Small-Angle Neutron-Scattering Studies of Mixed Micellar Structures Made of Dimeric Surfactants Having Imidazolium and Ammonium Headgroups

Planar imidazolium cation based gemini surfactants 16-Im-n-Im-16], 2Br(-) (where n = 2, 3, 4, 5, 6, 8, 10, and 12), exhibit different morphologies and internal packing arrangements by adopting different supramolecular assemblies in aqueous media depending on their number of spacer methylene units (CH2)(n). Detailed measurements of the small-angle neutron-scattering (SANS) cross sections from different imidazolium-based surfactant micelles in aqueous media (D2O) are reported. The SANS data, containing the information of aggregation behavior of such surfactants in the molecular level, have been analyzed on the basis of the Hayter and Penfold model for the macro ion solution to compute the interparticle structure factor S(Q) taking into account the screened Coulomb interactions between the dimeric surfactant micelles. The characteristic changes in the SANS spectra of the dimeric surfactant with n = 4 due to variation of temperature have also been investigated. These data are then compared with the SANS characterization data of the corresponding gemini micelles containing tetrahedral ammonium ion based polar headgroups. The critical micellar concentration of each surfactant micelle (cmc) has been determined using pyrene as an extrinsic fluorescence probe. The variation of cmc as a function of spacer chain length has been explained in terms of conformational variation and progressive looping of the spacer into the micellar interior upon increasing the n values. Small-angle neutron-scattering (SANS) cross sections from different mixed micelles composed of surfactants with ammonium headgroups, 16-A(0), 16-Am-n-Am-16], 2Br(-) (where n = 4), 16-I-0, and 16-Im-n-Im-16], 2Br(-) (where n = 4), in aqueous media (D2O) have also been analyzed. The aggregate composition matches with that predicted from the ideal mixing model.

Distinct Disulfide Isomers of mu-Conotoxins KIIIA and KIIIB Block Voltage-Gated Sodium Channels

In the preparation of synthetic conotoxins containing multiple disulfide bonds, oxidative folding can produce numerous permutations of disulfide bond connectivities. Establishing the native disulfide connectivities thus presents a significant challenge when the venom-derived peptide is not available, as is increasingly the case when conotoxins are identified from cDNA sequences. Here, we investigate the disulfide connectivity of mu-conotoxin KIIIA, which was predicted originally to have a C1-C9,C2-C15,C4-C16] disulfide pattern based on homology with closely related mu-conotoxins. The two major isomers of synthetic mu-KIIIA formed during oxidative folding were purified and their disulfide connectivities mapped by direct mass spectrometric collision-induced dissociation fragmentation of the disulfide-bonded polypeptides. Our results show that the major oxidative folding product adopts a C1-C15,C2-C9,C4-C16] disulfide connectivity, while the minor product adopts a C1-C16,C2-C9,C4-C15] connectivity. Both of these peptides were potent blockers of Na(v)1.2 (K-d values of 5 and 230 nM, respectively). The solution structure for mu-KIIIA based on nuclear magnetic resonance data was recalculated with the C1-C15,C2-C9,C4-C16] disulfide pattern; its structure was very similar to the mu-KIIIA structure calculated with the incorrect C1-C9,C2-C15,C4-C16] disulfide pattern, with an alpha-helix spanning residues 7-12. In addition, the major folding isomers of mu-KIIIB, an N-terminally extended isoform of mu-KIIIA, identified from its cDNA sequence, were isolated. These folding products had the same disulfide connectivities as mu-KIIIA, and both blocked Na(v)1.2 (K-d values of 470 and 26 nM, respectively). Our results establish that the preferred disulfide pattern of synthetic mu-KIIIA and mu-KIIIB folded in vitro is 1-5/2-4/3-6 but that other disulfide isomers are also potent sodium channel blockers. These findings raise questions about the disulfide pattern(s) of mu-KIIIA in the venom of Conus kinoshitai; indeed, the presence of multiple disulfide isomers in the venom could provide a means of further expanding the snail's repertoire of active peptides.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Threshold voltage model for accumulation mode polycrystalline SOI MOSFETs and comparisons with experimental results

