Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Classifier Features for Studying the Effect of Native Language on the Choice of Written Second Language Words

We apply machine learning techniques to study language transfer, a major topic in the theory of Second Language Acquisition (SLA). Using an SVM for the problem of native language classification, we show that a careful analysis of the effects of various features can lead to scientific insights. In particular, we demonstrate that character bigrams alone allow classification levels of about 66% for a 5-class task, even when content and function word differences are accounted for. This may show that native language has a strong effect on the word choice of people writing in a second language.
Maximizing the Throughput in Random Wireless Ad Hoc Networks

This paper focuses on determining the optimum transmission probability that maximizes the per-node throughput in a random wireless ad hoc network. The network self-interference is modeled as a Gaussian random variable which is equal to the sum of the interference from all other transmitting nodes. Given the path loss exponent η, node density λ, and the near field cut-off radius d0, analytical throughput expressions are derived for three different scenarios the AWGN channel, block Rayleigh faded channel with no CSI at the transmitter and the same channel assuming perfect CSI at the transmitter.
Molecular Neuron Realization

Universal Turing machine is a notional computing machine that stimulated work leading to the development of modern computers. The Turing machine operates on finite sequences of symbols by scanning a data type. The striking analogy to information-encoding biochemical reactions on information-carrying molecules was inspired to apply this methodology in neural networks. The essential feature of such approach is hybridization of pairs of complementary DNA strings and possibility to represent highly parallel selective operations, which can enable creating alternative, neural architectures. We describe our original model of molecular neuron based on DNA computing paradigm. During computation appropriate molecules are chosen, each specifying one of the finite number of initial states or processing elements.
Protein Products of the Open Reading Frames Encoding Nonstructural Proteins of Human Astrovirus Serotype 8

ABSTRACT Human astroviruses have a positive-strand RNA genome, which contains three open reading frames (ORF1a, ORF1b, and ORF2). The genomic RNA is translated into two nonstructural polyproteins, nsp1a and nsp1ab, that contain sequences derived from ORF1a and from both ORF1a and ORF1b, respectively. Proteins nsp1a and nsp1ab are thought to be proteolytically processed to yield the viral proteins implicated in the replication of the virus genome; however, the intermediate and final products of this processing have been poorly characterized. To identify the cleavage products of the nonstructural polyproteins of a human astrovirus serotype 8 strain, antisera to selected recombinant proteins were produced and were used to analyze the viral proteins synthesized in astrovirus-infected Caco-2 cells and in cells transfected with recombinant plasmids expressing the ORF1a and ORF1b polyproteins. Pulse-chase experiments identified proteins of approximately 145, 88, 85, and 75 kDa as cleavage intermediates during the polyprotein processing. In addition, these experiments and kinetic analysis of the synthesis of the viral proteins identified polypeptides of 57, 20, and 19 kDa, as well as two products of around 27 kDa, as final cleavage products, with the 57-kDa polypeptide most probably being the virus RNA polymerase and the two ∼27-kDa products being the viral protease. Based on the differential reactivities of the astrovirus proteins with the various antisera used, the individual polypeptides detected were mapped to the virus ORF1a and ORF1b regions.
Direct numerical simulation of turbulent Taylor–Couette flow

We investigate the dynamical and statistical features of turbulent Taylor–Couette flow (for a radius ratio 0.5) through three-dimensional direct numerical simulations (DNS) at Reynolds numbers ranging from 1000 to 8000. We show that in three-dimensional space the Görtler vortices are randomly distributed in banded regions on the wall, concentrating at the outflow boundaries of Taylor vortex cells, which spread over the entirecylinder surface with increasing Reynolds number. Görtler vortices cause streaky structures that form herringbone-like patterns near the wall. For the Reynolds numbers studied here, the average axial spacing of the streaks is approximately 100 viscous wall units, and the average tilting angle ranges from 16° to 20°. Simulationresults have been compared to the experimental data in the literature, and the flow dynamics and statistics are discussed in detail.
Three-dimensional multimodal image-guidance for neurosurgery

The authors address the use of multimodality imaging as an aid to the planning and guidance of neurosurgical procedures, and discuss the integration of anatomical (CT and MRI), vascular (DSA), and functional (PET) data for presentation to the surgeon during surgery. The authors' workstation is an enhancement of a commercially available system, and in addition to the guidance offered via a hand-held probe, it incorporates the use of multimodality imaging and adds enhanced realism to the surgeon through the use of a stereoscopic three-dimensional (3-D) image display. The probe may be visualized stereoscopically in single or multimodality images. The integration of multimodality data in this manner provides the surgeon with a complete overview of brain structures on which he is performing surgery, or through which he is passing probes or cannulas, enabling him to avoid critical vessels and/or structures of functional significance.
Simultaneous informative gene selection and clustering through multiobjective optimization

