceived behavioral control and subjective norms, perceived security, and perceived privacy in terms of the three knowledge sharing methods of browsing including like and favorite, publishing and replying, and to compare users' willingness to use the three knowledge sharing methods. A total of 482 questionnaires were collected online, and the hypotheses were tested and analyzed using structural equation modeling (SEM). According to the results, the factors affecting different sharing methods are not the same. Perceived behavioral control and perceived security can have a significant influence on their willingness to browse, users' willingness to publish and reply to posts is significantly influenced by their perception of behavioral control and subjective norms, while perceived usefulness also affects their willingness to respond, it can be seen that cognition is the most important factor affecting users' knowledge sharing among the three dimensions. In addition, users' willingness to browse is significantly greater than their willingness to reply, and their willingness to post is the lowest.

An Investigation of the Effects of Brain Fatigue on the Sustained Attention of Intelligent Coal Mine VDT Operators.

Intelligent mines require much more mental effort from visual display terminal (VDT) operators. Long periods of mental effort can easily result in operator fatigue, which further increases the possibility of operation error. Therefore, research into how brain fatigue affects the sustained attention of VDT operators in intelligent mines is important. The research methods were as follows: (1) Recruit 17 intelligent mine VDT operators as subjects. Select objective physiological indicators, such as reaction time, error rate, task duration, flicker fusion frequency, heart rate, electrodermal activity, and blink frequency, and combine these with the subjective Karolinska Sleepiness Scale to build a comprehensive brain fatigue evaluation system. (2) According to the fatigue-inducing experiment requirements, subjects are required to carry out mathematical operations in accordance with the rules during the presentation time, determine whether the results of the operations fall within the [7, 13] interval, and continue for 120 min to induce brain fatigue. (3) Perform the standard stimulus button response experiment of the sustained attention to response task, before and after brain fatigue, and compare each result. The results show that: (1) When the standard stimulus appeared in the EEG experiment, the amplitude of the early N100 component before and after brain fatigue was significantly different. When the bias stimulus appeared, the average amplitudes of the P200 component and the late positive component, before and after brain fatigue, were significantly different, suggesting that the brain fatigue of VDT workers in coal mines would reduce sustained attention; (2) After the 120 min of the continuous operation task, the subjects showed obvious brain fatigue. The objective brain fatigue was followed by an increase in reaction time, an increase in error rate, a decrease in flicker fusion frequency, an increase in heart rate, an increase in electrodermal current, an increase in the number of blinks, and a larger pupil diameter, and both the subjective and objective data indicated more significant changes in the subjects' brain fatigue at the 45th and 90th min. The results of the study could provide insight into the reduction in operational efficiency and safety of VDT operators in intelligent mines due to brain fatigue and further enrich the research in the area of brain fatigue in VDT operations.

Absolute quantification and characterization of oxylipins in lupus nephritis and systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with multi-organ inflammation and defect, which is linked to many molecule mediators. Oxylipins as a class of lipid mediator have not been broadly investigated in SLE. Here, we applied targeted mass spectrometry analysis to screen the alteration of oxylipins in serum of 98 SLE patients and 106 healthy controls. The correlation of oxylipins to lupus nephritis (LN) and SLE disease activity, and the biomarkers for SLE classification, were analyzed. Among 128 oxylipins analyzed, 92 were absolutely quantified and 26 were significantly changed. They were mainly generated from the metabolism of several polyunsaturated fatty acids, including arachidonic acid (AA), linoleic acid (LA), docosahexanoic acid (DHA), eicosapentanoic acid (EPA) and dihomo-γ-linolenic acid (DGLA). Several oxylipins, especially those produced from AA, showed different abundance between patients with and without lupus nephritis (LN). The DGLA metabolic activity and DGLA generated PGE1, were significantly associated with SLE disease activity. Random forest-based machine learning identified a 5-oxylipin combination as potential biomarker for SLE classification with high accuracy. Seven individual oxylipin biomarkers were also identified with good performance in distinguishing SLE patients from healthy controls (individual AUC > 0.7). Interestingly, the biomarkers for differentiating SLE patients from healthy controls are distinct from the oxylipins differentially expressed in LN patients vs. non-LN patients. This study provides possibilities for the understanding of SLE characteristics and the development of new tools for SLE classification.

Two potential fields fused adaptive path planning system for autonomous vehicle under different velocities.

