Miracle-dz/UniFAR-FTUs huggingface dataset:
Digging deeper into the Southern skies: a compact Milky Way companion discovered in first-year Dark Energy Survey data

We use the first-year Dark Energy Survey (DES) data down to previously unprobed photometric depths to search for stellar systems in the Galactic halo, therefore complementing the previous analysis of the same data carried out by our group earlier this year. Our search is based on a matched filter algorithm that produces stellar density maps consistent with stellar population models of various ages, metallicities, and distances over the survey area. The most conspicuous density peaks in these maps have been identified automatically and ranked according to their significance and recurrence for different input models. We report the discovery of one additional stellar system besides those previously found by several authors using the same first-year DES data. The object is compact, and consistent with being dominated by an old and metal-poor population. DES 1 is found at high significance and appears in the DES images as a compact concentration of faint blue point sources. Assuming different spatial profile parameterizations, the best-fitting heliocentric distance and total absolute magnitude in the range of 77.6-87.1 kpc and -3.00 less than or similar to M-V less than or similar to -2.21, respectively. The half-light radius of this object, r(h) similar to 10 pc and total luminosity are consistent with it being a low-mass halo cluster. It is also found to have a very elongated shape (epsilon similar to 0.57). In addition, our deeper probe of DES first-year data confirms the recently reported satellite galaxy candidate Horologium II as a significant stellar overdensity. We also infer its structural properties and compare them to those reported in the literature.
Use of Large Sample Sizes and Multiple Evaluation Methods in Human-Robot Interaction Experimentation

This paper presents details on planning and designing human studies for Human-Robot Interaction. There is a discussion of the importance of using large sample sizes to better represent the populations being investigated in order to have a better chance of obtaining statistically significant results for small to medium effects. Coverage of the four primary methods of evaluation are presented: (1) self-assessments, (2) behavioral observations, (3) psychophysiological measures, and (4) task performance metrics. The paper discusses the importance of using multiple methods of evaluation in order to have reliable and accurate results and to obtain convergent validity. Recommendations for planning and designing a large-scale, complex human study are detailed as well as lessons learned from a recent study that was conducted using 128 participants, four methods of evaluation, and a high fidelity, simulated disaster site.
Beyond eigenfaces: probabilistic matching for face recognition

We propose a technique for direct visual matching for face recognition and database search, using a probabilistic measure of similarity which is based on a Bayesian analysis of image differences. Specifically we model lure mutually exclusive classes of variation between facial images: intra-personal (variations in appearance of the same individual, due to different expressions or lighting) and extra-personal (variations in appearance due to a difference in identity). The likelihoods for each respective class are learned from training data using eigenspace density estimation and used to compute similarity based on the a posteriori probability of membership in the intra-personal class, and ultimately used to rank matches in the database. The performance advantage of this probabilistic technique over nearest-neighbor eigenface matching is demonstrated using results front ARPA's 1996 "FERET" face recognition competition, in which this algorithm was found to be the top performer.
Jointly optimal downlink beamforming and base station assignment

We present an algorithm that jointly determines the optimal downlink beamformers and the optimal assignment of each mobile to a base station. The optimality criterion is based on a systems perspective; provide sufficient quality of service for all users, transmitting as little excess power as possible. Since the algorithm is centralized and requires knowledge about all the channels in the system, it may be infeasible in a practical implementation. However, it provides the ultimate benchmark in system evaluations. Numerical examples show substantial gain compared to ordinary base station assignment.
Multi-sensor data fusion for realistic and accurate 3d reconstruction

