Miracle-dz/UniFAR-FTUs huggingface dataset:
A semantically confidence-weighted ITG induction algorithm

We propose a new algorithm to induce inversion transduction grammars, in which a crosslingual semantic frame based objective function is injected as confidence weighting in the early stages of statistical machine translation training. Unlike recent work on improving translation adequacy that uses a monolingual semantic frame based objective function to drive the tuning of loglinear mixture weights in the late stages of statistical machine translation training, our bilingual approach incorporates the semantic objective during the actual learning of the translation model’s structure. Our approach assigns higher confidence to training examples in which the semantic frames in the input language more closely match the semantic frames of the output language, as predicted automatically by XMEANT, the crosslingual semantic frame based machine translation evaluation metric. We chose to apply this approach to induce inversion transduction grammars (ITGs), since ITG alignments prune a large majority of the space of possible alignments, while at the same time empirically fully covering all the crosslingual semantic frame alternations of the type we are using for confidence weighting. Results show that boosting semantically compatible training examples in ITG induction improves Copyright c © by the paper’s authors. Copying permitted for private and academic purposes. In Proceedings of 3rd International Workshop on Semantic Machine Learning (SML 2016), 10th July 2016, New York City, NY, USA. the translation performance compared to either traditional GIZA++ alignment or conventional ITG alignment based approaches for phrase based statistical machine translation.
Loss of Inhibitory Neuron AMPA Receptors Contributes to Ataxia and Epilepsy in Stargazer Mice

Stargazer mice are characterized by ataxia and seizures, which resemble the human disorder absence epilepsy. Stargazin, the protein mutated in stargazer mice, promotes the expression and function of neuronal AMPA receptors (AMPARs). However, it is unclear how decreased expression of excitatory AMPARs generates stargazer seizures, given that seizures often result from increased neuronal excitability. Additionally, although stargazer ataxia has been attributed to loss of AMPARs from cerebellar granule cells, other cerebellar neurons have not been examined. To examine the role of AMPAR dysfunction in these behavioral phenotypes, electrophysiological recordings were used to probe AMPAR regulation in relevant brain regions. We found that both cerebellar Purkinje cells and inhibitory thalamic reticular nucleus neurons have strongly reduced synaptic AMPAR function in stargazer mice. Together, our data suggest that impaired AMPAR regulation in multiple neuron populations may contribute to the behavioral phenotypes of absence seizures and ataxia seen in stargazer mice and imply that an understanding of human genetic disorders will require knowledge of both the genes that are mutated as well as their precise cellular expression pattern.
Anomalous diffusion and dynamical correlation between the side chains and the main chain of proteins in their native state

Structural fluctuations of a protein are essential for a protein to function and fold. By using molecular dynamics (MD) simulations of the model α/β protein VA3 in its native state, the coupling between the main-chain (MC) motions [represented by coarse-grained dihedral angles (CGDAs) γn based on four successive Cα atoms (n - 1, n, n + 1, n + 2) along the amino acid sequence] and its side-chain (SC) motions [represented by CGDAs δn formed by the virtual bond joining two consecutive Cα atoms (n, n + 1) and the bonds joining these Cα atoms to their respective Cβ atoms] was analyzed. The motions of SCs (δn) and MC (γn) over time occur on similar free-energy profiles and were found to be subdiffusive. The fluctuations of the SCs (δn) and those of the MC (γn) are generally poorly correlated on a ps time-scale with a correlation increasing with time to reach a maximum value at about 10 ns. This maximum value is close to the correlation between the δn(t) and γn(t) time-series extracted from the entire duration of the MD runs (400 ns) and varies significantly along the amino acid sequence. High correlations between the SC and MC motions [δ(t) and γ(t) time-series] were found only in flexible regions of the protein for a few residues which contribute the most to the slowest collective modes of the molecule. These results are a possible indication of the role of the flexible regions of proteins for the biological function and folding.
Picture-based vocabulary assessment versus parental questionnaires: A cross-linguistic study of bilingual assessment methods

