Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Image Processing Techniques to Generate the Realistic Geometric Model for Discrete Element Method

To gain further insight into the interaction among the mix constituents, researchers utilized numerical simulation techniques, such as the Finite Element Method (FEM) and the Discrete Element Method (DEM). The Discrete Element Method was primarily introduced for the analysis of rock-mechanics and granular materials. In recent years, DEM has also been applied to simulate the properties of asphalt concrete. For the purpose of discrete element modeling of the materials two different mechanisms have been extensively employed, namely random geometry generation and importing pre-generated models. In order to gain more realistic simulation it is preferred to enhance more precise initial geometric models which are capable to represent the shape and arrangement of the constituents. For this purpose, two and three dimensional imaging techniques have been investigated by some researchers. In this paper, a userdefined 2D image processing technique was developed to generate the initial geometry of asphalt concrete mixtures. Asphalt concrete specimens were prepared in the laboratory and cut smoothly prior to optical scanning. The digital images were then processed and de-noised by defining the appropriate thresholds. The processed images were employed to generate the initial model for DEM. The presented methodology in this paper enables researchers to have a better comparison between the simulations and the experimental laboratory tests. It also facilitates defining clusters of circular particles to provide better representation of aggregate shape and angularity which yields significant benefits for numerical modeling techniques.
Inferring Tweedie Compound Poisson Mixed Models with Adversarial Variational Methods

The Tweedie Compound Poisson-Gamma model is routinely used for modelling non-negative continuous data with a discrete probability mass at zero. Mixed models with random effects account for the covariance structure related to the grouping hierarchy in the data. An important application of Tweedie mixed models is estimating the aggregated loss for insurance policies. However, the intractable likelihood function, the unknown variance function, and the hierarchical structure of mixed effects have presented considerable challenges for drawing inferences on Tweedie. In this study, we tackle the Bayesian Tweedie mixed-effects models via variational approaches. In particular, we empower the posterior approximation by implicit models trained in an adversarial setting. To reduce the variance of gradients, we reparameterize random effects, and integrate out one local latent variable of Tweedie. We also employ a flexible hyper prior to ensure the richness of the approximation. Our method is evaluated on both simulated and real-world data. Results show that the proposed method has smaller estimation bias on the random effects compared to traditional inference methods including MCMC; it also achieves a state-of-the-art predictive performance, meanwhile offering a richer estimation of the variance function.
ClustSeg : A Method for Text Segmentation

An automatic linear text segmentation in order to detect the best topic boundaries is a difficult and very useful task in many text processing systems. Some methods have tried to solve this problem with reasonable results, but they present some drawbacks as well. In this work, we propose a new method, called ClustSeg, based on a predefined window and a clustering algorithm to decide the topic cohesion. We compare our proposal against the best known methods, with a better performance against these algorithms.
BIS , BAS , and Bias : The Role of Personality and Cognitive Bias in Social Anxiety

0191-8869/$ see front matter Published by Elsevier doi:10.1016/j.paid. 2011.10. 041 ⇑ Corresponding author. Address: VISN 17 Center o Returning War Veterans, Central Texas Veterans Healt Drive (151C), Waco, TX 76711, United States. Tel. : +1 2 3752. E-mail address: Nathan.Kimbrel@va.gov (N.A. Kim The goal of the present research was to test the hypothesis that cognitive biases for negative and threatening social information mediate the effects of behavioral inhibition system (BIS) and behavioral approach system (BAS) sensitivity on social anxiety. Participants completed self-report measures of BIS and BAS and then underwent a social-threat induction procedure in which they were told they would have to perform a speech. A battery of cognitive bias measures was then administered, followed by a battery of state anxiety measures. Audience members also rated participants’ anxiety during the speech. Structural equation modeling was used to test the hypothesized model. As predicted, the fully-mediated model showed the best fit to the data, and higher BIS and lower BAS were found to have significant indirect effects on social anxiety via cognitive bias. Published by Elsevier Ltd.
EFFECT OF THE RECTUS FEMORIS KINESIO-TAPING ON MALE ATHLETES DURING THE STOP-JUMP TASK POST-FATIGUE