Clustering methods are used for unsupervised classification of tumor subclasses in microarray gene expression data sets organized in a fashion where the rows represent the tumor samples and columns represent the genes. Clustering algorithms can be very sensitive with respect to the set of features (genes) considered in the clustering process. It is important to select the set of informative and relevant genes to be used for clustering. In this article, a multiobjective genetic algorithm based technique has been proposed for performing the tasks of gene selection and fuzzy clustering simultaneously. A novel encoding technique is developed in this regard and the algorithm searches for the best cluster centers while minimizing the number of selected genes. The number of clusters is evolved automatically. The performance of the proposed technique has been illustrated on an artificial data set and compared with that of several other related feature selection/clustering approaches. Moreover its performance is demonstrated on two real life multi-class gene expression data sets viz., Brain tumor and Lung tumor data sets.
Learning from Examples: Instructional Principles from the Worked Examples Research

Worked examples are instructional devices that provide an expert's problem solution for a learner to study. Worked-examples research is a cognitive-experimental program that has relevance to classroom instruction and the broader educational research community. A frame- work for organizing the findings of this research is proposed, leading to instructional design principles. For instance, one instructional design principle suggests that effective examples have highly integrated components. They employ multiple modalities in presentation and emphasize conceptual structure by labeling or segmenting. At the lesson level, effective instruction employs multiple examples for each conceptual problem type, varies example formats within problem type, and employs surface features to signal deep structure. Also, examples should be presented in close proximity to matched practice problems. More- over, learners can be encouraged through direct training or by the structure of the worked example to actively self:explain examples. Worked examples are associated with early stages of skill development, but the design principles are relevant to constructivist research and teaching.
Causality, analyticity and an IR obstruction to UV completion

We argue that certain apparently consistent low-energy effective field theories described by local, Lorentzinvariant Lagrangians, secretly exhibit macroscopic non-locality and cannot be embedded in any UV theory whose S-matrix satisfies canonical analyticity constraints. The obstruction involves the signs of a set of leading irrelevant operators, which must be strictly positive to ensure UV analyticity. An IR manifestation of this restriction is that the “wrong” signs lead to superluminal fluctuations around non-trivial backgrounds, making it impossible to define local, causal evolution, and implying a surprising IR breakdown of the effective theory. Such effective theories can not arise in quantum field theories or weakly coupled string theories, whose S-matrices satisfy the usual analyticity properties. This conclusion applies to the DGP brane-world model modifying gravity in the IR, giving a simple explanation for the difficulty of embedding this model into controlled stringy backgrounds, and to models of electroweak symmetry breaking that predict negative anomalous quartic couplings for the W and Z. Conversely, any experimental support for the DGP model, or measured negative signs for anomalous quartic gauge boson couplings at future accelerators, would constitute direct evidence for the existence of superluminality and macroscopic non-locality unlike anything previously seen in physics, and almost incidentally falsify both local quantum field theory and perturbative string theory.
Evaluation of Oat Kernel Size Uniformity

Oat (Avena sativa L.) kernel size uniformity is important to the oat milling industry because oat-processing mills separate oats according to size to optimize dehulling efficiency. In this study, we compared two different approaches for analyzing oat kernel size uniformity, namely the sequential sieving of oat samples with a gradient of slotted sieve sizes and digital image analysis. Image analysis of size fractions provided evidence that sieving separated oat kernels according to their depth, whereas, digital image analysis measured kernel length and width, and derived a measure of the area of the oat kernel image. Samples identified by sieving with superior uniformity were those with greater proportions of large kernels. Histograms of oat kernel sizes derived from digital image analysis suggested oat kernel sizes were (within a genotype and location) composed of bimodal populations. A new statistical analysis allowed for the derivation of means and variances of each of these subpopulations, the numerical balance between the two subpopulations, and the extent of bimodality. Oat samples with lower levels of bimodality tended to be of higher test weight and groat percentage and thus, of better milling quality. Both methods appear satisfactory for evaluating oat kernel size uniformity, although the sequential sieving method is likely to be more useful to breeding programs because of its relative technical ease and simplicity.
Reading spike timing without a clock: intrinsic decoding of spike trains

The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access information in precise time-varying neural responses. Here, we review approaches to test the hypothesis that the activity of neural populations provides the temporal reference frames needed to decode temporal spike patterns. These approaches are based on comparing the single-trial stimulus discriminability obtained from neural codes defined with respect to network-intrinsic reference frames to the discriminability obtained from codes defined relative to the experimenter's computer clock. Application of this formalism to auditory, visual and somatosensory data shows that information carried by millisecond-scale spike times can be decoded robustly even with little or no independent external knowledge of stimulus time. In cortex, key components of such intrinsic temporal reference frames include dedicated neural populations that signal stimulus onset with reliable and precise latencies, and low-frequency oscillations that can serve as reference for partitioning extended neuronal responses into informative spike patterns.
Flow cytometric parameters for characterizing platelet activation by measuring P-selectin (CD62) expression: theoretical consideration and evaluation in thrombin-treated platelet populations.

