Miracle-dz/UniFAR-FTUs huggingface dataset:
Severe Viral Gastroenteritis in Children After Suboptimal Rotavirus Immunization in Taiwan

Background: The study aimed to investigate the molecular epidemiology of severe viral gastroenteritis (AGE) in children in Taiwan after the implementation of the rotavirus vaccine in the private sector. Methods: Fecal samples from hospitalized children with severe AGE from April 2004 to March 2011 were examined by reverse transcription-polymerase chain reaction or polymerase chain reaction to identify enteric viral pathogens. The study period was divided to prevaccine (before September 2006) and postvaccine (after October 2006) periods. The prevalence of enteric viruses between the 2 periods was analyzed. The disease burdens of rotavirus- and norovirus-associated diseases were assessed according to vaccine implementation status and were adjusted for age. Results: A total of 755 stool samples were collected from hospitalized patients with AGE; enteric viruses were identified in 586 patients (77.6%), including 44 with concomitant bacterial infection. Viral enteric infection by rotavirus, norovirus, astrovirus, sapovirus, enteric adenovirus, multiple viruses and bacterial coinfections were found in 216 (28.6%), 128 (17.0%), 24 (3.2%), 6 (0.8%), 69 (9.1 %), 99 (13.1%) and 44 (5.8%) patients, respectively. A significant increase of norovirus infection was found in the postvaccine period (P < 0.001); on the other hand, rotavirus infection in infants has been reduced substainally (P = 0.056) and the annual peak of rotavirus infection has gradually become less prominent, with a significant decline of coinfection of rotavirus with other pathogens. Conclusions: Suboptimal use of rotavirus vaccines in the private sector caused a slow but modest impact on severe rotavirus AGE, whereas norovirus infection became more common.
Noise-Robust Speech Features Based on Cepstral Time Coefficients

In this paper, we investigate the noise-robustness of features based on the cepstral time coefficients (CTC). By cepstral time coefficients, we mean the coefficients obtained from applying the discrete cosine transform to the commonly used mel-frequency cepstral coefficients (MFCC). Furthermore, we apply temporal filters used for computing delta and acceleration dynamic features to the CTC, resulting in delta and acceleration features in the frequency domain. We experiment with five different variations of such CTC-based features. The evaluation is done on the Aurora 3 noisy digit recognition tasks with four different languages. The results show all but one such feature set performance gain, the other feature sets actually lead to performance gains. The best feature set achieves an improvement of 25% over the baseline feature set of MFCC.
Laminar Flame Characteristics of C1–C5 Primary Alcohol-Isooctane Blends at Elevated Temperature

The laminar combustion characteristics of blends of isooctane and C1–C5 primary alcohols (i.e., methanol, ethanol, n -propanol, n -butanol and n -pentanol) were investigated using the spherical expanding flame methodology in a constant volume chamber at various equivalence ratios and volume fractions of alcohol. The stretch effect was removed using the nonlinear methodology. The results indicate that the laminar flame speeds of alcohol-isooctane blends increase monotonously with the increasing volume fraction of alcohol. Among the five alcohols, the addition of methanol is identified to be the most effective in enhancing laminar flame speed. The addition of ethanol results in an approximately equivalent laminar flame speed enhancement rate as those of n -propanol, n -butanol and n -pentanol at ratios of 0.8 and 1.5, and a higher rate at 1.0 and 1.2. An empirical correlation is provided to describe the laminar flame speed variation with the volume fraction of alcohol. Meanwhile, the laminar flame speed increases with the mass content of oxygen in the fuel blends. At the equivalence ratio of 0.8 and fixed oxygen content, similar laminar flame speeds are observed with different alcohols blended into isooctane. Nevertheless, with the increase of equivalence ratio, heavier alcohol-isooctane blends tend to exhibit higher values. Markstein lengths of alcohol-isooctane blends decrease with the addition of alcohol into isooctane at 0.8, 1.0 and 1.2, however they increase at 1.5. This is consistent with the behavior deduced from the Schlieren images.
Using predictions from a joint model for longitudinal and survival data to inform the optimal time of intervention in an abdominal aortic aneurysm screening programme

