Miracle-dz/UniFAR-FTUs huggingface dataset:
Cartography of Methicillin-Resistant S. aureus Transcripts: Detection, Orientation and Temporal Expression during Growth Phase and Stress Conditions

Background Staphylococcus aureus is a versatile bacterial opportunist responsible for a wide spectrum of infections. The severity of these infections is highly variable and depends on multiple parameters including the genome content of the bacterium as well as the condition of the infected host. Clinically and epidemiologically, S. aureus shows a particular capacity to survive and adapt to drastic environmental changes including the presence of numerous antimicrobial agents. Mechanisms triggering this adaptation remain largely unknown despite important research efforts. Most studies evaluating gene content have so far neglected to analyze the so-called intergenic regions as well as potential antisense RNA molecules. Principal Findings Using high-throughput sequencing technology, we performed an inventory of the whole transcriptome of S. aureus strain N315. In addition to the annotated transcription units, we identified more than 195 small transcribed regions, in the chromosome and the plasmid of S. aureus strain N315. The coding strand of each transcript was identified and structural analysis enabled classification of all discovered transcripts. RNA purified at four time-points during the growth phase of the bacterium allowed us to define the temporal expression of such transcripts. A selection of 26 transcripts of interest dispersed along the intergenic regions was assessed for expression changes in the presence of various stress conditions including pH, temperature, oxidative shocks and growth in a stringent medium. Most of these transcripts showed expression patterns specific for the defined stress conditions that we tested. Conclusions These RNA molecules potentially represent important effectors of S. aureus adaptation and more generally could support some of the epidemiological characteristics of the bacterium.
Comparison of serve and serve return statistics of high performance male and female tennis players from different age-groups

The serve and the serve return performance of professional, high performance Under-16 and high performance Under-12 male and female players was examined. Collectively, the players served approximately 60% of their first serves in. A significant gender by player group interaction was found for serving aces. Male professionals served significantly more aces than the Under-16 and Under-12 male players (p < .001) and female professional players (p < .004). Female professional players served more aces than the Under-12 female players (p < .003). Independent of gender, player group differences were noted with professionals serving significantly fewer double faults, winning a significantly greater percentage of points on first serve, and winning significantly more points on second serve return than the Under-16 and Under-12 groups (p < .001). The professionals also won a significantly higher percentage of points on second serve return than first serve return (p < .004). However, the male professionals won significantly fewer points on first serve return compared to all other groups (p < .001). The findings point to both age-group and gender differences in the way that the serve and serve return are used in matchplay. Coaches should be aware of these differences and structure their players training accordingly.
Entwicklung professioneller Handlungskompetenzen in der universitären Lehrerinnen- und Lehrerbildung: Erprobung und Wirkung eines Lehrveranstaltungskonzepts zum individualisierten Unterricht

Die universitäre Lehrerinnen- und Lehrerbildung steht vor der Herausforderung, Studierende auf die Anforderungen gemäss den KMK-Standards für die Lehrerbildung vorzubereiten. Damit werden Konzepte benötigt, mit denen sich professionelle Handlungskompetenzen entwickeln lassen. Im erprobten Lehrveranstaltungskonzept zum individualisierten Rechtschreibunterricht wurden fachwissenschaftliche und fachdidaktische Inhalte mit praktischer Erprobung verzahnt und die Kompetenzentwicklung der Studierenden wurde über subjektive Einschätzungen geprüft. Die Befunde zeigen hohe Zugewinne in den Kompetenzbereichen «Unterrichten» und «Erziehen», am höchsten fielen sie im Bereich «Beurteilen» aus.
Neglect of information privacy instruction: a case of educational malpractice?

Not only should InformationTechnology (IT) Educators be knowledgeable regarding data privacy legislation but they should be teaching correct system and database design principles to IT students in order to ensure future application design compliance with international legislative trends. Perhaps the most contentious and serious issue facing IT practitioners in the world today is data privacy. Data Privacy impacts every aspect of IT from database and application design to privacy and use policies, and system security and information assurance. The European Union Directive legislation has aggressively set the pattern of excellence in preserving individual data privacy worldwide, and Canada's Personal Information Protection and Electronic Document Act exerts an influence on U.S. commerce Within the U.S. laws such as the Health Insurance Portability and Accountability Act and the Gramm-Leach-Bliley Act seek to protect information privacy in specific industries.
A Scalable DDoS Detection Framework with Victim Pinpoint Capability

