Potential Driving Systems Associated with Extreme Rainfall across East Africa during October to December (OND) Season 2019

The East African (EA) region highly experiences intra-seasonal and inter-annual variation in rainfall amounts. This study investigates the driving factors for anomalous rainfall events observed during the season of October-November-December (OND) 2019 over the region. The study utilized daily rainfall data from Climate Hazards Group InfraRed Precipitation with Station Data Version 2 (CHIRPSv2) and the driving systems data. Statistical spatiotemporal analysis, correlation, and composite techniques were performed to investigate the teleconnection between OND 2019 seasonal rainfall and global synoptic climate systems. The findings showed that the OND 2019 experienced seasonal rainfall that was twice or greater than its seasonal climatology and varied with location. Further, the OND 2019 rainfall showed a positive correlation with the Indian Ocean Dipole (IOD) (0.81), Nino 3 (0.51), Nino 3.4 (0.47), Nino 4 (0.40), Pacific Decadal Oscillation (PDO) (0.22), and North Tropical Atlantic (NTA) (0.02), while El Nino-Southern Oscillation (ENSO) showed a negative correlation (−0.30). The region was dominated by southeasterly warming and humid winds that originated from the Indian Ocean, while the geopotential height, vertical velocity, and vorticity anomalies were closely related to the anomalous rainfall characteristics. The study deduced that the IOD was the major synoptic system that influenced maximum rainfall during the peak season of OND 2019. This study therefore provided insights on the diagnosis study of OND 2019 anomalous rainfall and its attribution over the EA. The findings of the study will contribute to improvements in forecasting seasonal rainfall by regional climate centers and national meteorological centers within the region.

A Sine Driving System for the Dynamic Experiment of the Aerofoil Model

The design principle and the structural characters of a new sine driving system apparatus, which have been used by NPU NF-3 wind tunnel in the dynamic stall experiments on the oscillating aerofoil model from 1994, is introduced. Some measures to improve the stability and flexibility are studied. The obvious advantages of the system are its simple structure, convenient operation and more accurate sine relationship between the attack angle and the rotating angle of the aerofoil The driving system has been proved advisable comparing with the experimental results both abroad and in many dynamic tests in NF-3 wind tunnel. It can provide guidelines for the study of the aerodynamic properties on the oscillating aerofoil.

Analysis and Control over Noises in Main Driving System of XK-736-type NC Miller

Some concrete methods are suggested in the article to control noises in main driving system of XK-736-type NC miller by analyzing working conditions of gears in the main driving system and bearings in the spindle gearshift system. Without changing the original design, noises are reduced ideally by modifying gear top, and by controlling the profile error ; the central distance of meshing gear, the quality of the inner and outer rings of bearings ; and the fit accuracy among bearing, hole and axis. The results may provide a reference for diagnosing and maintaining in future use.

Implementation and Evaluation of Local Dynamic Map in Safety Driving Systems

Cooperative safety driving systems using vehicle-to-vehicle and vehicle-to infrastructure communication are developed. Sensor data of vehicles and infrastructures are communicated in the cooperative safety driving system. LDM (Local Dynamic Map) is standardized by ETSI (European Telecommunications Standards Institute) to manage the vehicle sensor data and the map data. Implementations of LDM are reported on documents of ETSI, but there are no numerical results. The implementations of LDM are deployed the database management system. We think that the response time of the database becomes higher as the number of vehicles grows. In this paper, we have implemented and evaluated the LDM with the collision detection application.

On the Development of an Effective Pressure Driving System for Ultra-Low Permeability Reservoirs

Given its relevance to the exploitation of ultra-low permeability reservoirs,which account for a substantial proportion of the world’s exploited and still unexploited reserves,in the present study the development of an adequate water injection system is considered.Due to the poor properties and weak seepage capacity of these reservoirs,the water injection pressure typically increases continuously during water flooding.In this research,the impact on such a process of factors as permeability,row spacing,and pressure gradient is evaluated experimentally using a high-pressure large-scale outcrop model.On this basis,a comprehensive evaluation coefficient is introduced able to account for the effective driving pressure.

Optimum Driving System Design for Dual-Motor Pure Electric Vehicles

A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.

On Designing of the Main Elements of a Hybrid-Electric Vehicle Driving System

The paper deals with the designing of an electric drive system used for hybrid electric vehicles. The driving system is realized with an induction motor and a voltage source inverter. Specifically, the application is for a series hybrid vehicle powered by electric storage batteries charged by solar batteries. In the first part of the paper the designing of the electric storage batteries and of the photoelectric system is presented. In the second part of the paper some aspects regarding the designing of the induction motor are presented. Then some aspects concerning the voltage source inverter designing are exposed.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Thermodynamic re-assessment of the Mg-Gd-Y ternary system coupling with the driving forces for phase precipitations during aging process

