Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Coding of Interaural Time Differences with Bilateral Cochlear Implants: Effects of Congenital Deafness

Human bilateral cochlear implant users do poorly on tasks involving interaural time differences (ITD), a cue that provides important benefits to the normal hearing, especially in challenging acoustic environments, yet the precision of neural ITD coding in acutely deafened, bilaterally implanted cats is essentially normal (Smith and Delgutte, 2007a). One explanation for this discrepancy is that the extended periods of binaural deprivation typically experienced by cochlear implant users degrades neural ITD sensitivity, by either impeding normal maturation of the neural circuitry or altering it later in life. To test this hypothesis, we recorded from single units in inferior colliculus of two groups of bilaterally implanted, anesthetized cats that contrast maximally in binaural experience: acutely deafened cats, which had normal binaural hearing until experimentation, and congenitally deaf white cats, which received no auditory inputs until the experiment. Rate responses of only half as many neurons showed significant ITD sensitivity to low-rate pulse trains in congenitally deaf cats compared with acutely deafened cats. For neurons that were ITD sensitive, ITD tuning was broader and best ITDs were more variable in congenitally deaf cats, leading to poorer ITD coding within the naturally occurring range. A signal detection model constrained by the observed physiology supports the idea that the degraded neural ITD coding resulting from deprivation of binaural experience contributes to poor ITD discrimination by human implantees.
Shifted Power Method for Computing Tensor Eigenpairs

Recent work on eigenvalues and eigenvectors for tensors of order $m \ge 3$ has been motivated by applications in blind source separation, magnetic resonance imaging, molecular conformation, and more. In this paper, we consider methods for computing real symmetric-tensor eigenpairs of the form $\boldsymbol{\mathscr{A}}\mathbf{x}^{m-1} = \lambda \mathbf{x}$ subject to $\|\mathbf{x}\|=1$, which is closely related to optimal rank-1 approximation of a symmetric tensor. Our contribution is a shifted symmetric higher-order power method (SS-HOPM), which we show is guaranteed to converge to a tensor eigenpair. SS-HOPM can be viewed as a generalization of the power iteration method for matrices or of the symmetric higher-order power method. Additionally, using fixed point analysis, we can characterize exactly which eigenpairs can and cannot be found by the method. Numerical examples are presented, including examples from an extension of the method to finding complex eigenpairs.
ADVANCING THE STANDARD OF CARE : Cardiovascular and Neurovascular Emergencies

1. Relate the importance of balancing anti-ischemic efficacy with adverse bleeding potential when selecting anticoagulant and antiplatelet therapies for NSTE-ACS. 2. Discuss the demonstrated benefits of following evidence-based recommendations for the management of high-risk NSTE-ACS patients. 3. Elaborate on the importance of continuity of risk stratification and treatment decisions as patients with NSTE-ACS leave the ED and enter cardiology care.
Characterization of prognosis methods : an industrial approach

This article presents prognosis implementation from an industrial perspective. From the description of a use-case (available information, data, expertise, objective, expected performance indicators, etc.), an engineer should be able to select easily, among the large variety of prognosis methods, the ones that are compatible with his objectives and means. Many classifications of prognosis methods have already been published but they focus more on the techniques that are involved (physical model, statistical model, data-based model, .) than on the necessary inputs to build/learn the model and/or run it and the expected outputs. This paper presents the different strategies of maintenance and the place of prognostics in these strategies. The life cycle of a prognosis function is described, which helps to define relevant, yet certainly not complete, characteristics of prognosis problems and methods. Depending on the maintenance strategy, the prognosis function will not be used at the same step and with different objectives. Two different steps of use are defined when using the prognosis function: evaluation of the current state and prediction of the prognosis output. This paper gives also some elements of classification that will help an engineer choose the appropriate class of methods to use to solve a prognosis problem. The paper also illustrates on one example the fact that, depending on the information at hand, the prognosis method chosen is different.
Estimating nitrogen fluxes at the European scale by upscaling INTEGRATOR model outputs from selected sites

