Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating a Priori Knowledge in the Form of Detractors into Support Vector Classification

In this article, we extend the idea of a priori knowledge in the form of detractors presented recently for Support Vector Classification. We show that detractor points can belong to the new type of support vectors – training examples which lie above the margin. We present the new application for a priori knowledge in the form of detractors – improving generalization performance of Support Vector Classification while reducing complexity of a model by removing a bunch of support vectors. Indeed, the experiments show that the new type of a priori knowledge improves generalization performance of reduced models. The tests were performed on various classification data sets, and on stock price data from public domain repositories.
A complex prediction: three‐dimensional model of the yeast exosome

We present a model of the yeast exosome based on the bacterial degradosome component polynucleotide phosphorylase (PNPase). Electron microscopy shows the exosome to resemble PNPase but with key differences likely related to the position of RNA binding domains, and to the location of domains unique to the exosome. We use various techniques to reduce the many possible models of exosome subunits based on PNPase to just one. The model suggests numerous experiments to probe exosome function, particularly with respect to subunits making direct atomic contacts and conserved, possibly functional residues within the predicted central pore of the complex.
Feature Clustering for Accelerating Parallel Coordinate Descent

Large-scale L1-regularized loss minimization problems arise in high-dimensional applications such as compressed sensing and high-dimensional supervised learning, including classification and regression problems. High-performance algorithms and implementations are critical to efficiently solving these problems. Building upon previous work on coordinate descent algorithms for L1-regularized problems, we introduce a novel family of algorithms called block-greedy coordinate descent that includes, as special cases, several existing algorithms such as SCD, Greedy CD, Shotgun, and Thread-Greedy. We give a unified convergence analysis for the family of block-greedy algorithms. The analysis suggests that block-greedy coordinate descent can better exploit parallelism if features are clustered so that the maximum inner product between features in different blocks is small. Our theoretical convergence analysis is supported with experimental re- sults using data from diverse real-world applications. We hope that algorithmic approaches and convergence analysis we provide will not only advance the field, but will also encourage researchers to systematically explore the design space of algorithms for solving large-scale L1-regularization problems.
Survey on Age Invariant Facial Recognition

The research in age-related face recognition has gained a lot of prominence lately due to the challenging problems of human face aging processes and strong demand of robust face recognition system across ages. Such face recognition systems are crucial in practical applications that need the compensation of age, e.g. missing children identification or passport verification, where there is a significant age difference between probe and gallery images. This paper surveys the different models and the algorithms used for age invariant facial recognition that effectively matches faces of a person irrespective of their age. Here we consider two models, first is the generative model that utilizes global features based approaches and second is the discriminative model that uses local features based approaches and is considered better in performance compared to generative model.The discriminative approach addresses the face aging problem in a more direct way without relying on generative aging model. The discriminative model is used in many algorithms like, SIFT (Scale Invariant Feature Transform), PCA (Principle Component Analysis), MFDA (Multi Feature Discriminant Analysis) and others.
Conveying human-computer interaction concerns to software engineers through an interaction model

This paper addresses the challenge of efficiently representing and communicating decisions about human-computer interaction to collaborate with software engineers. It describes and illustrates in a case study how an interaction modeling language based on the semiotic engineering of human-computer interaction may be used to derive a skeleton of certain UML diagrams, namely: use case, class, and sequence diagrams. Our goal is to provide a clear representation of the interactive exchanges that may take place, in order to prevent human-computer interaction decisions to be lost or inadvertently overruled when designing the system architecture and internal functional behavior.
Empirical Centroid Fictitious Play: An Approach for Distributed Learning in Multi-Agent Games

The paper is concerned with distributed learning in large-scale games. The well-known fictitious play (FP) algorithm is addressed, which, despite theoretical convergence results, might be impractical to implement in large-scale settings due to intense computation and communication requirements. An adaptation of the FP algorithm, designated as the empirical centroid fictitious play (ECFP), is presented. In ECFP players respond to the centroid of all players' actions rather than track and respond to the individual actions of every player. Convergence of the ECFP algorithm in terms of average empirical frequency (a notion made precise in the paper) to a subset of the Nash equilibria is proven under the assumption that the game is a potential game with permutation invariant potential function. A more general formulation of ECFP is then given (which subsumes FP as a special case) and convergence results are given for the class of potential games. Furthermore, a distributed formulation of the ECFP algorithm is presented, in which, players endowed with a (possibly sparse) preassigned communication graph, engage in local, non-strategic information exchange to eventually agree on a common equilibrium. Convergence results are proven for the distributed ECFP algorithm.
Multipath Assisted Positioning with Band-Limited Signals in an Urban Environment

