Stress analysis of the adhesive resin layer in a reinforced pin-loaded joint used in glass structures

A reinforced pin-loaded joint used to assemble elements in a tempered glass structure consists of a steel bolt and a steel ring glued to a glass plate through an adhesive resin layer. The stiffness of a typical resin material is generally much lower than the stiffness of steel or glass. This fact leads us to make the assumption that the stress field in the adhesive resin layer is essentially due to the relative rigid displacements of the steel ring with respect to the glass plate. On the basis of this assumption, an analytical solution is obtained for the stresses in the adhesive resin layer. This solution is compared with and validated by the numerical results obtained by the finite element method.     

Inulin-based emulsion-filled gel as a fat replacer in prebiotic- and PUFA-enriched dry fermented sausages

In order to produce fermented sausages with prebiotic fibre and improved fatty acid composition, 16% of pork back fat was replaced with inulin gelled suspension (I) and inulin linseed oil gelled emulsion (IO). Physico-chemical analysis, fatty acid profiles, lipid oxidation, microbiological, textural, colour and sensory analysis were carried out. The fat content was lower in I (31.38%) and IO (35.36%) modified sausages compared to control (44.37%) (P < 0.05). IO sausages had lower SFA and MUFA and higher PUFA content with an improved n-6/n-3 ratio (2.23) (P < 0.05) and α-linolenic acid increment (5.74 g per 100 g). Reformulation led to decrease in springiness, chewiness and hardness and increase in adhesiveness of the sausages. Modified sausages had lower L* and higher a* values, while b* values of I sausages did not differ compared to control sausages. Modified sausages were acceptable regarding all sensory attributes. Lipid oxidation parameters showed higher susceptibility to oxidation and lipolysis in IO sausages.     

光纤衰减特性检测系统分析

本文论述了光纤光谱衰减特性检测系统的原理。用数学分析的方法得出光纤光谱衰减特性参数β(λ)的表达式,给出光谱衰减曲线β(λ)的拟合方法、数学模型及软件流程。     

Symbolic analysis and design of control systems using Mathematica

Contemporary computer tools can generate a tremendous amount of numerical data so the user might easily lose insight into the phenomenon being investigated. Those who use powerful computer algebra systems must thoroughly understand the assumptions that underlie the software. In this paper, the role and importance of symbolic computation in control engineering and signal processing is exemplified. Real-life application examples are presented in which systems are symbolically solved and simulated with Mathematica. We introduce an original approach to algorithm development, system design and symbolic processing that successfully overcomes some problems encountered in the traditional approach. Benefits of symbolic methods and the role of computer algebra systems are highlighted from the viewpoint of both academia and industry.     

CHARACTERISTICS OF MICROCUTTING FORCE VARIATION IN ULTRAPRECISION DIAMOND TURNING

An investigation of the characteristics of microcutting forces in diamond turning of crystalline materials is presented. The characteristics of the cutting forces were extracted and analyzed using statistical and spectrum analysis methods. A series of cutting experiments were done on a copper alloy and copper single crystals with different crystallographic orientations. Experimental results indicate that there exists a dominant frequency component and a periodicity of fluctuation of the cutting forces per workpiece revolution in the diamond turning of a single crystal material. The periodicity is closely related to the crystallographic orientation of the material being cut. As the depth of cut increases, the influence of crystallographic orientation of the single-crystal materials on microcutting forces is found to be more pronounced. Moreover, the cutting force ratio between the mean thrust force and the mean cutting force is found to vary with the depth of cut, and a large ratio was observed at a small depth of cut. These findings help to explain quantitatively the periodic fluctuations of microcutting forces (and hence the materials-induced vibration) in ultraprecision diamond turning, which are not encountered in conventional machining.     

Multi-Slice DCE-MRI Data Using P760 Distinguishes Between Metastatic and Non-Metastatic Rodent Prostate Tumors

An intermediate molecular weight contrast agent P760 was used to investigate the ability of multi-slice dynamic contrast-enhanced MRI (DCE-MRI) to distinguish metastatic from non-metastatic rodent prostate tumors. Non-metastatic AT2.1 and metastatic AT3.1 prostate tumors originally derived from the Dunning prostate cancer model were implanted on the hind leg of Copenhagen rats. Multi-sliced DCE-MRI data were acquired on a SIGNA 1.5 T scanner and analyzed using a recently developed empirical mathematical model. The P760 multi-slice DCE-MRI data in combination with the empirical mathematical model successfully distinguished between metastatic and non-metastatic rodent prostate tumors. Specifically, fitting the data with the empirical model showed that metastatic tumors had significantly faster contrast media uptake (p<0.001) and slower washout rates (p<0.01) than non-metastatic tumors     

Reexamination of slow relaxation of polymer chains in sol-gel transition

Using [2+2] photocycloaddition of coumarin groups attached to the PMMA chain backbone, we can gradually transfer a semidilute copolymer solution to a uniform speckle-free gel. We reexamined the effects of concentration, crosslinking density, solvent quality on the controversial scaling exponent (α_s) between the linewidth (Γ_s) of the slow mode and the scattering vector (q) during the sol-gel transition. Our results suggest that the slow mode is attributed to large thermally agitated density fluctuation and revealed that the variation of α_s is due to the relative length of 1/q to the correlation length (ξ) of the density fluctuation; namely, if ξ>1/q, α_s→3, while when ξ<1/q, α_s→2.     

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.