A self-powering system based on tire deformation during driving

Tire intelligence is vital in the improvement of the safety of vehicles because the tire supports the car body and is the contact point between the vehicle and the road. To create an intelligent tire, sensors must be installed to measure the behavior of the tire. However, it is difficult to apply a wired sensor system on the wheel of the tire. Hence, it is necessary to implement a self-powering, wireless system (a type of energy harvesting system) that can be mounted inside the tire. The purpose of this study is to convert the strain energy caused by deformation of the tire while driving into useful electrical energy to supply the sensor system. A flexible piezofiber is utilized for the energy conversion. The variation in strain, due to changes in speed, load, and the internal pressure of the tire, was measured along two axial directions to evaluate the amount of available strain energy. The amount of strain changed from 0.15% to 0.8%. To predict the amount of available energy from a tire, we perform an analysis of the relationship between the strain and the voltage. In addition, experiments for impedance matching between piezofiber and related circuits were conducted to optimize the external loads for transferring energy efficiently. Based on the procedure mentioned above, at least 0.58 mJ of electrical energy can be generated by using the laterally oriented strain (1500 to 2500 micro strain). The result of this study is expected to enhance the potential realization of self-generating wireless sensor systems for so-called ??intelligent?? tires.     

Study of an optimized gas strut layout to improve opening and closing quality

The most important factor in gas strut design is determining an optimized layout. If the layout is not optimized, vehicle operators will have a suboptimal experience when opening and closing the tailgate. A poor layout of the gas struts causes operators to work excessively when they open/close the tailgate, and vehicle owners will incur additional expenses due to deterioration in the body quality of the vehicle. Thus, an optimized gas strut layout is very important, even if it does not seem interesting. This paper describes the tailgate operation process and focuses on determining an optimized gas strut layout for opening/closing the tailgate easily.     

High-strain-rate fracture of adhesively bonded composite joints in DCB and TDCB specimens

Double-cantilever beam (DCB) and tapered double-cantilever beam (TDCB) specimens are the test configurations most commonly used to measure the fracture toughness of composites and adhesive joints. Strain rates of 1 to 18.47 m/s were applied to the test specimens via high-speed hydraulic test equipment. Because the fracture occurs through the adhesively bonded joints and the cracks grow rapidly, the crack length and beam displacement were recorded by a high-speed camera. An energy range from 0 to 10 J was often observed in the high-strain-rate fracture experiments for nonlinear plastic behavior of the dynamically loaded adhesively bonded DCB and TDCB specimens. The range of energy release rates (fracture energy) for TDCB specimen was 2 to 3 times higher than that of a DCB specimen for all high strain rates. The fracture energy of automotive adhesive joints can be estimated using the experimental results in this study for the fracture toughness (G_IC) under high rates of loading. The crack grows as the applied fracture energy exceeds the value of the critical energy release rate (G_IC) at the crack tip. The energy release rate was calculated using the fracture mechanics formula. The key fracture mechanics parameter, the fracture energy GIC, was ascertained as a function of the test rate and can be used to assess and model the overall joint performance.     

Impact of phytoplankton community size on a linked global ocean optical and ecosystem model

We isolated the effect phytoplankton cell size has on varying remote sensing reflectance spectra (R_rs(λ)) in the presence of optically active constituents by using optical and radiative transfer models linked in an offline diagnostic calculation to a global biogeochemical/ecosystem/circulation model with explicit phytoplankton size classes. Two case studies were carried out, each with several scenarios to isolate the effects of chlorophyll concentration, phytoplankton cell size, and size-varying phytoplankton absorption on R_rs(λ). The goal of the study was to determine the relative contribution of phytoplankton cell size and chlorophyll to overall R_rs(λ) and to understand where a standard band ratio algorithm (OC4) may under/overestimate chlorophyll due to R_rs(λ) being significantly affected by phytoplankton size. Phytoplankton cell size was found to contribute secondarily to R_rs(λ) variability and to amplify or dampen the seasonal cycle in R_rs(λ), driven by chlorophyll. Size and chlorophyll were found to change in phase at low to mid-latitudes, but were anti-correlated or poorly correlated at high latitudes. Phytoplankton size effects increased model calculated R_rs(443) in the subtropical ocean during local spring through early fall months in both hemispheres and decreased R_rs(443) in the Northern Hemisphere high latitude regions during local summer to fall months. This study attempts to tease apart when/where variability about the OC4 relationship may be associated with cell size variability. The OC4 algorithm may underestimate [Chl] when the fraction of microplankton is elevated, which occurs in the model simulations during local spring/summer months at high latitudes in both hemispheres.     

