Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Metapneumovirus as a Cause of Community-Acquired Respiratory Illness

Human metapneumovirus (HMPV) is a recently identified Paramyxovirus first isolated from hospitalized children with acute respiratory tract infections (ARTI). We sought evidence of HMPV infection in patients who had visited general practitioners, had influenzalike illnesses (ILI), and had negative tests for influenza and Human respiratory syncytial virus (HRSV). As part of national virologic surveillance, sentinel general practices in England and Wales collected samples from patients of all ages with ILI during winter 2000–01. Reverse transcriptase-polymerase chain reaction (PCR) for HMPV, influenza A (H1 and H3), influenza B, and HRSV was used to screen combined nose and throat swabs. PCR products from the HMPV-positive samples were sequenced to confirm identity and construct phylogenetic trees. Of 711 swabs submitted, 408 (57.3%) were negative for influenza and HRSV; HMPV was identified in 9 (2.2%) patients. HMPV appears to be associated with community-acquired ARTI. The extent of illness and possible complications related to this new human virus need to be clarified
Directed Search for Generalized Plans Using Classical Planners

We consider the problem of finding generalized plans for situations where the number of objects may be unknown and unbounded during planning. The input is a domain specification, a goal condition, and a class of concrete problem instances or initial states to be solved, expressed in an abstract first-order representation. Starting with an empty generalized plan, our overall approach is to incrementally increase the applicability of the plan by identifying a problem instance that it cannot solve, invoking a classical planner to solve that problem, generalizing the obtained solution and merging it back into the generalized plan. The main contributions of this paper are methods for (a) generating and solving small problem instances not yet covered by an existing generalized plan, (b) translating between concrete classical plans and abstract plan representations, and (c) extending partial generalized plans and increasing their applicability. We analyze the theoretical properties of these methods, prove their correctness, and illustrate experimentally their scalability. The resulting hybrid approach shows that solving only a few, small, classical planning problems can be sufficient to produce a generalized plan that applies to infinitely many problems with unknown numbers of objects.
Recent advances in electron and positron sources

Recent advances in electron and positron sources have resulted in new capabilities driven in most cases by the increasing demands of advanced accelerating systems. Electron sources for brighter beams and for high average-current beams are described. The status and remaining challenges for polarized electron beams are also discussed. For positron sources, recent activity in the development of polarized positron beams for future colliders is reviewed. Finally, a new proposal for combining laser cooling with beam polarization is presented.
Mechanisms for efficient multiprocessor combinator reduction

1. INTROI~CTION Over the past few years, there has been an increasing interest in multfprocessor reduction machines. The reason is the fact that these machines give the opportunity for efficient use of functional languages and powerful concepts naturally involved by these languages, such as higher order functions, stream processing and implicit parallelism. Furthermore, recent studies [9~12,19] have shown possible ways to use purely functional languages even to construct the operating system and the programming environment of a machine, at the cost of some minor additions (such as a HERCE operator). So, it has become realistic to base all the machine software on this kind of language. In this context, we are currently designing a multiprocessor architecture for a parallel reduction machine named MaRS, based on a combinator machine language. Since the seminal papers [21,22,23], several projects and studies close to our own have appeared, such as the SKIN2 processor [20], the DAPS model [13], the COBWEB project [11]. Other studies like the Rediflowmultiprocessor [17] or the Multilisp experiments [10], although involving different hypothesfes, are worth considering in this context. So, this paper will just describe briefly the MaRS machine, and focus on more original features which, as far as we know, do not appear in other projects. 2. H6,INFKATURKS OF u.nR The MaRS machine (standing for the French "Machine b R~duction Symbolique") is intended for the parallel execution of purely functional languages with no explicit primitive construct in the language to express parallelism. The underlying execution model is parallel graph reduction. The Permission to copy without fee all or part of thns material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publicauon and its date appear, and notice is given that copying ns by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specfic permission. default evaluation strategy is lazy evaluation with parallelism activated by some occurences of primitive functions. In order to increase parallelism, this strategy can be changed locally to call-by-value and eager evaluation, by means of optimizations made by the compiler, taking into account strictness analysis from primitives and programmer's annotations [4]. Annotations may be used optionally to indicate strict arguments of user functions. It should be noted that these user annotations are not algorithmic expression means, but mere pieces of /nformation for …
Representations of vertex operator algebras and braided finite tensor categories

We discuss what has been achieved in the past twenty years on the construction and study of a braided finite tensor category structure on a suitable module category for a suitable vertex operator algebra. We identify the main difficult parts in the construction, discuss the methods developed to overcome these difficulties and present some further problems that still need to be solved. We also choose to discuss three among the numerous applications of the construction.
Optimization of dynamic mobile robot path planning based on evolutionary methods

