Express Virtual Channels with Capacitively Driven Global Links

Networks on chip must deliver high bandwidth at low latencies while keeping within a tight power envelope. Using express virtual channels for flow control improves energy-delay throughput by letting packets bypass intermediate routers, but EVCs have key limitations. Nochi (NoC with hybrid interconnect) overcomes these limitations by transporting data payloads and control information on separate planes, optimized for bandwidth and latency respectively.     

Differential regulation of redox proteins and chaperones in HbEβ-thalassemia erythrocyte proteome

Purpose: In (hemoglobin, Hb) HbEβ‐thalassemia, HbE (β‐26 Glu→Lys) interacts with β‐thalassemia to produce clinical manifestation of varying severity. This is the first proteomic effort to study changes in protein levels of erythrocytes isolated from HbEβ‐thalassemic patients compared to normal. Experimental design: We have used 2‐DE and MALDI‐MS/MS‐based techniques to investigate the differential proteome profiling of membrane and Hb‐depleted fraction of cytosolic proteins of erythrocytes isolated from the peripheral blood samples of HbEβ‐thalassemia patients and normal volunteers. Results: Our study showed that redox regulators such as peroxiredoxin 2, Cu‐Zn superoxide dismutase and thioredoxin and chaperones such as α‐hemoglobin stabilizing protein and HSP‐70 were upregulated in HbEβ‐thalassemia. We have also observed larger amounts of membrane associated globin chains and indications of disruption of spectrin‐based junctional complex in the membrane skeleton of HbEβ‐thalassemic erythrocytes upon detection of low molecular weight fragments of β‐spectrin and decrease in β‐actin and dematin content. Conclusion and clinical relevance: We have observed interesting changes in the proteomic levels of redox regulators and chaperons in the thalassemic hemolysates and have observed strong correlation or association of the extent of such proteomic changes with HbE levels. This could be important in understanding the role of HbE in disease progression and pathophysiology.     

On Scene Segmentation and Histograms-Based Curve Evolution

We consider curve evolution based on comparing distributions of features, and its applications for scene segmentation. In the first part, we promote using cross-bin metrics such as the Earth Mover's Distance (EMD), instead of standard bin-wise metrics as the Bhattacharyya or Kullback-Leibler metrics. To derive flow equations for minimizing functionals involving the EMD, we employ a tractable expression for calculating EMD between one-dimensional distributions. We then apply the derived flows to various examples of single image segmentation, and to scene analysis using video data. In the latter, we consider the problem of segmenting a scene to spatial regions in which different activities occur. We use a nonparametric local representation of the regions by considering multiple one-dimensional histograms of normalized spatiotemporal derivatives. We then obtain semisupervised segmentation of regions using the flows derived in the first part of the paper. Our results are demonstrated on challenging surveillance scenes, and compare favorably with state-of-the-art results using parametric representations by dynamic systems or mixtures of them.     

Perceptron training algorithms designed using discrete-time control Liapunov functions

Perceptrons, proposed in the seminal paper McCulloch–Pitts of 1943, have remained of interest to neural network community because of their simplicity and usefulness in classifying linearly separable data and can be viewed as implementing iterative procedures for “solving” linear inequalities. Gradient descent and conjugate gradient methods, normally used for linear equalities, can be used to solve linear inequalities by simple modifications that have been proposed in the literature but not been analyzed completely. This paper applies a recently proposed control-inspired approach to the design of iterative steepest descent and conjugate gradient algorithms for perceptron training in batch mode, by regarding certain parameters of the training/algorithm as controls and then using a control Liapunov technique to choose appropriate values of these parameters.     

Non-fragile robust optimal guaranteed cost control of uncertain 2-D discrete state-delayed systems

This paper is concerned with the problem of non-fragile robust optimal guaranteed cost control for a class of uncertain two-dimensional (2-D) discrete state-delayed systems described by the general model with norm-bounded uncertainties. Our attention is focused on the design of non-fragile state feedback controllers such that the resulting closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible parameter uncertainties and controller gain variations. A sufficient condition for the existence of such controllers is established under the linear matrix inequality framework. Moreover, a convex optimisation problem is proposed to select a non-fragile robust optimal guaranteed cost controller stabilising the 2-D discrete state-delayed system as well as achieving the least guaranteed cost for the resulting closed-loop system. The proposed method is compared with the previously reported criterion. Finally, illustrative examples are given to show the potential of the proposed technique.     

