Purification of goat beta-lactoglobulin from whey by an ultrafiltration membrane enzymic reactor

This paper presents a novel contribution to the purification of goat beta-lactoglobulin by using an ultrafiltration membrane enzymic reactor. The basis of the purification process was the enzymic hydrolysis of contaminating proteins, alpha-lactalbumin and traces of serum albumin, by pepsin at 40 degrees C and pH 2, conditions under which beta-lactoglobulin is resistant to peptic digestion. Simultaneously, beta-lactoglobulin and peptides were separated by ultrafiltration. beta-Lactoglobulin was retained in the reactor while peptides generated by hydrolysis from alpha-lactalbumin and serum albumin permeated through the membrane. The process was made continuous by the addition of fresh whey to replace the lost permeate. Three mineral membranes with 10, 30 and 50 kDa molecular mass cut-off were tested and the 30 kDa membrane was selected for the continuous process. The simultaneous purification and concentration of beta-lactoglobulin from clarified goats' whey was achieved in a single step. The ultrafiltration membrane enzymic reactor could treat eight reactor volumes of clarified whey. The recovery of beta-lactoglobulin was 74%, its purity was 84% and its concentration 6.6-fold that in the initial clarified whey.     

Categorization creates functional features.

Many theories of object recognition and categorization claim that complex objects are represented in terms of characteristic features. The origin of these features has been neglected in theories of object categorization. Do they form a fixed and independent set that exists before experience with objects, or are features progressively extracted and developed as an organism categorizes its world? This article maintains that features can be learned flexibly as a consequence of categorizing and representing objects. All 3 experiments reported in this article used categories of unfamiliar, computer-synthesized 2-dimensional objects ("Martian cells"). The results showed that varying the order of category learning induced the creation of different features that changed the perceptual appearance and the featural representation of identical category exemplars. Network simulations supported a flexible rather than a fixed-feature interpretation of the data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A comparison between chip fractional and non-fractional samplingfor a direct sequence CDMA receiver

This paper examines the effects of chip fractional (CF) and chip non-fractional (CNF) sampling on the performance of a CDMA uplink receiver. The impact of the receiver front end filter, which is sampling rate dependent, is investigated. Models for burst and continuous transmissions are introduced. The discrete-time equivalent channels between the various users and the receiver are assumed to be known. First, the mutual information between the emitted sequences of symbols and the received sequence is investigated. It is analytically shown that the receiver systematically loses information in case of CNF sampling. Second, we have demonstrated that the CF receiver always achieves better performance in terms of minimum mean square error (MMSE) for both linear and decision feedback (DF) structures. A closed-form expression of the gain in performance is provided for the two metrics; under consideration. The importance of the gain due to CF sampling is also illustrated by means of computations for multipath channels. For a typical system setup, a gain of 0.1 bits per emitted symbol is observed for the mutual information. Considering the geometrical mean of symbol SINRs in case of linear and DF joint detection (JD) for a roll-off factor equal to 0.3, a gain of 0.4 dB arises for the CF linear detector, and a gain of 0.2 dB arises for the CF DF detector     

Real-time multi-scale brain data acquisition, assembly, and analysis using an end-to-end OptIPuter

