Miracle-dz/UniFAR-FTUs huggingface dataset:
Educational differences in smoking: international comparison

Abstract Objective: To investigate international variations in smoking associated with educational level. Design: International comparison of national health, or similar, surveys. Subjects: Men and women aged 20 to 44 years and 45 to 74years. Setting: 12 European countries, around 1990. Main outcome measures: Relative differences (odds ratios) and absolute differences in the prevalence of ever smoking and current smoking for men and women in each age group by educational level. Results: In the 45 to 74 year age group, higher rates of current and ever smoking among lower educated subjects were found in some countries only. Among women this was found in Great Britain, Norway, and Sweden, whereas an opposite pattern, with higher educated women smoking more, was found in southern Europe. Among men a similar north-south pattern was found but it was less noticeable than among women. In the 20 to 44 year age group, educational differences in smoking were generally greater than in the older age group, and smoking rates were higher among lower educated people in most countries. Among younger women, a similar north-south pattern was found as among older women. Among younger men, large educational differences in smoking were found for northern European as well as for southern European countries, except for Portugal. Conclusions: These international variations in social gradients in smoking, which are likely to be related to differences between countries in their stage of the smoking epidemic, may have contributed to the socioeconomic differences in mortality from ischaemic heart disease being greater in northern European countries. The observed age patterns suggest that socioeconomic differences in diseases related to smoking will increase in the coming decades in many European countries.
Multimodal authentication based on random projections and source coding

In this paper, we consider an authentication framework for independent modalities based on binary hypothesis testing using source coding jointly with the random projections. The source coding ensures the multimodal signals reconstruction at the decoder based on the authentication data. The random projections are used to cope with the security, privacy, robustness and complexity issues. Finally, the authentication performance is investigated for both direct and random projections domains. The asymptotic performance approximation is derived and compared with the exact solutions. The impact of modality fusion on the authentication system performance is demonstrated.
Improving the performance of multi-criteria recommendation system using fuzzy integrated meta heuristic

Recommender systems have been researched in the extreme in recent years, and are implemented in a variety of applications. Increasing number of E-commerce sites on the Internet has made the information overload. In general, users are enabled to provide overall ratings on items but many online systems allow users to provide their ratings on different criterions. So much research work have been made in the past to build a recommendation system focusing on the ratings of a single criterion. However, using the approach of multi criteria recommender systems in online environment is still in its developing phase. This proposed approach recommends the relevant item to the user with the help of Fuzzy Multi-criteria Decision Making approach.
Learning Phone Embeddings for Word Segmentation of Child-Directed Speech

This paper presents a novel model that learns and exploits embeddings of phone ngrams for word segmentation in child language acquisition. Embedding-based models are evaluated on a phonemically transcribed corpus of child-directed speech, in comparison with their symbolic counterparts using the common learning framework and features. Results show that learning embeddings significantly improves performance. We make use of extensive visualization to understand what the model has learned. We show that the learned embeddings are informative for both word segmentation and phonology in general.
Study of near consensus complex social networks using eigen theory

This paper extends the definition of an exact consensus complex social network to that of a near consensus complex social network. A near consensus complex social network is a social network with nontrivial topological features and steady state values of the decision certitudes of the majority of the nodes being either higher or lower than a threshold value. By using eigen theories, the relationships among the vectors representing the steady state values of the decision certitudes of the nodes, the influence weight matrix and the set of vectors representing the initial state values of the decision certitudes of the nodes that satisfies a given near consensus specification are characterized.
The N-terminus of Bunyamwera orthobunyavirus NSs protein is essential for interferon antagonism

Bunyamwera virus NSs protein is involved in the inhibition of cellular transcription and the interferon (IFN) response, and it interacts with the Med8 component of Mediator. A spontaneous mutant of a recombinant NSs-deleted Bunyamwera virus (rBUNdelNSs2) was identified and characterized. This mutant virus, termed mBUNNSs22, expresses a 21 aa N-terminally truncated form of NSs. Like rBUNdelNSs2, mBUNNSs22 is attenuated in IFN-deficient cells, and to a greater extent in IFN-competent cells. Both rBUNdelNSs2 and mBUNNSs22 are potent IFN inducers and their growth can be rescued by depleting cellular IRF3. Strikingly, despite encoding an NSs protein that contains the Med8 interaction domain, mBUNNSs22 fails to block RNA polymerase II activity during infection. Overall, our data suggest that both the interaction of NSs with Med8 and a novel unidentified function of the NSs N-terminus, seem necessary for Bunyamwera virus to counteract host antiviral responses.
Quantifying the risk of heart disease following acute ischaemic stroke: a meta-analysis of over 50 000 participants

