Miracle-dz/UniFAR-FTUs huggingface dataset:
GAWO: Genetic-based optimization algorithm for SMT

In this work, we propose GAWO, a new method for SMT parameters optimization based on the genetic algorithms. Like other existing methods, GAWO performs the optimization task through two nested loops, one for the translation and the other for the optimization. However, our proposition is especially designed to optimize the feature weights of the fitness function of GAMaT, a new genetic-based decoder for SMT. We tested GAWO to optimize GAMaT for French-English and Turkish-English translation tasks, and the results showed that we out-perform the previous performance by +4.0 points according to the BLEU for French-English and by +2.2 points for Turkish-English.
MODELING P WAVE MULTIPATHING IN SOUTHEAST ASIA

We have used data from the small aperture Chiang Mai seismic array (CMAR) in Thailand to characterize P-wave propagation in the mantle transition zone beneath south Asia. Our data consist of nearly 1700 events, which occurred at regional distances from CMAR with continental ray paths. We used time domain beam-forming techniques to estimate the 2D slowness vectors of all the first arriving energy and found only mild anomalies in back azimuth from what is predicted for the U.S. Geological Survey (USGS) epicenters. We also found that later arriving energy, appearing either as discrete secondary phases or as part of the coda, arrives along the great circle paths as well. This justified the use of slant-stack techniques that assume great circle propagation but retain high resolution in time. We designed an algorithm that generates smoothed slant-stacks and automatically picks local maxima in time-ray parameter space for a user-defined level of significance. The resulting values were averaged into time-distance bins in order to generate an image of P wave propagation across the region. We find that when large numbers of data are combined, the resulting images tend to be smeared and lack clear signals from triplications associated with the 410-km and 660-km discontinuities. This is true for a variety of frequency bands, beam formation techniques, binning parameters, and alignment techniques. In general, differences among source properties and lateral variation in Earth structure are significant enough to defocus the images. However, we find that triplicated arrivals are often visible for individual events and small geographical clusters of events. We have implemented a modeling technique that uses a niching genetic algorithm to globally search the model space and find groups of acceptable models. The models are described by 10–12 parameters that represent P velocities at nodes in the upper mantle, as well as the depths for discontinuities near 410 km and 660 km. We have experimented with objective functions defined using the curvature of the first arriving travel time curve, differential travel times at various distances, and combinations of the two. Estimates of differential ray parameters for multiple arrivals are not included in the objective function because the predicted differences are generally too small to be observed robustly at CMAR. Tests with noise-free synthetic data indicate good recovery of the input model in the upper mantle, with discontinuity depths usually within ±5 km, and velocity jumps within 20%. We are currently working on developing 1D models for the individual events and event groupings in which triplicated arrivals are confidently observed. 29th Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies
Advancement of Asian Cassava Molecular Breeding towards SDGs

Cassava is an important tropical starch crop that provides food security, income generation and industrial application in tropical countries. We have developed cassava research platform towards advancing molecular breeding and understanding biological phenomena by the international collaborations between Japan, Vietnam, Thailand, and Colombia. The platform provides: a) 20,000 full-length cDNA resources, b) Omic analyses, c) integrative database, d) transformation system and e) CRISPR/Cas9-mediated mutagenesis. We optimized the system for induction of friable embryonic calli in cassava. Using the improved protocol, we have produced several transgenic cassava plants to improve cassava biomass quantitatively and qualitatively. We also have analyzed the molecular mechanisms of various biological phenomena, such as tuberization, disease resistance, drought and high-salinity stress response by integrative Omic analyses. Furthermore, we have analyzed the effects of environmental factors on the developmental phenotypes in the fields of Vietnam and Cambodia. RIKEN group has educated young Asian researchers cutting-edge plant science. We hope that our approach using the cutting-edge research platform and ICT will advance the molecular breeding of useful cassava plants, such as high-yield, increased stress tolerance and beneficial modifications of starch quality and contribute to solve the SDGs.
PREDICTION OF 1 P / 19 Q CODELETION STATUS IN DIFFUSE GLIOMA PATIENTS USING PREOPERATIVE MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING

ii List of Figures. vii List of Tables . ix Chapter 1: Introduction . 1 1.1 New glioma classification in 2016 . 1 1.2 1p/19q chromosomal codeletion . 2 1.3 Determining 1p/19q codeletion status and Radiogenomics . 3 1.4 Central Hypothesis . 4 1.6 Organization of this thesis . 5 Chapter 2: Data acquisition and pre-processing . 6 2.1 BRATS 2017 dataset . 6 2.2 1p/19q status and patient information from TCGA . 7 2.3 Patient Characteristics . 8 2.4 Train/test dataset split . 8 2.5 Image pre-processing pipeline . 9 2.5. 1 N4 bias correction . 9 2.5. 2 Intensity Normalization . 10 2.5. 3 Intensity Discretization – Texture analysis only . 16 2.5. 4 Intensity Linearization – TDA and CNN analysis. 17
A Distributed Algorithm for the Cluster-Based Outlier Detection Using Unsupervised Extreme Learning Machines

Outlier detection is an important data mining task, whose target is to find the abnormal or atypical objects from a given dataset. The techniques for detecting outliers have a lot of applications, such as credit card fraud detection and environment monitoring. Our previous work proposed the Cluster-Based (CB) outlier and gave a centralized method using unsupervised extreme learning machines to compute CB outliers. In this paper, we propose a new distributed algorithm for the CB outlier detection (DACB). On the master node, we collect a small number of points from the slave nodes to obtain a threshold. On each slave node, we design a new filtering method that can use the threshold to efficiently speed up the computation. Furthermore, we also propose a ranking method to optimize the order of cluster scanning. At last, the effectiveness and efficiency of the proposed approaches are verified through a plenty of simulation experiments.
Analysis of Microstructures in Traffic Jams on Highways Based on Drone Observations

We investigate vehicle trajectories on a three-lane road segment of a highway which were obtain from drone observations. Based on these comprehensive datasets, we study distance headways to preceding vehicles and develop a method to quantify the local traffic density on a short distance ahead of a vehicle. We leverage these metrics to study a local traffic jam. The new method indicates increased traffic density ahead of a vehicle about 100 meters or 15 seconds before a vehicle is affected by the traffic jam. We also study the connection between vehicle speed and distance headway or traffic density, respectively, and quantify them by conditional probabilities and conditional means. On the one hand, the results give insights into microstructures of traffic jams. On the other hand, the novel method for local density calculation may be applied in vehicles to warn drivers of upcoming high density traffic situations which improves driving safety.
Toward an integrative theory of the firm: A relationship-based approach

This paper argues that the existing four major theories of the firm, i.e., the transaction cost theory, resource-based view, the entrepreneurial theory, and the stakeholder theory, are all insightful yet partial because each of them has a particular focus on the phenomenon of the firm. To better understand the nature and behaviors of the firm, we need a comprehensive yet integrative theory. Toward this end, this paper proposes a relationship-based theory of the firm (R’BT) which claims that it is the relationships between the entrepreneur and other individuals or firms that determine the existence, boundary, internal organization and competitive advantage of the firm.
Searching for ( the Neural Basis of ) Love : AAV-mediated CRISPR / Cas 9 editing of the oxytocin receptor gene in the prairie vole

Research on the monogamous prairie vole (Microtus ochrogaster) has tremendously advanced our knowledge on pair bonding the evolutionary antecedent of romantic love and has identified oxytocin (OXT) as a crucial neuromodulator in pair bond formation. A major impediment in elucidating the exact neural mechanisms via which OXT influences pair bonding has been difficulty in manipulating the genome of this non-traditional model organism. Here, we set out to develop adeno associated virus (AAV)-mediated CRISPR/Cas9 to target the OXT receptor (OXTR) gene in the adult prairie vole brain. We show that AAVCRISPR/Cas9 induces genomic edits both in vitro and in vivo, resulting in OXTR knock-down. Our results demonstrate that AAV-CRISPR/Cas9 can be used to perturb OXTR expression paving the way for the use of this technique to study the role of OXT in distinct neural pathways in pair bond formation.
Fibroblast-derived 3 D matrix differentially regulates the growth and drug-responsiveness of human cancer cells

