Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate Analysis of Anthropometric Traits Using Summary Statistics of Genome-Wide Association Studies from GIANT Consortium

Meta-analysis of single trait for multiple cohorts has been used for increasing statistical power in genome-wide association studies (GWASs). Although hundreds of variants have been identified by GWAS, these variants only explain a small fraction of phenotypic variation. Cross-phenotype association analysis (CPASSOC) can further improve statistical power by searching for variants that contribute to multiple traits, which is often relevant to pleiotropy. In this study, we performed CPASSOC analysis on the summary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) consortium using a novel method recently developed by our group. Sex-specific meta-analysis data for height, body mass index (BMI), and waist-to-hip ratio adjusted for BMI (WHRadjBMI) from discovery phase of the GIANT consortium study were combined using CPASSOC for each trait as well as 3 traits together. The conventional meta-analysis results from the discovery phase data of GIANT consortium studies were used to compare with that from CPASSOC analysis. The CPASSOC analysis was able to identify 17 loci associated with anthropometric traits that were missed by conventional meta-analysis. Among these loci, 16 have been reported in literature by including additional samples and 1 is novel. We also demonstrated that CPASSOC is able to detect pleiotropic effects when analyzing multiple traits.
Cognitive Principles and CALL Grammar Instruction: A Mind-Centered, Input Approach.

Cognitive learning theories increasingly inform the creation and design of Computer Assisted Language Learning (CALL) materials. Recent discussions have explored the potential benefits of underscoring CALL materials with socio-cognitive learning theories such as situated cognition (Salaberry 1996; Renie & Chanier, 1995). However, Reynolds, Sinatra, and Jetton (1996) remind educators that there are principally two types of learning theories, both of which enjoy empirical verification: experience-centered theories, like situated cognition, and mind-centered ones, such as those theories that recognize the importance of providing learners with comprehensible input (e.g., Krashen, 1982). Even if Krashen's theory of comprehensible input is empirically untenable, it is important to keep in mind that no documented cases of successful foreign language acquisition exist without exposure to some sort of comprehensible input (Long, 1990). Thus, CALL materials designers and educators should continue to explore mind-centered theories. Drawing on the latest advances in our understanding of the interaction between internal cognitive processes and foreign language learning--specifically, VanPatten's (1993) Processing Instruction framework--this author outlines principles with which CALL educators can design effective input-oriented tasks targeting grammar instruction. The article concludes with the presentation of a prototype CALL application implementing these principles.
Outage Performance Analysis of Correlated MIMO Optimum Combining Systems with and without Co-Channel Interference

In this paper, we investigate the outage performance of multiple-input/multiple-output (MIMO) systems employing optimum combining over spatially correlated Rayleigh fading channels with and without co-channel interference. Based on the theory of complex matrix variate distributions, we give a unified approach to the outage performance analysis for such MIMO systems, and derive exact closed-form expressions for the system outage probability, which are very general including some of existing related results as special cases and allowing for the correlated structures of both signal and interferers to be arbitrary at both transmitter and receiver ends
Cultural learning in the EFL classroom: the role of visuals

Visual texts are part of everyday communication and they have the potential to carry multiple layers of meaning. This complexity is what makes them an ideal resource not only for language learning, but also for developing learners’ intercultural communicative competence and cultural awareness. Cultural meanings are not locked into these materials; they are emergent and dependent on cultural and subcultural membership, lived experiences, and the geo-cultural grounding of learners who interact with them. In a small-scale research project, we aimed to explore how the cultural background of language learners influences their meaning-making processes and we found that the meanings learners create operate on three levels: universal meanings, cultural and subcultural meanings, and, finally, individual meanings. The richness of students’ interpretations points to the need to draw on them as resources in the language classroom, as they can provide the basis for negotiating cultural understanding.
Packing Steiner Trees: Separation Algorithms

In this paper, we investigate separation problems for classes of inequalities valid for the polytope associated with the Steiner tree packing problem, a problem that arises, e.g., in very large-scale integration (VLSI) routing. The separation problem for Steiner partition inequalities is \NP-hard in general. We show that it can be solved in polynomial time for those instances that come up in switchbox routing. Our algorithm uses dynamic programming techniques. These techniques are also applied to the much more complicated separation problem for alternating cycle inequalities. In this case, we can compute in polynomial time, given some point $y$, a lower bound for the gap $\alpha-a^Ty$ over all alternating cycle inequalities $a^Tx\ge\alpha$. This gives rise to a very effective separation heuristic. A by-product of our algorithm is the solution of a combinatorial optimization problem that is interesting in its own right: find a shortest path in a graph where the "length" of a path is its usual length minus the length of its longest edge.
Analysis on carrier delay ambiguity resolving in Connected Elements Interferometry

