Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the levels of endotoxin and β-d-glucan in the synovial fluid of hemodialysis patients

Abstract We analyzed the levels of endotoxin and β-d-glucan, which possibly induce cytokine production, in the synovial fluid of patients on long-term hemodialysis and compared the results to those in patients with osteoarthritis and rheumatoid arthritis. We studied 42 knees in 42 hemodialysis patients, 21 in 21 osteoarthritis patients, and 26 in 26 rheumatoid arthritis patients. The mean ages were 60.7, 63.2, and 59.7 years, respectively. The duration of hemodialysis in the long-term hemodialysis group averaged 14.0 years. The concentrations of endotoxin and β-d-glucan in the synovial fluid of these three groups were measured. The concentration of endotoxin was the same in the three groups. However, the concentration of β-d-glucan was significantly higher in long-term hemodialysis patients. This finding suggests that β-d-glucan may have some relation to the pathogenesis of the synovitis which exists in the hydrarthrosis of long-term hemodialysis patients.
A Semantic Approach for Semi-Automatic Detection of Sensitive Data

This article proposes an innovative approach and its implementation as an expert system to achieve the semi-automatic detection of candidate attributes for scrambling sensitive data. Its approach is based on semantic rules that determine which concepts have to be scrambled, and on a linguistic component that retrieves the attributes that semantically correspond to these concepts. Because attributes cannot be considered independently from each other, it also addresses the challenging problem of the propagation of the scrambling process through the entire database. One main contribution of this article's approach is to provide a semi-automatic process for the detection of sensitive data. The underlying knowledge is made available through production rules operationalizing the detection of the sensitive data. A validation of its approach using four different databases is provided.
Analytical model for jitter in networks with IPP traffic

In this paper we analyze jitter behavior for Interrupted Poisson process (IPP) as incoming traffic. We propose model for jitter on one node, as well as for end-to-end jitter with IPP traffic on network nodes. Our model describes jitter behavior with respect to phase probabilities, traffic load, and tagged traffic share in aggregate traffic flow. We conclude that jitter for IPP is heavily dependent on phase probabilities, and larger than jitter for Poisson process, as one limit case of IPP. End-to-end jitter always takes values between first node jitter value and sum of individual jitter values on each node. We offer more precise evaluation of these values, which also leads to some fast-to-compute approximations for limit cases of phase probabilities and traffic load. We propose our results as guidelines for jitter evaluation for real IP traffic.
Rater Experience, Rating Scale Length, and Judgments of L2 Pronunciation: Revisiting Research Conventions

This mixed-methods study examines the effects of rating scale length and rater experience on listeners' judgments of second-language (L2) speech. Twenty experienced and 20 novice raters, who were randomly assigned to 5-point or 9-point rating scale conditions, judged speech samples of 38 newcomers to Canada on numerical rating scales for comprehensibility, accentedness, and fluency. Results yielded high Cronbach's alpha coefficients and no group differences for rating scale length or rater experience. However, Rasch category probability plots revealed that raters had difficulty differentiating between scale steps, particularly in mid-scale range—a challenge that was exacerbated in the 9-point scale condition. Evidence from verbal protocols and posttask interviews suggested that experienced and novice raters adopted strategies to either draw on or offset their perceived experience with L2 speech in conducting their ratings. Implications for L2 pronunciation research are discussed, including the need to draw on raters' perceptions to develop a greater understanding of major listener perceptual constructs in L2 pronunciation and to move beyond adherence to the native speaking standard in data collection procedures.
Distributed distance matrix generator based on agents

The process of calculating similarities between different time series of a dataset -- i.e. a distance matrix -- is often very time-consuming, but can be sped-up significantly using distributed programming. This paper presents a distributed system for calculating the distance matrix that utilizes the agent technology. Software agents are employed to deal with dynamic properties of the computational network, such as sudden unavailability of a number of computers, as well as for load-balancing and task-sharing.
An O(mlogn) Algorithm for Computing Stuttering Equivalence and Branching Bisimulation

We provide a new algorithm to determine stuttering equivalence with time complexity O(mlogn), where n is the number of states and m is the number of transitions of a Kripke structure. This algorithm can also be used to determine branching bisimulation in O(m(log |Act| + log n)) time, where Act is the set of actions in a labeled transition system. Theoretically, our algorithm substantially improves upon existing algorithms, which all have time complexity of the form O(mn) at best. Moreover, it has better or equal space complexity. Practical results confirm these findings: they show that our algorithm can outperform existing algorithms by several orders of magnitude, especially when the Kripke structures are large. The importance of our algorithm stretches far beyond stuttering equivalence and branching bisimulation. The known O(mn) algorithms were already far more efficient (both in space and time) than most other algorithms to determine behavioral equivalences (including weak bisimulation), and therefore they were often used as an essential preprocessing step. This new algorithm makes this use of stuttering equivalence and branching bisimulation even more attractive.
Children’s acquisition of word order depends on syntactic/semantic role: Evidence from adjective-noun order