Recent studies have emphasized the importance of cellular microenvironment in modulating cell growth and signaling. In vitro, collagen matrices, Matrigel, and other synthetic support systems have been used to simulate in vivo microenvironments, and epithelial cells grown in these matrices manifest significant differences in proliferation, differentiation, response to drugs, and other parameters. However, these substrates do not closely resemble the mesenchymal microenvironment that is typically associated with advanced carcinomas in vivo, which is produced to a large extent by fibroblasts. In this study, we have evaluated the ability of a fibroblast-derived three-dimensional matrix to regulate the growth of a panel of 11 human tumor epithelial cell lines. Although proliferative and morphological responses to three-dimensional cues segregated independently, general responsiveness to the matrix correlated with the ability of matrix to influence drug responses. Fibroblast-derived three-dimensional matrix increased β1-integrin-dependent survival of a subset of human cancer cell lines during taxol treatment, while it sensitized or minimally influenced survival of other cells. β1-integrin-dependent changes in cell resistance to taxol did not correlate with degree of modulation of FAK and Akt, implying additional signaling factors are involved. Based on these results, we propose these matrices potentially have value as in vitro drug screening platforms.
RTL Guidelines for Static Power Reduction

This work consists on implementing power gating on a sub-system IP, in hopes to reduce static power consumption in chips implemented on low geometry technology. From the results obtained, conclusions are to be made on some lines to guide future low power implementations. This guidelines are to be tested on another component in order to observe their impact on power consumption.
Progressive Module Minimization for Re-encoding Transformed Soft Decoding of RS Codes

The interpolation based algebraic decoding for Reed-Solomon (RS) codes can correct errors beyond half of the code’s minimum Hamming distance through constructing a minimum polynomial Q(x,y) and finding its y-roots. The progressive algebraic soft decoding (PASD) constructs Q(x, y) with a progressively enlarged y-degree and terminates once the message is decoded, adapting the decoding capability and computation to the channel. This paper proposes the re-encoding transformed PASD algorithm, in which Q(x, y) is progressively constructed by the low-complexity module minimization (MM) technique. Re-encoding transform (ReT) results in a common divisor for polynomials of the image of the submodule basis. It can be removed, leading to a simpler image expansion and reduction. Consequently, Q(x,y) is constructed through the isomorphic image of the progressively enlarged submodule basis. Our complexity analysis characterizes the complexity reduction brought by the transform and shows high rate codes benefit a greater complexity reduction.
LOCATIVE ALTERNATION IN SLAVIC : THE ROLE OF PREFIXES

This paper deals with the phenomenon called locative alternation, the classification of locative verbs, the comparative analysis of locative verbs in two languages, English (E) and Russian (R), and syntactic-semantic correspondences. Two principal goals were set up. The first goal is to investigate the relation between the semantic structure of locative verbs and their syntactic configuration in R adopting the Broad Range class model of Pinker (1989) and to compare R locative verbs with their E counterparts. The more important goal is to offer some explanation for the fact that most non-alternating morphologically simple R content verbs can enter the Ground frame when prefixed with ZAand OB-. We are going to account for the role of prefixes (ZAand OB-, namely) in the locative alternation in R. The organization of this paper is as follows. In Section 1, we introduce locative verbs, talk about their classification, review the main approaches to the syntactic-semantic structure of locative verbs, and discuss what properties of verbs determine whether they can occur in the Figure frame, the Ground frame, or both as well as what properties permit the alternation. In Section 2, we first present an analysis of R locative verbs. We then discuss the status of Slavic prefixes and their role in the locative alternation, concentrating on the semantic contribution of two prefixes that usually trigger the alternation, ZAand OB-. We finally develop two approaches that explain why only particular prefixes play a role in the locative alternation and what their exact functions are.
Time Varying Price Discovery in VIX Exchange Traded Notes: A Tale of Retail vs. Institutional Trades

