A Coalition game model for spectrum pooling in wireless data access networks

We consider a setting in which several operators offer downlink wireless data access services in a certain geographical region. Each operator deploys several base stations or access points, and registers some subscribers. In such a situation, if operators pool their infrastructure, and permit the possibility of subscribers being served by any of the cooperating operators, then there can be overall better user satisfaction, and increased operator revenue. We use coalitional game theory to investigate such resource pooling and cooperation between operators.We use utility functions to model user satisfaction, and show that the resulting coalitional game has the property that if all operators cooperate (i.e., form a grand coalition) then there is an operating point that maximizes the sum utility over the operators while providing the operators revenues such that no subset of operators has an incentive to break away from the coalition. We investigate whether such operating points can result in utility unfairness between users of the various operators. We also study other revenue sharing concepts, namely, the nucleolus and the Shapely value. Such investigations throw light on criteria for operators to accept or reject subscribers, based on the service level agreements proposed by them. We also investigate the situation in which only certain subsets of operators may be willing to cooperate.

Compiler-Directed Frequency and Voltage Scaling for a Multiple Clock Domain

Multiple Clock Domain processors provide an attractive solution to the increasingly challenging problems of clock distribution and power dissipation. They allow their chips to be partitioned into different clock domains, and each domain’s frequency (voltage) to be independently configured. This flexibility adds new dimensions to the Dynamic Voltage and Frequency Scaling problem, while providing better scope for saving energy and meeting performance demands. In this paper, we propose a compiler directed approach for MCD-DVFS. We build a formal petri net based program performance model, parameterized by settings of microarchitectural components and resource configurations, and integrate it with our compiler passes for frequency selection.Our model estimates the performance impact of a frequency setting, unlike the existing best techniques which rely on weaker indicators of domain performance such as queue occupancies(used by online methods) and slack manifestation for a particular frequency setting (software based methods).We evaluate our method with subsets of SPECFP2000,Mediabench and Mibench benchmarks. Our mean energy savings is 60.39% (versus 33.91% of the best software technique)in a memory constrained system for cache miss dominated benchmarks, and we meet the performance demands.Our ED2 improves by 22.11% (versus 18.34%) for other benchmarks. For a CPU with restricted frequency settings, our energy consumption is within 4.69% of the optimal.

Design and Characterization of Stabilized Derivatives of Human CD4D12 and CD4D1

CD4 is present on the surface of T-lymphocytes and is the primary cellular receptor for HIV-1. CD4 consists of a cytoplasmic tail, one transmembrane region, and four extracellular domains, D1-D4. A construct consisting of the first two domains of CD4 (CD4D12) is folded and binds gp120 with similar affinity as soluble 4-domain CD4 (sCD4). However, the first domain alone (CD4D1) was previously shown to be largely unfolded and had 3-fold weaker affinity for gp120 when compared to sCD4 [Sharma, D.; et al. (2005) Biochemistry 44, 16192-16202]. We now report the design and characterization of three single-site mutants of CD4D12 (G6A, L51I, and V86L) and one multisite mutant of CD4D1 (G6A/L511/L5K/F98T). G6A, L51I, and V86L are cavity-filling mutations while L5K and F98T are surface mutations which were introduced to minimize the aggregation of CD4D1 upon removal of the second domain. Two mutations, G6A and V86L in CD4D12 increased the stability and yield of the protein relative to the wild-type protein. The mutant CD4D1 (CD4D1a) with the 4 mutations was folded and more stable compared to the original CD4D1, but both bound gp120 with comparable affinity. In in vitro neutralization assays, both CD4D1a and G6A-CD4D12 were able to neutralize diverse HIV-1 viruses with similar IC(50)s as 4-domain CD4. These stabilized derivatives of human CD4 can be useful starting points for the design of other more complex viral entry inhibitors.

Robust MMSE Tomlinson-Harashima Precoder for Multiuser MISO Downlink with Imperfect CSI

Non-linear precoding for the downlink of a multiuser MISO (multiple-input single-output) communication system in the presence of imperfect channel state information (CSI) is considered.The base station is equipped with multiple transmit antennas and each user terminal is equipped with a single receive antenna. The CSI at the transmitter is assumed to be perturbed by an estimation error. We propose a robust minimum mean square error (MMSE) Tomlinson-Harashima precoder (THP)design, which can be formulated as an optimization problem that can be solved efficiently by the method of alternating optimization(AO). In this method of optimization, the entire set of optimization variables is partitioned into non-overlapping subsets,and an iterative sequence of optimizations on these subsets is carried out, which is often simpler compared to simultaneous optimization over all variables. In our problem, the application of the AO method results in a second-order cone program which can be numerically solved efficiently. The proposed precoder is shown to be less sensitive to imperfect channel knowledge. Simulation results illustrate the improvement in performance compared to other robust linear and non-linear precoders in the literature.

