Miracle-dz/UniFAR-FTUs huggingface dataset:
A language for inquiring about the run‐time behaviour of programs

This paper describes a language for studying the behaviour of programs, based upon the data collected while these programs are executed by a computer. Besides being a useful tool in debugging, the language is also valuable in the experimental evaluation of the complexity of algorithms, in studying the interdependence of conditionals in a program and in determining the feasibility of transporting programs from one machine to another. The program one wishes to analyse is written in an Algol 60‐like language; when the program is executed it automatically stores, in a data base, the information needed to answer general questions about computational events which occurred during execution. This information consists (basically) of the list of labels passed while the program is being executed, and the current values of the variables. Since the list of labels is describable by regular expressions, these expressions can also be used to identify specific subparts of the list and therefore allow access to the values of the variables. This constitutes the basis for the design of the inquiry language. The user's questions are automatically answered by a processor which inspects the previously generated data base. The paper also presents examples of the use of the language and describes the implementation of its processor.
BioTorrents: A File Sharing Service for Scientific Data

The transfer of scientific data has emerged as a significant challenge, as datasets continue to grow in size and demand for open access sharing increases. Current methods for file transfer do not scale well for large files and can cause long transfer times. In this study we present BioTorrents, a website that allows open access sharing of scientific data and uses the popular BitTorrent peer-to-peer file sharing technology. BioTorrents allows files to be transferred rapidly due to the sharing of bandwidth across multiple institutions and provides more reliable file transfers due to the built-in error checking of the file sharing technology. BioTorrents contains multiple features, including keyword searching, category browsing, RSS feeds, torrent comments, and a discussion forum. BioTorrents is available at http://www.biotorrents. net.
Dopaminergic function in the psychosis spectrum: an [18F]-DOPA imaging study in healthy individuals with auditory hallucinations.

BACKGROUND The psychosis phenotype appears to exist in the population as a continuum, but it is not clear if subclinical psychotic symptoms and psychotic disorders share the same neurobiology. We investigated whether the dopaminergic dysfunction seen in psychotic disorders is also present in healthy, well-functioning people with hallucinations. METHODS We compared dopamine synthesis capacity (using 6-[(18)F]fluoro-L-DOPA [[(18)F]-DOPA] positron emission tomography imaging) in 16 healthy individuals with frequent persistent auditory verbal hallucinations (hallucinating group) with that in 16 matched controls. RESULTS There was no significant difference in dopamine synthesis capacity in the striatum, or its functional subdivisions, between groups and no relationship between subclinical psychotic symptom severity or schizotypal traits and dopamine synthesis capacity in the hallucinating group. CONCLUSIONS Altered dopamine synthesis capacity is unlikely to underlie subclinical hallucinations, suggesting that although there may be a phenomenological psychosis continuum, there are distinctions at the neurobiological level.
Multi-view image inpainting with sparse representations

This paper proposes a patch based image inpainting algorithm for multi-view images. In our framework we fill the holes which are created by removing objects from an image pair. We assume that a user provides two masks to remove objects from an image pair. Our algorithm consists of two stages. In the first stage we align the images and construct an exemplar dictionary with the patches sampled from the reference as well as the warped image. In the second stage, the reference image is iteratively filled by choosing patches along the boundary of the hole. We use l1-minimization framework to estimate the unknown pixels. This proposed method is observed to outperform existing techniques that are built upon exemplar based sparse reconstruction.
Predicting Bank Failures: A neural network approach

The purpose of this paper is to present a neural network approach to predicting bank failures and to compare it with existing prediction methods. The task of constructing a prediction model is cast as one of training a network with a set of bankruptcy cases. Empirical results show that neural network is a competitive method among existing ones in assessing the likelihood of bank failures, especially in reducing type I misclassification rate. Issues relating to the potential and limitations of.neural network as a modeling tool are also addressed.
The length of stay determinants for sun-and-sand tourism: an application for the Region of Murcia

While tourist arrivals increase annually in Spain, tourist average real expenditure has decreased significantly over the last few years, with important effects on tourism revenues. The process is clearly driven by the reduction of the length of stay of tourists at destinations, but surprisingly this variable has received little attention in the literature. We estimate a length of stay function for sun-and-sand tourists visiting the Region of Murcia over the period 2002-2006 using count data models. Our results show that both tourists’ personal and family characteristics together with economic variables (budget restrictions, income and prices) are key factors in determining the duration of the stay. Quantitative identification of the determinants of a tourist’s length of stay could provide important guidelines for designing policies aimed at influencing length of stay in tourist‘s seaside destinations.
Knowledge-free discovery of domain-specific multiword units

