Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel I 221 L Substitution in Neuraminidase Confers High-Level Resistance to Oseltamivir in In fl uenza B Viruses

Vanessa Escuret, Patrick J. Collins, Jean-Sébastien Casalegno, Sebastien G. Vachieri, Nicholas Cattle, Olivier Ferraris, Murielle Sabatier, Emilie Frobert, Valérie Caro, John J. Skehel, Steve Gamblin, Frédéric Valla, Martine Valette, Michèle Ottmann, John W. McCauley, Rodney S. Daniels, and Bruno Lina Laboratoire de Virologie et Centre National de Référence virus influenzae, and Service de Réanimation Pédiatrique, Hôpital Femme Mère Enfant, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron, Laboratoire Virpath EA4610, Faculté de Médecine Lyon Est, Université Claude Bernard Lyon 1, Université de Lyon, and Genotyping of Pathogens and Public Health Platform, Institut Pasteur, Paris, France; Division of Virology, Division of Molecular Structure, and WHO Collaborating Centre for Reference and Research on Influenza, Division of Virology, Medical Research Council National Institute for Medical Research, London, United Kingdom
Frozen-thawed embryo transfer cycles.

OBJECTIVE To review the outcomes of frozen-thawed embryo transfer cycles. DESIGN. Retrospective review. SETTING Tertiary assisted reproduction centre, Hong Kong. PATIENTS Subfertile patients undergoing frozen-thawed embryo transfer between July 2005 and December 2007. MAIN OUTCOME MEASURES Clinical and ongoing pregnancy rates. RESULTS A total of 983 frozen-thawed embryo transfer cycles performed during the study period were reviewed. The clinical pregnancy and ongoing pregnancy rates were 35% and 30%, respectively. Factors associated with successful outcome included younger maternal age (<=35 years) and 4 or more blastomeres at replacement, but not the method of insemination, the cause of subfertility, or the type of frozen-thawed embryo transfer cycle. The overall multiple pregnancy rate was 18%. For cycles with a single embryo replaced, embryos having 4-cell or higher stages at replacement gave an ongoing pregnancy rate of 25%, whereas those with less than 4 cells had a significantly lower ongoing pregnancy rate of 5% only. Blastomere lysis after thawing significantly reduced the clinical pregnancy and ongoing pregnancy rates of cycles with one embryo replaced. CONCLUSIONS Clinical pregnancy and ongoing pregnancy rates of frozen-thawed embryo transfer cycles were 35% and 30%, respectively. Higher pregnancy rates were associated with younger maternal age (<=35 years), blastomere numbers of 4 or more, and no blastomere lysis after thawing.
Automated plant identification using artificial neural networks

This paper describes a method of training an artificial neural network, specifically a multilayer perceptron (MLP), to act as a tool to help identify plants using morphological characters collected automatically from images of botanical herbarium specimens. A methodology is presented here to provide a practical way for taxonomists to use neural networks as automated identification tools, by collating results from a population of neural networks. A case study is provided using data extracted from specimens of the genus Tilia in the Herbarium of the Royal Botanic Gardens, Kew, UK. A classification accuracy of 44% was achieved on this challenging multiclass problem.
Fusion of Information Retrieval Engines (FIRE)

We examine the feasibility of fusing the outputs of multiple text retrieval engines to improve accuracy. We tested three Web-based search engines (Excite for Web Servers, Infoseek's Ultraseek Server, and Sony Search Engine) over a 74,520 document collection (TREC Wall Street Journal articles from 1990-92) with a set of 125 natural-language queries with relevance judgements (TREC topics 51-175). We show that a weighted combination of scores produces higher precision over the top 5, 105 20, and 30 documents than any single engine over the same data set. We also compare favorably against the state-of-the-art heuristics in merging search engines. Our results suggest that fusing the results from the most dissimilar engines (those with the least overlap in the retrieved sets) is a more effective strategy than simply weighting the best engines more heavily.
Phase unwrapping for 2-D blind deconvolution of ultrasound images

