The Essence of Non-Traditional Security Issues and Their Solutions

Non-traditional security issues have arisen since the 1960s,especially after the end of the Cold War,and are becoming a major issue in world security and politics.This reflects tremendous changes in the world situation.With diverse causes and plural referent objects,non-traditional security issues cover nearly all the problems in the world today and make development difficult to sustain.This raises the question of whether human society and the earth can survive.Power politics one-sidedly stresses the role of power,endangering the harmonious development of nations and the whole of human society.It is not at all conducive to the solution of non-traditional security issues.The solution of non-traditional security issues demands cooperation from all actors in the international community.Multiple means are needed to solve these issues.Equal dialogue between all the actors,which can easily be attained,will play an effective role,as long as all actors respect each other's differences.

Research on surface characteristics of non-traditional finishing

This paper reports results of investigations of some surface characteristics, and resulting performance of parts proc-essed using non-traditional finishing methods. The friction factor, precision keeping and anti-conglutination performance of the finished surfaces are considered, and surface characteristics such as microtopography and machining texture were investigated. The overall performance of surfaces finished using non-traditional finishing methods was found to be significantly better than that of traditional finishing methods.

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.

Motion Planning for Autonomous Driving with Real Traffic Data Validation

Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.

Ground threat prediction-based path planning of unmanned autonomous helicopter using hybrid enhanced artificial bee colony algorithm

Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.

Non-traditional Dialogues between Thoughts

The article considers a new and non-traditional form of dialogue. Calling it a ＂spiritual dialogue＂ or the intersection of thoughts, the author comments on this type of dialogue as a basis for interreligious, intercultural and intercivilizational dialogues, seeing it as their main motive force. In this study, firstly, traditional and non-traditional dialogues are compared and indicate their specific features on the basis of the work of the Eastern and the West thinkers. Then, the nontraditional dialogue has been considered in the context of modern information chaos. The last section of the article is devoted to the analysis of the basic principles of non-traditional dialogue, emphasizing the role of language. The conclusion of the article once again highlights the importance of non-traditional dialogue that starts in the inner world of the human being, which gives him a possibility to observe an object from two viewpoints and merge and these different views in the mind.

"Non-Traditional" Undertakings Enable Sichuan Farmers to Get Rich

We are publishing two stories about how in Sichuan Province, southwest China, farmers are getting rich with help from local governments by developing ＂non-traditional undertakings.＂ In China＇s current official terminology, a ＂non-traditional undertaking＂ can be anything other than the undertaking on which farmers, by tradition, depend for the bulk of their incomes-for example, crop and animal farming in most of China＇s farming areas. ＂Non-traditional＂ undertakings are more profitable than ＂traditional＂ ones.

C-PLAN指数作为免疫检查点抑制剂治疗晚期食管癌预后指标的临床研究

目的评估C反应蛋白(CRP)、体力状况评分(PS)、乳酸脱氢酶(LDH)、白蛋白(ALB)及衍生中性粒细胞与淋巴细胞比值(dNLR)综合(C-PLAN)指数在接受免疫检查点抑制剂(ICI)治疗的晚期食管癌患者中的预后价值。方法收集扬州大学附属医院接受ICI治疗的147例晚期食管癌患者首次免疫治疗前的血液学指标。对CRP、PS、LDH、ALB及dNLR进行评分并相加得到C-PLAN指数。采用卡方检验分析C-PLAN指数与临床病理特征的相关性;采用Kaplan-Meier生存曲线分析C-PLAN指数对患者总生存期(OS)与无进展生存期(PFS)的影响;采用单因素和多因素Cox风险比例回归模型分析C-PLAN指数是否为影响预后的独立因素。结果147例晚期食管癌患者根据C-PLAN指数分为低风险组(<2分,n=46)和高风险组(≥2分,n=101)。C-PLAN指数与年龄、性别、PS评分、吸烟、临床分期、体质量指数、病理类型、治疗策略和是否手术均无相关性(P>0.05)。低风险组PFS和OS优于高风险组,差异有统计学意义(P<0.001)。在单因素Cox回归分析中,C-PLAN指数是PFS(P<0.001)和OS(P=0.002)的影响因素。在多因素Cox分析中,C-PLAN指数是影响PFS(P=0.001)和OS(P=0.006)的独立预后因素。结论C-PLAN指数可以作为预测接受ICI治疗的晚期食管癌患者预后的可靠临床指标。

Selection of media tools for community planning:A study from the perspective of communicative planning

