Time Cumulative Effect Research Articles

The combination mode of forest and SVM for power network disaster response failure identification

The damage to power transmission and distribution equipment in different regions is inseparable from the erosion of natural and artificial disasters, affecting the power grid's regular power supply and users' typical power consumption. Therefore, research on failure risk prediction technology for power transmission and distribution equipment under different disasters has increasingly become critical to power grid reliability. Based on the combination mode of forest and Support Vector Machine (SVM), this study proposes a disaster response failure prediction model that considers the time cumulative effect of disaster elements. Based on this model, the failure degree indicators of different disaster elements are constructed by analyzing the relationship between disaster frequency and time. Then, the historical disaster data is used to calculate the index and form a training set with the monitoring data. The binary decision graph transformation method is combined with the adjacent node priority method to obtain the minimum cut set, and the SVM regression method is used to train to get the prediction model. The experimental results show that the effectiveness and accuracy of the proposed method are verified through the analysis of numerical examples and comparison of various techniques. The model's accuracy is 8.63 % higher than that of the traditional disaster prediction model, and the error rate of disaster failure prediction analysis is not more than 0.01.

Simulation of gross primary productivity and impact of drought in Liulin watershed of Taihang mountains over 2000–2020

As the largest flux in the global terrestrial carbon cycle, Gross Primary Productivity (GPP) is a key factor for the terrestrial carbon budget. Based on the eddy flux tower data, remote sensing data and the meteorological precipitation data, we calibrated three parameters of maximum light use efficiency, optimum temperature, and maximum temperature in the Vegetation Photosynthesis Model (VPM) to reproduce the GPP spatiotemporal characteristic in Liulin watershed of Taihang Mountains. We further analyzed the time lag effect and cumulative effect of the standard precipitation index (SPI) on GPP by the Pearson correlation coefficients. Results show that VPM captures the GPP characteristics of eddy flux tower observation in Liulin watershed. During the calibration period (R2 = 0.94, RMSE = 0.47 g C m-2·d-1) and validation period (R2 = 0.91, RMSE = 0.60 g C m-2 d-1), the adjusted VPM model successfully reproduced the temporal dynamics of site-observed GPP. From 2000 to 2020, VPM model can effectively reproduce the long-term variations in GPP (R2 = 0.69 vs. NIRv_GPP), with the GPP ranging from 446.4 to 828.1 g C m-2 y-1 and an average value of 545.6 g C m-2 y-1 in Liulin watershed. The GPP exhibited an increasing trend from 2000 to 2020. A mutation in the GPP occurred in 2010, with an average annual increase of 13.9 g C m-2 y-1 from 2000 to 2010 (p < 0.05), followed by an average annual increase of 10.22 g C m-2 y-1 from 2011 to 2020 (p > 0.05). The SPI effectively monitored drought events in the Liulin watershed. With a cumulative effect of 9 months and a lag effect of 6–7 months, the time lag and cumulative effects of drought had a long-term effect on GPP. It is imperative to have long-term eddy flux tower data and meteorological data to better evaluate the spatiotemporal dynamics of GPP and the impact of drought.

State space model detection of driving fatigue considering individual differences and time cumulative effect

Fatigue is an important cause of traffic crashes, and effective fatigue detection models can reduce these crashes. Research has found large differences in fatigued driving performance from driver to driver, as well as a significant cumulative effect of fatigue on a given driver over time. Both sources of variation can decrease the accuracy of detection systems, but previous studies have not done enough to evaluate these differences. The purpose of this study is therefore to develop a fatigue detection model that considers individual differences and the time cumulative effect of fatigue. Data on the lateral position of the car in its lane, steering wheel movement, speed, and eye movement were collected from 22 drivers using a driving simulator with an eye-tracking system. Drivers’ subjective fatigue scores were collected using the Karolinska Sleepiness Scale. State space models (SSMs) were built to detect fatigue in each driver, considering his or her individual features. As a time series model, the SSM can also address the time cumulative effect of fatigue, and it does not require a large dataset to achieve high levels of accuracy. The differences in SSM results confirm that diversity does exist among drivers’ fatigued driving performance, so the ability of the SSM to take into account driver-specific information from each individual driver suggests that it is more suitable for fatigue detection than models that use aggregated driver data. Results show that the fatigue detection accuracy of the SSM (77.73%) is higher than that of artificial neural network models (61.37%). The advantages of accuracy, high interpretability, and flexibility make the SSM a comprehensive and valuable individualized fatigue detection model for commercial use.

