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.

Defects and morphology engineering for constructing V_(s)-Ni_(3)S_(2)@V_(s)-Cu_(2)S nanotube heterojunction arrays toward efficient bifunctional electrocatalyst for overall water splitting

The development of highly active,stable and inexpensive electrocatalysts for hydrogen production by defects and morphology engineering remains a great challenge.Herein,S vacancies-rich Ni_(3)S_(2)@Cu_(2)S nan-otube heterojunction arrays were in-situ grown on copper foam(V_(s)-Ni_(3)S_(2)@V_(s)-Cu_(2)S NHAs/CF)for efficient electrocatalytic overall water splitting.With the merits of nanotube arrays and efficient electronic mod-ulation drived by the OD vacancy defect and 2D heterojunction defect,the resultant V_(s)-Ni_(3)S_(2)@V_(s)-Cu_(2)S NHAs/CF electrocatalyst exhibits excellent electrocatalytic activity with a low overpotential of 47 mV for the hydrogen evolution reaction(HER)at 10 mA cm^(-2) current density,and 263 mV for the oxygen evolution reaction(OER)at 50 mA cm^(-2) current density,as well as a cell voltage of 1.48 V at 10 mA cm^(-2).Moreover,the nanotube heterojunction arrays endows V_(s)-Ni_(3)S_(2)@V_(s)-Cu_(2)S NHAs/CF with outstanding stability in long-term catalytic processes,as confirmed by the continuous chronopotentiom-etry tests at current densities of 10 mA cm^(-2) for 100 h.

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.

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.

MOF-Derived Iron-Cobalt Phosphide Nanoframe as Bifunctional Electrocatalysts for Overall Water Splitting

Transition metal phosphides(TMPs)have emerged as an alternative to precious metals as efficient and low-cost catalysts for water electrolysis.Elemental doping and morphology control are effective approaches to further improve the performance of TMPs.Herein,Fe-doped CoP nanoframes(Fe-CoP NFs)with specific open cage configuration were designed and synthesized.The unique nano-framework structured Fe-CoP material shows overpotentials of only 255 and 122 mV at 10 mA cm^(−2)for oxygen evolution reaction(OER)and hydrogen evolution reaction(HER),respectively,overwhelming most transition metal phosphides.For overall water splitting,the cell voltage is 1.65 V for Fe-CoP NFs at a current density of 10 mA cm^(−2),much superior to what is observed for the classical nanocubic structures.Fe-CoP NFs show no activity degradation up to 100 h which contrasts sharply with the rapidly decaying performance of noble metal catalyst reference.The superior electrocatalytic performance of Fe-CoP NFs due to abundant accessible active sites,reduced kinetic energy barrier,and preferable*O-containing intermediate adsorption is demonstrated through experimental observations and theoretical calculations.Our findings could provide a potential method for the preparation of multifunctional material with hollow structures and offer more hopeful prospects for obtaining efficient earth-abundant catalysts for water splitting.

In-situ building of multiscale porous NiFeZn/NiZn-Ni heterojunction for superior overall water splitting

The development of efficient nonprecious bifunctional electrocatalysts for water electrolysis is crucial to enhance the sluggish kinetics of the oxygen evolution reaction(OER)and hydrogen evolution reaction(HER).A self-supporting,multiscale porous NiFeZn/NiZn-Ni catalyst with a triple interface heterojunction on nickel foam(NF)(NiFeZn/NiZn-Ni/NF)was in-situ fabricated using an electroplating-annealing-etching strategy.The unique multiinterface engineering and three-dimensional porous scaffold significantly modify the mass transport and electron interaction,resulting in superior bifunctional electrocatalytic performance for water splitting.The NiFeZn/NiZn-Ni/NF catalyst demonstrates low overpotentials of 187 m V for HER and 320 mV for OER at a current density of 600 mA/cm~2,along with high durability over 150 h in alkaline solution.Furthermore,an electrolytic cell assembled with NiFeZn/NiZn-Ni/NF as both the cathode and anode achieves the current densities of 600 and 1000 m A/cm2 at cell voltages of 1.796 and 1.901 V,respectively,maintaining the high stability at 50 mA/cm2 for over 100 h.These findings highlight the potential of NiFeZn/NiZn-Ni/NF as a cost-effective and highly efficient bifunctional electrocatalyst for overall water splitting.