Carrier delay ambiguity resolving is the essence to enable CEI (Connected Elements Interferometry) a high accurate measuring system. Two ways of resolving carrier delay ambiguity are discussed under different signal types in TT&C, including Δ DOR method and FX correlation method. According to 3σ rule, the requirement of difference phase measurement accuracy at certain carrier and bandwidth between different DOR tone in ΔDOR method is analyzed. Afterward, the scheme of FX correlation method to resolve ambiguity is proposed. The simulation results indicate that comparing to FX correlation method, ΔDOR has a lower SNR demand in the process of resolving ambiguity, while FX correlation needs further research in the future.
Measurement of Dissociation Degree in Pulsed RF Plasma

N atom density is determined in pulsed RF 27 MHz nitrogen plasma at the pressures ranging from 1.5 to 5 torr and effective discharge currents ranging from 80 to 140 mA. From time resolved measurements of fluorescence of second and first positive systems of nitrogen in after-glow the density is calculated using simple kinetic model of nitrogen after-glow. Calculated density of N atoms is in range (5-11) × 10 -13 cm -3 which respond to dissociation ratio in range (0.8 - 3) × 10 -3 . The gas temperature is estimated from spectra of second positive system (0-0) transition. The temperature ranges from 400 K to 600 K.
Predicting Economic Indicators from Web Text Using Sentiment Composition

Of late there has been a significant amount of work on using sources of text data from the Web (such as Twitter or Google Trends) to predict financial and economic variables of interest. Much of this work has relied on some form or other of superficial sentiment analysis to represent the text. In this work we present a novel approach to predicting economic variables using sentiment composition over text streams of Web data. We treat each text stream as a separate sentiment source with its own predictive distribution. We then use a Bayesian classifier combination model to combine the separate predictions into a single optimal prediction for the Nonfarm Payroll index, a primary economic indicator. Our results show that we can achieve high predictive accuracy using sentiment over big text streams.
Modelling Phrase-Based Statistical Machine Translation for English-Hindi Language

Machine Translation (MT) is the task of automatically translating a text from one language to another. In this paper, we describe the Translation Machine for English-Hindi language pair i.e. English is the source language and Hindi is the target language. Many Translation Machines have designed so far for various Indian Languages. But English-Hindi is more challenging and more popular one. The statistical approach is used for designing the particular Translation
Text feature selection based on improved adaptive GA

Text feature selection is crucial to improve the speed and accuracy of text categorization, and then improves the effect of complex network information filtering. Considering feature selection as an optimization problem, an improved genetic algorithm (GA) is proposed to fulfill text feature selection in this paper. Traditional adaptive genetic algorithm has poor adaptation. Compared with the traditional adaptive genetic algorithm, the fitness function formula, crossover probability formula and mutation probability formula are improved. We illustrated the validity of the improved genetic algorithm through experiments.
X chromosome-wide identification of SNVs in microRNA genes and non-obstructive azoospermia risk in Han Chinese population

Human X chromosome has higher densities of microRNAs (miRNAs) compared to the average densities on autosomes. Given that numbers of X-linked miRNAs can escape from meiotic sex chromosome inactivation (MSCI) silencing, it is proposed that X-linked miRNAs may play critical roles in the process of spermatogenesis. To test the hypothesis, we performed DNA capture sequencing of human X-linked miRNAs, which was followed by a two-stage case-control study to identify the non-obstructive azoospermia (NOA) related single nucleotide variants (SNVs) in 1107 NOA cases and 1191 fertile healthy controls. Eventually, we found rs5951785, located near hsa-miRNA-506/507, increased the risk of NOA, while rs1447393, near hsa-miRNA-510, decreased the risk of NOA. Functional analysis revealed that rs5951785 significantly inhibited cell proliferation and induced cell apoptosis. Taken together, our results demonstrated that X-linked miRNAs played important roles in the pathogenesis of NOA.
Tractography of the Corpus Callosum in Huntington’s Disease

White matter abnormalities have been shown in presymptomatic and symptomatic Huntington’s disease (HD) subjects using Magnetic Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI) methods. The largest white matter tract, the corpus callosum (CC), has been shown to be particularly vulnerable; however, little work has been done to investigate the regional specificity of tract abnormalities in the CC. Thus, this study examined the major callosal tracts by applying DTI-based tractography. Using TrackVis, a previously defined region of interest tractography method parcellating CC into seven major tracts based on target region was applied to 30 direction DTI data collected from 100 subjects: presymptomatic HD (Pre-HD) subjects (n = 25), HD patients (n = 25) and healthy control subjects (n = 50). Tractography results showed decreased fractional anisotropy (FA) and increased radial diffusivity (RD) across broad regions of the CC in Pre-HD subjects. Similar though more severe deficits were seen in HD patients. In Pre-HD and HD, callosal FA and RD were correlated with Disease Burden/CAG repeat length as well as motor (UHDRSI) and cognitive (URDRS2) assessments. These results add evidence that CC pathways are compromised prior to disease onset with possible demyelination occurring early in the disease and suggest that CAG repeat length is a contributing factor to connectivity deficits. Furthermore, disruption of these callosal pathways potentially contributes to the disturbances of motor and cognitive processing that characterize HD.
Real-time recognition of broadcast radio speech

