High pressure processing (HPP) is an interesting non-thermal technology that involves the sterilization of food by the mean of ultra-high pressures, which lead to extending the shelf life of processed food, as well as maintaining nutritional value and quality of food products. The consumers' increasing demand for this new products graped the interest of several already-existing high pressure equipment manufacturers around the globe. The successful of this technology encouraged them to enter the field of food processing and adjust their existing technologies to adapt to the new process. This review spots the major discoveries in HPP equipment history, describes the current applications of HHP in processing and provides comprehensive information about HPP equipment technology used in commercial and research applications. In addition, this paper presents the major manufacturers in HPP equipment industry around the world.
Cleaning-in-place is a common process in food industries to maintain the hygiene of the processing system. In this paper, analysis on removal kinetics of the fouling deposit has shown promising results which can be used to improve CIP protocol. The removal kinetics analyses on the cleanability experiments of pink guava puree fouling deposit were done using the laboratory-scale cleaning test rig. The experiments' parameters were temperatures (35-70 °C), Sodium hydroxide concentrations (1.0-2.0 wt%) and fluid velocities (0.6-1.5 m/s at Reynolds numbers range of Re = 4 × 10 4 to 18 × 10 4). Contact time of chemical wash and rinsing time were determined when the test object has reached a physically clean state. Two distinct cleaning stages: rapid and gradual were identified from the cleaning profiles and each stage has shown high effective removal rate at different cleaning conditions. The removal kinetics results were integrated with several types of cleaning protocols: 1) extreme cleaning; 2) optimal cleaning with water recirculation and 3) optimal cleaning. The cost analysis for every cleaning protocol has proved that the second cleaning protocol is more cost-effective compared to the other cleaning protocols.
EEG source localization is determining possible cortical sources of brain activities with scalp EEG. Generally, every step of the data processing sequence affects the accuracy of EEG source localization. In this paper, we introduce a fused multivariate empirical mode decomposing (MEMD) and inverse solution algorithm with an embedded unsupervised eye blink remover in order to localize the epileptogenic zone accurately. For this purpose, we constructed realistic forward models using MRI and boundary element method (BEM) for each patient to obtain results that are more realistic. We also developed an unsupervised algorithm utilizing a wavelet method to remove eye blink artifacts. Additionally, we applied MEMD, which is one of the recent and suitable feature extraction methods for non-linear, non-stationary, and multivariate signals such as EEG, to extract the signal of interest. We examined the localization results using the two most reliable linear distributed inverse methods in the literature: weighted minimum norm estimation (wMN) and standardized low resolution tomography (sLORETA). Results affirm the success of the proposed algorithm with the highest agreement compared to MRI reference by a specialist. Fusion of MEMD and sLORETA results in approximately zero localization error in terms of spatial difference with the validated MRI reference. High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.
In this paper we study the general localization principle for Fourier-Laplace series on unit sphere S N ⊂ R N+1 . Weak type (1, 1) property of maximal functions is used to establish the estimates of the maximal operators of Riesz means at critical index N−1 2 . The properties Jacobi polynomials are used in estimating the maximal operators of spectral expansions in L 2 (S N ). For extending positive results on critical line α = (N − 1)( 1 p − 1 2 ), 1 p 2, we apply interpolation theorem for the family of the linear operators of weak types. The generalized localization principle is established by the analysis of spectral expansions in L 2 . We have proved the sufficient conditions for the almost everywhere convergence of Fourier-Laplace series by Riesz means on the critical line.
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