The determination of stem cell fate by 3D scaffold structures through the control of cell shape

Stem cell response to a library of scaffolds with varied 3D structures was investigated. Microarray screening revealed that each type of scaffold structure induced a unique gene expression signature in primary human bone marrow stromal cells (hBMSCs). Hierarchical cluster analysis showed that treatments sorted by scaffold structure and not by polymer chemistry suggesting that scaffold structure was more influential than scaffold composition. Further, the effects of scaffold structure on hBMSC function were mediated by cell shape. Of all the scaffolds tested, only scaffolds with a nanofibrous morphology were able to drive the hBMSCs down an osteogenic lineage in the absence of osteogenic supplements. Nanofiber scaffolds forced the hBMSCs to assume an elongated, highly branched morphology. This same morphology was seen in osteogenic controls where hBMSCs were cultured on flat polymer films in the presence of osteogenic supplements (OS). In contrast, hBMSCs cultured on flat polymer films in the absence of OS assumed a more rounded and less-branched morphology. These results indicate that cells are more sensitive to scaffold structure than previously appreciated and suggest that scaffold efficacy can be optimized by tailoring the scaffold structure to force cells into morphologies that direct them to differentiate down the desired lineage. Published by Elsevier Ltd.

Analysis of the hierarchical structure of the B. subtilis transcriptional regulatory network

The transcriptional regulation of gene expression is orchestrated by complex networks of interacting genes. Increasing evidence indicates that these `transcriptional regulatory networks' (TRNs) in bacteria have an inherently hierarchical architecture, although the design principles and the specific advantages offered by this type of organization have not yet been fully elucidated. In this study, we focussed on the hierarchical structure of the TRN of the gram-positive bacterium Bacillus subtilis and performed a comparative analysis with the TRN of the gram-negative bacterium Escherichia coli. Using a graph-theoretic approach, we organized the transcription factors (TFs) and sigma-factors in the TRNs of B. subtilis and E. coli into three hierarchical levels (Top, Middle and Bottom) and studied several structural and functional properties across them. In addition to many similarities, we found also specific differences, explaining the majority of them with variations in the distribution of s-factors across the hierarchical levels in the two organisms. We then investigated the control of target metabolic genes by transcriptional regulators to characterize the differential regulation of three distinct metabolic subsystems (catabolism, anabolism and central energy metabolism). These results suggest that the hierarchical architecture that we observed in B. subtilis represents an effective organization of its TRN to achieve flexibility in response to a wide range of diverse stimuli.

Hierarchical modelling of acclimatory processesstar, open

The term acclimation has been used with several connotations in the field of acclimatory physiology. An attempt has been made, in this paper, to define precisely the term “acclimation” for effective modelling of acclimatory processes. Acclimation is defined with respect to a specific variable, as cumulative experience gained by the organism when subjected to a step change in the environment. Experimental observations on a large number of variables in animals exposed to sustained stress, show that after initial deviation from the basal value (defined as “growth”), the variables tend to return to basal levels (defined as “decay”). This forms the basis for modelling biological responses in terms of their growth and decay. Hierarchical systems theory as presented by Mesarovic, Macko & Takahara (1970) facilitates modelling of complex and partially characterized systems. This theory, in conjunction with “growth-decay” analysis of biological variables, is used to model temperature regulating system in animals exposed to cold. This approach appears to be applicable at all levels of biological organization. Regulation of hormonal activity which forms a part of the temperature regulating system, and the relationship of the latter with the “energy” system of the animal of which it forms a part, are also effectively modelled by this approach. It is believed that this systematic approach would eliminate much of the current circular thinking in the area of acclimatory physiology.