In this paper, the problem of multi-sensor data fusion for 3D dimensional reconstruction/assessment of manufactured parts is investigated. For this, a method relying on cooperation of two acquisition/processing techniques (stereoscopic and structured light sensors) is presented. The stereoscopic system reconstructs the outline of the object, whereas the structured light system represents the workpiece as points that characterize its 3D surfaces. The developed approach exploits the complementarity of the two acquired data sets. To represent the whole set of measurements in a common reference frame, a fusion method is developed based on the geometric characteristics of the workpiece used to define a cost function, which allows perfect alignment of the two point sets. This is further favored by use of a camera common to the two sensory systems. Experimental results demonstrate that the proposed method outputs results, which can be meaningfully used in applications such as quality control.
LAP TGF-Beta Subset of CD4+CD25+CD127− Treg Cells is Increased and Overexpresses LAP TGF-Beta in Lung Adenocarcinoma Patients

Lung cancer is the leading cause of cancer death worldwide. Adenocarcinoma, the most commonly diagnosed histologic type of lung cancer, is associated with smoking. Cigarette smoke promotes inflammation on the airways, which might be mediated by Th17 cells. This inflammatory environment may contribute to tumor development. In contrast, some reports indicate that tumors may induce immunosuppressive Treg cells to dampen immune reactivity, supporting tumor growth and progression. Thus, we aimed to analyze whether chronic inflammation or immunosuppression predominates at the systemic level in lung adenocarcinoma patients, and several cytokines and Th17 and Treg cells were studied. Higher proportions of IL-17-producing CD4+ T-cells were found in smoking control subjects and in lung adenocarcinoma patients compared to nonsmoking control subjects. In addition, lung adenocarcinoma patients increased both plasma concentrations of IL-2, IL-4, IL-6, and IL-10, and proportions of Latency Associated Peptide (LAP) TGF-β subset of CD4+CD25+CD127− Treg cells, which overexpressed LAP TGF-β. This knowledge may lead to the development of immunotherapies that could inhibit the suppressor activity mediated by the LAP TGF-β subset of CD4+CD25+CD127− Treg cells to promote reactivity of immune cells against lung adenocarcinoma cells.
Fast initialization of equalizers for VSB-based DTV transceivers in multipath channel

This paper proposes a fast initialization technique for equalization of 8-VSB-based digital television (DTV) signal in severe multipath channels. We consider the use of a modified decision feedback equalizer (MDFE) , for fast initialization. The feedback filter (FBF) of the MDFE can be initialized simply by estimating the channel impulse response and only the feedforward filter (FFF) of the MDFE need training for initialization. To overcome the shortage of the training sequence in the VSB DTV signal, we propose a new initialization method by generating a virtual training signal to initialize the FFF of the MDFE. Simulation results show that the proposed scheme can fast initialize the equalizer using less than 5000 symbols, while providing the receiver performance comparable to that of conventional schemes.
New Public Key Cryptosystems Using Polynomials over Non-commutative Rings

In this paper, we propose a new method for designing public key cryptosystems based on general non-commutative rings. The key idea of our proposal is that for a given non-commutative ring, we can define polynomials and take them as the underlying work structure. By doing so, it is easy to implement Diffie-Helman-like key exchange protocol. And consequently, ElGamal-like cryptosystems can be derived immediately. Moreover, we show how to extend our method to non-commutative groups (or semi-groups).
The use of wet paper codes with audio watermarking based on echo hiding

We consider an audio watermarking technique based on echo hiding that provides both a very high quality of audio signals just after embedding of some hidden messages and robustness of their extraction under the condition of natural signal transforms. The technique of cepstrum analysis is used for hidden message extraction along with its parameter optimization. Since the extracted bit error probability is kept still significant for an acceptable sound fidelity and embedding rate, we propose to use wet paper codes to reduce the error probability to zero at the cost of a very negligible embedding rate degradation.
Silver-coated endotracheal tubes associated with reduced bacterial burden in the lungs of mechanically ventilated dogs.

STUDY OBJECTIVES To evaluate the influence of silver-coated endotracheal tubes on the lung bacterial burden of mechanically ventilated dogs. DESIGN Randomized, double-blinded, controlled experiment. SETTING Animal research facility of a regional medical university. PATIENTS OR PARTICIPANTS Eleven healthy adult dogs. INTERVENTIONS The dogs were intubated either with cuffed, noncoated endotracheal tubes or with endotracheal tubes having a novel antimicrobial silver hydrogel coating and were challenged with buccal administration of Pseudomonas aeruginosa. MEASUREMENTS AND RESULTS The silver coating delayed the appearance of bacteria on the inner surface of the endotracheal tubes ([mean +/- SD] duration of mechanical ventilation before appearance of bacteria, 3.2 +/- 0.8 days; mean duration of mechanical ventilation, 1.8 +/- 0.4 days; p = 0.016). The mean total aerobic bacterial burden in the lung parenchyma was statistically lower among the dogs receiving the silver-coated endotracheal tubes compared to those not receiving them (4.8 +/- 0.8 vs 5.4 +/- 9 log cfu/g lung tissue, respectively; p = 0.010). Pronounced differences were seen in the gross and histologic assessments of inflammation in the lung. Using an increasing severity scale of 0 to 12 to assess four components of histology (ie, hyperemia, edema, cellular infiltration, and bacterial presence), dogs receiving noncoated endotracheal tubes had statistically greater histology scores compared to dogs receiving silver-coated endotracheal tubes (7.1 plus minus 1.6 vs 2.8 plus minus 1.2, respectively; p < 0.001). CONCLUSION These results suggest that the silver coating of endotracheal tubes may delay the onset of and decrease the severity of lung colonization by aerobic bacteria. Based on these results, clinical studies are planned to determine the safety and clinical efficacy of silver-coated endotracheal tubes in patients requiring mechanical ventilation in the ICU setting.
Exploring Crowdsourced Reverse Engineering

While Crowdsourcing has been successfully applied in the field of Software Engineering, it is widely overseen in Reverse Engineering. In this paper we introduce the idea of Crowdsourced Reverse Engineering and identify the three major challenges: 1) automatic task extraction, 2) source code anonymization and 3) quality control and results aggregation. To illustrate Crowdsourced Reverse Engineering, we outline our approach for performing the Reverse Engineering activity of concept assignment as a crowdsourced classification task and address suitable methods and considerations with regard to each of the the three challenges. Following a brief overview on existing research in which we position our approach against related work, we report on our experiences from an experiment conducted on the crowdsourcing platform microworkers.com, which yielded 187 results by 34 crowd workers, classifying 10 code fragments with decent quality.
Instrument State Research and Development Tax Credits : The Historical Emergence of a Distinctive Economic Policy

By 2010, all but 12 U.S. states had adopted some form of research and development tax credits. The forces driving the rapid rise and spread of this policy remain unclear. This event history analysis finds adoption to be associated with higher state unemployment levels, supporting the notion of “policy-making from disadvantage. ” Yet higher patenting activity is also associated with adoption, suggesting that having a strong preexisting research and development (R&D) infrastructure facilitates adoption. In the 1980s, having a Republican governor apparently propelled adoption, but partisan influences disappeared in later years. Having a governorship with constitutionally strong budgetary power and having a centralized governing board for higher education are associated with adoption, and interaction analyses indicate that the combination of a centralized board and a higher number of research universities are especially positive forces in adoption. The socioeconomic, political, and structural influences found in this article suggest several potentially fruitful directions for future analyses.
Modèles de graphe aléatoire à classes chevauchantes pour l'analyse des réseaux

