The C-terminus of Raf-1 acts as a 14-3-3-dependent activation switch

The Raf-1 protein kinase is a major activator of the ERK MAPK pathway, which links signaling by a variety of cell surface receptors to the regulation of cell proliferation, survival, differentiation and migration. Signaling by Raf-1 is regulated by a complex and poorly understood interplay between phosphorylation events and protein-protein interactions. One important mode of Raf-1 regulation involves the phosphorylation-dependent binding of 14-3-3 proteins. Here, we have examined the mechanism whereby the C-terminal 14-3-3 binding site of Raf-1, S621, controls the activation of MEK-ERK signaling. We show that phosphorylation of S621 turns over rapidly and is enriched in the activated pool of endogenous Raf-1. The phosphorylation on this site can be mediated by Raf-1 itself but also by other kinase(s). Mutations that prevent the binding of 14-3-3 proteins to S621 render Raf-1 inactive by specifically disrupting its capacity to bind to ATP, and not by gross conformational alteration as indicated by intact MEK binding. Phosphorylation of S621 correlates with the inhibition of Raf-1 catalytic activity in vitro, but 14-3-3 proteins can completely reverse this inhibition. Our findings suggest that 14-3-3 proteins function as critical cofactors in Raf-1 activation, which induce and maintain the protein in a state that is competent for both ATP binding and MEK phosphorylation.

T-cell epitope prediction and immune complex simulation using molecular dynamics:state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

Control integrated finite state machine design for photovoltaic module integrated converter

The operation state of photovoltaic Module Integrated Converter (MIC) is subjected to change due to different source and load conditions, while state-swap is usually implemented with flow chart based sequential controller in the past research. In this paper, the signatures for different operational states are evaluated and investigated, which lead to an effective control integrated finite state machine (CIFSM), providing real-time state-swap as fast as the local control loop. The proposed CIFSM is implemented digitally for a boost type MIC prototype and tested under a variety of load and source conditions. The test results prove the effectiveness of the proposed CIFSM design.

A learning feed-forward current controller for linear reciprocating vapor compressors

Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via a crank shaft. However, to ensure efficient and reliable operation under all conditions, it is essential that motor current of a linear compressor follows a sinusoidal current command with a frequency which matches the system resonant frequency. The design of a high-performance current controller for linear compressor drive presents a challenge since the system is highly nonlinear, and an effective solution must be low cost. In this paper, a learning feed-forward current controller for the linear compressors is proposed. It comprises a conventional feedback proportional-integral controller and a feed-forward B-spline neural network (BSNN). The feed-forward BSNN is trained online and in real time in order to minimize the current tracking error. Extensive simulation and experiment results with a prototype linear compressor show that the proposed current controller exhibits high steady state and transient performance. © 2009 IEEE.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Polarisation dynamics of vector soliton molecules in mode locked fibre laser

Two fundamental laser physics phenomena - dissipative soliton and polarisation of light are recently merged to the concept of vector dissipative soliton (VDS), viz. train of short pulses with specific state of polarisation (SOP) and shape defined by an interplay between anisotropy, gain/loss, dispersion, and nonlinearity. Emergence of VDSs is both of the fundamental scientific interest and is also a promising technique for control of dynamic SOPs important for numerous applications from nano-optics to high capacity fibre optic communications. Using specially designed and developed fast polarimeter, we present here the first experimental results on SOP evolution of vector soliton molecules with periodic polarisation switching between two and three SOPs and superposition of polarisation switching with SOP precessing. The underlying physics presents an interplay between linear and circular birefringence of a laser cavity along with light induced anisotropy caused by polarisation hole burning.

Productivity growth and efficiency measurements in fuzzy environments with an application to health care

Health care organizations must continuously improve their productivity to sustain long-term growth and profitability. Sustainable productivity performance is mostly assumed to be a natural outcome of successful health care management. Data envelopment analysis (DEA) is a popular mathematical programming method for comparing the inputs and outputs of a set of homogenous decision making units (DMUs) by evaluating their relative efficiency. The Malmquist productivity index (MPI) is widely used for productivity analysis by relying on constructing a best practice frontier and calculating the relative performance of a DMU for different time periods. The conventional DEA requires accurate and crisp data to calculate the MPI. However, the real-world data are often imprecise and vague. In this study, the authors propose a novel productivity measurement approach in fuzzy environments with MPI. An application of the proposed approach in health care is presented to demonstrate the simplicity and efficacy of the procedures and algorithms in a hospital efficiency study conducted for a State Office of Inspector General in the United States. © 2012, IGI Global.