This paper presents a real-time speech recognition system used to transcribe broadcast radio speech. The system is based on ABBOT, the hybrid connectionist-HMM large vocabulary continuous speech recognition system developed at the Cambridge University Engineering Department. Developments designed to make the system more robust to acoustic variability and to improve performance when decoding spontaneous speech are described. Modifications necessary to increase the speed of the system so that it operates in real-time are also described. Recognition results and latency figures are presented for speech collected from broadcast news segments on BBC Radio 4.
Towards teleconferencing by view synthesis and large-baseline stereo

We address the application of computer vision to semi-immersive teleconferencing, and present a prototype vision system synthesising a physically plausible video of a speaker to be displayed at a remote conferencing station. The main system components are a hierarchical, efficient large-baseline disparity estimation and a view synthesis module. We illustrate and discuss some results with a real-speaker sequence. We regard the development of such a system in the domain of advanced teleconferencing as the main contribution of this work.
A Process Model for Concept Invention

In this paper, we propose a computational framework that models concept invention. The framework is based on conceptual blending, a cognitive theory that models human creativity and explains how new concepts are created. Apart from the blending mechanism modeling the creation of new concepts, the framework considers two extra dimensions such as origin and destination. For the former, we describe how a Rich Background supports the discovery of input concepts to be blended. For the latter, we show how arguments, promoting or demoting the values of an audience, to which the invention is headed, can be used to evaluate the candidate blends created. Throughout the paper, we exemplify the computational framework in the domain of computer icons.
Specialized Face Perception Mechanisms Extract Both Part and Spacing Information: Evidence from Developmental Prosopagnosia

It is well established that faces are processed by mechanisms that are not used with other objects. Two prominent hypotheses have been proposed to characterize how information is represented by these special mechanisms. The spacing hypothesis suggests that face-specific mechanisms primarily extract information about spacing among parts rather than information about the shape of the parts. In contrast, the holistic hypothesis suggests that faces are processed as nondecomposable wholes and, therefore, claims that both parts and spacing among them are integral aspects of face representation. Here we examined these hypotheses by testing a group of developmental prosopagnosics (DPs) who suffer from deficits in face recognition. Subjects performed a face discrimination task with faces that differed either in the spacing of the parts but not the parts (spacing task), or in the parts but not the spacing of the parts (part task). Consistent with the holistic hypothesis, DPs showed lower performance than controls on both the spacing and the part tasks, as long as salient contrast differences between the parts were minimized. Furthermore, by presenting similar spacing and part tasks with houses, we tested whether face-processing mechanisms are specific to faces, or whether they are used to process spacing information from any stimulus. DPs' normal performance on the tasks of two houses indicates that their deficit does not result from impairment in a general-purpose spacing mechanism. In summary, our data clearly support face-specific holistic hypothesis by showing that face perception mechanisms extract both part and spacing information.
The Influence of Using Momentum and Impulse Computer Simulation to Senior High School Students’ Concept Mastery

This research is based on students’ lack of mastery of physics abstract concepts. Thus, this study aims to improve senior high school students’ mastery of momentum and impulse concepts with the use of computer simulation. To achieve these objectives, the research method employed was pre experimental design with one group pre-test post-test. A total of 36 science students of grade 11 in one of public senior high school in Bandung became the sample in this study. The instruments utilized to determine the increase of students’ concept mastery were pretest and posttest in the form of multiple choices. After using computer simulations in physics learning, students’ mastery of momentum and impulse concept has increased as indicated by the normalized gain of 0.64 with the medium category.
Wide-band microstrip antenna with an H-shaped coupling aperture

Theoretical and experimental results of a wide-band planar antenna are presented. This antenna can achieve a wide bandwidth, low cross-polarization levels, and low backward radiation levels. For wide bandwidth and easy integration with active circuits, it uses aperture-coupled stacked square patches. The coupling aperture is an H-shaped aperture. Based on the finite-difference time-domain method, a parametric study of the input impedance of the antenna is presented, and effects of each parameter on the antenna impedance are illustrated. One antenna is also designed, fabricated, and measured. The measured return loss exhibits an impedance bandwidth of 21.7%. The cross-polarization levels in both E and H planes are better than 23 dB. The front-to-back ratio of the antenna radiation pattern is better than 22 dB. Both theoretical and experimental results of S parameters and radiation patterns are presented and discussed.
Image retrieval system based on wavelet network