Les reseaux sont largement utilises dans de nombreux domaines scientifiques afin de representer les interactions entre objets d'interet. Ainsi, en biologie, les reseaux de regulation s'appliquent a decrire les mecanismes de regulation des genes, a partir de facteurs de transcription, tandis que les reseaux metaboliques permettent de representer des voies de reactions biochimiques. En sciences sociales, ils sont couramment utilises pour representer les interactions entre individus. Dans ce contexte, de nombreuses methodes non-supervisees de clustering ont ete developpees afin d'extraire des informations, a partir de la topologie des reseaux. La plupart d'entre elles partitionne les noeuds dans des classes disjointes, en fonction de leurs profils de connection. Recemment, des etudes ont mis en evidence les limites de ces techniques. En effet, elles ont montre qu'un grand nombre de reseaux contenaient des noeuds connus pour appartenir a plusieurs groupes simultanement. Pour repondre a ce probleme, nous proposons l'Overlapping Stochastic Block Model (OSBM). Cette approche autorise les noeuds a appartenir a plus d'une classe et generalise le tres connu Stochastic Block Model (SBM), sous certaines hypotheses. Nous montrons que le modele est identifiable dans des classes d'equivalence et nous proposons un algorithme d'inference base sur des techniques variationnelles globales et locales. Finalement, en utilisant des donnees simulees et reelles, nous comparons nos travaux avec d'autres approches.
Adaptive Robot Language Tutoring Based on Bayesian Knowledge Tracing and Predictive Decision-Making

In this paper, we present an approach to adaptive language tutoring in child-robot interaction. The approach is based on a dynamic probabilistic model that represents the interrelations between the learner's skills, her observed behaviour in tutoring interaction, and the tutoring action taken by the system. Being implemented in a robot language tutor, the model enables the robot tutor to trace the learner's knowledge and to decide which skill to teach next and how to address it in a game-like tutoring interaction. Results of an evaluation study are discussed demonstrating how participants in the adaptive tutoring condition successfully learned foreign language words. CCS Concepts. Computing methodologies → Probabilistic reasoning; Cognitive robotics;. Applied computing → Interactive learning environments;. Human-centered computing → Empirical studies in HCI;
Do sibling relationships protect adolescents in residential care and traditional families from developing psychopathologies?

ABSTRACT The transition of young people to residential care is caused, usually, by the need for removal from a dysfunctional environment, which can poten tially disrupt their healthy development and put them at a higher risk. Sibling relationships have been identified as critical to adapting to the developmental process. The present study analyzes whether sibling relationship quality can protect from the development of certain psychopathologies among adolescents from traditional families, as well as institutionalized adolescents. We also intend to analyze the differences in sibling relationship quality and psychopathological symptoms, according to the adolescents' family structure, gender and age. The sample consisted of 387 adolescents, 215 from traditional families and 172 in residential care, aged from 12 to 18 years old. The results show that siblings can play an important role in the prevention of psychopathological symptoms. Young people in residential care appear to have higher psychopathological symptoms; nevertheless, they also present higher levels of pro-social behaviors with siblings.
The impact of substance use disorders on treatment engagement among justice-involved veterans with posttraumatic stress disorder.

Veterans involved with the criminal justice system represent a particularly vulnerable population who experience high rates of both posttraumatic stress disorder (PTSD) and substance use disorders (SUD). This study sought to investigate whether having co-occurring SUD is a barrier to PTSD treatment. This is a retrospective observational study of a national sample of justice-involved veterans served by the Veterans Health Administration Veterans Justice Outreach program who had a diagnosis of PTSD (N = 27,857). Mixed effects logistic regression models with a random effect for facility (N = 141 medical centers) were utilized to estimate the odds of receiving each type of PTSD treatment as a function of having a SUD diagnosis. Results indicate that a majority of veterans with PTSD served by the Veterans Justice Outreach program have an SUD diagnosis (73%), and having a co-occurring SUD was associated with higher odds of receiving PTSD treatment, after adjusting for demographic differences. Although not without limitations, these results suggest that among justice-involved veterans enrolled in the Veterans Health Administration with PTSD, having an SUD comorbidity is not a barrier to PTSD treatment and may in fact facilitate access to PTSD treatment. (PsycINFO Database Record
Two-resonator circuit quantum electrodynamics: Dissipative theory