The discovery of multiword units is one of the key steps in the preprocessing of raw text. In this paper, we propose a know ledge-free approach for the discovery on such entities- It does not only outperform state-of-the-art approaches, but is also fully unsupervised. Furthermore, it does not demand the setting of any threshold, making it appropriate for usage by non-experts. The approach proposed is evaluated against five other metrics on a medical corpus.
Trust and Knowledge Transfer between Business Partners: the Mediating Effects of Three Factors

Knowledge transfer is of vital importance for business partners. The influence of trust between business partners in particular on knowledge transfer is evident. However, it is not clear how the relationship between trust and knowledge transfer works. This study provides a better understanding of that relationship by demonstrating that communication, cooperative behavior and fear of losing one's unique value have a mediating effect on the relationship between trust and knowledge transfer. Specifically, trust increases knowledge transfer through improving communication, improving cooperative behavior, and reducing fear of losing one's unique value. These findings have important implications at both a managerial and theoretical level. For managers, this paper emphasizes trust's central role in the knowledge transfer process in terms of communication, cooperative behavior and fear of losing one's unique value. On the theoretical level, this study provides empirical evidence for three mechanisms that help explain the effect of trust on knowledge transfer between business partners.
Ferroelectric Liquid Crystal Dammann Grating by Patterned

In this article, a ferroelectric liquid crystal (FLC) dammann grating (DG) is demonstrated based on the patterned photoalignment technology. By applying low electric field (10 V) on the FLC DG, the grating can switch between a diffractive state with 7 × 7 optical spots array and a non-diffractive state, depending on the polarity of electric field. The FLC DG shows very fast switching speed with switching on time and off time to be only 81 μs and 59 μs respectively. Comparing with other fast LC DGs such as the ones based on blue phase LC or dual-frequency LC, the switching speed of the proposed FLC DG is about one order faster, which provides great potential and perspective for the FLC DG to be applied in a broad range of optical applications such as optical communication and beam shaping.
Observed Variation of Three‐Dimensional Return Stroke Speeds Along the Channel in Rocket‐Triggered Lightning

An improved very high frequency location system, multiple antenna radiation continuous observation system (MARCOS), is combined with high‐speed video observation to explore radiation source evolution during return stroke (RS) stages in triggered lightning. A three‐dimensional (3‐D) channel reconstruction is performed for speed measurement of the RS processes. The 3‐D average speeds for the two selected strokes (RS1 and RS3) over the bottom channel within 1 km are 9.24 × 107 m/s and 1.07 × 108 m/s, respectively. The high temporal‐spatial resolution of MARCOS permits thorough examination of the speed variation. Our observation shows that the 3‐D RS speeds of both RS1 and RS3 are increased initially with height for the first several hundred meters, maximized, and then decreased with height. To the best of our knowledge, this is the first evidence regarding nonmonotonic 3‐D RS speed variation in triggered lightning.
Discovery of Cyclotide-Like Protein Sequences in Graminaceous Crop Plants: Ancestral Precursors of Circular Proteins?[W]

Cyclotides are peptides from plants of the Rubiaceae and Violaceae families that have the unusual characteristic of a macrocylic backbone. They are further characterized by their incorporation of a cystine knot in which two disulfides, along with the intervening backbone residues, form a ring through which a third disulfide is threaded. The cyclotides have been found in every Violaceae species screened to date but are apparently present in only a few Rubiaceae species. The selective distribution reported so far raises questions about the evolution of the cyclotides within the plant kingdom. In this study, we use a combined bioinformatics and expression analysis approach to elucidate the evolution and distribution of the cyclotides in the plant kingdom and report the discovery of related sequences widespread in the Poaceae family, including crop plants such as rice (Oryza sativa), maize (Zea mays), and wheat (Triticum aestivum), which carry considerable economic and social importance. The presence of cyclotide-like sequences within these plants suggests that the cyclotides may be derived from an ancestral gene of great antiquity. Quantitative RT-PCR was used to show that two of the discovered cyclotide-like genes from rice and barley (Hordeum vulgare) have tissue-specific expression patterns.
The genus Acacia (Fabaceae) in East Africa: Distribution, diversity and the protected area network