Quantifying the drought sensitivity of grassland under different climate zones in Northwest China

Grassland is essential for maintaining the stability and functionality of terrestrial ecosystems. Although previous research has explored how grassland responds to drought, the drought sensitivity of grassland (DSG) across climate zones and aridity gradients remains uncertain. In this study, we conducted a comprehensive investigation spanning 1982 to 2015 in Northwest China. To assess the time-cumulative effect (TCE) and the time-lag effect (TLE) of drought on grassland, we employed Spearman rank correlation analysis, utilizing long-term datasets of the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). This analysis allowed us to quantify the DSG in the region and further examine its variations across climate zones and aridity gradient. Our results revealed that 81.2 % and 99.7 % of the grassland in Northwest China was influenced by the TCE and TLE of drought, respectively, with 38.2 % and 60.9 % of these effects being statistically significant (p < 0.05). The mean accumulated and lagged timescales of drought on grassland were 7.89 and 9.41 months, respectively. Remarkably, the highest DSG was observed in the semi-arid zone (0.58), followed by the arid (0.54), sub-humid (0.51), and humid (0.44) zones. Furthermore, we identified significant nonlinear variation patterns of DSG along the aridity gradient, characterized by several discernible trend breaks. These findings contribute to our understanding of the impacts of drought on vegetation, particularly in ecologically fragile regions.

Impacts of High-Speed Rail on Regional Economic Growth: An Empirical Analysis of the Moderated Mediation Effects

Transportation infrastructure is crucial for economic growth. Nonetheless, conclusions from empirical investigations concerning the impacts of high-speed rail (HSR) on regional economic growth exhibit inconsistency and are even controversial. In this work, we incorporate the HSR variable into the traditional Dixit–Stiglitz–Krugman (DSK) model, and establish both a structural equation model (SEM) and a threshold model to verify the nonlinear and volatile relationship between HSR development and regional economic growth. The main conclusions are as follows: The opening of HSR (HSR_O), the service intensity of HSR (HSR_S), and the time-cumulative effect of HSR (HSR_T) all have a positive impact on regional economic growth through market size, with labor and capital stock acting as moderating variables. Only under the condition that the regional capital stock exceeds 141.90 million yuan (US$20.56 million), 122.24 million yuan (US$17.71 million), and 128.70 million yuan (US$18.65 million), respectively, will HSR_O, HSR_S, and HSR_T have a favorable effect on regional economic growth. However, the varying influence on regional economic growth is minimally related to labor stock. Finally, directions for further research, and policy implications of the development of HSR for regional planners and local authorities are proposed.

Impact of pregnancy-related anxiety on preschoolers' emotional and behavioral development: Gender specificity, critical time windows and cumulative effect

BackgroundStudies on the gender-specific effect of PrA on children's emotional and behavioral development are limited. Lack of PrA data on the entire pregnancy had caused difficulties in identifying the key time window and cumulative effects. MethodsBased on Ma'anshan Birth Cohort in China, mothers at pregnancy and children followed up to 4 years of age were tested using the PrA questionnaire and the Achenbach Child Behavior Checklist (CBCL) 1.5–5. Finally, 1699 mother-child pairs were included in the study and regression models were developed for analysis. ResultsChildren of mothers with PrA are at significantly elevated risk for abnormal mood/behavior at preschool age. Girls seemed to be more sensitive to maternal PrA than boys, mainly manifested in internalizing problems; The third trimester of pregnancy might be a critical time window when maternal PrA affected children's internalizing problems; Longer the duration women had PrA during pregnancy, more possibilities their children would have to develop internalizing and externalizing problems. LimitationsThe PrA questionnaire may be different from PrA questionnaires in other countries such as due to different cultural contexts. Findings need to be interpreted with more caution. Factors such as maternal postpartum depression and care practices of nursing staff were not considered. No data were collected on disease as well as caregiver emotional status, which also impacts the reporting and identification of emotional/behavioral problems in children. ConclusionsGender-specific and cumulative effect of PrA on preschoolers' emotional/behavioral development is observed. The third trimester of pregnancy might be the critical time window.

