Dynamic landslide susceptibility mapping based on the PS-InSAR deformation intensity.

In order to meet the needs of refined landslide risk management, the extended correlation framework of dynamic susceptibility modeling desiderates to be further explored. This work considered the Wanzhou channel of the Three Gorges Reservoir Area as the experimental site, with a transportation channel with significant economic value to carry out innovative research in two stages. (i) Five machine learning models logistic regression (LR), multilayer perceptron neural network (MLPNN), support vector machine (SVM), random forest (RF), and decision tree (DT) were used to explore landslide susceptibility distribution based on detailed landslide boundaries. (ii) Based on the PS-InSAR technology, the dynamic factor of deformation intensity was obtained. Subsequently, the dynamic factor was combined with proposed static factors (topography conditions, geological conditions, hydrological conditions, and human activities) to generate dynamic landslide susceptibility mapping (DLSM). The receiver operating characteristic (ROC) curve, accuracy, precision, recall, and F1 score were proposed as evaluation metrics. Compared with ignoring the dynamic factor, the predictive accuracy of some models was further improved when considering the dynamic factor. Especially the DT model, the area under the curve of ROC (AUC) value increased by 2%, and obtained the highest AUC value (93.1%). The susceptibility results of introducing the dynamic factor are more in line with the spatial distribution of actual landslides. The research framework proposed in this study has important reference significance for the dynamic management and prevention of landslide disasters in the study area.

Using HFACS to understand human error in railway dispatcher performance: a study of proactive safety inspection records.

This study analyzes 4,095 proactive safety inspection records obtained from a large dispatching centre by utilising the HFACS framework. These proactive safety inspection records offer comprehensive documentation of incidents, capturing major accidents and numerous minor discrepancies and lapses that often go unnoticed in accident reports. The analysis revealed that most incidents were attributed to unsafe actions, primarily skill-based errors and poor decision-making. Additionally, contributing factors such as adverse mental states, personal readiness, and crew resource management were found to play a significant role as preconditions for unsafe acts. Path analyses further established a significant correlation between factors such as unsafe supervision, preconditions for unsafe acts, and the occurrence of unsafe acts. In our discussion, we critically evaluate the strengths and limitations of proactive safety inspection records in safety research. Moreover, we emphasise these findings' potential to enhance safety within the railway industry.

Based on a substantial dataset comprising proactive safety inspection records of railway dispatchers rather than the incident reports utilised in prior studies, this paper presents a causal model of human error among railway dispatchers in combination with HFACS and critically evaluates the strengths and limitations of active safety inspection records.

Study of Pharmacokinetics for Ivermectin B1a from Beagle Dogs.

Ivermectin has been widely used for antiparasitic drug, and has recently shown a broad-spectrum antiviral activity, including anti-Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the pharmacokinetic property of ivermectin has not been fully investigated yet. During the plasma preparation, ~32-46% of ivermectin was found in the precipitation. An Liquid Chromatograph-Mass Spectrometer (LC-MS/MS) method for ivermectin in the whole blood samples from beagle dogs was developed and validated. The specificity, accuracy, precision (intra-day and inter-day), matrix effect, recovery and stability of analyte reported here are satisfied with the criteria of Food and Drug Administration (FDA)-Bioanalysis guideline. The oral administrations pharmacokinetics of ivermectin in beagle dogs under fasting and after high-fat meal were studied, and the following parameters were obtained: fasting Cmax, 104 ± 35 µg·L-1; area under the concentration-time curve (AUC0-∞), 2,555 ± 941 h·µg·L-1; and high-fat meal Cmax, 147 ± 35 µg·L-1; AUC0-∞, 4,198 ± 1,279 h·µg·L-1. When the P-gp inhibitor curcumin was also coadministrated orally, Cmax and AUC0-∞ were found to be 177 ± 57 and 4,213 ± 948 h·µg·L-1, respectively. With the comparison to fasting treatment, coadministration of P-gp inhibitor curcumin resulted in increase of the exposure of ivermectin by 1.6-fold, while the exposure after the high-fat diet versus fasting was increased approximately in 1.4-fold, indicating that alternative absorption might play an important role for increasing the exposure of ivermectin for future clinic applications.

A python system for regional landslide susceptibility assessment by integrating machine learning models and its application.