In most approaches to the problem of two-dimensional homomorphic deconvolution of ultrasound images, the estimation of a corresponding point-spread function (PSF) is necessarily the first stage in the process of image restoration. This estimation is usually performed in the Fourier domain by either successive or simultaneous estimation of the amplitude and phase of the Fourier transform (FT) of the PSF. This paper addresses the problem of recovering the FT-phase of the PSF, which is an important reconstruction problem by itself. The purpose of this paper is twofold. First, it provides a theoretical framework, establishing that the FT-phase of the PSF can be effectively estimated by a proper smoothing of the FT-phase of the appropriate radio-frequency (RF) image. Second, it presents a novel approach to the estimation of the FT-phase of the PSF, by solving a continuous Poisson equation over a predefined smooth subspace, in contrast to the discrete Poisson equation solver used for the classical least mean squares phase unwrapping algorithms, followed by a smoothing procedure. The proposed approach is possible due to the distinct properties of the FT-phases, among which the most important property is the availability of precise values of their partial derivatives. This property overcomes the main disadvantage of the discrete schemes, which routinely use wrapped (principal ) values of the phase in order to approximate its partial derivatives. Since such an approximation is feasible subject to the restriction that the partial phase differences do not exceed /spl pi/ in absolute value, the discrete schemes perform satisfactory only for few practical situations. The proposed approach is shown to be independent of this restriction and, thus, it performs for a wider class of the phases with significantly lower errors. The main advantages of the novel method over the algorithms based on discrete schemes are demonstrated in a series of computer simulations and for in vivo measurements.
The effect of points and audio on concentration, engagement, enjoyment, learning, motivation, and classroom dynamics using Kahoot!

There are many examples on the use of game-based learning in and outside the classroom, along with evaluation of their effect in terms of engagement, learning, classroom dynamics, concentration, motivation and enjoyment. Most of the research in this area focuses on evaluations of the use of game-based learning applications and the effect they have on the students. The majority of these papers show that gamebased learning has a positive effect compared to more traditional learning methods. However, there are very few papers that investigate what specific elements in game-based learning applications that produce a positive effect. In this paper, we present an experiment where we investigated how the use of points and audio affect the learning environment. Specifically, the paper presents results from an experiment where the same lecture was taught for different group of students using the game-based learning platform Kahoot! One group used Kahoot! as it supposed to be used with audio and points, one group used Kahoot! with audio but without points, one group used Kahoot! without audio but with points, and one group used Kahoot! without points and audio. The results from the experiment reveal that there are some significant differences whether audio and points are used in game-based learning in the areas of concentration, engagement, enjoyment, and motivation. The most surprising finding was how the classroom dynamics was positively affected by the use of audio. A total of 593 students participated in this experiment with a gender distribution of 44% female and 56 male students.
Silencing of a novel tumor metastasis suppressor gene LASS2/TMSG1 promotes invasion of prostate cancer cell in vitro through increase of vacuolar ATPase activity

Homo sapiens longevity assurance homologue 2 of yeast LAG1 (LASS2), also known as tumor metastasis suppressor gene 1 (TMSG1), is a newly found tumor metastasis suppressor gene in 1999. Preliminary studies showed that it not only suppressed tumor growth but also closely related to tumor metastasis, however, its molecular mechanisms is still unclear. There have been reported that protein encoded by LASS2/TMSG‐1 could directly interact with the C subunit of Vacuolar ATPase (V‐ATPase), which suggested that LASS2/TMSG1 might inhibit the invasion and metastasis through regulating the function of V‐ATPase. Thus, in this study, we explored the effect of small interference RNA (siRNA) targeting LASS2/TMSG1 on the invasion of human prostate carcinoma cell line PC‐3M‐2B4 and its molecular mechanisms associated with the V‐ATPase. Real‐time fluorogentic quantitative PCR (RFQ‐PCR) and Western blot revealed dramatic reduction of 84.5% and 60% in the levels of LASS2/TMSG1 mRNA and protein after transfection of siRNA in PC‐3M‐2B4 cells. The V‐ATPase activity and extracellular hydrogen ion concentration were significantly increased in 2B4 cells transfected with the LASS2/TMSG1‐siRNA compared with the controls. The activity of secreted MMP‐2 was up‐regulated in LASS2/TMSG1‐siRNA treated cells compared with the controls; and the capacity for migration and invasion in LASS2/TMSG1‐siRNA treated cells was significantly higher than the controls. Thus, we concluded that silencing of LASS2/TMSG1 may promote invasion of prostate cancer cell in vitro through increase of V‐ATPase activity and extracellular hydrogen ion concentration and in turn the activation of secreted MMP‐2. J. Cell. Biochem. 113: 2356–2363, 2012. © 2012 Wiley Periodicals, Inc.
The Perception and Management of 24/7 Work Availability: Work-life balance in the tramp shipping industry