A Randomized Algorithm for Large Scale Support Vector Learning

We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the subsets chosen. In the context of text classification we show that, by using ideas from random projections, a sample size of O(log n) can be used to obtain a solution which is close to the optimal with a high probability. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up SVM learners, without loss in accuracy. 1

Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

Fast algorithms for frequent episode discovery in event sequences

In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

Badly approximable numbers and vectors in Cantor-like sets

We show that a large class of Cantor-like sets of R-d, d >= 1, contains uncountably many badly approximable numbers, respectively badly approximable vectors, when d >= 2. An analogous result is also proved for subsets of R-d arising in the study of geodesic flows corresponding to (d+1)-dimensional manifolds of constant negative curvature and finite volume, generalizing the set of badly approximable numbers in R. Furthermore, we describe a condition on sets, which is fulfilled by a large class, ensuring a large intersection with these Cantor-like sets.

Expression of VP1 protein of serotype A and O of foot-and-mouth disease virus in transgenic sunnhemp plants and its immunogenicity for guinea pigs

Recently, transgenic plants expressing immunogenic proteins of foot-and-mouth disease virus (FMDV) have been used as oral or parenteral vaccines against foot-and-mouth disease (FMD). They exhibit advantages like cost effectiveness, absence of processing, thermostability, and easy oral application. FMDV VP1 protein of single serotype has been mostly used as immunogen. Here we report the development of a bivalent vaccine with tandem-linked VP1 proteins of two serotypes, A and O, present in transgenic forage crop Crotalaria juncea. The expression of the bivalent protein in the transgenic plants was confirmed by Western blot analysis. Guinea pig reacted to orally or parenterally applied vaccine by humoral as well as cell-mediated immune responses including serum antibodies and stimulated lymphocytes, respectively. The vaccine protected the animals against a challenge with the virus of serotype A as well as O. This is the first report on the development of a bivalent FMD vaccine using a forage crop.

ATP release and autocrine signaling through P2X4 receptors regulate gamma delta T cell activation

Purinergic signaling plays a key role in a variety of physiological functions, including regulation of immune responses. Conventional alpha beta T cells release ATP upon TCR cross-linking; ATP binds to purinergic receptors expressed by these cells and triggers T cell activation in an autocrine and paracrine manner. Here, we studied whether similar purinergic signaling pathways also operate in the ``unconventional'' gamma delta T lymphocytes. We observed that gamma delta T cells purified from peripheral human blood rapidly release ATP upon in vitro stimulation with anti-CD3/CD28-coated beads or IPP. Pretreatment of gamma delta T cells with (10)panx-1, CBX, or Bf A reversed the stimulation-induced increase in extracellular ATP concentration, indicating that panx-1, connexin hemichannels, and vesicular exocytosis contribute to the controlled release of cellular ATP. Blockade of ATP release with (10)panx-1 inhibited Ca2+ signaling in response to TCR stimulation. qPCR revealed that gamma delta T cells predominantly express purinergic receptor subtypes A2a, P2X1, P2X4, P2X7, and P2Y11. We found that pharmacological inhibition of P2X4 receptors with TNP-ATP inhibited transcriptional up-regulation of TNF-alpha and IFN-gamma in gamma delta T cells stimulated with anti-CD3/CD28-coated beads or IPP. Our data thus indicate that purinergic signaling via P2X4 receptors plays an important role in orchestrating the functional response of circulating human gamma delta T cells. J. Leukoc. Biol. 92: 787-794; 2012.

Two-Dimensional Correlation Analysis of Temperature-Dependent FT-IR Spectra of Oleic Acid

In the present study, variable temperature FT-IR spectroscopic investigations were used to characterize the spectral changes in oleic acid during heating oleic acid in the temperature range from -30 degrees;C to 22 degrees C. In order to extract more information about the spectral variations taking place during the phase transition process, 2D correlation spectroscopy (2DCOS) was employed for the stretching (C?O) and rocking (CH2) band of oleic acid. However, the interpretation of these spectral variations in the FT-IR spectra is not straightforward, because the absorption bands are heavily overlapped and change due to two processes: recrystallization of the ?-phase and melting of the oleic acid. Furthermore, the solid phase transition from the ?- to the a-phase was also observed between -4 degrees C and -2 degrees C. Thus, for a more detailed 2DCOS analysis, we have split up the spectral data set in the subsets recorded between -30 degrees C to -16 degrees C, -16 degrees C to 10 degrees C, and 10 degrees C to 22 degrees C. In the corresponding synchronous and asynchronous 2D correlation plots, absorption bands that are characteristic of the crystalline and amorphous regions of oleic acid were separated.

