Nucleocytoplasmic transport: taking an inventory

In eukaryotic cells, the enclosure of the genetic information in the nucleus allows the spatial and temporal separation of DNA replication and transcription from cytoplasmic protein synthesis. This compartmentalization not only permits a high level of regulation of these processes but at the same time necessitates a system of selective macromolecular transport between the nucleus and the cytoplasm. Transfer of macromolecules between both compartments is mediated by soluble receptors that interact with components of nuclear pore complexes (NPCs) to move their specific cargos. Transport occurs by way of a great variety of different pathways defined by individual receptors and accessory factors. Often, processes in substrate biogenesis that precede transport concurrently recruit transport factors to substrates, thus making transport responsive to correct and orderly synthesis of substrates. Some current challenges are to understand how transport factor-substrate interactions are controlled and integrated with sequential steps in substrate biogenesis, how large macromolecular complexes are restructured to fit through the NPC channel and to understand how transport factor-NPC interactions lead to actual translocation through the NP

Optimal Filtering with Linear Canonical Transformations

Cataloged from PDF version of article.Optimal filtering with linear canonical transformations allows smaller mean-square errors in restoring signals degraded by linear time- or space-variant distortions and non-stationary noise. This reduction in error comes at no additional computational cost. This is made possible by the additional flexibility that comes with the three free parameters of linear canonical transformations, as opposed to the fractional Fourier transform which has only one free parameter, and the ordinary Fourier transform which has none. Application of the method to severely degraded images is shown to be significantly superior to filtering in fractional Fourier domains in certain cases

The fractional Fourier domain decomposition

Cataloged from PDF version of article.We introduce the fractional Fourier domain decomposition. A procedure called pruning, analogous to truncation of the singular-value decomposition, underlies a number of potential applications, among which we discuss fast implementation of space-variant linear systems. (c) 1999 Published by Elsevier Science B.V. All rights reserved

Towards Project Portfolio Management for Sustainable Outcomes in the Construction Industry

It is imperative that organisations improve their sustainability and there is a global push to reduce the environmental impact from project activities. This is especially true in construction, yet there is no ex1stmg framework to guide decision making and project portfolio management (PPM) for sustainable construction. This paper discusses the application of project portfolio management to the area of sustainable development in the construction industry. Using the understanding gained from existing PPM practices in a range of industries and the current approaches to risk and sustainability management in the construction industry, we propose a new maturity model for PPM. The maturity model aims to guide the introduction of sustainability factors into multi-project resource scheduling and risk analysis in the coustruction industry, and can be used to make the contribution to sustainability from an overall portfolio more sustainable than the sum of the contribution from individual projects, 1

The fractional fourier transform

A brief introduction to the fractional Fourier transform and its properties is given. Its relation to phase-space representations (time- or space-frequency representations) and the concept of fractional Fourier domains are discussed. An overview of applications which have so far received interest are given and some potential application areas remaining to be explored are noted. © 2001 EUCA

The fractional Fourier transform and its applications to image representation and beamforming

The ath order fractional Fourier transform operator is the ath power of the ordinary Fourier transform operator. We provide a brief introduction to the fractional Fourier transform, discuss some of its more important properties, and concentrate on its applications to image representation and compression, and beamforming. We show that improved performance can be obtained by employing the fractional Fourier transform instead of the ordinary Fourier transform in these applications

Fractional Fourier transform-exceeding the classical concepts of signal's manipulation

The fractional Fourier transform is a signal processing tool which is strongly associated with optical data manipulation. It has fast computational algorithms and it suggests solutions to interesting signal processing tasks. In this paper we review its properties as well as present a new set of its applications for blind source separation of images and for RF photonics (a field in which photonic devices are used to process RF signals). © 2007 Pleiades Publishing, Ltd

Fractional Fourier domain decomposition

We introduce the fractional Fourier domain decomposition. A procedure called pruning, analogous to truncation of the singular-value decomposition, underlies a number of potential applications, among which we discuss fast implementation of space-variant linear systems

Optimal filtering in fractional fourier domains

For time-invariant degradation models and stationary signals and noise, the classical Fourier domain Wiener filter, which can be implemented in O(NlogN) time, gives the minimum mean-square-error estimate of the original undistorted signal. For time-varying degradations and nonstationary processes, however, the optimal linear estimate requires O(N2) time for implementation. We consider filtering in fractional Fourier domains, which enables significant reduction of the error compared with ordinary Fourier domain filtering for certain types of degradation and noise (especially of chirped nature), while requiring only O(N\og N) implementation time. Thus, improved performance is achieved at no additional cost. Expressions for the optimal filter functions in fractional domains are derived, and several illustrative examples are given in which significant reduction of the error (by a factor of 50) is obtained. © 1997 IEEE

Digital computation of the fractional fourier transform

An algorithm for efficient and accurate computation of the fractional Fourier transform is given. For signals with time-bandwidth product N, the presented algorithm computes the fractional transform in O(JVlogjY) time. A definition for the discrete fractional Fourier transform that emerges from our analysis is also discussed. © 1996 IEEE