Miracle-dz/UniFAR-FTUs huggingface dataset:
Inactivation of a Testis-specific Lis1 Transcript in Mice Prevents Spermatid Differentiation and Causes Male Infertility*

Lis1 protein is the non-catalytic component of platelet-activating factor acetylhydrolase 1b (PAF-AH 1B) and associated with microtubular structures. Hemizygous mutations of the LIS1 gene cause type I lissencephaly, a brain abnormality with developmental defects of neuronal migration. Lis1 is also expressed in testis, but its function there has not been determined. We have generated a mouse mutant (LIS1GT/GT) by gene trap integration leading to selective disruption of a Lis1 splicing variant in testis. Homozygous mutant males are infertile with no other apparent phenotype. We demonstrate that Lis1 is predominantly expressed in spermatids, and spermiogenesis is blocked when Lis1 is absent. Mutant spermatids fail to form correct acrosomes and nuclei appear distorted in size and shape. The tissue architecture in mutant testis appears severely disturbed displaying collapsed seminiferous tubules, mislocated germ cells, and increased apoptosis. These results provide evidence for an essential and hitherto uncharacterized role of the Lis1 protein in spermatogenesis, particularly in the differentiation of spermatids into spermatozoa.
Screening for chloroquine maculopathy in populations with uncertain reliability in outcomes of automatic visual field testing

Purpose: The purpose of this study was to compare screening methods for the early detection of maculopathy in patients treated with chloroquine (CQ) or hydroxychloroquine (HCQ) and to identify the risk factors for the development of toxic maculopathy. Methods: We performed a prospective study of all 217 patients taking CQ and/or HCQ and seen in our center between July 2011 and December 2013. All subjects underwent a complete ocular examination, as well as spectral domain optical coherence tomography (SD-OCT), fundus autofluorescence (FAF), and 10-2 Humphrey visual field (10-2 HVF). Results: The median age of patients was 51 years, median CQ/HCQ duration was 40 months, and median cumulative dose was 180 g. The prevalence of at least two abnormal tests was 7.4% (16/217). SD-OCT had the highest sensitivity, specificity, predictive values and accuracy while 10-2 HVF showed in 30% of nonreliable results and had the lowest specificity and positive predictive value. In multivariate analysis, an age of older than 60 years (P = 0.002), CQ duration of more than 5 years (P < 0.001), and CQ dose more than 3 mg/kg/day (P = 0.005) were associated with toxicity. Conclusions: In patients with unreliable outcomes of 10-2 HVF testing, SD-OCT in combination with FAF might represent a suitable alternative screening tool for toxic maculopathy.
Family: the challenge of prevention of drug use.

CONTENTS OF THE BOOK From the original research for the knowledge and evaluation of family prevention programs in the five European countries we decided to enrich our study with different contributions in this field. Thus, some researchers have contributed to the organization of this book, having participated in the elaboration of some chapters. In the first chapter a description and a socio-historical framework of the evolution of the prevention concept are made. Throughout the years we have been learning how to better define and interpret the true meaning of drug use primary prevention. From the information to prevention as science a long way has been covered in a short period of time. In the second chapter we mention and describe all the existing theoretical models. We remind you that only some time ago preventive interventions were performed according to the idea that information on drugs was necessary and sufficient to avoid youngsters using them. The prevention models give support and frame the different preventive interventions, justifying the options made. In the third chapter, and based on the wider and deeper knowledge on protective and risk factors, we present the prevention strategies more often used. We also describe the preventive programs mentioned in the three areas we highlighted: Family – School – Community. In Chapter 4, after the definition of our research aims, we present the grids used in the reading of the selected projects in the five countries. They are two distinct grids that help us to understand the different levels of preventive intervention: a) one, which we call Level I grid, that refers to all the preventive interventions socalled occasional; b) Level II grid, which mentions long time actions with a theoretical framework. We also present and discuss the obtained data. In the fifth chapter we present the contribution of three of our researchers, approaching several themes. Professor Boyer, bearing in mind the results of IREFREA’s research (Mendes & Relvas et al, 1999) develops the issue of religion/spirituality as a protective factor. Dr. Susanna Pietralunga describes the preventive activities in family context and their evolution, from the Italian reality. Professor Paula Relvas approaches the family life cycle: a framework for primary prevention of drug use. In Chapter 7 the conclusions of our work are presented and a series of orientations are suggested, taking into account future preventive activities in family context.
Bayesian Model Averaging and Forecasting

This paper focuses on the problem of variable selection in linear regression models. I briefly review the method of Bayesian model averaging, which has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. Some of the literature is discussed with particular emphasis on forecasting in economics. The role of the prior assumptions in these procedures is highlighted, and some recommendations for applied users are given.
Abnormal electrical brain responses to pitch in congenital amusia

