Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient rendering of large 3-D and 4-D scalar fields

Title of Dissertation: EFFICIENT RENDERING OF LARGE 3-D AND 4-D SCALAR FIELDS Jusub Kim, Doctor of Philosophy, 2008 Dissertation directed by: Professor Joseph JaJa Department of Electrical and Computer Engineering Rendering volumetric data, as a compute/communication intensive and highly parallel application, represents the characteristics of future workloads for desktop computers. Interactively rendering volumetric data has been a challenging problem due to its high computational and communication requirements. With the consistent trend toward high resolution data, it has remained a difficult problem despite the continuous increase in processing power, because of the increasing performance gap between computation and communication. On the other hand, the new multicore architecture trend in computational units in PC, which can be characterized by parallelism and heterogeneity, provides both opportunities and challenges. While the new on-chip parallel architectures offer opportunities for extremely high performance, widespread use of those parallel processors requires extensive changes in previous algorithms to take advantage of the new architectures. In this dissertation, we develop new methods and techniques to support interactive rendering of large volumetric data. In particular, we present a novel method to layout data on disk for efficiently performing an out-of-core axis-aligned slicing of large multidimensional scalar fields. We also present a new method to efficiently build an out-of-core indexing structure for n-dimensional volumetric data. Then, we describe a streaming model for efficiently implementing volume ray casting on a heterogeneous compute resource environment. We describe how we implement the model on SONY/TOSHIBA/IBM Cell Broadband Engine and on NVIDIA CUDA architecture. Our results show that our out-of-core techniques significantly reduce the communication bandwidth requirements and that our streaming model very effectively makes use of the strengths of those heterogeneous parallel compute resource environment for volume rendering. In all cases, we achieve scalability and load balancing, while hiding memory latency. EFFICIENT RENDERING OF LARGE 3-D and 4-D SCALAR FIELDS
Preparticipation cardiovascular screening in young athletes

The sudden and unexpected death of an apparently healthy young athlete is relatively uncommon (0.5–2.1/100 000 athletes per year), but the catastrophic nature of these events mandates the medical community to adopt more widespread and extensive preparticipation cardiovascular screening (PPS). 1 2 PPS in young athletes (<35 years old) is a systemic method to identify athletes at risk for life-threatening cardiovascular events.3 Excluding these athletes from competitive sports participation leads to a reduction in the incidence of exercise related sudden cardiac death (SCD). 3 According to the Italian law all young competitive athletes (about 10% of the population) have been screened in a nationwide screening program in Italy for over 25 years. In the Veneto region in northern Italy, this resulted in a decrease of SCD among young athletes of 89% (from 3.6/100 000 per year in 1979 to 0.4/100 000 athletes per year in 2004). 3 This reduction was predominantly attributed to identification of cardiomyopathy and electrical disease, and by excluding these athletes from competitive sports participation. The number of false positive test results was reported at 7%. 3 The “Italian experience” is at the moment the only prospective population based study regarding PPS. This Italian protocol was adopted by the European Society of Cardiology (ESC) as the “common European protocol”, and by the International Olympic Committee (IOC), the international soccer association Federation Internationale de Football Association (FIFA) and the international federation for cyclists Union Cycliste Internationale (UCI) as …
Elimination of antiviral defense by viral RNase III

Sweet potato (Ipomoea batatas) is an important subsistence and famine reserve crop grown in developing countries where Sweet potato chlorotic stunt virus (SPCSV; Closteroviridae), a single-stranded RNA (ssRNA) crinivirus, synergizes unrelated viruses in co-infected sweet potato plants. The most severe disease and yield losses are caused by co-infection with SPCSV and a potyvirus, Sweet potato feathery mottle virus (SPFMV; Potyviridae). Potyviruses synergize unrelated viruses by suppression of RNA silencing with the P1/HC-Pro polyprotein; however, the SPCSV-SPFMV synergism is unusual in that the potyvirus is the beneficiary. Our data show that transformation of an SPFMV-resistant sweet potato variety with the double-stranded RNA (dsRNA)-specific class 1 RNA endoribonuclease III (RNase3) of SPCSV broke down resistance to SPFMV, leading to high accumulation of SPFMV antigen and severe disease symptoms similar to the synergism in plants co-infected with SPCSV and SPFMV. RNase3-transgenic sweet potatoes also accumulated higher concentrations of 2 other unrelated viruses and developed more severe symptoms than non-transgenic plants. In leaves, RNase3 suppressed ssRNA-induced gene silencing (RNAi) in an endonuclease activity-dependent manner. It cleaved synthetic double-stranded small interfering RNAs (siRNAs) of 21, 22, and 24 bp in vitro to products of approximately 14 bp that are inactive in RNAi. It also affected total siRNA isolated from SPFMV-infected sweet potato plants, suggesting a viral mechanism for suppression of RNAi by cleavage of siRNA. Results implicate RNase3 in suppression of antiviral defense in sweet potato plants and reveal RNase3 as a protein that mediates viral synergism with several unrelated viruses, a function previously described only for P1/HC-Pro.
Symptom Clusters in Women With Relapsing-Remitting Multiple Sclerosis