Purpose: As a contribution to the endeavour of developing appropriate tools for bilingual language assessment, this paper investigates the concurrence between two new tools from the recent COST Action IS0804 (Bi-SLI), and the differences between children across two different migrant communities. Approach: Two new tools from the battery Language Impairment Testing in Multilingual Settings (LITMUS) were used: the direct assessment tool Cross-linguistic Lexical Tasks (CLT) and the reporting instrument Parents of Bilingual Children Questionnaire (PaBiQ), which offers an indirect measure of overall language skills. Data: The participants were 36 children (4;2–6;6) of Polish immigrants to Norway or the UK. Correlations were investigated with Kendall’s rank correlation, and comparisons carried out with Wilcoxon rank sum tests. Findings: The results from the two tools correlated. The CLT results were higher in the minority language (Polish) than in the majority language, with no difference between the groups. Still, the parents in the UK judged their children as less proficient in Polish than those in Norway did. Two different accounts for this incongruity are discussed. Firstly, parents in the UK may set higher benchmarks for their children’s minority language skills than the parents in Norway. Alternative accounts of this interpretation related to differences in the parents’ socio-economic background, minority language proficiency or language attitudes are discussed. Secondly, parental report may indicate early stages of attrition of the minority language among the children in the UK that the direct lexical assessment tool may not be sensitive enough to uncover. Originality: The study used two new tools designed for multilingual children to compare two groups of children of a recent and growing immigration group, whose language development is currently underinvestigated. Implications: The findings underscore the complexity of assessing bilingual children’s full language competence. The cross-cultural differences documented call for further longitudinal research comparing immigrant children from different language backgrounds.
The Association of Posttraumatic Stress Disorder Risk With Help-Seeking Behavior: A Cross-Sectional Study of Earthquake and Tsunami Survivors in Japan

The Great East Japan Earthquake in March 2011 and subsequent tsunami affected the northeastern coast of Japan. We investigated the association between the risk of posttraumatic stress disorder (PTSD) and help-seeking behaviors of survivors in a landlocked city in Japan’s Tohoku area at 1 year after this disaster. The participants were 902 residents of Ichinoseki City and 218 evacuees from coastal areas to the city. We used sociodemographic characteristics, the Trauma Screening Questionnaire with a score ≥6 defined as predicted PTSD, and the General Help-Seeking Questionnaire. We examined the whole sample and the stratified samples between the Ichinoseki residents and the evacuees. Missing values were complemented using a multiple imputation method after a missing-value analysis. Data from the final sample of 1,101 respondents were analyzed using logistic regression and sensitivity analyses. Compared with the Ichinoseki residents, the evacuees were older, showed higher Trauma Screening Questionnaire scores, and had fewer house occupants. However, the prevalence of predicted PTSD was not different between the 2 groups. In the whole sample and among the Ichinoseki residents, predicted PTSD was associated with an active help-seeking behavior, possibly from mental health professionals. In the evacuees, predicted PTSD was not associated with any specific help-seeking behavior. Although survivors with predicted PTSD in the whole sample and among the Ichinoseki residents showed an active help-seeking behavior, the evacuees with predicted PTSD showed little active help-seeking behavior. Traumatized survivors’ help-seeking activity may also vary according to the type of disaster and/or evacuation situation.
The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria.

BACKGROUND Polycystic ovary syndrome (PCOS) is considered to be the most common endocrine disorder in women of reproductive age, yet debate over appropriate diagnostic criteria and design limitations with sampling methodology have left some doubt as to the actual prevalence in the community. The objective of this study was to create a representative prevalence estimate of PCOS in the community under the National Institutes of Health (NIH) criteria and the more recent Rotterdam consensus criteria and Androgen Excess Society (AES) criteria. METHODS A retrospective birth cohort study was carried out in which 728 women born during 1973-1975 in a single maternity hospital were traced and interviewed in adulthood (age = 27-34 year; n = 728). Symptoms of PCOS (hyperandrogenism, menstrual dysfunction and polycystic ovaries) were identified by examination and the presence of polycystic ovaries in those that did not consent to the ultrasound were imputed. RESULTS The estimated prevalence of PCOS in this birth cohort using the NIH criteria was 8.7 +/- 2.0% (with no need for imputation). Under the Rotterdam criteria, the prevalence was 11.9 +/- 2.4% which increased to 17.8 +/- 2.8% when imputed data were included. Under the AES recommendations, PCOS prevalence was 10.2 +/- 2.2%, and 12.0 +/- 2.4% with the imputed data. Of the women with PCOS, 68-69% did not have a pre-existing diagnosis. CONCLUSIONS The Rotterdam and AES prevalence estimates were up to twice that obtained with the NIH criteria in this, as well other prevalence studies. In addition, this study also draws attention to the issue of many women with PCOS in the community remaining undiagnosed.
Physics-based sound synthesis and control: crushing, walking and running by crumpling sounds

