Miracle-dz/UniFAR-FTUs huggingface dataset:
A Preliminary Workload Analysis of SPECjvm2008

SPECjvm2008 is a new benchmark program suite for measuring client-side Java runtime environment. It replaces JVM98, which has been used for the same purpose for more than ten years. It consists of 38 benchmark programs grouped into eleven categories and has wide variety of workloads from computation-intensive kernels to XML file processors. In this paper, we present the results of running SPEC\-jvm2008 on three machines that have CPUs with the same microarchitecture and different cache sizes and clock speeds. The result of measurements include instruction and data cache reference and miss rates, and the effect of the multi-threading. We relate these workload parameters to the SPECjvm2008 performance metrics. Roughly speaking, an L2 cache of 1MB sufficiently lows the cache miss rates of SPECjvm2008 and compared to the single-core, 1.5 to 2 times speed-ups are achieved by dual-core executions.
Discovery of Semantic Relationships in PolSAR Images Using Latent Dirichlet Allocation

We propose a multilevel semantics discovery approach for bridging the semantic gap when mining high-resolution polarimetric synthetic aperture radar (PolSAR) remote sensing images. First, an Entropy/Anisotropy/Alpha-Wishart classifier is employed to discover low-level semantics as classes representing the physical scattering properties of targets (e.g., low-entropy/surface scattering/high anisotropy). Then, the images are tiled into patches and each patch is modeled as a bag-of-words, a histogram of the class labels. Next, latent Dirichlet allocation is applied to discover their higher level semantics as a set of topics. Our results demonstrate that topic semantics are close to human semantics used for basic land-cover types (e.g., grassland). Therefore, using the topic description (bag-of-topics) of PolSAR images leads to a narrower semantic gap in image mining. In addition, a visual exploration of the topic descriptions helps to find semantic relationships, which can be used for defining new semantic categories (e.g., mixed land-cover types) and designing rule-based categorization schemes.
Unsubscription: A Simple Way to Ease Overload in Email

The constant growth of machine-generated mail, which today consists of more than 90% of non-spam mail traffic, is a major contributor toinformation overload in email, where users become overwhelmed with a flood of messages from commercial entities. A large part of this traffic is often junk mail that the user would prefer not to receive. Surprisingly, nearly 95% of this traffic is in fact solicited by the users themselves in the form of subscriptions to mailing services. These subscriptions are many times unintentional. Although unsubscription option from such services is enforced by commercial laws, it is hardly actually used by users. We perform a large scale study ofunsubscribable traffic, namely, messages that provide unsubscription option to users. We consider users behavior over such traffic in Yahoo Web mail service, and demonstrate a significant gap between users low interest in this traffic, and their lack of active behavior in decreasing its load. We conjecture that the cause of this gap is the lack of an efficient and easily accessible mechanism that would help users to unsubscribe. We validate our conjecture with an online large scale experiment, where we provide users with a novel mail feature for managing unsubscribable traffic, based on personalized recommendations. The experiment demonstrates the imminent need that exists for such a mechanism.
Development and Characterization of a Highly Specific and Sensitive SYBR Green Reverse Transcriptase PCR Assay for Detection of the 2009 Pandemic H1N1 Influenza Virus on the Basis of Sequence Signatures