Congenital amusia is a lifelong disability that prevents afflicted individuals from enjoying music as ordinary people do. The deficit is limited to music and cannot be explained by prior brain lesion, hearing loss, or any cognitive or socioaffective disturbance. Recent behavioral results suggest that this disorder is critically dependent on fine‐grained pitch discrimination. Here, we present novel electrophysiological evidence that this disorder can be traced down to a right‐lateralized N2‐P3 response elicited by pitch changes. This abnormal brain response begins as early as 200 milliseconds after tone onset and may serve as a marker of an anomaly in music acquisition. Ann Neurol 2005;58:478–482
Introduction : The Third International Workshop on Epigenetic Robotics

This paper summarizes the paper and poster contributions to the Third International Workshop on Epigenetic Robotics. The focus of this workshop is on the cross-disciplinary interaction of developmental psychology and robotics. Namely, the general goal in this area is to create robotic models of the psychological development of various behaviors. The term “epigenetic” is used in much the same sense as the term “developmental” and while we could call our topic “developmental robotics”, developmental robotics can be seen as having a broader interdisciplinary emphasis. Our focus in this workshop is on the interaction of developmental psychology and robotics and we use the phrase “epigenetic robotics” to capture this focus.
Pitch estimation of noisy speech signals using EMD-fourier based hybrid algorithm

This paper focuses on a pitch estimation method of noisy speech signal using the combination of empirical mode decomposition (EMD) and discrete Fourier transform (DFT). The noisy speech signal is filtered within the range of fundamental frequency. Normalized autocorrelation function (NACF) is computed from the pre-filtered noisy speech signal. The NACF is decomposed by EMD to generate a finite number of band limited signal called Intrinsic Mode Function (IMF). DFT is applied to NACF to determine the dominant frequency of the analyzing speech frame. The IMF with fundamental period closest to that of the dominant frequency is selected as the target IMF containing the fundamental period. The performance of the proposed pitch estimation method is compared in terms of gross pitch error (GPE) with the recent algorithms. The experimental results show that the proposed one performs better for noisy and clean speech signals.
A Study of Second Language Identity and Motivation among Undergraduates in Sri Lankan Universities

Measuring the motivational elements of students towards learning English and demarcating the salient elements of their motivation is crucial as this information can be used to make the English learning experience more effective. The motivation of Sri Lankan undergraduate students towards learning English is generally rated as quite low. Therefore, measuring the motivational elements pertaining to their L2 learning and finding the salient features would be essential to enhancing their learning experience within the university system. The study of motivation in SLA has taken a different direction from the socioeducational method by R. Gardner and R. N. Lalonde (1985) which heavily focused on the concept of integrativeness as the main motivating element in SLA. As this was later found to be inadequate in explaining the current learning experience of ESL or EFL in a more globalized and international context, additional elements were incorporated to make the measurement more meaningful Dornyei (2009a) conceptualized the L2 self-system which is conditioned to meet the current status of SLA. The L2 self-system incorporates integrativeness and also uses the concept of the ‘ideal L2 self’, corresponding with motivation as the drive for the ultimate goal of a competent L2 self. It has been validated a number of times in both EFL and ESL contexts as Japan, China, Iran and Pakistan. This system has not been so far implemented to study the L2 motivation within the ESL context in Sri Lanka. This study presents the motivational elements present among the undergraduates studying in government funded universities in Sri Lanka. 3 An online questionnaire developed for this by integrating subscales from previous studies from Tagushi, Magid, and Papi (2009) and Ryan (2009) with the addition of a few contextual questions, was distributed among Sri Lankan undergraduate students. After testing the completed questionnaires for reliability the salient motivating factors for different demographics were extracted and the correlations between salient factors were studied. The study shows a strong correlation between the ‘ideal L2 self’ and the ‘ought to L2 self’ which is an indication of strong motivation towards learning the L2. The findings also indicates that Sri Lankan undergraduate students are strongly influenced by promotional instrumentality and preventional instrumentality, denoted by the strong correlation between the two subscales. Their motivation is geared towards learning English for the personal extrinsic goals such as employment opportunities and graduate studies. While their levels of motivation was generally high the need to pedagogically assist their requirements of promotional instrumentality was seen as a crux to the pedagogical implications. A significant difference between the demographics in the study was not observed.
A Study onControl of Myoelectric Prosthetic Hand Based on Surface EMG Pattern Recognition

As robots come closer to humans, an efficient human–robot control interface is an utmost necessity. In this paper, electromyographic (EMG) signals from the muscles of the human upper limb are used as the control interface between the user and a robot arm. An accurate and computationally efficient means of classifying surface myoelectric signal patterns has been the subject of considerable research effort in recent years. This paper presents a method of using SVM for classification, and examines overlappedsegmentation toimprove controller performance. In order to improve the classification an Artificial -euro-Fuzzy inference system (A-FIS) has been used by the researchers. Secondly, some recent applications of myoelectric control of human arm prosthesis by using machine learning algorithms are compared. Finally, characterization of EMG for human arm prosthesis has been discussed.
Protein structure prediction servers at University College London