Based on research on children’s verb production, Usage-Based theorists have argued that children learn grammatical abstractions in the preschool years. The fact that, in English verb clauses, word order determines semantic/syntactic roles leaves open the possibility that children are learning not just syntactic frames, but the relationship between order and semantic/syntactic roles. To clarify the nature of children’s abstract knowledge, we taught novel adjectives to English-speaking children (2 to 4 years), both prenominally and postnominally. Unlike verbs, adjective position in a sentence does not change the semantic/syntactic role of the adjective. Children showed sensitivity to the canonical order, but even four-year-olds frequently used novel adjectives postnominally. We argue that a strong motivation for ordering words grammatically is when order determines semantic/syntactic roles.
Counting Process Models for Infectious Disease Data: Distinguishing Exposure to Infection from Susceptibility

SUMMARY Differences in infection rates among types of individuals within a population can arise from differences in amount of exposure to infection or from differences in susceptibility to infection. We derive models for infection rates that incorporate contact rates between individuals and variables affecting susceptibility to infection. We emphasize the distinction between controlling for exposure opportunity (expected exposure) and actual exposure. We present a marked counting process model for the combined contact and infection transmission processes. When the contact process is not observable, we develop thinned counting process models that reduce to a proportional hazards model. We show that the different commonly used parameters for evaluating covariate effects, such as vaccine efficacy, form a hierarchy depending on the amount of information available about the components of the transmission system.
High‐fat diet ameliorates neurological deficits caused by defective astrocyte lipid metabolism

The mammalian CNS is considered to be autonomous in lipid metabolism. Glial cells, in particular astrocytes, have been shown to be highly active in lipid synthesis and secretion. To determine the importance of astrocytes as lipid providers in the brain, we generated mice in which the sterol regulatory element‐binding protein (SREBP) cleavage‐activating protein (SCAP) was deleted from astrocytes using cre/lox technology. SCAP mutant mice showed microcephaly, without effects on astrocyte survival. SCAP deletion in astrocytes led to a loss of cholesterol and fatty acid synthesis pathways. SCAP mutants showed progressive motor deficits, dyskinesia, and reduced anxiety. Interestingly, SCAP mutants showed changes in brain sterol and fatty acid profiles that were concordant with reduced lipid synthesis as well as with increased uptake of dietary lipids. Accordingly, a high‐fat diet rich in cholesterol and monounsaturated fatty acids, but not a fish oil diet rich in polyunsaturated fatty acids, improved motor deficits and survival of the mutant mice. These observations establish a critical role for astrocytes in brain lipid metabolism and demonstrate that dietary lipids can rescue astrocyte‐mediated lipid deficiency. The ability to correct these neurological deficits suggests that lipid supplementation may serve as a treatment for brain disorders associated with defective astrocyte lipid synthesis. —Camargo, N. , Brouwers, J. F. , Loos, M. , Gutmann, D. H. , Smit, A. B. , Verheijen, M. H. G. High‐fat diet ameliorates neurological deficits caused by defective astrocyte lipid metabolism. FASEB J. 26, 4302–4315 (2012). www.fasebj. org
Symbolic Execution for Verification

In previous work, we presented a symbolic execution method which starts with a concrete model of the program but progressively abstracts away details only when these are known to be irrelevant using interpolation. In this paper, we extend the technique to handle unbounded loops. The central idea is to progressively discover the strongest invariants through a process of loop unrolling. The key feature of this technique, called the minimax algorithm, is intelligent backtracking which directs the search for the next invariant. We then present an analysis of the main differences between our symbolic execution method and mainstream techniques mainly based on abstract refinement (CEGAR). Finally, we evaluate our technique against available state-of-the-art systems.
Visual, auditory, and somatosensory convergence on cells in superior colliculus results in multisensory integration.

