Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region

The objective of this research is to develop a non-destructive method for predicting cooked beef tenderness using optical scattering of light on fresh beef muscle tissue. A hyperspectral imaging system (λ = 496–1,036 nm) that consists of a CCD camera and an imaging spectrograph, was used to acquire beef steak images. The hyperspectral image consisted of 120 bands with spectral intervals of 4.54 nm. Sixty-one fresh beef steaks, including 44 strip loin and 17 tenderloin cuts, were collected. After imaging, the steaks were cooked and Warner-Bratzler shear (WBS) force values were collected as tenderness references. The optical scattering profiles were derived from the hyperspectral images and fitted to the modified Lorentzian function. Parameters, such as the peak height, full scattering width at half maximum (FWHM), and the slope around the FWHM were determined at each wavelength. Stepwise regression was used to identify 7 key wavelengths and parameters. The parameters were then used to predict the WBS scores. The model was able to predict WBS scores with an R = 0.67. Optical scattering implemented with hyperspectral imaging shows limited success for predicting current status of tenderness in beef steak.     

NMR studies of poly(2-hydroxy ethyl methacrylate-co-2-vinyl pyridine)

Copolymers of 2-hydroxy ethyl methacrylate-2-vinyl pyridine (H/V) of different composition were synthesized by free radical bulk polymerization using azobisisobutyronitrile (AIBN) as an initiator under nitrogen atmosphere. The copolymer compositions were calculated from ¹H NMR spectra. The reactivity ratios for H/V copolymers obtained from a linear Kelen-Tudos method (KT) and nonlinear error-in-variables method (EVM) are r_H = 0.50 ± 0.10, r_V = 1.04 ± 0.08 and r_H = 0.55, r_V = 1.06 respectively. The complete spectral assignment of methine, methylene, methyl, carbonyl, and aromatic carbon regions in term of compositional and configurational sequences of H/V copolymers were done with the help of ¹³C{¹H} NMR, distortionless enhancement by polarization transfer (DEPT), two-dimensional heteronuclear single quantum coherence (HSQC) along with total correlated spectroscopy (TOCSY). © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Breast feeding: Mo, As, Mn, Zn and Cu concentrations in milk of economically poor Indian tribal and urban women

The breast milk of 86 economically poor Indian women was analysed by neutron activation analyses for Mo, As, Mn, Zn, and Cu concentrations. The colostrum of 10 tribal women contained 0.27 microgram Cu/g, 2.1 micrograms Zn/g, 19.9 ng Mn/g, 0.73 ng As/g and 5.4 ng Mo/g, whereas 19 urban women had corresponding concentrations of 0.91 microgram Cu/g, 7.3 micrograms Zn/g, 15.3 ng Mn/g, 0.5 ng As/g and 15.3 ng Mo/g. A survey of mature milk between 1 and 6 months, 6 and 12 months and 1 and 2.5 years indicated decreasing concentrations of Zn and Mo, but increasing Mn concentrations as the post-partum period progressed. Malnourished infants received breast milk containing less Cu, Zn and Mn than those who were better nourished and of the same age group. The results, therefore, imply the necessity of supplementing breast feeds in the economically poorer groups.     

Dynamic proteome in enigmatic preeclampsia: an account of molecular mechanisms and biomarker discovery

The coevolution of genomics and proteomics has led to advancements in the field of diagnosis and molecular mechanisms of disease. Proteomics is now stepping into the field of obstetrics, where early diagnosis of pregnancy complication such as preeclampsia (PE) is imperative. PE is a multifactorial disease characterized by hypertension with proteinuria, which is a leading cause of maternal and neonatal morbidity and mortality occurring in 5-7% of pregnancies worldwide. This review discusses the probable molecular mechanisms that lead to PE and summarizes the proteomics research carried out in understanding the pathogenicity of PE, and for identifying the candidate biomarker for diagnosis of the disease.     

A novel dynamic pricing scheme for contributing peers in the VoD system

In this paper we have proposed a dynamic pricing scheme for the contributing peers in the Video on Demand (VoD) system. The scheme provides an effective mechanism to maximize the profit through the residual resources of the contributing peers. A utilization function is executed for each contributing peer to estimate the utility factor based on the parameters such as initial setup cost, holding cost, chaining cost and salvage cost. In this paper, we urge an effective dynamic pricing algorithm that efficiently utilizes a range of parameters with a varying degree of complexity. The key findings of the algorithm are (i) each contributing peers are benefitted by the monetary based on its resource contributions to the VoD system and (ii) a high degree of social optimum is established by proficiently aggregating the contributing peer’s resources with the overall resources of the VoD system. We validate our claim by simulating the proposed dynamic pricing scheme with other standard pricing schemes such as altruism, cost model and game theory perspective. The result of our dynamic pricing scheme shows the best utility factor than other standard pricing schemes.     