Globalization, and fierce competition has been one of the main factors contributing to the increase of 24/7 work availability. 24/7 work availability is defined by the constant reachability of workers, and is regarded to be enhanced by the introduction and democratization of ICT. Arguably, constant work availability has shown to negatively affect individuals’ work-life balance. To contextualize, as well as illustrate 24/7 work availability, the tramp shipping industry, which is characterized by high intensity and global logistics, is analyzed due to its full implementation of 24/7 work availability. This thesis aims to advance the knowledge on the sociology of contemporary work. Particularly, to comprehend how individuals in the tramp shipping industry perceive and manage 24/7 work availability, by applying boundary theory and to understand how boundary management can be utilized to establish work-life balance. In order to provide different perspectives to the central concept, literature and theory from various fields of research is thoroughly reviewed in the thesis. Boundary theory, person-environment fit model, and cultural theory are thus used as lenses and support the analysis of the collected empirical material. The empirical material is based on thirteen semi-structured interviews with individuals involved in the tramp shipping industry from different organizations. This thesis demonstrates that the workers perceptions are heavily influenced by the shipping industry’s culture, and its survival is dependent on the industry finding workers with similar traits to ensure person-environment fit. The individuals management of 24/7 work availability seems to be determined by their professional goals, job identification, age, and experiences. In a society where unsustainable constant connectivity and availability seem to be of the essence, boundary management is raised as the main suggestion to establish work-life balance. In the long-run, this is found to benefit both employer and employee. Key words: 24/7 work availability; boundaries; work-life balance; work-life conflict; tramp shipping. (Less)
Novel histogram-weighted cortical thickness networks and a multi-scale analysis of predictive power in Alzheimer's disease

Network analysis based on anatomical covariance (cortical thickness) has been gaining increasing popularity in the last decade. However, there has not been a systematic study of the impact of nodal sizes and edge definitions on predictive performance among various network studies. In order to obtain a clear understanding of relative performance, there is a need for systematic comparison. In this study, we present a histogram-based approach to construct weighted networks that enables a comparison across vastly different methods of network analysis. We design several weighted networks based on cortical thickness and perform a robust evaluation and comparison of their predictive power. We present several interesting insights obtained.
Time Out of Joint : Attractors in AsynchronousRandom Boolean

Random Boolean networks (RBNs) are complex systems composed of many simple components which have been much analysed and shown to have many robust generic properties. Some synchronous versions have been innuential as highly abstract models of speciic biological systems, but for many biological phenomena asynchronous versions are more plausible models. Though asyn-chronous RBNs are indeterministic they can be shown to have generic properties that are simpler than, and very diierent from, the synchronous versions. These properties are demonstrated for the rst time here through computer simulation and through analysis.
Towards the automated generation of term-weighting schemes for text categorization

This paper describes ongoing research on the use of genetic programming to learn term-weighting schemes to be used for text classification. A term-weighting scheme (TWS) determines the way in which documents are represented before applying a text classification model. We propose a genetic program that aims at learning an effective TWS that can improve the performance in text classification. We report preliminary experimental results that give evidence of the validity of the proposal.
Radio Resource Allocation and Packet Scheduling Strategies for Single-Cell OFDMA Packet Networks