In this paper, a simple but accurate semi analytical charge sheet model is presented for threshold voltage of accumulation mode polycrystalline silicon on insulator (PSOI) MOSFETs. In this model, we define the threshold voltage (V-T) of the polysilicon accumulation mode MOSFET as the gate voltage required to raise the surface potential (phi(s)) to a value phi(sT) necessary to overcome the charge trapping in the grain boundary and to create channel accumulation charge that is equal to the channel accumulation charge available in the case of single crystal silicon accumulation mode MOSFET at that phi(sT). The correctness of the model is demonstrated by comparing the theoretically estimated values of threshold voltage with the experimentally measured threshold voltages on the accumulation mode PSOI MOSFETs fabricated in the laboratory using LPCVD polysilicon layers doped with boron to achieve dopant densities in the range 3.3 x 10(-15)-5 x 10(17)/cm(3). Further, it is shown that the threshold voltage values of accumulation mode PSOI MOSFETs predicted by the present model match very closely with the experimental results, better than those obtained with the models previously reported in the literature. (C) 2012 Elsevier B.V. All rights reserved.

Fatigue Crack Growth Study and Remaining Life Assessment of High Strength and Ultra High Strength Concrete Beams

This paper presents the details of crack growth study and remaining life assessment of concrete specimens made up of high strength concrete (HSC, HSC1) and ultra high strength concrete (UHSC). Flexural fatigue tests have been conducted on HSC, HSC1 and UHSC beams under constant amplitude loading with a stress ratio of 0.2. It is observed from the studies that (i) the failure patterns of HSC1 and UHSC beams indicate their ductility as the member was intact till the crack propagated up to 90% of the beam depth and (ii) the remaining life decreases with increase of notch depth (iii) the failure of the specimen is influenced by the frequency of loading. A ``Net K'' model has been proposed by using non-linear fracture mechanics principles for crack growth analysis and remaining life prediction. SIF (K) has been computed by using the principle of superposition. SIP due to the cohesive forces applied on the effective crack face inside the process zone has been obtained through Green's function approach by applying bi-linear tension softening relationship to consider the cohesive the stresses acting ahead of the crack tip. Remaining life values have been have been predicted and compared with the corresponding experimental values and observed that they are in good agreement with each other.

Network properties of decoys and CASP predicted models: a comparison with native protein structures

Protein structure space is believed to consist of a finite set of discrete folds, unlike the protein sequence space which is astronomically large, indicating that proteins from the available sequence space are likely to adopt one of the many folds already observed. In spite of extensive sequence-structure correlation data, protein structure prediction still remains an open question with researchers having tried different approaches (experimental as well as computational). One of the challenges of protein structure prediction is to identify the native protein structures from a milieu of decoys/models. In this work, a rigorous investigation of Protein Structure Networks (PSNs) has been performed to detect native structures from decoys/ models. Ninety four parameters obtained from network studies have been optimally combined with Support Vector Machines (SVM) to derive a general metric to distinguish decoys/models from the native protein structures with an accuracy of 94.11%. Recently, for the first time in the literature we had shown that PSN has the capability to distinguish native proteins from decoys. A major difference between the present work and the previous study is to explore the transition profiles at different strengths of non-covalent interactions and SVM has indeed identified this as an important parameter. Additionally, the SVM trained algorithm is also applied to the recent CASP10 predicted models. The novelty of the network approach is that it is based on general network properties of native protein structures and that a given model can be assessed independent of any reference structure. Thus, the approach presented in this paper can be valuable in validating the predicted structures. A web-server has been developed for this purpose and is freely available at http://vishgraph.mbu.iisc.ernet.in/GraProStr/PSN-QA.html.