ABSTRACT The emergence and rapid spread of the 2009 H1N1 pandemic influenza virus showed that many diagnostic tests were unsuitable for detecting the novel virus isolates. In most countries the probe-based TaqMan assay developed by the U.S. Centers for Disease Control and Prevention was used for diagnostic purposes. The substantial sequence data that became available during the course of the pandemic created the opportunity to utilize bioinformatics tools to evaluate the unique sequence properties of this virus for the development of diagnostic tests. We used a comprehensive computational approach to examine conserved 2009 H1N1 sequence signatures that are at least 20 nucleotides long and contain at least two mismatches compared to any other known H1N1 genome. We found that the hemagglutinin (HA) and neuraminidase (NA) genes contained sequence signatures that are highly conserved among 2009 H1N1 isolates. Based on the NA gene signatures, we used Visual-OMP to design primers with optimal hybridization affinity and we used ThermoBLAST to minimize amplification artifacts. This procedure resulted in a highly sensitive and discriminatory 2009 H1N1 detection assay. Importantly, we found that the primer set can be used reliably in both a conventional TaqMan and a SYBR green reverse transcriptase (RT)-PCR assay with no loss of specificity or sensitivity. We validated the diagnostic accuracy of the NA SYBR green assay with 125 clinical specimens obtained between May and August 2009 in Chile, and we showed diagnostic efficacy comparable to the CDC assay. Our approach highlights the use of systematic computational approaches to develop robust diagnostic tests during a viral pandemic.
Sport, rhetoric, and gender : historical perspectives and media representations

PART I: SPORT LANGUAGE PER SE Sportswomanship: The Cultural Acceptance of Sport for Women Versus the Accommodation of Cultured Women in Sport L.M. Mawson Language, Gender, and Sport: A Review of the Research Literature J.O Segrave, K.L.McDowell & J.G. King 'Throw Like a Girl' Doesn't Mean What It Used To: Research on Gender, Language, and Power F.L. Wachs PART II: HISTORICAL PERSPECTIVES "A Glow of Pleasurable Excitement": Images of the New Athletic Woman in American Popular Culture, 1880-1920 N.G. Rosoff A Woman in a Man's World: Annie Laurie, One of America's First Sportswriters M.Sowell White Sauvage-ry: Revisiting the Collegians and Coeds of Old Siwash College J.Stang PART III: PRINT MEDIA REPRESENTATIONS She Got Game, but She Don't Got Fame S.Burris Strong Enough to Be a Man, But Made a Woman: Discourses of Femininity in Sports Illustrated for Women C.Cooky Running a Different Race? The Rhetoric of 'Women's-Only' Content in Runner's World M.Hardin & J.Dodd Control: Em-powerment and the Fitness Discourse J.S. Maguire Minimizing the Maxim Model? : Interpreting the Sexual Body Rhetoric of Teenage Moms through Physical Education T.Orchard, J.Stark & J.Halas PART IV: BROADCAST MEDIA REPRESENTATIONS Television and Aerobic Sport: Empowerment and Patriarchy in Denise Austin's Daily Workouts M.Camacho We Don't Glow, We Sweat: The Ever Changing Commentary about Women's Athletics J.R. Hallmark PART V: VISUAL MEDIA REPRESENTATIONS Game Face: Sports Reporters: Use of Sexualized Language in Coverage of Women's Professional Tennis K.L. Bissell The Vamp, the Homebody, and the Upstart: Women, Language, and Baseball Films L.K. Fuller Britney, the Body, and the Blurring of Popular Cultures: A Case Study of Music Videos, Gender, a Transcendent Celebrity, and Health Issues C.Sabiston & B.Wilson PART VI: CLASSIC CASE STUDIES NASCAR's Boy Wonder: Jeff Gordon as Ambivalent Sex Symbol in a Macho Sub-Culture S.A. G.M. Crawford Hey, I'm the Coach's Wife, not the Team Mom': The Rhetoric of Little League Mothers' Role Performances K.Golombisky "Man-On": The Culture of Girls' Soccer S.C. Mooney The Making of the Perfect Sacrifice: An Analysis of Football Coaches' Rhetorical Descriptions of Their Wives D.L. Tucker GirlSpeak: Adolescent Females Talk About Their Athletic Identities S.G. Zieff
Collaborative signaling by mixed chemoreceptor teams in Escherichia coli