Three types of ecological events (crushing, walking and running) have been considered. Their acoustic properties have been modeled following the physics-based approach. Starting from an existing physically-based impact model, we have superimposed to it the dynamic and temporal stochastic characteristics governing crushing events. The resulting model has been finally triggered by control rules defining walking and running time patterns. This bottom-up design strategy was made possible because the sound synthesis and sound control models could be directly connected each other via a common switchboard of driving and control parameters. The existence of a common interface specification for all the models follows from the application of physics-based modeling, and translates in major advantages when those models are implemented as independent, self-contained blocks and procedures connected together in real-time inside a software like pd.
Robustness, Risk, and Regularization in Support Vector Machines

We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in protection to noise and control overfitting, but without being overly conservative. Our first formulation allows the noise between different samples to be correlated. We show that the standard norm-regularized support vector machine classifier is a solution to a special case of our first formulation, thus providing an explicit link between regularization and robustness in pattern classification. Our second formulation is based on a softer version of robust optimization called comprehensive robustness. We show that this formulation is equivalent to regularization by any arbitrary convex regularizer, thus extending our first equivalence result. Moreover, we explain how the connection of comprehensive robustness to convex risk-measures can be used to design risk-measure constrained classifiers with robustness to the input distribution. Our formulations result in convex optimization problems that can be easily solved. Finally, we provide some empirical results that show the promise of comprehensive robust classifiers.
Outreach Communication Strategy in Community Mobilisation for Reproductive Health Education in Niger State of Nigeria

Abstract This study looked into operational significance of outreach communication adopted in the community based reproductive health education project in Bida Emirate Council in Niger State, Nigeria. The outreach initiative became imperative given the limitations placed on traditional individual extension methods. Hence, the use of outreach communication that involves extending community services to reach a wider segment of the population collectively. This project being evaluated comprises community visitations and educational campaigns with folk musical performances, videocassette recorder shows, question and answer sessions and drama sketches. A sample of 288 residents from both urban and rural communities assessed the effectiveness of the outreach program in the study area. Findings from the study reveal that outreach programs mobilized, entertained and educated people on the issues raised on the project such as family planning, sexually transmitted diseases, safe motherhood and Acquired Immune Deficiency Syndrome. Residents from rural areas ranked the outreach highly in the area of social service. Outreach program strategy in various ways promoted participation in the program initiative such as dancing, listening, watching and questioning. It was hence recommended that outreach communication programs should be a virile component in all development programs, particularly, in rural areas where access to other forms of communication support is in short supply.
Data Mining of Inputs: Analysing Magnitude and Functional Measures

The problem of data encoding and feature selection for training back-propagation neural networks is well known. The basic principles are to avoid encrypting the underlying structure of the data, and to avoid using irrelevant inputs. This is not easy in the real world, where we often receive data which has been processed by at least one previous user. The data may contain too many instances of some class, and too few instances of other classes. Real data sets often include many irrelevant or redundant input fields. This paper examines the use of weight matrix analysis techniques and functional measures using two real (and hence noisy) data sets. The first part of this paper examines the use of the weight matrix of the trained neural network itself to determine which inputs are significant. A new technique is introduced and compared with two other techniques from the literature. We present our experience and results on some satellite data augmented by a terrain model. The task was to predict the forest supra-type based on the available information. A brute force technique eliminating randomly selected inputs was used to validate our approach. The second part of this paper examines the use of measures to determine the functional contribution of inputs to outputs. Inputs which include minor but unique information to the network are more significant than inputs with higher magnitude contribution but providing redundant information, which is also provided by another input. A comparison is made to sensitivity analysis, where the sensitivity of outputs to input perturbation is used as a measure of the significance of inputs. This paper presents a novel functional analysis of the weight matrix based on a technique developed for determining the behavioral significance of hidden neurons. This is compared with the application of the same technique to the training and test data. Finally, a novel aggregation technique is introduced.
Lidar Strip Adjustment with Automatically Reconstructed Roof Shapes

In recent years, the performance of lidar systems has steadily improved due to an increase in the achievable point density. The main error sources affecting the quality of lidar‐derived secondary products such as digital terrain models (DTMs) and digital surface models (DSMs) are the result of systematic errors coming from insufficient boresight calibration. The effects of boresight misalignments are visually recognised as discrepancies of the laser point clouds at selected objects (such as building roofs) in overlapping areas of neighbouring lidar strips. In this work, a strip adjustment method is presented that corrects the systematic errors of the laser point cloud using five strip parameters (three shifts plus two angular corrections for heading and roll). The strip adjustment procedure uses 2D and 3D tie elements and takes advantage of a new 3D measurement technique applied to building roofs. The strip adjustment method is applied to three different datasets, consisting of conventional first/last pulse and full‐waveform data. The results show that systematic discrepancies are typical for datasets that have already been processed by the flight companies. These errors can be reduced by more than 70% by applying the new strip adjustment approach. Preliminary investigations indicate that a higher laser point density and the inclusion of intensity and pulse width within full‐waveform lidar data lead to better results.
Effect of vagal cooling on the counterregulatory response to hypoglycemia induced by a low dose of insulin in the conscious dog.