While location-awareness in cellular radio networks has arisen more and more interest in recent years, positioning using cellular radio signals might show very weak performance due to shadowing and multipath propagation, especially in urban and indoor scenarios. Beyond, the number of base stations within communication range is often too low for positioning. The standard methods for positioning try to mitigate the effect of multipath propagation on the line-of-sight path. Though, various recently published results show that multipath components arising from reflections and scattering can actually be exploited, and hence the number of base stations required for positioning can be decreased. However, these results are based on the assumption of a high system bandwidth, e.g. 100 MHz or more. This is much higher than the bandwidth of cellular signals currently deployed. By performing measurements where we emulate a multipath scenario, we show that the tracking of a receiver is possible using a 3GPP-LTE system of a bandwidth of only 20 MHz in a simple urban scenario. We apply an advanced signal processing algorithm to track multipath components impinging at a moving receiver, and feed those results into a particle filter for position estimation. Our results indicate that tracking the receiver is possible with only two base stations, even if one of them is not in line-of-sight. The positioning error is always below 7 meters.
On the lifetime of wireless sensor networks

Network lifetime has become the key characteristic for evaluating sensor networks in an application-specific way. Especially the availability of nodes, the sensor coverage, and the connectivity have been included in discussions on network lifetime. Even quality of service measures can be reduced to lifetime considerations. A great number of algorithms and methods were proposed to increase the lifetime of a sensor network—while their evaluations were always based on a particular definition of network lifetime. Motivated by the great differences in existing definitions of sensor network lifetime that are used in relevant publications, we reviewed the state of the art in lifetime definitions, their differences, advantages, and limitations. This survey was the starting point for our work towards a generic definition of sensor network lifetime for use in analytic evaluations as well as in simulation models—focusing on a formal and concise definition of accumulated network lifetime and total network lifetime. Our definition incorporates the components of existing lifetime definitions, and introduces some additional measures. One new concept is the ability to express the service disruption tolerance of a network. Another new concept is the notion of time-integration: in many cases, it is sufficient if a requirement is fulfilled over a certain period of time, instead of at every point in time. In addition, we combine coverage and connectivity to form a single requirement called connected coverage. We show that connected coverage is different from requiring noncombined coverage and connectivity. Finally, our definition also supports the concept of graceful degradation by providing means of estimating the degree of compliance with the application requirements. We demonstrate the applicability of our definition based on the surveyed lifetime definitions as well as using some example scenarios to explain the various aspects influencing sensor network lifetime.
Lossy Compression of Scanned Map Images

An algorithm for lossy compression of scanned map images is proposed. The algorithm is based on color quantization, efficient statistical context tree modeling and arithmetic coding. The ratedistortion performance is evaluated on a set of scanned maps and compared to JPEG2000 lossy compression algorithm, and to ECW, which is a commercially available solution for compression of satellite and aerial images. The proposed algorithm outperforms these competitors in rate-distortion sense for the most part of the operational rate-distortion curve.
Draft Genome Sequence of Synechococcus sp. Strain CB0101, Isolated From the Chesapeake Bay Estuary

ABSTRACT Here, we report the draft genome sequence of the estuarine Synechococcus sp. strain CB0101. The genomics information of this strain will facilitate the study of the poorly understood Synechococcus subcluster 5.2 and how this strain is capable of thriving in a dynamic estuarine system, such as the Chesapeake Bay.
as a Novel Tumor Suppressor in Lung Cancer β Factor 3 Binding Protein Targets Identifies Hepatocyte Nuclear A Transcriptional Profiling Study of CCAAT / Enhancer

We showed previously that CCAAT/enhancer binding protein (C/ EBP ), a tissue-specific transcription factor, is a candidate tumor suppressor in lung cancer. In the present study, we have performed a transcriptional profiling study of C/EBP target genes using an inducible cell line system. This study led to the identification of hepatocyte nuclear factor 3 (HNF3 ), a transcription factor known to play a role in airway differentiation, as a downstream target of C/EBP . We found downregulation of HNF3 expression in a large proportion of lung cancer cell lines examined and identified two novel mutants of HNF3 , as well as hypermethylation of the HNF3 promoter. We also developed a tetracycline-inducible cell line model to study the cellular consequences of HNF3 expression. Conditional expression of HNF3 led to significant growth reduction, proliferation arrest, apoptosis, and loss of clonogenic ability, suggesting additionally that HNF3 is a novel tumor suppressor in lung cancer. This is the first study to show genetic abnormalities of lung-specific differentiation pathways in the development of lung cancer.
Examination of reproductive aging milestones among women who carry the FMR1 premutation.