Theoretical and Experimental Investigation of Geomagnetic Energy Effect for LEO Debris Deorbiting

Space debris is increasingly problematic and needs active removal, especially in low Earth orbits (LEO). Paying for the vast cost of the disposal of debris from the situation is still inevitable even though pivotal technical hurdles have been overcome with the growing maturity of capturing and deorbiting methods. To this end, a novel geomagnetic energy (GME) propellant approach is firstly proposed to propel a spinning tethered spacecraft for LEO debris deorbiting, without the use of expendable fuel and a large-length tether. In this method, the time-cumulative effect of the interacted torque of the spacecraft’s electromagnet and geomagnetic field is used to accelerate the rotating system for GME storage, and the space momentum exchange from the angular momentum of system to the linear momentum of debris is introduced to deorbit the debris for GME release. Next, an on-orbit directional GME storage mechanism is built, and the corresponding two optimal strategies are put forward. Both theoretical and simulation results demonstrate that GME can be stored in the expected direction on any inclined LEO below 1000 km. Deorbiting kg-level debris can be accomplished within several orbital periods with the existing magnetorquer technology. Finally, proof-of-principle experiments of the GME effect are performed and elementarily validate the LEO GME utilization in space.

Global trends in total fertility rate and its relation to national wealth, life expectancy and female education

ObjectivesAlong with the development of the times and progress of the society, the total fertility rate (TFR) markedly changed in each country. Therefore, it is critical to describe the trend of TFR and explore its influencing factors. However, previous studies did not consider the time lag and cumulative effect in the associations between the influencing factors and TFR. Thus, our study aimed to analyze the associations from a new dimension.MethodsThe study was employed using national-level data from the World Bank and United Nations Development Programme. Distributed lag non-linear models with 5-year lag were used to examine the independent associations between the relevant factors and TFR.ResultsThe cumulative exposure-TFR curves were inverted U-shaped for log gross domestic product (GDP) per capita and life expectancy at birth, while the cumulative exposure-response curves were approximately linear for female expected years of schooling and human development index (HDI). However, it is worth noting that in the developed regions, TFR increased slightly with the high level of GDP per capita, female expected years of schooling and HDI.ConclusionsNowadays, with the growth of GDP per capita, life expectancy at birth, female expected years of schooling and HDI, TFR are on a drastic downward trend in most regions. Besides, with the development of society, when levels of the factors continued to increase, TFR also showed a slight rebound. Therefore, governments, especially those in developing countries, should take measures to stimulate fertility and deal with a series of problems caused by declining TFR.

Fatigue Driving Detection Method Based on Combination of BP Neural Network and Time Cumulative Effect.