Joint models of longitudinal and survival data can be used to predict the risk of a future event occurring based on the evolution of an endogenous biomarker measured repeatedly over time. This has led naturally to the use of dynamic predictions that update each time a new longitudinal measurement is provided. In this paper, we show how such predictions can be utilised within a fuller decision modelling framework, in particular to allow planning of future interventions for patients under a ‘watchful waiting’ care pathway. Through the objective of maximising expected life‐years, the predicted risks associated with not intervening (e.g. the occurrence of severe sequelae) are balanced against risks associated with the intervention (e.g. operative risks). Our example involves patients under surveillance in an abdominal aortic aneurysm screening programme where a joint longitudinal and survival model is used to associate longitudinal measurements of aortic diameter with the risk of aneurysm rupture. We illustrate how the decision to intervene, which is currently based on a diameter measurement greater than a certain threshold, could be made more personalised and dynamic through the application of a decision modelling approach.
Hydrocephalus Is a Determinant of Early Mortality in Putaminal Hemorrhage

Background and Purpose Previous studies have shown that the volume of intracerebral hemorrhage and Glasgow Coma Score (GCS) on admission are powerful predictors of 30-day mortality. However, the significance of hydrocephalus associated with deep cerebral hemorrhage has not been studied extensively. The purpose of this study was to determine the prognostic indicators of 30-day mortality in patients with deep cerebral hemorrhage. Methods We studied 100 consecutive patients with deep cerebral hemorrhage between 1994 and 1998. Deep cerebral hemorrhage was divided into 2 groups: putaminal hemorrhage (lateral group) and thalamic and caudate hemorrhage (medial group). Univariate and multivariate logistic regression analyses were performed to determine independent prognostic indicators of 30-day mortality. Results Hydrocephalus was present in 40 of the 100 patients. The 30-day mortality was 29%, and hydrocephalus was present in 76% of those who died. Multivariate analyses showed 2 independent prognostic indicators of 30-day mortality for putaminal hemorrhage: GCS ≤8 (P =0.002, odds ratio [OR] 37.7, CI 3.6 to 396.9) and hydrocephalus (P =0.005, OR 27.4, CI 2.7 to 282.6). However, only GCS ≤8 (P =0.0002, OR 16.5, CI 3.7 to 73.4) was predictive of 30-day mortality for thalamic and caudate hemorrhage. This model (GCS ≤8 and hydrocephalus) has a sensitivity of 57% and a specificity of 91% for predicting 30-day mortality for putaminal hemorrhage. When both attributes were present in putaminal hemorrhage (GCS ≤8 and hydrocephalus), 1 (11%) of 9 patients survived, and when both attributes were missing 28 (100%) of 28 patients survived. Conclusions Obstructive hydrocephalus on admission in a comatose patient with a putaminal hemorrhage predicts 30-day mortality.
Influence of hydrogen-consuming bacteria on cellulose degradation by anaerobic fungi

The presence of methanogens Methanobacterium arboriphilus, Methanobacterium bryantii, or Methanobrevibacter smithii increased the level of cellulose fermentation by 5 to 10% in cultures of several genera of anaerobic fungi. When Neocallimastix sp. strain L2 was grown in coculture with methanogens the rate of cellulose fermentation also increased relative to that for pure cultures of the fungus. Methanogens caused a shift in the fermentation products to more acetate and less lactate, succinate, and ethanol. Formate transfer in cocultures of anaerobic fungi and M. smithii did not result in further stimulation of cellulolysis above the level caused by H2 transfer. When Selenomonas ruminatium was used as a H2-consuming organism in coculture with Neocallimastix sp. strain L2, both the rate and level of cellulolysis increased. The observed influence of the presence of methanogens is interpreted to indicate a shift of electrons from the formation of electron sink carbon products to H2 via reduced pyridine nucleotides, favoring the production of additional acetate and probably ATP. It is not known how S. ruminantium exerts its influence. It might result from a lowered production of electron sink products by the fungus, from consumption of electron sink products or H2 by S. ruminantium, or from competition for free sugars which in pure culture could exert an inhibiting effect on cellulolysis.
Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network