A hybrid current controller for linear reciprocating vapor compressors

Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via crank shaft However, to ensure efficient and reliable operation under all conditions, it is essential that the motor current of the linear compressor follows a sinusoidal command profile with a frequency which matches the system resonant frequency. This paper describes a hybrid current controller for the linear compressors. It comprises a conventional proportional-integral (PI) controller, and a B-spline neural network compensator which is trained on-line and in real-time in order to minimize the current tracking error under all conditions with uncertain disturbances. It has been shown that the hybrid current controller has a superior steady-state and transient performance over the conventional carrier based PI controller. The performance of the proposed hybrid controller has been demonstrated by extensive simulations and experiments. It has also been shown that the linear compressor operates stably under the current feedback control and the piston stroke can be adjusted by varying the amplitude of the current command. © 2007 IEEE.

Leontief Model Analysis with Fuzzy Parameters by Basic Matrixes Method

The basic matrixes method is suggested for the Leontief model analysis (LM) with some of its components indistinctly given. LM can be construed as a forecast task of product’s expenses-output on the basis of the known statistic information at indistinctly given several elements’ meanings of technological matrix, restriction vector and variables’ limits. Elements of technological matrix, right parts of restriction vector LM can occur as functions of some arguments. In this case the task’s dynamic analog occurs. LM essential complication lies in inclusion of variables restriction and criterion function in it.

The System of Quality Prediction on the Basis of a Fuzzy Data and Psychography of the Experts

The system of development unstable processes prediction is given. It is based on a decision-tree method. The processing technique of the expert information is offered. It is indispensable for constructing and processing by a decision-tree method. In particular data is set in the fuzzy form. The original search algorithms of optimal paths of development of the forecast process are described. This one is oriented to processing of trees of large dimension with vector estimations of arcs.

Fast and slowly evolving vector solitons in mode-locked fibre lasers

We report on a new vector model of an erbium-doped fibre laser mode locked with carbon nanotubes. This model goes beyond the limitations of the previously used models based on either coupled nonlinear Schrödinger or Ginzburg-Landau equations. Unlike the previous models, it accounts for the vector nature of the interaction between an optical field and an erbium-doped active medium, slow relaxation dynamics of erbium ions, linear birefringence in a fibre, linear and circular birefringence of a laser cavity caused by in-cavity polarization controller and light-induced anisotropy caused by elliptically polarized pump field. Interplay of aforementioned factors changes coherent coupling of two polarization modes at a long time scale and so results in a new family of vector solitons (VSs) with fast and slowly evolving states of polarization. The observed VSs can be of interest in secure communications, trapping and manipulation of atoms and nanoparticles, control of magnetization in data storage devices and many other areas.

Fopid Controller Design for Robust Performance Using Particle Swarm Optimization

Mathematics Subject Classification: 26A33; 93C15, 93C55, 93B36, 93B35, 93B51; 03B42; 70Q05; 49N05

Vector solitons in mode locked fibre lasers

We overview our recent results on polarisation dynamics of vector solitons in erbium doped fibre laser mode locked with carbon nanotubes. Our experimental and theoretical study revealed new families of vector solitons for fundamental and bound-state soliton operations. The observed scenario of the evolution of the states of polarisation (SOPs) on the Poincare sphere includes fast polarisation switching between two and three SOPs along with slow SOP evolution on a double scroll chaotic attractor. The underlying physics presents an interplay between effects of birefringence of the laser cavity and light induced anisotropy caused by polarisation hole burning. © 2014 IEEE.

Polarization dynamics of bound state solitons in a carbon nanotubes mode locked erbium doped fiber laser

Optical solitons are important in the modern photonics. Passively mode locked erbium doped fiber lasers provide a neat platform to study soliton dynamics. Soliton interaction dynamics is important for various applications and has quite different manifestations, including e.g. such as bound state solitons [1], soliton rains [2]. Soliton interactions have been observed with different mode locking approaches such as figure-of-eight [3] and nonlinear polarization rotation [4]. Carbon nanotubes (CNT) have recently been widely applied as an efficient saturable absorber for passively mode locked fiber lasers. We have recently studied the polarization dynamics in a CNT mode locked vector soliton erbium doped fiber laser [5]. So far, the polarization dynamics of bound state solitons have yet to be investigated. In this report, we present a wide range of polarization dynamics of bound state solitons generated in a CNT mode locked erbium doped fiber laser. The fiber laser consists of ∼ 2 m highly doped erbium fiber (Liekki Er80-8/125) as the gain medium, an optical isolator to ensure unidirectional oscillation anda 980 nm laser diode is used to pump the gain through the 1550/980 nm wavelength division multiplexer. A fused 10:90 coupler is used to couple 10 % of the light out of the laser cavity and two in-line polarization controllers (NewPort) are used to control the birefringence of the cavity and polarization of the pump light respectively. The total cavity length is ∼ 7.8 m indicating a 25.7 MHz fundamental repetition rate. © 2013 IEEE.