In community planning,due to the lack of evidence regarding the selection of media tools,this study examines how a common but differentiated ideal speech situation can be created as well as how more appropriate media tools can be defined and selected in the community planning process.First,this study describes the concept and theoretical basis of media used in community planning from the perspectives of the multiple effects of media evolution on communicative planning.Second,the classification criteria and typical characteristics of media tools used to support community planning are clarified from three dimensions:acceptability,cost effectiveness,and applicability.Third,strategies for applying media tools in the four phases of communicative planning-namely,state analysis,problem identification,contradictory solution and optimization-are described.Finally,trends in the development of media tools for community planning are explored in terms of multistakeholder engagement,supporting scientific decision-making and multiple-type media integration.The results provide a reference for developing more inclusive,effective,and appropriate media tools for enhancing decision-making capacity and modernizing governance in community planning and policy-making processes.

Influence of a diet meal plan on pepsinogen I and II,gastrin-17,and nutritional status in gastric ulcer patients

BACKGROUND Gastric ulcers(GUs)have a high risk of clinical morbidity and recurrence,and further exploration is needed for the prevention,diagnosis,and treatment of the disease.AIM To investigated the effects of a diet plan on pepsinogen(PG)I,PG II,gastrin-17(G-17)levels and nutritional status in patients with GUs.METHODS A total of 100 patients with GUs treated between May 2022 and May 2023 were enrolled,with 47 patients in the control group receiving routine nursing and 53 patients in the experimental group receiving dietary nursing intervention based on a diet plan.The study compared the two groups in terms of nursing efficacy,adverse events(vomiting,acid reflux,and celialgia),time to symptom improvement(burning sensation,acid reflux,and celialgia),gastric function(PG I,PG II,and G-17 levels),and nutritional status[prealbumin(PA)and albumin(ALB)levels].RESULTS The experimental group showed a markedly higher total effective rate of nursing,a significantly lower incidence of adverse events,and a shorter time to symptom improvement than the control group.Additionally,the experimental group’s post-intervention PG I,PG II,and G-17 levels were significantly lower than preintervention or control group levels,whereas PA and ALB levels were significantly higher.CONCLUSION The diet plan significantly reduced PG I,PG II,and G-17 levels in patients with GUs and significantly improved their nutritional status.

Optimal search path planning of UUV in battlefeld ambush scene

Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.

Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

Exploration of Detailed Planning Practice of Chemical Industrial Parks under the Background of Territorial Space Planning

With the gradual completion of the overall planning of city and county land space,the detailed planning will be prepared according to the requirements of transmitting and refining the upper planning.Industrial parks are one of the“main forces”of local economic development,and the preparation of their detailed planning will escort their development.The key points of the Control Indicators of Construction Land in Industrial Projectsissued in 2008 and 2023 were compared,and the new requirements for detailed planning under the background of territorial space and the contradictions between the detailed planning of industrial parks and the overall planning of the upper territorial space were sorted out based on the summary of the existing problems in the development of chemical parks.It provides some ideas for the practice of detailed planning of chemical industrial parks under the background of territorial space.

Succession Plan for Nursing Academic Program Administrators

Leadership succession in nursing academic programs poses a significant challenge, primarily due to the limited availability of professionals with the competencies required for effective leadership [1]. This study aims to address this gap by investigating the critical factors in succession planning for nursing program administrators. The research objectives include identifying the competencies necessary for academic administrators, assessing the experience of current administrators, and developing a comprehensive succession plan framework. The research uses qualitative methods, including literature review, interviews with nursing administrators, and analysis of existing succession models. Results highlight the importance of integrating strategic planning into succession processes to ensure smooth transitions and organizational stability. Conclusions suggest that a formalized succession plan, incorporating mentorship and leadership development, can mitigate leadership gaps in nursing academia [2].

基于链式管理的“plan list”在经鼻蝶入路垂体瘤切除术患者围手术期的应用

目的探讨基于链式管理的“plan list”在经鼻蝶入路垂体瘤切除术患者围手术期的应用效果。方法选取2023年4月至10月就诊于遵义医科大学附属医院神经外科经鼻蝶入路垂体瘤切除术的患者80例,按随机数字表法将其分为对照组(40例)和干预组(40例)。对照组采用常规围手术期护理,干预组在常规围手术期护理基础上实施基于链式管理的“plan list”护理。比较两组出院前1天的疾病不确定感量表(MUIS)、医学应对方式问卷(MCMQ)得分及纽卡斯尔护理满意度量表(NSNS)得分情况。结果干预后,两组MUIS得分低于干预前,且干预组低于对照组(P<0.05)。干预后,两组面对维度得分高于干预前,且干预组高于对照组(P<0.05);两组回避维度得分低于干预前,且干预组低于对照组(P<0.05);干预后,对照组屈服得分高于干预前,干预组屈服得分低于干预前,且干预组低于对照组(P<0.05)。干预后,两组NSNS得分高于干预前,且干预组高于对照组(P<0.05)。结论基于链式管理的“plan list”有利于护理人员根据患者病情进行动态评估、跟踪及病情的整体观察,提高了患者疾病应对方式能力与满意度,降低疾病不确定感,值得临床推广使用。