Landslide susceptibility assessment is considered the first step in landslide risk assessment, but current studies mostly rely on GIS platforms or other software for data preprocessing. The modeling process is relatively complicated and multi-models cannot be integrated. With regard to this issue, this study develops a Python system for automatic assessment of regional landslide susceptibility. The Python system implements landslide susceptibility assessment through three modules: geographic data processing, machine learning modeling and result evaluation analysis. For geographic data processing, ten landslide influencing factors can be used to construct an evaluation factor dataset and reclassify the thematic maps based on the frequency ratio method. Four built-in machine learning models (logistic regression (LR), multi-layer perceptron (MLP), support vector machine (SVM) and extreme gradient boosting (XGBoost)) are integrated into the system to complete susceptibility modeling and calculation. Additionally, receiver operating characteristic (ROC) curves can be automatically generated to evaluate the accuracy. The system was then applied into Lantian County in Shaanxi Province as a demonstration example. The results show that the areas under the ROC curve (AUC) of the four models are 0.838 (LR)、0.882 (SVM)、0.809 (MLP) and 0.812 (XGBoost), respectively, indicating that the SVM model was the most suitable model for landslide susceptibility assessment in Lantian County in the Loess Plateau of China. The system has now been made open source on Github, which can effectively improve the efficiency of regional landslide susceptibility assessment, especially provide tools for data processing and modeling for non-professionals.

A multi-level analysis on the causes of train-pedestrian collisions in Southwest China 2011-2020.

Collisions between trains and pedestrians are the primary cause of railway casualties. However, there remains a lack of comprehensive understanding regarding the underlying causes of this phenomenon. This study employs a multi-level approach to investigate the factors associated with the occurrence and severity of train-pedestrian collisions. The investigation is based on 2160 independent cases that occurred in southwest China from 2011 to 2020. Multiple contributing factors related to the victim, train, track, and socio-economic status of the surrounding district were examined, utilizing information from various sources. At the county level, several risk factors were identified in predicting the occurrence rate. These factors include higher population density and a greater number of normal-speed stations. However, the presence of high-speed train stations did not exhibit any significant impact. Additionally, the study found that regulations pertaining to protective fences were highly effective in reducing the occurrence rate. Regarding the prediction of collision severity, certain factors were found to increase the death rate. These factors include young men as victims, engaging in lying down or crossing behaviors, higher train speeds, gentle downhill slopes, lower education levels, and a higher proportion of the labor force. These findings emphasize the necessity of adopting a comprehensive perspective when examining the causes of train-pedestrian collisions. Furthermore, it underscores the significance of considering the notable differences between rapidly developing countries such as China and developed countries. Based on our findings, we also provide corresponding policy suggestions.

Establishment of recombinant Catharanthus roseus stem cells stably overexpressing ORCA4 for terpenoid indole alkaloids biosynthesis.

Catharanthus roseus is a perennial herb of the Apocynaceae family, from which about 200 kinds of alkaloids have been characterized. Most alkaloids from C. roseus are terpenoid indole alkaloids (TIAs), such as vinblastine and vincristine, which are widely used in the clinic for their good antitumor activity. However, they were only biosynthesized in C. roseus, and their content in C. roseus is extremely low. The access to these valuable compounds is by plant extraction or chemical semisynthesis from their precursors catharanthine and vindoline. Since catharanthine and vindoline are also obtained from C. roseus, the supply of vinblastine and vincristine makes it difficult to meet market demands. Therefore, how to improve the yield of TIAs is an attractive issue. In this study, we compared the regulatory effect of two critical transcription factors, octadecanoid-derivative responsive Catharanthus AP2-domain protein 3 (ORCA3) and octadecanoid-derivative responsive Catharanthus AP2-domain protein 4 (ORCA4), on the biosynthesis of TIAs in C. roseus. The results showed that overexpressing both two transcription factors could increase the accumulation of TIAs. The effect was more significant when ORCA4 was overexpressed. To acquire C. roseus TIAs on a continuous and consistent basis, we then created and acquired C. roseus stem cells stably overexpressing ORCA4. This is the first time a recombinant C. roseus stem cell system with stable ORCA4 overexpression has been developed, which not only provides new ideas for future research in this area but also breaches new life into the industrial application of using plant cell culture to obtain natural products.

How Work-Family Conflict Influenced the Safety Performance of Subway Employees during the Initial COVID-19 Pandemic: Testing a Chained Mediation Model.