A Computationally Efficient PWM Algorithm for Multilevel Inverters

Centred space vector PWM (CSVPWM) technique is popularly used for three level voltage source inverters. The reference voltage vector is synthesized by time-averaging of the three nearest voltage vectors produced by the inverter. Identifying the three voltage vectors, and calculation of the dwelling time for each vector are both computationally intensive. This paper analyses the process of PWM generation in CSVPWM. This analysis breaks up a three-level inverter into six different conceptual two level inverters in different regions of the fundamental cycle. Control of 3-level inverter is viewed as the control of the appropriate 2-level inverter. The analysis leads to a systematic simplification of the computations involved, finally resulting in a computationally efficient PWM algorithm. This algorithm exploits the equivalence between triangle comparison and space vector approaches to PWM generation. This algorithm does not involve any 3-phase/2-phase or 2-phase/3-phase transformation. This also does not involve any transformation from rectangular to polar coordinates, and vice versa. Further no evaluation of trigonometric functions is necessary. This algorithm also provides for the mitigation of DC neutral point unbalance, and is well suited to digital implementation. Simulation and experimental results are presented.

Choice of Classifiers in Hierarchical Recognition of Online Handwritten Kannada and Tamil Aksharas

In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.

Multilevel inverters for low-power application

Multilevel inverters are an attractive solution in the medium-voltage and high-power applications. However in the low-power range also it can be a better solution compared to two-level inverters, if MOSFETs are used as devices switching in the order of 100 kHz. The effect of clamping diodes in the diode-clamped multilevel inverters play an important role in determining its efficiency. Power loss introduced by the reverse recovery of MOSFET body diode prohibits the use of MOSFET in hard-switched inverter legs. A technique of avoiding reverse recovery loss of MOSFET body diode in a three-level neutral point clamped inverter is suggested. The use of multilevel inverters topology enables operation at high switching frequency without sacrificing efficiency. High switching frequency of operation reduces the output filter requirement, which in turn helps in reducing the size of the inverter. This study elaborates the trade-off analysis to quantify the suitability of multilevel inverters in the low-power applications. Advantages of using a MOSFET-based three-level diode-clamped inverter for a PM motor drive and UPS systems are discussed.

Synthesis and structural characterization of two-dimensional hierarchical covellite nano-structures

We report a simple, template free and low-temperature hydrothermal reaction pathway using Cu(II) - thiourea complex (prepared in situ from copper (II) chloride and thiourea as precursors) and citric acid as complexing agent to synthesize two-dimensional hierarchical nano-structures of covellite (CuS). The product was characterized with the help of X-ray powder diffraction (XRD), scanning electron microscopy (SEM), energy dispersive analysis of X-ray spectroscopy (EDAX) and X-ray photoelectron spectroscopy (XPS). The concentration of citric acid in the hydrothermal precursor solution was seen to have a profound effect on the nanostructure of the product generated. Based on the outcoming product nano-architecture at different concentration of the ionic surfactant in the hydrothermal precursor solution a possible mechanism suited for reaction and further nucleation is also discussed. (C) 2012 Elsevier B.V. All rights reserved.

Design and analysis of a peer-to-peer based distributed clock synchronisation protocol for wireless sensor networks

Clock synchronisation is an important requirement for various applications in wireless sensor networks (WSNs). Most of the existing clock synchronisation protocols for WSNs use some hierarchical structure that introduces an extra overhead due to the dynamic nature of WSNs. Besides, it is difficult to integrate these clock synchronisation protocols with sleep scheduling scheme, which is a major technique to conserve energy. In this paper, we propose a fully distributed peer-to-peer based clock synchronisation protocol, named Distributed Clock Synchronisation Protocol (DCSP), using a novel technique of pullback for complete sensor networks. The pullback technique ensures that synchronisation phases of any pair of clocks always overlap. We have derived an exact expression for a bound on maximum synchronisation error in the DCSP protocol, and simulation study verifies that it is indeed less than the computed upper bound. Experimental study using a few TelosB motes also verifies that the pullback occurs as predicted.