Abstract. A comparison was made between upscaled model results of nitrogen (N) fluxes to air and water from 450 sites within the EU-27 and results derived for the entire EU-27 area using the model INTEGRATOR. The 450 sites were selected using stratified random sampling, dividing the EU-27 into 150 strata and selecting three sites at random within each stratum. The strata were based on important environmental factors influencing N fluxes. Hierarchical divisive cluster analysis was used to reduce the numerous combinations of environmental factors to the required total of 150, such that the heterogeneity of environmental factors within strata was as small as possible. Modelled NH3, N2O and NOx emissions and N leaching/runoff obtained were scaled up from the 450 sites to the entire EU-27 and were within 10% of results obtained by running the model for the whole of the EU-27 using about 36 500 sites. This implies that a reliable estimate of N fluxes for EU-27 can be made by upscaling results of the 450 selected sites suggesting that dramatic reduction in computation time can be achieved without substantial deterioration of results
Statistical Properties of Single-Marker Tests for Rare Variants

With the dramatic technological developments of genome-wide association single-nucleotide polymorphism (SNP) chips and next generation sequencing, human geneticists now have the ability to assay genetic variation at ever-rarer allele frequencies. To fully understand the impact of these rare variants on common, complex diseases, we must be able to accurately assess their statistical significance. However, it is well established that classical association tests are not appropriate for the analysis of low-frequency variation, giving spurious findings when observed counts are too few. To further our understanding of the asymptotic properties of traditional association tests, we conducted a range of simulations of a typical rare variant (~1%) under the null hypothesis and tested the allelic χ2, Cochran–Armitage trend, Wald, and Fisher's exact tests. We demonstrate that rare variation shows marked deviation from the expected distributional behavior for each test, with fewer minor alleles corresponding to a greater degree of test statistics deflation. The effect becomes more pronounced at progressively smaller α levels. We also show that the Wald test is particularly deflated at α levels consistent with genome-wide association significance, much more so than the other association tests considered. In general, these classical association tests are inappropriate for the analysis of variants for which the minor allele is observed fewer than 80 times, largely irrespective of sample size.
From Touchpad to Smart Lens: A Comparative Study on Smartphone Interaction with Public Displays

Todayâ€™s smartphones provide the technical means to serve as interfaces for public displays in various ways. Even though recent research has identified several new approaches for mobile-display interaction, inter-technique comparisons of respective methods are scarce. The authors conducted an experimental user study on four currently relevant mobile-display interaction techniques (â€˜Touchpadâ€™, â€˜Pointerâ€™, â€˜Mini Videoâ€™, and â€˜Smart Lensâ€™) and learned that their suitability strongly depends on the task and use case at hand. The study results indicate that mobile-display interactions based on a traditional touchpad metaphor are time-consuming but highly accurate in standard target acquisition tasks. The direct interaction techniques Mini Video and Smart Lens had comparably good completion times, and especially Mini Video appeared to be best suited for complex visual manipulation tasks like drawing. Smartphone-based pointing turned out to be generally inferior to the other alternatives. Examples for the application of these differentiated results to real-world use cases are provided.
Beyond Keywords and Relevance: A Personalized Ad Retrieval Framework in E-Commerce Sponsored Search