This paper presents evolutionary methods for optimization in dynamic mobile robot path planning. In dynamic mobile path planning, the goal is to find an optimal feasible path from starting point to target point with various obstacles, as well as smoothness and safety in the proposed path. Pattern search (PS) algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to find an optimal path for mobile robots to reach to target point with obstacle avoidance. For showing the success of the proposed method, first they are applied to two different paths with a dynamic environment in obstacles. The first results show that the PSO algorithms are converged and minimize the objective function better that the others, while PS has the lower time compared to other algorithms in the initial and modified environment. The second test path is in the z-type environment that we compare the mentioned algorithms on it. Also in this environment, the same result is repeated.
Severe proteinuria, sustained for 6 months, induces tubular epithelial cell injury and cell infiltration in rats but not progressive interstitial fibrosis.

BACKGROUND Sustained proteinuria is reported to be very harmful to the tubulointerstitium, leading to severe interstitial injury. However, it remains unclear whether sustained proteinuria itself is responsible for severe interstitial injury because, in the previously reported models, the development of factors other than proteinuria in tubulointerstitial lesions could not be excluded completely. METHODS After treatment to induce immune tolerance to mouse immunoglobulin, 20 rats were injected with anti-rat slit diaphragm monoclonal antibody (mAb) 5-1-6 twice a week for 6 months and were then sacrificed. RESULTS mAb 5-1-6 induced massive proteinuria in 11 rats. In nine rats with mild proteinuria, no histological alteration could be detected with light microscopy and immunofluorescence. In nephrotic rats, light microscopy showed minor glomerular abnormalities, with interstitial oedema, tubular epithelial cell degeneration and interstitial cell infiltration. Immunofluorescence revealed increased expression of vimentin and an increased number of OX1-, OX19- and ED1-positive cells. However, we could not detect any accumulation of type I and IV collagen or laminin in the tubulointerstitium. RT-PCR showed that the expression of mRNA for type I collagen was not increased, compared with that in control rats. CONCLUSIONS We succeeded in developing a model of persistent nephrosis without severe glomerular abnormalities, nephrectomy or other manoeuvres known to induce disturbed haemodynamics, using an agent without tubulointerstitial toxicity, and considered it to be suitable for investigating the direct toxicity of proteinuria. In this model, isolated massive proteinuria induced interstitial injury. However, the degree of injury was suggested to be much less than that observed in other previously developed models.
Predicting Clinical Phenotype Using OTU-Based Metagenome Representation

We demonstrate a computational method to predict the clinical phenotypes of a patient from raw metagenomic sequence read data. We compared two state of the art programs for annotating the sequence data, UCLUST and Kraken, and using their output for feature generation. We apply these programs to a set of over 1.3 million reads from 904 patients, some of whom have liver cirrhosis, encephalopathy due to liver cirrhosis, or neither disease. Once the reads have been processed by UCLUST or Kraken, we use Support Vector Machines to setup the clinical phenotype prediction problem. We find that too many false negatives are being predicted by the classifier. In order to address the issue, we scale features to improve the classification model and evaluate the end results on a held-out test set. We demonstrate our approach works quickly and accurately with an 85.64% success rate when we use the UCLUST representation. We also find that UCLUST generally performs better than Kraken, with the latter having an 80.66% success rate. We also test our classifier on several subsets of the data, with success rates ranging from 69.81% to 96.72%.
A qualitative analysis of what is it like growing up with a sibling with Autism

This is a qualitative study into the perspective experiences of typically developing children’s relationships with their autistic siblings. Previous research is often inconclusive and focuses on the negative attributes of these relationships. Five children in two focus groups between the ages of 6 and 15 participated in this study. Independent interviews were carried out on the parents of the siblings to gain an understanding of their family. The study used thematic analysis to identify key emergent themes for analysis and interpretation. This research lends support against traditional views of what it is like growing up with a sibling with a disability. The analysis suggests the experiences show no significant differences in their interactions compared to ‘normal’ sibling pairs. Siblings express worries over bullying and anger but are accepting, supporting and understanding of their siblings autism and have an unconditional admiration for their sibling.
Recommendation Engine based on Anonymous Users and Implicit Feedback for an Online Travel Web Application

