Freeze-thaw cycles and associated geomorphology in a post-glacial environment:current glacial,paraglacial,periglacial and proglacial scenarios at Pico de Orizaba volcano,Mexico

The glacial history of Pico de Orizaba indicates that during the Last Glacial Maximum,its icecap covered up to~3000 m asl;due to the air temperature increasing,its main glacier has retreated to 5050 m asl.The retraction of the glacier has left behind an intense climatic instability that causes a high frequency of freeze-thaw cycles of great intensity;the resulting geomorphological processes are represented by the fragmentation of the bedrock that occupies the upper parts of the mountain.There is a notable lack of studies regarding the fragmentation and erosion occurring in tropical high mountains,and the associated geomorphological risks;for this reason,as a first stage of future continuous research,this study analyzes the freezing and thawing cycles that occur above 4000 m asl,through continuous monitoring of surface ground temperature.The results allow us to identify and characterize four zones:glacial,paraglacial,periglacial and proglacial.It was found that the paraglacial zone presents an intense drop of temperature,of up to~9℃ in only sixty minutes.The rock fatigue and intense freeze-thaw cycles that occur in this area are responsible for the high rate of rock disintegration and represent the main factor of the constant slope dynamics that occur at the site.This activity decreases,both in frequency and intensity,according to the distance to the glacier,which is where the temperature presents a certain degree of stability,until reaching the proglacial zone,where cycles are almost non-existent,and therefore there is no gelifraction activity.The geomorphological processes have resulted in significant alterations to the mountain slopes,which can have severe consequences in terms of risk and water.

Artificial Intelligence Based Multi-Scenario mmWave Channel Modeling for Intelligent High-Speed Train Communications

A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a trend.This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave(mmWave)HST communications.Firstly,the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios.By setting the positions of transmitter(Tx),receiver(Rx),and other parameters,the multi-scenarios wireless channel big data is acquired.Then,based on the obtained channel database,radial basis function neural network(RBF-NN)and back propagation neural network(BP-NN)are trained for channel characteristic prediction and scenario classification.Finally,the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error(RMSE).The results show that RBF-NN can generally achieve better performance than BP-NN,and is more applicable to prediction of HST scenarios.

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.

Historical Changes and Multi-scenario Prediction of Land Use and Terrestrial Ecosystem Carbon Storage in China

Terrestrial carbon storage(CS)plays a crucial role in achieving carbon balance and mitigating global climate change.This study employs the Shared Socioeconomic Pathways and Representative Concentration Pathways(SSPs-RCPs)published by the Intergovernmental Panel on Climate Change(IPCC)and incorporates the Policy Control Scenario(PCS)regulated by China’s land management policies.The Future Land Use Simulation(FLUS)model is employed to generate a 1 km resolution land use/cover change(LUCC)dataset for China in 2030 and 2060.Based on the carbon density dataset of China’s terrestrial ecosystems,the study analyses CS changes and their relationship with land use changes spanning from 1990 to 2060.The findings indicate that the quantitative changes in land use in China from 1990 to 2020 are characterised by a reduction in the area proportion of cropland and grassland,along with an increase in the impervious surface and forest area.This changing trend is projected to continue under the PCS from 2020 to 2060.Under the SSPs-RCPs scenario,the proportion of cropland and impervious surface predominantly increases,while the proportions of forest and grassland continuously decrease.Carbon loss in China’s carbon storage from 1990 to 2020 amounted to 0.53×10^(12)kg,primarily due to the reduced area of cropland and grassland.In the SSPs-RCPs scenario,more significant carbon loss occurs,reaching a peak of8.07×10^(12)kg in the SSP4-RCP3.4 scenario.Carbon loss is mainly concentrated in the southeastern coastal area and the Beijing-TianjinHebei(BTH)region of China,with urbanisation and deforestation identified as the primary drivers.In the future,it is advisable to enhance the protection of forests and grassland while stabilising cropland areas and improving the intensity of urban land.These research findings offer valuable data support for China’s land management policy,land space optimisation,and the achievement of dual-carbon targets.