BACKGROUND The fragile X premutation is characterized by a large CGG repeat track (55-199 repeats) in the 5' UTR of the FMR1 gene. This X-linked mutation leads to an increased risk for premature ovarian failure; interestingly, the association of repeat size with risk is non-linear. We hypothesize that the premutation-associated ovarian insufficiency is due to a diminished oocyte pool and examined reproductive aging milestones by repeat size group to determine if the same non-linear association is observed. METHODS We analyzed cross-sectional reproductive history questionnaire data from 948 women with a wide range of repeat sizes. RESULTS We have confirmed the non-linear relationship among premutation carriers for ovarian insufficiency. The mid-range repeat size group (80-100 repeats), not the highest group, had an increased risk for: altered cycle traits (shortened cycle length, irregular cycles and skipped cycles), subfertility and dizygotic twinning. Smoking, a modifiable risk, decreased the reproductive lifespan of women with the premutation by about 1 year, similar to its effect on non-carriers. As expected, premutation carriers were found to be at an increased risk for osteoporosis. CONCLUSIONS Possible molecular mechanisms to explain the non-linear repeat size risk for ovarian insufficiency are discussed.
A 1-V 25-dB 100-MHz CMOS variable gain amplifier cell

This paper proposes a novel low-voltage, low-power wide-bandwidth variable gain amplifier (VGA) cell. The proposed circuit combines source degeneration and current-mode techniques to achieve high linearity and constant bandwidth. Using a 0.35-/spl mu/m CMOS process and dissipating 84 /spl mu/W from a 1-V supply voltage, the proposed VGA cell can have a voltage gain varying from 0 dB to 25-dB DC gain while maintaining a constant bandwidth of 100-MHz.
Manual Khalifa Therapy Improves Functional and Morphological Outcome of Patients with Anterior Cruciate Ligament Rupture in the Knee: A Randomized Controlled Trial

Rupture of the anterior cruciate ligament (ACL) is a high incidence injury usually treated surgically. According to common knowledge, it does not heal spontaneously, although some claim the opposite. Regeneration therapy by Khalifa was developed for injuries of the musculoskeletal system by using specific pressure to the skin. This randomized, controlled, observer-blinded, multicentre study was performed to validate this assumption. Thirty patients with complete ACL rupture, magnetic resonance imaging (MRI) verified, were included. Study examinations (e.g., international knee documentation committee (IKDC) score) were performed at inclusion (t 0). Patients were randomized to receive either standardised physiotherapy (ST) or additionally 1 hour of Khalifa therapy at the first session (STK). Twenty-four hours later, study examinations were performed again (t 1). Three months later control MRI and follow-up examinations were performed (t 2). Initial status was comparable between both groups. There was a highly significant difference of mean IKDC score results at t 1 and t 2. After 3 months, 47% of the STK patients, but no ST patient, demonstrated an end-to-end homogeneous ACL in MRI. Clinical and physical examinations were significantly different in t 1 and t 2. ACL healing can be improved with manual therapy. Physical activity can be performed without pain and nearly normal range of motion after one treatment of specific pressure.
Atomic parity violation: Principles, recent results, present motivations

We review the progress made in the determination of the weak charge, QW, of the cesium nucleus which raises the status of Atomic Parity Violation measurements to that of a precision electroweak test. Not only is it necessary to have a precision measurement of the electroweak asymmetry in the highly forbidden 6S–7S transition, but one also needs a precise calibration procedure. The 1999 precision measurement by the Boulder group implied a 2.5 σ deviation of QW from the theoretical prediction. This triggered many particle physicist suggestions as well as examination by atomic theoretical physicists of several sources of corrections. After about three years, the disagreement was removed without appealing to "New Physics". Concurrently, an original experimental approach was developed in our group for more than a decade. It is based on detection by stimulated emission with amplification of the left–right asymmetry. We present our decisive, recent progress together with our latest results. We emphasize the important impact for electroweak theory, of future measurements in cesium possibly pushed to the 0.1% level. Other possible approaches are currently explored in several atoms.
Preliminary study on the digital analysis of occlusion based on the balance of occlusal force model

This paper presents a digital method to quantitatively analyze occlusion and equilibrium by using the balance of occlusal force (BOOF) model. The occlusal relationship is recovered by the registration between computed tomography digital models and dental cast digital models. Based on the BOOF model established according to occlusal contact information and mechanical equilibrium constraints, the center position of force and the distribution of the occlusal force are studied, measured, and compared with the T-Scan system. The proposed method can be applied to occlusal analysis of clinical models and extended to orthodontics, prosthodontics and implantodontics to provide a mechanical basis and reference for designing prostheses, dental implants, and surgical guides. A case research is used to explain the entire process of digital analysis of occlusion. The results proved the accuracy and feasibility of this method.
Developmental Outcomes of Children of Homeless Substance-Abusing Mothers