Geometry of static balancing during posture transition

The interaction between the digital human model (DHM) and environment typically occurs in two distinct modes; one, when the DHM maintains contacts with the environment using its self weight, wherein associated reaction forces at the interface due to gravity are unidirectional; two, when the DHM applies both tension and compression on the environment through anchoring. For static balancing in first mode of interaction, it is sufficient to maintain the projection of the centre of mass (COM) inside the convex region induced by the weight supporting segments of the body on a horizontal plane. In DHM, static balancing is required while performing specified tasks such as reach, manipulation and locomotion; otherwise the simulations would not be realistic. This paper establishes the geometric relationships that must be satisfied for maintaining static balance while altering the support configurations for a given posture and altering the posture for a given support condition. For a given location of the COM for a system supported by multiple point contacts, the conditions for simultaneous withdrawal of a specified set of contacts have been determined in terms of the convex hulls of the subsets of the points of contact. When the projection of COM must move beyond the existing support for performing some task, new supports must be enabled for maintaining static balance. This support seeking behavior could also manifest while planning for reduction of support stresses. Feasibility of such a support depends upon the availability of necessary features in the environment. Geometric conditions necessary for selection of new support on horizontal,inclined and vertical surfaces within the workspace of the DHM for such dynamic scenario have been derived. The concepts developed are demonstrated using the cases of sit-to-stand posture transition for manipulation of COM within the convex supporting polygon, and statically stable walking gaits for support seeking within the kinematic capabilities of the DHM. The theory developed helps in making the DHM realize appropriate behaviors in diverse scenarios autonomously.

Interferon-gamma- and glucocorticoid-mediated pathways synergize to enhance death of CD4(+) CD8(+) thymocytes during Salmonella enterica serovar Typhimurium infection

Thymic atrophy is known to occur during infections; however, there is limited understanding of its causes and of the cross-talk between different pathways. This study investigates mechanisms involved in thymic atrophy during a model of oral infection by Salmonella enterica serovar Typhimurium (S.typhimurium). Significant death of CD4+CD8+ thymocytes, but not of single-positive thymocytes or peripheral lymphocytes, is observed at later stages during infection with live, but not heat-killed, bacteria. The death of CD4+CD8+ thymocytes is Fas-independent as shown by infection studies with lpr mice. However, apoptosis occurs with lowering of mitochondrial potential and higher caspase-3 activity. The amounts of cortisol, a glucocorticoid, and interferon- (IFN-), an inflammatory cytokine, increase upon infection. To investigate the functional roles of these molecules, studies were performed using Ifn/ mice together with RU486, a glucocorticoid receptor antagonist. Treatment of C57BL/6 mice with RU486 does not affect colony-forming units (CFU), amounts of IFN- and mouse survival; however, there is partial rescue in thymocyte death. Upon infection, Ifn/ mice display higher CFU and lower survival but more surviving thymocytes are recovered. However, there is no difference in cortisol amounts in C57BL/6 and Ifn/ mice. Importantly, the number of CD4+CD8+ thymocytes is significantly higher in Ifn/ mice treated with RU486 along with lower caspase-3 activity and mitochondrial damage. Hence, endogenous glucocorticoid and IFN--mediated pathways are parallel but synergize in an additive manner to induce death of CD4+CD8+ thymocytes during S.typhimurium infection. The implications of this study for host responses during infection are discussed.

A regularized linear classifier for effective text classification

In document community support vector machines and naïve bayes classifier are known for their simplistic yet excellent performance. Normally the feature subsets used by these two approaches complement each other, however a little has been done to combine them. The essence of this paper is a linear classifier, very similar to these two. We propose a novel way of combining these two approaches, which synthesizes best of them into a hybrid model. We evaluate the proposed approach using 20ng dataset, and compare it with its counterparts. The efficacy of our results strongly corroborate the effectiveness of our approach.

Hybrid online non-negative matrix factorization for clustering of documents

When document corpus is very large, we often need to reduce the number of features. But it is not possible to apply conventional Non-negative Matrix Factorization(NMF) on billion by million matrix as the matrix may not fit in memory. Here we present novel Online NMF algorithm. Using Online NMF, we reduced original high-dimensional space to low-dimensional space. Then we cluster all the documents in reduced dimension using k-means algorithm. We experimentally show that by processing small subsets of documents we will be able to achieve good performance. The method proposed outperforms existing algorithms.