Miracle-dz/UniFAR-FTUs huggingface dataset:
1 Transparent Dynamic Optimization

Dynamic optimization refers to the runtime optimization of a native program binary. This paper describes the design and implementation of Dynamo, a prototype dynamic optimizer that is capable of optimizing a native program binary at runtime. Dynamo is a realistic implementation, not a simulation, that is written entirely in user-level software, and runs on a PA-RISC machine under the HPUX operating system. Dynamo does not depend on any special programming language, compiler, operating system or hardware support. The program binary is not instrumented and is left untouched during Dynamo’s operation. Dynamo observes the program’s behavior through interpretation to dynamically select hot instruction traces from the running program. The hot traces are optimized using low-overhead optimization techniques and emitted into a software code cache. Subsequent instances of these traces cause the cached version to be executed, resulting in a performance boost. Contrary to intuition, we demonstrate that it is possible to use a piece of software to improve the performance of a native, statically optimized program binary, while it is executing. Dynamo not only speeds up real application programs, its performance improvement is often quite significant. For example, the performance of many +O2 optimized SPECint95 binaries running under Dynamo is comparable to the performance of their +O4 optimized version running without Dynamo.
Mathematical Analysis of Stochastic Regularization Approach for Super-Resolution Reconstruction

Traditionally, several distorting processes affect the quality of image sequences or video acquired by commercial digital cameras. Some of the more important distorting effects include warping, blurring, down sampling and additive noise. The term SRR (Super-Resolution Reconstruction) ranges from blur removal by deconvolution in single image to the creation of a single high resolution image from multiple low resolution images having relative sub-pixel displacements. In all cases, the goal of SRR is to remove the effect of possible blurring and noise in the LR images and to obtain images with resolutions that go beyond the conventional limits of the uncompensated imaging system. Thus, the major advantage of this approach is that the cost of implementation is reduced and the existing low resolution (LR) imaging systems can still be utilized. Due to the importance of SRR research and the advantages of the SRR algorithm, this article aims to review the mathematical analysis of the SRR algorithm based on stochastic regularization approaches, one of the most popular techniques introduced by the SRR research community during the last two decades. The mathematical models of SRR algorithm based on classical L1 and L2 norms with several classical regularization functions are comprehensively derived. Finally, the mathematical solutions of each case are obtained by the classical systematical approach.
Proton magnetic resonance spectroscopy in patients with solitary and sporadic temporal lobe epileptic seizures

Proton magnetic resonance spectroscopy (1H MRS) is an optional diagnostic method for potential epilepsy surgery candidates. The aim of this study was to determine the credibility of 1H MRS examination in a group of patients suffering from solitary and sporadic epileptic seizures generated in temporal lobe. We recorded a 100% sensitivity of 1H MRS in a group of ten patients in terms of detection of a pathological process in the temporal lobe. 1H MRS also enabled determination of lateralization of the pathological process in three patients with bilateral epileptiform abnormalities on electroencephalography. Based on these results we suggest new perspectives on 1H MRS as a part of standard diagnostic algorithm for solitary and sporadic temporal lobe epileptic seizures, particularly in cases with normal electroencephalography and magnetic resonance imaging findings.
INFORMATIVE MPC FORMULATIONS FOR ORTHONORMAL LAGUERRE SERIES MIMO MODELS

An informative model predictive control (MPC) algorithm is presented. The formulation builds upon recent advances in the field that extend certainty equivalence formulations with semi-definite constraints. The proposed adaptive control algorithm and the previous methods are presented in the context of fixed state transition dynamics generated by a finite orthonormal Laguerre basis. The development of an implementable convex relaxation is presented along with an illustrative example.
Pair Diagram and Cyclic Properties Characterizing the Inverse of Reversible Automata '