Chemoreceptors of the methyl-accepting chemotaxis protein family form clusters, typically at the cell pole(s), in both Bacteria and Archaea. To elucidate the architecture and signaling role of receptor clusters, we investigated interactions between the serine (Tsr) and aspartate (Tar) chemoreceptors in Escherichia coli by constructing Tsr mutations at the six hydrophobic and five polar residues implicated in “trimer of dimers” formation. Tsr mutants with proline replacements could not mediate serine chemotaxis, receptor clustering, or clockwise flagellar rotation. Alanine and tryptophan mutants, although also nonchemotactic, formed receptor clusters, and some produced clockwise flagellar rotation, indicating receptor-coupled activation of the signaling CheA kinase. The alanine and tryptophan mutants evidently assemble defective receptor complexes that cannot modulate CheA activity in response to serine stimuli. In cells containing wild-type Tar receptors, tryptophan replacements in Tsr interfered with Tar function, whereas four Tsr mutants with alanine replacements regained Tsr function. These epistatic and rescuable phenotypes imply interactions between Tsr and Tar dimers in higher-order signaling teams. The bulky side chain in tryptophan mutants may prevent stimulus-induced conformational changes in the team, whereas the small side chain in alanine mutants may permit signaling control when teamed with functional receptor molecules. Direct physical interactions between Tsr and Tar molecules were observed by in vivo chemical crosslinking. Wild-type Tsr crosslinked to Tar, whereas a clustering-defective proline replacement mutant did not. These findings indicate that bacterial chemoreceptor clusters are comprised of signaling teams, seemingly based on trimers of dimers, that can contain different receptor types acting collaboratively.
Multi-robot pose graph localization and data association from unknown initial relative poses via expectation maximization

This paper presents a novel approach for multirobot pose graph localization and data association without requiring prior knowledge about the initial relative poses of the robots. Without a common reference frame, the robots can only share observations of interesting parts of the environment, and trying to match between observations from different robots will result in many outlier correspondences. Our approach is based on the following key observation: while each multi-robot correspondence can be used in conjunction with the local robot estimated trajectories, to calculate the transformation between the robot reference frames, only the inlier correspondences will be similar to each other. Using this concept, we develop an expectation-maximization (EM) approach to efficiently infer the robot initial relative poses and solve the multi-robot data association problem. Once this transformation between the robot reference frames is estimated with sufficient measure of confidence, we show that a similar EM formulation can be used to solve also the full multi-robot pose graph problem with unknown multi-robot data association. We evaluate the performance of the developed approach both in a statistical synthetic-environment study and in a real-data experiment, demonstrating its robustness to high percentage of outliers.
The Role of the PFC in Semantic Memory Tasks

The PFC plays an important role in memory tasks in organizing free recall. However, very little is known about the exact mechanisms underlying PFC function. Many researchers, like Morris Moscovitch (1994) believe the PFC supplies cues to other memory areas but details concerning this hypothetical function are vague. Anderson (2003), in contrast, believes that the PFC directly suppresses semantic memory traces. These potential functions of the PFC were explored in the following work. A model of non-strategic memory was built using a TCM framework, and a number of different implementations were evaluated. The model was then applied to Anderson's RIF work, to determine whether an item inhibition account of memory was necessary to explain RIF results. Finally, the model was applied to semantic memory strategies in free recall results to guide empirical research. It was found that no direct inhibition was necessary to explain RIF, and that, in a timed and categorized free recall task, the PFC best performs a semantic strategy by generating category labels at recall. Implications of this work were then discussed.
Moderators of Youth Exercise Intention and Behavior

This study tested moderators of the theory of planned behavior (TPB) based on geographical region, gender, race, and income among adolescents in an exercise context using multigroup path analyses. Participants were eighth- and ninth-grade students from Louisiana (LA; N = 448, Mage = 14.37 years) and Pennsylvania (PA; N = 681, Mage = 14.28 years). They completed measures of intention, attitude, subjective norm, perceived behavioral control, and exercise behavior. Based on two path analyses, geographical region was a significant moderator (p < .001); therefore, the moderating effects of gender, race, and income were analyzed separately for each state. Gender was a significant moderator for LA (p < .001) but not for PA (p = .90). Race and income did not moderate the TPB relationships within each state. Findings support the moderating effect of geographical region on the TPB construct relationships and indicate that gender moderates the TPB construct relationships in LA youth.
A Motivational Journey : A study about the entrepreneur and the changes in motivation from start-up to present