This study examined the impact of work-family conflict on subway employees' safety performance during the initial wave of the COVID-19 pandemic. We proposed a chain mediation model in which job burnout and affective commitment play mediating roles in this process. Using questionnaire data from 632 Chinese subway employees during February 2020, structural equation modeling analyses were performed. The analyses showed that work-family conflict had a significant negative impact on subway employee safety performance. Moreover, job burnout completely mediated the influence of work-family conflict on safety performance, while affective commitment only partially mediated the influence of job burnout on safety performance. These findings suggest the important role played by Work-Family balance during the pandemic and contribute to a deeper understanding of the inner mechanisms. We also discussed several practical implications for organizations to reduce the negative impact of work-family conflict on safety performance.

The Effect of Time Window Length on EEG-Based Emotion Recognition.

Various lengths of time window have been used in feature extraction for electroencephalogram (EEG) signal processing in previous studies. However, the effect of time window length on feature extraction for the downstream tasks such as emotion recognition has not been well examined. To this end, we investigate the effect of different time window (TW) lengths on human emotion recognition to find the optimal TW length for extracting electroencephalogram (EEG) emotion signals. Both power spectral density (PSD) features and differential entropy (DE) features are used to evaluate the effectiveness of different TW lengths based on the SJTU emotion EEG dataset (SEED). Different lengths of TW are then processed with an EEG feature-processing approach, namely experiment-level batch normalization (ELBN). The processed features are used to perform emotion recognition tasks in the six classifiers, the results of which are then compared with the results without ELBN. The recognition accuracies indicate that a 2-s TW length has the best performance on emotion recognition and is the most suitable to be used in EEG feature extraction for emotion recognition. The deployment of ELBN in the 2-s TW can further improve the emotion recognition performances by 21.63% and 5.04% when using an SVM based on PSD and DE features, respectively. These results provide a solid reference for the selection of TW length in analyzing EEG signals for applications in intelligent systems.

Groundwater level prediction based on a combined intelligence method for the Sifangbei landslide in the Three Gorges Reservoir Area.

The monitoring and prediction of the groundwater level (GWL) significantly influence the landslide kinematics. Based on the long-term fluctuation characteristics of the GWL and the time lag of triggering factors, a dynamic prediction model of the GWL based on the Maximum information coefficient (MIC) algorithm and the long-term short-term memory (LSTM) model was proposed. The Sifangbei landslide in the Three Gorges Reservoir area (TGRA) in China, wherein eight GWL monitoring sensors were installed in different locations, was taken as a case study. The monitoring data represented that the fluctuation of the GWL has a specific time lag concerning the accumulated rainfall (AR) and the reservoir water level (RWL). In addition, there were spatial differences in the fluctuation of the GWL, which was controlled by the elevation and the micro landform. From January 19, 2015, to March 6, 2017, the measured data were used to set up the predicted models. The MIC algorithm was adopted to calculate the lag time of the GWL, the RWL, and the AR. The LSTM model is a time series prediction algorithm that can transmit historical information. The Gray wolf optimization (GWO) algorithm was used to seek the most suitable hyperparameter of the LSTM model under the specific prediction conditions. The single-factor GWO-LSTM model without considering triggering factors and the support vector machine regression (SVR) model were considered to compare the prediction results. The results indicate that the MIC-GWO-LSTM model reached the highest accuracy and improved the prediction accuracy by considering the factor selection process with the learner training process. The proposed MIC-GWO-LSTM model combines the advantages of each algorithm and effectively constructs the response relationship between the GWL fluctuation and triggering factors; it also provides a new exploration for the GWL prediction, monitoring, and early warning system in the TGRA.

Characteristics of Train-Pedestrian Collisions in Southwest China, 2011-2020.

Although train-pedestrian collisions are the primary source of railway casualties, the characteristics of this phenomenon have not been fully investigated in China. This study examined such collisions in the Greater Sichuan-Chongqing area of China by conducting a thorough descriptive analysis of 2090 incident records from 2011 to 2020. The results showed that such collisions have declined gradually over the past decade, but the fatality rate remains high. We found that such collisions were more likely to happen to men, senior citizens and people crossing the tracks and that they occurred more frequently in the morning. While collision rates dropped in February, collisions were more likely to occur in December. In contrast to the situation in Western countries, weekends were not related to increased occurrence. The absence of a protective fence led to a higher collision rate, but level crossings are no longer a concern since most such structures in China have been rebuilt as overpasses. Mild slopes and extreme curvatures were also found to increase the occurrence of such collisions. Freight trains were most likely to be involved in train-pedestrian collisions, and collisions caused by high-speed trains were rare both absolutely and relatively. However, when collisions did occur, higher train speeds were linked with higher fatality rates. The findings suggest that patterns of train-pedestrian collisions in China differ from those in the Western world. This difference might be caused by differences in culture, geography, weather and railway development policies. Future research directions and possible preventive measures are also discussed.