ILP-assisted de novo drug design

The accurate and early detection of epileptic seizures in continuous electroencephalographic (EEG) data has a growing role in the management of patients with epilepsy. Early detection allows for therapy to be delivered at the start of seizures and for caregivers to be notified promptly about potentially debilitating events. The challenge to detecting epileptic seizures, however, is that seizure morphologies exhibit considerable inter-patient and intra-patient variability. While recent work has looked at addressing the issue of variations across different patients (inter-patient variability) and described patient-specific methodologies for seizure detection, there are no examples of systems that can simultaneously address the challenges of inter-patient and intra-patient variations in seizure morphology. In our study, we address this complete goal and describe a multi-task learning approach that trains a classifier to perform well across many kinds of seizures rather than potentially overfitting to the most common seizure types. Our approach increases the generalizability of seizure detection systems and improves the tradeoff between latency and sensitivity versus false positive rates. When compared against the standard approach on the CHB–MIT multi-channel scalp EEG data, our proposed method improved discrimination between seizure and non-seizure EEG for almost 83 % of the patients while reducing false positives on nearly 70 % of the patients studied.     

An improved timestamp-based remote user authentication scheme

To protect the remote server from various malicious attacks, many authentication schemes have been proposed. Some schemes have to maintain a password verification table in the remote server for checking the legitimacy of the login users. To overcome potential risks of verification tables, researchers proposed remote user authentication schemes using smartcard, in which the remote server only keeps a secret key for computing the user’s passwords and does not need any verification table for verifying legal user. In 2003 Shen, Lin, and Hwang proposed a timestamp-based password authentication scheme using smartcards in which the remote server does not need to store the passwords or verification table for user authentication. Unfortunately, this scheme is vulnerable to some deadly attacks. In this paper, we analyze few attacks and finally propose an improved timestamp-based remote user authentication scheme. The modified scheme is more efficient and secure than original scheme.     

OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Pre-Existing Ontologies

There has been an explosion in the types, availability and volume of data accessible in an information system, thanks to the World Wide Web (the Web) and related inter-networking technologies. In this environment, there is a critical need to replace or complement earlier database integration approaches and current browsing and keyword-based techniques with concept-based approaches. Ontologies are increasingly becoming accepted as an important part of any concept or semantics based solution, and there is increasing realization that any viable solution will need to support multiple ontologies that may be independently developed and managed. In particular, we consider the use of concepts from pre-existing real world domain ontologies for describing the content of the underlying data repositories. The most challenging issue in this approach is that of vocabulary sharing, which involves dealing with the use of different terms or concepts to describe similar information. In this paper, we describe the architecture, design and implementation of the OBSERVER system. Brokering across the domain ontologies is enabled by representing and utilizing interontology relationships such as (but not limited to) synonyms, hyponyms and hypernyms across terms in different ontologies. User queries are rewritten by using these relationships to obtain translations across ontologies. Well established metrics like precision and recall based on the extensions underlying the concepts are used to estimate the loss of information, if any.     

Design of fructose-2,6-bisphosphatase inhibitors: a novel virtual screening approach

Fructose-2,6-bisphosphatase (FBPase-2) is a switch between gluconeogenesis and glycolysis in the hepatic cells. The structural features required for inhibitory activity of FBPase-2 were unidentified; no leads are available for inhibiting this important enzyme. In this paper pharmacophore mapping, molecular docking methods were employed in a virtual screening strategy to identify leads for FBPase-2. A receptor based pharmacophore map was modeled which comprised of important interactions as observed in co-crystal of rat liver isozyme with the product inhibitor fructose-6-phosphate. The pharmacophore model was validated against two databases of best docked structural analogues of fructose-2,6-bisphosphate and fructose-6-phosphate. The query generated was submitted for flexible search of ligands in chemical databases, namely LeadQuest, Maybridge and NCI. The hits obtained were further screened by molecular docking using FlexX.     

Effect of impurities (graphite) on the high-temperature creep properties of NiAl

Previous high-temperature compression creep studies of NiAl have shown peculiar behaviour in the temperature range 700 to 900° C, which was perhaps due to precipitation of impurities in the matrix. To isolate the impurity effect, high-purity NiAl samples with 0.15 at% and 0.20 at% carbon (graphite) additions have been creep tested at four temperatures between 700 and 850° C. Addition of graphite has been shown to produce a significant reduction in the creep strength of the alloyS. However, alloys with higher graphite concentrations have shown better creep resistance than those with lower graphite concentrations. Transmission electron microscopy indicates the presence of competing softening and hardening mechanisms in the alloys. Softening is due to the graphite particles acting as a dislocation source. Hardening results from a grain-boundary hardening mechanism due to the graphite particles segregating at grain boundaries and a dislocation-impurity (fine graphite) interaction, developing a Cottrell-like atmosphere.