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With the ongoing promotion and adoption of electric vehicles, intelligent and connected technologies have been continuously advancing. Electrical control systems implemented in electric vehicles have emerged as a critical research direction. Various drive-by-wire chassis systems, including drive-by-wire driving and braking systems and steer-by-wire systems, are extensively employed in vehicles. Concurrently, unavoidable issues such as conflicting control system objectives and execution system interference emerge, positioning integrated chassis control as an effective solution to these challenges. This paper proposes a model predictive control-based longitudinal dynamics integrated chassis control system for pure electric commercial vehicles equipped with electro–mechanical brake (EMB) systems, centralized drive, and distributed braking. This system integrates acceleration slip regulation (ASR), a braking force distribution system, an anti-lock braking system (ABS), and a direct yaw moment control system (DYC). This paper first analyzes and models the key components of the vehicle. Then, based on model predictive control (MPC), it develops a controller model for integrated stability with double-layer torque distribution. The required driving and braking torque for each wheel are calculated according to the actual and desired motion states of the vehicle and applied to the corresponding actuators. Finally, the effectiveness of this strategy is verified through simulation results from Matlab/Simulink. The simulation shows that the braking deceleration of the braking condition is increased by 32% on average, and the braking distance is reduced by 15%. The driving condition can enter the smooth driving faster, and the time is reduced by 1.5 s~5 s. The lateral stability parameters are also very much improved compared with the uncontrolled vehicles.

The contour following task of a multi-axis servo system is one of the most important applications of modern computer numerical control (CNC) machining. Reducing the contour error is an important content in the multi-axis contour following task. A common method to solve this problem is the cross-coupling control (CCC). Since the traditional CCC method cannot meet the requirements of tracking accuracy and contour control accuracy at large curvature positions in free-form curve machining, the main contribution of this paper is to propose a novel integrated control strategy based on arc length parameters for contour error compensation, which consists of a double-circle weighted approximation contour error estimation model based on arc length parameters module, an improved cross-coupling position command shaping controller (CPCSC) module, and an improved position error compensator (PEC) module. To improve the accuracy of contour error estimation for large free-form curvature trajectories, a double-circle weighted approximation contour error estimation model based on arc length parameters is proposed. The method first finds the nearest interpolation point by backtracking method and calculates the backward reference points by using the method based on arc length parameters. Then, the obtained backward reference points are used as the expected instruction points by the double-circle weighted approximation method, and the estimated value of contour error is calculated. Moreover, an improved structure of CPCSC is proposed. Compared with the traditional biaxial CCC structure, the advantage of this new structure is that the compensator design and stability analysis in its CCC are relatively simple, and it can be easily implemented on most current systems by reprogramming the reference position command subroutine. In addition, an improved PEC method is further proposed to reduce contour error. The main advantage of this module is that it can simultaneously improve tracking and contouring performances by compensating position errors in advance. The feasibility of the proposed integrated control strategy is verified by serval non-uniform rational B-spline (NURBS) parametric curve contour following experiments. Moreover, the results of comparative experiments indicate that the proposed integrated control strategy can significantly improve the tracking and contour control accuracy of biaxial contour following tasks compared with none-CCC method and CCC method, and has better contour control performance in large curvature positions.