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RAPID MOLECULAR DETECTION OF METHICILLIN-RESISTANT S. AUREUS IN THE INTENSIVE CARE UNIT

Staphylococcus aureus is found in the nose andon the skin of a variety of healthy individuals,andis an opportunistpathogen in patients with loweredhost resistance.The isoxazolylpenicillin (e.g.me-thicillin,cloxacillin,flucloxacillin) have been themainstay of treatment for infection over2 5years.But emergence of antibiotic resistance(MRSA) is aproblem in hospitals due to transmission of epi-demic MRSA strains with antibiotic resistance.Ac-quisition of MRSA continues to be of major con-cern…     

Effect of ABCA1-V771M polymorphism on plasma lipid levels and its relationship with coronary atherosclerotic heart disease

Objective To explore the risk association of ABCA1-V771M polymorphism with coronary heart disease (CHD) in Hart nationality in Northwest of China. Methods With case-control study, ABCA1-V771M polymorphism was detected in 204 unrelated Hart nationality people in Northwest of China, and all the subjects by coronary angiography were grouped into 106 cases and 98 controls. The genotypes and alleles frequency distribution of ABCA1-V771M polymorphisms were analyzed by PCR-RFLP analysis, and the clinical statistics of serum lipids were compared and its effects of ABCA1-V771M polymorphism on the plasma lipid levels and coronary atherosclerotic heart disease were analyzed. Results The genotypic frequencies of ABCA1-V771M polymorphism matched well under Hardy-Weinberg equilibrium (P>0.05), V and M allelic frequencies were 33.3% and 66.7%. In comparison with VV VM genotype carriers, MM genotypes carriers had much lower plasma levels of HDL-C (P<0. 001) and much higher plasma levels of TG (P<0. 05). M allelic frequency in CHD group was significantly higher than V allelic frequency (P<0. 05). M allele was related with more severity of atherosclerosis in the coronary artery than V allele (P<0.05). However, there was no obvious difference in the incidence of AMI among carriers with three genotypes of ABCA1-V771M polymorphism (P>0.05). Conclusion ABCA1-V771M polymorphism was not only associated with the plasma levels of HDL-C and TG, but also related to the susceptibility and severity of coronary atheroselerotic heart disease. Moreover, M771 allele appeared to be atherogenie among Han population in Northwest of China.     

Commodity flow estimation for a metropolitan scale freight modeling system: supplier selection considering distribution channel using an error component logit mixture model

Freight forecasting models have been significantly improved in recent years, especially in the field of goods vehicle behavior modeling. On the other hand, the improvements to commodity flow modeling, which provide inputs for goods vehicle simulations, were limited. Contributing to this component in urban freight modeling systems, we propose an error component logit mixture model for matching a receiver to a supplier that considers two-layers in supplier selection: distribution channels and specific suppliers. The distribution channel is an important element in freight modeling, as the type of distribution channel is relevant to various aspects of shipments and vehicle trips. The model is estimated using the data from the Tokyo Metropolitan Freight Survey. We demonstrate how typical establishment survey data (i.e. establishment and outbound shipment records) can be used to develop the model. The model captures the correlation structure of potential suppliers defined by business function and provides insights on the differences in the supplier choice by distribution channel. The reproducibility tests confirm the validity of the proposed approach, which is currently integrated into a metropolitan-scale agent-based freight modeling system, for practical use.