Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient alias set analysis using SSA form

Precise, flow-sensitive analyses of pointer relationships often represent each object using the set of local variables that point to it (the alias set), possibly augmented with additional predicates. Many such analyses are difficult to scale due to the size of the abstraction and due to flow sensitivity. The focus of this paper is on efficient representation and manipulation of the alias set. Taking advantage of certain properties of static single assignment (SSA) form, we propose an efficient data structure that allows much of the representations of sets at different points in the program to be shared. The transfer function for each statement, instead of creating an updated set, makes only local changes to the existing data structure representing the set. The key enabling properties of SSA form are that every point at which a variable is live is dominated by its definition, and that the definitions of any set of simultaneously live variables are totally ordered according to the dominance relation. We represent the variables pointing to an object using a list ordered consistently with the dominance relation. Thus, when a variable is newly defined to point to the object, it need only be added to the head of the list. A back edge at which some variables cease to be live requires only dropping variables from the head of the list. We prove that the analysis using the proposed data structure computes the same result as a set-based analysis. We empirically show that the proposed data structure is more efficient in both time and memory requirements than set implementations using hash tables and balanced trees.
Helping Poor Readers Demonstrate Their Science Competence

Solving test items might require abilities in test-takers other than the construct the test was designed to assess. Item and student characteristics such as item format or reading comprehension can impact the test result. This experiment is based on cognitive theories of text and picture comprehension. It examines whether integration aids, which relate pictorial representations to the corresponding textual representations in item stimuli, affect performance in a science test. The results show that items containing referential connections between both representations and highlighting associated information are easier to solve than non-integrated items (i.e., items without aids). However, this is only true for information-complementary representations, not for information-equivalent representations. Furthermore, an effect of reading comprehension on students’ test performance observed when complementary information was presented in a non-integrated format was absent in the integrated format condition.
Genetic interaction between Caenorhabditis elegans teneurin ten-1 and prolyl 4-hydroxylase phy-1 and their function in collagen IV–mediated basement membrane integrity during late elongation of the embryo

A whole-genome RNAi screen identified phy-1 as a novel interaction partner of the Caenorhabditis elegans gene ten-1. It is shown that the catalytic subunit of prolyl 4-hydroxylase, which is coded for by phy-1, is important for type IV collagen secretion and that the transmembrane protein TEN-1 links the epidermis to muscle cells through the basement membrane.
Super-symmetric decomposition of the fourth-order cumulant tensor. Blind identification of more sources than sensors

Ideas for higher-order array processing are introduced, focusing on fourth-order cumulant statistics. They are expressed in an index-free formalism allowing the exploitation of all their symmetry properties. It is shown that, when dealing with 4-index quantities, symmetries are related to rank properties. The rich symmetry structure yields a class of identification algorithms. An algebraic technique for blind identification is included, and a few others are briefly indicated. <<ETX>>
Late Cretaceous ocean: Coupled simulations with the National Center for Atmospheric Research Climate System Model

[1] Deep-ocean circulation may be a significant factor in determining climate. Here, we describe two long, fully coupled atmosphere-ocean simulations with the National Center for Atmospheric Research Climate System Model for the Late Cretaceous (80 Ma). Our results suggest that higher levels of atmospheric CO2 and the altered paleogeography of the Late Cretaceous resulted in a surface ocean state, temperature, salinity, and circulation, significantly different than at present. This, in turn, resulted in deepwater features that, although formed by mechanisms similar to the present, were quite different from the present. The simulations exhibit large overturning cells in both hemispheres extending from the surface to the ocean bottom and with intensity comparable to the present-day North Atlantic simulated overturning. In the Northern Hemisphere the sinking takes place in the Pacific due to cooling of the much warmer and saltier waters compared to the present day. In the Southern Hemisphere the sinking occurs primarily in the southern Atlantic and Indian Oceans. For a simulation with atmospheric CO2reduced from 6 times to 4 times preindustrial concentrations, the southern branch is reduced by 35%percnt; due to less poleward transport of salty waters in the South Atlantic Ocean. Warm waters inferred from proxy data in deep-sea cores can be explained by the high-latitude sites of overturning. These results contradict the traditional hypothesis that warm Cretaceous ocean bottom waters must have formed by sinking in shallow low-latitude seas.
Detecting Plagiarism Based on the Creation Process

All methodologies for detecting plagiarism to date have focused on the final digital “outcome”, such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction logs with the software used to create the work. Detection relies on comparing the histograms of multiple logs’ command use. A work is classified as plagiarism if its log deviates too much from logs of “honestly created” works or if its log is too similar to another log. The technique supports the detection of plagiarism for digital outcomes that stem from unique tasks, such as theses and equal tasks such as assignments for which the same problem sets are solved by multiple students. Focusing on the latter case, we evaluate this approach using logs collected by an interactive development environment (IDE) from more than 60 students who completed three programming assignments.
The role of emotional intelligence on coach-athlete relationships and motivational climate