Background The overlap in the epidemiology of malaria and helminths has been identified as a potential area to exploit for the development of an integrated control strategy that may help to achieve elimination of malaria and helminths. A randomized, controlled, observer-blind trial was conducted to assess the feasibility and safety of combining mass drug administration (MDA) for schistosomiasis and soil transmitted helminths (STH) with seasonal malaria chemoprevention (SMC) among children living in Senegal. Methods Female and male children aged 1–14 years were randomized 1:1:1, to receive Vitamin A and Zinc on Day 0, followed by SMC drugs (sulfadoxine-pyrimethamine and amodiaquine) on Days 1–3 (control group); or praziquantel and Vitamin A on Day 0, followed by SMC drugs on Days 1–3 (treatment group 1); or albendazole and praziquantel on Day 0, followed by SMC drugs on Days 1–3 (treatment group 2). Safety assessment was performed by collecting adverse events from all children for six subsequent days following administration of the study drugs. Pre- and post-intervention, blood samples were collected for determination of haemoglobin concentration, malaria microscopy, and PCR assays. Stool samples were analyzed using Kato-Katz, Merthiolate-iodine-formalin and PCR methods. Urine filtration, PCR and circulating cathodic antigen tests were also performed. Results From 9 to 22 June 2022, 627 children aged 1–14 years were randomized into the three groups described above. Mild, transient vomiting was observed in 12.6% (26/206) of children in treatment group 2, in 10.6% (22/207) in group 1, and in 4.2% (9/214) in the control group (p = 0.005). Pre-intervention, the geometric mean value of Plasmodium falciparum parasite density was highest among children who received albendazole, praziquantel with SMC drugs. Post-intervention, the parasite density was highest among children who received SMC drugs only. Children who received praziquantel and SMC drugs had a lower risk of developing severe anaemia than their counterparts who received SMC drugs alone (OR = 0.81, 95% CI 0.13–5.00, p = 0.63). Conclusions Integration of MDA for helminths with SMC drugs was safe and feasible among Senegalese children. These findings support further evaluation of the integrated control model. Trial registration : The study is registered at Clinical Trial.gov NCT05354258.

This paper proposes an integrated trajectory tracking strategy for unmanned delivery vehicles operating under complex road geometries and varying adhesion conditions. The method combines adaptive speed regulation informed by road curvature and adhesion with lateral predictive control. A Proportional-Integral-Derivative (PID) controller is utilized for speed regulation to suppress tire force saturation. while the lateral controller adopts model predictive control (MPC) and generates steering commands by solving a quadratic programming (QP) problem with explicit constraints that cover bounds on input magnitude and input rate. Extensive co-simulations using MATLAB/Simulink and Carsim demonstrate that the proposed method outperforms traditional fixed-speed control strategies in both single- and double-lane change scenarios. It achieves superior tracking accuracy and vehicle stability and effectively suppresses sideslip and instability under low adhesion conditions. The results validate the effectiveness of the control strategy, providing key theoretical and practical insights for the safe and reliable operation of unmanned delivery vehicles in complex urban environments.

Background Poverty contributes to the transmission of schistosomiasis via multiple pathways, with the insufficiency of appropriate interventions being a crucial factor. The aim of this article is to provide more economical and feasible intervention measures for endemic areas with varying levels of poverty. Methods We collected and analyzed the prevalence patterns along with the cost of control measures in 11 counties over the last 20 years in China. Seven machine learning models, including XGBoost, support vector machine, generalized linear model, regression tree, random forest, gradient boosting machine and neural network, were used for developing model and calculate marginal benefits. Results The XGBoost model had the highest prediction accuracy with an R 2 of 0.7308. Results showed that risk surveillance, snail control with molluscicides and treatment were the most effective interventions in controlling schistosomiasis prevalence. The best combination of interventions was interlacing seven interventions, including risk surveillance, treatment, toilet construction, health education, snail control with molluscicides, cattle slaughter and animal chemotherapy. The marginal benefit of risk surveillance is the most effective intervention among nine interventions, which was influenced by the prevalence of schistosomiasis and cost. Conclusions In the elimination phase of the national schistosomiasis program, emphasizing risk surveillance holds significant importance in terms of cost-saving. Graphical Abstract

The merging behavior of vehicles at entry ramps and the speed differences between ramps and mainline traffic cause merging traffic bottlenecks. Current research, primarily focusing on single traffic control strategies, fails to achieve the desired outcomes. To address this issue, this paper explores an integrated control strategy combining Variable Speed Limits (VSL) and Lane Change Control (LCC) to optimize traffic efficiency in ramp merging areas. For scenarios involving multiple ramp merges, a multi-agent reinforcement learning approach is introduced to optimize control strategies in these areas. An integrated control system based on the Factored Multi-Agent Centralized Policy Gradients (FACMAC) algorithm is developed. By transforming the control framework into a Decentralized Partially Observable Markov Decision Process (Dec-POMDP), state and action spaces for heterogeneous agents are designed. These agents dynamically adjust control strategies and control area lengths based on real-time traffic conditions, adapting to the changing traffic environment. The proposed Factored Multi-Agent Centralized Policy Gradients for Integrated Traffic Control in Dynamic Areas (FM-ITC-Darea) control strategy is simulated and tested on a multi-ramp scenario built on a multi-lane Cell Transmission Model (CTM) simulation platform. Comparisons are made with no control and Factored Multi-Agent Centralized Policy Gradients for Integrated Traffic Control (FM-ITC) strategies, demonstrating the effectiveness of the proposed integrated control strategy in alleviating highway ramp merging bottlenecks.

