This article presents a model predictive control design for improving the yaw stability of a rear-wheel-drive vehicle equipped with an electronic limited slip differential (ELSD) and differential ...braking capability. It first develops a model for an ELSD system for predicting its torque distribution dynamics, then uses the model in designing an intelligent ELSD control that prevents unwanted oversteering yaw moments through direct control of the ELSD clutch pressure. Since differential braking degrades the vehicle's longitudinal motion and driver comfort, two control actuations are prioritized: 1) ELSD clutch pressure and 2) differential braking. An appropriate stability limit is defined for the vehicle yaw rate, and two control objectives: 1) enforcing the yaw rate stability limit and 2) tracking the desired yaw rate are defined and prioritized. The actuation priorities and the objective priorities are combined within a model predictive control structure with particular soft constraints such that the low priority actuation is activated when the high priority objective demands it. Additionally, optimum corner braking forces are calculated by geometrically analyzing tire force vectors. The performance of the proposed controller, implemented in a Cadillac CTS vehicle, is experimentally evaluated for a variety of driving maneuvers.
Single-cell transcriptomic analysis is widely used to study human tumors. However, it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to ...resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5 Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma, to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes, such as KRAS, and signatures, including epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.
► Water droplet Dynamics at GDL surface are analyzed both theoretically and numerically. ► Drag forces on a droplet are examined in both entrance and fully developed regions. ► Droplet deformation ...due to pressure variation is analyzed. ► The droplet detachment velocity at GDL surface is analytically obtained. ► Relation between the Weber and Reynolds numbers at the droplet detachment velocity is developed.
Water management is critical to achieving/maintaining high performance of polymer electrolyte fuel cells (PEFCs); and elucidating the dynamic behavior of liquid water droplets in a PEFC channel is essential to water management. In this work, the dynamics of liquid water droplets in a single PEFC gas flow channel is investigated through theoretical and numerical analyses. Forces on water droplet, droplet deformation and detachment are examined. The pressure and viscous drags are computed and compared at different flow regimes (which exhibit different droplet-dynamic scenarios) such as that in the entrance and fully developed flow regions. The expression for describing droplet shape change is derived, and it is found that the droplet can deform significantly at high gas-flow rates and when the droplet is relatively large (relative to the channel dimension). The detachment velocity is analyzed by comparing the wall adhesion and drag forces, and an expression relating the Weber number to the Reynolds number using the detachment velocity is developed. Follow-on work is also briefly discussed.
In this paper, a general control allocation (CA) algorithm is proposed based on a lexicographic optimization (LO) strategy for a vehicle's longitudinal and lateral control. The primary objective of ...this CA is to distribute the torque adjustments of the lateral controller such that the error between the desired and actual forces and moments at the vehicle's center of gravity is minimized, while maintaining the longitudinal tire slip ratios close to a desired range. Presence of various constraints in practical systems can significantly increase the complexity and effort of properly adjusting the tuning parameters in the objective function. Hence, an LO method is used to prioritize the objectives. Lateral stability of the vehicle has the highest priority and is subject to the constraint of maintaining small tire slip ratios. The second priority of CA is assigned to minimize the adjustment torques. The proposed LO-based approach reduces exhaustive vehicle testing commonly required for tuning of the separately designed controllers and the cost and time of the implementation. In addition, it makes the algorithm easily transferable from one vehicle to another by reducing the number of tuning parameters. Simulation and experimental results are presented to show the effectiveness of the proposed approach.
•A joint learning framework for both bone segmentation and landmark digitization.•A displacement map is used to explicitly model the spatial context information.•Results achieved by our method are ...clinically acceptable.•Only 1 min to complete both tasks of bone segmentation and landmark digitization.
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Cone-beam computed tomography (CBCT) scans are commonly used in diagnosing and planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities. Based on CBCT images, it is clinically essential to generate an accurate 3D model of CMF structures (e.g., midface, and mandible) and digitize anatomical landmarks. This process often involves two tasks, i.e., bone segmentation and anatomical landmark digitization. Because landmarks usually lie on the boundaries of segmented bone regions, the tasks of bone segmentation and landmark digitization could be highly associated. Also, the spatial context information (e.g., displacements from voxels to landmarks) in CBCT images is intuitively important for accurately indicating the spatial association between voxels and landmarks. However, most of the existing studies simply treat bone segmentation and landmark digitization as two standalone tasks without considering their inherent relationship, and rarely take advantage of the spatial context information contained in CBCT images. To address these issues, we propose a Joint bone Segmentation and landmark Digitization (JSD) framework via context-guided fully convolutional networks (FCNs). Specifically, we first utilize displacement maps to model the spatial context information in CBCT images, where each element in the displacement map denotes the displacement from a voxel to a particular landmark. An FCN is learned to construct the mapping from the input image to its corresponding displacement maps. Using the learned displacement maps as guidance, we further develop a multi-task FCN model to perform bone segmentation and landmark digitization jointly. We validate the proposed JSD method on 107 subjects, and the experimental results demonstrate that our method is superior to the state-of-the-art approaches in both tasks of bone segmentation and landmark digitization.