We previously demonstrated, using a nerve-cooling technique, that the vagus nerves are not essential for the counterregulatory response to hypoglycemia caused by high levels of insulin. Because high insulin levels per se augment the central nervous system response to hypoglycemia, the question arises whether afferent nerve fibers traveling along the vagus nerves would play a role in the defense of hypoglycemia in the presence of a more moderate insulin level. To address this issue, we studied two groups of conscious 18-h-fasted dogs with cooling coils previously placed on both vagus nerves. Each study consisted of a 100-min equilibration period, a 40-min basal period, and a 150-min hypoglycemic period. Glucose was lowered using a glycogen phosphorylase inhibitor and a low dose of insulin infused into the portal vein (0.7 mU.kg(-1) min(-1)). The arterial plasma insulin level increased to 15 +/- 2 microU/ml and the plasma glucose level fell to a plateau of 57 +/- 3 mg/dl in both groups. The vagal cooling coils were perfused with a 37 degrees C (SHAM COOL; n = 7) or a -20 degrees C (COOL; n = 7) ethanol solution for the last 90 min of the study to block parasympathetic afferent fibers. Vagal cooling caused a marked increase in the heart rate and blocked the hypoglycemia-induced increase in the arterial pancreatic polypeptide level. The average increments in glucagon (pg/ml), epinephrine (pg/ml), norepinephrine (pg/ml), cortisol (microg/dl), glucose production (mg.kg(-1). min(-1)), and glycerol (micromol/l) in the SHAM COOL group were 53 +/- 9, 625 +/- 186, 131 +/- 48, 4.63 +/- 1.05, -0.79 +/- 0.24, and 101 +/- 18, respectively, and in the COOL group, the increments were 39 +/- 7, 837 +/- 235, 93 +/- 39, 6.28 +/- 1.03 (P < 0.05), -0.80 +/- 0.20, and 73 +/- 29, respectively. Based on these data, we conclude that, even in the absence of high insulin concentrations, afferent signaling via the vagus nerves is not required for a normal counterregulatory response to hypoglycemia.
Visualizing an Execution Trace as a Compact Sequence Diagram Using Dominance Algorithms

Visualizing an execution trace of an object-oriented sys-tem as sequence diagrams is effective to understand the behavior of the system. However, sequence diagrams extracted from an execution trace are too large for developers to inspect since a trace involves a large number of objects and method calls. To support developers to understand extracted sequence diagrams, it is necessary to remove the less important details of the diagrams. In this paper, we apply a dominance algorithm to a dynamic call graph among objects in order to detect and remove local objects contributing to internal behavior of dominator objects. The case study shows our approach automatically removed about 40 percent of the objects from execution traces on average.
An Approach to Declarative Programming Based on a Rewriting Logic

We propose an approach to declarative programming which integrates the functional and relational paradigms by taking possibly non-deterministic lazy functions as the fundamental notion. Classical equational logic does not supply a suitable semantics in a natural way. Therefore, we suggest to view programs as theories in a constructor-based conditional rewriting logic. We present proof calculi and a model theory for this logic, and we prove the existence of free term models which provide an adequate intended semantics for programs. We develop a sound and strongly complete lazy narrowing calculus, which is able to support sharing without the technical overhead of graph rewriting and to identify safe cases for eager variable elimination. Moreover, we give some illustrative programming examples, and we discuss the implementability of our approach.
Associations of Home and Classroom Environments with Head Start Children's Code-Related and Oral Language Skills

ABSTRACT This study used data from the Head Start Family and Child Experiences Survey (FACES) 2009 4-year-old cohort to examine associations among family characteristics, home and classroom environments, and the emergent literacy skills of Head Start children. Results from hierarchical linear models suggest that both family and classroom contexts play a unique and interactive role in supporting Head Start children's development of different sets of emergent literacy skills. Parental warmth was positively related to children's oral language skills (i.e., receptive and expressive vocabulary knowledge), and teachers' educational level and the quality of instructional support in the classroom were significantly associated with children's code-related skills (i.e., letter-name and letter-sound knowledge). Further, high-quality instructional support in the classroom buffered the negative influence of low maternal education on children's oral language skills. Interventions focusing on enhancing the quality of parent-child interactions, in addition to professional development for teachers designed to improve the quality of instructional support, may contribute to promoting the development of emergent literacy skills of young children from low-income families.