Artificial potential fields and optimal controllers are two common methods for path planning of autonomous vehicles. An artificial potential field method is capable of assigning different potential ...functions to different types of obstacles and road structures and plans the path based on these potential functions. It does not, however, include the vehicle dynamics in the path-planning process. On the other hand, an optimal path-planning controller integrated with vehicle dynamics plans an optimal feasible path that guarantees vehicle stability in following the path. In this method, the obstacles and road boundaries are usually included in the optimal control problem as constraints and not with any arbitrary function. A model predictive path-planning controller is introduced in this paper such that its objective includes potential functions along with the vehicle dynamics terms. Therefore, the path-planning system is capable of treating different obstacles and road structures distinctly while planning the optimal path utilizing vehicle dynamics. The path-planning controller is modeled and simulated on a CarSim vehicle model for some complicated test scenarios. The results show that, with this path-planning controller, the vehicle avoids the obstacles and observes road regulations with appropriate vehicle dynamics. Moreover, since the obstacles and road regulations can be defined with different functions, the path-planning system plans paths corresponding to their importance and priorities.
In this paper, a new fast tool servocontrol method for noncircular turning process (NCTP) is presented. Based on the tracking and disturbance rejection requirements for NCTP, the controller is ...designed through a combined active disturbance rejection control and feedforward arrangement by exploiting the unique disturbance estimation and compensation concept and the known reference acceleration signals. In such a design framework, an extended state observer is applied to estimate and compensate for the variant dynamics of the system, nonlinearly variable cutting load, and other uncertainties. Then, a simple proportional integral controller and the acceleration feedforward design produce the control law. To quantify the controller performances, the transfer function description of the controller is derived, and the dynamic stiffness and tracking have been analyzed. By defining the vector margin variation rate, the effects of the plant parameter variations on closed-loop stability are also addressed. Experimental results of machining the first- and second-order oval profiles demonstrate that the tracking error is less than 3 mum for different cutting parameters.
Active disturbance rejection control (ADRC) is a new design concept that shows promising power in dealing with the uncertainties of control systems. However, most of the previous work has been ...numerical time-domain development and frequency-domain analysis for the linear framework. This paper focuses on the frequency-domain analysis of the nonlinear ADRC behavior using the describing function method and characterizes the effect of the fal nonlinearity parameter on the performance of the closed-loop system. Both the describing function of the nonlinearity and the transfer function description of the system's linear portion are derived. The stability, dynamic stiffness, and tracking performance are analyzed for a second-order single-input single-output plant. The analysis results show that the nonlinearity parameter plays a crucial role in the system performance. The nonlinear ADRC has higher control efficiency than the linear ADRC but reduces the stability margin of the system. Using the fast tool servo case, simulations and hardware experiments are conducted, and the results further support the analysis.
Accumulation and selection of somatic mutations in a Darwinian framework result in intra-tumor heterogeneity (ITH) that poses significant challenges to the diagnosis and clinical therapy of cancer. ...Identification of the tumor cell populations (clones) and reconstruction of their evolutionary relationship can elucidate this heterogeneity. Recently developed single-cell DNA sequencing (SCS) technologies promise to resolve ITH to a single-cell level. However, technical errors in SCS data sets, including false-positives (FP) and false-negatives (FN) due to allelic dropout, and cell doublets, significantly complicate these tasks. Here, we propose a nonparametric Bayesian method that reconstructs the clonal populations as clusters of single cells, genotypes of each clone, and the evolutionary relationship between the clones. It employs a tree-structured Chinese restaurant process as the prior on the number and composition of clonal populations. The evolution of the clonal populations is modeled by a clonal phylogeny and a finite-site model of evolution to account for potential mutation recurrence and losses. We probabilistically account for FP and FN errors, and cell doublets are modeled by employing a Beta-binomial distribution. We develop a Gibbs sampling algorithm comprising partial reversible-jump and partial Metropolis-Hastings updates to explore the joint posterior space of all parameters. The performance of our method on synthetic and experimental data sets suggests that joint reconstruction of tumor clones and clonal phylogeny under a finite-site model of evolution leads to more accurate inferences. Our method is the first to enable this joint reconstruction in a fully Bayesian framework, thus providing measures of support of the inferences it makes.
