The experimental and numerical analysis of the ballistic performance of elastomer matrix Kevlar composites

In this paper, the behavior of high-velocity impact of Kevlar fabric and elastomer composites was investigated both experimentally and numerically. The experimental tests were performed by a gas gun device and hemispherical projectiles at different velocities, ranging from 122 m/s to 152 m/s for 2- and 4-layer samples. The penetration resistance of these composites during impact was determined using ABAQUS/Explicit. The present study's novelty lies in choosing the finite element model for Kevlar fabric and elastomer matrix in composites with nonlinear behavior to estimate the damage mechanism in the impact zone. For this purpose, the material model of the formable was used to define the damage criteria for Kevlar, and the material model of the VUMAT was used to consider the non-linear behavior and damage evolution of elastomer matrix with one of the damage criteria. Then, the dynamic behavior of the laminate was studied by a Split Hopkinson Pressure Bar. The effect of the number of layers, the shape of the projectile, the energy absorption and failure mechanisms were studied. The verification of this numerical model with experimental observations showed good agreement. The results reveal that elastomeric composites can cause to increase energy absorption and reduce the damaged area

Healthy Eating Index-2015 as a Predictor of Ulcerative Colitis Risk in a Case–Control Cohort

Objective: There is compelling clinical evidence implicating certain dietary components in the development and clinical course of progression in ulcerative colitis (UC). This study aimed to assess whether any association exists between ulcerative colitis and scores on a healthy eating index. Methods: In this case-control study patients with UC were recruited and assessed together with healthy controls. The participants completed a validated 168-item food frequency questionnaire, the results of which were subsequently used to generate individual healthy eating index (HEI-2015) scores. Results: Altogether 58 patients with UC and 123 healthy controls were recruited. After controlling for confounding factors, participants who were in the highest quartile of the HEI-2015 had a 66% lower odds ratio (OR) of UC than the lowest quartile (OR = 0.34, 95% confidence interval 0.12-0.96). Conclusion: HEI-2015 was associated with UC in this cohort. Further elucidation of the role of key dietary elements is now warranted

Experimental Evaluation of Fluid Connectivity in Two-Phase Flow in Porous Media During Drainage

This study aims to experimentally investigate the possibility of combining two extended continuum theories for two-phase flow. One of these theories considers interfacial area as a separate state variable, and the other explicitly discriminates between connected and disconnected phases. This combination enhances our potential to effectively model the apparent hysteresis, which generally dominates two-phase flow. Using optical microscopy, we perform microfluidic experiments in quasi-2D artificial porous media for various cyclic displacement processes and boundary conditions. Specifically for a number of sequential drainage processes, with detailed image (post-)processing, pore-scale parameters such as the interfacial area between the phases (wetting, non-wetting, and solid), and local capillary pressure, as well as macroscopic parameters like saturation, are estimated. We show that discriminating between connected and disconnected clusters and the concept of the interfacial area as a separate state variable can be an appropriate way of modeling hysteresis in a two-phase flow scheme. The drainage datasets of capillary pressure, saturation, and specific interfacial area, are plotted as a surface, given by f (Pc, sw, awn) = 0. These surfaces accommodate all data points within a reasonable experimental error, irrespective of the boundary conditions, as long as the corresponding liquid is connected to its inlet. However, this concept also shows signs of reduced efficiency as a modeling approach in datasets gathered through combining experiments with higher volumetric fluxes. We attribute this observation to the effect of the porous medium geometry on the phase distribution. This yields further elaboration, in which this speculation is thoroughly studied and analyzed

Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease

Previous studies have demonstrated altered brain activity in Alzheimer\u27s disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18 F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from F-18 FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid beta 1-42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD