Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Sparse Representation Classification Face Recognition Based on Deep Learning

The existing face recognition under pose and illumination variations is a challenging problem. A novel sparse recognition face recognition algorithm based on deep learning is presented in this paper. The deep learning network extracted global and local information, the deep learning network adopted the supervised Convolution restricted Boltzmann machine. The features extracted could recover the face image and reduce intraidentity variances, while maintaining discriminativeness between identities. The algorithm obtained the feature by the deep network and realized fast sparse classification by smoothed l0 norm. Experimental results on FERET face database show that the proposed algorithm can improve recognition rate and recognition speed when dealing with various conditions such as pose variation.
Fuzzy clustering algorithms for symbolic interval data based on adaptive and non-adaptive Euclidean distances

The recording of symbolic interval data has become a common practice with the recent advances in database technologies. This paper presents fuzzy c-means clustering algorithms for symbolic interval data. The proposed methods furnish a partition of the input data and a corresponding prototype (a vector of intervals) for each class by optimizing an adequacy criterion which is based on adaptive and non-adaptive Euclidean distance between vectors of intervals. Experiments with real and synthetic symbolic interval data sets showed the usefulness of the proposed method.
Recognition of OOV proper names in diachronic audio news

LVCSR based audio indexing approaches are preferred as they allow search, navigation, browsing and structuring of audio/video documents based on their content. A major challenge with LVCSR based indexing of diachronic audio data, for e.g. broadcast audio news, is OOV words and specifically OOV PNs which are very important for indexing applications. In this paper we propose an approach for recognition of OOV PNs in audio news documents using PNs extracted from collections of diachronic text news from the internet. The approach has two steps (a) reduce the long list of OOV PNs in the diachronic text corpus to a smaller list of OOV PNs which are relevant to the audio document, using probabilistic topic models (b) perform a phonetic search for the target OOV PNs with the reduced list of relevant OOV PNs. We evaluate our approach on French broadcast news videos published over a period of 6 months. Latent Dirichlet Allocation topic model is trained on diachronic text news to model PN-topic relationships and then to retrieve OOV PNs relevant to the audio document. Our proposed method retrieves up to 90% of the relevant OOV PNs by reducing the OOV PN search space to only 5% of the total OOV PNs. Phonetic search for target OOV PNs gives an F1-score up to 0.392.
Requirements on collider data to match the precision of WMAP on supersymmetric dark matter.

If future colliders discover supersymmetric particles and probe their properties, one could predict the dark matter density of the Universe and would constrain cosmology with the help of precision data provided by WMAP and PLANCK. We investigate how well the relic density can be predicted in minimal supergravity (mSUGRA), with and without the assumption of mSUGRA when analysing data. We determine the parameters to which the relic density is most sensitive, and quantify the collider accuracy needed. Theoretical errors in the prediction are investigated in some detail.
Cocaine vaccine for the treatment of cocaine dependence in methadone-maintained patients: a randomized, double-blind, placebo-controlled efficacy trial.

CONTEXT Cocaine dependence, which affects 2.5 million Americans annually, has no US Food and Drug Administration-approved pharmacotherapy. OBJECTIVES To evaluate the immunogenicity, safety, and efficacy of a novel cocaine vaccine to treat cocaine dependence. DESIGN A 24-week, phase 2b, randomized, double-blind, placebo-controlled trial with efficacy assessed during weeks 8 to 20 and follow-up to week 24. SETTING Cocaine- and opioid-dependent persons recruited from October 2003 to April 2005 from greater New Haven, Connecticut. PARTICIPANTS One hundred fifteen methadone-maintained subjects (67% male, 87% white, aged 18-46 years) were randomized to vaccine or placebo, and 94 subjects (82%) completed the trial. Most smoked crack cocaine along with using marijuana (18%), alcohol (10%), and nonprescription opioids (44%). INTERVENTION Over 12 weeks, 109 of 115 subjects received 5 vaccinations of placebo or succinylnorcocaine linked to recombinant cholera toxin B-subunit protein. Main Outcome Measure Semiquantitative urinary cocaine metabolite levels measured thrice weekly with a positive cutoff of 300 ng/mL. RESULTS The 21 vaccinated subjects (38%) who attained serum IgG anticocaine antibody levels of 43 microg/mL or higher (ie, high IgG level) had significantly more cocaine-free urine samples than those with levels less than 43 microg/mL (ie, low IgG level) and the placebo-receiving subjects during weeks 9 to 16 (45% vs 35% cocaine-free urine samples, respectively). The proportion of subjects having a 50% reduction in cocaine use was significantly greater in the subjects with a high IgG level than in subjects with a low IgG level (53% of subjects vs 23% of subjects, respectively) (P = .048). The most common adverse effects were injection site induration and tenderness. There were no treatment-related serious adverse events, withdrawals, or deaths. CONCLUSIONS Attaining high (>or=43 microg/mL) IgG anticocaine antibody levels was associated with significantly reduced cocaine use, but only 38% of the vaccinated subjects attained these IgG levels and they had only 2 months of adequate cocaine blockade. Thus, we need improved vaccines and boosters. Trial Registration clinicaltrials.gov Identifier: NCT00142857.
Modeling Role-Based Privacy in Social Networking Services

As social networking services are getting more and more common, the need for privacy enhancing options, sophisticated identity management and anonymity emerges. In this paper the authors propose using Role-Based Privacy as a response for these needs and introduce a novel model called Nexus-Identity Network that is capable of describing services extended with such functionality. The concerned principles of Role-Based Privacy are conferred in the paper and criteria are presented for anonymity. Conforming to the criteria the authors suggest storing the profiles of different identities in a tree hierarchy in a user-friendly manner. The analysis of anonymity shows that the network has a structure that can be easily interpreted similarly to graphs representing connections in regular social networks. The ease of profile management and network visualization are advantages of the Nexus-Identity Model which can make a social networking service privacy- and user-friendly as well.
Current Views on Genetics and Epigenetics of Cholesterol Gallstone Disease

Cholesterol gallstone disease, one of the commonest digestive diseases in western countries, is induced by an imbalance in cholesterol metabolism, which involves intestinal absorption, hepatic biosynthesis, and biliary output of cholesterol, and its conversion to bile acids. Several components of the metabolic syndrome (e.g., obesity, type 2 diabetes, dyslipidemia, and hyperinsulinemia) are also well-known risk factors for gallstones, suggesting the existence of interplay between common pathophysiological pathways influenced by insulin resistance, genetic, epigenetic, and environmental factors. Cholesterol gallstones may be enhanced, at least in part, by the abnormal expression of a set of the genes that affect cholesterol homeostasis and lead to insulin resistance. Additionally, epigenetic mechanisms (mainly DNA methylation, histone acetylation/deacetylation, and noncoding microRNAs) may modify gene expression in the absence of an altered DNA sequence, in response to different lithogenic environmental stimuli, such as diet, lifestyle, pollutants, also occurring in utero before birth. In this review, we will comment on various steps of the pathogenesis of cholesterol gallstones and interaction between environmental and genetic factors. The epigenomic approach may offer new options for therapy of gallstones and better possibilities for primary prevention in subjects at risk.
Posttranscriptional Repression of GacS/GacA-Controlled Genes by the RNA-Binding Protein RsmE Acting Together with RsmA in the Biocontrol Strain Pseudomonas fluorescens CHA0

ABSTRACT In the plant-beneficial soil bacterium Pseudomonas fluorescens CHA0, the production of biocontrol factors (antifungal secondary metabolites and exoenzymes) is controlled at a posttranscriptional level by the GacS/GacA signal transduction pathway involving RNA-binding protein RsmA as a key regulatory element. This protein is assumed to bind to the ribosome-binding site of target mRNAs and to block their translation. RsmA-mediated repression is relieved at the end of exponential growth by two GacS/GacA-controlled regulatory RNAs RsmY and RsmZ, which bind and sequester the RsmA protein. A gene (rsmE) encoding a 64-amino-acid RsmA homolog was identified and characterized in strain CHA0. Overexpression of rsmE strongly reduced the expression of target genes (hcnA, for a hydrogen cyanide synthase subunit; aprA, for the main exoprotease; and phlA, for a component of 2,4-diacetylphloroglucinol biosynthesis). Single null mutations in either rsmA or rsmE resulted in a slight increase in the expression of hcnA, aprA, and phlA. By contrast, an rsmA rsmE double mutation led to strongly increased and advanced expression of these target genes and completely suppressed a gacS mutation. Both the RsmE and RsmA levels increased with increasing cell population densities in strain CHA0; however, the amount of RsmA showed less variability during growth. Expression of rsmE was controlled positively by GacA and negatively by RsmA and RsmE. Mobility shift assays demonstrated specific binding of RsmE to RsmY and RsmZ RNAs. The transcription and stability of both regulatory RNAs were strongly reduced in the rsmA rsmE double mutant. In conclusion, RsmA and RsmE together account for maximal repression in the GacS/GacA cascade of strain CHA0.
Optimising Acute Body Mass Management Practices in Australian Olympic Combat Sports