Early recognition and rapid initiation of high-quality cardiopulmonary resuscitation (CPR) are key to maximising chances of achieving successful return of spontaneous circulation in patients with ...out-of-hospital cardiac arrests (OHCAs), as well as improving patient outcomes both inside and outside hospital. Mechanical chest compression devices such as the LUCAS-2 have been developed to assist rescuers in providing consistent, high-quality compressions, even during transportation. However, providing uninterrupted and effective compressions with LUCAS-2 during transportation down stairwells and in tight spaces in a non-supine position is relatively impossible. In this study, we proposed adaptations to the LUCAS-2 to allow its use during transportation down stairwells and examined its effectiveness in providing high-quality CPR to simulated OHCA patients. 20 volunteer emergency medical technicians were randomised into 10 pairs, each undergoing 2 simulation runs per experimental arm (LUCAS-2 versus control) with a loaded Resusci Anne First Aid full body manikin weighing 60 kg. Quality of CPR compressions performed was measured using the CPRmeter placed on the sternum of the manikin. The respective times taken for each phase of the simulation protocol were recorded. Fisher's exact tests were used to analyse categorical variables and median test to analyse continuous variables. The LUCAS-2 group required a longer time (~ 35 s) to prepare the patient prior to transport (p < 0.0001) and arrive at the ambulance (p < 0.0001) compared to the control group. The CPR quality in terms of depth and rate for the overall resuscitation period did not differ significantly between the LUCAS-2 group and control group, though there was a reduction in both parameters when evaluating the device's automated compressions during transport. Nevertheless, the application of the LUCAS-2 device yielded a significantly higher chest compression fraction of 0.76 (p < 0.0001). Our novel adaptations to the LUCAS-2 device allow for uninterrupted compressions in patients being transported down stairwells, thus yielding better chest compression fractions for the overall resuscitation period. Whether potentially improved post-OHCA survival rates may be achieved requires confirmation in a real-world scenario study.
Stable and robust walking in various environments is one of the most important abilities for a humanoid robot. This paper addresses walking pattern synthesis and sensory feedback control for humanoid ...stair climbing. The proposed stair-climbing gait is formulated to satisfy the environmental constraint, the kinematic constraint, and the stability constraint; the selection of the gait parameters is formulated as a constrained nonlinear optimization problem. The sensory feedback controller is phase dependent and consists of the torso attitude controller, zero moment point compensator, and impact reducer. The online learning scheme of the proposed feedback controller is based on a policy gradient reinforcement learning method, and the learned controller is robust against external disturbance. The effectiveness of our proposed method was confirmed by walking experiments on a 32-degree-of-freedom humanoid robot.
Since December 2019, there has been an outbreak of a novel coronavirus (COVID-19) infection in Wuhan, China. Meanwhile, the outbreak also drew attention and concern from the World Health Organization ...(WHO). COVID-19 is another human infectious disease caused by coronavirus. The transmission of COVID-19 is potent and the infection rate is fast. Since there is no specific drug for COVID-19, the treatment is mainly symptomatic supportive therapy. In addition, it should be pointed out that patients with severe illness need more aggressive treatment and meticulous care. Recently, accurate RNA detection has been decisive for the diagnosis of COVID-19. The development of highly sensitive RT-PCR has facilitated epidemiological studies that provide insight into the prevalence, seasonality, clinical manifestations and course of COVID-19 infection. In this review, we summarize the epidemiology and characteristics of COVID-19.
Single-cell sequencing enables the inference of tumor phylogenies that provide insights on intra-tumor heterogeneity and evolutionary trajectories. Recently introduced methods perform this task under ...the infinite-sites assumption, violations of which, due to chromosomal deletions and loss of heterozygosity, necessitate the development of inference methods that utilize finite-sites models. We propose a statistical inference method for tumor phylogenies from noisy single-cell sequencing data under a finite-sites model. The performance of our method on synthetic and experimental data sets from two colorectal cancer patients to trace evolutionary lineages in primary and metastatic tumors suggests that employing a finite-sites model leads to improved inference of tumor phylogenies.
This article presents a model predictive vehicle stability controller that considers tire force nonlinearities and the combined-slip effect. Loss of cornering forces caused by increased longitudinal ...slip and changes in the slip angle due to the vehicle lateral response are considered in the prediction model of the controller. The developed controller adjusts tire slip ratios based on forces of the front and rear axles, monitors tire capacities, and normal forces, and exhibits excellent performance in maintaining lateral responses within a stable region. The performance of the proposed predictive controller is assessed in software simulations as well as road experiments in various pure-slip and combined-slip driving scenarios and under different road friction conditions.
Although obesity is associated with risk for chronic kidney disease and improved survival, less is known about the associations of obesity with risk of acute kidney injury and post acute kidney ...injury mortality.
In a single-center inception cohort of almost 15,000 critically ill patients, we evaluated the association of obesity with acute kidney injury and acute kidney injury severity, as well as in-hospital and 1-year survival. Acute kidney injury was defined using the Kidney Disease Outcome Quality Initiative criteria.
The acute kidney injury prevalence rates for normal, overweight, class I, II, and III obesity were 18.6%, 20.6%, 22.5%, 24.3%, and 24.0%, respectively, and the adjusted odds ratios of acute kidney injury were 1.18 (95% CI, 1.06-1.31), 1.35 (1.19-1.53), 1.47 (1.25-1.73), and 1.59 (1.31-1.87) when compared with normal weight, respectively. Each 5-kg/m² increase in body mass index was associated with a 10% risk (95% CI, 1.06-1.24; p < 0.001) of more severe acute kidney injury. Within-hospital and 1-year survival rates associated with the acute kidney injury episodes were similar across body mass index categories.
Obesity is a risk factor for acute kidney injury, which is associated with increased short- and long-term mortality.
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