Objective Following an acute stroke, there is a high risk of recurrence. However, the leading cause of mortality following a stroke is due to coronary artery disease (CAD) and myocardial infarction (MI) but that risk has not been robustly quantified. We sought to reliably quantify the risk of ischaemic heart disease (IHD) in patients presenting with acute ischaemic stroke (AIS) in the absence of a known cardiac history. Setting A meta-analysis study. PubMed, MEDLINE, EMBASE and Google Scholar were searched for potential studies up to October 2015. Included studies reported an acute cerebral ischaemic event and followed for CAD or MI within 1 year in patients without known IHD. Using arcsine transformed proportions for meta-analysis, studies were combined using a generic inverse variance random-effects model to calculate the pooled standardised mean difference and 95% CIs. These were interpreted as the percentage prevalence of CAD or incidence of MI following AIS. Results 17 studies with 4869 patients with AIS demonstrated a mean average of asymptomatic CAD in 52%. Anatomical methods of CAD detection revealed a prevalence of asymptomatic ≥50% coronary stenosis in 32% (95% CI 19% to 47%; p<0.00001). 8 studies with 47229 patients with ischaemic stroke revealed an overall risk of MI in the year following stroke of 3% (95% CI 1% to 5%; p<0.00001) despite the absence of any cardiac history. Conclusions One-third of patients with ischaemic stroke with no cardiac history have more than 50% coronary stenosis and 3% are at risk of developing MI within a year. Our findings provide a reliable quantitative measure of the risk of IHD following AIS in patients with no cardiac history.
Conceptions of Grammar Teaching: A Case Study of Teachers' Beliefs and Classroom Practices.

This paper presents a case study that investigated and compared the beliefs and actual classroom practices of two experienced English language teachers with regards to grammar teaching in a primary school in Singapore. Areas where practices converged with or diverged from beliefs about grammar teaching are examined and discussed as well as the factors that have influenced the teachers' actual classroom practices. The findings suggest that teachers do indeed have a set of complex belief systems that are sometimes not reflected in their classroom practices for various complicated reasons, some directly related to context of teaching.
Prevalence of Bovine Mastitis Pathogens in Bulk Tank Milk in China

The objectives of this study were to estimate the herd prevalence of major mastitis pathogens in bulk tank milk (BTM) in China dairy herds, to determine the relationship between the presence of mastitis pathogens and bulk tank milk somatic cell counts (BTSCC), and to investigate the impact of different dairy cattle farming modes and region on bacterial species. BTM samples collected from 894 dairy herds in China were examined for the presence of mastitis pathogens. The Flinders Technology Associates (FTA) cards were used for BTM sample collection, storage, and transportation and bacterial DNA amplification by real-time PCR. Among contagious pathogens, Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus dysgalactiae were detected in 50.1, 92.2, and 72.3% of the 894 BTM samples, respectively. Among environmental pathogens, E. coli, Streptococcus uberis, Enterococcus spp. , Klebsiella spp. , Serratia marcescens, Corynebacterium bovis, and Arcanobacterium pyogenes were detected in 28.6, 8.9, 35.7, 20.0, 1.3, 17.0, and 67.2% of the BTM samples, respectively. Staphylococcal β-lactamase gene was detected in 61.7% of the BTM samples. The presence of Staphylococcus aureus and Arcanobacterium pyogenes were significantly associated with high BTSCC, respectively. Significant differences were found in presence of Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus dysgalactiae in BTM sampled from the small household farms, dairy-farming communities, and large-scaled dairy farms. There were significant differences in the presence of Streptococcus agalactiae, Streptococcus dysgalactiae, Arcanobacterium pyogenes, staphylococcal β-lactamase gene, Staphylococcus spp. , Klebsiella spp. , Enterococcus spp. , and Streptococcus uberis in BTM among Inner Mongolia, Heilongjiang, and Hebei province. In conclusion, contagious mammary pathogens are predominated among pathogens in BTM samples in China.
High-speed microvia formation with UV solid-state lasers

Laser drilling has emerged in the last five years as the most widely accepted method of creating microvias in high-density electronic interconnect and chip packaging devices. Most commercially available laser drilling tools are currently based on one of two laser types: far-IR CO/sub 2/ lasers and UV solid-state lasers at 355 nm. While CO/sub 2/ lasers are recognized for their high average power and drilling throughput, UV lasers are known for high-precision material removal and their ability to drill the smallest vias, with diameters down to about 25-30 /spl mu/m now achievable in production. This paper presents an historical overview of techniques for drilling microvias with UV solid-state lasers. Blind and through via formation by percussion drilling, trepanning, spiralling, and image projection with a shaped beam are discussed. Advantages and range of applicability of each technique are summarized. Drivers of throughput scaling over the last five years are outlined, and representative current-generation performance is presented.
When is it the case that one tableau suffices ? A note on Prince ( 2015 )