Influence of two-period cross-over design on the bioequivalence study of gefitinib tablets in beagle dogs.

Generally, two-period cross-over design is used in bioequivalence (BE) study. High intra-subject variability of gefitinib was reported in a clinical BE study, and significant changes in gefitinib exposures were observed among different periods in our previous BE study in dogs. Therefore, commercial gefitinib tablets from the same batch were used in the present study and assigned to two groups: the testing drug (GF1) group and the reference drug (GF2) group. A single-oral-dose, two-period cross-over study with a 7-day washout (approximately 24 half-lives) under fasting condition was conducted in 12 dogs to explore the factors. The results showed that the mean values of AUC(0-t), AUC(0-∞), Cmax and Tmax of these two GF1 and GF2 groups were similar. However, the GF1 and GF2 did not meet the acceptance criteria of bioequivalence with 90% confidence intervals, since the values obtained were 76.22%-117.43% for AUC(0-t) and 87.55%-131.59% for Cmax. ANOVA revealed a significant difference between the two periods (P < 0.05). Interestingly, the mean AUC(0-t) of gefitinib in the period 2 was 2.3-fold greater than that in the period 1, while Cmax in the period 2 was 1.7-fold higher than that in the period 1. However, the volume of distribution was significantly decreased, becoming 0.4-fold lower in the period 2. No statistically significant difference in the half-life and Tmax was observed between the two periods (P < 0.05). The pharmacokinetic alteration might come from the different physiological absorption and/or metabolism between periods. Since a 7-day washout interval was applied, DDI risk from P450s and/or P-gp would not play a significant role in the non-bioequivalence. As regard the variability, the intra-subject variation crossing the periods was much larger than the inter-subject variation within each period. The absorption and/or metabolism function of the gut bacteria might play an important role in the increasing exposure of gefitinib in the second period, especially with the comparison with the analysis from the high-fat-diet treatments in humans. Therefore, further studies might be needed to evaluate whether the assessment of bioequivalence could be facilitated by a much longer washout interval allowing the recovery of gut bacteria.

The Adoption of QR Code Mobile Payment Technology During COVID-19: A Social Learning Perspective.

The increasing number of quick response (QR) code mobile payment users heralds the coming of a cashless society. However, the extent to which the coronavirus disease 2019 (COVID-19) pandemic accelerated the adoption of QR code mobile payment has not been sufficiently researched. Based on social learning theory, this study models how external interaction with the environment has affected the internal appraisal and behavioral intention to adopt QR code mobile payment during COVID-19. Empirical results from 248 respondents revealed that perceived severity and social influence positively affected the perception of utilitarian and health benefits of respondents, which in turn influenced the behavioral intention to use the QR code mobile payment. The theoretical contribution and managerial implications of this study are also discussed.

Effects of rainfall on surface environment and morphological characteristics in the Loess Plateau.

Slope failure is a one of major process that causes severe landform variation and environment variation, and slope failure has become a major hidden danger to human settlement and urban construction in this vast loess region. The physical model of slope failure as induced by artificial rainfall was constructed in the field, and monitored the pore water pressure (PWP), earth stress (ES), volumetric water content (VWC), electrical conductivity (EC), and temperature (T) of the soil using this physical simulation. The surface morphology of slope started to occur in the slope as a result of erosion caused by rainfall and rainwater infiltration at the beginning of the experiment; concurrently, PWP, ES, VWC, and EC were increased gradually. Meanwhile, the saturated weight of the soil rose. In the middle of the experiment, PWP, ES, VWC, and EC were increased rapidly as the artificial rainfall continued, and the ratio of soil pore the soil fell. The slope landform was obviously occurred during the experiment, when it was noted that PWP, ES, VWC, and EC of the soil rapidly decreased. Afterwards, slope failure evolved into a debris flow; eventually, the landform was entirely changed in the slope. The soil became more compact toward the end of the experiment, and PWP, ES, VWC, and EC were slowly increased; these factors indicated that the loess slope was temporarily stable. This study could potentially be used to provide the relevant parameters for numerical simulations of landform variation in loess regions, and provide reference for regional land use planning and environmental development.