The article presents the development of a recommendation engine for an online travel website which sells summer holiday and whose customer segment is mainly students and young people. On contrary to the traditional recommenders; the developed recommender will be based on anonymous users as the application itself don’t have any login functionality and rely on implicit feedback which will be gathered through web mining. Developed system will use a hybrid model in recommendations which will combine item-to-item collaborative filtering with content-based filtering. In addition to these well-known algorithms the effect of contextual information to the recommendation process will also be evaluated by evaluating our system with different data sets which consists of only week or weekend days. Item and User modeling will be done implicitly through the web logs of the application itself. Finally the article will conclude by giving our conclusions from this project.
Lipoprotein(a) and Coronary Heart Disease: Meta-Analysis of Prospective Studies

BackgroundStudies of the association between the plasma concentration of lipoprotein(a) [Lp(a)] and coronary heart disease (CHD) have reported apparently conflicting findings. We report a meta-analysis of the prospective studies with at least 1 year of follow-up published before 2000. Methods and ResultsThe following information was abstracted for each study: geographical location of study, size, type of cohort (population-based or selected because of previous disease), mean age, follow-up duration, blood storage temperature and duration, assay methods, degree of adjustment for potential confounders, and relationship of baseline Lp(a) measurement with subsequent CHD risk. There were 5436 deaths from CHD or nonfatal myocardial infarctions during a weighted mean follow-up of 10 years in the 27 eligible studies. Comparison of individuals in the top third of baseline plasma Lp(a) measurements with those in the bottom third in each study yielded a combined risk ratio of 1.6 (95% CI 1.4 to 1.8, 2 P <0.00001), with similar findings when the analyses were restricted to the 18 studies of general populations (combined risk ratio 1.7, 95% CI 1.4 to 1.9; 2 P <0.00001). Despite differences among studies in blood storage techniques and assay methods, there was no significant heterogeneity among the results from the 18 population-based studies or among those from the 9 studies of patients with previous disease. Lp(a) was only weakly correlated with classical vascular risk factors, and adjustment for those that had been recorded made little difference to the reported risk ratios. ConclusionsThese prospective studies demonstrate a clear association between Lp(a) and CHD, but further studies are needed to determine the extent to which this is causal.
T Cell IFN-γ Suppression Following Alcohol and Burn Injury Is Independent of miRNA155

miRNA155 has been implicated in normal T cell function and their differentiations into the Th1 subtype. We have shown that acute alcohol (ethanol) intoxication combined with burn injury suppresses T cell IFN-γ release. Herein, we examined whether the decrease in IFN-γ is resulted from altered expression of miRNA155 and transcription factors -NFAT, Tbx21, Jun and Fos - in T cells following ethanol and burn injury. Mice received ethanol (∼3 g/Kg) 4 hours prior to ∼12.5% total body surface area sham or burn injury and were sacrificed one day after injury. Splenic T cells were harvested and cultured with anti-CD3 (2 µg/ml) in the presence or absence of rIL-12 (10 ng/ml) or PMA (10 ng/ml) plus ionomycin (50 ng/ml) for 48 hours. We observed a significant decrease in miRNA155, NFAT, Tbx21, Jun and Fos expression as well as IFN-γ release in T cells cultured with anti-CD3 following ethanol and burn injury compared with shams. The co-treatment of T cells with rIL-12 prevented the decrease in IFN-γ and NFAT, Tbx21, Jun and Fos, but not miRNA155. In contrast, the co-treatment with PMA plus ionomycin normalized the expression of NFAT. It did not prevent the decrease in IFN-γ, Tbx21, Jun, Fos and miRNA155. Finally, results obtained in miRNA155-/- mice did not show any change in T cell release of IFN-γ or expression of nuclear factors compared to wildtype mice. Together, these findings suggest that while ethanol and burn injury decreases the expression of miRNA155, it may not be involved in decreased IFN-γ under those conditions.
CO(1–0) line imaging of massive star-forming disc galaxies at z=1.5–2.2

We present detections of the CO(J= 1-0) emission line in a sample of four massive star-forming galaxies at z~1.5-2.2 obtained with the Karl G. Jansky Very Large Array (VLA). Combining these observations with previous CO(2-1) and CO(3-2) detections of these galaxies, we study the excitation properties of the molecular gas in our sample sources. We find an average line brightness temperature ratios of R_{21}=0.70+\-0.16 and R_{31}=0.50+\-0.29, based on measurements for three and two galaxies, respectively. These results provide additional support to previous indications of sub-thermal gas excitation for the CO(3-2) line with a typically assumed line ratio R_{31}~0.5. For one of our targets, BzK-21000, we present spatially resolved CO line maps. At the resolution of 0.18'' (1.5 kpc), most of the emission is resolved out except for some clumpy structure. From this, we attempt to identify molecular gas clumps in the data cube, finding 4 possible candidates. We estimate that <40 % of the molecular gas is confined to giant clumps (~1.5 kpc in size), and thus most of the gas could be distributed in small fainter clouds or in fairly diffuse extended regions of lower brightness temperatures than our sensitivity limit.
CLOpinionMiner: Opinion Target Extraction in a Cross-Language Scenario