In recent years, various intrusion detection and prevention systems have been proposed to detect DDoS attacks and mitigate the caused damage. However, many existing IDS systems still keep per-flow state to detect anomaly, and thus do not scale with link speeds in multigigabit networks. In this paper, we present a two-level approach for scalable and accurate DDoS attack detection by exploiting the asymmetry in the attack traffic. In the coarse level, we use a modified count-min sketch (MCS) for fast detection, and in the fine level, we propose a bidirectional count sketch (BCS) to achieve better accuracy. At both detection levels, sketch structures are utilized to ensure the scalability of our scheme. The main advantage of our approach is that it can track the victims of attacks without recording every IP address found in the traffic. Such feature is significant for the detection in the highspeed environment. We also propose a SRAM-based parallel architecture to achieve high-speed process. Furthermore, we analyze accuracy estimation issues to provide hints for practical deployment with constraint memory. We finally demonstrate how to extend our original scheme to a collaborative detection framework. Experimental results using the real Internet traffic show that our approach is able to quickly detect anomaly events and track those victims with a high level of accuracy while it can save over 90% key storage compared with previous sketch-based approaches.
Story segmentation for speech transcripts in sparse data conditions

Information Retrieval systems determine relevance by comparing information needs with the content of potential retrieval units. Unlike most textual data, automatically generated speech transcripts cannot by default be easily divided into obvious retrieval units due to a lack of explicit structural markers. This problem can be addressed by automatically detecting topically cohesive segments, or stories. However, when the content collection consists of speech from less formal domains than broadcast news, most of the standard automatic boundary detection methods are potentially unsuitable due to their reliance on learned features. In particular for conversational speech, the lack of adequate training data can present a significant issue. In this paper four methods for automatic segmentation of speech transcriptions are compared. These are selected because of their independence from collection specific knowledge and implemented without the use of training data. Two of the four methods are based on existing algorithms, the others are novel approaches based on a dynamic segmentation algorithm (QDSA) that incorporates information about the query, and WordNet. Experiments were done on a task similar to TREC SDR unknown boundaries condition. For the best performing system, QDSA, the retrieval scores for a tfidf-type ranking function were equivalent to a reference segmentation, and improved through document length normalization using the bm25/Okapi method. For the task of automatically segmenting speech transcripts for use in information retrieval, we conclude that a training-poor processing paradigm which can be crucial for handling surprise data is feasible.
Encoding Pointer Information for Querying and Reusing

We study the encoding scheme to enable efficient querying and reusing of pointer information (points-to, aliasing, ModRef, etc.). We empirically figure out the equivalence and hub properties and develop a scheme, PesTrie, to encode pointer information. The experiment shows that, PesTrie yields 10X and 14.8X smaller storage files than traditional bitmap and BDD encoding. With compactness at time, PesTrie encoding is orders of magnitude faster than traditional on-demand way to serve queries.
Genomic and Secretomic Analyses Reveal Unique Features of the Lignocellulolytic Enzyme System of Penicillium decumbens

Many Penicillium species could produce extracellular enzyme systems with good lignocellulose hydrolysis performance. However, these species and their enzyme systems are still poorly understood and explored due to the lacking of genetic information. Here, we present the genomic and secretomic analyses of Penicillium decumbens that has been used in industrial production of lignocellulolytic enzymes in China for more than fifteen years. Comparative genomics analysis with the phylogenetically most similar species Penicillium chrysogenum revealed that P. decumbens has evolved with more genes involved in plant cell wall degradation, but fewer genes in cellular metabolism and regulation. Compared with the widely used cellulase producer Trichoderma reesei, P. decumbens has a lignocellulolytic enzyme system with more diverse components, particularly for cellulose binding domain-containing proteins and hemicellulases. Further, proteomic analysis of secretomes revealed that P. decumbens produced significantly more lignocellulolytic enzymes in the medium with cellulose-wheat bran as the carbon source than with glucose. The results expand our knowledge on the genetic information of lignocellulolytic enzyme systems in Penicillium species, and will facilitate rational strain improvement for the production of highly efficient enzyme systems used in lignocellulose utilization from Penicillium species.
Lifting factorization and design based on stationary wavelet transform

The main advantage of the stationary wavelet transform is its translation invariance of the wavelet coefficients. In this paper, based on the polyphase representation of wavelet transform, a new structure is proposed to that the traditional stationary wavelet transform can be obtained with a finite number of alternating lifting and dual lifting steps starting from the Lazy wavelet, using the equivalent relation of position-swapping between up (down) sampler and filter. Moreover, one can increase the vanishing moments of stationary wavelet by designing proper (dual) lifting steps. It overcomes the drawback in former algorithm, which can only be used to design interpolating wavelets starting from odd-even splitting. Furthermore, we present that the asymptotically reduces the computational complexity of the standard algorithm by a factor two.
A Comparison of Different Strategies for Automated Semantic Document Annotation