Contingent negative variation during a modified cueing task in simulated driving.

The obscured pedestrian-motor vehicle crash has become a serious danger to driving safety. The present study aims to investigate the contingent negative variation (CNV) during the anticipation of an obscured pedestrian-motor vehicle crash in simulated driving. We adopted two cueing tasks: (i) a traditional cognitive paradigm of cueing task that has been widely used to study anticipatory process, and (ii) a modified cueing task in simulated driving scenes, in which Electroencephalogram (EEG) signals of 32 participants were recorded to detect the CNV. Simulated car following and pedestrian crossing tasks were designed to measure anticipation-related driving behaviors. The results showed that both early and late CNVs were observed in two cueing tasks. The mean amplitude of the late CNV during a modified cueing task in simulated driving was significantly larger than that in a traditional cueing task, which was not the case for the early CNV potentials. In addition, both early and late CNVs elicited in simulated driving were significantly correlated with anticipatory driving behaviors (e.g., the minimum time to collision). These findings show that CNV potentials during the anticipation of an obscured pedestrian-motor vehicle crash might predict anticipation-related risky driving behaviors.

Regional Rainfall Warning System for Landslides with Creep Deformation in Three Gorges using a Statistical Black Box Model.

Establishing an efficient regional landslide rainfall warning system plays an important role in landslide prevention. To forecast the performance of landslides with creep deformation at a regional scale, a black box model based on statistical analysis was proposed and was applied to Yunyang County in the Three Gorges Reservoir area (TGRA), China. The data samples were selected according to the characteristics of the landslide displacement monitoring data. Then, the rainfall criteria applied to different time periods were determined by correlation analysis between rainfall events and landslides and by numerical simulation on landslide movement under certain rainfall conditions. The cumulative rainfall thresholds that were determined relied on the displacement ratio model, which considered landslide scale characteristics and the statistical relationship between daily rainfall data and monthly displacement data. These thresholds were then applied to a warning system to determine a five-level warning partition of landslides with creep deformation in Yunyang County. Finally, landslide cases and displacement monitoring data were used to validate the accuracy of the model. The validation procedure showed that the warning results of the model fit well with actual conditions and that this model could provide the basis for early warning of landslides with creep deformation.

Studies on oral bioavailability and first-pass metabolism of withaferin A in rats using LC-MS/MS and Q-TRAP.

Withaferin A (WA) is one of the major bioactive steroidal lactones with extensive pharmacological activities present in the plant Withania somnifera. The absolute oral bioavailability of WA remains unknown and human-related in vitro data are not available. Therefore, in the present study, the absolute oral bioavailability of WA in male rats and the in vitro screening of absorption factors by Q-trap and LC-MS/MS analysis were conducted to explore possible clinical properties of WA. The developed and validated analytical methods were successfully applied to the pharmacokinetic studies and in vitro measurement of WA. The oral bioavailability was determined to be 32.4 ± 4.8% based on intravenous (5 mg/kg) and oral (10 mg/kg) administrations of WA in male rats. The in vitro results showed that WA could be easily transported across Caco-2 cells and WA did not show as a substrate for P-glycoprotein. Moreover, the stability of WA was similar between male rat and human in simulated gastric fluid (stable), in intestinal microflora solution (slow decrease) and in liver microsomes (rapid depletion, with a half-life of 5.6 min). As such, the first-pass metabolism of WA was further verified by rat intestine-liver in situ perfusion, revealing that WA rapidly decreased and 27.1% remained within 1 h, while the content of three major metabolites (M1, M4, M5) identified by Q-trap increased. This perfusion result is consistent with the oral bioavailability results in vivo. The first-pass metabolism of WA might be the main barrier in achieving good oral bioavailability in male rats and it is predicted to be similar in humans. This study may hold clinical significance.

Comparison of in vitro/in vivo blood distribution and pharmacokinetics of artemisinin, artemether and dihydroartemisinin in rats.

