Dependence of diffusivity on density and solute diameter in liquid phase: A molecular dynamics study of Lennard-Jones system

Investigations into the variation of self-diffusivity with solute radius, density, and degree of disorder of the host medium is explored. The system consists of a binary mixture of a relatively smaller sized solute, whose size is varied and a larger sized solvent interacting via Lennard-Jones potential. Calculations have been performed at three different reduced densities of 0.7, 0.8, and 0.933. These simulations show that diffusivity exhibits a maximum for some intermediate size of the solute when the solute diameter is varied. The maximum is found at the same size of the solute at all densities which is at variance with the prediction of the levitation effect. In order to understand this anomaly, additional simulations were carried out in which the degree of disorder has been varied while keeping the density constant. The results show that the diffusivity maximum gradually disappears with increase in disorder. Disorder has been characterized by means of the minimal spanning tree. Simulations have also been carried out in which the degree of disorder is constant and only the density is altered. The results from these simulations show that the maximum in diffusivity now shifts to larger distances with decrease in density. This is in agreement with the changes in void and neck distribution with density of the host medium. These results are in excellent agreement with the predictions of the levitation effect. They suggest that the effect of disorder is to shift the maximum in diffusivity towards smaller solute radius while that of the decrease in density is to shift it towards larger solute radius. Thus, in real systems where the degree of disorder is lower at higher density and vice versa, the effect due to density and disorder have opposing influences. These are confirmed by the changes seen in the velocity autocorrelation function, self part of the intermediate scattering function and activation energy. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.3701619]

Analysis of Parameter Values in the van der Waals and Platteeuw Theory for Methane Hydrates Using Monte Carlo Molecular Simulations

The van der Waals and Platteuw (vdVVP) theory has been successfully used to model the thermodynamics of gas hydrates. However, earlier studies have shown that this could be due to the presence of a large number of adjustable parameters whose values are obtained through regression with experimental data. To test this assertion, we carry out a systematic and rigorous study of the performance of various models of vdWP theory that have been proposed over the years. The hydrate phase equilibrium data used for this study is obtained from Monte Carlo molecular simulations of methane hydrates. The parameters of the vdWP theory are regressed from this equilibrium data and compared with their true values obtained directly from simulations. This comparison reveals that (i) methane-water interactions beyond the first cage and methane-methane interactions make a significant contribution to the partition function and thus cannot be neglected, (ii) the rigorous Monte Carlo integration should be used to evaluate the Langmuir constant instead of the spherical smoothed cell approximation, (iii) the parameter values describing the methane-water interactions cannot be correctly regressed from the equilibrium data using the vdVVP theory in its present form, (iv) the regressed empty hydrate property values closely match their true values irrespective of the level of rigor in the theory, and (v) the flexibility of the water lattice forming the hydrate phase needs to be incorporated in the vdWP theory. Since methane is among the simplest of hydrate forming molecules, the conclusions from this study should also hold true for more complicated hydrate guest molecules.

Model Pseudoconvex Domains and Bumping

The Levi geometry at weakly pseudoconvex boundary points of domains in C-n, n >= 3, is sufficiently complicated that there are no universal model domains with which to compare a general domain. Good models may be constructed by bumping outward a pseudoconvex, finite- type Omega subset of C-3 in such a way that: (i) pseudoconvexity is preserved, (ii) the (locally) larger domain has a simpler defining function, and (iii) the lowest possible orders of contact of the bumped domain with partial derivative Omega, at the site of the bumping, are realized. When Omega subset of C-n, n >= 3, it is, in general, hard to meet the last two requirements. Such well-controlled bumping is possible when Omega is h-extendible/semiregular. We examine a family of domains in C-3 that is strictly larger than the family of h-extendible/semiregular domains and construct explicit models for these domains by bumping.

Computational interrogation of cis-regulatory elements of genes that are common targets of luteotropin and luteolysin in the primate corpus luteum

The rapid recent increase in microarray-based gene expression studies in the corpus luteum (CL) utilizing macaque models gathered increasing volume of data in publically accessible microarray expression databases. Examining gene pathways in different functional states of CL may help to understand the factors that control luteal function and hence human fertility. Co-regulation of genes in microarray experiments may imply common transcriptional regulation by sequence-specific DNA-binding transcriptional factors. We have computationally analyzed the transcription factor binding sites (TFBS) in a previously reported macaque luteal microarray gene set (n = 15) that are common targets of luteotropin (luteinizing hormone (LH) and human chorionic gonadotropin (hCG)) and luteolysin (prostaglandin (PG) F-2 alpha). This in silico approach can reveal transcriptional networks that control these important genes which are representative of the interplay between luteotropic and luteolytic factors in the control of luteal function. Our computational analyses revealed 6 matrix families whose binding sites are significantly over-represented in promoters of these genes. The roles of these factors are discussed, which might help to understand the transcriptional regulatory network in the control of luteal function. These factors might be promising experimental targets for investigation of human luteal insufficiency. (C) 2012 Elsevier B.V. All rights reserved.