Improved Unit Commitment with Accurate Dynamic Scenarios Clustering Based on Multi-Parametric Programming and Benders Decomposition

Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.

Multi-scenario Simulation of the Impact of Land Use Change on the Ecosystem Service Value in the Suzhou-Wuxi-Changzhou Metropolitan Area,China

As the most economically developed metropolitan area in China’s Yangtze River Delta,the rapid changing land use patterns of Suzhou-Wuxi-Changzhou(Su-Xi-Chang) metropolitan area have profound impacts on the ecosystem service value(ESV).Based on the patterns of land use change and the ESV change in Su-Xi-Chang metropolitan area from 2000 to 2020,we set up four scenarios:natural development scenario,urban development scenario,arable land protection scenario and ecological protection scenario,and simulated the impact of land use changes on the ESV in these scenarios.The results showed that:1) the area of built-up land in the Su-XiChang metropolitan area increased significantly from 2000 to 2020,and the area of other types of land decreased.Arable land underwent the highest transfer-out area,and was primarily converted into built-up land.The total ESV of Su-Xi-Chang metropolitan area increased initially then declined from 2000–2020,and the value of almost all individual ecosystem services decreased.2) Population density,GDP per area,night lighting intensity,and road network density can negatively impact the ESV.3) The total ESV loss under the natural development and urban development scenarios was high,and the expansion of the built-up land and the drastic shrinkage of the arable land contributed to the ESV decline under both scenarios.The total ESV under arable land protection and ecological protection scenarios increases,and therefore these scenarios are suitable for future land use optimization in Su-Xi-Chang.This study could provide a certain reference for land use planning and allocation,and offer guidance for the rational allocation of land resources.

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

Analysis of factors influencing carbon emissions in the Yangtze River Delta region and projections of carbon peak scenarios

Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.

Application of Patient Simulators Combined with Internet plus Scenario Simulation Teaching Models on Intravenous Infusion Nursing Education in China

Objective: To explore the effectiveness of applying patient simulators combined with Internet Plus scenario simulation teaching models on intravenous (IV) infusion nursing education, and to provide scientific evidence for the implementation of advanced teaching models in future nursing education. Methods: Enrolled 60 nurses who took the IV infusion therapy training program in our hospital from January 2022 to December 2023 for research. 30 nurses who were trained in traditional teaching models from January to December 2022 were selected as the control group, and 30 nurses who were trained with simulation-based teaching models with methods including simulated patients, internet, online meetings which can be replayed and scenario simulation, etc. from January to December 2023 were selected as the experimental group. Evaluated the learning outcomes based on the Competency Inventory for Nursing Students (CINS), Problem-Solving Inventory (PSI), comprehensive learning ability, scientific research ability, and proficiency in the theoretical knowledge and practical skills of IV infusion therapy. Nursing quality, the incidence of IV infusion therapy complications and nurse satisfaction with different teaching models were also measured. Results: The scientific research ability, PSI scores, CINS scores, and comprehensive learning ability of the experimental group were better than those of the control group (P 0.05), and their assessment results of practical skills, nursing quality of IV infusion therapy during training, and satisfaction with teaching models were all better than those of the control group with statistical significance (P < 0.05). The incidence of IV infusion therapy complications in the experimental group was lower than that in the control group, indicating statistical significance (P < 0.05). Conclusions: Teaching models based on patient simulators combined with Internet Plus scenario simulation enable nursing students to learn more directly and practice at any time and in any place, and can improve their proficiency in IV infusion theoretical knowledge and skills (e.g. PICC catheterization), core competencies, problem-solving ability, comprehensive learning ability, scientific research ability and the ability to deal with complicated cases. Also, it helps provide high-quality nursing education, improve the nursing quality of IV therapy, reduce the incidence of related complications, and ensure the safety of patients with IV therapy.