In most sponsored search platforms, advertisers bid on some keywords for their advertisements (ads). Given a search request, ad retrieval module rewrites the query into bidding keywords, and uses these keywords as keys to select Top N ads through inverted indexes. In this way, an ad will not be retrieved even if queries are related when the advertiser does not bid on corresponding keywords. Moreover, most ad retrieval approaches regard rewriting and ad-selecting as two separated tasks, and focus on boosting relevance between search queries and ads. Recently, in e-commerce sponsored search more and more personalized information has been introduced, such as user profiles, long-time and real-time clicks. Personalized information makes ad retrieval able to employ more elements (e.g. real-time clicks) as search signals and retrieval keys, however it makes ad retrieval more difficult to measure ads retrieved through different signals. To address these problems, we propose a novel ad retrieval framework beyond keywords and relevance in e-commerce sponsored search. Firstly, we employ historical ad click data to initialize a hierarchical network representing signals, keys and ads, in which personalized information is introduced. Then we train a model on top of the hierarchical network by learning the weights of edges. Finally we select the best edges according to the model, boosting RPM/CTR. Experimental results on our e-commerce platform demonstrate that our ad retrieval framework achieves good performance.
To Appear in ISCA 2018 Final Version In Preparation . Rethinking Belady ’ s Algorithm to Accommodate Prefetching

This paper shows that in the presence of data prefetchers, cache replacement policies are faced with a large unexplored design space. In particular, we observe that while Belady’s MIN algorithm minimizes the total number of cache misses— including those for prefetched lines—it does not minimize the number of demand misses. To address this shortcoming, we introduce Demand-MIN, a variant of Belady’s algorithm that minimizes the number of demand misses at the cost of increased prefetcher traffic. Together, MIN and DemandMIN define the boundaries of an important design space, with many intermediate points lying between them. To reason about this design space, we introduce a simple conceptual tool, which we use to define a new cache replacement policy called Prefetch-Aware Hawkeye. Our empirical evaluation shows that for a mix of SPEC 2006 benchmarks running on a 4-core system with a stride prefetcher, PrefetchAware Hawkeye improves IPC by 7.7% over an LRU baseline, compared to 6.4% for the previous state-of-the-art. On an 8-core system, Prefetch-Aware Hawkeye improves IPC by 9.4% compared to 5.8% for the previous state-of-the-art.
Electricity Production by Geobacter sulfurreducens Attached to Electrodes

ABSTRACT Previous studies have suggested that members of the Geobacteraceae can use electrodes as electron acceptors for anaerobic respiration. In order to better understand this electron transfer process for energy production, Geobacter sulfurreducens was inoculated into chambers in which a graphite electrode served as the sole electron acceptor and acetate or hydrogen was the electron donor. The electron-accepting electrodes were maintained at oxidizing potentials by connecting them to similar electrodes in oxygenated medium (fuel cells) or to potentiostats that poised electrodes at +0.2 V versus an Ag/AgCl reference electrode (poised potential). When a small inoculum of G. sulfurreducens was introduced into electrode-containing chambers, electrical current production was dependent upon oxidation of acetate to carbon dioxide and increased exponentially, indicating for the first time that electrode reduction supported the growth of this organism. When the medium was replaced with an anaerobic buffer lacking nutrients required for growth, acetate-dependent electrical current production was unaffected and cells attached to these electrodes continued to generate electrical current for weeks. This represents the first report of microbial electricity production solely by cells attached to an electrode. Electrode-attached cells completely oxidized acetate to levels below detection (<10 μM), and hydrogen was metabolized to a threshold of 3 Pa. The rates of electron transfer to electrodes (0.21 to 1.2 μmol of electrons/mg of protein/min) were similar to those observed for respiration with Fe(III) citrate as the electron acceptor (Eo′ =+0.37 V). The production of current in microbial fuel cell (65 mA/m2 of electrode surface) or poised-potential (163 to 1,143 mA/m2) mode was greater than what has been reported for other microbial systems, even those that employed higher cell densities and electron-shuttling compounds. Since acetate was completely oxidized, the efficiency of conversion of organic electron donor to electricity was significantly higher than in previously described microbial fuel cells. These results suggest that the effectiveness of microbial fuel cells can be increased with organisms such as G. sulfurreducens that can attach to electrodes and remain viable for long periods of time while completely oxidizing organic substrates with quantitative transfer of electrons to an electrode.
IMPLEMENTATIONS OF THE SCHMIDT-KALMAN ‘ CONSIDER ’ FILTER