Radio resource allocation and packet scheduling schemes are expected to play a key role in the overall performance of OFDMA-based wireless networks. Inevitably, efficient resource allocation strategies have to exploit information laying in different OSI layers, allowing for a cross-layer design. In this work we evaluate current static resource allocation schemes (PHY layer) and extend them to incorporate MAC layer information. Furthermore, we enhance current schemes with SNR scheduling in time-domain, achieving near optimum system performance. The evaluation is based on our joint MAC-PHY layer system model. Scheme's performance is evaluated in terms of average throughput-delay through simulations.
Improving Student Interpersonal Skills and Social Growth in Diverse Learning Communities through Teamwork.

This action research project sought to improve the social skills of targeted first-, third-, and fourth-grade students. Students demonstrated an inability to collaborate with others, a disregard for the feelings and opinions of others, a lack of responsibility, excessive noise, incomplete assignments, unnecessary physical contact, inappropriate language, and a general disregard for classroom rules. Implemented interventions were: physical rearrangement of the classroom, direct instruction of social skills, role playing, use of community circles, establishment of rules, increased interaction within groups, and reflection. Post-intervention data indicated an increase in student use of the targeted social skills. Slight gains were observed in student collaboration and cooperative learning strategies. A decrease in student behavioral referrals signified a decline in inappropriate student behaviors in two of the three targeted schools. (Four appendices include student survey forms. Contains 91 references.) (Author/EV) Reproductions supplied by EDRS are the best that can be made from the original document. U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) ). This document has been reproduced as received from the person or organization 1-1 kr) originating it. Minor changes have been made to improve reproduction quality. 71Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. IMPROVING STUDENT INTERPERSONAL SKILLS AND SOCIAL GROWTH IN DIVERSE LEARNING COMMUNITIES THROUGH TEAMWORK Beth Bearbower Rhonda Mitchell K. Susie Summers An Action Research Project Submitted to the Graduate Faculty of the School of Education in Partial Fulfillment of the Requirements for the Degree of Master of Arts in Teaching and Leadership Saint Xavier University & Sky Light Field-Based Masters Program
Using Feature Models for Developing Self-Configuring Smart Homes

Increasingly, Smart Homes should dynamically reconfigure their services at run-time in response to changing conditions in the user actions, and in the surrounding physical environment. Considering the high heterogeneity of technologies and user requirements involved in Smart Homes, these systems become difficult to adjust to the specific user needs. This paper introduces an approach to build selfconfiguring Smart Homes using Features models. We apply Feature modelling to specify the different ways in which the system can evolve from an abstract perspective. We show an infrastructure for transforming these Feature Models to an executable Reconfiguration Plan. In this way, the entire development process is taken into account. Since the models forming the basis for reconfiguration are available at design time, we are able to check the validity of configurations according to context conditions.
Edinburgh Research Explorer Recovery in Scotland

‘Recovery’ has become a key element in Scottish mental health policy and practice, despite continuing uncertainty over just what is meant by ‘recovery’. This paper draws on social movement theory to explore the processes underlying the growth of recovery in Scotland. Based on documentary analysis and semi-structured interviews with key actors, it looks at the emergence of a ‘recovery movement’ in Scotland, and in particular at how that movement articulated a ‘recovery frame’ that subsequently came to inform policy and practice. It then reflects on the dilemmas posed by this success, as the recovery movement expanded to intersect with state agencies, and the recovery frame was adapted to accommodate the needs of government policy. It concludes that the future of the recovery movement in Scotland will depend on its ability to maintain a sufficiently broad and inclusive framing of recovery even as it becomes associated with specific policies and practice. respondents occupy and represent. Consequently, our designations provide no than an approximate, if occasionally suggestive guide to the various interests represented by our respondents. Given the impossibility of specifying in advance any hard-and-fast classification of our interviewees, all of the interviews followed the same basic schedule of questions, with follow-up questions being determined by the interviewees’ initial responses.
Language detection in audio content analysis