This study aimed to investigate the biomechanics of the stop-jump task under the effect of Kinesio-taping (KT) applied on rectus femoris before and after fast-induced fatigue on male athletes. Nine male college athletes served as the subject. Two force plates and ten highspeed cameras were synchronized to capture the stop-jump tasks. The results showed that the jumping height decreased, the vertical ground reaction force (GRF) and the peak proximal tibia anterior shear force increased, and the time to peak vertical GRF was earlier after intervened fatigue in the non-taping group. We also found that the peak proximal tibia anterior shear force did not increase after fatigue when following the application of KT. We recommend that KT is used to intense exercises or competition with repeated jumping.
Step 1 : Clothoid Step 2 : Velocity Profile Step 3 : Trajectory

In this paper, we propose a neural motion planner for learning to drive autonomously in complex urban scenarios that include traffic-light handling, yielding, and interactions with multiple road-users. Towards this goal, we design a holistic model that takes as input raw LIDAR data and a HD map and produces interpretable intermediate representations in the form of 3D detections and their future trajectories, as well as a cost volume defining the goodness of each position that the self-driving car can take within the planning horizon. We then sample a set of diverse physically possible trajectories and choose the one with the minimum learned cost. Importantly, our cost volume is able to naturally capture multi-modality. We demonstrate the effectiveness of our approach in real-world driving data captured in several cities in North America. Our experiments show that the learned cost volume can generate safer planning than all the baselines.
Application of Artificial Neural Networks to Composite Ply

Artificial neural networks can provide improved computational efficiency relative to existing methods when an algorithmic description of functional relationships is either totally unavailable or is complex in nature. For complex calculations, significant reductions in elapsed computation time are possible. The primary goal of this project is to demonstrate the applicability of artificial neural networks to composite material characterization. As a test case, a neural network has been trained to accurately predict composite hygral, thermal, and mechanical properties when provided with basic information concerning the environment, constituent materials, and component ratios used in the creation of the composite. A brief introduction on neural networks is provided along with a description of the project itself.
Agricultural reforms and ‘ growth miracles ’ : evidence from China

Poor countries are overwhelmingly agrarian while rich countries are not. Early growth theorists put capital accumulation at the heart of this transition. More recent cross-country evidence finds a limited role for capital accumulation, though country specific growth accounting exercises suggest suggest importance in some instances (e.g. Young 1995). Because these countries are often poor initially, savings from the agricultural sector provide a potentially important source of capital. In this paper I exploit China’s unique institutional environment and 1978-84 agricultural reforms, to show that agricultural surpluses were an important source of capital in early reform-era China. By liberalising the planting of cash crops, market oriented reforms beginning in 1978 favoured farmers with land suited to these crops, while geographic capital and labour market frictions limited the extent to which local economic shocks dissipate through the rest of the economy. I use the GAEZ soil productivity data, to identify counties with a comparative advantage in cash crops which, combined with the timing of the reforms, provides a source of plausibly exogenous variation in agricultural output. I then show that counties experiencing larger increases in agricultural output also had faster post-reform growth in nonagricultural output, with a medium run elasticity of 0.7. Patterns of agricultural employment, savings, investment, firm entry and factor utilisation are consistent with a model where higher agricultural surpluses increased the supply of capital for non-state enterprises, but not with alternative mechanisms. JEL Codes: O11, O13 O43, P32 ∗s.h. marden@lse.ac. uk. I thank my advisors, Robin Burgess and Gerard Padrò-i-Miquel, for their continued guidance and encouragement. This paper has also benefited from discussions with Oriana Bandiera, Tim Besley, Gharad Bryan, Francesco Casselli, Jon De Quidt, Melissa Dell, Dave Donaldson, Ben Faber, Thiemo Fetzer, Jason Garred, Stelios Michalopoulos, Ben Moll, Nathan Nunn, Gianmarco Ottaviano, Michael Peters, Silvana Tenreyo, Kelly Zhang and seminar participants at LSE, Oxford (CSAE), Manchester (RES), UEA and the IEA World Congress. I gratefully acknowledge financial support from the Economic and Social Research Council and the Royal Economic Society. All errors remain my own.
Relationships of the Sphaeromatidae genera ( Peracarida : Isopoda ) inferred from 18 S rDNA and 16 S rDNA genes