One method to account for parameters errors in the Kalman filter is to ‘consider’ their effect in the so-called Schmidt-Kalman filter. This paper addresses issues that arise when implementing a consider Kalman filter as a real-time, recursive algorithm. A favorite implementation of the Kalman filter as an onboard navigation subsystem is the UDU formulation. A new way to implement a UDU Schmidt-Kalman filter is proposed. The nonoptimality of the recursive Schmidt-Kalman filter is also analyzed, and a modified algorithm is proposed to overcome this limitation.
Synergistic Roles of Eukaryotic Translation Elongation Factors 1Bγ and 1A in Stimulation of Tombusvirus Minus-Strand Synthesis

Host factors are recruited into viral replicase complexes to aid replication of plus-strand RNA viruses. In this paper, we show that deletion of eukaryotic translation elongation factor 1Bgamma (eEF1Bγ) reduces Tomato bushy stunt virus (TBSV) replication in yeast host. Also, knock down of eEF1Bγ level in plant host decreases TBSV accumulation. eEF1Bγ binds to the viral RNA and is one of the resident host proteins in the tombusvirus replicase complex. Additional in vitro assays with whole cell extracts prepared from yeast strains lacking eEF1Bγ demonstrated its role in minus-strand synthesis by opening of the structured 3′ end of the viral RNA and reducing the possibility of re-utilization of (+)-strand templates for repeated (-)-strand synthesis within the replicase. We also show that eEF1Bγ plays a synergistic role with eukaryotic translation elongation factor 1A in tombusvirus replication, possibly via stimulation of the proper positioning of the viral RNA-dependent RNA polymerase over the promoter region in the viral RNA template.These roles for translation factors during TBSV replication are separate from their canonical roles in host and viral protein translation.
Accelerated Extra-Gradient Descent: A Novel Accelerated First-Order Method

We provide a novel accelerated first-order method that achieves the asymptotically optimal convergence rate for smooth functions in the first-order oracle model. To this day, Nesterov's Accelerated Gradient Descent (AGD) and variations thereof were the only methods achieving acceleration in this standard blackbox model. In contrast, our algorithm is significantly different from AGD, as it relies on a predictor-corrector approach similar to that used by Mirror-Prox [Nemirovski, 2004] and Extra-Gradient Descent [Korpelevich, 1977] in the solution of convex-concave saddle point problems. For this reason, we dub our algorithm Accelerated Extra-Gradient Descent (AXGD). Its construction is motivated by the discretization of an accelerated continuous-time dynamics [Krichene et al., 2015] using the classical method of implicit Euler discretization. Our analysis explicitly shows the effects of discretization through a conceptually novel primal-dual viewpoint. Moreover, we show that the method is quite general: it attains optimal convergence rates for other classes of objectives (e.g., those with generalized smoothness properties or that are non-smooth and Lipschitz-continuous) using the appropriate choices of step lengths. Finally, we present experiments showing that our algorithm matches the performance of Nesterov's method, while appearing more robust to noise in some cases.
Channel characterization for wideband 60 GHz wireless link within a metal enclosure

A metal cabinet is chosen to emulate the environment within mechatronic systems, which have metal enclosures in general. There is no channel characterization study for such an environment to the best our knowledge. The wireless channel impulse response has been measured in different volumes in closed metal cabinet at 60 GHz, using a frequency sounding technique for a line-of-sight (LOS) scenarios. Large root-mean-square (rms) delay spread (RDS) and very small path loss coefficients are among the distinguishing features of the developed channel model.
RNA Targets and Specificity of Staufen, a Double-stranded RNA-binding Protein in Caenorhabditis elegans*