The Role of Emotional Intelligence on Coach-Athlete Relationships and Motivational Climate Eric Steege Research has revealed that Emotional Intelligence is linked to improved conflict resolution, enhanced social attachments and mental health, and the ability to create a collective set of goals that motivate others (Pau & Croucher, 2003). The recent surge of research assessing the role EI may play in leadership effectiveness, motivation, and social attachments within nonsport domains overlaps with similar research within sport that assesses the influence of emotion on coaching effectiveness (Frijda & Mesquita, 1994; Mageau & Vallerand, 2003). Thus, the purpose of this investigation was to examine if higher EI coached athletes (N=34) varied compared to lower EI coached athletes(N=46) in their strength of the coach-athlete relationship, perceived motivational climate, college soccer satisfaction, and coaches’ ability to motivate. Results of the investigation indicate that lower EI coached athletes reported stronger coachathlete relationships compared to higher EI coached athletes but no significant difference between the groups were reported on perceived motivational climate, college soccer satisfaction, and coaches’ ability to motivate. The practical implications of these results are discussed, while relevant EI research within non-sport domains and a purposed line of coaching research using EI theory are explored.
Efficient waveform inversion and imaging: A strategy for selecting temporal frequencies

Prestack migration and/or inversion may be implemented in either the time or the frequency domain. In the frequency domain, it is possible to discretize the frequencies with a much larger sampling interval than that dictated by the sampling theorem and still obtain an imaging result that does not suffer from aliasing (wrap around) in the depth domain. The selection of input frequencies can be reduced when a range of offsets is available; this creates a redundancy of information in the wavenumber coverage of the target. In order to optimize the use of this information, we define a new discretization strategy that depends on the maximum effective offset present in the surface seismic survey: the larger the range of offsets, the fewer frequencies are required. The strategy, exact in a homogeneous 1D earth, selects frequencies by making use of the well-known effect of image stretch in normal-moveout (NMO) correction and in migration (usually considered detrimental for the imaging). The strategy is also useful in more general earth models: we apply it to the 2D Marmousi model and recover a continuous range of wavenumbers using only three input frequencies. The Marmousi inversion result accurately predicts all other data frequencies, demonstrating the redundancy of the data.
Design methodologies for securing cyber-physical systems

Cyber-Physical Systems (CPS) are in most cases safety- and mission-critical. Standard design techniques used for securing embedded systems are not suitable for CPS due to the restricted computation and communication budget available in the latter. In addition, the sensitivity of sensed data and the presence of actuation components further increase the security requirements of CPS. To address these issues, it is necessary to provide new design methods in which security is considered from the beginning of the whole design flow and addressed in a holistic way. In this paper, we focus on the design of secure CPS as part of the complete CPS design process, and provide insights into new requirements on platform-aware design of control components, design methodologies and architectures posed by CPS design. We start by discussing methods for the multi-disciplinary modeling, simulation, tools, and software synthesis challenges for CPS. We also present a framework for design of secure control systems for CPS, while taking into account properties of the underlying computation and communication platforms. Finally, we describe the security challenges in the computing hardware that is used in CPS.
Polymorph Impact on the Bioavailability and Stability of Poorly Soluble Drugs

Drugs with low water solubility are predisposed to poor and variable oral bioavailability and, therefore, to variability in clinical response, that might be overcome through an appropriate formulation of the drug. Polymorphs (anhydrous and solvate/hydrate forms) may resolve these bioavailability problems, but they can be a challenge to ensure physicochemical stability for the entire shelf life of the drug product. Since clinical failures of polymorph drugs have not been uncommon, and some of them have been entirely unexpected, the Food and Drug Administration (FDA) and the International Conference on Harmonization (ICH) has required preliminary and exhaustive screening studies to identify and characterize all the polymorph crystal forms for each drug. In the past, the polymorphism of many drugs was detected fortuitously or through manual time consuming methods; today, drug crystal engineering, in particular, combinatorial chemistry and high-throughput screening, makes it possible to easily and exhaustively identify stable polymorphic and/or hydrate/dehydrate forms of poorly soluble drugs, in order to overcome bioavailability related problems or clinical failures. This review describes the concepts involved, provides examples of drugs characterized by poor solubility for which polymorphism has proven important, outlines the state-of-the-art technologies and discusses the pertinent regulations.
Beauty Pays: Why Attractive People Are More Successful