The Sphaeromatidae has 100 genera and close to 700 species with a worldwide distribution. Most are abundant primarily in shallow (< 200 m) marine communities, but extend to 1.400 m, and are occasionally present in permanent freshwater habitats. They play an important role as prey for epibenthic fishes and are commensals and scavengers. Sphaeromatids’ impressive exploitation of diverse habitats, in combination with diversity in female life history strategies and elaborate male combat structures, has resulted in extraordinary levels of homoplasy. We sequenced specimens from 39 genera for nuclear 18S rDNA and mitochondrial 16S rDNA genes, comprehensively reviewed the effects of alignments on tree topology, and performed Garli and MrBayes analyses. These data consistently retrieved clades (genus groups), Sphaeroma, Exosphaeroma, Cymodoce, Ischyromene, Cerceis, and Dynamenella and the monogeneric clade of Gnorimosphaeroma. We define the major clades using morphological characters, attribute sampled taxa to consistently and strongly supported ones and suggest placement of unsampled genera based on their morphological characteristics. Within each clade, we also highlight unresolved and poorly sampled genera. We point out taxonomic problems in hopes of encouraging further phylogenetic exploration. Although we identify clades containing consistent generic groups and are confident that some groups will prove stable and reliable, we feel our sampling is insufficient to propose nomenclatural changes at this time.
Chapter 2 Rapid Earthquake Loss Assessment After Damaging Earthquakes

This article summarizes the work done over last decades regarding the development of new approaches and setting up of new applications for earthquake rapid response systems that function to estimate earthquake losses in quasi real time after an earthquake. After a critical discussion of relevant earthquake loss estimation methodologies, the essential features and the characteristics of the available loss estimation software are summarized. Currently operating near real time loss estimation tools can be classified under two main categories depending on the size of area they cover: Global and Local Systems. For the global or regional near real time loss estimation systems: GDACS, WAPMERR, PAGER, ELER and SELENA methodologies are. Examples are provided for the local rapid earthquake loss estimation systems including: Taiwan Earthquake Rapid Reporting System, Realtime Earthquake Assessment Disaster System in Yokohama, Real Time Earthquake Disaster Mitigation System of the Tokyo Gas Co., IGDAS Earthquake Protection System and Istanbul Earthquake Rapid Response System.
Risk Adjustment for Socioeconomic Status or Other Sociodemographic Factors

On behalf of our nearly 5,000 member hospitals, health systems and other health care organizations, and our 43,000 individual members, the American Hospital Association (AHA) appreciates the opportunity to comment on the National Quality Forum’s (NQF) draft recommendations from its expert panel convened to consider whether quality measures should be risk adjusted for sociodemographic factors, such as Medicaid status, income, education and homelessness. Given that NQF-endorsed measures are extensively used in the Centers for Medicare & Medicaid Services (CMS) programs, we address our comments to both NQF and CMS. If adopted by NQF, the panel’s recommendations would change NQF’s existing measure endorsement criteria to allow NQF-endorsed measures to include sociodemographic factors in their risk adjustment approach when there is a conceptual link to what is being measured, and evidence suggesting adjustment is necessary and appropriate. We commend NQF for convening a highly-qualified expert panel to address this consequential issue, and thank the panel for its balanced, thoughtful and comprehensive review.
Detection and Counting of Vehicles in A High Way Traffic Videos