Modeling harvest rates and numbers from age and sex ratios: A demonstration for elephant populations

Illegal harvest rates of wildlife populations are often unknown or difficult to estimate from field data due to under-reporting or incomplete detection of carcasses. This is especially true for elephants that are killed for ivory or in conflicts with people. We describe a method to infer harvest rates from coarse field data of three population parameters, namely, adult female to male ratio, male old-adult to young-adult ratio, and proportion of adult males in the population using Jensen's (2000) 2-sex, density-dependent Leslie matrix model. The specific combination of male and female harvest rates and numbers can be determined from the history of harvest and estimate of population size. We applied this technique to two populations of elephants for which data on age structure and records of mortality were available-a forest-dwelling population of the Asian elephant (at Nagarahole, India) and an African savannah elephant population (at Samburu, Kenya) that had experienced male-biased harvest regimes over 2-3 decades. For the Nagarahole population, the recorded numbers of male and female elephants killed illegally during 1981-2000 were 64% and 88% of the values predicted by the model, respectively, implying some non-detection or incomplete reporting while for the Samburu population the recorded and modeled numbers of harvest during 1990-1999 closely matched. This technique, applicable to any animal population following logistic growth model, can be especially useful for inferring illegal harvest numbers of forest elephants in Africa and Asia.

Constraints on Be-10 and Ca-41 distribution in the early solar system from Al-26 and Be-10 studies of Efremovka CAIs

Three refractory coarse grained CAIs from the Efremovka CV3 chondrite, one (E65) previously shown to have formed with live Ca-41, were studied by ion microprobe for their Al-26-Mg-26 and Be-10-B-10 systematic in order to better understand the origin of Be-10. The high precision Al-Mg data and the inferred Al-26/Al-27 values attest that the precursors of the three CAIs evolved in the solar nebula over a period of few hundred thousand years before last melting-crystallization events. The initial Be-10/Be-9 ratios and delta B-10 values defined by the Be-10 isochrons for the three Efremovka CAIs are similar within errors. The CAI Be-10 abundance in published data underscores the large range for initial Be-10/Be-9 ratios. This is contrary to the relatively small range of Al-26/Al-27 variations in CAIs around the canonical ratio. Two models that could explain the origin of this large Be-10/Be-9 range are assessed from the collateral variations predicted for the initial delta B-10 values: (i) closed system decay of Be-10 from a ``canonical'' Be-10/Be-9 ratio and (ii) formation of CAIs from a mixture of solid precursors and nebula gas irradiated during up to a few hundred thousand years. The second scenario is shown to be the most consistent with the data. This shows that the major fraction of Be-10 in CAIs was produced by irradiation of refractory grains, while contributions of galactic cosmic rays trapping and early solar wind irradiation are less dominant. The case for Be-10 production by solar cosmic rays irradiation of solid refractory precursors poses a conundrum for Ca-41 because the latter is easily produced by irradiation and should be more abundant than what is observed in CAIs. Be-10 production by irradiation from solar energetic particles requires high Ca-41 abundance in early solar system, however, this is not observed in CAIs. (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.

On the mechanism of room temperature superconductivity in substitutionally doped graphene

A combined mechanism involving phononic and electronic processes is suggested for superconductivity in substitutionally doped graphene. The electronic mechanism is similar to the one used for doped fullerene system, MxC60 (M K, Rb, etc.) and triggered by bond polarization due to doped impurities such as B or Al. It is found that on increasing the doping, the superconducting critical temperature can be raised to room temperature. The details of the combined model are given along with the predicted values of T-c. (C) 2013 Elsevier Ltd. All rights reserved,

Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions

Background: The number of genome-wide association studies (GWAS) has increased rapidly in the past couple of years, resulting in the identification of genes associated with different diseases. The next step in translating these findings into biomedically useful information is to find out the mechanism of the action of these genes. However, GWAS studies often implicate genes whose functions are currently unknown; for example, MYEOV, ANKLE1, TMEM45B and ORAOV1 are found to be associated with breast cancer, but their molecular function is unknown. Results: We carried out Bayesian inference of Gene Ontology (GO) term annotations of genes by employing the directed acyclic graph structure of GO and the network of protein-protein interactions (PPIs). The approach is designed based on the fact that two proteins that interact biophysically would be in physical proximity of each other, would possess complementary molecular function, and play role in related biological processes. Predicted GO terms were ranked according to their relative association scores and the approach was evaluated quantitatively by plotting the precision versus recall values and F-scores (the harmonic mean of precision and recall) versus varying thresholds. Precisions of similar to 58% and similar to 40% for localization and functions respectively of proteins were determined at a threshold of similar to 30 (top 30 GO terms in the ranked list). Comparison with function prediction based on semantic similarity among nodes in an ontology and incorporation of those similarities in a k nearest neighbor classifier confirmed that our results compared favorably. Conclusions: This approach was applied to predict the cellular component and molecular function GO terms of all human proteins that have interacting partners possessing at least one known GO annotation. The list of predictions is available at http://severus.dbmi.pitt.edu/engo/GOPRED.html. We present the algorithm, evaluations and the results of the computational predictions, especially for genes identified in GWAS studies to be associated with diseases, which are of translational interest.