Two flow cytometric parameters are generally used to quantify platelet activation as measured by P-selectin (CD62) expression: percentage and mean channel fluorescence of CD62-positive platelets (%(+) and MCF(+), respectively). We describe a method for calculation of indices of platelet activation for positive (IPA(+)) and total (IPA(Sigma)) platelets, which reflect integrated amounts of CD62 expressed in these populations; IPA(+) is calculated as the product of %(+) and MCF(+), whereas IPA(Sigma) is exclusively determined by mean fluorescence of the total platelet population (MCF(Sigma)) and does not depend on %(+). We use these parameters to characterize human platelet activation in whole blood samples treated with varying human alpha-thrombin concentrations, mimicking the variations in platelet activation in a number of clinical settings. Multiparameter analysis of CD62 expression may be useful for selective diagnosis of disorders with systemic or localized platelet activation and for monitoring the clinical course of the disease and effect of therapeutic interventions.
The synthetic triterpenoid RTA dh404 (CDDO-dhTFEA) restores Nrf2 activity and attenuates oxidative stress, inflammation, and fibrosis in rats with chronic kidney disease

Abstract 1. Chronic oxidative stress and inflammation are major mediators of chronic kidney disease (CKD) and result in impaired activation of the cytoprotective transcription factor Nrf2. Given the role of oxidative stress and inflammation in CKD pathogenesis, strategies aimed at restoring Nrf2 activity may attenuate CKD progression. 2. The present study investigated whether the synthetic triterpenoid RTA dh404 (2-cyano-3,12-dioxooleana-1,9-dien-28-oic acid-9,11-dihydro-trifluoroethyl amide or CDDO-dhTFEA) would afford renal protection in a 5/6 nephrectomized rat model of CKD. RTA dh404 (2 mg/kg/day) was orally administered once daily for 12 weeks after 5/6 nephrectomy surgery. 3. The remnant kidneys from the vehicle-treated CKD rats showed activation of nuclear factor kappaB (NF-κB), upregulation of NAD(P)H oxidase, glomerulosclerosis, interstitial fibrosis and inflammation, as well as marked reductions in Nrf2 and its target gene products (i.e. catalase, heme oxygenase-1, thioredoxin 1, thioredoxin reductase 1 and peroxiredoxin 1). The functional and structural deficits in the kidney were associated with increased (∼30%) mean arterial pressure (MAP). Treatment with RTA dh404 restored MAP, increased Nrf2 and expression of its target genes, attenuated activation of NF-κB and transforming growth factor-β pathways, and reduced glomerulosclerosis, interstitial fibrosis and inflammation in the CKD rats. 4. Thus, chronic treatment with RTA dh404 was effective in restoring Nrf2 activity and slowing CKD progression in rats following 5/6 nephrectomy.
Informed data distribution selection in a self-predicting storage system

Systems should be self-predicting. They should continuously monitor themselves and provide quantitative answers to What.if questions about hypothetical workload or resource changes. Self-prediction would significantly simplify administrators' decision making, such as acquisition planning and performance tuning, by reducing the detailed workload and internal system knowledge required. This paper describes and evaluates support for self-prediction in a cluster-based storage system and its application to What.if questions about data distribution selection.
Outage probability analysis in cellular systems with noisy Weibull-faded lognormal-shadowed links

We consider the problem of determining the outage probability in cellular systems where each of the links is lognormal-shadowed, Weibull-faded and corrupted by additive noise. We propose two solutions for this problem; a simple lower bound on the outage probability based on the concavity of the logarithmic function and an approximate expression based on the use of the central limit theorem. The approximate expression is slightly more complicated than the lower bound but provides a better accuracy for most of the parameters values. We verify the accuracy of the proposed expressions by comparing them to the outage probability obtained by means of Monte Carlo simulations.
Building expressive, area-efficient coherence directories