Automatic detecting and counting vehicles in unsupervised video on highways is a very challenging problem in computer vision with important practical applications such as to monitor activities at traffic intersections for detecting congestions, and then predict the traffic flow which assists in regulating traffic. Manually reviewing the large amount of data they generate is often impractical. The background subtraction and image segmentation based on morphological transformation for tracking and counting vehicles on highways is proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm segments the image by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more accurately, as well as adapt effectively to changing environments.
Flow in Computer Human Environment

Flow or optimal experience is a concept connected with intrinsic motivation which has been explored in the past 30 years. Many researches showed correlation between flow, on one side, and positive experiences and well-being on the other side. The more time students spend in the state of flow, the better quality of their experiences: they experience a higher level of concentration, creativity and positive emotions (Nakamura & Csikszentmihalyi, 2002). The aim of this study was to explore whether students of “Faculty of Electrical Engineering and Computing” (FEEC), Zagreb, Croatia, experience flow while engaged in computer programming and related study fields, and which variables contribute to experiencing flow. The sample consisted of 142 students. The research was conducted via online questionnaire and paper-pencil testing in March and April of 2011. Results show that students experience flow while programming (M=5, 1 ; on the scale of 8). Proportion of variance explained of flow was 39% (F=8, 621 ; df=92 ; p<0, 01). Variables which contributed to flow were: grade acquired in programming subjects at the university (β=0, 23 ; p<0, 05), number of programming languages one is familiar with and can use (β=0, 20 ; p<0, 05) and positive affect (β=0, 47 ; p<0, 01).
Molecular Mapping of Genesand QTLs in Pigeonpea Reyazul

Pigeonpea is one of the most important grain legume crops grown in arid and semiarid regions of the world. There is an increasing demand for the development of new cultivars with high yield potential and better adaptability to adverse environmental conditions. Recent advances in genomics tools and techniques have helped to develop large repertoire of molecular markers and genotypic platforms. The availability of molecular markers facilitated the development of high-density genetic maps that have been used in discovery of important/major QTLs for targeted traits in pigeonpea. In addition, the availability of high-throughput genotypic platforms helped to generate whole genome genotypic data in high-throughput manner necessary for whole genome scanning/ genome-wide association mapping of economically important traits. The advances in comparative genomics, transcriptomics, and whole genome sequencing have uncovered thousands of useful genes including some genes unique to pigeonpea crop. The availability of wealth of genomics resources/information will facilitate molecular breeding aimed at improving production and productivity of pigeonpea in extreme environments of arid and semiarid regions of the world. R.R. Mir (&) I.A. Rather M.A. Bhat G.A. Parray Division of Plant Breeding and Genetics, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir (SKUAST-K), Kashmir 180009, India e-mail: imrouf2006@gmail.com R.K. Varshney International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India © Springer International Publishing AG 2017 R.K. Varshney et al. (eds.), The Pigeonpea Genome, Compendium of Plant Genomes, DOI 10.1007/978-3-319-63797-6_6 55
Congestion-Aware Internet Pricing for Media Streaming

Media webcasting and conferencing that involve many geographically distributed participants contribute significantly to congestion in the Internet. The current usage-based data pricing model does not take into account the hidden cost imposed by media streaming in the Internet core, including the network cost of replicating and relaying traffic in video multicast, and could potentially exacerbate congestion. In lieu of the recently emerged content sponsoring, in this paper, we present a simple congestion pricing model for ISPs (e.g. Comcast) to charge media streaming operators (e.g. Netflix) based on the bandwidth-delay product on each overlay link (either server-to-server or server-touser) that the media streaming operator has chosen to use. The proposed pricing policy incentivizes different media streaming applications to collectively reduce their “waiting packets” in the Internet, alleviating congestion. We formulate the min-cost single and multiple multicast problems for the applications to construct their streaming overlays, based on a dense pool of CDN nodes. An efficient EM algorithm is given to solve the proposed geometric optimization problem and is evaluated through simulations.
Revisiting the Early BARC Tritium Results