Prince (2015) shows that OT has the following surprising property: no ranking information is lost by replacing two violation tableaux with the single tableau obtained by summing any row of one of the two original tableaux with any row of the other. Which properties of OT are responsible for this result? This squib answers this question: Prince’s result that “one tableau suffices” holds whenever grammatical optimization is relative to a strict additive weak ordering. As an application, Prince’s result is extended from OT to HG.
Global Warming’s “Six Americas Short Survey”: Audience Segmentation of Climate Change Views Using a Four Question Instrument

ABSTRACT Audience segmentation has long been used in marketing, public health, and communication, and is now becoming an important tool in the environmental domain as well. Global Warming's Six Americas is a well-established segmentation of Americans based on their climate change beliefs, attitudes, and behaviors. The original Six Americas model requires a 36 question-screener and although there is increasing interest in using these segments to guide education and outreach efforts, the number of survey items required is a deterrent. Using 14 national samples and machine learning algorithms, we identify a subset of four questions from the original 36, the Six Americas Short SurveY (SASSY), that accurately segment survey respondents into the Six Americas categories. The four items cover respondents' global warming risk perceptions, worry, expected harm to future generations, and personal importance of the issue. The true positive accuracy rate for the model ranges between and across the six segments on a 20 hold-out set. Similar results were achieved with four out-of-sample validation data sets. In addition, the screener showed test-retest reliability on an independent, two-wave sample. To facilitate further research and outreach, we provide a web-based application of the new short-screener.
HTN Planning Approach Using Fully Instantiated Problems

Many planning techniques have been developed to allow autonomous systems to act and make decisions based on their perceptions of the environment. Among these techniques, HTN (Hierarchical Task Network) planning is one of the most used in practice. Unlike classical approaches of planning. HTN operates by decomposing task into sub-tasks until each of these sub-tasks can be achieved an action. This hierarchical representation provide a richer representation of planning problems and allows to better guide the plan search and provides more knowledge to the underlying algorithms. In this paper, we propose a new approach of HTN planning in which, as in conventional planning, we instantiate all planning operators before starting the search process. This approach has proven its effectiveness in classical planning and is necessary for the development of effective heuristics and encoding planning problems in other formalism such as CSP or SAT. The instantiation is actually used by most modern planners but has never been applied in an HTN based planning framework. We present in this article a generic instantiation algorithm which implements many simplification techniques to reduce the process complexity inspired from those used in classical planning. Finally we present some results obtained from an experimentation on a range of problems used in the international planning competitions with a modified version of SHOP planner using fully instantiated problems.
Hoping control of a one-legged robot

the hopping control of a one-legged robot is investigated using Spring Loaded Inverted Pendulum (SLIP). The hopping progress of a robot is divided into the flight phase and the stance phase. The dynamics Models of a hopping robot are established using Lagrangian equation. The Impact models of a robot's landing and take-off phase are obtained under instantaneous impact hypothesis. The periodic hopping control of a robot is realized using one actuator and simple PD control technology. The computer simulations show that the control algorithm proposed in this paper is effective for the periodic hopping control of a robot, and the double periodic hopping will be appeared when the PD parameters are increased.
Finding Temporal Structure in Text: Machine Learning of Syntactic Temporal Relations

This research proposes and evaluates a linguistically motivated approach to extracting temporal structure from text. Pairs of events in a verb-clause construction were considered, where the first event is a verb and the second event is the head of a clausal argument to that verb. All pairs of events in the TimeBank that participated in verb-clause constructions were selected and annotated with the labels BEFORE, OVERLAP and AFTER. The resulting corpus of 895 event-event temporal relations was then used to train a machine learning model. Using a combination of event-level features like tense and aspect with syntax-level features like the paths through the syntactic tree, support vector machine (SVM) models were trained which could identify new temporal relations with 89.2% accuracy. High accuracy models like these are a first step towards automatic extraction of temporal structure from text.
Novel HIV-1 MiRNAs Stimulate TNFα Release in Human Macrophages via TLR8 Signaling Pathway

Purpose To determine whether HIV-1 produces microRNAs and elucidate whether these miRNAs can induce inflammatory response in macrophages (independent of the conventional miRNA function in RNA interference) leading to chronic immune activation. Methods Using sensitive quantitative Real Time RT-PCR and sequencing, we detected novel HIV-derived miRNAs in the sera of HIV+ persons, and associated with exosomes. Release of TNFα by macrophages challenged with HIV miRNAs was measured by ELISA. Results HIV infection of primary alveolar macrophages produced elevated levels of viral microRNAs vmiR88, vmiR99 and vmiR-TAR in cell extracts and in exosome preparations from conditioned medium. Furthermore, these miRNAs were also detected in exosome fraction of sera from HIV-infected persons. Importantly, vmiR88 and vmiR99 (but not vmiR-TAR) stimulated human macrophage TNFα release, which is dependent on macrophage TLR8 expression. These data support a potential role for HIV-derived vmiRNAs released from infected macrophages as contributing to chronic immune activation in HIV-infected persons, and may represent a novel therapeutic target to limit AIDS pathogenesis. Conclusion Novel HIV vmiR88 and vmiR99 are present in the systemic circulation of HIV+ persons and could exhibit biological function (independent of gene silencing) as ligands for TLR8 signaling that promote macrophage TNFα release, and may contribute to chronic immune activation. Targeting novel HIV-derived miRNAs may represent a therapeutic strategy to limit chronic immune activation and AIDS progression.
Hashing on Nonlinear Manifolds