A Chebyshev polynomial-based unified model (CPBUM) neural network is introduced and applied to control a magnetic bearing systems. First, we show that the CPBUM neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional feedforward/recurrent neural network. It turns out that the CPBUM neural network is more suitable in the design of controller than the conventional feedforward/recurrent neural network. Second, we propose the inverse system method, based on the CPBUM neural networks, to control a magnetic bearing system. The proposed controller has two structures; namely, off-line and on-line learning structures. We derive a new learning algorithm for each proposed structure. The experimental results show that the proposed neural network architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.
Analysis of the Arabinose-5-Phosphate Isomerase of Bacteroides fragilis Provides Insight into Regulation of Single-Domain Arabinose Phosphate Isomerases

ABSTRACT Arabinose-5-phosphate isomerases (APIs) catalyze the interconversion of d-ribulose-5-phosphate and d-arabinose-5-phosphate, the first step in the biosynthesis of 3-deoxy-d-manno-octulosonic acid (Kdo), an essential component of the lipopolysaccharide in Gram-negative bacteria. Classical APIs, such as Escherichia coli KdsD, contain a sugar isomerase domain and a tandem cystathionine beta-synthase domain. Despite substantial effort, little is known about structure-function relationships in these APIs. We recently reported an API containing only a sugar isomerase domain. This protein, c3406 from E. coli CFT073, has no known physiological function. In this study, we investigated a putative single-domain API from the anaerobic Gram-negative bacterium Bacteroides fragilis. This putative API (UniProt ID Q5LIW1) is the only protein encoded by the B. fragilis genome with significant identity to any known API, suggesting that it is responsible for lipopolysaccharide biosynthesis in B. fragilis. We tested this hypothesis by preparing recombinant Q5LIW1 protein (here referred to by the UniProt ID Q5LIW1), characterizing its API activity in vitro, and demonstrating that the gene encoding Q5LIW1 (GenBank ID YP_209877.1) was able to complement an API-deficient E. coli strain. We demonstrated that Q5LIW1 is inhibited by cytidine 5′-monophospho-3-deoxy-d-manno-2-octulosonic acid, the final product of the Kdo biosynthesis pathway, with a Ki of 1.91 μM. These results support the assertion that Q5LIW1 is the API that supports lipopolysaccharide biosynthesis in B. fragilis and is subject to feedback regulation by CMP-Kdo. The sugar isomerase domain of E. coli KdsD, lacking the two cystathionine beta-synthase domains, demonstrated API activity and was further characterized. These results suggest that Q5LIW1 may be a suitable system to study API structure-function relationships.
Unbiased Regression Trees for Longitudinal and Clustered Data

A new version of the RE-EM regression tree method for longitudinal and clustered data is presented. The RE-EM tree is a methodology that combines the structure of mixed effects models for longitudinal and clustered data with the flexibility of tree-based estimation methods. The RE-EM tree is less sensitive to parametric assumptions and provides improved predictive power compared to linear models with random effects and regression trees without random effects. The previously-suggested methodology used the CART tree algorithm for tree building, and therefore that RE-EM regression tree method inherits the tendency of CART to split on variables with more possible split points at the expense of those with fewer split points. A revised version of the RE-EM regression tree corrects for this bias by using the conditional inference tree as the underlying tree algorithm instead of CART. Simulation studies show that the new version is indeed unbiased, and has several improvements over the original RE-EM regression tree in terms of prediction accuracy and the ability to recover the correct tree structure.
On k-set consensus problems in asynchronous systems

In this paper, we investigate the k-set consensus problem in asynchronous distributed systems. In this problem, each participating process begins the protocol with an input value and by the end of the protocol must decide on one value so that at most k total values are decided by all correct processes. We extend previous work by exploring several variations of the problem definition and model, including for the first time investigation of Byzantine failures. We show that the precise definition of the validity requirement, which characterizes what decision values are allowed as a function of the input values and whether failures occur, is crucial to the solvability of the problem. For example, we show that allowing default decisions in case of failures makes the problem solvable for most values of k despite a minority of failures, even in face of the most severe type of failures (Byzantine). We introduce six validity conditions for this problem (all considered in various contexts in the literature), and demarcate the line between possible and impossible for each case. In many cases, this line is different from the one of the originally studied k-set consensus problem. Index Terms—Agreement problems, Byzantine failures, consensus, crash failures, distributed systems, validity conditions. E
Repeating a Classic Set of Experiments on Size Effect in Shear of Members without Stirrups