Unarmed Olympic combat sports include the striking sports of boxing and taekwondo and the grappling sports of judo and wrestling. All of these sports separate competitors into weight divisions, attempting to reduce physical differences and create ‘an even playing field’. It is common for these athletes (and those in other weight category sports) to undertake both chronic and rapid weight loss (RWL) prior to competition in an attempt to obtain a competitive edge over smaller opponents. Recognising this, reviews and guidelines have been established to assist with optimising chronic body mass (BM) management in combat sport athletes. However no consolidated guidelines for RWL exist, despite the vast majority of combat sport athletes engaging in these practices. Thus the overarching aim of this body of work was to complement existing chronic BM guidance by developing pragmatic guidelines and recommendations regarding acute BM manipulation to assist Australian Olympic combat sport athletes. ; Submitted in the fulfilment of the requirements of the degree of Doctor of Philosophy, University of the Sunshine Coast, 2017.
Can this video be promoted? - Endogenous and exogenous popularity processes in social media

We study what drives the popularity of cultural items, by computationally quantifying a video's potential to become viral. We propose to model popularity lifecycles as the endogenous response to exogenous stimuli, dubbed Hawkes intensity process. This model can explain the complex, multi-phase, longitudinal popularity of a Youtube video. Moreover, it can also forecast the future popularity, outperforming the state-of-the-art method. Finally, we characterize the susceptibility of a video to become popular through two parameters corresponding to the strength of its exogenous and endogenous response, respectively. The adequacy of the model for these tasks is validated on a dataset of the most Tweeted and shared videos over 6 months.
Remarks on continuum cardinals on Boolean algebras

We give some results concerning various generalized continuum cardinals. The results answer some natural questions which have arisen in preparing a new edition of 5 . To make the paper self‐contained we define all of the cardinal functions that enter into the theorems here. There are many problems concerning these new functions, and we formulate some of the more important ones.
Going Forward from B to A? Proposals for the Eurozone Crisis

After reviewing the main determinants of the current Eurozone crisis, this paper discusses the feasibility of introducing fiscal currencies as a way to restore fiscal space in peripheral countries, such as Greece, which have so far adopted austerity measures in order to abide by their commitments with Eurozone institutions and the IMF. We show that the introduction of fiscal currencies would speed up the recovery, without violating the rules of Eurozone Treaties. At the same time, these processes could help the transition of the euro from its current status of single currency to a status of “common clearing currency” along the lines proposed by Keynes at Bretton Woods as a system of international settlements. Eurozone countries could therefore move from “Plan B” aimed at addressing member state domestic problems, to a “Plan A” of a better European monetary system.
A Surface Reconstruction Approach with a Rotated Camera

The applications of 3D information acquisition and 3D solid surface reconstruction are increasing in the last years. This paper presents a solution of capturing 3D information from 2D image sequence, which captures 3D information with a rotated camera. Solutions for 3D information acquisition are briefly reviewed first, and current work on 3D information acquisition from 2D image sequence is described. We consider 3D points acquisition, and describe the result based on graph-cutted by horizontal tangents from several different viewpoints. The results are many compound and smooth curves, and multi-slices, which can be used to reconstruct the solid surface. The algorithm is suitable for protuberant solid reconstruction especially.
Nuclear reorganisation and chromatin decondensation are conserved, but distinct, mechanisms linked to Hox gene activation

The relocalisation of some genes to positions outside chromosome territories, and the visible decondensation or unfolding of interphase chromatin, are two striking facets of nuclear reorganisation linked to gene activation that have been assumed to be related to each other. Here, in a study of nuclear reorganisation around the Hoxd cluster, we suggest that this may not be the case. Despite its very different genomic environment from Hoxb, Hoxd also loops out from its chromosome territory, and unfolds, upon activation in differentiating embryonic stem (ES) cells and in the tailbud of the embryo. However, looping out and decondensation are not simply two different manifestations of the same underlying change in chromatin structure. We show that, in the limb bud of the embryonic day 9.5 embryo, where Hoxd is also activated, there is visible decondensation of chromatin but no detectable movement of the region out from the chromosome territory. During ES cell differentiation, decondensed alleles can also be found inside of chromosome territories, and loci that have looped out of the territories can appear to still be condensed. We conclude that evolutionarily conserved chromosome remodelling mechanisms, predating the duplication of mammalian Hox loci, underlie Hox regulation along the rostrocaudal embryonic axis. However, we suggest that separate modes of regulation can modify Hoxd chromatin in different ways in different developmental contexts.
Approximation Algorithms for a Balanced Capacity and Distance Constrained Vehicle Routing Problem