Postpartum Family Planning at the Timbuktu Hospital in Mali

Introduction: Postpartum family planning is the prevention of pregnancies during the 12 months following childbirth. Few studies have been devoted to postpartum family planning in Mali. Our work will contribute to reducing unmet need for family planning. Objective: To study the use of contraceptive methods in the postpartum period in the obstetrics and gynecology unit of Timbuktu hospital. Materials and Methods: This was a descriptive and analytical cross-sectional study with prospective collection of data from January 1, 2022 to December 31, 2023. All women who gave birth having chosen and benefited from a contraceptive method were included. The statistical test used was the Fisher test with a significance threshold fixed at 5%. Results: The frequency of contraception in the postpartum period was 17.03%. The average age of clients was 26.14% with extremes of 14 and 45 years. They were paupiparous at 56.4% with an inter-birth interval of less than 12 months at 12.3%. More than half of the counseling (58.5%) was done during postnatal visits. The methods chosen were implants at 48.1%, injectable progestins at 21.3%, intrauterine device at 14.7%, miro-progestin pills at 13.5%, tubal ligation at 1 .4% and condoms at 1%. The regular follow-up rate was 51.1% of cases and 25.6% had no follow-up. Conclusion: The overall rate of postpartum family planning of 17.08% remains low. Improving FP staff skills will reduce unmet needs and contribute to increasing contraceptive prevalence in Timbuktu.

Correlates of Mistimed Pregnancy and Unmet Need for Family Planning among Women of Reproductive Age in Sandema, Ghana

Background: Globally, an estimated 80 million unintended pregnancies comprising both mistimed and unwanted pregnancies are recorded yearly. Yet only half of the women at risk of mistimed pregnancy use contraceptives. In developing countries, over 100 million females have unmet need, and national surveys in Ghana indicate 23% unmet need rate. Methods: Using a cross-sectional community-based approach, a sample size of 300 women of reproductive age were selected using multi-step cluster sampling techniques. The study was quantitative, using structured interviewer-administered questionnaires. Results: Two-third (66%) of the women in reproductive age still had unmet need, 71% were currently pregnant, and more than a third (36%) confirmed ever having a mistimed pregnancy. Fifty-three percent (53%) of the women confirmed never communicating with their partners on family planning issues, a little below half (45%) took their own health care decisions. Seventy nine percent (79%) ever received family planning services from a health professional. Factors related to unmet needs included mistimed pregnancy, level of education, preferred birth/pregnancy interval, communication between partners and the autonomy to spend self-earnings. Conclusion: Considering that high rates of unmet need results in mistimed pregnancy, improved policies around the influence of unmet need on mistimed pregnancies are needed.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

Heuristic Expanding Disconnected Graph:A Rapid Path Planning Method for Mobile Robots

Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low planning efficiency owing to high redundancy and large computational complexity.Due to the limitations of the neighborhood search strategy,the robots could hardly obtain the most optimal global path.A global path planning algorithm,denoted as EDG*,is proposed by expanding nodes using a well-designed expanding disconnected graph operator(EDG)in this paper.Firstly,all obstacles are marked and their corners are located through the map pre-processing.Then,the EDG operator is designed to find points in non-obstruction areas to complete the rapid expansion of disconnected nodes.Finally,the EDG*heuristic iterative algorithm is proposed.It selects the candidate node through a specific valuation function and realizes the node expansion while avoiding collision with a minimum offset.Path planning experiments were conducted in a typical indoor environment and on the public dataset CSM.The result shows that the proposed EDG*reduced the planning time by more than 90%and total length of paths reduced by more than 4.6%.Compared to A*,Dijkstra and JPS,EDG*does not show an exponential explosion effect in map size.The EDG*showed better performance in terms of path smoothness,and collision avoidance.This shows that the EDG*algorithm proposed in this paper can improve the efficiency of path planning and enhance path quality.