An overview of smart packaging technologies for monitoring safety and quality of meat and meat products

The food packaging sector has experienced much development since its inception. In the past few decades, innovations in packaging sector have led to the development of smart packaging (SP) systems that carve a niche in a highly competitive food industry. SP systems have great potential for improving the shelf‐life, and safety of food products apart from their basic roles of protecting the products against unwanted biological, chemical, and physical damage and keeping them clean. Indicators and sensors, SP components, are used for real‐time monitoring of meat quality and subsequently inform the retailers and consumers about the freshness, microbiological, temperature, and shelf life status of the products. Barcodes and radio‐frequency identification tags are employed in meat packaging for real‐time information about the authenticity, and traceability of the products in the supply chain. Recently, innovations in SP technologies resulted in fast, sensitive, and effective detection, sensing, and record keeping of freshness, microbiological, and shelf life status of meat and meat products. The SP system shows promise for extensive utilization in the meat industry in response to the consumer appreciation for safe, and quality meat products, as well as their waste reduction notions. This paper gives an updated overview of ongoing scientific research, and recent technological advances that offer the perspectives of developing smart meat packaging systems that are capable of monitoring the physical, microbial, and chemical changes of the package contents from producer to the point of sale and even beyond, and remediating potential adverse reactions.     

Deep features-based speech emotion recognition for smart affective services

Emotion recognition from speech signals is an interesting research with several applications like smart healthcare, autonomous voice response systems, assessing situational seriousness by caller affective state analysis in emergency centers, and other smart affective services. In this paper, we present a study of speech emotion recognition based on the features extracted from spectrograms using a deep convolutional neural network (CNN) with rectangular kernels. Typically, CNNs have square shaped kernels and pooling operators at various layers, which are suited for 2D image data. However, in case of spectrograms, the information is encoded in a slightly different manner. Time is represented along the x-axis and y-axis shows frequency of the speech signal, whereas, the amplitude is indicated by the intensity value in the spectrogram at a particular position. To analyze speech through spectrograms, we propose rectangular kernels of varying shapes and sizes, along with max pooling in rectangular neighborhoods, to extract discriminative features. The proposed scheme effectively learns discriminative features from speech spectrograms and performs better than many state-of-the-art techniques when evaluated its performance on Emo-DB and Korean speech dataset.

     

Stochastic multiscale fracture analysis of three-dimensional functionally graded composites

A new moment-modified polynomial dimensional decomposition (PDD) method is presented for stochastic multiscale fracture analysis of three-dimensional, particle-matrix, functionally graded materials (FGMs) subject to arbitrary boundary conditions. The method involves Fourier-polynomial expansions of component functions by orthonormal polynomial bases, an additive control variate in conjunction with Monte Carlo simulation for calculating the expansion coefficients, and a moment-modified random output to account for the effects of particle locations and geometry. A numerical verification conducted on a two-dimensional FGM reveals that the new method, notably the univariate PDD method, produces the same crude Monte Carlo results with a five-fold reduction in the computational effort. The numerical results from a three-dimensional, edge-cracked, FGM specimen under a mixed-mode deformation demonstrate that the statistical moments or probability distributions of crack-driving forces and the conditional probability of fracture initiation can be efficiently generated by the univariate PDD method. There exist significant variations in the probabilistic characteristics of the stress-intensity factors and fracture-initiation probability along the crack front. Furthermore, the results are insensitive to the subdomain size from concurrent multiscale analysis, which, if selected judiciously, leads to computationally efficient estimates of the probabilistic solutions.     

Mesoscale finite element prediction of concrete failure

The present paper studies the failure of concrete from the mesoscopic point of view. Biphasic cubic concrete samples containing spherical aggregates embedded in a homogenized mortar have been simulated using standard finite element method. Linear elasticity and damage-plasticity hypotheses are considered for the aggregates and mortar, respectively. Various triaxial loading conditions are assumed for each sample to generate adequate discrete failure points within the stress space. In the next step, the approximated failure surfaces of specimens are constructed using the Delaunay triangulation technique. The effects of mesostructural features such as aggregate grading curve, aggregate volumetric share, and more importantly the controlling parameters of mortar’s damage-plasticity constitutive model have been investigated. Finally, the failure modes of some selected samples have been reported and discussed.     

Coherent control of symmetric and asymmetric diffraction grating via relative phase

ABSTRACT

We present a theoretical model to realize the symmetric and asymmetric diffraction grating in a four-level atomic medium. The proposed atomic medium follows a double lambda configuration where four fields interact with it. We get control over symmetric and asymmetric behavior of the diffraction grating by manipulating the relative phase of the fields. Interestingly, the symmetric and asymmetric diffraction grating become prominent when the vortex beam is used instead of the plane wave. Enhanced first, second, and third-order diffraction gratings are achieved via the vortex beam. Further, we find control over asymmetric diffraction gratings by the relative phase of the fields. Coherent control of asymmetric diffraction grating in negative and positive diffracted angles is also achieved via the relative phase.     