Professor Harold V. McIntosh has realized deep and elegant contributions in the analysis and understanding of cellular automata. Inspired in his work about applying graph and algebraic tools in the study of reversible automata, this paper implements some of his ideas and results for characterizing the features of the inverse rule for a reversible one-dimensional cellular automata. In particular, we use the pair diagram for knowing the size of the inverse neighborhood and the position of its evolution and we take advantage of the cyclic behavior in finite configurations for obtaining the inverse local rule.
Non-stationary noise power spectral density estimation based on regional statistics

Estimating the noise power spectral density (PSD) is essential for single channel speech enhancement algorithms. In this paper, we propose a noise PSD estimation approach based on regional statistics. The proposed regional statistics consist of four features representing the statistics of the past and present periodograms in a short-time period. We show that these features are efficient in characterizing the statistical difference between noise PSD and noisy speech PSD. We therefore propose to use these features for estimating the speech presence probability (SPP). The noise PSD is recursively estimated by averaging past spectral power values with a time-varying smoothing parameter controlled by the SPP. The proposed method exhibits good tracking capability for non-stationary noise, even for abruptly increasing noise level.
Solving swath problems optimally

We present the first optimal algorithms for swath segment scheduling for orbiting spacecraft. We present a comparison between an integer program formulation and a branch and bound formulation that makes use of a flow network transformation, each capable of solving instances of these problems optimally. We also compare our techniques with the current state of the practice: the Aster scheduling algorithm. No technique strictly dominates all others, and we characterize their respective advantages and disadvantages. Note that this problem is NP-complete. The primary goal of our work is to solve the largest swath problems possible, both quickly, and where feasible, optimally
Study on the selection of thermal power enterprise’s coal suppliers based on wavelet neural network

BP neural network has the shortcomings of slow convergence and is prone to fall into local optimums flows. In this paper, structure and learning algorithm of wavelet neural network are briefly introduced, then a new method of wavelet neural network which can make full use of part characteristic of wavelet time frequent and combine the ability of self study of neural network is presented to form a model for selection of thermal power enterprisepsilas coal suppliers.
Internet and Computer Crime: System Architecture as Crime Control

New technologies provide new opportunities and new potentials. Technological developments, however, do not determine human fates; rather, they change the constraints within which people act. The global reach of the Internet, the low marginal cost of online activity, and the relative anonymity of users have changed the balance of forces that have previously served to keep in check certain undesirable behaviors in the physical world. These characteristics of cyberspace have lowered the cost of perpetrating undesirable behavior by eliminating certain barriers to entry, lowering transaction costs and reducing the probability of getting caught. In addition, these characteristics make traditional enforcement strategies, particularly identifying and apprehending perpetrators after they commit online crime, both less effective and more expensive. At the same time, however, other characteristics of cyberspace provide new opportunities to control illegal acts. Unlike in the physical world, in cyberspace certain readily identifiable third parties - Internet service providers (ISPs) - have exclusive technical control over the infrastructure through which most illegal online behavior is carried out. Thus, one strategy for controlling online behavior is to impose some responsibility on such third parties in order to control user misconduct before illegal acts are committed or to help identify and apprehend criminals after the fact. In other cases, the same logic can be applied to second parties - that is, victims of online crime who control the systems on which crime is committed - and legal responsibility to encourage optimal victim behavior can also be employed. The purpose of this paper is to briefly examine the rationale and opportunity for online crime control through system architecture by imposing certain technical responsibilities on victims and implicated third parties. In particular, we examine affirmative obligations for ISPs to report criminal activity and retain data, and for victims to employ some minimal level of technical protective measures. In addition, we briefly discuss tort-based mechanisms to encourage both victims and third parties to adopt reasonable technical measures to prevent illegal behavior.
Feature Fusion Based CartoonCharacter Retrieval Using Semi-Msl