Fatigue driving has always received a lot of attention, but few studies have focused on the fact that human fatigue is a cumulative process over time, and there are no models available to reflect this phenomenon. Furthermore, the problem of incorrect detection due to facial expression is still not well addressed. In this article, a model based on BP neural network and time cumulative effect was proposed to solve these problems. Experimental data were used to carry out this work and validate the proposed method. Firstly, the Adaboost algorithm was applied to detect faces, and the Kalman filter algorithm was used to trace the face movement. Then, a cascade regression tree-based method was used to detect the 68 facial landmarks and an improved method combining key points and image processing was adopted to calculate the eye aspect ratio (EAR). After that, a BP neural network model was developed and trained by selecting three characteristics: the longest period of continuous eye closure, number of yawns, and percentage of eye closure time (PERCLOS), and then the detection results without and with facial expressions were discussed and analyzed. Finally, by introducing the Sigmoid function, a fatigue detection model considering the time accumulation effect was established, and the drivers’ fatigue state was identified segment by segment through the recorded video. Compared with the traditional BP neural network model, the detection accuracies of the proposed model without and with facial expressions increased by 3.3% and 8.4%, respectively. The number of incorrect detections in the awake state also decreased obviously. The experimental results show that the proposed model can effectively filter out incorrect detections caused by facial expressions and truly reflect that driver fatigue is a time accumulating process.

Does agricultural mechanization improve agricultural environment efficiency? Evidence from China's planting industry.

Environmental problems caused by energy consumption in the rapid popularization of China's agricultural mechanization (AM) have caused increasing concern. Using the panel data of China's 30 provinces from 2001 to 2019, this article adopts a stochastic frontier analysis method with output-oriented distance function to measure agricultural environment efficiency (AEE) based on net carbon sinks and empirically analyzes the impact of AM on AEE. The main findings are as follows: Firstly, the AEE of the nation and all provinces shows an upward trend over time and has significant spatial positive autocorrelation characteristics. Secondly, there is an inverted U-shaped relationship between AM and AEE. Meanwhile, AM has spatial spillover effect and time cumulative effect on AEE. These basic conclusions are still robust after using instrumental variables, spatial autoregressive model, sub-sample regression, changing spatial weight matrix, and independent variable. Thirdly, the effect of AM on AEE depends on the input effect and output effect caused by AM. The mechanism is mainly reflected in agricultural technology progress, expansion of the scale of farming operation, optimization of resource allocation, and spatial spillover. Given these findings, the paper adds considerable value to the empirical literature and provides various policy and practical implications.

Regional-scale vegetation-climate interactions on the Qinghai-Tibet Plateau

Response and feedback of vegetation growth to climate change are a series biogeophysical processes from local to regional scales. Revealing the vegetation-climate interaction is fundamental to understand the evolution of earth surface system in the context of global climate change. Due to the low temperature and vulnerable biotic and abiotic settings, the alpine ecosystems are sensitive to climate change, peculiarly in the Qinghai-Tibet Plateau (QTP). By combining the climate factors (precipitation and temperature) and vegetation state indicated by the Enhanced Vegetation Index (EVI) data we try to reveal the pertinent temporal reaction mode of vegetation to climate change on the QTP. The vegetation-climate interactions were investigated by using the Granger causality test technique. The prime findings of this study are: (1) vegetation showed a strong sensitivity to warming-wetting climate in most arid and semi-arid areas of the QTP; (2) the reaction patterns of EVI to precipitation show a temporal lag of 0–1 months, which was strongest to the cumulative precipitation within 1–2 months; (3) The time lag effect and cumulative effect of temperature on vegetation both occurred within 1 to 2 months; (4) The unidirectional Granger causes of precipitation and temperature to vegetation accounted for 17.65% and 8.66% of the entire QTP, respectively. This study emphasizes a sensitive response of the vegetation to climate change (precipitation and temperature) in the QTP. Vegetation feedback makes the fluctuations and effects of climate more complicated. The results indicated that more insights into the future forecasting of climate change and vegetation dynamics can be acquired by a specific and comprehensive analysis of vegetation-climate coupled feedback.