Annexin A2 and PSF proteins interact with p53 IRES and regulate translation of p53 mRNA

p53 mRNA has been shown to be translated into two isoforms, full-length p53 (FL-p53) and a truncated isoform Delta N-p53, which modulates the functions of FL-p53 and also has independent functions. Previously, we have shown that translation of p53 and Delta N-p53 can be initiated at Internal Ribosome Entry Sites (IRES). These two IRESs were shown to regulate the translation of p53 and Delta N-p53 in a distinct cell-cycle phase-dependent manner. Earlier observations from our laboratory also suggest that the structural integrity of the p53 RNA is critical for IRES function and is compromised by mutations that affect the structure as well as RNA protein interactions. In the current study, using RNA affinity approach we have identified Annexin A2 and PTB associated Splicing Factor (PSF/SFPQ) as novel ITAFs for p53 IRESs. We have showed that the purified Annexin A2 and PSF proteins specifically bind to p53 IRES elements. Interestingly, in the presence of calcium ions Annexin A2 showed increased binding with p53 IRES. Immunopulldown experiments suggest that these two proteins associate with p53 mRNA ex vivo as well. Partial knockdown of Annexin A2 and PSF showed decrease in p53 IRES activity and reduced levels of both the p53 isoforms. More importantly the interplay between Annexin A2, PSF and PTB proteins for binding to p53mRNA appears to play a crucial role in IRES function. Taken together, our observations suggest pivotal role of two new trans-acting factors in regulating the p53-IRES function, which in turn influences the synthesis of p53 isoforms.

On the relation between K-means and PLSA

Non-negative matrix factorization [5](NMF) is a well known tool for unsupervised machine learning. It can be viewed as a generalization of the K-means clustering, Expectation Maximization based clustering and aspect modeling by Probabilistic Latent Semantic Analysis (PLSA). Specifically PLSA is related to NMF with KL-divergence objective function. Further it is shown that K-means clustering is a special case of NMF with matrix L2 norm based error function. In this paper our objective is to analyze the relation between K-means clustering and PLSA by examining the KL-divergence function and matrix L2 norm based error function.

Tradeoff of average service cost and average delay for the state dependent M/M/1 queue

The optimal tradeoff between average service cost rate and average delay, is addressed for a M/M/1 queueing model with queue-length dependent service rates, chosen from a finite set. We provide an asymptotic characterization of the minimum average delay, when the average service cost rate is a small positive quantity V more than the minimum average service cost rate required for stability. We show that depending on the value of the arrival rate, the assumed service cost rate function, and the possible values of the service rates, the minimum average delay either a) increases only to a finite value, b) increases without bound as log(1/V), or c) increases without bound as 1/V, when V down arrow 0. We apply the analysis to a flow-level resource allocation model for a wireless downlink. We also investigate the asymptotic tradeoff for a sequence of policies which are obtained from an approximate fluid model for the M/M/1 queue.

Case for multiple views of function in design based on a common definition

Functions are important in designing. However, several issues hinder progress with the understanding and usage of functions: lack of a clear and overarching definition of function, lack of overall justifications for the inevitability of the multiple views of function, and scarcity of systematic attempts to relate these views with one another. To help resolve these, the objectives of this research are to propose a common definition of function that underlies the multiple views in literature and to identify and validate the views of function that are logically justified to be present in designing. Function is defined as a change intended by designers between two scenarios: before and after the introduction of the design. A framework is proposed that comprises the above definition of function and an empirically validated model of designing, extended generate, evaluate, modify, and select of state-change, and an action, part, phenomenon, input, organ, and effect model of causality (Known as GEMS of SAPPhIRE), comprising the views of activity, outcome, requirement-solution-information, and system-environment. The framework is used to identify the logically possible views of function in the context of designing and is validated by comparing these with the views of function in the literature. Describing the different views of function using the proposed framework should enable comparisons and determine relationships among the various views, leading to better understanding and usage of functions in designing.

In vitro and in vivo characterization of designed immunogens derived from the CD-helix of the stem of influenza hemagglutinin

The conserved stem domain of influenza virus hemagglutinin (HA) is a target for broadly neutralizing antibodies and a potential vaccine antigen for induction of hetero-subtypic protection. The epitope of 12D1, a previously reported bnAb neutralizing several H3 subtype influenza strains, was putatively mapped to residues 76-106 of the CD-helix, also referred to as long alpha helix (LAH) of the HA stem. A peptide derivative consisting of wt-LAH residues 76-130 conjugated to keyhole limpet hemocyanin was previously shown to confer robust protection in mice against challenge with influenza strains of subtypes H3, H1, and H5 which motivated the present study. We report the design of multiple peptide derivatives of LAH with or without heterologous trimerization sequences and show that several of these are better folded than wt-LAH. However, in contrast to the previous study immunization of mice with wt-LAH resulted in negligible protection against a lethal homologous virus challenge, while some of the newly designed immunogens could confer weak protection. Combined with structural analysis of HA, our data suggest that in addition to LAH, other regions of HA are likely to significantly contribute to the epitope for 12D1 and will be required to elicit robust protection. In addition, a dynamic, flexible conformation of isolated LAH peptide may be required for eliciting a functional anti-viral response. Proteins 2013; 81:1759-1775. (c) 2013 Wiley Periodicals, Inc.

