On U(1) Gauge Theory Transfer-Matrix in Fourier Basis*

The properties of the transfer-matrix of U(1) lattice gauge theory in the Fourier basis are explored. Among other statements it is shown: (i) the transfer-matrix is block-diagonal, (ii) all consisting vectors of a block are known based on an arbitrary block vector, (iii) the ground-state belongs to the zero-mode's block. The emergence of maximum-points in matrix-elements as functions of the gauge coupling is clarified. Based on explicit expressions for the matrix-elements we present numerical results as tests of our statements.     

Synthesis,Characterization, Structural Description,Micellization Behavior,DNA Binding Study and Antioxidant Activity of 4, 5 and 6-Coordinated Copper(II) and Zinc(II) Complexes

Four mononuclear copper(II) and zinc(II) complexes were synthesized by the reaction of copper and zinc salts with 3,4-dichlorophenylactic acid, 2-bromophenylactic acid, biphenylacetic acid (O-donor ligand) and bipyridine (N-donor ligands) having the general formulae [(L)₂Cu(bp)(H₂O)] ( 1 ), [(BpA)₂Cu(bp)] ( 2 ), [(L)₂Zn(bp)(H₂O)] ( 3 ) and [(L*)₂Zn(bp)] ( 4 ) (L = 3,4-dichlorophenylacetate, L* = 2-bromophenylacetate bp = bipyridine, and BpA = biphenylacetate). Structures of all compounds were characterized through FT-IR spectroscopy and X-ray diffraction analysis. FT-IR spectra of all complexes confirmed the binding mode of Cu-O and Zn-O. XRD data revealed that complexes 1 – 3 exhibited distorted octahedral arrangement, whereas complex 4 has a distorted tetrahedral environment. Micellization behavior was examined with anionic surfactant (SDS) by conductance measurement as well as absorption spectral analysis. DNA binding study was assessed through viscosity measurement and UV/Vis spectrophotometry. DPPH free radical scavenging assay was measured by UV/Vis spectrophotometry. The results showed nice biological potential of all the complexes.     

Purification of low-abundance lysozyme in egg white via free-flow electrophoresis with gel-filtration chromatography

As an effective separation tool, free-flow electrophoresis has not been used for purification of low-abundance protein in complex sample matrix. Herein, lysozyme in complex egg white matrix was chosen as the model protein for demonstrating the purification of low-content peptide via an FFE coupled with gel fitration chromatography (GFC). The crude lysozyme in egg while was first separated via free-flow zone electrophoresis (FFZE). After that, the fractions with lysozyme activity were condensed via lyophilization. Thereafter, the condensed fractions were further purified via a GFC of Sephadex G50. In all of the experiments, a special poly(acrylamide- co-acrylic acid) (P(AM-co-AA)) gel electrophoresis and a mass spectrometry were used for identification of lysozyme. The conditions of FFZE were optimized as follows: 130 μL/min sample flow rate, 4.9 mL/min background buffer of 20 mM pH 5.5 Tris-Acetic acid, 350 V, and 14 °C as well as 2 mg/mL protein content of crude sample. It was found that the purified lysozyme had the purity of 80% and high activity as compared with its crude sample with only 1.4% content and undetectable activity. The recoveries in the first and second separative steps were 65% and 82%, respectively, and the total recovery was about 53.3%. The reasons of low recovery might be induced by diffusion of lysozyme out off P(AM-co-AA) gel and co-removing of high-abundance egg ovalbumin. All these results indicated FFE could be used as alternative tool for purification of target solute with low abundance.     

Purification of hyaluronidase as an anticancer agent inhibiting CD44

Hyaluronidase (Hyal) can be employed to accomplish a diversity of complications related to hyaluronic acid (HA). Hyal contains some classes of catalysts that cleave HA. This enzyme is detected in several human tissues as well as in animal venoms, pathogenic organisms and cancers. Destructive cancer cells regularly increase the CD44 receptor existing in a cell membrane. This receptor acts as an exact receptor for HA, and HA is recognized to motivate the migration, spread, attack and metastasis of cancer cells. Nearly all of the methods used to purify Hyal are highly costly and not proper for industrial applications. This survey aims to review different methods of Hyal purification, which acts as an anticancer agent by degrading HA in tissues and thus inhibiting the CD44–HA interaction. Hyal can be successfully employed in the management of cancer, which is associated with HA–CD44. This review has described different methods for Hyal purification to prepare an origin to develop a novel purification technique for this highly appreciated protein. Using multiple columns is not applicable for the purification of Hyal and thus cannot be used at the industrial level. It is better to use affinity chromatography of anti-Hyal for Hyal with one-step purification.     

Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features

Extraction of relevant lip features is of continuing interest in the visual speech domain. Using end-to-end feature extraction can produce good results, but at the cost of the results being difficult for humans to comprehend and relate to. We present a new, lightweight feature extraction approach, motivated by human-centric glimpse-based psychological research into facial barcodes, and demonstrate that these simple, easy to extract 3D geometric features (produced using Gabor-based image patches), can successfully be used for speech recognition with LSTM-based machine learning. This approach can successfully extract low dimensionality lip parameters with a minimum of processing. One key difference between using these Gabor-based features and using other features such as traditional DCT, or the current fashion for CNN features is that these are human-centric features that can be visualised and analysed by humans. This means that it is easier to explain and visualise the results. They can also be used for reliable speech recognition, as demonstrated using the Grid corpus. Results for overlapping speakers using our lightweight system gave a recognition rate of over 82%, which compares well to less explainable features in the literature.     

Vector and Cell Line Engineering Technologies Toward Recombinant Protein Expression in Mammalian Cell Lines

The rapid growth of global biopharmaceutical market in the recent years has been a good indication of its significance in biotechnology industry. During a long period of time in recombinant protein production from 1980s, optimizations in both upstream and downstream processes were launched. In this regard, one of the most promising strategies is expression vector engineering technology based on incorporation of DNA opening elements found in the chromatin border regions of vectors as well as targeting gene integration. Along with these approaches, cell line engineering has revealed convenient outcomes in isolating high-producing clones. According to the fact that more than 50% of the approved therapeutic proteins is being manufactured in mammalian cell lines, in this review, we focus on several approaches and developments in vector and cell line engineering technologies in mammalian cell culture.     

Robust Mean-Squared Error Estimation of Multiple Signals in Linear Systems Affected by Model and Noise Uncertainties

This paper is a continuation of the work in [11] and [2] on the problem of estimating by a linear estimator, N unobservable input vectors, undergoing the same linear transformation, from noise-corrupted observable output vectors. Whereas in the aforementioned papers, only the matrix representing the linear transformation was assumed uncertain, here we are concerned with the case in which the second order statistics of the noise vectors (i.e., their covariance matrices) are also subjected to uncertainty. We seek a robust mean-squared error estimator immuned against both sources of uncertainty. We show that the optimal robust mean-squared error estimator has a special form represented by an elementary block circulant matrix, and moreover when the uncertainty sets are ellipsoidal-like, the problem of finding the optimal estimator matrix can be reduced to solving an explicit semidefinite programming problem, whose size is independent of N. The research was partially supported by BSF grant #2002038     

3D discrete X-ray transform

The analysis of 3D discrete volumetric data becomes increasingly important as computation power increases. 3D analysis and visualization applications are expected to be especially relevant in areas like medical imaging and nondestructive testing, where elaborated continuous theory exists. However, this theory is not directly applicable to discrete datasets. Therefore, we have to establish theoretical foundations that will replace the existing inexact discretizations, which have been based on the continuous regime. We want to preserve the concepts, properties, and main results of the continuous theory in the discrete case. In this paper, we present a discretization of the continuous X-ray transform for discrete 3D images. Our definition of the discrete X-ray transform is shown to be exact and geometrically faithful as it uses summation along straight geometric lines without arbitrary interpolation schemes. We derive a discrete Fourier slice theorem, which relates our discrete X-ray transform with the Fourier transform of the underlying image, and then use this Fourier slice theorem to derive an algorithm that computes the discrete X-ray transform in O(n⁴logn) operations. Finally, we show that our discrete X-ray transform is invertible.     

Resource allocation in dynamic PERT networks with finite capacity

This article models the resource allocation problem in dynamic PERT networks with finite capacity of concurrent projects (COnstant Number of Projects In Process (CONPIP)), where activity durations are independent random variables with exponential distributions, and the new projects are generated according to a Poisson process. The system is represented as a queuing network with finite concurrent projects, where each activity of a project is performed at a devoted service station with one server located in a node of the network. For modeling dynamic PERT networks with CONPIP, we first convert the network of queues into a stochastic network. Then, by constructing a proper finite-state continuous-time Markov model, a system of differential equations is created to solve and find the completion time distribution for any particular project. Finally, we propose a multi-objective model with three conflict objectives to optimally control the resources allocated to the servers, and apply the goal attainment method to solve a discrete-time approximation of the original multi-objective problem.