Miracle-dz/UniFAR-FTUs huggingface dataset:
Cutting Edge: Cross-Presentation of Cell-Associated Antigens to MHC Class I Molecule Is Regulated by a Major Transcription Factor for Heat Shock Proteins1

The ability for the professional APC to cross-present Ag to MHC class I from parenchymal cells is essential for priming as well as tolerance of CD8+ T cells against intracellular Ags. Since cross-presentations of non-cell-associated free Ags are inefficient, the roles of molecular chaperones or heat shock proteins (HSPs) in chaperoning Ags to APCs have been postulated. We herein genetically addressed this hypothesis using mice that were defective of heat shock factor 1 (Hsf1), a major transcription factor for HSPs. Hsf1−/− mice have a decreased expression of several HSPs including HSP90 and HSP70. Using multiple Ag systems, we demonstrated that cross-priming of Ag-specific CD8+ T cells was inefficient when Ag expression was restricted to Hsf1−/− non-APCs. Our study provides the first genetic evidence for the roles of Hsf1 in regulating cross-presentation of MHC class I-associated Ags.
Deeply learnt hashing forests for content based image retrieval in prostate MR images

Deluge in the size and heterogeneity of medical image databases necessitates the need for content based retrieval systems for their efficient organization. In this paper, we propose such a system to retrieve prostate MR images which share similarities in appearance and content with a query image. We introduce deeply learnt hashing forests (DL-HF) for this image retrieval task. DL-HF effectively leverages the semantic descriptiveness of deep learnt Convolutional Neural Networks. This is used in conjunction with hashing forests which are unsupervised random forests. DL-HF hierarchically parses the deep-learnt feature space to encode subspaces with compact binary code words. We propose a similarity preserving feature descriptor called Parts Histogram which is derived from DL-HF. Correlation defined on this descriptor is used as a similarity metric for retrieval from the database. Validations on publicly available multi-center prostate MR image database established the validity of the proposed approach. The proposed method is fully-automated without any user-interaction and is not dependent on any external image standardization like image normalization and registration. This image retrieval method is generalizable and is well-suited for retrieval in heterogeneous databases other imaging modalities and anatomies.
Energy‐efficient scheduling algorithms for batch‐of‐tasks (BoT) applications on heterogeneous computing systems

One of the major design constraints of a heterogeneous computing system is optimal scheduling, that is, mapping of tasks on the processing nodes in order to optimize the QoS parameters. Because of the huge energy consumption by computing resources, negative environmental effects and reduced system reliability, energy has unavoidably been added as a new parameter to the list of QoS parameters. Energy optimization in scheduling strategies along with makespan makes it an even more challenging combinatorial optimization problem. This work proposes two energy‐aware scheduling algorithms G1 and G2 to schedule a batch‐of‐tasks, made of a collection of independent tasks, on heterogeneous processors in order to minimize the makespan and the energy consumption. The proposed algorithms schedule tasks based on weighted aggregation cost function to the appropriate processors followed by task migration phase designed to further minimize the makespan and the energy consumption. The study evaluates the performance of the proposed algorithms with some of the peers, that is, MinMin, MINSuff on account of makespan, energy consumption, flowtime, and utilization. An experimental study reveals that the proposed algorithm (G2) consistently performs better under various test conditions. Copyright © 2015 John Wiley & Sons, Ltd.
EEG Responses to TMS Are Sensitive to Changes in the Perturbation Parameters and Repeatable over Time