We introduce a framework for automated semantic document annotation that is composed of four processes, namely concept extraction, concept activation, annotation selection, and evaluation. The framework is used to implement and compare different annotation strategies motivated by the literature. For concept extraction, we apply entity detection with semantic hierarchical knowledge bases, Tri-gram, RAKE, and LDA. For concept activation, we compare a set of statistical, hierarchy-based, and graph-based methods. For selecting annotations, we compare top-k as well as kNN. In total, we define 43 different strategies including novel combinations like using graph-based activation with kNN. We have evaluated the strategies using three different datasets of varying size from three scientific disciplines (economics, politics, and computer science) that contain 100, 000 manually labeled documents in total. We obtain the best results on all three datasets by our novel combination of entity detection with graph-based activation (e.g., HITS and Degree) and kNN. For the economic and political science datasets, the best F-measure is . 39 and . 28, respectively. For the computer science dataset, the maximum F-measure of . 33 can be reached. The experiments are the by far largest on scholarly content annotation, which typically are up to a few hundred documents per dataset only.
An Efficient Static Algorithm for Computing the Soft Error Rates of Combinational Circuits

Soft errors have emerged as an important reliability challenge for nanoscale VLSI designs. In this paper, we present a fast and efficient soft error rate (SER) computation algorithm for combinational circuits. We first present a novel parametric waveform model based on the Weibull function to represent particle strikes at individual nodes in the circuit. We then describe the construction of the SET descriptor that efficiently captures the correlation between the transient waveforms and their associated rate distribution functions. The proposed algorithm consists of operations to inject, propagate and merge SET descriptors while traversing forward along the gates in a circuit. The parameterized waveforms enable an efficient static approach to calculate the SER of a circuit. We exercise the proposed approach on a wide variety of combinational circuits and observe that our algorithm has linear runtime with the size of the circuit. The runtimes for soft error estimation were observed to be in the order of about one second, compared to several minutes or even hours for previously proposed methods
Section: Behavioral/systems/cognitive Neuroscience 6 7 8

1 2 Title: Low-intensity electric fields induce two distinct response components in 3 neocortical neuronal populations. 4 5 Running title: Cortical activity evoked by low-intensity electric fields 6 7 8 Authors: Weifeng Xu , Brian S. Wolff 2, 1, , and Jian-young Wu* 9 1. Department of Neuroscience, Georgetown University Medical Center, Washington, 10 DC 20057, USA 11 2. Georgetown University Medical center Interdepartmental Program of Neuroscience 12 3. These two authors contributed equally to this work. 13 * Correspondence: wuj@georgetown.edu 14 15 Corresponding Author: Jian-young Wu 16 Georgetown University 17 Department of Neuroscience 18 Basic Science Building 207A, 3900 Reservoir Road, NW, Washington, DC 20057, USA 19 Phone: (202) 687-1614 Fax: (202) 687-0617 20 Email: wuj@georgetown.edu 21 22 23 Articles in PresS. J Neurophysiol (August 13, 2014). doi:10.1152/jn.00740. 2013
Receptive Fields of Visual Neurons: The Early Years

This paper traces the history of the visual receptive field (RF) from Hartline to Hubel and Wiesel. Hartline (1938, 1940) found that an isolated optic nerve fiber in the frog could be excited by light falling on a small circular area of the retina. He called this area the RF, using a term first introduced by Sherrington (1906) in the tactile domain. In 1953 Kuffler discovered the antagonistic center—surround organization of cat RFs, and Barlow, Fitzhugh, and Kuffler (1957) extended this work to stimulus size and state of adaptation. Shortly thereafter, Lettvin and colleagues (1959) in an iconic paper asked “what the frog's eye tells the frog's brain”. Meanwhile, Jung and colleagues (1952–1973) searched for the perceptual correlates of neuronal responses, and Jung and Spillmann (1970) proposed the term perceptive field (PF) as a psychophysical correlate of the RF. The Westheimer function (1967) enabled psychophysical measurements of the PF center and surround in human and monkey, which correlated closely with the underlying RF organization. The sixties and seventies were marked by rapid progress in RF research. Hubel and Wiesel (1959–1974), recording from neurons in the visual cortex of the cat and monkey, found elongated RFs selective for the shape, orientation, and position of the stimulus, as well as for movement direction and ocularity. These findings prompted the emergence in visual psychophysics of the concept of feature detectors selective for lines, bars, and edges, and contributed to a model of the RF in terms of difference of Gaussians (DOG) and Fourier channels. The distinction between simple, complex, and hypercomplex neurons followed. Although RF size increases towards the peripheral retina, its cortical representation remains constant due to the reciprocal relationship with the cortical magnification factor (M). This constitutes a uniform yardstick for M-scaled stimuli across the retina. Developmental studies have shown that RF properties are not fixed. RFs possess their full response inventory already at birth, but require the interaction with appropriate stimuli within a critical time window for refinement and consolidation. Taken together these findings paved the way for a better understanding of how objective properties of the external world are encoded to become subjective properties of the subjective, perceptual world.
The effects of familiarity and first impressions on eyewitness testimony in a target-absent line-up