On the possible variation of the lightning striking distance as assumed in the IEC lightning protection standard as a function of structure height

The effect of structure height on the lightning striking distance is estimated using a lightning strike model that takes into account the effect of connecting leaders. According to the results, the lightning striking distance may differ significantly from the values assumed in the IEC standard for structure heights beyond 30m. However, for structure heights smaller than about 30m, the results show that the values assumed by IEC do not differ significantly from the predictions based on a lightning attachment model taking into account the effect of connecting leaders. However, since IEC assumes a smaller striking distance than the ones predicted by the adopted model one can conclude that the safety is not compromised in adhering to the IEC standard. Results obtained from the model are also compared with Collection Volume Method (CVM) and other commonly used lightning attachment models available in the literature. The results show that in the case of CVM the calculated attractive distances are much larger than the ones obtained using the physically based lightning attachment models. This indicates the possibility of compromising the lightning protection procedures when using CVM. (C) 2014 Elsevier B.V. All rights reserved.

Optimization of degree of sphericity of primary phase during cooling slope casting of A356 Al alloy: Taguchi method and regression analysis

The present work presents the results of experimental investigation of semi-solid rheocasting of A356 Al alloy using a cooling slope. The experiments have been carried out following Taguchi method of parameter design (orthogonal array of L-9 experiments). Four key process variables (slope angle, pouring temperature, wall temperature, and length of travel of the melt) at three different levels have been considered for the present experimentation. Regression analysis and analysis of variance (ANOVA) has also been performed to develop a mathematical model for degree of sphericity evolution of primary alpha-Al phase and to find the significance and percentage contribution of each process variable towards the final outcome of degree of sphericity, respectively. The best processing condition has been identified for optimum degree of sphericity (0.83) as A(3), B-3, C-2, D-1 i.e., slope angle of 60 degrees, pouring temperature of 650 degrees C, wall temperature 60 degrees C, and 500 mm length of travel of the melt, based on mean response and signal to noise ratio (SNR). ANOVA results shows that the length of travel has maximum impact on degree of sphericity evolution. The predicted sphericity obtained from the developed regression model and the values obtained experimentally are found to be in good agreement with each other. The sphericity values obtained from confirmation experiment, performed at 95% confidence level, ensures that the optimum result is correct and also the confirmation experiment values are within permissible limits. (c) 2014 Elsevier Ltd. All rights reserved.

Crack stability in edge-notched clamped beam specimens: modeling and experiments

Stability of a fracture toughness testing geometry is important to determine the crack trajectory and R-curve behavior of the specimen. Few configurations provide for inherent geometric stability, especially when the specimen being tested is brittle. We propose a new geometrical construction called the single edge notched clamped bend specimen (SENCB), a modified form of three point bending, yielding stable cracking under load control. It is shown to be particularly suitable for small-scale structures which cannot be made free-standing, (e.g., thin films, coatings). The SENCB is elastically clamped at the two ends to its parent material. A notch is inserted at the bottom center and loaded in bending, to fracture. Numerical simulations are carried out through extended finite element method to derive the geometrical factor f(a/W) and for different beam dimensions. Experimental corroborations of the FEM results are carried out on both micro-scale and macro-scale brittle specimens. A plot of vs a/W, is shown to rise initially and fall off, beyond a critical a/W ratio. The difference between conventional SENB and SENCB is highlighted in terms of and FEM simulated stress contours across the beam cross-section. The `s of bulk NiAl and Si determined experimentally are shown to match closely with literature values. Crack stability and R-curve effect is demonstrated in a PtNiAl bond coat sample and compared with predicted crack trajectories from the simulations. The stability of SENCB is shown for a critical range of a/W ratios, proving that it can be used to get controlled crack growth even in brittle samples under load control.