This study investigates the intraday price discovery between the VIX shortterm futures ETNs (VXX) and inverse VIX short-term ETNs (XIV) for the period January 3, 2011 to December 31, 2015. Applying both the Hasbrouck (1995) information share and the Gonzalo and Granger (1995) common factor weight approach, we observe strong time variation in the price discovery contribution between the direct and inverse notes. We find that the classical measures of trading costs and market liquidity are significant determinants of price discovery. We also document that price discovery of the VXX increases with the greater institutional ownership and on those days the level of the VIX tends to be high. We also report that order imbalance of both retail and institutional investors has a significant effect on price discovery.
A new take on the relationship between interest rates and credit spreads

ABSTRACT We revisit the link between interest rates and corporate bond credit spreads by applying Rigobon’s (2003) unique heteroskedasticity-based identification methodology to their interconnected dynamics through a bivariate VAR system. This different approach allows us to account for simultaneity issues and use this framework to test the various possible explanations for the credit spread – interest rate relation that have been proposed by the literature over the years. We find that credit spreads do indeed respond negatively to interest rates, a result consistent with Merton’s (1974) structural model. This negative relation is robust to macroeconomic shocks, market uncertainty, business cycles, different sample periods, bond callability, and bond ratings. We also find the magnitude of the negative relation to be larger for high-yield bonds than for investment-grade bonds, and are able to rule out the option-like feature of callable bonds proposed by Duffee (1998) as the main driver of the negative nature of the relationship. These results have important portfolio and risk management implications.
Dense 3 D Face Correspondence

This is the author version of the paper: Syed Zulqarnain Gilani, Ajmal Mian, Faisal Shafait, and Ian Reid. ”Dense 3D face correspondence. ” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),40(7), 2017. We present an algorithm that automatically establishes dense correspondences between a large number of 3D faces. Starting from automatically detected sparse correspondences on the outer boundary of 3D faces, the algorithm triangulates existing correspondences and expands them iteratively by matching points of distinctive surface curvature along the triangle edges. After exhausting keypoint matches, further correspondences are established by generating evenly distributed points within triangles by evolving level set geodesic curves from the centroids of large triangles. A deformable model (K3DM) is constructed from the dense corresponded faces and an algorithm is proposed for morphing the K3DM to fit unseen faces. This algorithm iterates between rigid alignment of an unseen face followed by regularized morphing of the deformable model. We have extensively evaluated the proposed algorithms on synthetic data and real 3D faces from the FRGCv2, Bosphorus, BU3DFE and UND Ear databases using quantitative and qualitative benchmarks. Our algorithm achieved dense correspondences with a mean localisation error of 1.28mm on synthetic faces and detected 14 anthropometric landmarks on unseen real faces from the FRGCv2 database with 3mm precision. Furthermore, our deformable model fitting algorithm achieved 98.5% face recognition accuracy on the FRGCv2 and 98.6% on Bosphorus database. Our dense model is also able to generalize to unseen datasets.
SYMBIOTIC MYCORRHIZAL FUNGI ISOLATED VIA EX SITU SEED BAITING INDUCE SEED GERMINATION OF DENDROBIUM CATENATUM LINDL. (ORCHIDACEAE)

The epiphytic orchid species Dendrobium catenatum is extensively used as a traditional medicine in China. Overexploitation has led to endangerment and rarity of the species in the wild, and conservation measures are immediately needed. As in many orchid species, mycorrhizal symbiotic seed germination is recognized as a powerful tool for orchid seedling propagation, reintroduction, and species conservation. Obtaining efficient and specific fungi for enhancing seed germination, protocorm formation, and further seedling development is a prerequisite. In this study, eight purified fungal strains were isolated from host orchid protocorms via an ex situ baiting technique. Phylogenetic analysis using ITS-rDNA placed the eight fungal strains into the taxa Tulasnellaceae, Ceratobasidiaceae, and Sebacinales, the typical orchid mycorrhizal symbionts. The fungi induced seed germination and also increased growth during protocorm formation, seedling formation, and seedling development. One strain in particular (SSCDO-5) exhibited significant benefits under 12/12 h light/dark conditions between 20 and 90 days after sowing. Our results suggest that inoculation with the fungus SSCDO-5 might assist in the propagation of D. catenatum and could be employed ex situ and in situ for conservation purposes.
A Descriptive Study of Adolescent Perceptions of Rural Versus Urban Kentucky High School Student Mental Health Challenges