A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction. These servers are available from our software home page at .
Programming by Examples - and its applications in Data Wrangling

Programming by Examples (PBE) has the potential to revolutionize enduser programming by enabling end users, most of whom are non-programmers, to create scripts for automating repetitive tasks. PBE involves synthesizing intended programs in an underlying domain-specific language (DSL) from example based specifications (Ispec). We formalize the notion of Ispec and discuss some principles behind designing useful DSLs for synthesis. A key technical challenge in PBE is to search for programs that are consistent with the Ispec provided by the user. We present a divide-and-conquer based search paradigm that leverages deductive rules and version space algebras for manipulating sets of programs. Another technical challenge in PBE is to resolve the ambiguity that is inherent in the Ispec. We show how machine learning based ranking techniques can be used to predict an intended program within a set of programs that are consistent with the Ispec. We also present some user interaction models including program navigation and active-learning based conversational clarification that communicate actionable information to the user to help resolve ambiguity in the Ispec. The above-mentioned concepts are illustrated using practical PBE systems for data wrangling (including FlashFill, FlashExtract, FlashRelate), several of which have already been deployed in the real world.
DEMOCRATIZATION, INSTITUTIONAL REFORM, AND POLITICAL CONFLICT: Evaluating Alternative Explanations of Electoral Reform in Costa Rica

This article seeks to identify the conditions that prompt executives and legislators to reform electoral laws, especially those with far-ranging and redistributive consequences. It pursues this objective by evaluating the ability of alternative models of political behavior and institutional reform to account for the promulgation of the 1946 Electoral Code in Costa Rica, one of the oldest and most stable democracies in Latin America and in the world, more generally. The 1946 Electoral Code, among other reasons, merits study because its enactment threatened to loosen the governing party’s grip on the presidency in the 1948 elections and promised to eradicate—if not reduce—its majority in Congress in the 1946 midterm as well as 1948 elections. A central conclusion of this article is that, contrary to some recent critiques of strategic models of institutional change, the inability of legislative seat maximization or career protection models to explain the promulgation of the 1946 Electoral Code does not mean that rational choice theories cannot account for the reform of electoral laws. By developing a third model that focuses upon the interest incumbents have in promoting political stability, this paper shows that the creation of institutions that promise to punish key sectors of the ruling bloc is prompted, in part, by the threat of a civil war that at least some incumbents fear losing. The establishment of institutions with such redistributive repercussions also stems from the willingness of some within the ruling bloc to fashion a new alliance with those in the opposition who also share an interest in political stability.
Alzheimer’s disease: biological aspects, therapeutic perspectives and diagnostic tools

Alzheimer’s disease (AD) is the most common form of dementia among older people. Dementia is an irreversible brain disorder that seriously affects a person’s ability to carry out daily activities. It is characterized by loss of cognitive functioning and behavioral abilities, to such an extent that it interferes with the daily life and activities of the affected patients. Although it is still unknown how the disease process begins, it seems that brain damage starts a decade or more before problems become evident. Scientific data seem to indicate that changes in the generation or the degradation of the amyloid-b peptide (Aβ) lead to the formation of aggregated structures that are the triggering molecular events in the pathogenic cascade of AD. This review summarizes some characteristic features of Aβ misfolding and aggregation and how cell damage and death mechanisms are induced by these supramolecular and toxic structures. Further, some interventions for the early diagnosis of AD are described and in the last part the potential therapeutic strategies adoptable to slow down, or better block, the progression of the pathology are reported.
Raga Verification in Carnatic Music Using Longest Common Segment Set

There are at least 100 r¯agas that are regularly performed in Carnatic music concerts. The audience determines the identity of r¯agas within a few seconds of listening to an item. Most of the audience consists of people who are only avid listeners and not performers. In this paper, an attempt is made to mimic the listener. A r¯aga veriﬁcation framework is therefore suggested. The r¯aga veriﬁcation system assumes that a speciﬁc r¯aga is claimed based on similarity of movements and motivic patterns. The system then checks whether this claimed r¯aga is correct. For every r¯aga , a set of cohorts are chosen. A r¯aga and its cohorts are represented using pallavi lines of compositions. A novel approach for matching, called Longest Common Segment Set (LCSS), is introduced. The LCSS scores for a r¯aga are then normalized with respect to its cohorts in two different ways. The resulting systems and a baseline system are compared for two partitionings of a dataset. A dataset of 30 r¯agas from Charsur Foundation 1 is used for analysis. An equal error rate (EER) of 12% is obtained.
Period2 Deficiency Blunts Hypoxia-Induced Mobilization and Function of Endothelial Progenitor Cells