Eyewitness identification is often the leading factor contributing to convictions, however, eyewitness misidentifications are the leading cause of the incarceration of innocent persons. Even more troubling is that eyewitness identifications are often made with high confidence. Familiarity is a key component of eyewitness identification. Familiarity refers to our recognition of familiar faces – friends, celebrities and even unfamiliar faces learned during experiments. First impressions, on the other hand, are the snap judgments we make about a person’s character and intentions based on their facial features, attractiveness and race. The present study will investigate 1) whether eyewitness identifications are affected by the target being familiar; 2) if being familiar leads to more accurate identifications; and 3) if our first impressions of a target (positive, negative, or neutral target description) affect our identification accuracy and perceptions of guilt. We will also investigate if our perceptions differ based on the race of a target.
Multichannel Analysis of Underwater Surface Waves Near Vancouver, B.C., Canada

Surface (Scholte) waves acquired during underwater seismic surveys with hydrophone arrays are analyzed using the multichannel analysis of surface waves (MASW) method to construct shear-wave velocity (Vs) profiles for the upper 40-m of water-bottom sediments in the Fraser River delta area, near Vancouver, British Columbia, Canada. Shear wave profiles are obtained using the Rayleigh-wave inversion method (based on the multimodal dispersion curves) since theory suggests the difference in phase velocities between the two types of surface waves (i.e., the Scholte vs. the Rayleigh waves) is minor and usually falls below the uncertainty of the measurement. Vs profiles calculated from dispersion analysis are compared with measured Vs profiles available from nearby land boreholes (within a few hundred meters of the underwater sites). The comparison shows MASW values are in good agreement with the overall trend of borehole values, but lower in general by about ten percent. This shift seems to be attributable to the water-bottom sediments being softer and their density being greater (at depths < 5 m) than sediments on land. Simple multichannel processing (surgical mute) seems critical to suppress the influence of the strong broad-band channel waves trapped in the water layer before extracting the dispersion curve.
Neural substrates of cognitive emotion regulation: a brief review

ABSTRACT The current paper aims to review the recent evidence on the neural correlates of emotion regulation. The review is organized into two main sections. First, cognitive models that neuroimaging research is based on are introduced with a specific emphasis on the process-specific explanations of emotion regulation. In the second section, neuroimaging research is discussed in line with the evidence from human and nonhuman animals. Existing evidence suggests that regulation of emotions may be achieved either by bottom-up, subcortical, or top-down frontal mechanisms. The former way acts on the initial phases of emotion generation, whereas the latter appears to influence the higher-order structures for cognitive change and modulation of emotional responses. Although there is still an ongoing debate on when the generation stops and regulation starts on the emotion process, with respect to neural mechanisms, underlying regulatory strategies appear to be more consistent. Potential questions are also addressed for future research to contribute to especially the individual differences adaptive emotion regulation.
Description of the Minimizers of Least Squares Regularized with 퓁0-norm. Uniqueness of the Global Minimizer

We have an $\sf{M}\times\sf{N}$ real-valued arbitrary matrix $A$ (e.g., a dictionary) with $\sf{M} 0$. For several decades, this objective has attracted a ceaseless effort to conceive algorithms approaching a good minimizer. Our theoretical contributions, summarized below, shed new light on the existing algorithms and can help in the conception of innovative numerical schemes. Solving the normal equation associated with any $\sf{M}$-row submatrix of $A$ is equivalent to computing a local minimizer $\hat u$ of ${\mathcal{F}}_d$. (Local) minimizers $\hat u$ of ${\mathcal{F}}_d$ are strict if and only if the submatrix, composed of those columns of $A$ wh.
RRT∗-Connect: Faster, asymptotically optimal motion planning

We present an efficient asymptotically-optimal randomized motion planning algorithm solving single-query path planning problems using a bidirectional search. The algorithm combines the benefits from the widely known algorithms RRT-Connect and RRT* and scores better than both by finding a solution faster than RRT*, and -unlike RRT-Connect - converging towards a theoretical optimum. We outline the proposed algorithm and proof its optimality. The efficiency and robustness is demonstrated in a number of real world applications which benefit from the bidirectional approach: planning car trajectories in a parking garage for the autonomous vehicle CoCar, generating cost-efficient trajectories for the multi-legged walking robot LAURON V in a planetary exploration scenario and performing mobile manipulation tasks for our highly actuated service robot HoLLiE. Moreover, we compare and show the improvements over "vanilla" RRT in a set of challenging benchmarks. RRT*-Connect will contribute to increase the performance of autonomous robots and vehicles due to the reduced motion planning time in complex environments.