ISSN: 2560-9815 (Print) 2560-9823 (Online) Journal homepage: http://www.theyoungresearcher. com All articles appearing in The Young Researcher are licensed under CC BY-NC-ND 2.5 Canada License. Recommended Citation Tu, A. (2018). A descriptive study of adolescent perceptions of rural versus urban Kentucky high school student mental health challenges. The Young Researcher, 2 (1), 148-163. Retrieved from http://www.theyoungresearcher. com/papers/tu.pdf A Descriptive Study of Adolescent Perceptions of Rural Versus Urban Kentucky High School Student Mental Health Challenges
DEVELOPMENT OF A DIGITAL REACTIVITY METER FOR CRITICALITY PREDICTION AND CONTROL ROD WORTH EVALUATION IN PRESSURIZED WATER REACTORS

In this work, we have proposed the development of a digital reactivity meter in order to monitor subcriticality continuously during criticality approach in a PWR. A subcritical reactivity meter can provide an easy prediction of the estimated critical point prior to reactor criticality, without complicated hand calculation. Moreover, in order to reduce the interval of the Physics Tests from the economical point of view, a subcritical reactivity meter can evaluate the control rod worth from direct subcriticality measurement. In other words, count rate of Source Range (SR) detector recorded during the criticality approach could be used for subcriticality evaluation or control rod worth evaluation. Basically, a digital reactivity meter is based on the inverse solution of the kinetic equations of a reactor with the external neutron source in one-point reactor model. There are some difficulties in the direct application of a digital reactivity meter to the subcriticality measurement. When the Inverse Kinetic method is applied to a sufficiently high power level or to a core without an external neutron source, the neutron source term may be neglected. When applied to a lower power level or in the sub-critical domain, however, the source effects must be taken in account. Furthermore, some treatments are needed in using the count rate of Source Range (SR) detector as input signal to the digital reactivity meter. To overcome these difficulties, we have proposed a digital reactivity meter combined with a methodology of the modified Neutron Source Multiplication (NSM) method with correction factors for subcriticality measurements in PWR.
COMBINATORY POSSIBILITIES IN MURRINH-PATHA COMPLEX PREDICATES : A TYPE-DRIVEN APPROACH

This paper is concerned with complex predicates in MurrinhPatha, a Northern Australian language. In Murrinh-Patha, a verb usu ally has a bipartite structure, i.e., the lexical meaning of a word is det ermined together by two different parts. This paper looks at the combinatory p ossibilities of these two parts, establishes some factors which may play a ro le in the selection process and proposes a formal modeling of the data using a fi e-grained semantic type hierarchy. The paper then compares this appro ch t accounts utilizing the idea of lexical conceptual structures (LCSs) (Jackendoff, 1990) such as e.g., Butt (1995) and Wilson (1999).
The effectiveness of quantitative easing in Japan : New evidence from a structural factor-augmented VAR

This paper provides a new empirical framework to examine the effectiveness of Japanese monetary policy during the "lost" decade characterized both by stagnation and deflation. We combine advantages of Markov-Switching VAR methodology with those of structural factor analysis in a so-called the MS-Factor-augmented VAR model to establish three major findings. First we propose new empirical evidence supporting the ability of quantitative easing to provide stimulation to both output and prices. Second, we show that the decisive change in regime occurred in two steps: it crept out in May 1995 and established itself durably in February 1999. Third, our results show that the non-neutrality of money and the price divergence in the pre-1995 regime, which characterized the MS-VAR model, are not present with the MS-FAVAR one. JEL Classification : C32; E52