Within days of the F&P announcement of 1989, several groups at BARC embarked on a program to look for the generation of neutrons and tritium when deuterium (or hydrogen) is loaded into metals such as Pd, Ti and Ni. Electrolytic, gas and plasma loading techniques were deployed. Post run electrolyte samples were analyzed for tritium content using standard liquid scintillation techniques. In the case of gas and plasma loaded “dry” samples, surface tritium content was measured directly using windowless beta counters. Autoradiography was deployed as a very effective tool to monitor the spatial distribution of tritium in the near surface layers of test samples. The first confirmation of copious tritium generation was obtained on 21 April 1989 in a commercial “Milton Roy” Pd–D2O electrolytic cell. The results obtained during the first year of the BARC Cold Fusion campaign were presented at ICCF 1 in March 1990 where we reported observing tritium generation in 22 different electrolytic cells, which were set up totally independently by diverse research groups. The present paper revisits the early BARC tritium results obtained in a variety of experimental configurations during the period 1989–1996. © 2015 ISCMNS. All rights reserved. ISSN 2227-3123
Environment 1 + 0 Estimate Uncertainty Robot Trajectory 1 + 1 Preferences Human Correction avoid ignore avoid interact

It is difficult for humans to efficiently teach robots how to correctly perform a task. One intuitive solution is for the robot to iteratively learn the human’s preferences from corrections, where the human improves the robot’s current behavior at each iteration. When learning from corrections, we argue that while the robot should estimate the most likely human preferences, it should also know what it does not know, and integrate this uncertainty as it makes decisions. We advance the state-of-the-art by introducing a Kalman filter for learning from corrections: this approach obtains the uncertainty of the estimated human preferences. Next, we demonstrate how the estimate uncertainty can be leveraged for active learning and risk-sensitive deployment. Our results indicate that obtaining and leveraging uncertainty leads to faster learning from human corrections.
INFLUENCE OF PULSED ELECTROPHORETIC DEPOSITION OF GRAPHITIC CARBON NANOTUBE ON ELECTROCHEMICAL CAPACITOR PERFORMANCE

Carbon nanotube (CNT)-based electrochemical capacitor (EC) has been actively studied as a high-power density energy storage for the portable product and energy sustainable development. The present work reports the deposit yields and graphitic concentration of CNT deposited by pulsed electrophoretic deposition (EPD) for the use as EC’s active electrode materials. Using a conventional EPD apparatus, the pulsed EPD was conducted at pulse separation times (pause widths) of 30 to 50 s, alternated with the pulse width of 2.5 min. SEM micrograph showed the pulsed EPD at the pulse separation time of 30 s reduced the deposited CNT coating’s density. An increase of the graphitic concentration by 40% as compared to the CNT coating deposited by continuous EPD was indicated by the IG/ID ratio of the Raman spectra results. The enrichment of graphitic phase in the EC drastically enlarged the specific capacitance of the EC by 150% as compared to the continuous EPD’s EC result. The finding opens up the possibility of EC performance enhancement by controlling the graphitic CNT concentration of the electrode materials using pulse EPD process.
ALPHA-AMYLASE IN RECOMBINANT BACILLUS

Yuko Yoneda, “Increased Production of Extracellular Enzymes by the Synergistic Effect of Genes Introduced into Bacillus substilis by Stepwise Transformation'. Applied and Environmental Microbiol ogy, 39:274-276 (1980). Leung et al., "Characterization of an insertion in the Phase (b105 genome that blocks host Bacillus subtilis lysis and provides strong expression of heterologous genes”. Gene, 154: 1-6 (1995). Thornewell et al., “An efficient expression and Secretion system based on Bacillus subtiis phage (b105 and its use for the production of B. cereus B-lactamas I”. Gene, 133:47-53 (1993). Wei et al., “Plasmid Stability and O-Amylase Production in Batch and continuous Cultures of Bacillus subtilis TN 106 Pat5', 33:101