In the current paper we have investigated the capacitated distance constraint vehicle routing problem for the standard approximation algorithm. This problem consists of a number of different types of vehicles at the depot which differ at their capacity, cost and maximum distance bound. We have designed an approximation algorithm for this problem in the case that the tours are balanced.
DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics †

The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector’s dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability.
An exploratory study on the use of Twitter and Facebook in tandem

The diversity of available Social Network Sites (SNSs) enables people to use multiple services to fulfill their communication needs. Accordingly, this paper argues there is value in studying SNSs simultaneously -- that key insights regarding SNS use will be revealed when multiple services are examined together. To demonstrate this point, we present a study of 198 Facebook users with the goal of predicting the likelihood of each being a Twitter user based on their Facebook usage. Exploratory factor analysis on twelve activity metrics collected via the Facebook API led to the identification of five discrete usage dimensions. Of these five dimensions, only those that corresponded to functionality not available in Twitter significantly (and positively) predicted ownership of an account. This result suggests complementary use of the two SNSs based on feature differentiation.
A Fault Detection filter design method for a class of linear time-varying systems

In this paper we propose a Fault Detection (FD) filter design method for linear parameter varying (LPV) systems. The FD filter is an optimal Hinfin Luenberger observer synthesized by minimizing frequency conditions which ensure guaranteed levels of disturbance rejection and fault detection. Via the Bounded Real Lemma (BRL) and the Separation Principle the design method is formulated as a convex LMI optimization problem. The resulting residual generator is parameter-dependent and uses the plant parameter assumed measurable on-line. Finally, a FD threshold logic is proposed in order to reduce the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example.
The Brain Drain: Curse or Boon?

The migration of skilled individuals from developing countries has typically been considered to be costly for the sending country, due to lost investments in education, high fiscal costs and labour market distortions. Economic theory, however, raises the possibility of a beneficial brain drain primarily through improved incentives to acquire human capital. Our survey of empirical and theoretical work shows under what circumstances a developing country can benefit from skilled migration. It argues that the sectoral aspects of migration and screening of migrants in the receiving country are of major importance in determining the welfare implications of the brain drain. These issues, as well as the size of the sending country, duration of migration and the effect of diaspora populations, should be addressed in future empirical work on skilled migration. JEL
Synergizing Specification Miners through Model Fissions and Fusions (T)

Software systems are often developed and released without formal specifications. For those systems that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date. To deal with the absence of formal specifications, researchers have proposed techniques to infer the missing specifications of an implementation in a variety of forms, such as finite state automaton (FSA). Despite the progress in this area, the efficacy of the proposed specification miners needs to improve if these miners are to be adopted. We propose SpecForge, a new specification mining approach that synergizes many existing specification miners. SpecForge decomposes FSAs that are inferred by existing miners into simple constraints, through a process we refer to as model fission. It then filters the outlier constraints and fuses the constraints back together into a single FSA (i.e., model fusion). We have evaluated SpecForge on execution traces of 10 programs, which includes 5 programs from DaCapo benchmark, to infer behavioral models of 13 library classes. Our results show that SpecForge achieves an average precision, recall and F-measure of 90.57%, 54.58%, and 64.21% respectively. SpecForge outperforms the best performing baseline by 13.75% in terms of F-measure.
Activity classification using a state transition diagram and activity levels

Wireless health monitoring systems are suggested for use in the health care of the elderly to enable independent but secure living for as long as possible. Activity monitoring is highly valued by welfare and health personnel because it gives an overview of the well-being of the elderly. In this paper, a state transition diagram based activity classification MATLAB-algorithm is described. The state transition diagram takes consideration of the reasonable sequential states. The system distinguishes between different states and activity levels with the help of a single waist worn measurement unit consisting of a tri-axial accelerometer and a tri-axial gyroscope. The allowable states are stand, sit, lie, walk, and fall. Every second of data is classified into one of the previous states, but also into one of the four possible activity levels: passivity, light activity, activity, and intense activity. The performance of the state classification is tested with the data collected in a home environment. The sensitivity and specificity values for the state transitions are in the range of 80-100%. The classifier detects longer continuous periods in the same state with a minimum probability of 85.7%.