Background High-density electroencephalography (hd-EEG) combined with transcranial magnetic stimulation (TMS) provides a direct and non-invasive measure of cortical excitability and connectivity in humans and may be employed to track over time pathological alterations, plastic changes and therapy-induced modifications in cortical circuits. However, the diagnostic/monitoring applications of this technique would be limited to the extent that TMS-evoked potentials are either stereotypical (non-sensitive) or random (non-repeatable) responses. Here, we used controlled changes in the stimulation parameters (site, intensity, and angle of stimulation) and repeated longitudinal measurements (same day and one week apart) to evaluate the sensitivity and repeatability of TMS/hd-EEG potentials. Methodology/Principal Findings In 10 volunteers, we performed 92 single-subject comparisons to evaluate the similarities/differences between pairs of TMS-evoked potentials recorded in the same/different stimulation conditions. For each pairwise comparison, we used non-parametric statistics to calculate a Divergence Index (DI), i.e., the percentage of samples that differed significantly, considering all scalp locations and the entire post-stimulus period. A receiver operating characteristic analysis showed that it was possible to find an optimal DI threshold of 1.67%, yielding 96.7% overall accuracy of TMS/hd-EEG in detecting whether a change in the perturbation parameters occurred or not. Conclusions/Significance These results demonstrate that the EEG responses to TMS essentially reflect deterministic properties of the stimulated neuronal circuits as opposed to stereotypical responses or uncontrolled variability. To the extent that TMS-evoked potentials are sensitive to changes and repeatable over time, they may be employed to detect longitudinal changes in the state of cortical circuits.
Focused Entailment Graphs for Open IE Propositions

Open IE methods extract structured propositions from text. However, these propositions are neither consolidated nor generalized, and querying them may lead to insufficient or redundant information. This work suggests an approach to organize open IE propositions using entailment graphs. The entailment relation unifies equivalent propositions and induces a specific-to-general structure. We create a large dataset of gold-standard proposition entailment graphs, and provide a novel algorithm for automatically constructing them. Our analysis shows that predicate entailment is extremely context-sensitive, and that current lexical-semantic resources do not capture many of the lexical inferences induced by proposition entailment.
Higher-order symbolic execution via contracts

We present a new approach to automated reasoning about higher-order programs by extending symbolic execution to use behavioral contracts as symbolic values, thus enabling symbolic approximation of higher-order behavior. Our approach is based on the idea of an abstract reduction semantics that gives an operational semantics to programs with both concrete and symbolic components. Symbolic components are approximated by their contract and our semantics gives an operational interpretation of contracts-as-values. The result is an executable semantics that soundly predicts program behavior, including contract failures, for all possible instantiations of symbolic components. We show that our approach scales to an expressive language of contracts including arbitrary programs embedded as predicates, dependent function contracts, and recursive contracts. Supporting this rich language of specifications leads to powerful symbolic reasoning using existing program constructs. We then apply our approach to produce a verifier for contract correctness of components, including a sound and computable approximation to our semantics that facilitates fully automated contract verification. Our implementation is capable of verifying contracts expressed in existing programs, and of justifying contract-elimination optimizations.
The Quasi-Market Revolution in the Head

• Summary: The article explores the use of ideology by a group of care managers in the United Kingdom (n = 44) in their work environments. It draws upon ethnomethodological research which investigated the motivations of qualified employees for entering and remaining within state social work. As well as exploring the impact and uses of ideology, the article also questions the disparagement of universalism in the postmodern inspired critique of welfare. This is sustained by highlighting the broad and universal impact of neoliberalism in relation to the care management labour process. • Findings: Care managers utilize ideology throughout their practice, although this is predominantly inspired by external factors, notably legislation and policy. Despite this, there is evidence of some application of professional, and/or critical ideologies, which can offer respite from, and act as a form of resistance against neoliberal ideology within the care management labour process. Nevertheless, in practice, such resistance tends to be dispersed, sporadic and often individualistic. • Applications : It is proposed that the greater use of `emancipatory' ideology in the education and practice of care managers may help in resisting further deskilling and disenfranchisement. Also, the work of Gramsci and Foucault offers a potential framework to contextualize forms of anti-market resistance.
Secure SWIPT Networks Based on a Non-Linear Energy Harvesting Model