Most of us know there is a payoff to looking good, and in the quest for beauty we spend countless hours and billions of dollars on personal grooming, cosmetics, and plastic surgery. But how much better off are the better looking? Based on the evidence, quite a lot. The first book to seriously measure the advantages of beauty, Beauty Pays demonstrates how society favors the beautiful and how better-looking people experience startling but undeniable benefits in all aspects of life. Noted economist Daniel Hamermesh shows that the attractive are more likely to be employed, work more productively and profitably, receive more substantial pay, obtain loan approvals, negotiate loans with better terms, and have more handsome and highly educated spouses. Hamermesh explains why this happens and what it means for the beautiful--and the not-so-beautiful--among us. Exploring whether a universal standard of beauty exists, Hamermesh illustrates how attractive workers make more money, how these amounts differ by gender, and how looks are valued differently based on profession. He considers whether extra pay for good-looking people represents discrimination, and, if so, who is discriminating. Hamermesh investigates the commodification of beauty in dating and how this influences the search for intelligent or high-earning mates, and even examines whether government programs should aid the ugly. He also discusses whether the economic benefits of beauty will persist into the foreseeable future and what the "looks-challenged" can do to overcome their disadvantage. Reflecting on a sensitive issue that touches everyone, Beauty Pays proves that beauty's rewards are anything but superficial.
Cryptanalysis of an authentication scheme for multi-gateway wireless sensor networks

Wireless sensor network has wide potential application in many fields such as military, agricultural and healthcare. However, it also has some vulnerabilities because of its openness. For this reason, many researchers have proposed various user authentication schemes for added security of wireless sensor networks. Recently, Wu et al. proposed an authentication scheme for multi-gateway wireless sensor networks in Internet of Things deployment. Wu et al. claimed that their scheme is secure against user forgery attack and session key leakage. However, we found that the scheme is vulnerable to outsider and user impersonation attacks. In this paper, we revisit Wu et al.'s scheme and analyze its vulnerabilities.
Filter-Free Optically Switchable and Tunable Ultrawideband Monocycle Generation Based on Wavelength Conversion and Fiber Dispersion

In this letter, a novel filter-free scheme for all-optical ultrawideband monocycle generation based on wavelength conversion in semiconductor optical amplifier and group-velocity dispersion in single-mode fiber is proposed and experimentally demonstrated. The system is optically switchable in pulse polarity, and tunable in both pulsewidth and radio-frequency spectrum.
Unified Multi-Cue Depth Estimation from Light-Field Images: Correspondence, Defocus, Shading, and Specularity

Light-field cameras have recently become available to the consumer market. An array of micro-lenses captures enough information that one can refocus images after acquisition, as well as shift one's viewpoint within the sub-apertures of the main lens, effectively obtaining multiple views. Thus, depth cues from defocus, correspondence, specularity, and shading are available simultaneously in a single capture. Previously, defocus could be achieved only through multiple image exposures focused at different depths; correspondence and specularity cues needed multiple exposures at different viewpoints or multiple cameras; and shading required very well controlled scenes and low-noise data. Moreover, all four cues could not easily be obtained together.In this thesis, we will present a novel framework that decodes the light-field images from a consumer Lytro camera and uses the decoded image to compute dense depth estimation by obtaining the four depth cues: defocus, correspondence, specularity, and shading. By using both defocus and correspondence cues, depth estimation is more robust with consumer-grade noisy data than previous works. Shading cues from light-field data enable us to better regularize depth and estimate shape. By using specularity, we formulate a new depth measure that is robust against specularity, making our depth measure suitable for glossy scenes. By combining the cues into a high quality depth map, the results are suitable for a variety of complex computer vision applications.
A zinc finger protein, essential for chromosome segregation, constitutes a putative DNA binding subunit of the Saccharomyces cerevisiae kinetochore complex, Cbf3.

A multisubunit protein complex, Cbf3, is a component of the Saccharomyces cerevisiae kinetochore. Cbf3 was recently shown to be essential for chromosome segregation in vivo and for movement of centromere DNA (CEN) along microtubules in vitro. Cbf3 contains three proteins, Cbf3a, Cbf3b and Cbf3c. Here the characterization of Cbf3b is described. Cbf3b contains an N‐terminal Zn2Cys6 type zinc finger domain, a C‐terminal acidic domain and a putative coiled coil dimerization domain. Cbf3b is essential for growth. Mutations within the zinc finger domain result in cells that exhibit a G2‐M cell cycle delay and increased chromosome loss in each mitotic cell division. Therefore, Cbf3b has an essential function in chromosome segregation and the zinc finger domain executes part of this function presumably by providing the specific interaction between Cbf3 and CEN. Finally, data are provided to show that Cbf3c is encoded by CTF13, a gene that had been cloned recently by complementing a temperature sensitive mutant that exhibits chromosome loss as a result of a defective centromere.
Extension and verification of the asymmetric autoregressive conditional duration models