Cartoon is popular and successful media in our life, its creation is usually of high cost and labor intensive. The computer assisted systems are designed to reduce the time cost of the cartoon production and to develop novel systems that can synthesize new cartoons by reusing existing cartoon materials. For that purpose, we propose a method for cartoon character retrieval with two applications, namely content based cartoon image retrieval and cartoon clip synthesis. In order to retrieve similar cartoon characters two issues are considered. The first issue is how to represent the cartoon characters. The color histogram, hausdorff edge feature, skeleton features and curvature scale space are used to represent the color, shape and gesture of the cartoon characters. The second issue is to combine these features using semi-supervised multi-view subspace learning algorithm. This algorithm uses patch alignment framework to construct and align local patches. Aligned patches have high dimension, it is not efficient to retrieve similar character. In order to improve the efficiency, alternating optimization is utilized for reducing high to low dimensional subspace. Within that space similar characters can be retrieved. This method is useful for animators and cartoon enthusiasts to effectively create new animations.
Large-Scale Analysis of B-Cell Epitopes on Influenza Virus Hemagglutinin – Implications for Cross-Reactivity of Neutralizing Antibodies

Influenza viruses continue to cause substantial morbidity and mortality worldwide. Fast gene mutation on surface proteins of influenza virus result in increasing resistance to current vaccines and available antiviral drugs. Broadly neutralizing antibodies (bnAbs) represent targets for prophylactic and therapeutic treatments of influenza. We performed a systematic bioinformatics study of cross-reactivity of neutralizing antibodies (nAbs) against influenza virus surface glycoprotein hemagglutinin (HA). This study utilized the available crystal structures of HA complexed with the antibodies for the analysis of tens of thousands of HA sequences. The detailed description of B-cell epitopes, measurement of epitope area similarity among different strains, and estimation of antibody neutralizing coverage provide insights into cross-reactivity status of existing nAbs against influenza virus. We have developed a method to assess the likely cross-reactivity potential of bnAbs for influenza strains, either newly emerged or existing. Our method catalogs influenza strains by a new concept named discontinuous peptide, and then provide assessment of cross-reactivity. Potentially cross-reactive strains are those that share 100% identity with experimentally verified neutralized strains. By cataloging influenza strains and their B-cell epitopes for known bnAbs, our method provides guidance for selection of representative strains for further experimental design. The knowledge of sequences, their B-cell epitopes, and differences between historical influenza strains, we enhance our preparedness and the ability to respond to the emerging pandemic threats.
Carrots That Look Like Sticks: Toward an Understanding of Multitasking Incentive Schemes

Constructing compensation schemes for effort in multi-dimensional tasks is complex, particularly when some dimensions are not easily observable. When incentive schemes contractually reward workers for easily observed measures, such as quantity produced, the standard model predicts that unrewarded dimensions, such as quality, will be neglected. Yet, there remains mixed empirical evidence in favor of this standard principal-agent model prediction. This paper reconciles the literature by using both theory and empirical evidence. The theory outlines conditions under which principals can use a piece rate scheme to induce higher quantity and quality levels than analogous fixed wage schemes. Making use of a series of complementary laboratory and field experiments we show that this effect occurs because the agent is uncertain about the principal's monitoring ability and the principal's choice of a piece rate signals to the agent that she is efficient at monitoring.
Peri- and Postnatal Developmental Toxicity of Salcaprozate Sodium (SNAC) in Sprague-Dawley Rats

Salcaprozate sodium (SNAC) (sodium 8-((2-hydroxybenzoyl) amino) octanoate, CAS RN 203787-91-1) is classified as an oral absorption promoter and may be a useful means for improving the absorption of certain nutrients and pharmaceutical agents. Presented herein is a subset of data from a larger study evaluating the potential effects of SNAC on the gestation, parturition, lactation, maternal behavior, and offspring development of rats. Pregnant Crl:CD BR VAF/Plus female rats (F0; n = 25) received SNAC at 1000 mg/kg/d orally (gavage) from implantation through lactation and weaning. F1 pups were exposed in utero and potentially through maternal milk; observations continued through sexual maturity. The study concluded with Caesarean sectioning of F1 dams for litter observations and fetal evaluations. No deaths, abortions, premature deliveries, or gross lesions occurred in (F0) dams. Excess salivation, red perivaginal substance, and slight reductions in body weights, body weight gains, and/or feed intake were noted in late gestation/early lactation. SNAC was associated with a prolonged gestation period, leading to a greater number of dams with stillborn pups, higher number of stillborn pups, and reduced live litter size. Offspring body weights/gains, feed consumption, age of sexual maturation, mating, fertility, behavioral parameters, and organ weights at necropsy were unaffected by SNAC. No gross external changes were observed in F1 or F2 pups. In summary, SNAC administered orally at 1000 mg/kg/d to pregnant rats from gestation to weaning resulted in a slight decrease in maternal body weights (−3.8%) and prolonged gestation, along with an increase in stillbirths, but had no effects on growth and development in surviving offspring.
Optimized Designs of p-Cycles for Survivable Multicast Sessions in Optical WDM Networks