Artemisinin and its derivatives have been widely used for treatment of malaria and the therapeutic targets are considered within the red blood cells. In the recent studies on the erythrocytes' uptake of artemisinin-derivatives in vitro, applying the radioisotope-labeled technology, it was trying to predict the in vivo disposition properties, but different distribution results were revealed from a preliminary study in one human. The pharmacokinetic differences among blood cells and plasma still remain unclear. To explore the therapeutic related pharmacokinetics and compare the in vitro-in vivo blood distribution in rats, an improving blood sample preparation and LC-MS/MS detection method was developed and successfully validated. The lower limit of quantification was smaller than the previous studies. In the in vitro blood distribution studies, the content ratios from blood cells to plasma were compared in the concentrations from 20 ng/mL to 1000 ng/mL. Such ratios were determined to be 1.1-1.6 for artemisinin, 0.9-1.2 for artemether, and around 0.7 for dihydroartemisinin. In the oral administration pharmacokinetic studies in rats, the concentration ratios from blood cells to plasma were from high (2.6-3.6) to medium (1.3-2.5), and low (0.5-1.5) for artemisinin, artemether, and dihydroartemisinin respectively in all measuring time points, displaying the similar affinity order toward blood cells in artemisinin > artemether > dihydroartemisinin as the in vitro measurements. The dosages of 10 mg/kg for intravenous administrations of artemisinin and 200 mg/kg for oral administrations of artemisinin or artemether were used for the pharmacokinetic study in rats. The geometric mean exposures (AUC(0-t)) of artemisinin, artemether and dihydroartemisinin in blood cells were determined to be 2.6 folds, 1.7 folds, or 1.2 folds greater than those in plasma, respectively. Referring to the in vitro distribution, the AUC(0-t) ratios from the blood cells measurements to the plasma measurements of these three antimalarial drugs were also in a similar trend as the in vitro distribution measurements. Furthermore, the half-life (t1/2) of artemether in blood cells was even longer than that in plasma, while the clearance of artemisinin, artemether, or dihydroartemisinin in blood cells was slower than that in plasma. Particularly, it was found that the concentrations of artemisinin and artemether were presented in blood cells over longer time period than in plasma above their antimalarial IC50, which might result from both the affinity toward blood cells and the drugs clearance differences between blood cells and plasma. These results were indicated that the exposures and pharmacokinetic properties in the whole blood or the blood cells should be taken into account for the drug candidates with higher distribution affinity toward blood cells especially for the antimalarial drugs.

The impairing effects of mental fatigue on response inhibition: An ERP study.

Mental fatigue is one of the main reasons for the decline of response inhibition. This study aimed to explore the impairing influence of mental fatigue on a driver's response inhibition. The effects of mental fatigue on response inhibition were assessed by comparing brain activity and behavioral indices when performing a Go/NoGo task before and after a 90-min fatigue manipulation task. Participants in the driving group performed a simulated driving task, while individuals in the control group spent the same time watching movies. We found that participants in the driving group reported higher levels of mental fatigue and had a higher percentage of eye closure and larger lateral deviations from their lane positions, which indicated there was effective manipulation of mental fatigue through a prolonged simulated driving task. After manipulation of mental fatigue, we observed increased reaction time and miss rates, delayed NoGo-N2 latency and Go-P3 latency, and decreased NoGo-P3 amplitude, which indicated that mental fatigue may slow down the speed of the inhibition process, delay the evaluation of visual stimuli and reduce the availability of attentional resources. These findings revealed the underlying neurological mechanisms of how mental fatigue impaired response inhibition.

The Impairing Effect of Mental Fatigue on Visual Sustained Attention under Monotonous Multi-Object Visual Attention Task in Long Durations: An Event-Related Potential Based Study.

The impairing effects of mental fatigue on visual sustained attention were assessed by event-related potentials (ERPs). Subjects performed a dual visual task, which includes a continuous tracking task (primary task) and a random signal detection task (secondary task), for 63 minutes nonstop in order to elicit ERPs. In this period, the data such as subjective levels of mental fatigue, behavioral performance measures, and electroencephalograms were recorded for each subject. Comparing data from the first interval (0-25 min) to that of the second, the following phenomena were observed: the subjective fatigue ratings increased with time, which indicates that performing the tasks leads to increase in mental fatigue levels; reaction times prolonged and accuracy rates decreased in the second interval, which indicates that subjects' sustained attention decreased.; In the ERP data, the P3 amplitudes elicited by the random signals decreased, while the P3 latencies increased in the second interval. These results suggest that mental fatigue can modulate the higher-level cognitive processes, in terms of less attentional resources allocated to the random stimuli, which leads to decreased speed in information evaluating and decision making against the stimuli. These findings provide new insights into the question that how mental fatigue affects visual sustained attention and, therefore, can help to design countermeasures to prevent accidents caused by low visual sustained attention.