Driver drowsiness detection using mixed-effect ordered logit model considering time cumulative effect

Drowsy driving is one of the main causes of traffic crashes, a serious threat to road traffic safety. The effective early detection of a drowsiness state can help provide a timely warning for drivers, but previous studies have seldom considered the cumulative effect of drowsiness over time. The purpose of this study is therefore to establish a model to detect a driver's drowsiness level by considering individual differences combined with the time cumulative effect (TCE) of drowsiness. Driving behavior and eye movement data from 27 drivers were collected by a driving simulator with an eye-tracking system, and the Karolinska Sleepiness Scale (KSS) was used to record drivers’ perceptions of their states of drowsiness. Since the degree of driver drowsiness was shown to increase with time, a mixed-effect ordered logit (MOL) model was established, and a non-decreasing function of time was applied to consider time accumulation. Results showed that with increasing drowsiness, the standard deviation of lateral position and percentage of driver eyelid closure (PERCLOS) increased significantly. Consideration of these variables can thus improve the accuracy of drowsy driving detection. The developed MOL-TCE model was compared with a non-TCE MOL and a TCE mixed generalized ordered response (MGOR) model. The drowsiness detection accuracy of the MOL-TCE model was 62.84%, higher than the 61.04% accuracy of the MGOR-TCE and appreciably higher than the 52.47% of the non-TCE MOL model.

Effect of pulsed millisecond current magnetic field on the proliferation of C6 rat glioma cells

ABSTRACTIn recent years, using electromagnetic fields as a targeted therapy for tumors has become a new idea. This paper aims to study the response of rat glioma cells (C6) when the external electromagnetic field parameters change and to obtain a complete working range of magnetic field parameters. Four-day, 4-h daily millisecond magnetic field exposure experiments were performed with C6 cells. The peak values of magnetic field intensity were 260 mT, 90 mT, 19 mT and 6 mT. Each day after exposure, cell morphology and cell viability assay (MTT method) were measured. The response of C6 cells shows a significant window effect and time cumulative effect on the cell, and it is non-destructive. The working inhibited magnetic field range of magnetic field increase rate dB/dt (T/s) is [34, 119.5] and [166.75, 527.25], the magnetic field amplitude B (mT) is [6, 260], the magnetic field integral Bt (mT·s) is [0.1649, 0.8085] and the energy integral B2t (mT2·s) is [2.317, 53.328]. Our findings provide the theoretical and experimental basis for clinical applications of electromagnetic fields.

Chronic exposure of bumblebees to neonicotinoid imidacloprid suppresses the entire mevalonate pathway and fatty acid synthesis

Determining the side effects of pesticides on pollinators is an important topic due to the increasing loss of pollinators. We aimed to determine the effects of chronic sublethal exposure of the neonicotinoid pesticide imidacloprid on the bumblebee Bombus terrestris under laboratory conditions. The analytical standard of imidacloprid in sugar solution was used for the treatment. Verification of pesticides using UHPLC-QqQ-MS/MS in the experimental bumblebees showed the presence of only two compounds, imidacloprid and imidacloprid-olefin, which were found in quantities of 0.57 ± 0.22 and 1.95 ± 0.43 ng/g, respectively. Thus, the level of the dangerous metabolite imidacloprid-olefin was 3.4-fold higher than that of imidacloprid. Label-free nanoLC-MS/MS quantitative proteomics of bumblebee heads enabled quantitative comparison of 2883 proteins, and 206 proteins were significantly influenced by the imidacloprid treatment. The next analysis revealed that the highly downregulated markers are members of the terpenoid backbone biosynthesis pathway (KEGG: bter00900) and that imidacloprid treatment suppressed the entire mevalonate pathway, fatty acid synthesis and associated markers. The proteomics results indicate that the consequences of imidacloprid treatment are complex, and the marker changes are associated with metabolic and neurological diseases and olfaction disruption. This study provides important markers and can help to explain the widely held assumptions from biological observations. SignificanceThe major finding is that all markers of the mevalonate pathway were substantially downregulated due to the chronic imidacloprid exposure. The disbalance of mevalonate pathway has many important consequences. We suggest the mechanism associated with the novel toxicogenic effect of imidacloprid. The results are helpful to explain that imidacloprid impairs the cognitive functions and possesses the delayed and time cumulative effect.