Self-derivation and reconstruction of silver nanoparticle reinforced cobalt-nickel bimetallic hydroxides through interface engineering for overall water splitting

Designing efficient and long-lasting non-metal electrocatalysts is an urgent task for addressing the issue of kinetic hysteresis in electrochemical oxidation reactions.The bimetallic hydroxides,catalyzing the oxygen evolution reaction(OER),have significant research potential because hydroxide reconstruction to generate an active phase is a remarkable advantage.Herein,the complete reconstruction of ultrathin CoNi(OH)_(2) nanosheets was achieved by embedding Ag nanoparticles into the hydroxide to induce a spontaneous redox reaction(SRR),forming heterojunction Ag@CoNi(OH)_(2) for bifunctional hydrolysis.Theoretical calculations and in situ Raman and ex situ characterizations revealed that the inductive effect of the Ag cation redistributed the charge to promote phase transformation to highly activate Ag-modified hydroxides.The Co-Ni dual sites in Co/NiOOH serve as novel active sites for optimizing the intermediates,thereby weakening the barrier formed by OOH^*.Ag@CoNi(OH)_(2) required a potential of 1.55 V to drive water splitting at a current density of 10 mA cm^(-2),with nearly 98.6% Faraday efficiency.Through ion induction and triggering of electron regulation in the OER via the synergistic action of the heterogeneous interface and surface reconstruction,this strategic design can overcome the limited capacity of bimetallic hydroxides and bridge the gap between the basic theory and industrialization of water decomposition.

Asymmetric configuration activating lattice oxygen via weakening d-p orbital hybridization for efficient C/N separation in urea overall electrolysis

Urea oxidation reaction(UOR)is proposed as an exemplary half-reaction in renewable energy applications because of its low thermodynamical potential.However,challenges persist due to sluggish reaction kinetics and complex by-products separation.To this end,we introduce the lattice oxygen oxidation mechanism(LOM),propelling a novel UOR route using a modified CoFe layered double hydroxide(LDH)catalyst termed CFRO-7.Theoretical calculations and in-situ characterizations highlight the activated lattice oxygen(O_(L))within CFRO-7 as pivotal sites for UOR,optimizing the reaction pathway and accelerating the kinetics.For the urea overall electrolysis application,the LOM route only requires a low voltage of 1.54 V to offer a high current of 100 mA cm^(-2) for long-term utilization(>48 h).Importantly,the by-product NCO^(-)−is significantly suppressed,while the CO_(2)2/N_(2) separation is efficiently achieved.This work proposed a pioneering paradigm,invoking the LOM pathway in urea electrolysis to expedite reaction dynamics and enhance product selectivity.

Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors

BACKGROUND The colon cancer prognosis is influenced by multiple factors,including clinical,pathological,and non-biological factors.However,only a few studies have focused on computed tomography(CT)imaging features.Therefore,this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics,and establishes a nomogram to provide critical guidance for the individualized treatment.AIM To establish and validate a nomogram to predict the overall survival(OS)of patients with colon cancer.METHODS A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021.The patients were randomly divided into training and testing groups at a 1:1 ratio.Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS,and a nomogram model was constructed for the training group.Survival curves were calculated using the Kaplan–Meier method.The concordance index(C-index)and calibration curve were used to evaluate the nomogram model in the training and testing groups.RESULTS Multivariate logistic regression analysis revealed that lymph node metastasis on CT,perineural invasion,and tumor classification were independent prognostic factors.A nomogram incorporating these variables was constructed,and the C-index of the training and testing groups was 0.804 and 0.692,respectively.The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS.CONCLUSION A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability.It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.