Towards the performance evaluation of 4th generation wireless communication standards: LTE versus Mobile WiMAX

Advances in wireless communication protocols and networking toward support of the next generation of mobile and radio broadband technologies have contributed to a strong competition among various telecommunication standards in particular Long Term Evolution (LTE) and Mobile Worldwide Interoperability for Microwave Access (WiMAX). In this paper, we provide an in‐depth comparison analysis of LTE and Mobile WiMAX at the physical (PHY) layer by studying the most similar PHY configuration scenarios for these two technologies. Our study includes a throughput analysis of downlink (DL) and uplink (UL) transmissions in time division duplex with the least overhead possible and different antenna schemes as well as modulation and code rates. This study also performs an overhead analysis in both protocols to provide a more in‐depth understanding of the PHY layer capacity in various PHY layer configurations. Our simulation results generally show higher performance for LTE in both DL and UL transmission with 7 Mbps in DL and 5 Mbps in UL, when using one antenna port. However, by increasing the number of antennas for multiple‐input/multiple‐output configurations, the results illustrate a reduction in the performance of LTE compared to Mobile WiMAX. This arises from the increase in reference signal overhead in LTE from 4.7% in single‐input/single‐output (SISO) to 14.28% in 4 × 4 multiple‐input/multiple‐output (MIMO). Copyright © 2013 John Wiley & Sons, Ltd.     

Theranostic Interpolation of Genomic Instability in Breast Cancer

Breast cancer is a diverse disease caused by mutations in multiple genes accompanying epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance results in genomic instability. Theranostic has the potential to foretell and estimate therapy response, contributing a valuable opportunity to modify the ongoing treatments and has developed new treatment strategies in a personalized manner. “Omics” technologies play a key role while studying genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics, metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many effective results. Several diverse tools are used to investigate genomic instability and underlying mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the implications of computational biology regarding mutational and pathway analyses, identification of prognostic markers, and the development of strategies for precision medicine. We also review different technologies required for the investigation of genomic instability in breast cancer cells, including recent therapeutic and preventive advances in breast cancer.     

Isolation,purification, and antioxidant activities of polysaccharides from Ziziphus Jujuba cv. Muzao

In the present study, crude polysaccharides from Ziziphus Jujuba cv. Muzao were isolated and purified using DEAE cellulose-52 and Sephadex G-100 size-exclusion chromatography; four fractions were collected, namely GZMP-1, GZMP-2, GZMP-3, and GZMP-4. The molecular weights of these four fractions were measured to be 111.2, 95.1, 84.2, and 571.4 kDa, respectively, using high-performance gel permeation chromatography. Gas chromatography analysis of the monosaccharide composition confirmed that GZMP-1 was composed of rhamnose, arabinose, glucose, and galactose. Rhamnose, arabinose, and galactose were the main components present in GZMP-2 and GZMP-3, whereas GZMP-4 was composed of only rhamnose and arabinose. Scanning electron microscopy showed relatively smooth surfaces for GZMP-1 and GZMP-4, whereas GZMP-2 and GZMP-3 had more folds on their surfaces. Fourier transform infrared spectroscopy analyses indicated that GZMP-1 and ZMP mainly had α-type glycosidic linkages. The in vitro antioxidant activities of the polysaccharides revealed that jujube polysaccharides exhibit remarkable antioxidant activity, and can scavenge DPPH radical and OH radical in a concentration-dependent manner. The results of this work suggest that polysaccharides from Z. Jujuba cv. Muzao have potential to be used as functional food and in the development of natural antioxidant drug carriers.     

Monte Carlo study of ion-induced secondary electron emission from SiO2

Here we describe a recently developed direct Monte Carlo program to study kinetic electron emission from SiO₂ target. The program includes excitation of the target electrons (by projectile ions, recoiling target atoms and fast primary electrons), subsequent transport and escape of these electrons from the target surface. The program can be used to calculate the electron yields, distribution of electron excitation points in the target and other physical parameters of the emitted electrons. In order to demonstrate the capabilities of this program, we report a study on the kinetic electron emission from SiO₂ induced by fast (1-10 keV) rare gas ions. The calculated kinetic electron yield for various ion energies and masses is in good agreement with the predictions of most frequently applied theoretical model. In addition, the effects of projectile energy, mass and impact angle on the depth distribution of electron excitation points and average escape depth of the outgoing electrons were investigated. It is important to mention that the existing experimental techniques are not capable to measure these parameters.