The effect of cell size and channel density on neuronal information encoding and energy efficiency

Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

Shape-function-relationship (SFR) framework for semantic interoperability of product model

The problem of semantic interoperability arises while integrating applications in different task domains across the product life cycle. A new shape-function-relationship (SFR) framework is proposed as a taxonomy based on which an ontology is developed. Ontology based on the SFR framework, that captures explicit definition of terminology and knowledge relationships in terms of shape, function and relationship descriptors, offers an attractive approach for solving semantic interoperability issue. Since all instances of terms are based on single taxonomy with a formal classification, mapping of terms requires a simple check on the attributes used in the classification. As a preliminary study, the framework is used to develop ontology of terms used in the aero-engine domain and the ontology is used to resolve the semantic interoperability problem in the integration of design and maintenance. Since the framework allows a single term to have multiple classifications, handling context dependent usage of terms becomes possible. Automating the classification of terms and establishing the completeness of the classification scheme are being addressed presently.

Photovoltaic structures using thermally evaporated SnS and CdS thin films

Polycrystalline tin sulfide thin films were prepared by thermal evaporation technique. The films grown at substrate temperature of 300 degrees C had an orthorhombic crystal structure with strong preferred orientation along (111) plane. Electrical resistivity of the deposited films was about 32.5 Omega cm with a direct optical band gap of 1.33 eV. Carrier concentration and mobility of charge carriers estimated from the Hall measurement were found to be 6.24 x 10(15) cm(-3) and 30.7 cm(2)V(-1) s(-1) respectively. Heterojunction solar cells were fabricated in superstrate configuration using thermally evaporated SnS as an absorber layer and CdS, In: CdS as window layer. The resistivity of pure CdS thin film of a thickness of 320 nm was about 1-2 Omega cm and was reduced to 40 x 10(-3) Omega cm upon indium doping. The fabricated solar cells were characterized using solar simulator. The solar cells with indium doped CdS window layer showed improved performance as compared to pure CdS window layer. The best device had a conversion efficiency of 0.4% and a fill factor of 33.5%. (C) 2013 Elsevier B.V. All rights reserved.

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by Network Structure

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define `synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in `synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony.

A finite element method for the Saint-Venant torsion and bending problems for prismatic beams

In this work, we present a finite element formulation for the Saint-Venant torsion and bending problems for prismatic beams. The torsion problem formulation is based on the warping function, and can handle multiply-connected regions (including thin-walled structures), compound and anisotropic bars. Similarly, the bending formulation, which is based on linearized elasticity theory, can handle multiply-connected domains including thin-walled sections. The torsional rigidity and shear centers can be found as special cases of these formulations. Numerical results are presented to show the good coarse-mesh accuracy of both the formulations for both the displacement and stress fields. The stiffness matrices and load vectors (which are similar to those for a variable body force in a conventional structural mechanics problem) in both formulations involve only domain integrals, which makes them simple to implement and computationally efficient. (C) 2014 Elsevier Ltd. All rights reserved.

Unraveling the Intricate Organization of Mammalian Mitochondrial Presequence Translocases: Existence of Multiple Translocases for Maintenance of Mitochondrial Function

Mitochondria are indispensable organelles implicated in multiple aspects of cellular processes, including tumorigenesis. Heat shock proteins play a critical regulatory role in accurately delivering the nucleus-encoded proteins through membrane-bound presequence translocase (Tim23 complex) machinery. Although altered expression of mammalian presequence translocase components had been previously associated with malignant phenotypes, the overall organization of Tim23 complexes is still unsolved. In this report, we show the existence of three distinct Tim23 complexes, namely, B1, B2, and A, involved in the maintenance of normal mitochondrial function. Our data highlight the importance of Magmas as a regulator of translocase function and in dynamically recruiting the J-proteins DnaJC19 and DnaJC15 to individual translocases. The basic housekeeping function involves translocases B1 and B2 composed of Tim17b isoforms along with DnaJC19, whereas translocase A is nonessential and has a central role in oncogenesis. Translocase B, having a normal import rate, is essential for constitutive mitochondrial functions such as maintenance of electron transport chain complex activity, organellar morphology, iron-sulfur cluster protein biogenesis, and mitochondrial DNA. In contrast, translocase A, though dispensable for housekeeping functions with a comparatively lower import rate, plays a specific role in translocating oncoproteins lacking presequence, leading to reprogrammed mitochondrial functions and hence establishing a possible link between the TIM23 complex and tumorigenicity.