Based on the available experimental phase equilibrium relations and aging precipitation sequences,the Mg–Gd–Y ternary system has been thermodynamically re-assessed by means of CALPHAD technique.To simulate the experimentally reported aging precipitation sequence,α(Mg)_(SS)(supersaturated)→GP zones(D019-type,metastable)→β’-Mg_(7)Gd(c-bco,metastable)→β_(1)-Mg_(3)Gd(fcc,metastable)→β-Mg_(5)Gd(fcc,stable)near the Mg–Gd side,andα(Mg)SS(supersaturated)→β’-Mg_(7)Y(c-bco,metastable)→β-Mg_(24)Y_(5)(bcc,stable)near the Mg–Y side,the effective nucleation driving forces obtained by deducting the nucleation resistances from the thermodynamic driving forces are calculated and analyzed.Two metastable components,GP zones(D019-type)andβ’(c-bco)ordered fromα(Mg)_(SS),do not exist in the stable equilibrium phase diagram but appear in the annealing process of typical alloys.The Redlich–Kister equations are adopted to describe three solution phases,Liquid,HCP_A3 and BCC_A2.The intermediate compounds Mg_(2)Y,Mg_(24)Y_(5),Mg_(2)Gd,Mg_(3)Gd and Mg_(5)Gd are expressed by the formulas of(Mg,Y)_(2/3)(Gd,Mg,Y)_(1/3),Mg_(24/29)(Gd,Mg,Y)_(4/29)Y1/29,(Gd,Mg)_(2/3)(Gd,Mg,Y)_(1/3),(Gd,Mg)_(3/4)(Gd,Mg,Y)_(1/4)and Mg_(5/6)(Gd,Mg,Y)_(1/6),respectively.In particular,the two-sublattice models(Gd,Mg,Y)_(1/2)(Gd,Mg,Y)_(1/2),(Gd,Mg,Y)_(3/4)(Gd,Mg,Y)_(1/4)and(Gd,Mg,Y)_(7/8)(Gd,Mg,Y)_(1/8)have been respectively used to describe the stable Mg(Gd,Y)(BCC_B2)alloy compound as well as the metastable GP zones(D019-type)andβ’(c-bco)phase,in order to cope with the order-disorder transitions.A set of self-consistent thermodynamic parameters has been obtained to ensure the thermodynamic calculations well consistent with the reported experimental data,containing not only the stable equilibrium phase diagram but also the aging precipitation sequence.

Driving pressure in mechanical ventilation:A review

Driving pressure(ΔP)is a core therapeutic component of mechanical ventilation(MV).Varying levels ofΔP have been employed during MV depending on the type of underlying pathology and severity of injury.However,ΔP levels have also been shown to closely impact hard endpoints such as mortality.Considering this,conducting an in-depth review ofΔP as a unique,outcome-impacting therapeutic modality is extremely important.There is a need to understand the subtleties involved in making sureΔP levels are optimized to enhance outcomes and minimize harm.We performed this narrative review to further explore the various uses ofΔP,the different parameters that can affect its use,and how outcomes vary in different patient populations at different pressure levels.To better utilizeΔP in MV-requiring patients,additional large-scale clinical studies are needed.

Land use change and its driving factors in the ecological function area:A case study in the Hedong Region of the Gansu Province,China

Land use and cover change(LUCC)is important for the provision of ecosystem services.An increasing number of recent studies link LUCC processes to ecosystem services and human well-being at different scales recently.However,the dynamic of land use and its drivers receive insufficient attention within ecological function areas,particularly in quantifying the dynamic roles of climate change and human activities on land use based on a long time series.This study utilizes geospatial analysis and geographical detectors to examine the temporal dynamics of land use patterns and their underlying drivers in the Hedong Region of the Gansu Province from 1990 to 2020.Results indicated that grassland,cropland,and forestland collectively accounted for approximately 99% of the total land area.Cropland initially increased and then decreased after 2000,while grassland decreased with fluctuations.In contrast,forestland and construction land were continuously expanded,with net growth areas of 6235.2 and 455.9 km^(2),respectively.From 1990 to 2020,cropland was converted to grassland,and both of them were converted to forestland as a whole.The expansion of construction land primarily originated from cropland.From 2000 to 2005,land use experienced intensified temporal dynamics and a shift of relatively active zones from the central to the southeastern region.Grain yield,economic factors,and precipitation were the major factors accounting for most land use changes.Climatic impacts on land use changes were stronger before 1995,succeeded by the impact of animal husbandry during 1995-2000,followed by the impacts of grain production and gross domestic product(GDP)after 2000.Moreover,agricultural and pastoral activities,coupled with climate change,exhibited stronger enhancement effects after 2000 through their interaction with population and economic factors.These patterns closely correlated with ecological restoration projects in China since 1999.This study implies the importance of synergy between human activity and climate change for optimizing land use via ecological patterns in the ecological function area.

Landscape ecological risk assessment and its driving factors in the Weihe River basin,China

Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.