Dengue fever, a mosquito-borne disease caused by the dengue virus, imposes a substantial disease burden on the world. Wolbachia not only manipulates the reproductive processes of mosquitoes through maternal inheritance and cytoplasmic incompatibility (CI) but also restrain the replication of dengue viruses within mosquitoes, becoming a novel approach for biologically combating dengue fever. A combined use of Wolbachia and insecticides may help to prevent pesky mosquito bites and dengue transmission. A model with impulsive spraying insecticide is introduced to examine the spread of Wolbachia in wild mosquitoes. We prove the stability and permanence results of periodic solutions in the system. Partial rank correlation coefficients (PRCCs) can determine the importance of the contribution of input parameters on the value of the outcome variable. PRCCs are used to analyze the influence of input parameters on the threshold condition of the population replacement strategy. We then explore the impacts of mosquito-killing rates and pulse periods on both population eradication and replacement strategies. To further investigate the effects of memory intensity on the two control strategies, we developed a Caputo fractional-order impulsive mosquito population model with integrated control measures. Simulation results show that for the low fecundity scenario of individuals, as memory intensity increases, the mosquito eradication strategy will occur at a slower speed, potentially even leading to the mosquito replacement strategy with low female numbers. For the high fecundity scenario of individuals, with increasing memory intensity, the mosquito replacement strategy will be achieved more quickly, with lower mosquito population amplitudes and overall numbers. It indicates that although memory factors are not conducive to implementing a mosquito eradication strategy, achieving the replacement strategy with a lower mosquito amount is helpful. This work will be advantageous for developing efficient integrated control strategies to curb dengue transmission.

Over the past decades China has made a great stride in controlling schistosomiasis, eliminating transmission of Schistosoma japonicum in 5 provinces and remarkably reducing transmission intensities in the rest of the seven endemic provinces. Recently, an integrated control strategy, which focuses on interventions on humans and bovines, has been implemented throughout endemic areas in China. This strategy assumes that a reduction in transmission of S. japonicum from humans and bovines to the intermediate Oncomelania snail host would eventually block the transmission of this parasite, and has yielded effective results in some endemic areas. Yet the transmission of S. japonicum is relatively complicated – in addition to humans and bovines, more than 40 species of mammalians can serve as potential zoonotic reservoirs. Here, we caution that some factors – potential roles of other mammalian reservoirs and human movement in sustaining the transmission, low sensitivity/specificity of current diagnostic tools for infections, praziquantel treatment failures, changes in environmental and socio-economic factors such as flooding in key endemic areas - may pose great obstacles towards transmission interruption of the parasite. Assessing potential roles of these factors in the transmission and implications for current control strategies aiming at transmission interruption is needed.

The impacts of invasive aquatic plants (IAPs) are well documented and extensive relative to other functional groups of invasive species. Operational control of IAPs has evolved from a limited range of general biocides and physical control methods to the development of more targeted methods that offer more selective control measures. Despite the increase in IAP control strategies, several studies have identified the need to better serve IAP managers through identification and implementation of control- related research needs. Successfully aligning research needs and management products requires consulting with all interested parties to develop research questions and engagement of managers interested in adaptive management in the research programs. To this end, it is vital to use a process in which ecologists, practitioners, and decision-makers work collaboratively to develop scientific research, a process known as translational ecology. We identify IAP control-related research needs through a combination of species-specific literature reviews and an expert elicitation workshop for 20 priority IAP. Based on the literature reviews and workshop, generalized research needs, species-specific research needs, and an analysis of factors related to tool availability were developed. While the scope of this case study is the Great Lakes region, the IAPs and associated research needs discussed in this study are relevant to researchers studying these globally invasive species anywhere within their invasive range and should be used to inform research wherever it is undertaken. These findings will help agencies and academic institutions to plan future research activities and project proposals and serve as a reference document to inform funding agencies as they make decisions related to invasive aquatic plant control and research.