We optimize resource allocation to enable com- munication security in simultaneous wireless information and power transfer (SWIPT) for internet-of-things (IoT) networks. The resource allocation algorithm design is formulated as a non-convex optimization problem. We aim at maximizing the total harvested power at energy harvesting (EH) receivers via the joint optimization of transmit beamforming vectors and the covariance matrix of the artificial noise injected to facilitate secrecy provisioning. The proposed problem formulation takes into account the non-linearity of energy harvesting circuits and the quality of service requirements for secure communication. To obtain a globally optimal solution of the resource allocation problem, we first transform the resulting non-convex sum-of- ratios objective function into an equivalent objective function in parametric subtractive form, which facilitates the design of a novel iterative resource allocation algorithm. In each iteration, the semidefinite programming (SDP) relaxation approach is adopted to solve a rank-constrained optimization problem optimally. Nu- merical results reveal that the proposed algorithm can guarantee communication security and provide a significant performance gain in terms of the harvested energy compared to existing designs which are based on the traditional linear EH model.
Neural Network Grasping Controller for Continuum Robots

Continuum or hyper-redundant robots are robots which exhibit behavior similar to biological trunks, tentacles and snakes. Unlike traditional robots, continuum robot manipulators do not have rigid joints, hence the manipulators are compliant, extremely dexterous, and capable of dynamic, adaptive manipulation in unstructured environments; however, the development of high-performance control algorithms for these manipulators is a challenging problem. In this paper, we present an approach to whole arm grasping control for continuum robots. The grasping controller is developed in two stages; high level path planning for the grasping objective, and a low level joint controller using a neural network feedforward component to compensate for dynamic uncertainties. These techniques are used to enable whole arm grasping without using contact force measurements and without using a dynamic model of the continuum robot
On Their Own: Librarians' Self-Directed, Work-Related Learning

Personal members of the American Library Association (ALA) were queried in order to gather baseline data on their self-directed, informal, work-related learning. Results showed that 77 percent of respondents recalled having undertaken such learning. Comparison with time spent in formal continuing education (CE) activities revealed that three times as many hours were spent on self-directed learning (SDL). Philip Candy's framework for conceptualizing SDL provided a model for examining relationships among variables likely to influence SDL. Those variables that measured librarians' professional activities and the size of the institution employing them were the most salient. Institutional policies and resources in support of professional development were not predictors of SDL as measured in this study.
Investigation of a Novel Five-Phase Modular Permanent-Magnet In-Wheel Motor

To increase the driving comfortableness and reliability of electric vehicles, multi-phase fault-tolerant permanent-magnet synchronous motors (PMSM) are becoming promising candidates, especially for the vehicles adopting in-wheel PMSM schemes. In this paper, a novel five-phase fault-tolerant modular in-wheel PMSM is proposed and investigated. The applicable slot/pole combinations are recommended for five-phase PMSM, and the 40-slot/42-pole scheme is selected for the wheel driven application in this paper. The electromagnetic structure was designed, and the fault-tolerant tooth was optimized to obtain better torque curve. The fault-tolerant ability was analyzed under some fault conditions, including one phase open-circuited, two adjacent phases open-circuited, two non-adjacent phases open-circuited and one single phase short-circuited. The results indicate that the drive system can survive these fault conditions; through proper current control strategies, different fault-tolerant performances can be obtained. The proposed scheme is proved to have satisfying electromagnetic and fault-tolerant performances.
Genetic polymorphism of the β-tubulin gene of Onchocerca volvulus in ivermectin naïve patients from Cameroon, and its relationship with fertility of the worms

Observations of low response of patients infected with Onchocerca volvulus to ivermectin suggest that the parasite may be under a selection process toward potential resistance. To limit the extension of this phenomenon, it is crucial to characterize the genes of O. volvulus that are involved. For this, O. volvulus adult worms collected before the introduction of ivermectin in an onchocerciasis endemic area of central Cameroon were genotyped for β-tubulin. To derive a baseline to investigate the selective pressure of ivermectin, we analysed (1) the frequency distribution of the β-tubulin alleles, and (2) the relationship between the different β-tubulin related genotypes and the fertility status of the female worms. The frequency of allele b of the β-tubulin gene was very low, as it was observed in West Africa. We observed a deficit of heterozygous female worms leading to Hardy Weinberg disequilibrium, which might be explained by a shorter life-span of these worms compared to the homozygous worms. Unexpectedly, our results also show that the heterozygous female worms were much less fertile than the homozygotes: more than two thirds of the homozygotes were fertile, whereas only 37% of the heterozygotes were fertile. These results will be further considered when analysing post-treatment data.
Effective Channel Shortening by Modified MSSNR Algorithm for Simplified UWB Receiver