Background: Staufen binds and regulates structured mRNAs. Results: C. elegans Staufen binds double-stranded RNAs in vitro. 418 putative mRNA targets have been identified. Mutants lacking a single RNA-binding domain enhance RNAi. Conclusion: Staufen associates with target RNAs in vivo. stau-1 mutants perturb RNAi. Significance: RNA targets of Staufen are identified in an intact organism, and a connection between Staufen and RNAi is identified. The Staufen family consists of proteins that possess double-stranded RNA-binding domains (dsRBDs). Staufen proteins of Drosophila and mammals regulate mRNA localization, translation, and decay. We report analysis of Staufen in Caenorhabditis elegans, which we have designated STAU-1. We focus on its biochemical properties, mRNA targets, and possible role in RNAi. We show that STAU-1 is expressed as mRNA and protein at all stages of C. elegans development. The wild-type, full-length protein, purified from bacteria, binds duplex RNA with high affinity in vitro. Purified, mutant proteins lacking single dsRBDs still bind RNA efficiently, demonstrating that no single domain is required for binding to duplex RNA (although dsRBD2 could not be tested). STAU-1 mRNA targets were identified via immunoprecipitation with specific anti-STAU-1 antibodies, followed by microarray analysis (RIP-Chip). These studies define a set of 418 likely STAU-1 mRNA targets. Finally, we demonstrate that stau-1 mutants enhance exogenous RNAi and that stau-1;eri-1 double mutants exhibit sterility and synthetic germ line defects.
Structure-guided SCHEMA recombination generates diverse chimeric channelrhodopsins

Significance Critical for regulating cell function, integral membrane proteins (MPs) are key engineering targets. MP engineering is limited because these proteins are difficult to express with proper plasma membrane localization in heterologous systems. We investigate the expression, localization, and light-induced behavior of the light-gated MP channel, channelrhodopsin (ChR), because of its utility in studying neuronal circuitry. We used structure-guided SCHEMA recombination to generate libraries of chimeric ChRs that are diverse in sequence yet still capable of efficient expression, localization, and useful light-induced functionality. The conservative nature of recombination generates unique protein sequences that tend to fold and function. Recombination is also innovative: chimeric ChRs can outperform their parents or even exhibit properties not known in natural ChRs. Integral membrane proteins (MPs) are key engineering targets due to their critical roles in regulating cell function. In engineering MPs, it can be extremely challenging to retain membrane localization capability while changing other desired properties. We have used structure-guided SCHEMA recombination to create a large set of functionally diverse chimeras from three sequence-diverse channelrhodopsins (ChRs). We chose 218 ChR chimeras from two SCHEMA libraries and assayed them for expression and plasma membrane localization in human embryonic kidney cells. The majority of the chimeras express, with 89% of the tested chimeras outperforming the lowest-expressing parent; 12% of the tested chimeras express at even higher levels than any of the parents. A significant fraction (23%) also localize to the membrane better than the lowest-performing parent ChR. Most (93%) of these well-localizing chimeras are also functional light-gated channels. Many chimeras have stronger light-activated inward currents than the three parents, and some have unique off-kinetics and spectral properties relative to the parents. An effective method for generating protein sequence and functional diversity, SCHEMA recombination can be used to gain insights into sequence–function relationships in MPs.
Keyphrase Extraction From Punjabi Corpus

Punjabi, the official language of the Indian Punjab, is an Indo-Aryan language. Keyphrase extraction is a Natural Language Processing task to identify keyphrases in a document. Keyphrases are groups of words that describe the meaning of a document, provide a brief summary and characterize the document's contents. This paper describes an automated system for extraction of keyphrases from Punjabi corpus.
Logarithmic distributions prove that intrinsic learning is Hebbian

In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas examined. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears to be a general, functional property in all cases analyzed. We then created a generic neural model to investigate adaptive learning rules that create and maintain lognormal distributions. We conclusively demonstrate that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This provides a solution to the long-standing question about the type of plasticity exhibited by intrinsic excitability.