New food safety challenges of viral contamination from a global perspective: Conventional,emerging, and novel methods of viral control

Food- and waterborne viruses, such as human norovirus, hepatitis A virus, hepatitis E virus, rotaviruses, astroviruses, adenoviruses, and enteroviruses, are major contributors to all foodborne illnesses. Their small size, structure, and ability to clump and attach to inanimate surfaces make viruses challenging to reduce or eliminate, especially in the presence of inorganic or organic soils. Besides traditional wet and dry methods of disinfection using chemicals and heat, emerging physical nonthermal decontamination techniques (irradiation, ultraviolet, pulsed light, high hydrostatic pressure, cold atmospheric plasma, and pulsed electric field), novel virucidal surfaces, and bioactive compounds are examined for their potential to inactivate viruses on the surfaces of foods or food contact surfaces (tools, equipment, hands, etc.). Every disinfection technique is discussed based on its efficiency against viruses, specific advantages and disadvantages, and limitations. Structure, genomic organization, and molecular biology of different virus strains are reviewed, as they are key in determining these techniques effectiveness in controlling all or specific foodborne viruses. Selecting suitable viral decontamination techniques requires that their antiviral mechanism of action and ability to reduce virus infectivity must be taken into consideration. Furthermore, details about critical treatments parameters essential to control foodborne viruses in a food production environment are discussed, as they are also determinative in defining best disinfection and hygiene practices preventing viral infection after consuming a food product.     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

Analytical study of surface wave multiple refraction in boundary of a scalar impedance surface with a tensor impedance surface

In this paper, the multiple refraction phenomenon is investigated on the boundary of a scalar impedance surface (SIS) and a tensor impedance surface (TIS). When a surface wave (SW) propagates on the SIS and radiates to the boundary of the TIS, the propagation direction of it is changed and the refraction phenomenon is accrued. The method that is proposed in this paper can predict the multiple refraction for the SW. Moreover, another analytical method is introduced for designing the proposed structure which the double refraction (DR) occurs at arbitrary angles on it. Using it, a sample of the structure is designed by printed circuits in 15.2GHz and the results are verified by the full‐wave simulation and measurement. The results are shown that in the structure, DR is occurred in 2° and 22° as predicted. The proposed method can provide many applications such as design of SW power dividers based on the TISs, impedance surface based waveguides, holographic antennas, and feeding of array antennas.     

Simulation and energy optimization of the stabilizer tower of a pyrolysis gasoline hydrogenation unit

Energy optimization of second distillation tower of a pyrolysis gasoline hydrogenation unit has been studied by the thermal cycle of vapor recompression method. The mentioned cycle is connected to the second distillation tower of the stabilizer of pyrolysis gasoline, and the results are found promising. The composite pinch curve for both the current and the optimized methods are shown. Moreover, an increase in the heat transfer rate in heat exchanger E-1014 causes energy recovery in reboiler. According to simulation results, by vapor recompression to 1970 kPa and using this heat source for thermal integration, condenser and reboiler’s energies are decreased by 56.93 and 30.4 percentage, respectively.     

A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.     

The application of internet of things in healthcare: a systematic literature review and classification

Universal Access in the Information Society - The Internet of Things (IoT) is an ecosystem that integrates physical objects, software and hardware to interact with each other. Aging of population,...     

A local view on the Hudetz correction of the Yager entropy of dynamical systems

In this paper, we define a local version of Hudetz correction for the Yager entropy of dynamical systems. It is proved that the introduced function is indeed a local entropy map for the Hudetz correction of the Yager entropy, in the sense that, the Hudetz correction of the Yager entropy of a continuous map on a compact metric space is attained by integrating the introduced local entropy.     

Green synthesis of zinc oxide nanoparticles using Amygdalus scoparia Spach stem bark extract and their applications as an alternative antimicrobial,anticancer, and anti-diabetic agent

For the first time in this study, Zinc oxide nanoparticles were biosynthesized by the eco-friendly and cost-effective procedure using Amygdalus scoparia stem bark extract then used as antibacterial, antifungal, anticancer, and anti-diabetic agents. The characterization techniques confirmed the biosynthesis, crystalline nature, structure, size, elemental composition of ZnO NPs and bioactive compounds that exist in A. scoparia extract accounting for Zn²⁺ ion reduction, capping and stabilization of ZnO NPs. The ZnO NPs displayed remarkable inhibitory activity against E. coli, E. aerigenes, S. aureus, P. oryzae, F. thapsinum, and F. semitectum compared to antibiotic standards. The ZnO NPs showed significant inhibitory effects on cancer cell lines, while it had no toxic effect on Vero normal cell line. The ZnO NPs (30 mg/kg)-treated diabetic rats showed significantly higher levels of insulin and lower AST, ALT and blood glucose compared with the STZ induced diabetic group and other treated groups (P < 0.05). The ZnO NPs- and extract-treated rats showed significantly higher levels of IR, GluT2, and GCK expression and lower TNFα expression compared with the STZ induced diabetic rats. Our findings showed that ZnO NPs represented an outstanding performance for biological applications.     

Preparation of immunomagnetic beads coupled with a rhodamine hydrazine immunosensor for the detection of Mycobacterium avium subspecies paratuberculosis in bovine feces,milk, and colostrum

The aim of this study was to develop and evaluate a method for detecting Mycobacterium avium ssp. paratuberculosis (MAP) bacteria in bovine fecal, milk, and colostrum samples using immunomagnetic beads (IMB) and a rhodamine hydrazone immunosensor. Immunomagnetic beads were prepared by using purified antibodies from hyperimmunized sera that were coupled to Fe nanoparticles with diethylene triamine pentaacetic acid (DTPA) or ethyl (dimethyl aminopropyl) carbodiimide (EDC)-N-hydroxy succinimide (NHS) as linkers. Rhodamine hydrazone particles were synthesized and coupled to IgY anti-MAP antibodies using DTPA or EDC-NHS linkers. Separation efficiency of the IMB was tested on bovine fecal, milk, and colostrum samples experimentally contaminated with MAP. The studied methods were evaluated on their ability to detect MAP and separate bacteria in complex mediums. The ELISA results indicated 95% efficacy in antibody coupling to IMB, with the DTPA-IMB method being more efficient than the EDC-NHS-IMB method. By using the DTPA-IMB method, MAP bacteria were successfully recovered from fecal, milk, and colostrum samples. The DTPA-IMB method used in combination with the rhodamine hydrazone immunosensor had a limit of detection equal to 30 and 30,000 MAP cells/mL using chromogenic and fluorescent properties, respectively. Combining the DTPA-IMB separation method with the rhodamine hydrazone immunosensor provides a fast, sensitive, and cost-beneficial method for detecting MAP in bovine feces, milk, and colostrum.