Network service outage causes tremendous revenue loss and service disruption for both unicast and multicast traffic. In particular, multicast traffic suffers more in network failures than unicast traffic does, because a link in a multicast tree might carry traffic to multiple destinations. Hence, network survivability is crucial to provisioning of multicast sessions in optical WDM networks. The preconfigured protection cycle (p- cycle) method, originally proposed for unicast traffic protection [1] by W. D. Grover, combines the rings' simplicity, fast speed in switching, and the meshes' flexibility in routing, efficiency in resource utilization. Although p-cycles have been extensively studied for unicast traffic protection, they have been rarely applied to multicast traffic protection. We have recently proposed applying link p-cycle based approaches, namely Dynamic p-Cycle (DpC) design and link p-cycle based Protected Working Capacity Envelope (PWCE) design to dynamic provisioning of survivable multicast traffic [2]. In this paper, we analyze the existing multicast protection approaches and present Integer Linear Programming (ILP) methods for p-cycle based protection of static multicast sessions. We consider the approaches of p-cycle based ILP joint optimization (JOP) and Non-joint optimization (NJOP), and the approach of p-cycle based ILP optimization of spare capacity (SOP). These ILP optimization methods serve as the bench mark for p-cycle based heuristic algorithms [3]. We also compare the results with that of the Path Pair Protection approach in [4] . We show that the p- cycle based JOP offers the least total capacity consumption, compared with other optimization approaches.
On the Effective Spatial Separations in the Clustering of Faint Galaxies

Several recent measurements have been made of the angular correlation function w(θ, m) of faint galaxies in deep surveys (e.g., in the Hubble Deep Field, hereafter HDF). Are the measured correlations indicative of the gravitational growth of primordial perturbations, or of the relationship between galaxies and (dark matter-dominated) galaxy halos? A first step in answering this question is to determine the typical spatial separations of galaxies whose spatial correlations, ξ(r, z), contribute most of the angular correlation. The median spatial separation of galaxy pairs contributing to a fraction p of the angular correlation signal in a galaxy survey is denoted by r (§ 3) and compared with the perpendicular distance, r⊥, at the median redshift, zmed, of the galaxies. Over a wide range in spatial correlation growth rates, ϵ, and median redshifts, r is no more than about twice the value of r⊥, while r is typically 4 times r⊥. Values of r for redshift distributions representative of recent surveys indicate that many angular correlation measurements correspond to spatial correlations at comoving length scales well below 1 h-1 Mpc. For Ω0 = 1 and λ0 = 0, the correlation signal at 4'' predominant in the Villumsen et al. (1996) estimates of w(θ, m) for faint HDF galaxies corresponds to r(HDF) ≈ 40 h-1 kpc; other cosmologies and angles up to 10'' can increase this to r(HDF)≲200 h-1 kpc. The proper separations are (1 + z) times smaller, where 1 ≲ z ≲ 2. These scales are small: the faint galaxy angular correlation measurements are at scales where halo and/or galaxy existence, let alone interactions, may modify the spatial correlation function. These measurements could be used to probe the radial extent of halos at high redshift.
BATS: The Blind Audio Tactile Mapping System