Self-assembly of perovskite nanocrystals:From driving forces to applications

Self-assembly of metal halide perovskite nanocrystals(NCs)into superlattices can exhibit unique collective properties,which have significant application values in the display,detector,and solar cell field.This review discusses the driving forces behind the self-assembly process of perovskite NCs,and the commonly used self-assembly methods and different self-assembly structures are detailed.Subsequently,we summarize the collective optoelectronic properties and application areas of perovskite superlattice structures.Finally,we conclude with an outlook on the potential issues and future challenges in developing perovskite NCs.

Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

Research on the quasi-isentropic driving model of aluminized explosives in the detonation wave propagation direction

Taking CL-20(Hexanitrohexaazaisowurtzitane)-based aluminized explosives with high gurney energy as the research object, this research experimentally investigates the work capability of different aluminized explosive formulations when driving metal flyer plates in the denotation wave propagation direction.The research results showed that the formulations with 43 μm aluminum(Al) powder particles(The particle sizes of Al powder were in the range of 2~43 μm) exhibited the optimal performance in driving flyer plates along the denotation wave propagation direction. Compared to the formulations with Al powder 13 μm, the formulations with Al powder 2 μm delivered better performance in accelerating metal flyer plates in the early stage, which, however, turned to be poor in the later stage. The CL-20-based explosives containing 25% Al far under-performed those containing 15% Al. Based on the proposed quasi-isentropic hypothesis, relevant isentropy theories, and the functional relationship between detonation parameters and entropy as well as Al reaction degree, the characteristic lines of aluminized explosives in accelerating flyer plates were theoretically studied, a quasi-isentropic theoretical model for the aluminized explosive driving the flyer plate was built and the calculation methods for the variations of flyer plate velocity, Al reaction degree, and detonation product parameters with time and axial positions were developed. The theoretical model built is verified by the experimental results of the CL-20-based aluminized explosive driving flyer plate. It was found that the model built could accurately calculate the variations of flyer plate velocity and Al reaction degree over time. In addition, how physical parameters including detonation product pressure and temperature varied with time and axial positions was identified. The action time of the positive pressure after the detonation of aluminized explosives was found prolonged and the downtrend of the temperature was slowed down and even reversed to a slight rise due to the aftereffect reaction between the Al powder and the detonation products.

Spatio-temporal evolution and topographic gradient effect of land use and ecosystem service value in the Lhasa River Basin

The Lhasa River Basin forms an essential human settlement area in the southern part of the Qinghai-Tibet Plateau.This study employed ecosystem service value(ESV)evaluation model,terrain gradient grading,and Geodetector to analyze land use and ESV in the Lhasa River Basin from 1985 to 2020.The findings reveal that:(1)From 1985 to 2020,grassland was the dominant land use.There was a trend of grassland reduction and the expansion of other land types.(2)ESV has increased over the research period(with a total increase of 0.84%),with higher values in the southeast and lower values in the northwest.Grassland contributed the most to ESV,and climate regulation and hydrological regulation were the ecosystem services that contribute the most to ESV.(3)Natural factors like NDVI and altitude,as well as economic factors like population density and distance from roads,influenced the spatial differentiation of ESV,the explanatory power of NDVI reached up to 0.47.The interaction between factors had a greater impact than individual factors.These research results can provide theoretical support for national spatial planning and ecological environment protection in the Lhasa River Basin and other similar areas.

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement Learning Theory

The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.

GDMNet: A Unified Multi-Task Network for Panoptic Driving Perception

To enhance the efficiency and accuracy of environmental perception for autonomous vehicles,we propose GDMNet,a unified multi-task perception network for autonomous driving,capable of performing drivable area segmentation,lane detection,and traffic object detection.Firstly,in the encoding stage,features are extracted,and Generalized Efficient Layer Aggregation Network(GELAN)is utilized to enhance feature extraction and gradient flow.Secondly,in the decoding stage,specialized detection heads are designed;the drivable area segmentation head employs DySample to expand feature maps,the lane detection head merges early-stage features and processes the output through the Focal Modulation Network(FMN).Lastly,the Minimum Point Distance IoU(MPDIoU)loss function is employed to compute the matching degree between traffic object detection boxes and predicted boxes,facilitating model training adjustments.Experimental results on the BDD100K dataset demonstrate that the proposed network achieves a drivable area segmentation mean intersection over union(mIoU)of 92.2%,lane detection accuracy and intersection over union(IoU)of 75.3%and 26.4%,respectively,and traffic object detection recall and mAP of 89.7%and 78.2%,respectively.The detection performance surpasses that of other single-task or multi-task algorithm models.

Spatiotemporal characteristics and driving mechanisms of land use/land cover(LULC)changes in the Jinghe River Basin,China

Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.

Perception Enhanced Deep Deterministic Policy Gradient for Autonomous Driving in Complex Scenarios

Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous driving.To address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a Perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the Roundabouts.Specifically,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions.Furthermore,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput efficiency.Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.