The shear tests performed by Bazant and Kazemi in 1991 have been cited as strong evidence that the theory of fracture mechanics applies to the shear strength of beams without stirrups. It has also been noted in the past, however, that these results are not totally consistent with other size effect experimental series. This paper provides a detailed summary of duplicate experiments carried out to determine if the original 1991 results were reproducible. It was found that the repeat experiments were 31 to 70% stronger than the original results. All experimental results were stronger than the predictions of the ACI and CSA codes. Cracks patterns were observed to scale with the beam size. A comparison of historical data indicated that the higher strengths were likely not a result of random variation, but due to a systematic effect in the original testing, making them inconsistent with other tests. Potential reasons for the differences from the 1991 results are presented and discussed.
Exploiting prolific types for memory management and optimizations

In this paper, we introduce the notion of prolific and non-prolific types, based on the number of instantiated objects of those types. We demonstrate that distinguishing between these types enables a new class of techniques for memory management and data locality, and facilitates the deployment of known techniques. Specifically, we first present a new type-based approach to garbage collection that has similar attributes but lower cost than generational collection. Then we describe the short type pointer technique for reducing memory requirements of objects (data) used by the program. We also discuss techniques to facilitate the recycling of prolific objects and to simplify object co-allocation decisions.We evaluate the first two techniques on a standard set of Java benchmarks (SPECjvm98 and SPECjbb2000). An implementation of the type-based collector in the Jalapeño VM shows improved pause times, elimination of unnecessary write barriers, and reduction in garbage collection time (compared to the analogous generational collector) by up to 15%. A study to evaluate the benefits of the short-type pointer technique shows a potential reduction in the heap space requirements of programs by up to 16%.
Exploring Students' Knowledge Construction Strategies in Computer-Supported Collaborative Learning Discussions Using Sequential Analysis

Online collaborative learning allows discussion to occur at greater depth where knowledge can be constructed remotely. However students were found to construct knowledge at low-level where they discussed by sharing and comparing opinions; those are inadequate for new knowledge creation. As such, this research attempted to investigate the students' behaviour and their strategies to construct knowledge during online collaborative discussions. Using the combination of content analysis and sequential analysis technique, this research found that groups those being able to construct high-level knowledge tend to negotiate on shared information. Argumentation is also found to contribute for successful knowledge construction at higher-level. This study suggests triggering argumentation and emphasizing on problem-solving tasks for better knowledge construction sustainability.
USING THE AMOVA FRAMEWORK TO ESTIMATE A STANDARDIZED GENETIC DIFFERENTIATION MEASURE

Abstract Comparison of population structure between studies can be difficult, because the value of the often-used FST-statistic depends on the amount of genetic variation within populations. Recently, a standardized measure of genetic differentiation was developed based on GST, which addressed this problem, though no method was provided to estimate this standardized measure without bias. Here I present a method to estimate a standardized measure of population differentiation based on the analysis of molecular variance framework. One advantage of the method is that it can be readily expanded to include different hierarchical levels in the tested population structure.
Radiation therapy for choroid plexus carcinoma patients with Li-Fraumeni syndrome: advantageous or detrimental?