Single-cell RNA-seq is a powerful tool in decoding the heterogeneity in complex tissues by generating transcriptomic profiles of the individual cell. Here, we report a single-nuclei RNA-seq ...(snRNA-seq) transcriptomic study on human retinal tissue, which is composed of multiple cell types with distinct functions. Six samples from three healthy donors are profiled and high-quality RNA-seq data is obtained for 5873 single nuclei. All major retinal cell types are observed and marker genes for each cell type are identified. The gene expression of the macular and peripheral retina is compared to each other at cell-type level. Furthermore, our dataset shows an improved power for prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrate that obtaining single cell transcriptomes from human frozen tissues can provide insight missed by either human bulk RNA-seq or animal models.
This paper investigates the handling control and stability of an all-wheel-drive vehicle whose axles are individually equipped with an electric motor connected to an open differential. This could ...offer a potential configuration for the mass production of electric all-wheel-drive vehicles because of reduced cost and complexity. Although there is no torque vectoring or direct yaw moment control in this configuration, considerable handling improvement can be achieved by optimised front/rear torque distribution due to the longitudinal and lateral tire force coupling. In this study, a model predictive control design is presented with a coupled force prediction model for vehicle handling dynamics. The controller optimises the front/rear torque allocation to track the desired handling response and ensure vehicle stability. This study also compensates for actuator delay by incorporating the actuator dynamics into the control design. The performance of the proposed controller is evaluated through software simulations and experimental tests conducted on an electric all-wheel-drive Chevrolet Equinox.
A multi-actuation model predictive controller is designed to improve the stability of the performance vehicles during high-speed maneuvers. The actuators included in this study are four electric ...motors for the wheels and two active aerodynamic wings at the front and rear of the vehicle. The designed controller integrates optimal corner torque allocation with an optimal active aerodynamics control system. A model predictive control scheme is used to adjust the air wings angle of attack and optimize the corner torques. A high-level constraint adjustment module is added to the controller to observe nonlinear tire behavior and optimize aerodynamic wings activation as required. Nonlinear tire behavior and actuator dynamics are considered and included in the prediction model. The controller performance is verified in simulation with MATLAB/Simulink and CarSim.
Abstract
Compact objects (COs) can exist and evolve in an active galactic nuclei (AGN) disk, triggering a series of attractive CO-related multimessenger events around a supermassive black hole. To ...better understand the nature of an embedded CO and its surroundings and to investigate CO-related events more accurately, in this paper, we study the specific accretion process of a CO in an AGN disk and explore the role of outflow feedback. We show that the asymptotically isotropic outflow generated from the CO hyper-Eddington accretion would truncate the circum-CO disk and push out its surrounding gas, resulting in recurrent formation and refilling of an outflow cavity to intermittently stop the accretion. Applying this universal cyclic process to black holes (BHs) and neutron stars (NSs), we find that, even if it is above the Eddington rate, the mass rate accreted onto a BH is dramatically reduced compared with the initial gas captured rate and thus consumes little mass of the AGN disk; outflow feedback on an NS is generally similar, but possesses complexities on the existence of a stellar magnetic field and hard surface. We demonstrate that although outflow feedback itself may be unobservable, it remarkably alters the CO evolution via reducing its mass growth rate, and the AGN disk can survive from the otherwise drastic CO accretion overlooking outflow. In addition, we discuss the potential influence of an underdense cavity on CO-related events, which embodies the significant role of outflow feedback as well.
In this paper, an integrated vehicle and wheel stability control is developed and experimentally evaluated. The integrated structure provides a more accurate solution as the output of the stability ...controller is not altered by a separate unit, therefore its optimality is not compromised. Model predictive control is used to find the optimal control actions. The proposed control scheme can be applied to a wide variety of vehicle driveline and actuation configurations such as: four, front and rear wheel drive systems. Computer simulations as well as experiments are provided to show the effectiveness of the proposed control algorithm.
•An integrated stability and traction control system is developed using MPC.•The integrated design results in a superior performance in critical maneuvers.•The resulting controller is model based and quickly transferable to other vehicles.•The proposed controller can be adopted in various driveline/actuator configurations.
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