Background and aims - Plants are often overlooked in conservation planning, yet they are the foundation of all terrestrial ecosystems. The East Africa region is used to investigate the effectiveness of protected areas for conserving plants. With a wide range of ecosystems and 771 protected areas covering nearly one quarter of the land area, East Africa is an ideal location to assess the effectiveness of protected areas through distribution modelling of the genus Acacia. Methods - Herbarium specimen data (2,047 records) were collated from East Africa for 65 taxa (species, subspecies, varieties) from the genus Acacia. Generalised Additive Models were used to determine climatic drivers, and thence to extrapolate climatic suitability across the region. For two Acacia taxa, we investigated the potential for climate-induced range-shifts using a downscaled regional climate model under two IPCC scenarios. Key results - Approximately two thirds of Acacia diversity hotspots had < 10% coverage by protected areas. Furthermore, the protected area network covered less of the predicted ranges of the Acacia taxa and contained fewer taxa per unit area than would be expected under randomised placement. Areas with suitable climate for high-elevation, moisture-dependent taxa such as A. abyssinica subsp. calophylla are predicted to contract their potential range by up to 80% towards mountain peaks, where protected areas are dominated by low-level protection forest reserves. Conversely, the area of suitable environment for a xerophytic low-elevation species (A. turnbulliana) is predicted to increase by up to 77%. Conclusions - East Africa's national parks may not be preserving an important component of ecosystem diversity, a situation exacerbated by climate change. Even within the genus Acacia, different species are predicted to respond differently to climate change. Priority areas for research and conservation are identified based on overlap between predicted high Acacia diversity and gaps in the collection record, with northern and eastern Kenya highlighted as particularly important. High elevation protected areas are also predicted to become increasingly important as climatic refugia in a warmer future. © 2012 National Botanic Garden of Belgium and Royal Botanical Society of Belgium.
Complex Network Analysis of a Tourism Content Sharing Network

This paper presents results of the analysis of a tourism information Web-site (AmFostAcolo.ro) by using Complex Networks (CN) methods. The work accomplished here complements a previous paper, where we discussed data extraction and modelling into a complex network. Properties of the resulted network, communities and vertices are looked upon, in order to extract useful information and detect social phenomena. Temporal analysis methods are employed for examining the evolution of the web-site. The results obtained prove the natural development of the Web-site and the usefulness of CN analysis methods in this scenario.
Stringy Derivation of Nahm Construction of Monopoles

We derive the Nahm construction of monopoles from exact tachyon condensation on unstable D-branes. The Dirac operator used in the Nahm construction is identified with the tachyon profile in our D-brane approach, and we provide physical interpretation of the procedures Nahm gave. Crucial is the introduction of infinite number of brane-antibranes from which arbitrary D-brane can be constrcuted, exhibitting a unified view of various D-branes. We explicitly show the equivalence of the D3-brane boundary state with the monopole profile and the D1-brane boundary state with the Nahm data as transverse scalars.
(Nearly) Sample-Optimal Sparse Fourier Transform

We consider the problem of computing a k-sparse approximation to the discrete Fourier transform of an n-dimensional signal. Our main result is a randomized algorithm that computes such an approximation using O(k log n(log log n)O(1)) signal samples in time O(k log2 n(log log n)O(1)), assuming that the entries of the signal are polynomially bounded. The sampling complexity improves over the recent bound of O(k log n log(n/k)) given in [15], and matches the lower bound of Ω(k log(n/k)/log log n) from the same paper up to poly(log log n) factors when k = O(n1-δ) for a constant δ > 0.
Manifold-Adaptive Dimension Estimation

Intuitively, learning should be easier when the data points lie on a low-dimensional submanifold of the input space. Recently there has been a growing interest in algorithms that aim to exploit such geometrical properties of the data. Oftentimes these algorithms require estimating the dimension of the manifold first. In this paper we propose an algorithm for dimension estimation and study its finite-sample behaviour. The algorithm estimates the dimension locally around the data points using nearest neighbor techniques and then combines these local estimates. We show that the rate of convergence of the resulting estimate is independent of the dimension of the input space and hence the algorithm is “manifold-adaptive”. Thus, when the manifold supporting the data is low dimensional, the algorithm can be exponentially more efficient than its counterparts that are not exploiting this property. Our computer experiments confirm the obtained theoretical results.
Tracking Motion Direction and Distance With Pyroelectric IR Sensors

Passive IR (PIR) sensors are excellent devices for wireless sensor networks (WSN), being low-cost, low-power, and presenting a small form factor. PIR sensors are widely used as a simple, but reliable, presence trigger for alarms, and automatic lighting systems. However, the output of a PIR sensor depends on several aspects beyond simple people presence, as, e.g., distance of the body from the sensor, direction of movement, and presence of multiple people. In this paper, we present a feature extraction and sensor fusion technique that exploits a set of wireless nodes equipped with PIR sensors to track people moving in a hallway. Our approach has reduced computational and memory requirements, thus it is well suited for digital systems with limited resources, such as those available in sensor nodes. Using the proposed techniques, we were able to achieve 100% correct detection of direction of movement and 83.49%-95.35% correct detection of distance intervals.
Consistent thinning of large geographical data for map visualization