ABSTRACT We extend the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot [Asymmetric ACD models: Introducing price information in ACD models, Empir. Econ. 28 (2003), pp. 709–731] which allows describing the joint dynamics of financial durations, i.e. times between selected micro-events (trades, price, or volume changes) and the corresponding event categories. The generalized beta distribution of the second kind (GB2) is proposed as the distribution for the error terms in the model. The GB2 distribution allows for flexible non-monotonic shapes of baseline hazard functions, which facilitates a plethora of temporal dependence patterns for event arrival times. We propose the procedures for checking the adequacy of the parametric specification with the help of simulation methods that allow computing the model residuals. Moreover, we show how to assess the goodness of fit of the AACD model using probability integral transforms. The model is used to investigate striking regularities in the manner currency dealers execute their market orders in the interbank foreign exchange spot market.
ksrMKL: a novel method for identification of kinase–substrate relationships using multiple kernel learning

Phosphorylation exerts a crucial role in multiple biological cellular processes which is catalyzed by protein kinases and closely related to many diseases. Identification of kinase–substrate relationships is important for understanding phosphorylation and provides a fundamental basis for further disease-related research and drug design. In this study, we develop a novel computational method to identify kinase–substrate relationships based on multiple kernel learning. The comparative analysis is based on a 10-fold cross-validation process and the dataset collected from the Phospho.ELM database. The results show that ksrMKL is greatly improved in various measures when compared with the single kernel support vector machine. Furthermore, with an independent test dataset extracted from the PhosphoSitePlus database, we compare ksrMKL with two existing kinase–substrate relationship prediction tools, namely iGPS and PKIS. The experimental results show that ksrMKL has better prediction performance than these existing tools.
Post-operative endophthalmitis: Antibiogram & genetic relatedness between Pseudomonas aeruginosa isolates from patients & phacoemulsifiers.

BACKGROUND & OBJECTIVES Though not frequently but there are reports showing phacoemulsifiers as a potent source of infection in post-operative cases of endophthalmitis. This study was carried out to find antibiogram and genetic relatedness between Pseudomonas aeruginosa isolates from a post-cataract surgery endophthalmitis outbreak (3 patients) and internal tubings of 5 phacoemulsifiers. METHODS In vitro antimicrobial sensitivity patterns of the 8 bacterial isolates were observed. Genetic analysis of the bacterial isolates was done using random amplification of polymorphic DNA (RAPD) assay and PCR ribotyping. The resulting DNA band patterns were examined visually and by computer assisted analysis using unweighted pair group method. RESULTS The three P. aeruginosa patient isolates were found to be different from the five phacoemulsifier isolates in sensitivity towards 3 antibiotics and by genetic analysis (33 and 44% homology by RAPD assay and PCR ribotyping). Two of the patient isolates shared 100 per cent genetic homology by RAPD assay and another pair shared 100 per cent homology by PCR ribotyping. The five isolates from phacoemulsifiers did not share significant genetic homology. There was significant genetic variation between bacterial isolates from patients and phaco emulsifiers. INTERPRETATION & CONCLUSION Though the three P. aeruginosa isolates obtained from the patients were phenotypically similar and genetically close, they differed from the phaco-machine isolates both genetically, and in their antibiogram profile. However, the five phacoemulsifier isolates were genetically diverse though they shared the same antibiogram profile. Therefore the Ringer's lactate from phacomachines could not be conclusively proven to be the source of infection.
Using delay tolerant network for the Internet of Things: Opportunities and challenges

Delay Tolerant Network (DTN) is a class of network architectures that address the lack of continuous network connectivity. This issue has been studied for over a decade by promoting new routing protocols. However, recent researches in DTN should rekindle proposed solutions to support new emerging network-based applications, in which DTN techniques can be used to offer delay tolerant support. Example of these applications domains is Internet of Things (IoT). We survey the use of DTN solutions in IoT applications to overcome connectivity problems considering the opportunities and challenges for each technology. The purpose of this work is to introduce most recent solutions that enable delay tolerant IoT. We propose a taxonomy and discuss advantages and limitations for each study.
PSO tuned Adaptive Neuro-fuzzy Controller for Vehicle Suspension Systems

In this paper, Particle Swarm Optimization (PSO) technique is applied to tune the Adaptive Neuro Fuzzy Controller (ANFIS) for vehicle suspension system. LQR controller is used to obtain the training data set for the vehicle suspension system. Subtractive clustering technique is used to formulate ANFIS which approximates the actuator output force as a function of system states. PSO algorithm search for optimal radii for subtractive clustering based ANFIS. Training is done off line and the cost function is based on the minimization of the error between actual and approximated output. Simulation results show that the PSO-ANFIS based vehicle suspension system exhibits an improved ride comfort and good road holding ability.