In this paper, we present a modified version of the maximum shortening signal to noise ratio (MSSNR) algorithm for channel shortening in a time hopping (TH) pulse position modulated (PPM) ultra wideband (UWB) communication system. The proposed algorithm introduces two additional UWB channel related parameters in the optimization problem along with the conventional energy criterion. This modification significantly improve the performance of the conventional MSSNR algorithm and enables it to handle the extreme nature of channel shortening needed in UWB systems. We also derive a lower bound for bit error rate (BER) as a comparison bench mark. The proposed algorithm does not need any training or channel estimation and outperforms the conventional MSSNR algorithm in terms of different comparative parameters.
Gaussian selection applied to text-independent speaker verification

Fast speaker verification systems can be realised by reducing the computation associated with searching of mixture components within the statistical model such as a Gaussian mixture model, GMM. Several improvements regarding computational efficiency have already been proposed for speaker verification. In this paper, the technique of Gaussian selection is applied to the speaker verification task. Gaussian selection is commonly known in speech recognition where it is used to speed up the scoring process of HMM recognisers. Here we use the same technique to reduce the computation of mixture components within the GMM framework. Experiments compare different selection methods on the text-independent Odyssey 2001 speaker verification database. Further, the selection methods are compared with the baseline approach of scoring all mixture components in the full model. The results reveal a computational reduction of factor ten with only minor degradation in verification performance.
Improving Semantic Concept Detection Through Optimizing Ranking Function

In this paper, a kernel-based learning algorithm, kernel rank, is presented for improving the performance of semantic concept detection. By designing a classifier optimizing the receiver operating characteristic (ROC) curve using kernel rank, we provide a generic framework to optimize any differentiable ranking function using effective smoothing functions. kernel rank directly maximizes a 1-D quality measure of ROC, i.e., AUC (area under the ROC). It exploits the kernel density estimation to model the ranking score distributions and approximate the correct ranking count. The ranking metric is then derived and the learnable parameters are naturally embedded. To address the issues of computation and memory in learning, an efficient implementation is developed based on the gradient descent algorithm. We apply kernel rank with two types of kernel density functions to train the linear discriminant function and the Gaussian mixture model classifiers. From our experiments carried out on the development set for TREC Video Retrieval 2005, we conclude that (1) kernel rank is capable of training any differentiable classifier with various kernels; and (2) the learned ranking function performs better than traditional maximization likelihood or classification error minimization based algorithms in terms of AUC and average precision (AP).
Subset Typicality Lemmas and Improved Achievable Regions in Multiterminal Source Coding

Consider the following information theoretic setup wherein independent codebooks of N correlated random variables are generated according to their respective marginals. The problem of determining the conditions on the rates of codebooks to ensure the existence of at least one codeword tuple which is jointly typical with respect to a given joint density (called the multivariate covering lemma) has been studied fairly well and the associated rate regions have found applications in several source coding scenarios. However, several multiterminal source coding applications, such as the general multi-user Gray-Wyner network, require joint typicality only within subsets of codewords transmitted. Motivated by such applications, we ask ourselves the conditions on the rates to ensure the existence of at least one codeword tuple which is jointly typical within subsets according to given per subset joint densities. This report focuses primarily on deriving a new achievable rate region for this problem which strictly improves upon the direct extension of the multivariate covering lemma, which has quite popularly been used in several earlier work. Towards proving this result, we derive two important results called `subset typicality lemmas' which can potentially have broader applicability in more general scenarios beyond what is considered in this report. We finally apply the results therein to derive a new achievable region for the general multi-user Gray-Wyner network.
A Vacuolar v–t-SNARE Complex, the Predominant Form In Vivo and on Isolated Vacuoles, Is Disassembled and Activated for Docking and Fusion