Abstract This study evaluated the impact ofan extended shelter-based child development/family therapy intervention, called Building Blocks, on the development of children of substance- abusing homeless mothers. The homeless children had greater than expected percentages ofdevelopmental deficits in a number of the developmental domains. Those children who participated in the extended child development/family therapy services were one fourth as likely to have a developmental deficit at 12 months compared to children who did not receive these services. Interventions must be intensive and long-term to improve the developmental outcomes of children with multiple risks ofpoverty, homelessness, and family substance abuse.
Resveratrol as a Therapeutic Agent for Alzheimer's Disease

Alzheimer's disease (AD) is the most common cause of dementia, but there is no effective therapy till now. The pathogenic mechanisms of AD are considerably complex, including Aβ accumulation, tau protein phosphorylation, oxidative stress, and inflammation. Exactly, resveratrol, a polyphenol in red wine and many plants, is indicated to show the neuroprotective effect on mechanisms mostly above. Recent years, there are numerous researches about resveratrol acting on AD in many models, both in vitro and in vivo. However, the effects of resveratrol are limited by its pool bioavailability; therefore researchers have been trying a variety of methods to improve the efficiency. This review summarizes the recent studies in cell cultures and animal models, mainly discusses the molecular mechanisms of the neuroprotective effects of resveratrol, and thus investigates the therapeutic potential in AD.
Document Clustering in Reduced Dimension Vector Space

Document clustering is a popular tool for automatically organizing a large collection of texts. Clustering algorithms are usually applied to documents represented as vectors in a high dimensional term space. We investigate the use of Latent Semantic Analysis to create a new vector space, that is the optimal representation of the document collection. Documents are projected onto a small subspace of this vector space and clustered. We compare the performance of clustering algorithms when applied to documents represented in the full term space and in reduced dimension subspace of the LSA-generated vector space. We report significant improvements in cluster quality for LSA subspaces with optimal dimensionality. We discuss the procedure for determining the right number of dimensions for the subspace. Moreover, when this number is small, the total running time of the clustering algorithm is comparable to the one that uses the full term space.
Spoofing: social commentary or effective marketing tool? Testing promotion vs. prevention message frames in college students’ fight against obesity

Abstract Spoofs parody regular advertisements in an attempt to discourage consumers from using or buying certain products. Using regulatory focus theory, the overarching question in this paper was whether spoofs (promotion vs. prevention) act as anti-consumption messages to fight obesity among college students. In Study 1, a repeated measures design was employed where participants were shown the regular ad followed by either spoof, while in Study 2, a between-subjects design was used and participants were exposed to either one of the three ads. Findings from both studies confirmed that spoofing potentially impacts brands, specifically, purchase intentions. Effectiveness of either spoof varies with respect to the presentation order of the ads and levels of anti-commercial consumer rebellion. Theoretical and managerial implications are discussed.
Depression Increases Sympathetic Activity and Exacerbates Myocardial Remodeling after Myocardial Infarction: Evidence from an Animal Experiment

Depression is an independent risk factor for cardiovascular events and mortality in patients with myocardial infarction (MI). Excessive sympathetic activation and serious myocardial remodeling may contribute to this association. The aim of this study was to discuss the effect of depression on sympathetic activity and myocardial remodeling after MI. Wild-type (WT) rats were divided into a sham group (Sham), a myocardial infarction group (MI), a depression group (D), and a myocardial infarction plus depression group (MI+D). Compared with controls, the MI+D animals displayed depression-like behaviors and attenuated body weight gain. The evaluation of sympathetic activity showed an increased level in plasma concentrations of epinephrine and norepinephrine and higher expression of myocardial tyrosine hydroxylase in the MI+D group than the control groups (p<0.05 for all). Cardiac function and morphologic analyses revealed a decreased fractional shortening accompanied by increased left ventricular dimensions, thinning myocardium wall, and reduced collagen repair in the MI+D group compared with the MI group (p<0.05 for all). Frequent premature ventricular contractions, prolonged QT duration and ventricular repolarization duration, shorted effective refractory period, and increased susceptibility to ventricular arrhythmia were displayed in MI+D rats. These results indicate that sympathetic hyperactivation and exacerbated myocardial remodeling may be a plausible mechanism linking depression to an adverse prognosis after MI.
Completeness of MLL proof-nets w.r.t. weak distributivity

Abstract We examine ‘weak-distributivity’ as a rewriting rule defined on multiplicative proofstructures (so, in particular, on multiplicative proof-nets: MLL). This rewriting does not preserve the type of proof-nets, but does nevertheless preserve their correctness. The specific contribution of this paper, is to give a direct proof of completeness for : starting from a set of simple generators (proof-nets which are a n-ary ⊗ of Ց-ized axioms), any mono-conclusion MLL proof-net can be reached by rewriting (up to ⊗ and Ց associativity and commutativity).