We present a theoretical treatment for the dissipative two-resonator circuit quantum electrodynamics setup referred to as quantum switch. There, switchable coupling between two superconducting resonators is mediated by a superconducting qubit operating in the dispersive regime, where the qubit transition frequency is far detuned from those of the resonators. We derive an effective Hamiltonian for the quantum switch beyond the rotating-wave approximation and provide a detailed study of the dissipative dynamics. As a central finding, we derive analytically how the qubit affects the quantum switch even if the qubit has no dynamics, and we estimate the strength of this influence. The analytical results are corroborated by numerical calculations, where coherent oscillations between the resonators, the decay of coherent and Fock states, and the decay of resonatorresonator entanglement are studied. Finally, we suggest an experimental protocol for extracting the damping constants of qubit and resonators by measuring the quadratures of the resonator fields.
TaxCollector: Modifying Current 16S rRNA Databases for the Rapid Classification at Six Taxonomic Levels

The high level of conservation of 16S ribosomal RNA gene (16S rRNA) in all Prokaryotes makes this gene an ideal tool for the rapid identification and classification of these microorganisms. Databases such as the Ribosomal Database Project II (RDP-II) and the Greengenes Project offer access to sets of ribosomal RNA sequence databases useful in identification of microbes in a culture-independent analysis of microbial communities. However, these databases do not contain all of the taxonomic levels attached to the published names of the bacterial and archaeal sequences. TaxCollector is a set of scripts developed in Python language that attaches taxonomic information to all 16S rRNA sequences in the RDP-II and Greengenes databases. These modified databases are referred to as TaxCollector databases, which when used in conjunction with BLAST allow for rapid classification of sequences from any environmental or clinical source at six different taxonomic levels, from domain to species. The TaxCollector database prepared from the RDP-II database is an important component of a new 16S rRNA pipeline called PANGEA. The usefulness of TaxCollector databases is demonstrated with two very different datasets obtained using samples from a clinical setting and an agricultural soil. The six TaxCollector scripts are freely available on http://taxcollector.sourceforge. net and on http://www.microgator. org.
An Approach to Modelling and Evaluating AGG Based Reliable Software Systems

AGG is a well established development environment which is used to model software systems in terms of graphs. Though AGG provides an appropriate basis for system modelling and verification, it can neither analyze nor evaluate the system reliability. In this paper, we propose an AGG-based strategy which, by combining generalized stochastic petri net (GSPN) and tools for reliability analysis, supports software system reliability modelling and evaluation. This work expands this idea in three directions: First, we give an AGG reliability model in which we add error attribute to AGG graph for capturing system error information, and at the same time performing the system error state transition through the AGG production. Second, we present how to map rules from the AGG reliability model into the GSPN one, which in turn can be used for reliability evaluation. The other direction is to use a Client/Server application to demonstrate our approach.
Impact of Genetic Notification on Smoking Cessation: Systematic Review and Pooled-Analysis

Objectives This study aimed to evaluate the impact of genetic notification of smoking-related disease risk on smoking cessation in the general population. Secondary objectives were to assess the impact of genetic notification on intention-to-quit smoking and on emotional outcomes as well as the understanding and the recall of this notification. Methods A systematic review of articles from inception to August 2011 without language restriction was realized using PubMed, Embase, Scopus, Web of Science, PsycINFO and Toxnet. Other publications were identified using hand search. The pooled-analysis included only randomized trials. Comparison groups were (i) high and low genetic risk versus control, and (ii) high versus low genetic risk. For the pooled-analysis random effect models were applied and sensitivity analyses were conducted. Results Eight papers from seven different studies met the inclusion criteria of the review. High genetic risk notification was associated with short-term increased depression and anxiety. Four randomized studies were included in the pooled-analysis, which revealed a significant impact of genetic notification on smoking cessation in comparison to controls (clinical risk notification or no intervention) in short term follow-up less than 6 months (RR = 1.55, 95% CI 1.09–2.21). Conclusions In short term follow-up, genetic notification increased smoking cessation in comparison to control interventions. However, there is no evidence of long term effect (up to 12 month) on smoking cessation. Further research is needed to assess more in depth how genetic notification of smoking-related disease could contribute to smoking cessation.