ABSTRACT The purpose of this secondary analysis was to investigate the relationships among a set of symptoms (fatigue, depression, impaired cognitive function, sleep disturbance) with pain severity and demographic variables. The sample of 40 women with relapsing-remitting multiple sclerosis completed instruments of pain, fatigue, depression, sleep disturbance, and an objective cognitive measure. Analysis identified one symptom cluster of pain, fatigue, depression, sleep disturbance, and impaired cognitive function, whereas a relationship between that symptom cluster and employment status existed. Pain severity correlated with fatigue, sleep disturbance, depression, and impaired cognitive function. Preliminary findings support providing education on symptoms to women with relapsing-remitting multiple sclerosis to ultimately guide their care.
The Formation of Streptococcus mutans Persisters Induced by the Quorum-Sensing Peptide Pheromone Is Affected by the LexA Regulator

ABSTRACT The presence of multidrug-tolerant persister cells within microbial populations has been implicated in the resiliency of bacterial survival against antibiotic treatments and is a major contributing factor in chronic infections. The mechanisms by which these phenotypic variants are formed have been linked to stress response pathways in various bacterial species, but many of these mechanisms remain unclear. We have previously shown that in the cariogenic organism Streptococcus mutans, the quorum-sensing peptide CSP (competence-stimulating peptide) pheromone was a stress-inducible alarmone that triggered an increased formation of multidrug-tolerant persisters. In this study, we characterized SMU.2027, a CSP-inducible gene encoding a LexA ortholog. We showed that in addition to exogenous CSP exposure, stressors, including heat shock, oxidative stress, and ofloxacin antibiotic, were capable of triggering expression of lexA in an autoregulatory manner akin to that of LexA-like transcriptional regulators. We demonstrated the role of LexA and its importance in regulating tolerance toward DNA damage in a noncanonical SOS mechanism. We showed its involvement and regulatory role in the formation of persisters induced by the CSP-ComDE quorum-sensing regulatory system. We further identified key genes involved in sugar and amino acid metabolism, the clustered regularly interspaced short palindromic repeat (CRISPR) system, and autolysin from transcriptomic analyses that contribute to the formation of quorum-sensing-induced persister cells.
Surface-Texturing of Single-Crystalline Silicon Wafers

In this work, alkaline-based anisotropic etchants, tetramethylammonium hydroxide (TMAH) and potassium hydroxide (KOH)/isopropyl alcohol (IPA) solutions, have been used for the surface texturing of the single-crystalline silicon wafers used for solar cells. The pyramid morphology produced by the surface texturing can reduce the surface reflection of the incident light and increase the light absorption so that the efficiency of the solar cells can be increased. The experimental data shows that the optimized surface texturing has been obtained with 5 wt. % TMAH anisotropic etching at 80 °C. The surface reflectance of the polished front surface can be reduced to 17 % and the surface reflectance of the unpolished backside surface can be reduced to 3 %, respectively. This result shows that the anisotropic etching can effectively reduce the surface reflectance. While for the surface texturing with KOH/IPA mixture, the front surface reflectance can only be reduced to 35 % and the backside surface reflectance can only be reduced to 5 %, respectively. Besides, debris of Si nano-crystals exists around the pyramid base area when texturing with the KOH/IPA mixture.
Passivity-based control applied to the dynamic positioning of ships

A family of passivity-based controllers for dynamic positioning of ships is presented. The authors exploit the idea of shaping the energy function of the closed-loop system to obtain different formulations of the passivity-based control law using the interconnection and damping assignment-passivity-based control (IDA-PBC) methodology. A salient feature of this study is that the proposed control laws are output feedback controllers and the relative velocity measurement is not required. First, we design and analyse two static controllers which can be seen as a non-linear version of the conventional proportional-derivative (PD) controllers. In presence of unknown disturbances, these controllers do not provide the desired regulation properties. To remove this discrepancy we propose, also in the context of the IDA-PBC technique, a dynamic extension of the system and obtain two new controllers that have the desired regulation properties. These new control laws can be seen as a non-linear version of the conventional proportional-integral-derivative (PID) controllers. Simulations are included to validate the theoretical results.
Mixture-model based estimation of gene expression variance from public database improves identification of differentially expressed genes in small sized microarray data