Mainstream chip multiprocessors already include a significant number of cores that make straightforward snooping-based cache coherence less appropriate. Further increase in core count will almost certainly require more sophisticated tracking of data sharing to minimize unnecessary messages and cache snooping. Directory-based coherence has been the standard solution for large-scale shared-memory multiprocessors and is a clear candidate for on-chip coherence maintenance. A vanilla directory design, however, suffers from inefficient use of storage to keep coherence metadata. The result is a high storage overhead for larger scales. Reducing this overhead leads to saving of resources that can be redeployed for other purposes. In this paper, we exploit familiar characteristics of coherence metadata, but with novel angles and propose two practical techniques to increase the expressiveness of directory entries, particularly for chip-multiprocessors. First, it is well known that the vast majority of cache lines have a small number of sharers. We exploit a related fact with a subtle but important difference: that a significant portion of directory entries only need to track one node. We can thus use a hybrid representation of sharers list for the whole set. Second, contiguous memory regions often share the same coherence characteristics and can be tracked by a single entry. We propose a multi-granular mechanism that does not rely on any profiling, compiler, or OS support to identify such regions. Moreover, it allows co-existence of line and region entries in the same locations, thus making regions more applicable. We show that both techniques improve the expressiveness of directory entries, and, when combined, can reduce directory storage by more than an order of magnitude with negligible loss of precision.
M-TCP + : Using Disconnection Feedback to Improve Performance of TCP in Wired / Wireless Networks

In this paper, we propose the M-TCP algorithm for heterogeneous wired/wireless networks. The algorithm is a modification of M-TCP that was proposed for deployment in mobile cellular networks. It is recommended that Internet hosts enable the delayed acknowledgement (delayed ACK) option to maximize network bandwidth by reducing the number of ACKs sent to a TCP sender by a TCP receiver. The M-TCP algorithm performs best when the TCP delayed ACK option is enabled. The algorithm relies on feedback sent from a wireless host in anticipation of disconnections. We compare the performance of the MTCP algorithm with the performance of M-TCP, TCP NewReno, and TCP SACK in both the absence and the presence of disconnections for a file transfer protocol (download) application. We also simulate network scenarios with traffic congestion. The M-TCP algorithm performance is evaluated in terms of file download response time, goodput, and retransmission ratio, with and without the delayed ACK option. In scenarios without disconnections, the M-TCP algorithm does not introduce significant processing delay. Furthermore, in scenarios with disconnections, the M-TCP algorithm shows 2%–15% performance improvement.
A framework for multi-valued reasoning over inconsistent viewpoints

In requirements elicitation, different stakeholders often hold different views of how a proposed system should behave, resulting in inconsistencies between their descriptions. Consensus may not be needed for every detail, but it can be hard to determine whether a particular disagreement affects the critical properties of the system. We describe the Xbel framework for merging and reasoning about multiple, inconsistent state machine models. Xbel permits the analyst to choose how to combine information from the multiple viewpoints, where each viewpoint is described using an underlying multi-valued logic. The different values of our logics typically represent different levels of agreement. Our multi-valued model checker, Xchek, allows us to check the merged model against properties expressed in a temporal logic. The resulting framework can be used as an exploration tool to support requirements negotiation, by determining what properties are preserved for various combinations of inconsistent viewpoints.
Automatic edition of songs for Guitar Hero/Frets on Fire

In this contribution, an automatic system of song edition for Guitar Hero/Frets on Fire is presented. The system performs three fundamental stages: time analysis, frequency analysis and button allocation. The temporal analysis of the musical signal is used to obtain the rhythmic pattern of the song. The frequency analysis is perform on the basis of aMel filter bank because these filters provide an approximation to the human perception of low and high frequency sounds. The allocation of buttons is done using the rhythmic pattern extracted, the Mel filters outputs and, also, taking into account a selectable difficulty level. The distributions of the buttons obtained with the designed system are similar to the ones found in the predetermined songs of the games.
Processing Dictionary Definitions with Phrasal Pattern Hierarchies

This paper shows how dictionary word sense definitions can be analysed by applying a hierarchy of phrasal patterns. An experimental system embodying this mechanism has been implemented for processing definitions from the Longman Dictionary of Contemporary English. A property of this dictionary, exploited by the system, is that it uses a restricted vocabulary in its word sense definitions. The structures generated by the experimental system are intended to be used for the classification of new word senses in terms of the senses of words in the restricted vocabulary. Examples illustrating the output generated are presented, and some qualitative performance results and problems that were encountered are discussed. The analysis process applies successively more specific phrasal analysis rules as determined by a hierarchy of patterns in which less specific patterns dominate more specific ones. This ensures that reasonable incomplete analyses of the definitions are produced when more complete analyses are not possible, resulting in a relatively robust analysis mechanism. Thus the work reported addresses two robustness problems faced by current experimental natural language processing systems: coping with an incomplete lexicon and with incomplete knowledge of phrasal constructions.