This paper presents a content-based image retrieval (CBIR) system using the image features extracted by wavelet network and color information descriptors. In this work, average precision and recall are computed for all queries to evaluate the proposed algorithm. The experimental results have demonstrated an improved performance (higher precision and recall values) when compared with other CBIR methods.
Managing Risks on Critical IT Systems in Public Service Organizations

Public service organizations rely on IT systems to fulfill their missions. IT incidents are more and more frequent and the impacts of IT incidents on the organizations are getting more severe. There is a strong need to manage risks on service related IT systems in public service organizations. Risk management process practiced in software development companies cannot be used in public service organizations directly, due to differences in business processes. This paper presents a risk management model for these kinds of organizations. The methods of using the model to manage risks are illustrated in an example where a number of identified risks are analyzed and risk reduction activities are identified. How to make risk management a continuous and regular event is also suggested. This model can be practiced by public service organizations directly and enrich their own risk list continuously.
Decreased functional connectivity between the amygdala and the left ventral prefrontal cortex in treatment-naive patients with major depressive disorder: a resting-state functional magnetic resonance imaging study

Background Convergent studies provide support for abnormalities in the structure and functioning of the prefrontal cortex (PFC) and the amygdala, the key components of the neural system that subserves emotional processing in major depressive disorder (MDD). We used resting-state functional magnetic resonance imaging (fMRI) to examine potential amygdala–PFC functional connectivity abnormalities in treatment-naive subjects with MDD. Methods Resting-state fMRI data were acquired from 28 individuals with MDD and 30 healthy control (HC) subjects. Amygdala–PFC functional connectivity was compared between the MDD and HC groups. Results Decreased functional connectivity to the left ventral PFC (VPFC) from the left and right amygdala was observed in the MDD group, compared with the HC group (p < 0.05, corrected). Conclusions The treatment-naive subjects with MDD showed decreased functional connectivity from the amygdala to the VPFC, especially to the left VPFC. This suggests that these connections may play an important role in the neuropathophysiology of MDD at its onset.
ON PREDICTING RELATIONSHIP SATISFACTION FROM JEALOUSY: THE MODERATING EFFECTS OF LOVE

ABSTRACT Researchers in the interdisciplinary research area of close relationships have recently had a renewed interest in relationship satisfaction and its causes. In some of the several recent studies that have looked at the determinants of relationship satisfaction, a positive link between jealousy and relationship satisfaction has, somewhat counterintuitvely, been found. Other studies have likewise shown a negative relationship between jealousy and relationship satisfaction such that as one ' s level of jealousy increases, his or her satisfaction decreases. In an effort to clarify this seemingly conflicting evidence, data was collected from a sample of 134 currently dating heterosexual participants. The participants completed self-report measures of relationship satisfaction, jealousy, and love. Moderated multiple regression analyses were conducted on the data. It was found that level of jealousy alone is a fair predictor of relationship satisfaction. However, this relationship is qualified by a significant interaction between jealousy and love. In other words, jealousy can predict relationship satisfaction, but this relationship depends on how much one loves his or her partner. Implications of the results and potential problems with the study are discussed.
Stereo Reconstruction for Visual Navigation

Visual Navigation is the key to enabling useful mobile robots to work autonomously in unmapped dynamic environments. It involves positioning a robot by tracking the world as it moves past a camera. This paper describes techniques we are developing to improve the accuracy of transformations calculated by matching sets of points between two views. This tells us how far the robot has moved. In the best contemporary Visual Navigation algorithms an approximate estimate of the transformation is improved using the Bundle Adjustment algorithm to incorporate all information from point correspondences tracked over multiple views. This iterative optimisation procedure is computationally intensive and prone to convergence to false minima however, so it is desirable to start as close to the true solution as possible. We compare existing algorithms used to extract a transformation for this initial solution and adapt them to provide improved performance when tracking 3d points from stereo cameras that have uncertain depth.
The Impact of Unethical Reasoning on Academic Dishonesty: Exploring the Moderating Effect of Social Desirability

The relationship between unethical reasoning and academic dishonesty (cheating, plagiarism, outside help, and electronic cheating) is stronger for students with low social desirability perceptions than for students with high social desirability perceptions. For those with high social desirability perceptions, the relationship between their unethical reasoning and their academically dishonest behavior is significantly impacted by their concern of how they are seen by others. For those with low social desirability perceptions, the relationship between their unethical reasoning and their academically dishonest behavior is significantly stronger as they are less impacted by how they are seen by others.