Motivation: The small number of samples in many microarray experiments is a challenge for the correct identification of differentially expressed gens (DEGs) by conventional statistical means. Information from public microarray databases can help more efficient identification of DEGs. To model various experimental conditions of a public microarray database, we applied Gaussian mixture model and extracted bi- or tri-modal distributions of gene expression. Prior variance of Baldi's Bayesian framework was estimate for the analysis of the small sample-sized datasets. Results: First, we estimated the prior variance of a gene expression by pooling variances obtained from mixture modeling of large samples in the public microarray database. Then, using the prior variance, we identified DEGs in small sample-sized test datasets using the Baldi's framework. For benchmark study, we generated test datasets having several samples from relatively large datasets. Our proposed method outperformed other benchmark methods in terms of detecting gold-standard DEGs from the test datasets. The results may be a challenging evidence for usage of public microarray databases in microarray data analysis. Availability: Supplementary data are available at http://www.snubi. org/publication/MixBayes Contact: juhan@snu.ac. kr
Structural Parameter Identification Based on Equivalent Single Degree Systems

In order to solve the problems of optimization algorithm used to identify the physical parameters of structures, a new method based on a series of equivalent single degree systems is proposed in this paper. The key idea of the method is that a multi-degree system can be represented by a series of single degree systems that can be identified one by one to perform the identification of the whole system. This method can not only decrease the dimensions of optimization algorithm, but also reduce the amount of estimation work in searching for the bound of parameters, and at the same time improve the identification results when parameters might suddenly change. In the numerical simulation of the physical parameter identification of a multi-degree system, Differential evolution is one of the optimization algorithm methods which are used to identify a series of equivalent single degree systems instead of the multi-degree system they represent, and the identification results prove that the method proposed in this paper is valid.
Futures Trading: Design of a Strategy

The paper describes the futures trading and aims to design the speculators trading strategy. The problem is formulated as the decision making task and such as is solved. The solution of the task leads to complex mathematical problems and the approximations of the decision making is demanded. Two kind of approximation are used in the paper: Monte Carlo for the multi-step prediction and iteration spread in time for the optimization. The solution is applied to the real-market data and the results of the off-line experiments are presented. Keywords—futures trading, decision making
Hepatitis C Virus (HCV) Genotype 1 Subtype Identification in New HCV Drug Development and Future Clinical Practice

Background With the development of new specific inhibitors of hepatitis C virus (HCV) enzymes and functions that may yield different antiviral responses and resistance profiles according to the HCV subtype, correct HCV genotype 1 subtype identification is mandatory in clinical trials for stratification and interpretation purposes and will likely become necessary in future clinical practice. The goal of this study was to identify the appropriate molecular tool(s) for accurate HCV genotype 1 subtype determination. Methodology/Principal Findings A large cohort of 500 treatment-naïve patients eligible for HCV drug trials and infected with either subtype 1a or 1b was studied. Methods based on the sole analysis of the 5′ non-coding region (5′NCR) by sequence analysis or reverse hybridization failed to correctly identify HCV subtype 1a in 22.8%–29.5% of cases, and HCV subtype 1b in 9.5%–8.7% of cases. Natural polymorphisms at positions 107, 204 and/or 243 were responsible for mis-subtyping with these methods. A real-time PCR method using genotype- and subtype-specific primers and probes located in both the 5′NCR and the NS5B-coding region failed to correctly identify HCV genotype 1 subtype in approximately 10% of cases. The second-generation line probe assay, a reverse hybridization assay that uses probes targeting both the 5′NCR and core-coding region, correctly identified HCV subtypes 1a and 1b in more than 99% of cases. Conclusions/Significance In the context of new HCV drug development, HCV genotyping methods based on the exclusive analysis of the 5′NCR should be avoided. The second-generation line probe assay is currently the best commercial assay for determination of HCV genotype 1 subtypes 1a and 1b in clinical trials and practice.
Simultaneous numerical optimization of the mechanical and electrical properties of polyaniline coated kenaf fiber using response surface methodology: nanostructured polyaniline on natural fiber

Response surface methodology was used to simultaneously optimize the electrical and mechanical properties of newly developed conducting biofibers made up of kenaf fiber/polyaniline (KF/PANI). The effect of process parameters such as PANI amount (1–10 wt.%), dopant concentration (5–25 N), and molar ratio of aniline/oxidant solutions (0.5–1.5) were studied using Design of Experiment. Both of the responses (electrical conductivity and unit break) obtained a quadratic model. The experimental values were in good agreement compared to the optimized process. The scanning electron microscope images of the optimized sample revealed uniform PANI component on the KF with nanofibrillar features.
On Numerical Simulations of Integrate-and-Fire Neural Networks