The purpose of this thesis is to identify what motivational changes occur while a lifestyle entrepreneur moves through three different organizational stages. The focus will however be on stage one and three. The problem of an under-researched field is addressed and how the motivation of specific lifestyle entrepreneurs, in these cases hairdressing salon owners, has changed. This thesis has been conducted with an interpretivistic viewpoint, an inductive approach and with a qualitative research method. The authors have selected to analyze the data through pattern matching and dividing the interviewees into two different case studies, one for each of the two chosen organizational stages in focus. In conclusion the authors found that intrinsic and extrinsic motivations have had different effects within all stages in the organizational life cycle. The authors have discovered that during stage one the intrinsic motivations play a large role. During stage one where the organization is small and young the lifestyle entrepreneurs are motivated by factors such as independence and self-efficacy. Stage two is a more extrinsic dominated phase with the factors integrated regulations and identified regulation as motivators. The third stage is a return to the intrinsic motivations with factors such as locus of control and egoistic passion. This is further explained within the chapter with help of the analysis and empirical findings. A figure has been presented to show the different phases and their motivational change.
The logarithmic number system for strength reduction in adaptive filtering

An important technique for reducing power consumption in VLSI systems is strength reduction, the substitution of a less-costly operation such as a shift, for a more-costly operation such a multiplication. Using a logarithmic number representation provides several opportunities for strength reductions; in particular, multiplication is performed as the fixed-point addition of logarithms, and extracting a square root is implemented via a shift. These reductions occur transparently at the hardware level; consequently relatively little algorithmic modification is required, and they are readily applicable to adaptive filtering. For performing Givens rotations in the QR decomposition recursive least squares adaptive filter, logarithmic arithmetic is shown to compare favorably to other strength reduction techniques, such as CORDIC arithmetic, in terms of switched capacitance and numerical accuracy.
Neural Networks for Fingerprint Recognition

After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images originate from the same finger. In one experiment, the neural network is trained using a few hundred pairs of images and its performance is subsequently tested using several thousand pairs of images originated from a subset of the database corresponding to 20 individuals. The error rate currently achieved is less than 0.5%. Additional results, extensions, and possible applications are also briefly discussed.
Trypanosoma cruzi in the rectum of the bug Triatoma infestans: effects of blood ingestion by the starved vector.

To follow the developmental effects of feeding of the insect host after long starvation periods, the population density and composition of an established infection of Trypanosoma cruzi in the rectum of Triatoma infestans were determined 60 days after the last feeding (daf) and then at different intervals after feeding. The original population decreased and then increased up to the 10th daf. In starved bugs, about 30% were spheromastigotes (including intermediate forms), 20% epimastigotes, and 50% trypomastigotes, but one daf, these forms represented 2%, 70%, and 10%, respectively. In addition, one daf there were about 10% giant cells, i.e., a multiple division stage. In the following two days, this form represented on average 30-50% of the total population, but it then disappeared nearly completely. Thus, giant cells evidently develop by rapid growth of epimastigotes, if conditions become optimal after long starvation periods of the vector.
Spectral unmixing using nonnegative matrix factorization with smoothed L0 norm constraint