BACKGROUND Choroid plexus carcinomas (CPCs) are rare pediatric tumors often associated with Li-Fraumeni Syndrome (LFS), a germline mutation in the TP53 tumor-suppressor gene, predisposing to cancer. MATERIALS AND METHODS We performed a systemic literature review from 1990-2013 to evaluate the hypothesis that radiation therapy should be avoided in patients with CPC and LFS. Overall survival (OS) was compared using Kaplan-Meier curves and log-rank tests. RESULTS Twenty-eight patients were documented with CPC and LFS. Eleven out of 17 patients received radiation therapy. The survival of patients receiving radiation was inferior to that of those without radiation [median (±95% confidence interval) 2-year OS=0.18 ± 0.12% versus 0.58 ± 0.12%]. The log-rank tests suggested the difference to be marginally significant (p=0.056). CONCLUSION This finding provides evidence for pursuing treatment approaches that do not include radiation therapy for patients with LFS.
Genetic Variability and Evolutionary Implications of RNA Silencing Suppressor Genes in RNA1 of Sweet Potato Chlorotic Stunt Virus Isolates Infecting Sweetpotato and Related Wild Species

Background The bipartite single-stranded RNA genome of Sweet potato chlorotic stunt virus (SPCSV, genus Crinivirus; Closteroviridae) encodes a Class 1 RNase III (RNase3), a putative hydrophobic protein (p7) and a 22-kDa protein (p22) from genes located in RNA1. RNase3 and p22 suppress RNA silencing, the basal antiviral defence mechanism in plants. RNase3 is sufficient to render sweetpotato (Ipomoea batatas) virus-susceptible and predisposes it to development of severe diseases following infection with unrelated virus. The incidence, strains and gene content of SPCSV infecting wild plant species have not been studied. Methodology/Principal Findings Thirty SPCSV isolates were characterized from 10 wild Ipomoea species, Hewittia sublobata or Lepistemon owariensis (family Convolvulaceae) in Uganda and compared with 34 local SPCSV isolates infecting sweetpotatoes. All isolates belonged to the East African (EA) strain of SPCSV and contained RNase3 and p7, but p22 was not detected in six isolates. The three genes showed only limited genetic variability and the proteins were under purifying selection. SPCSV isolates lacking p22 synergized with Sweet potato feathery mottle virus (SPFMV, genus potyvirus; Potyviridae) and caused severe symptoms in co-infected sweetpotato plants. One SPCSV isolate enhanced accumulation of SPFMV, but no severe symptoms developed. A new whitefly-transmitted virus (KML33b) encoding an RNase3 homolog (<56% identity to SPCSV RNase3) able to suppresses sense-mediated RNA silencing was detected in I. sinensis. Conclusions/Significance SPCSV isolates infecting wild species and sweetpotato in Uganda were genetically undifferentiated, suggesting inter-species transmission of SPCSV. Most isolates in Uganda contained p22, unlike SPCSV isolates characterized from other countries and continents. Enhanced accumulation of SPFMV and increased disease severity were found to be uncoupled phenotypic outcomes of RNase3-mediated viral synergism in sweetpotato. A second virus encoding an RNase3-like RNA silencing suppressor was detected. Overall, results provided many novel and important insights into evolutionary biology of SPCSV.
A constitutive model for shape memory polymers with application to torsion of prismatic bars

In this article, satisfying the second law of thermodynamics, we present a 3D constitutive model for shape memory polymers. The model is based on an additive decomposition of the strain into four parts. Also, evolution laws for internal variables during both cooling and heating processes are proposed. Since temperature has considerable effect on the shape memory polymer behavior, for simulation of a shape memory polymer–based structure, it is required to perform a heat-transfer analysis. Commonly, an experimentally observed temperature rate–dependent behavior of shape memory polymers is justified by a rate-dependent glassy temperature, but using the heat-transfer analysis, it is shown that the glassy temperature could be considered as a constant material parameter. To this end, implementing the constitutive model within a nonlinear finite element code, we simulate torsion of a shape memory polymer rectangular bar and a circular tube. Moreover, we compare the predicted results with experimental data recently reported in the literature, which shows a good agreement.
Validating and Extending Semantic Knowledge Bases using Video Games with a Purpose

Large-scale knowledge bases are important assets in NLP. Frequently, such resources are constructed through automatic mergers of complementary resources, such as WordNet and Wikipedia. However, manually validating these resources is pro-hibitively expensive, even when using methods such as crowdsourcing. We pro-pose a cost-effective method of validating and extending knowledge bases using video games with a purpose. Two video games were created to validate concept-concept and concept-image relations. In experiments comparing with crowdsourcing, we show that video game-based validation consistently leads to higher-quality annotations, even when players are not compensated.