It is shown that very small time steps are required to reproduce correctly the synchronization properties of large networks of integrate-and-fire neurons when the differential system describing their dynamics is integrated with the standard Euler or second-order Runge-Kutta algorithms. The reason for that behavior is analyzed, and a simple improvement of these algorithms is proposed.
Acquiring Correct Knowledge for Natural Language Generation

Natural language generation (NLG) systems are computer software systems that produce texts in English and other human languages, often from non-linguistic input data. NLG systems, like most ai systems, need substantial amounts of knowledge. However, our experience in two NLG projects suggests that it is difficult to acquire correct knowledge for NLG systems; indeed, every knowledge acquisition (KA) technique we tried had significant problems. In general terms, these problems were due to the complexity, novelty, and poorly understood nature of the tasks our systems attempted, and were worsened by the fact that people write so differently. This meant in particular that corpus-based KA approaches suffered because it was impossible to assemble a sizable corpus of high-quality consistent manually written texts in our domains; and structured expert-oriented KA techniques suffered because experts disagreed and because we could not get enough information about special and unusual cases to build robust systems. We believe that such problems are likely to affect many other NLG systems as well. In the long term, we hope that new KA techniques may emerge to help NLG system builders. In the shorter term, we believe that understanding how individual KA techniques can fail, and using a mixture of different KA techniques with different strengths and weaknesses, can help developers acquire NLG knowledge that is mostly correct.
Children's peer assessment and self-disclosure in the presence of an educational robot

Research in education has long established how children mutually influence and support each other's learning trajectories, eventually leading to the development and widespread use of learning methods based on peer activities. In order to explore children's learning behavior in the presence of a robotic facilitator during a collaborative writing activity, we investigated how they assess their peers in two specific group learning situations: peer-tutoring and peer-learning. Our scenario comprises of a pair of children performing a collaborative activity involving the act of writing a word/letter on a tactile tablet. In the peer-tutoring condition, one child acts as the teacher and the other as the learner, while in the peer-learning condition, both children are learners without the attribution of any specific role. Our experiment includes 40 children in total (between 6 and 8 years old) over the two conditions, each time in the presence of a robot facilitator. Our results suggest that the peer-tutoring situation leads to significantly more corrective feedback being provided, as well as the children more disposed to self-disclosure to the robot.
Data Analysis Project : Semi-Supervised Discovery of Named Entities and Relations from the Web

This project studies semi-supervised discovery of named entities, relational entities and prepositional phrase attachments within a read-the-web framework. Meanings of an entity can be improvised and updated faster in the internet world than printed references. The main idea of this project is to study the feasibility of characterizing entities by web content directly. The approach is that contextual words around an entity on web pages are first extracted and converted into a Bag-Of-Word (BOW) representation. We then apply several supervised and semi-supervised learning methods on top of these contextual words for several well known research problems: Named Entities Recognition, Relation Extraction and Prepositional Phrase Attachment.
Spread of ropivacaine by a weight‐based formula in a pediatric caudal block: a fluoroscopic examination

Background: Caudal block is the most common regional technique to provide post‐operative analgesia in pediatric infra‐umbilical surgery. This study was designed to define how many spinal segments would be covered by the weight‐based dosage of caudally administered 0.2% ropivacaine in children using the fluoroscopic method.
Mapping the Number of Molecules and Brightness in the Laser Scanning Microscope

We describe a technique based on moment-analysis for the measurement of the average number of molecules and brightness in each pixel in fluorescence microscopy images. The average brightness of the particle is obtained from the ratio of the variance to the average intensity at each pixel. To obtain the average number of fluctuating particles, we divide the average intensity at one pixel by the brightness. This analysis can be used in a wide range of concentrations. In cells, the intensity at any given pixel may be due to bright immobile structures, dim fast diffusing particles, and to autofluorescence or scattering. The total variance is given by the variance of each of the above components in addition to the variance due to detector noise. Assuming that all sources of variance are independent, the total variance is the sum of the variances of the individual components. The variance due to the particles fluctuating in the observation volume is proportional to the square of the particle brightness while the variance of the immobile fraction, the autofluorescence, scattering, and that of the detector is proportional to the intensity of these components. Only the fluctuations that depend on the square of the brightness (the mobile particles) will have a ratio of the variance to the intensity >1. Furthermore, changing the fluorescence intensity by increasing the illumination power, distinguishes between these possible contributions. We show maps of molecular brightness and number of cell migration proteins obtained using a two-photon scanning microscope operating with a photon-counting detector. These brightness maps reveal binding dynamics at the focal adhesions with pixel resolution and provide a picture of the binding and unbinding process in which dim molecules attach to the adhesions or large molecular aggregates dissociate from adhesion.