Homotypic vacuole fusion in yeast requires Sec18p (N-ethylmaleimide–sensitive fusion protein [NSF]), Sec17p (soluble NSF attachment protein [α-SNAP]), and typical vesicle (v) and target membrane (t) SNAP receptors (SNAREs). We now report that vacuolar v- and t-SNAREs are mainly found with Sec17p as v–t-SNARE complexes in vivo and on purified vacuoles rather than only transiently forming such complexes during docking, and disrupting them upon fusion. In the priming reaction, Sec18p and ATP dissociate this v–t-SNARE complex, accompanied by the release of Sec17p. SNARE complex structure governs each functional aspect of priming, as the v-SNARE regulates the rate of Sec17p release and, in turn, Sec17p-dependent SNARE complex disassembly is required for independent function of the two SNAREs. Sec17p physically and functionally interacts largely with the t-SNARE. (a) Antibodies to the t-SNARE, but not the v-SNARE, block Sec17p release. (b) Sec17p is associated with the t-SNARE in the absence of v-SNARE, but is not bound to the v-SNARE without t-SNARE. (c) Vacuoles with t-SNARE but no v-SNARE still require Sec17p/Sec18p priming, whereas their fusion partners with v-SNARE but no t-SNARE do not. Sec18p thus acts, upon ATP hydrolysis, to disassemble the v–t-SNARE complex, prime the t-SNARE, and release the Sec17p to allow SNARE participation in docking and fusion. These studies suggest that the analogous ATP-dependent disassembly of the 20-S complex of NSF, α-SNAP, and v- and t-SNAREs, which has been studied in detergent extracts, corresponds to the priming of SNAREs for docking rather than to the fusion of docked membranes.
Similarities as Evidence for Common Ancestry: A Likelihood Epistemology

Darwin claims in the Origin that similarity is evidence for common ancestry, but that adaptive similarities are ‘almost valueless’ as evidence. This second claim seems reasonable for some adaptive similarities but not for others. Here we clarify and evaluate these and related matters by using the law of likelihood as an analytic tool and by considering mathematical models of three evolutionary processes: directional selection, stabilizing selection, and drift. Our results apply both to Darwin’s theory of evolution and to modern evolutionary biology. 1 Introduction 2 The Likelihood Framework 3 A Sufficient Condition for a Similarity to Favour Common Ancestry over Separate Ancestry 4 The 1/p Criterion and Its Limitations 5 Directional Selection versus Drift 6 Stabilizing Selection versus Drift 7 Going beyond Two Taxa 8 Conclusions Appendix 1 Introduction 2 The Likelihood Framework 3 A Sufficient Condition for a Similarity to Favour Common Ancestry over Separate Ancestry 4 The 1/p Criterion and Its Limitations 5 Directional Selection versus Drift 6 Stabilizing Selection versus Drift 7 Going beyond Two Taxa 8 Conclusions Appendix
Transcription of the isoamylase gene (iam) in Pseudomonas amyloderamosa SB-15

S1 nuclease mapping of RNA prepared from Pseudomonas amyloderamosa SB-15 suggested that the iam gene coding for isoamylase (glycogen 6-glucanohydrolase [EC 3.2.1.68]) is transcribed from two promoters. The transcription start site for the upstream promoter (termed P1) was located -182 base pairs from the first nucleotide of the initiation codon of iam, whereas the start site for the downstream promoter (termed P2) was 99 base pairs downstream of the P1 start site. Transcriptions from these promoters were induced by maltose and were not repressed by glucose. The promoter regions contained sequences homologous to the consensus sequence recognized by sigma 54 RNA polymerase of enteric bacteria and found in promoters of other Pseudomonas species. Northern (RNA) hybridization provided evidence that the iam gene is transcribed as monocistronic mRNAs with an approximate size of 2.6 kilobases.