Background In the clinic, variations in circadian rhythm are evident in patients with cardiovascular disease, and the risk of cardiovascular events increases when rhythms are disrupted. In this study, we focused on the role of the circadian gene period2 (per2) in mobilization and function of endothelial progenitor cells (EPCs) in vitro and in vivo after myocardial infarction (MI) in mice. Methods and Results MI was produced by surgical ligation of the left anterior descending coronary artery in mice with and without per2 deficiency. Trans-thoracic echocardiography was used to evaluate cardiac function in mice. Per2−/− mice with MI showed decreased cardiac function and increased infarct size. The number of CD34+ cells and capillary density were decreased in the myocardium of per2−/− mice on immunohistochemistry. Flow cytometry revealed decreased number of circulating EPCs in per2−/− mice after MI. In vitro, per2−/− EPCs showed decreased migration and tube formation capacity under hypoxia. Western blot analysis revealed inhibited activation of extracellular signal-regulated kinase and Akt signaling in the bone marrow of per2−/− mice and inhibited PI3K/Akt expression in per2−/− EPCs under hypoxia. Conclusions Per2 modulates EPC mobilization and function after MI, which is important to recovery after MI in mice.
Recommending relevant projects via user behaviour: an exploratory study on github

Social coding sites (e.g., Github) provide various features like Forking and Sending Pull-requests to support crowd-based software engineering. When using these features, a large amount of user behavior data is recorded. User behavior data can reflect developers preferences and interests in software development activities. Online service providers in many fields have been using user behavior data to discover user preferences and interests to achieve various purposes. In the field of software engineering however, there has been few studies in mining large amount of user behavior data. Our goal is to design an approach based on user behavior data, to recommend relevant open source projects to developers, which can be helpful in activities like searching for the right open source solutions to quickly build prototypes. In this paper, we explore the possibilities of such a method by conducting a set of experiments on selected data sets from Github. We find it a promising direction in mining projects' relevance from user behavior data. Our study also obtain some important issues that is worth considering in this method.
A Shallow High-Order Parametric Approach to Data Visualization and Compression

Explicit high-order feature interactions efficiently capture essential structural knowledge about the data of interest and have been used for constructing generative models. We present a supervised discriminative High-Order Parametric Embedding (HOPE) approach to data visualization and compression. Compared to deep embedding models with complicated deep architectures, HOPE generates more effective high-order feature mapping through an embarrassingly simple shallow model. Furthermore, two approaches to generating a small number of exemplars conveying high-order interactions to represent large-scale data sets are proposed. These exemplars in combination with the feature mapping learned by HOPE effectively capture essential data variations. Moreover, through HOPE, these exemplars are employed to increase the computational efficiency of kNN classification for fast information retrieval by thousands of times. For classification in two-dimensional embedding space on MNIST and USPS datasets, our shallow method HOPE with simple Sigmoid transformations significantly outperforms state-of-the-art supervised deep embedding models based on deep neural networks, and even achieved historically low test error rate of 0.65% in two-dimensional space on MNIST, which demonstrates the representational efficiency and power of supervised shallow models with high-order feature interactions.
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Despite their increasing importance as data retrieval tools, most Information Retrieval (IR) systems are deficient in precision and recall. Lack of disambiguation power is one reason for the poor performance of these systems. Correctly disambiguating and expanding a query with intended synonyms before retrieval may improve the performance. We use the local context of a word to identify its sense. In our case, the local context of a word is the ordered list of words from the closest content word on each side of the target word up to the target word which is expressed as a placeholder. For example, in “the jury had been charged to investigate reports of irregularities in the primary. ” the right-side local context of “charged” is “X to investigate”. Due to this definition of context, words used in the same context (called selectors) most of the time have related senses. So, DQ RFFXUUHQFH RI D ZRUG DQG LWV V\QRQ\P EHORQJ WR WKH VDPH VHQVH LI WKH\ KDYH VLPLODU ORFDO FRQWH[WV. We use WordNet (Miller 1990) and selectors extracted from Associated Press articles (Yuret 1998) for disambiguation. Selectors help us find the right WordNet synset (synonyms of only one sense) of a word in its context. Figure 1 shows the process of extracting selectors of the word FKDUJH in the sentence fragment “the jury had been charged to investigate reports of irregularities in the primary. ”. The final tally of selectors for this fragment is shown in Table 1. Figure 2 shows the same process for the sentence fragment “the company was charged for towing the car. ”. The final tally of selectors for this fragment is shown in Table 2. Selector Frequency Appointed 52 Assigned 28 Established 20 Hired 16 . 7DEOH : )LQDO WDOO\ RI VHOHFWRU IUHTXHQFLHV IRU )LJXUH