Stiff-String Basis Functions for Vibration Analysis of High Speed Rotating Beams

A new rotating beam finite element is developed in which the basis functions are obtained by the exact solution of the governing static homogenous differential equation of a stiff string, which results from an approximation in the rotating beam equation. These shape functions depend on rotation speed and element position along the beam and account for the centrifugal stiffening effect. Using this new element and the Hermite cubic finite element, a convergence study of natural frequencies is performed, and it is found that the new element converges much more rapidly than the conventional Hermite cubic element for the first two modes at higher rotation speeds. The new element is also applied for uniform and tapered rotating beams to determine the natural frequencies, and the results compare very well with the published results given in the literature.

Time and Energy Complexity of Distributed Computation of a Class of Functions in Wireless Sensor Networks

We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

PE_PGRS Antigens of Mycobacterium tuberculosis Induce Maturation and Activation of Human Dendritic Cells

Mycobacterium tuberculosis, the causative agent of pulmonary tuberculosis, infects one-third of the world's population. Activation of host immune responses for containment of mycobacterial infections involves participation of innate immune cells, such as dendritic cells (DCs). DCs are sentinels of the immune system and are important for eliciting both primary and secondary immune responses to pathogens. In this context, to understand the molecular pathogenesis of tuberculosis and host response to mycobacteria and to conceive prospective vaccine candidates, it is important to understand how cell wall Ags of M.tuberculosis and, in particular, the proline-glutamic acid-polymorphicguanine-cytosine-rich sequence (PE_PGRS) family of proteins modulate DC maturation and function. In this study, we demonstrate that two cell wall-associated/secretory PE_PGRS proteins, PE_PGRS 17 (Rv0978c) and PE_PGRS 11 (Rv0754), recognize TLR2, induce maturation and activation of human DCs, and enhance the ability of DCs to stimulate CD4(+) T cells. We further found that PE_PGRS protein-mediated activation of DCs involves participation of ERK1/2, p38 MAPK, and NF-kappa B signaling pathways. Priming of human DCs with IFN-gamma further augmented PE_PGRS 17 or PE_PGRS 11 Ag-induced DC maturation and secretion of key proinflammatory cytokines. Our results suggest that by activating DCs, PE_PGRS proteins, important mycobacterial cell wall Ags, could potentially contribute in the initiation of innate immune responses during tuberculosis infection and hence regulate the clinical course of tuberculosis. The Journal of Immunology, 2010, 184: 3495-3504.

Targeting the fibroblast growth factor receptor family in cancer

Fibroblast growth factors (FGFs) regulate a plethora of biological functions, in both the embryonic and adult stages of development, binding their cognate receptors and thus activating a variety of downstream signalling pathways. Deregulation of the FGF/FGFR signalling axis, observed in multifarious tumor types including squamous non-small cell lung cancer, occurs through genomic FGFR alterations that drive ligand-independent receptor signalling or alterations that support ligand-dependent activation. Mutations are not restricted to the tyrosine kinase domain and aberrations appear to be tumor type dependent. As well as its complementarity and synergy with VEGF of particular interest is the interplay between FGFR and EGFR and the ability of these pathways to offer a compensatory signalling escape mechanism when either is inhibited. Hence there exists a rationale for a combinatorial approach to inhibition of these dysregulated pathways to reverse drug resistance. To date, several multi-target tyrosine kinase inhibitors as well as FGFR specific tyrosine kinase inhibitors (TKIs), monoclonal antibodies and FGF ligand traps have been developed. Promising preclinical data has resulted in several drugs entering clinical trials. This review explores aberrant FGFR and its potential as a therapeutic target in solid tumors.

Understanding Membranes through the Molecular Design of Lipids

Lipids are amphiphilic molecules that are composed of hydrophilic and hydrophobic regions. A typical membranous aggregate (vesicles, water-filled lipid nanospheres) is formed upon the self-organization of lipids in water from a diverse collection of amphiphiles producing a dynamic supramolecular structure that shows phase behavior and ordering as required for specific biological functions. The determination of various physical properties of lipid aggregates is the key to determining structure-function relationships. Over the years, we have designed and synthesized a wide variety of lipid molecular systems for the investigation of their membrane-forming properties and have used them for purposes such as gene delivery and enzyme activation. In this feature article, we focus on our work on various types of lipids including ion-paired amphiphiles, cholesterol-based lipids, aromatic lipids, macrocyclic lipids containing disulfide tethers; cationic dimeric lipids, and so forth. The emphasis is oil experimental design and bottom-line conclusions.