Reconcile the contradictory wettability requirements for the reduction and oxidation half-reactions in overall CO_(2) photoreduction via alternately hydrophobic surfaces

The overall photocatalytic CO_(2) reduction reaction(OPCRR)that can directly convert CO_(2) and H_(2)O into fuels represents a promising renewable energy conversion technology.As a typical redox reaction,the OPCRR involves two half-reactions:the CO_(2) reduction half-reaction(CRHR)and the water oxidation half-reaction(WOHR).Generally,both half-reactions can be promoted by adjusting the wettability of catalysts.However,there is a contradiction in wettability requirements for the two half-reactions.Specifically,CRHR prefers a hydrophobic surface that can accumulate more CO_(2) molecules on the active sites,ensuring the appropriate ratio of gas-phase(CO_(2))to liquid-phase(H_(2)O)reactants.Conversely,the WOHR prefers a hydrophilic surface that can promote the departure of the gaseous product(O_(2))from the catalyst surface,preventing isolation between active sites and the reactant(H_(2)O).Here,we successfully reconciled the contradictory wettability requirements for the CRHR and WOHR by creating an alternately hydrophobic catalyst.This was achieved through a selectively hydrophobic modification method and a charge-transfer-control strategy.Consequently,the collaboratively promoted CRHR and WOHR led to a significantly enhanced OPCRR with a solar-to-fuel conversion efficiency of 0.186%.Notably,in ethanol production,the catalyst exhibited a 10.64-fold increase in generation rate(271.44μmol g^(-1)h~(-1))and a 4-fold increase in selectivity(55.77%)compared to the benchmark catalyst.This innovative approach holds great potential for application in universal overall reactions involving gas participation.

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.

Parallel Computing Based Solution for Reliability-constrained Distribution Network Planning

The main goal of distribution network(DN)expan-sion planning is essentially to achieve minimal investment con-strained by specified reliability requirements.The reliability-constrained distribution network planning(RcDNP)problem can be cast as an instance of mixed-integer linear programming(MILP)which involves ultra-heavy computation burden espe-cially for large-scale DNs.In this paper,we propose a parallel computing based solution method for the RcDNP problem.The RcDNP is decomposed into a backbone grid and several lateral grid problems with coordination.Then,a parallelizable aug-mented Lagrangian algorithm with acceleration method is devel-oped to solve the coordination planning problems.The lateral grid problems are solved in parallel through coordinating with the backbone grid planning problem.Gauss-Seidel iteration is adopted on the subset of the convex hull of the feasible region constructed by decomposition.Under mild conditions,the opti-mality and convergence of the proposed method are verified.Numerical tests show that the proposed method can significant-ly reduce the solution time and make the RcDNP applicable for real-worldproblems.

High-throughput calculation-based rational design of Fe-doped MoS_(2) nanosheets for electrocatalytic p H-universal overall water splitting

Electrocatalytic water splitting is crucial for H2generation via hydrogen evolution reaction(HER)but subject to the sluggish dynamics of oxygen evolution reaction(OER).In this work,single Fe atomdoped MoS_(2)nanosheets(SFe-DMNs)were prepared based on the high-throughput density functional theory(DFT)calculation screening.Due to the synergistic effect between Fe atom and MoS_(2)and optimized intermediate binding energy,the SFe-DMNs could deliver outstanding activity for both HER and OER.When assembled into a two-electrode electrolytic cell,the SFe-DMNs could achieve the current density of 50 mA cm^(-2)at a low cell voltage of 1.55 V under neutral condition.These results not only confirmed the effectiveness of high-throughput screening,but also revealed the excellent activity and thus the potential applications in fuel cells of SFe-DMNs.

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 theControlIndicatorsofConstruction LandinIndustrialProjectsissued 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.

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.

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.

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.

A Reverse Path Planning Approach for Enhanced Performance of Multi-Degree-of-Freedom Industrial Manipulators

In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking.While Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion optimization.Achieving satisfactory results in practical scenarios remains challenging.In response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial manipulators.The approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free path.To enhance convergence speed,the Q-learning algorithm in RL is augmented with Dyna-Q.Additionally,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection technique.Furthermore,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power joints.The efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target positions.Experimental results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target point.Moreover,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.

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.