Performance Tuning and Reliability Analysis of the Electrostatically Configured Nanotube Tunnel FET with Impact of Interface Trap Charges

Silicon - This paper examines, an electrostatically configured Nano-Tube Tunnel Field-Effect Transistor (ED-NTTFET). During the fabrication process, different charges such as fixed charge, oxide...     

A Numerical Investigation of Heat Suppression in HEMT for Power Electronics Application

Silicon - In this paper, AlGaN/GaN High Electron Mobility Transistor (HEMT) with stacked passivation (Diamond/SiN) is proposed and investigated. The implementation of stacked passivation in HEMT...     

A Simple D 2-Sampling Based PTAS for k-Means and Other Clustering Problems

Given a set of points \(P \subset\mathbb{R}^{d}\) , the k-means clustering problem is to find a set of k centers \(C = \{ c_{1},\ldots,c_{k}\}, c_{i} \in\mathbb{R}^{d}\) , such that the objective function ∑ _x∈P e(x,C)², where e(x,C) denotes the Euclidean distance between x and the closest center in C, is minimized. This is one of the most prominent objective functions that has been studied with respect to clustering. D ²-sampling (Arthur and Vassilvitskii, Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA’07, pp. 1027–1035, SIAM, Philadelphia, 2007) is a simple non-uniform sampling technique for choosing points from a set of points. It works as follows: given a set of points \(P \subset\mathbb{R}^{d}\) , the first point is chosen uniformly at random from P. Subsequently, a point from P is chosen as the next sample with probability proportional to the square of the distance of this point to the nearest previously sampled point. D ²-sampling has been shown to have nice properties with respect to the k-means clustering problem. Arthur and Vassilvitskii (Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA’07, pp. 1027–1035, SIAM, Philadelphia, 2007) show that k points chosen as centers from P using D ²-sampling give an O(logk) approximation in expectation. Ailon et al. (NIPS, pp. 10–18, 2009) and Aggarwal et al. (Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, pp. 15–28, Springer, Berlin, 2009) extended results of Arthur and Vassilvitskii (Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA’07, pp. 1027–1035, SIAM, Philadelphia, 2007) to show that O(k) points chosen as centers using D ²-sampling give an O(1) approximation to the k-means objective function with high probability. In this paper, we further demonstrate the power of D ²-sampling by giving a simple randomized (1+?)-approximation algorithm that uses the D ²-sampling in its core.     

An efficient new method for the detection of QRS in electrocardiogram

A simple and efficient new method for QRS detection in Electrocardiogram (ECG) is proposed in this paper. Initially data is preprocessed using two stage median filter for removing baseline drift. The second stage enhances the peaks of ECG wave components by using sixth power of signal. The next stage identifies the QRS complex by taking a variable window size. The detection sensitivity (Se) and positive predictivity (+P) of CSE (Common Standards for Quantitative Electrocardiography) measurement database, MIT/BIH (Massachusetts Institute of Technology/Beth Israel Hospital) Arrhythmia database, European ST-T database and QT database are Se 99.51 & +P 99.69%, Se 99.21 & +P 99.34%, Se 99.53 & +P 99.72% and Se 99.87 & +P 99.95% respectively. These four standard databases used to perform QRS detection considered 368 cases, tested 1,006,168 beats and achieved overall average sensitivity 99.52% and positive predictivity 99.69%. The MIT/BIH Noise Stress Test Database also tested by proposed method.     

Formation of Nanocrystalline Calcia by the Decomposition of Calcite

Formation of nanocrystalline calcia from calcite has been studied in situ via transmission electron microscopy. The crystallographic transformation occurred via two mechanisms: the first is by distortion of the cleaved rhombohedron of calcite, formed by {104} planes in hexagonal coordinates, into a cube. This produced a microstructure of oriented, elongated nanocrystals of calcia with planar boundaries. In the second mechanism, the micrometer-sized parent calcite particles broke up into nano-sized grains as the decomposition began, leading to irregularly shaped, randomly oriented nanocrystals of calcia.