Operational criteria for battlefield vehicles

textModern military ground vehicles are no longer able to respond effectively to the rapidly changing mission requirements of modern military conflicts. Military vehicle architectures, which utilize passive suspension components and traditional drivetrain/steering systems, do not provide the operational flexibility to meet the demands of the operator. Advances in intelligent actuation technology allow for the development of a new vehicle architecture - the Intelligent Corner Vehicle (ICV). The ICV utilizes intelligent actuator technology to actively control the four degrees of freedom of each wheel of the vehicle - drive, camber, steering, and suspension. The utilization of intelligent actuation requires the characterization of the motions and behavior of the tire and the vehicle chassis in order to effectively apply the tire to the road surface - the development of vehicle performance criteria. A brief review of the state of wheeled military systems is presented. Many modern military vehicles were designed to improve protection at the expense of mobility - a process that has had negative effects on vehicle capability. An overview of the pneumatic tire used for wheeled vehicles is presented, highlighting the nonlinearities of tire behavior. The complexity of tire force generation drives the need for the application of intelligent actuation. Traditional actuation of wheel motion is presented along with a variety of current efforts to apply intelligent actuation to individual degrees of freedom of the tire. These efforts can be shown to improve vehicle performance, but intelligent actuation must be applied to all aspects of tire motion, requiring the use of the ICV architecture and the generation of performance criteria by which the complex motion of the vehicle may be evaluated. The Robotics Research Group has a history of developing and evaluating performance criteria for complex dynamic systems. and review of performance criteria developed for serial chain robotics is presented. These criteria address task independent actuator motion in addition to actuator ranges and limits, and their application to the ICV is discussed. A brief overview of several important concepts of classical vehicle dynamics are presented. The application of criteria derived from these concepts to the ICV architecture is discussed. This report presents the complexities of tire behavior and vehicle motion, the need for alternative architectures (the ICV), and a variety of performance criteria required to evaluate vehicle motion in real time. Criteria that are presented are summarized along with their definition and physical meaning. Future work for the development of the ICV involves the generation of a vehicle model for evaluating the application and range values of the presented criteria.Mechanical Engineerin

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management