A Hybrid Multilevel Inverter System Based on Dodecagonal Space Vectors for Medium Voltage IM Drives

Dodecagonal (12-sided) space vector pulsewidth modulation (PWM) schemes are characterized by the complete absence of (6n +/- 1)th-order harmonics (for odd n) in the phase voltages, within the linear modulation range and beyond, including over-modulation. This paper presents a new topology suitable for the realization of such multilevel inverter schemes for induction motor (IM) drives, by cascading two-level inverters with flying-capacitor-inverter fed floating H-bridge cells. Now, any standard IM may be used to get the dodecagonal operation which hitherto was possible only with open-end winding IM. To minimize the current total harmonic distortion (THD), a strategy for synchronous PWM is also proposed. It is shown that the proposed method is capable of obtaining better THD figures, compared to conventional dodecagonal schemes. The topology and the PWM strategy are validated through analysis and subsequently verified experimentally.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Hierarchical sampling for metastable conformers determines biomolecular recognition: the case of malectin and diglucosylated N-glycan interactions

Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin's exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate-aromatic interactions including CH-pi and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to beta-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Genetic analysis of Indian tasar silkmoth (Antheraea mylitta) populations

Indian tasar silkmoth, Antheraea mylitta is an economically important wild silkmoth species distributed across India. A number of morphologically and ethologically well-defined ecotypes are known for this species that differ in their primary food plant specificity. Most of these ecotypes do not interbreed in nature, but are able to produce offspring under captive conditions. Microsatellite markers were developed for A. mylitta, and out of these, ten well-behaved microsatellite loci were used to analyze the population structure of different ecoraces. A total of 154 individual moths belonging to eight different ecoraces, were screened at each locus. Hierarchical analysis of population structure using Analysis of MOlecular VAriance (AMOVA) revealed significant structuring (F-ST = 0.154) and considerable inbreeding (F-IS = 0.505). A significant isolation by distance was also observed. The number of possible population clusters was investigated using distance method, Bayesian algorithm and self organization maps (SOM). The first two methods revealed two distinct clusters, whereas the SOM showed the different ecoraces not to be clearly differentiated. These results suggest that although there is a large degree of phenotypic variation among the different ecoraces of A. mylitta, genetically they are not very different, and the phenotypic differences may largely be a result of their respective ecology.

Bimodality and re-entrant behaviour in the hierarchical self-assembly of polymeric nanoparticles

We show that a film of a suspension of polymer grafted nanoparticles on a liquid substrate can be employed to create two-dimensional nanostructures with a remarkable variation in the pattern length scales. The presented experiments also reveal the emergence of concentration-dependent bimodal patterns as well as re-entrant behaviour that involves length scales due to dewetting and compositional instabilities. The experimental observations are explained through a gradient dynamics model consisting of coupled evolution equations for the height of the suspension film and the concentration of polymer. Using a Flory-Huggins free energy functional for the polymer solution, we show in a linear stability analysis that the thin film undergoes dewetting and/or compositional instabilities depending on the concentration of the polymer in the solution. We argue that the formation via `hierarchical self-assembly' of various functional nanostructures observed in different systems can be explained as resulting from such an interplay of instabilities.

Reduced common-mode voltage operation of a new seven-level hybrid multilevel inverter topology with a single DC voltage source

In this study, analysis of extending the linear modulation range of a zero common-mode voltage (CMV) operated n-level inverter by allowing reduced CMV switching is presented. A new hybrid seven-level inverter topology with a single DC supply is also presented in this study and inverter operation for zero and reduced CMV is analysed. Each phase of the inverter is realised by cascading two three-level flying capacitor inverters with a half-bridge module in between. Proposed inverter topology is operated with zero CMV for modulation index <86% and is operated with a CMV magnitude of V-dc/18 to extend the modulation range up to 96%. Experimental results are presented for zero CMV operation and for reduced common voltage operation to extend the linear modulation range. A capacitor voltage balancing algorithm is designed utilising the pole voltage redundancies of the inverter, which works for every sampling instant to correct the capacitor voltage irrespective of load power factor and modulation index. The capacitor voltage balancing algorithm is tested for different modulation indices and for various transient conditions, to validate the proposed topology.