PE_PGRS Antigens of Mycobacterium tuberculosis Induce Maturation and Activation of Human Dendritic Cells

Mycobacterium tuberculosis, the causative agent of pulmonary tuberculosis, infects one-third of the world's population. Activation of host immune responses for containment of mycobacterial infections involves participation of innate immune cells, such as dendritic cells (DCs). DCs are sentinels of the immune system and are important for eliciting both primary and secondary immune responses to pathogens. In this context, to understand the molecular pathogenesis of tuberculosismand host response to mycobacteria and to conceive prospective vaccine candidates, it is important to understand how cell wall Ags of M. tuberculosis and, in particular, the proline-glutamic acid-polymorphic guanine-cytosine-rich sequence (PE_PGRS) family of proteins modulate DC maturation and function. In this study, we demonstrate that two cell wall-associated/secretory PE_PGRS proteins, PE_PGRS 17 (Rv0978c) and PE_PGRS 11 (Rv0754), recognize TLR2, induce maturation and activation of human DCs, and enhance the ability of DCs to stimulate CD4(+) T cells. We further found that PE_PGRS protein-mediated activation of DCs involves participation of ERK1/2, p38 MAPK, and NF-kappa B signaling pathways. Priming of human DCs with IFN-gamma further augmented PE_PGRS 17 or PE_PGRS 11 Ag-induced DC maturation and secretion of key proinflammatory cytokines. Our results suggest that by activating DCs, PE_PGRS proteins, important mycobacterial cell wall Ags, could potentially contribute in the initiation of innate immune responses during tuberculosis infection and hence regulate the clinical course of tuberculosis. The Journal of Immunology, 2010, 184: 3495-3504.

Nonlinear ensemble prediction of chaotic daily rainfall

The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.

Boundary value problems for third-order nonlinear ordinary differential equations

In this paper, we describe how to analyze boundary value problems for third-order nonlinear ordinary differential equations over an infinite interval. Several physical problems of interest are governed by such systems. The seminumerical schemes described here offer some advantages over solutions obtained by using traditional methods such as finite differences, shooting method, etc. These techniques also reveal the analytic structure of the solution function. For illustrative purposes, several physical problems, mainly drawn from fluid mechanics, are considered; they clearly demonstrate the efficiency of the techniques presented here.

Balancing Social Citizenship and New Paternalism : Finnish activation policy and street-level practice in a comparative perspective

The study examines the origin and development of the Finnish activation policy since the mid-1990s by using the 2001 activation reform as a benchmark. The notion behind activation is to link work obligations to welfare benefits for the unemployed. The focus of the thesis is policy learning and the impact of ideas on the reform of the welfare state. The broader research interests of the thesis are summarized by two groups of questions. First, how was the Finnish activation policy developed and what specific form did it receive in the 2001 activation reform? Second, how does the Finnish activation policy compare to the welfare reforms in the EU and in the US? What kinds of ideas and instruments informed the Finnish policy? To what extent can we talk about a restructuring or transformation of the Nordic welfare policy? Theoretically, the thesis is embedded in the comparative welfare state research and the concepts used in the contemporary welfare state discourse. Activation policy is analysed against the backdrop of the theories about the welfare state, welfare state governance and citizenship. Activation policies are also analysed in the context of the overall modernization and individualization of lifestyles and its implications for the individual citizen. Further, the different perspectives of the policy analysis are applied to determine the role of implementation and street-level practice within the whole. Empirically, the policy design, its implementation and the experiences of the welfare staff and recipients in Finland are examined. The policy development, goals and instruments of the activation policies have followed astonishingly similar paths in the different welfare states and regimes over the last two decades. In Finland, the policy change has been manifested through several successive reforms that have been introduced since the mid-1990s. The 2001 activation reform the Act on Rehabilitative Work Experience illustrates the broader trend towards stricter work requirements and draws its inspiration from the ideas of new paternalism. The ideas, goals and instruments of the international activation trend are clearly visible in the reform. Similarly, the reform has implications for the traditional Nordic social policies, which incorporate institutionalised social rights and the provision of services.

Asymmetric cross-coupled differential pair configuration to realize neuron activation function and its derivative

In this brief, we present a new circuit technique to generate the sigmoid neuron activation function (NAF) and its derivative (DNAF). The circuit makes use of transistor asymmetry in cross-coupled differential pair to obtain the derivative. The asymmetry is introduced through external control signal, as and when required. This results in the efficient utilization of the hard-ware by realizing NAF and DNAF using the same building blocks. The operation of the circuit is presented in the subthreshold region for ultra low-power applications. The proposed circuit has been experimentally prototyped and characterized as a proof of concept on the 1.5-mum AMI technology.