Large-scale map visualization systems play an increasingly important role in presenting geographic datasets to end-users. Since these datasets can be extremely large, a map rendering system often needs to select a small fraction of the data to visualize them in a limited space. This article addresses the fundamental challenge of thinning: determining appropriate samples of data to be shown on specific geographical regions and zoom levels. Other than the sheer scale of the data, the thinning problem is challenging because of a number of other reasons: (1) data can consist of complex geographical shapes, (2) rendering of data needs to satisfy certain constraints, such as data being preserved across zoom levels and adjacent regions, and (3) after satisfying the constraints, an optimal solution needs to be chosen based on objectives such as maximality, fairness, and importance of data. This article formally defines and presents a complete solution to the thinning problem. First, we express the problem as an integer programming formulation that efficiently solves thinning for desired objectives. Second, we present more efficient solutions for maximality, based on DFS traversal of a spatial tree. Third, we consider the common special case of point datasets, and present an even more efficient randomized algorithm. Fourth, we show that contiguous regions are tractable for a general version of maximality for which arbitrary regions are intractable. Fifth, we examine the structure of our integer programming formulation and show that for point datasets, our program is integral. Finally, we have implemented all techniques from this article in Google Maps [Google 2005] visualizations of fusion tables [Gonzalez et al. 2010], and we describe a set of experiments that demonstrate the trade-offs among the algorithms.
Dengue Virus Type 1 Nonstructural Glycoprotein NS1 Is Secreted from Mammalian Cells as a Soluble Hexamer in a Glycosylation-Dependent Fashion

ABSTRACT Nonstructural glycoprotein NS1, specified by dengue virus type 1 (Den-1), is secreted from infected green monkey kidney (Vero) cells in a major soluble form characterized by biochemical and biophysical means as a unique hexameric species. This noncovalently bound oligomer is formed by three dimeric subunits and has a molecular mass of 310 kDa and a Stokes radius of 64.4 Å. During protein export, one of the two oligosaccharides of NS1 is processed into an endo-β-N-acetylglucosaminidase F-resistant complex-type sugar while the other remains of the polymannose type, protected in the dimeric subunit from the action of maturation enzymes. Complete processing of the complex-type sugar appears to be required for efficient release of soluble NS1 into the culture fluid of infected cells, as suggested by the repressive effects of the N-glycan processing inhibitors swainsonine and deoxymannojyrimicin. These results, together with observations related to the absence of secretion of NS1 from Den-infected insect cells, suggest that maturation and secretion of hexameric NS1 depend on the glycosylation status of the host cell.
A high‐resolution investigation of temperature, salinity, and upwelling activity proxies in corals

We present a high‐resolution study of five geochemical components of a New Caledonia coral core. Minor and trace elements (Sr/Ca, U/Ca, Mg/Ca, Ba/Ca), together with oxygen isotopes (δ18O), were investigated at near‐fortnightly resolution. Geochemical measurements were compared to sea surface temperature (SSTTSG) and salinity (SSSTSG) recorded by a thermosalinograph (TSG) located less than 10 m from the coral. Results show that Sr/Ca, Mg/Ca, and δ18O are temperature‐dependent (correlation coefficient to local SSTTSG between 0.74 and 0.84). Their robustness as SST tracers is tested against a satellite‐based data set for a 4 year validation period. U/Ca has a more complex behavior and appears to be linked to both SSTTSG and SSSTSG, despite relatively small local SSS variations. For the first time this salinity‐related imprint is quantified in a U/Ca coralline ratio. In addition to SST and SSS tracers, Ba/Ca measurements provide a possible way to investigate upwelling activity occurrences.
Determining bearing faults using wavelet and approximate entropy

Bearing faults appear to be one of the main factors that cause the interruption of automation processes. In this paper ldquoWavelet Analysisrdquo and ldquoApproximate Entropyrdquo was applied to vibration data taken from a shaft-bearing setup to predict the presence and development of bearing faults. The purpose is to distinguish the normal and the defective bearing sorted by the degree of defectiveness, using wavelet packet analysis and approximate entropy with high frequency demodulated raw vibration data. Normal bearing with low amplitude but numerous frequency components, and defective bearing with a characteristic of high amplitudes and certain frequency components can be distinguished by approximate entropy. Wavelet packet analysis can be applied to the derived data to get which frequency components are more essential for getting better results.
Optimized Data Pre-Processing for Discrimination Prevention

Non-discrimination is a recognized objective in algorithmic decision making. In this paper, we introduce a novel probabilistic formulation of data pre-processing for reducing discrimination. We propose a convex optimization for learning a data transformation with three goals: controlling discrimination, limiting distortion in individual data samples, and preserving utility. We characterize the impact of limited sample size in accomplishing this objective, and apply two instances of the proposed optimization to datasets, including one on real-world criminal recidivism. The results demonstrate that all three criteria can be simultaneously achieved and also reveal interesting patterns of bias in American society.
Score informed audio source separation using a parametric model of non-negative spectrogram

In this paper we present a new technique for monaural source separation in musical mixtures, which uses the knowledge of the musical score. This information is used to initialize an algorithm which computes a parametric decomposition of the spectrogram based on non-negative matrix factorization (NMF). This algorithm provides time-frequency masks which are used to separate the sources with Wiener filtering.