Spectral unmixing (SU) is a hot topic in remote sensing image interpretation, where the linear mixing model (LMM) is discussed widely for its validity and simplicity [1]. SU often includes two facts as follows: 1) endmembers extraction; 2) abundances estimation. Mathematically, in the SU model, the collections, the endmember signatures, and the abundances are nonnegative [1]. Therefore, nonnegative matrix factorization (NMF) has a great potential to solve SU, especially for LMM [2]. In fact, NMF (or NMF like) algorithms have been widely discussed in SU, such as NMF based on minimum volume constraint (NMF-MVC) [1], NMF based on minimum distance constraint (NMF-MDC) [3], and so on. These methods have advantages and disadvantages, respectively. In light of that the abundances are often sparse and sparse NMF tends to result more determinate factors, NMF with sparseness constraint has attracted more and more attentions [4-6]. To solve SU using sparse NMF practically, one problem should be addressed firstly, that is how to select the functions to measure the sparseness feature. Since the abundance suffers from sum-to-one constraint physically, the widely used measure based on L1 norm constraint may be degenerate [7, 8]. As the smoothed L0 norm of the signals can reflect the sparseness intuitively and it is easy to be optimized, we focus on NMF with smoothed L0 norm constraint (NMF-SL0) in this work [9]. The rest of this paper is organized as follows. In Section II, typical SU and NMF models are presented. Section III describes the L0-based sparse NMF for solving SU, together with the gradient based optimization algorithm NMF-SL0. Simulations using synthetic mixtures and real hyperspectral images are presented in Section IV. Finally, conclusions are summarized in Section V.
Characterization of presenilin-amyloid precursor interaction using bacterial expression and two-hybrid systems for human membrane proteins

An Escherichia coli system was used to produce the human membrane proteins presenilin 1 and amyloid precursor protein and to analyse their interaction. Our data indicate that the main binding site for amyloid precursor protein is located in the N-terminal three-transmembrane segments of presenilin and not in the proposed active site containing the two conserved aspartate residues. The data also suggest the presence of an additional segment of sufficient hydrophobicity at the C-terminus of PS1 to act potentially as a transmembrane segment. The implications of these findings for the function of γ-secretase are discussed.
EBP1 and DRBP76/NF90 binding proteins are included in the major histocompatibility complex class II RNA operon

Major histocompatibility complex class II mRNAs encode heterodimeric proteins involved in the presentation of exogenous antigens during an immune response. Their 3′UTRs bind a protein complex in which we identified two factors: EBP1, an ErbB3 receptor-binding protein and DRBP76, a double-stranded RNA binding nuclear protein, also known as nuclear factor 90 (NF90). Both are well-characterized regulatory factors of several mRNA molecules processing. Using either EBP1 or DRBP76/NF90-specific knockdown experiments, we established that the two proteins play a role in regulating the expression of HLA-DRA, HLA-DRB1 and HLA-DQA1 mRNAs levels. Our study represents the first indication of the existence of a functional unit that includes different transcripts involved in the adaptive immune response. We propose that the concept of ‘RNA operon’ may be suitable for our system in which MHCII mRNAs are modulated via interaction of their 3′UTR with same proteins.
Split-door criterion for causal identification: Automatic search for natural experiments

Unobserved or unknown confounders complicate even the simplest attempts to estimate the effect of one variable on another using observational data. When cause and effect are both affected by unobserved confounders, methods based on identifying natural experiments have been proposed to eliminate confounds. However, their validity is hard to verify because they depend on assumptions about the independence of variables, that by definition, cannot be measured. In this paper we investigate a particular scenario in time series data that permits causal identification in the presence of unobserved confounders and present an algorithm to automatically find such scenarios. Specifically, we examine what we call the split-door setting, when the effect variable can be split up into two parts: one that is potentially affected by the cause, and another that is independent of it. We show that when both of these variables are caused by the same (unobserved) confounders, the problem of identification reduces to that of testing for independence among observed variables. We discuss various situations in which split-door variables are commonly recorded in both online and offline settings, and demonstrate the method by estimating the causal impact of Amazon's recommender system, obtaining more than 23,000 natural experiments that provide similar---but more precise---estimates than past studies.