Convergence of inputs from different sensory modalities onto individual neurons is a phenomenon that occurs widely throughout the brain at many phyletic levels and appears to represent a basic neural mechanism by which an organism integrates complex environmental stimuli. In the present study, neurons in the superior colliculus (SC) were used as a model to examine how single neurons deal with simultaneous cues from different sensory modalities (e.g., visual, auditory, somatosensory). The functional result of multisensory convergence on an individual cell was determined by comparing the responses evoked from it by a combined-modality (multimodal) stimulus with those elicited by each (unimodal) component of that stimulus presented alone. Superior colliculus cells exhibited profound changes in their activity when individual sensory stimuli were combined. These "multisensory interactions" were found to be widespread among deep laminae cells and fell into one of two functional categories: response enhancement, characterized by a significant increase in the number of discharges evoked; and response depression, characterized by a significant decrease in the discharges elicited. Multisensory response interactions most often reflected a multiplicative, rather than summative, change in activity. Their absolute magnitude varied from cell to cell and, when stimulus conditions were altered, within the same cell. However, the percentage change of enhanced interactions was generally inversely related to the vigor of the responses that could be evoked by presenting each unimodal stimulus alone and suggest that the potential for response amplification was greatest when responses evoked by individual stimuli were weakest. The majority of cells exhibiting multi-sensory characteristics were demonstrated to have descending efferent projections and thus had access to premotor and motor areas of the brain stem and spinal cord involved in SC-mediated attentive and orientation behaviors. These data show that multisensory convergence provides the descending efferent cells of the SC with a dynamic response character. The responses of these cells and the SC-mediated behaviors that they underlie need not be immutably tied to the presence of any single stimulus, but can vary in response to the particular complex of stimuli present in the environment at any given moment.
Divinity and Experience: The Religion of the Dinka

This study of the religion of Southern Sudan's Dinka people is now considered a minor classic of social anthropology. Lienhardt examines the complex meanings of divine imagery and relates these to the Dinkas' experience of life and death. From the role of priests to the translation of hymns, prayers, and myths, Lienhardt provides an unparalleled analysis and interpretation of this Sudanese religion.
Performance evaluation of an automatic web service composition architecture

Automatic Web service Composition (AWSC) is still a big challenge in service oriented architecture (SOA), since there is no platform where is possible to implement and test algorithms for AWSC. This paper presents the Automatic Web service composition Architecture (AWSCA), an architecture in which is possible to implement and run the algorithms for AWSC in an environment proposed for a fair comparison. To reach this objective is proposed a prototype that is able to deploy and execute Automated Composite Web services. This prototype consists of a tool which receives as input a graph with the description of the composite Web service flow, performs and controls the execution and interaction between the services. This approach makes possible to evaluate the performance and to compare the algorithms for AWSC in order to identify which one is a better choice for certain scenarios.
Telling English Tweets Apart : the Case of US , GB , AU

In this paper, we study how to automatically tell different varieties of English apart on Twitter by taking samples from American (US), British (GB) and Australian (AU) English. We track cities and apply filters to generate ground-truth data. We perform expert evaluation to get a sense of the difficulty of the task. We then cast the problem as a classification task: given a tweet (or a set of tweets from a user) in English, the goal is to automatically identify whether the tweet (or set of tweets) is US, GB or AU English. We perform experiments to compare some linguistic features against simple statistical features and show that character Ngrams are quite effective for the task. Our work is closely related to socio-linguistics, especially research on diatopic varieties, linguistic landscapes, and World Englishes [5].
Cellular localization , accumulation and trafficking of DWNTs in human prostate cancer cells

The carbon nanotubes (CNT) complexes (RNA-wrapped, oxidized DWNT) were endocytosed by capture in clathrin-coated vesicles, revealed by clear co-localization with both clathrin and transferrin. CNT complexes were also found in early endosomes, which was confirmed by co-localization with early endosome antigen (EEA). CNT complexes were not sorted for recycling back to the cell membrane (via fast recycling endosomes), as co-localization with Rab 4 was not observed. Instead, the overlapping of CNT complexes with both LAMP2 antibody and LysoTracker® marker indicated their sequestration in lysosomes. CNTs were also found within within vesicles of the secretory pathway (Rab11-positive vesicles), which for the first time suggests an exact route for their exocytosis.
Do Policies that Reduce Unemployment Raise its Volatility?: Evidence from OECD Countries