The BATS project focuses on helping students with visual impairments access and explore spatial information using standard computer hardware and open source software. Our work is largely based on prior techniques used in presenting maps to the blind such as text-to-speech synthesis, auditory icons, and tactile feedback. We add spatial sound to position auditory icons and speech callouts in three dimensions, and use consumer-grade haptic feedback devices to provide additional map information through tactile vibrations and textures. Two prototypes have been developed for use in educational settings and have undergone minimal assessment. A system for public release and plans for more rigorous evaluation are in development.
Effects of Dexamphetamine and Music on Reversal Learning

Background: Reversal learning has proven to be a valuable task in assessing the inhibitory process that is central to executive control. Psycho-stimulants and music are prevalent factors that influence cognition. Objectives: The present study aimed at investigating the influences of dexamphetamine and music on inhibitory control. Materials and Methods: This experimental study was conducted between May and June 2014 in the laboratory animal center of Shiraz University of Medical Sciences, Shiraz, Iran. Thirty mice were divided to five groups including a control group, a witness group, and three experimental groups. Food availability was restricted in order to maintain the subjects at 85% of their free-feeding body weight for behavioral testing. After discrimination learning, animals received four injections of 2 mg/kg dexamphetamine at two-hour intervals. The music group was exposed to music half an hour before reversal learning. Results: According to the results of the repeated measure analysis of variance (ANOVA), music increased errors (mean difference: -2.40, 95% CI: -3.59 to -1.22), yet dexamphetamine had no significant effect on reversal learning. Due to various advantages, we transited to the mixed model that showed increasing (Beta: 2.2 95% CI: 0.26 to 4.13) and borderline (Beta: 1.8 95% CI: -0.13 to 3.73) effects on the number of errors for dexamphetamine and music group, respectively. Conclusions: Drug-treated subjects were impaired in their ability to modulate behavior, based upon changing information about stimulus-reward associations, possibly due to the inability to inhibit their response. These effects may have relevance to some mental disorders such as drug-abuse, schizophrenia, and obsessive-compulsive disorder.
The Division Inhibitor EzrA Contains a Seven-Residue Patch Required for Maintaining the Dynamic Nature of the Medial FtsZ Ring

ABSTRACT The essential cytoskeletal protein FtsZ assembles into a ring-like structure at the nascent division site and serves as a scaffold for the assembly of the prokaryotic division machinery. We previously characterized EzrA as an inhibitor of FtsZ assembly in Bacillus subtilis. EzrA interacts directly with FtsZ to prevent aberrant FtsZ assembly and cytokinesis at cell poles. EzrA also concentrates at the cytokinetic ring in an FtsZ-dependent manner, although its precise role at this position is not known. Here, we identified a conserved patch of amino acids in the EzrA C terminus that is essential for localization to the FtsZ ring. Mutations in this patch (designated the “QNR patch”) abolish EzrA localization to midcell but do not significantly affect EzrA's ability to inhibit FtsZ assembly at cell poles. ezrA QNR patch mutant cells exhibit stabilized FtsZ assembly at midcell and are significantly longer than wild-type cells, despite lacking extra FtsZ rings. These results indicate that EzrA has two distinct activities in vivo: (i) preventing aberrant FtsZ ring formation at cell poles through inhibition of de novo FtsZ assembly and (ii) maintaining proper FtsZ assembly dynamics within the medial FtsZ ring, thereby rendering it sensitive to the factors responsible for coordinating cell growth and cell division.
Classification of Privacy Management Techniques in Pervasive Computing

Context awareness, the ability to adapt to the needs of each user, is a fundamental property of pervasive computing systems. Context information is created by tracking the actions and collecting real-time user data, such as location or body temperature. As the system collects more information about its users, the quality of its context-aware services increases, and so does a potential threat to the users’ privacy if the context information is compromised. This paper surveys a wide range of existing pervasive computing systems that address this complex problem, and provides a generalized classification of privacy management techniques used by these systems. A comparative analysis of the surveyed systems and their privacy features is also presented.