At iGrid 2005 we demonstrated the transparent operation of a biology experiment on a test-bed of globally distributed visualization, storage, computational, and network resources. These resources were bundled into a unified platform by utilizing dynamic lambda allocation, high bandwidth protocols for optical networks, a Distributed Virtual Computer (DVC) [N. Taesombut, A. Chien, Distributed Virtual Computer (DVC): Simplifying the development of high performance grid applications, in: Proceedings of the Workshop on Grids and Advanced Networks, GAN 04, Chicago, IL, April 2004 (held in conjunction with the IEEE Cluster Computing and the Grid (CCGrid2004) Conference)], and applications running over the Scalable Adaptive Graphics Environment (SAGE) [L. Renambot, A. Rao, R. Singh, B. Jeong, N. Krishnaprasad, V. Vishwanath, V. Chandrasekhar, N. Schwarz, A. Spale, C. Zhang, G. Goldman, J. Leigh, A. Johnson, SAGE: The Scalable Adaptive Graphics Environment, in: Proceedings of WACE 2004, 23–24 September 2004, Nice, France, 2004]. Using these layered technologies we ran a multi-scale correlated microscopy experiment [M.E. Maryann, T.J. Deerinck, N. Yamada, E. Bushong, H. Ellisman Mark, Correlated 3D light and electron microscopy: Use of high voltage electron microscopy and electron tomography for imaging large biological structures, Journal of Histotechnology 23 (3) (2000) 261–270], where biologists imaged samples with scales ranging from 20X to 5000X in progressively increasing magnification. This allows the scientists to zoom in from entire complex systems such as a rat cerebellum to individual spiny dendrites. The images used spanned multiple modalities of imaging and specimen preparation, thus providing context at every level and allowing the scientists to better understand the biological structures. This demonstration attempts to define an infrastructure based on OptIPuter components which would aid the development and design of collaborative scientific experiments, applications and test-beds and allow the biologists to effectively use the high resolution real estate of tiled displays.     

Reflections on self-determination theory.

Self-determination theory (SDT; Deci & Ryan, 2008) has led to much research over the past 25 years or so. The present collection of articles in this special issue attests to that. In this last article, we present a short overview of issues that cut across these papers as well as make recommendations for future research. We believe that the future is quite bright for SDT. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A New State-space-based Algorithm to Assess the Stability of the Finite-difference Time-domain Method for 3D Finite Inhomogeneous Problems

The finite-difference time-domain (FDTD) method is an explicit time discretization scheme for Maxwell's equations. In this context it is well-known that explicit time discretization schemes have a stability induced time step restriction. In this paper, we recast the spatial discretization of Maxwell's equations, initially without time discretization, into a more convenient format, called the FDTD state-space system. This in turn allows us to derive a new algorithm in order to determine the stability limit of FDTD for lossy, inhomogeneous finite problems. It is shown that a crucial parameter is the spectral norm of the matrix resulting from the spatial discretization of the curl operator. In a rectangular simulation domain the time step upper bound can be calculated in closed form and results in a time step limit less stringent than the Courant condition. Finally, the validity of the technique is illustrated by means of some pertinent numerical examples.     

What can two images tell us about a third one?

This paper discusses the problem of predicting image features in an image from image features in two other images and the epipolar geometry between the three images. We adopt the most general camera model of perspective projection and show that a point can be predicted in the third image as a bilinear function of its images in the first two cameras, that the tangents to three corresponding curves are related by a trilinear function, and that the curvature of a curve in the third image is a linear function of the curvatures at the corresponding points in the other two images. Our analysis relies heavily on the use of the fundamental matrix which has been recently introduced (Faugeras et al, 1992) and on the properties of a special plane which we call the trifocal plane. Though the trinocular geometry of points and lines has been very recently addressed, our use of the differential properties of curves for prediction is unique.We thus completely solve the following problem: given two views of an object, predict what a third view would look like. The problem and its solution bear upon several areas of computer vision, stereo, motion analysis, and model-based object recognition. Our answer is quite general since it assumes the general perspective projection model for image formation and requires only the knowledge of the epipolar geometry for the triple of views. We show that in the special case of orthographic projection our results for points reduce to those of Ullman and Basri (Ullman and Basri, 1991). We demonstrate on synthetic as well as on real data the applicability of our theory.     

Synthesis and properties of europium complexes derived fromcoumarin-derivatized azamacrocycles

Synthesis and properties of a series of new europium fluorescent probes based on azamacrocyclic compounds derivatized with coumarins as lanthanide sensitizers are described. Photophysical properties were investigated in water and standard human plasma. In the developed series, two compounds proved efficient for energy transfer from coumarin-centered to Eu³⁺-centered levels and are compatible with FRET experiments involving UV-LEDs excitation source. Some of the compounds exhibit interesting characteristics as wavelength-ratiometric pH sensors.