Path planning is a basic function for autonomous vehicle (AV). However, it is difficult to adapt to different velocities and different types of obstacles including dynamic obstacle and static obstacle (such as road boundary) for AV. To solve the problem of path planning under different velocities and different types of obstacles, a two potential fields fused adaptive path planning system (TPFF-APPS) which includes two parts, a potential field fusion controller and an adaptive weight assignment unit, is presented in this work. In the potential field fusion controller, a novel potential velocity field is built by velocity information and fused with a traditional artificial potential field for adapting various velocities. The adaptive weight assignment unit is designed to distribute adaptively the weights of two potential fields for adapting different types of obstacles at the same time, including road boundary and dynamic obstacles. The simulation is carried on the Carsim-Matlab co-simulation platform, and the simulation results indicate that the proposed TPFF-APPS has excellent performance for path planning adapting to different velocities and different types of obstacles.

Interacting multiple model-based adaptive control system for stable steering of distributed driver electric vehicle under various road excitations.

Distributed driver electric vehicle (DDEV) works under various road excitations in practice, which may cause the changes in steering performance significantly. However, the various road excitations are not a priority for stable steering problem of DDEV, and this possibly leads to unstable steering performance, particularly oversteer or tail flick. To solve this problem, an interacting multiple model-based adaptive control system (IMM-ACS) is presented in this work. The proposed IMM-ACS integrates an interacting multiple model controller (IMMC) and a stable steering controller (SSC). The IMMC is designed to establish an adaptive vehicle model based on four typical road models, and to improve the adaptability of control system to various road excitations by the model interaction method. The SSC is designed to guarantee the yaw and longitudinal stability based on the adaptive vehicle model, by the active steering and torque distribution, and the SSC is realized by the model predictive controller (MPC). Besides, this work establishes a Carsim-Matlab co-simulation platform, where the simulation is designed and the results show that the proposed IMM-ACS can achieve excellent steering performance for DDEV with the adaptive capacity.

Molecular Cloning and Expression Profiles of Thermosensitive TRP Genes in Agasicles hygrophila.

Global warming has gradually reduced the control efficacy of Agasicles hygrophila against the invasive weed Alternanthera philoxeroides. To better understand the summer collapse of A. hygrophila populations, we cloned the cDNA sequences of the high temperature-sensing TRPA1, Painless, and Pyrexia from A. hygrophila, and analyzed their temporal expressions and the impacts of high temperatures on their expression in eggs, the most vulnerable stage of A. hygrophila to hot temperatures. All the three genes obtained had the signature domains of TRPA channels and were constitutively expressed in eggs, larvae (L1, L2, L3), pupae, and adults, but AhPainless had the highest expression, followed by AhPyrexia, and AhTRPA1. The lowest and highest expression stages were adult and pupae for AhTRPA1, egg and L3 for AhPainless, and pupae/adult and L2 for AhPyrexia. The expressions of AhTRPA1, AhPainless, and AhPyrexia remained low at the preferred temperature range of 25-28 °C, elevated to their peak levels at 37.5, 30, and 30 °C, respectively, then fell to their 25-28 °C levels (AhTRPA1, AhPainless) or a lower level (AhPyrexia) at one or more temperatures >30 or 37.5 °C. These results suggest that their temperature-sensing roles and importance may be different, stage-specific, and their expression may be decoupled from their activation.

Heat sensitivity of eggs attributes to the reduction in Agasicles hygrophila population.

Agasicles hygrophila has been introduced worldwide as a control agent for the invasive weed Alternanthera philoxeroides. However, global warming has potential impact on its controlling efficacy. The aim of this research was to explore the primary factors responsible for the greatly reduced A. hygrophila population in hot summers. To imitate the temperature conditions in summers, different developmental stages of A. hygrophila were treated with high temperatures from 32.5 °C to 45 °C for 1-5 h. Based on the survival rate, the heat tolerance of each developmental stage was ranked from lowest to highest as follows: egg, 1st, 2nd, 3rd instar larva, adult and pupa. Eggs showed the lowest heat tolerance with 37.5 °C as the critical temperature affecting larval hatching. Heat treatment of the A. hygrophila eggs at 37.5 °C for 1 h decreased the hatch rate to 24%. Our results indicated that when compared with the control at 25 °C, 1 h treatment at 37.5 °C prolonged the duration of the egg stage, shortened the duration of oviposition and total longevity, and changed the reproductive pattern of A. hygrophila. The net reproductive rate, intrinsic rate and finite rate were all significantly reduced. The results suggest that low heat tolerance of the eggs was the major factor responsible for the reduction of A. hygrophila populations, and the key temperature was 37.5 °C. Therefore, appropriate measures should be taken to protect eggs in order to maintain the efficacy of A. hygrophila in the biological control of A. philoxeroides in hot summers.