Spatiotemporal Characteristics and Future Scenario Simulation of the Trade-offs and Synergies of Mountain Ecosystem Services: A Case Study of the Dabie Mountains Area, China

Mountain ecosystems play an essential role in supporting regional sustainable development and improving local ecological environments. However, economic development in mountainous areas has long been lagging, and multiple conflicts related to resource assurance, ecological protection, and economic development have emerged. An accurate grasp of the current status and evolutionary trends of mountain ecosystems is essential to enhance the overall benefits of ecosystem services and maintain regional ecological security. Based on the In VEST(Integrated Valuation of Ecosystem Services and Trade-offs) model, this study analyzed the spatiotemporal evolution patterns and the trade-offs and synergies among ecosystem services(ES) in the Dabie Mountains Area(DMA) of eastern China. The Markov-PLUS(Patch-generating Land Use Simulation) model was used to conduct a multi-scenario simulation of the area's future development. Water yield(WY) and soil conservation(SC) had overall increasing trends during 2000-2020, carbon storage(CS)decreased overall but slowed with time, and habitat quality(HQ) increased and then decreased. The ecological protection scenario is the best scenario for improving ES in the DMA by 2030;compared to 2020, the total WY would decrease by 3.77 × 10^(8) m^(3), SC would increase by 0.65 × 10^(6) t, CS would increase by 1.33 × 10^(6) t, and HQ would increase by 0.06%. The comprehensive development scenario is the second-most effective scenario for ecological improvement, while the natural development scenario did not have a significant effect. However, as the comprehensive development scenario considers both environmental protection and economic development, which are both vital for the sustainable development of the mountainous areas, this scenario is considered the most suitable path for future development. There are trade-offs between WY, CS, and HQ, while there are synergies between SC, CS, and HQ. Spatially, the DMA's central core district is the main strong synergistic area, the marginal zone is the weak synergistic area, and trade-offs are mainly distributed in the transition zone.

Radio Communication Scenarios in 5G-Railways

With the rapid development of railways,especially high-speed railways,there is an increasingly urgent demand for new wireless communication system for railways.Taking the mature 5G technology as an opportunity,5G-railways(5G-R)have been widely regarded as a solution to meet the diversified demands of railway wireless communications.For the design,deployment and improvement of 5GR networks,radio communication scenario classification plays an important role,affecting channel modeling and system performance evaluation.In this paper,a standardized radio communication scenario classification,including 18 scenarios,is proposed for 5GR.This paper analyzes the differences of 5G-R scenarios compared with the traditional cellular networks and GSM-railways,according to 5G-R requirements and the unique physical environment and propagation characteristics.The proposed standardized scenario classification helps deepen the research of 5G-R and promote the development and application of the existing advanced technologies in railways.

Prediction of forest fire occurrence in China under climate change scenarios

Climate change has an impact on forest fire patterns.In the context of global warming,it is important to study the possible effects of climate change on forest fires,carbon emission reductions,carbon sink effects,forest fire management,and sustainable development of forest ecosystems.This study is based on MODIS active fire data from 2001-2020 and the influence of climate,topography,vegetation,and social factors were integrated.Temperature and precipitation information from different scenarios of the BCC-CSM2-MR climate model were used as future climate data.Under climate change scenarios of a sustainable low development path and a high conventional development path,the extreme gradient boosting model predicted the spatial distribution of forest fire occurrence in China in the 2030s(2021-2040),2050s(2041-2060),2070s(2061-2080),and2090s(2081-2100).Probability maps were generated and tested using ROC curves.The results show that:(1)the area under the ROC curve of training data(70%)and validation data(30%)were 0.8465 and 0.8171,respectively,indicating that the model can reasonably predict the occurrence of forest fire in the study area;(2)temperature,elevation,and precipitation were strongly correlated with fire occurrence,while land type,slope,distance from settlements and roads,and slope direction were less strongly correlated;and,(3)based on future climate change scenarios,the probability of forest fire occurrence will tend to shift from the south to the center of the country.Compared with the current climate(2001-2020),the occurrence of forest fires in 2021-2040,2041-2060,2061-2080,and 2081-2100 will increase significantly in Henan Province(Luoyang,Nanyang,S anmenxia),Shaanxi Province(Shangluo,Ankang),Sichuan Province(Mianyang,Guangyuan,Ganzi),Tibet Autonomous Region(Shannan,Linzhi,Changdu),Liaoning Province(Liaoyang,Fushun,Dandong).

