Study on the Influence of Road Geometry on Vehicle Lateral Instability

According to the accident analysis of vehicles in the curve, the skidding, rollover, and lateral drift of vehicles are determined as means to evaluate the lateral stability of vehicles. -e utility truck of rear-wheel drive (RWD) is researched, which is high accident rate. Human-vehicle-road simulation models are established by CarSim. -rough the orthogonal experiment method, the effects of different road geometries, speed, and interaction factors between road geometries on vehicle lateral stability are studied. In this paper, skidding risk of the vehicle is characterized by the Side-way Force Coefficient (SFC). Rollover risk of the vehicle is characterized by lateral acceleration and the load transfer ratio. Lateral drift risk of the vehicle is characterized by the sideslip angle of wheels. -e results of orthogonal analysis reveal that the maximum tire-road friction coefficient and speed are highly significant in skidding of the vehicle. -e effects of the combination of horizontal alignment and superelevation on vehicle skidding are important. -e effects of horizontal alignment and speed on vehicle rollover risk are highly significant. -e effects of superelevation on vehicle rollover risk are significant. -e effects of the interaction of horizontal alignment and superelevation are also important on vehicles’ rollover risk. -e speed and the maximum tire-road friction coefficient have highly significant effect on the vehicle’s lateral drift. -e superelevation has a significant effect on the vehicle’s lateral drift. -e effects of the interaction of horizontal alignment and superelevation and longitudinal slope are also important on the lateral drift of the vehicle

The Influence of Road Geometry on Vehicle Rollover and Skidding

This paper analyzes the influence of single and combined unfavorable road geometry on rollover and skidding risks of D-class mid-sized sport utility vehicles (SUVs) with front-wheel drive for roads with design speeds at 80 km/h. A closed-loop simulation model of human-vehicle-road interactions is established to examine the systematic influence of road geometry on vehicle rollover and skidding. The effects of different road geometry on rollover and skidding on SUVs are studied for pavement surface with good and poor friction when vehicles are in the action of steady state cornering. The rollover and skidding risks of the most unfavorable road segments are assessed. The critical wheel is defined by the threshold of skidding during curve negotiation. The results found that SUVs are not easy to rollover on the most unfavorable roads, regardless of good or poor friction of pavement surface. The safety margin of rollover is greater than that of skidding. The safety margin of skidding is minimal on poor friction roads. Therefore, for the sake of driving safety, it is not recommended to design the roads with these unfavorable road geometry combinations

Robust H

The paper mainly investigates the H∞ fuzzy control problem for a class of nonlinear discrete-time stochastic systems with Markovian jump and parametric uncertainties. The class of systems is modeled by a state space Takagi-Sugeno (T-S) fuzzy model that has linear nominal parts and norm-bounded parameter uncertainties in the state and output equations. An H∞ control design method is developed by using the Lyapunov function. The decoupling technique makes the Lyapunov matrices and the system matrices separated, which makes the control design feasible. Then, some strict linear matrix inequalities are derived on robust H∞ norm conditions in which both robust stability and H∞ performance are required to be achieved. Finally, a computer-simulated truck-trailer example is given to verify the feasibility and effectiveness of the proposed design method

Study on Spinnability of PP/PU Blends and Preparation of PP/PU Bi-component Melt Blown Nonwovens

Melt blown polymer blends offers a good way to combine two polymers in the same fiber generating nonwovens with new and novel properties. In this study, polypropylene (PP) and polyurethane (PU) were blended to prepare PP/PU bicomponent melt blown nonwovens. The spinnability of PP/PU composites was investigated and PP/PU bi-component nonwovens with compositions of 95/5, 90/10, 80/20 and 70/30 were prepared by using the melt blowing technique. The melt blown fibers exhibited a ‘sea-island’ structure with PP as the continuous phase and PU as the dispersed phase. When the content of PU in the blend was above 40 %, PP/PU melt blown nonwovens could not be produced due to fiber breaking. For PP/PU (90/10) nonwovens, it was found that the average fiber diameter decreased with increasing die to collector (DCD) and elevated hot air pressure

A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children.

A quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to ∼95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations.IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification

Classification of rheumatoid arthritis status with candidate gene and genome-wide single-nucleotide polymorphisms using random forests

Abstract Using the North American Rheumatoid Arthritis Consortium (NARAC) candidate gene and genome-wide single-nucleotide polymorphism (SNP) data sets, we applied regression methods and tree-based random forests to identify genetic associations with rheumatoid arthritis (RA) and to predict RA disease status. Several genes were consistently identified as weakly associated with RA without a significant interaction or combinatorial effect with other candidate genes. Using random forests, the tested candidate gene SNPs were not sufficient to predict RA patients and normal subjects with high accuracy. However, using the top 500 SNPs, ranked by the importance score, from the genome-wide linkage panel of 5742 SNPs, we were able to accurately predict RA patients and normal subjects with sensitivity of approximately 90% and specificity of approximately 80%, which was confirmed by five-fold cross-validation. However, in a complete training-testing framework, replication of genetic predictors was less satisfactory; thus, further evaluation of existing methodology and development of new methods are warranted.http://deepblue.lib.umich.edu/bitstream/2027.42/117372/1/12919_2007_Article_2426.pd

High-Resolution 3D Heart Models of Cardiomyocyte Subpopulations in Cleared Murine Heart

Biological tissues are naturally three-dimensional (3D) opaque structures, which poses a major challenge for the deep imaging of spatial distribution and localization of specific cell types in organs in biomedical research. Here we present a 3D heart imaging reconstruction approach by combining an improved heart tissue-clearing technique with high-resolution light-sheet fluorescence microscopy (LSFM). We have conducted a three-dimensional and multi-scale volumetric imaging of the ultra-thin planes of murine hearts for up to 2,000 images per heart in x-, y-, and z three directions. High-resolution 3D volume heart models were constructed in real-time by the Zeiss Zen program. By using such an approach, we investigated detailed three-dimensional spatial distributions of two specific cardiomyocyte populations including HCN4 expressing pacemaker cells and Pnmt(+) cell-derived cardiomyocytes by using reporter mouse lines Hcn4(DreER/tdTomato) and Pnmt(Cre/ChR2−tdTomato). HCN4 is distributed throughout right atrial nodal regions (i.e., sinoatrial and atrioventricular nodes) and the superior-inferior vena cava axis, while Pnmt(+) cell-derived cardiomyocytes show distinct ventral, left heart, and dorsal side distribution pattern. Our further electrophysiological analysis indicates that Pnmt + cell-derived cardiomyocytes rich left ventricular (LV) base is more susceptible to ventricular arrhythmia under adrenergic stress than left ventricular apex or right ventricle regions. Thus, our 3D heart imaging reconstruction approach provides a new solution for studying the geometrical, topological, and physiological characteristics of specific cell types in organs