Experiments have shown that Language Identification systems for telephonic speech using shifted delta cepstra as the feature set and Gaussian mixture models as the backend, offers superior performance than other competing techniques. This paper aims to address the task of Language Identification for audio signals. The abundance of digital music from the Internet calls for a reliable real-time system for analyzing and properly categorizing them. Previous research has mainly focused on categorizing audio files into appropriate genres; however genre types vary with language. This paper proposes a systematic audio content analysis strategy by initially detecting whether an audio file has any vocals present in it and, if present, then detecting the language of the song. Given the language of the song, genre detection becomes a closed set classification problem.
Changes in the bacterial community structure and diversity during bamboo retting.

Microbial retting is a critical step in obtaining fiber bundles from bamboo culm using indigenous microorganisms. A cultivation-independent technique for monitoring the changes in bacteria community during bamboo retting was applied in this work. This technique involves genetic profiling of PCR-amplified small-subunit rRNA and the single-strand conformation polymorphism (SSCP) gel analysis of the PCR-amplified 16S rDNA fragments. The study revealed that both the structure and the diversity of investigated communities varied with the incubation periods and sample locations. The bacteria bands from SCCP gel profiles related to Bacillus sp. decreased in intensity, and Phaeospirillum sp. and Azospirillum brasilense completely disappeared during the 4(th) and 5(th) month of incubation, while the bands related to the Sphingomonas japonica, Alphaproteobacterium Ellin335 and Microbacterium sp. increased. The bands closely related to Sphingomonads, Brevundimonas brasilense, Pseudoclavibacter sp. , Agrococcus jenensis and Oxalophagus oxalicus remained dominant during the whole incubation period. This study showed that the use of PCR assay targeting 16S rRNA and SCCP profiling provided valuable information on monitoring the bacteria dynamic changes occurring in the bacteria community during bamboo retting, which is crucial for controlling the quality of the retting process and improving the retting efficiency, and thus benefits for fiber recovery.
Meaning Matters

The paper reviews the conceptual foundations of advertising polysemy—the occurrence of different interpretations for the same advertising message. We provide a cross-disciplinary perspective on advertising polysemy, with examples from research and practice, to explain the conditions that lead to the emergence of multiple interpretations for the same message. We review what we call purposeful polysemy as strategic ambiguity and present a framework of advertising polysemy. Propositions for research are provided, and implications for studying and understanding polysemy's prevalence in advertising are discussed. The concept of purposeful polysemy—advertising polysemy emerging as a consequence of a firm's strategic efforts—is increasingly relevant to both academics and practitioners.
Theory of Modules

Because large-scale software development is a struggle against internal program complexity, the modules into which programs are divided play a central role in software engineering. A module encapsulating a data type allows the programmer to ignore both the details of its operations, and of its value representations. It is a primary strength of program proving that as modules divide a program, making it easier to understand, so do they divide its proof. Each module can be verified in isolation, then its internal details ignored in a proof of its use. This paper describes proofs of module abstractions based on functional semantics, and contrasts this with the Alphard formalism based on Hoare logic.
DEMOGRAPHIC AND CLINICAL CHARACTERISTICS OF CONSISTENT AND INCONSISTENT LONGITUDINAL REPORTERS OF LIFETIME SUICIDE ATTEMPTS IN ADOLESCENCE THROUGH YOUNG ADULTHOOD

Within the context of the recent release of the 2012 National Suicide Prevention Strategy, and as the third leading cause of death for individuals 10‐ to 24‐years‐old, suicide prevention is a national priority. A consistently reported and robust risk factor for suicide is a prior suicide attempt; however few studies have investigated the consistency of self‐reported lifetime suicide attempts. The goal of this study is to describe the prevalence and characteristics of inconsistent reporting of suicide attempt in a longitudinal cohort of participants annually assessed in 12 waves of data collected from middle school (age 12) to early adulthood (age 22).