Potential global distribution of the guava root-knot nematode Meloidogyne enterolobii under different climate change scenarios using MaxEnt ecological niche modeling

In recent years,Meloidogyne enterolobii has emerged as a major parasitic nematode infesting many plants in tropical or subtropical areas.However,the regions of potential distribution and the main contributing environmental variables for this nematode are unclear.Under the current climate scenario,we predicted the potential geographic distributions of M.enterolobii worldwide and in China using a Maximum Entropy(MaxEnt)model with the occurrence data of this species.Furthermore,the potential distributions of M.enterolobii were projected under three future climate scenarios(BCC-CSM2-MR,CanESM5 and CNRM-CM6-1)for the periods 2050s and 2090s.Changes in the potential distribution were also predicted under different climate conditions.The results showed that highly suitable regions for M.enterolobii were concentrated in Africa,South America,Asia,and North America between latitudes 30°S to 30°N.Bio16(precipitation of the wettest quarter),bio10(mean temperature of the warmest quarter),and bio11(mean temperature of the coldest quarter)were the variables contributing most in predicting potential distributions of M.enterolobii.In addition,the potential suitable areas for M.enterolobii will shift toward higher latitudes under future climate scenarios.This study provides a theoretical basis for controlling and managing this nematode.

Water yield and biomass production for on a eucalypt-dominated Mediterranean catchment under different climate scenarios

Worldwide,forests are vital in the regulation of the water cycle regulation and in water balance allocation.Knowledge of ecohydrological responses of production forests is essential to support management strategies,especially where water is already scarce.Shifting climatological patterns are expected to impact thermopluviometric regimes,water cycle components,hydrological responses,and plant physiology,evapotranspiration rates,crop productivity and land management operations.This work(1)assessed the impacts of different predicted climate conditions on water yield;(2)inferred the impacts of climate change on biomass production on eucalypt-to-eucalypt succes sion.To this end,the widely accepted Soil and Water Assessment Tool(SWAT)was run with the RCA,HIRHAM5 and RACMO climate models for two emission scenarios(RCP 4.5 and8.5).Three 12-year periods were considered to simulate tree growth under coppice regime.The results revealed an overall reduction in streamflow and water yield in the catchment in line with the projected reduction in total annual precipitation.Moreover,HIRHAM5 and RACMO models forecast a slight shift in seasonal streamflow of up to 2 months(for2024-2048)in line with the projected increase in precipitation from May to September.For biomass production,the extreme climate model(RCA)and severe emis sion scenario(RCP 8.5)predicted a decrease up to 46%.However,in the less extreme and more-correlated(with actual catchment climate conditions)climate models(RACMO and HIRHAM5)and in the less extreme emission scenario(RCP 4.5),biomass production increased(up to 20%),and the growth cycle was slightly reduced.SWAT was proven to be a valuable tool to assess climate change impacts on a eucalypt-dominated catchment and is a suitable decision-support tool for forest managers.

The Climate Response to Global Forest Area Changes under Different Warming Scenarios in China

Human activities have notably affected the Earth’s climate through greenhouse gases(GHG), aerosol, and land use/land cover change(LULCC). To investigate the impact of forest changes on regional climate under different shared socioeconomic pathways(SSPs), changes in surface air temperature and precipitation over China under low and medium/high radiative forcing scenarios from 2021 to 2099 are analyzed using multimodel climate simulations from the Coupled Model Intercomparison Project Phase 6(CMIP6). Results show that the climate responses to forest changes are more significant under the low radiative forcing scenario. Deforestation would increase the mean, interannual variability, and the trend of surface air temperature under the low radiative forcing scenario, but it would decrease those indices under the medium/high radiative forcing scenario. The changes in temperature show significant spatial heterogeneity. For precipitation, under the low radiative forcing scenario, deforestation would lead to a significant increase in northern China and a significant decrease in southern China, and the effects are persistent in the near term(2021–40), middle term(2041–70), and long term(2071–99). In contrast, under the medium/high radiative forcing scenario, precipitation increases in the near term and long term over most parts of China, but it decreases in the middle term, especially in southern, northern,and northeast China. The magnitude of precipitation response to deforestation remains comparatively small.