In this paper we examine whether past labour market reforms aiming at reducing the rate of unemployment have raised its long-run volatility. Using non-linear panel data models applied to 24 OECD countries between 1985 and 2007, as well as Monte-Carlo techniques, we do not find any evidence of such policy trade-off. In contrast, we find that reduced unemployment benefit duration, more competition-inducing product market regulation and looser employment protection legislation are associated with a weaker persistence of unemployment over time, which implies a lower volatility of unemployment in the long run. More specifically, the evidence suggests that even in the case of reforms that may have raised the shortterm sensitivity of unemployment to business cycles (such as with the easing of employment protection), the weaker persistence effect dominates the higher cyclical volatility, implying a net reduction in long-term volatility. Est-ce que les politiques qui reduisent le chomage augmentent sa volatilite ? : Une analyse empirique couvrant les pays de l'OCDE Cette etude examine dans quelle mesure les reformes passees du marche du travail visant a reduire le taux de chomage peuvent avoir eu pour effet d’accroitre sa volatilite. L’analyse empirique combinant l’estimation de modeles non-lineaires bases sur des donnees de panel couvrant 24 pays de l’OCDE sur la periode 1985-2007 et l’application de techniques de Monte Carlo, n’a pas mis a jour d’elements permettant d’etayer l’hypothese d’un tel conflit (trade-off) dans l’impact des politiques publiques du marche du travail. A l’inverse, l’etude montre qu’une reduction de la duree des benefices d’assurance chomage, une reforme de la reglementation conduisant a une plus forte concurrence sur le marche des produits et services, ainsi qu’un assouplissement de la legislation sur la protection de l’emploi entrainent une plus faible persistance du chomage, impliquant une plus faible volatilite a long terme. Meme dans les cas ou des reformes ont pu accroitre la sensibilite du chomage aux fluctuations cycliques, l’effet de cette plus grande variance cyclique sur la volatilite a long terme est plus que compensee par la baisse de la persistance.
A Time-Efficient Method for Anomaly Detection in Hyperspectral Images

We propose a computationally efficient method for determining anomalies in hyperspectral data. In the first stage of the algorithm, the background classes, which are the dominant classes in the image, are found. The method consists of robust clustering of a randomly chosen small percentage of the image pixels. The clusters are the representatives of the background classes. By using a subset of the pixels instead of the whole image, the computation is sped up, and the probability of including outliers in the background model is reduced. Anomalous pixels are the pixels with spectra that have large relative distances from the cluster centers. Several clustering techniques are investigated, and experimental results using realistic hyperspectral data are presented. A self-organizing map clustered using the local minima of the U-matrix (unified distance matrix) is identified as the most reliable method for background class extraction. The proposed algorithm for anomaly detection is evaluated using realistic hyperspectral data, is compared with a state-of-the-art anomaly detection algorithm, and is shown to perform significantly better.
Acute liver failure is associated with elevated liver stiffness and hepatic stellate cell activation

Acute liver failure (ALF) is associated with massive short‐term cell death, whereas chronic liver injury is accompanied by continuous cell death. Hepatic stellate cells (HSCs) contribute to tissue repair and liver fibrosis in chronic liver injury, although their role in ALF remains unexplained. Twenty‐nine patients (median age = 43 years, 17 females and 12 males) with ALF according to the Acute Liver Failure Study Group criteria were included. Upon the diagnosis of ALF and after 7 days, we determined liver stiffness (LS) with FibroScan, standard laboratory parameters, and serum levels of matrix metalloproteinase 1 (MMP‐1), MMP‐2, MMP‐9, tissue inhibitor of metalloproteinases 1 (TIMP‐1), TIMP‐2, hyaluronic acid, and markers of overall cell death (M65) and apoptosis (M30). Stellate cell activation and progenitor response were analyzed immunohistochemically in biopsy samples of 12 patients with α‐smooth muscle actin (α‐SMA), keratin‐17, and keratin‐19 staining, respectively. Cell death markers (M30 level = 2243 ± 559.6 U/L, M65 level = 3732 ± 839.9 U/L) and fibrosis markers (TIMP‐1 level = 629.9 ± 69.4 U/mL, MMP‐2 level = 264 ± 32.5 U/mL, hyaluronic acid level = 438.5 ± 69.3 μg/mL) were significantly increased in patients versus healthy controls. This was paralleled by collagen deposition, elevated α‐SMA expression, and higher LS (25.6 ± 3.0 kPa). ALF was associated with ductular progenitor proliferation. Conclusion: Our results demonstrate HSC activation and a progenitor response in ALF. Positive correlations between LS, the degree of liver cell damage, and the intensity of HSC activation suggest that fibrosis is a response to ALF in an attempt to repair damaged tissue. (Hepatology 2010)
The pure parsimony haplotyping problem: overview and computational advances

Haplotyping estimation from aligned single-nucleotide polymorphism fragments has attracted more and more attention in recent years due to its importance in analysis of many fine-scale genetic data. Its application fields range from mapping of complex disease genes to inferring population histories, passing through designing drugs, functional genomics, and pharmacogenetics. The literature proposes a number of estimation criteria to select a set of haplotypes among possible alternatives. Usually, such criteria can be expressed under the form of objective functions, and the sets of haplotypes that optimize them are referred to as optimal. One of the most important estimation criteria is the pure parsimony, which states that the optimal set of haplotypes for a given set of genotypes is that having minimal cardinality. Finding the minimal number of haplotypes necessary to explain a given set of genotypes involves solving an optimization problem, called the pure parsimony haplotyping (PPH) estimation problem, which is notoriously -hard. This article provides an overview of PPH, and discusses the different approaches to solution that occur in the literature.