Learning-based hashing methods have attracted considerable attention due to their ability to greatly increase the scale at which existing algorithms may operate. Most of these methods are designed to generate binary codes preserving the Euclidean similarity in the original space. Manifold learning techniques, in contrast, are better able to model the intrinsic structure embedded in the original high-dimensional data. The complexities of these models, and the problems with out-of-sample data, have previously rendered them unsuitable for application to large-scale embedding, however. In this paper, how to learn compact binary embeddings on their intrinsic manifolds is considered. In order to address the above-mentioned difficulties, an efficient, inductive solution to the out-of-sample data problem, and a process by which nonparametric manifold learning may be used as the basis of a hashing method are proposed. The proposed approach thus allows the development of a range of new hashing techniques exploiting the flexibility of the wide variety of manifold learning approaches available. It is particularly shown that hashing on the basis of t-distributed stochastic neighbor embedding outperforms state-of-the-art hashing methods on large-scale benchmark data sets, and is very effective for image classification with very short code lengths. It is shown that the proposed framework can be further improved, for example, by minimizing the quantization error with learned orthogonal rotations without much computation overhead. In addition, a supervised inductive manifold hashing framework is developed by incorporating the label information, which is shown to greatly advance the semantic retrieval performance.
A Partial Evaluator for Curry

We present a partial evaluator for functional logic programs written in Curry. In contrast to previous approaches to the partial evaluation of functional logic programs, we take into account the features used in contemporary Curry programs, in particular, non-deterministic operations and recursive let expressions. For this purpose, we base our partial evaluator on FlatCurry, an intermediate language for the representation of Curry programs. We sketch our approach and present initial benchmarks of our implementation.
Exploring Social Music Behavior: An Investigation of Music Selection at Parties

This paper builds an understanding how music is currently listened to by small (fewer than 10 individuals) to medium-sized (10 to 40 individuals) gatherings of people—how songs are chosen for playing, how the music fits in with other activities of group members, who supplies the music, the hardware/software that supports song selection and presentation. This fine-grained context emerges from a qualitative analysis of a rich set of participant observations and interviews focusing on the selection of songs to play at social gatherings. We suggest features for software to support music playing at parties.
New Developments in Lexical Functional Grammar

This article provides a brief introduction to a number of key advances in LFG since the late 1980s. A description of the framework itself is given in Neidle (this volume), which provides an overview of the 1982 version of the theory, together with a sketch of a major subsequent development, Lexical Mapping Theory. LFG as a framework for linguistic description has its roots in the desire to elaborate a fully explicit, mathematically precise and computationally oriented model of linguistic structures which would support a psychologically plausible model of human linguistic processing. Since that time, LFG has been applied to the description of a wide variety of diierent languages, and has enjoyed a signiicant degree of innuence in computational linguistics. A very striking aspect of LFG is its stability as a framework. The fundamental architecture of the theory has remained constant since the late 1970s. A very important facet of LFG syntax, which signals it out from many other syntactic theories, is the representation of diierent dimensions of the syntax (c-structure and f-structure, or external and internal syntax) by means of diierent formal entities: the architecture combines a context free grammar formalism (for c-structure) with attribute value structures (for f-structures). These (and other) diierent dimensions are related by structural correpondence functions, or projections, the most familiar of which is the function mapping c-structure nodes into f-structure,. As the theory has progressed, light has been cast on the nature of other structures and work has proceeded on the mapping functions. This brief review, which focusses on LFG syntax, touches on the nature of one dimension (in addition to f-structure and c-structure), namely argument structure, and the argument structure to f-structure projection. In section 1 we discuss recent work in Lexical Mapping Theory, which concerns both the nature of argument structure and the mapping from argument structure of f-structure. Much other work in LFG has been concerned with extending the description languages of LFG (for c-structure and f-structure), and on the c to f-structure projection. The rest of this review of recent development focusses on this, and on the range of syntactic analyses made available in the LFG architecture. We pick out for particular attention three aspects of this work: that on principles of c-structure organisation and the mapping to f-structure; that on the extension of the f-structure description language to include functional uncertainty equations and some linguistic analyses which exploit this; and …