A Rigorous Analysis of Vehicle-to-Vehicle Range Performance in a Rural Channel Propagation Scenario as a Function of Antenna Type and Location via Simulation and Field Trails

Vehicle-to-Everything(V2X) communications will be an essential part of the technology in future autonomous drive decision systems.A fundamental procedure is to establish a robust communication channel between end-to-end devices.Due to the antenna placed at different positions on vehicles,the existing cellular electro-magnetic(EM) wave propagation modelling does not fit properly for V2X direct communication application.In order to figure out a feasible understanding of this problem,this paper focuses on the propagation channel analysis in a rural Vehicle-to-Vehicle(V2V) scenario for vehicular communication with antenna position experiments at different heights.By adopting the ray-tracing algorithm,a rural scenario simulation model is built up via the use of a commercial-off-the-shelf(COTS) EM modelling software package,that computes the path loss received power and delay spread for a given propagation channel.Next,a real-world vehicle measurement campaign was performed to verify the simulation results.The simulated and measured receiver power was in good agreement with each other,and the results of this study considered two antenna types located at three different relative heights between the two vehicles.This research provides constructive guidance for the V2V antenna characteristics,antenna placement and vehicle communication channel analysis.

Study on 5G Application Scenarios in Intelligent High-Speed Railway

5G technology is indispensable for developing comprehensive perception and ubiquitous interconnection of intelligent high-speed railways(HSRs),and can be applied to many scenarios in intelligent construction,intelligent equipment,intelligent operation and in other fields.In order to promote the standardized application of 5G technology in intelligent HSRs in a scientific and orderly manner and to avoid redundant construction and wasteful investment,it is imperative to carry out a systematical top-level design of the application scenarios at the initial stage.To this end,after investigating and analyzing the 5G application demands in different aspects of HSRs and the general structure of the railway 5G network,this paper formulates an overall planning of 5G technology application scenarios and proposes solutions to some typical application scenarios in the intelligent HSR system,based on the architecture and requirements of the intelligent HSR system.

CMIP6情景模式比较计划(ScenarioMIP)概况与评述

情景模式比较计划(ScenarioMIP)是第六次国际耦合模式比较计划(CMIP6)最重要的子计划之一。该子计划基于不同共享社会经济路径可能发生的能源结构所产生的人为排放及土地利用变化,设计了一系列新的情景预估试验,为未来气候变化机理研究以及气候变化减缓和适应研究提供关键的数据支持。文中将重点介绍ScenarioMIP的试验设计及模式参与情况,并对其应用前景加以讨论和展望。

Measurements and Characterization for the Vehicle-to-Infrastructure Channel in Urban and Highway Scenarios at 5.92GHz

In the future smart transportation system, reliable vehicle-to-infrastructure(V2 I) communication is very important to ensure vehicle driving safety and to improve vehicle driving efficiency. In this paper, V2 I channel measurements at 5.92 GHz are conducted in typical urban and highway scenarios.The frequency and bandwidth of transmission, as well as the deployment of the RSU(roadside unit) and the OBU(on board unit), are selected by considering the recommendation proposed by 3 GPP TR 36.885. Then,based on the measured data, the key channel characteristic parameters of the V2 I channel are extracted,including path loss, root-mean-square delay spread,stationarity distance, and Doppler spread, etc. Also,the statistical characteristics of the parameters, including time-varying and Doppler characteristics, are investigated and characterized. The work in this paper helps researchers design technology and communication systems in similar scenarios.

从Scenarios到状态图的算法分析

采用Scenarios进行需求建模能够反映从用户角度观察到的系统的行为,状态图是系统行为的精确描述。从Scenario到状态图的自动转换是指软件开发过程中从UML需求模型自动生成行为模型的过程,其研究对于细化系统行为,保持开发过程中模型间的一致性有重要意义。对其研究现状及进展进行了介绍,并对现有算法进行了总结和分类,进一步指出这些算法的不足和今后需要改进的方向。