A New Prediction Method for Chaotic Time Series

In order to show the time cumulative effect in the process for the time series prediction, the process neural network is taken. The training algorithm of modified particle swarm is used to the model for the learning speed. The training data is sunspot data from 1700 to 2007. Simulation result shows that the prediction model and algorithm has faster training speed and prediction accuracy than the artificial neural network.

Discussion of Basic Elasticity Models Applied to Induced Traffic in China

This paper aims to further discuss basic elasticity models in China, using the panel data set of annual observations of China and six areas (North China, East China, Southwest China, South Central China, Northeast China and Northwest China) for the years 1990-2008. Based on the related foreign concept of induced traffic, autocorrelation model, autoregressive distributed lag model and dummy model are researched. According to the detailed analysis of empirical results, these models are available to China. Lane-kilometers are found to have a statistical relationship with VKT (vehicle-kilometers of travel) of 0.060-0.882 in short-term and 0.086-1.194 in long-term in China and six areas. These mean the necessary of considering induced traffic in China. About the basic elasticity models discussed in this paper, autoregressive distributed lag model is better suitable in China. It not only includes the time delay and cumulative effect but also brings more economic explanations than autocorrelation model.

Mass transfer evaluation of ultrasonic osmotic dehydration of cherry tomatoes in sucrose and salt solutions

AbstractIn order to elaborate dehydration and osmotic equilibrium characteristics of cherry tomatoes and to analyse the applicability of Peleg model in prediction of equilibrium moisture content and the methodology of Crank’s solution to Fick’s diffusion law in calculation of effective diffusivity, cherry tomatoes were osmotically treated in ternary solution (water, sucrose and NaCl) with or without ultrasound at 30 °C. Results indicated that, a time cumulative effect of ultrasound occurred about 30 min for water loss (WL), while for sugar gain it happened after 45 min, which made the dehydration efficiency index best at the ultrasonic power of 150 W for 40 min. As a function of salt content, the equilibrium WL followed well the first order exponential decay model, and the equilibrium salt content followed well the second order polynomial. A great relative error (29.13%) between the practical determination and the predicted value indicated that Peleg model was not suitable for prediction of equilibrium moisture content. A great truncation error (865%) occurred when moisture effective diffusivity (6.66 × 10−9 m2 s−1) was calculated with Crank’s solution to Fick’s diffusion law by letting n = 1 as compared to that (0.77 × 10−9 m2 s−1) by letting n = 100.

Effects of intermediate filament cytoskeleton on the matrix anabolism of rabbit articular chondrocytes in vitro

Objective To investigate the effects of disruption of intermediate filament cytoskeleton on the matrix anabolism of rabbit articular chondrocytes in vitro. Methods One-month-old New Zealand rabbits were killed and their knee joints were taken out under the aseptic condition. The chondrocytes were isolated by enzymolysis method and inoculated into a 6-well plate. The medium was abandoned after cell attachment and the cells were divided into two groups randomly. The cells in control group were cultured with DMEM/F12,while those in intermediate filament disruption group (IF disruption group) cultured in the media containing 5 mmol/L acrylamide. The glycosaminoglycan (GAG) content was determined by Alician Blue method,and the hydroxyproline content was measured to estimate collagen synthesis in the supernatant when medium was changed after 4 and 7 days. Results There was no significant difference in GAG content in the supernatant between the two groups with medium change after 4 and 7 days (P>0. 05). The GAG content in the two groups were all significantly increased with the culture time (P 0. 05), but significantly decreased at the 7th day as compared with the control group (P 0.05 ). There was no significant change in the hydroxyproline content in the supernatant of IF disruption group between the 7 th day and 4th day. Conclusion The GAG synthesis of chondrocytes has time cumulative effect,however,disruption of intermediate filament has no effect on the GAG synthesis. The disruption of the intermediate filament can decrease the collagen synthesis of chondrocytes in vitro, suggesting that the intermediate filament is necessary for the collagen synthesis of articular chondrocytes. Key words: Chondrocyte; Cytoskeleton; Intermediate filament; Collagen