Opinion target extraction is a subtask of opinion mining which is very useful in many applications. The problem has usually been solved by training a sequence labeler on manually labeled data. However, the labeled training datasets are imbalanced in different languages, and the lack of labeled corpus in a language limits the research progress on opinion target extraction in this language. In order to address the above problem, we propose a novel system called CLOpinionMiner which investigates leveraging the rich labeled data in a source language for opinion target extraction in a different target language. In this study, we focus on English-to-Chinese cross-language opinion target extraction. Based on the English dataset, our method produces two Chinese training datasets with different features. Two labeling models for Chinese opinion target extraction are trained based on Conditional Random Fields (CRF). After that, we use a monolingual co-training algorithm to improve the performance of both models by leveraging the enormous unlabeled Chinese review texts on the web. Experimental results show the effectiveness of our proposed approach.
Draco 119: A Remarkable Heavy-Element-deficient Giant

We report the abundance analysis of new high signal-to-noise ratio (S/N) spectra of the most metal-poor ([Fe/H] = -2.95) star currently known to be a member of a dwarf galaxy, the Draco dSph red giant D119. No absorption lines for elements heavier than Ni are detected in two Keck HIRES spectra covering the 3850-6655 Å wavelength range, a phenomenon not previously noted in any other metal-poor star. We present upper limits for several heavy-element abundances. The most stringent limits, based on the nondetection of Sr II and Ba II lines, indicate that the total s- and r-process enrichment of D119 is at least 100 times smaller than Galactic stars of similar metallicity. The light-element abundances are consistent with the star having formed out of material enriched primarily by massive Type II supernovae (M > 20-25 M☉). If this is the case, we are forced to conclude that massive, metal-poor Type II supernovae did not contribute to the r-process in the proto-Draco environment. We compare the abundance pattern observed in D119 to current predictions of prompt enrichment and pair-instability supernovae and find that the model predictions fail by an order of magnitude or more for many elements.
An Interactive Web-based Simulation Tool for Surgical Thread

— Interactive web-based computer simulations are needed by the medical community to replicate the experience of surgical procedures as closely and realistically as possible without the need to practice on corpses, animals and/or plastic models. In this paper, we offer a review on current state of the research on simulations of surgical threads, identify future needs and present our proposed plans to meet them. Our goal is to create a physics-based simulator, which will predict the behavior of surgical thread when subjected to conditions commonly encountered during surgery. To that end, we will i) develop three dimensional finite element models based on the Cosserat theory of elasticity ii) test and feedback results with the medical community and iii) develop a web-based user interface to run/command our simulator and visualize the results. The impacts of our research are that i) it will contribute to the development of a new generation of training for medical school students and ii) the simulator will be useful to expert surgeons in developing new, better and less risky procedures.
Integrated Detection of Attacks Against Browsers, Web Applications and Databases

Anomaly-based techniques were exploited successfully to implement protection mechanisms for various systems. Recently, these approaches have been ported to the web domain under the name of "web application anomaly detectors" (or firewalls) with promising results. In particular, those capable of automatically building specifications, or models, of the protected application by observing its traffic (e.g., network packets, system calls, or HTTP requests and responses) are particularly interesting, since they can be deployed with little effort.Typically, the detection accuracy of these systems is significantly influenced by the model building phase (often called training), which clearly depends upon the quality of the observed traffic, which should resemble the normal activity of the protected application and must be also free from attacks. Otherwise, detection may result in significant amounts of false positives (i.e., benign events flagged as anomalous) and negatives (i.e., undetected threats). In this work we describe Masibty, a web application anomaly detector that have some interesting properties. First, it requires the training data not to be attack-free. Secondly, not only it protects the monitored application, it also detects and blocks malicious client-side threats before they are sent to the browser. Third, Masibty intercepts the queries before they are sent to the database, correlates them with the corresponding HTTP requests and blocks those deemed anomalous.Both the accuracy and the performance have been evaluated on real-world web applications with interesting results. The system is almost not influenced by the presence of attacks in the training data and shows only a negligible amount of false positives, although this is paid in terms of a slight performance overhead.
Scatter Search for Binary Problems

In this chapter we propose a procedure based on the scatter search methodology that can be used for searching the solution space of optimization problems whose solutions can be represented as binary vectors. It is a black-box procedure in the sense that it is not customized to solve a particular problem in this class. We compare it with three software products based on metaheuristic technologies when solving two well known binary optimization problems: the knapsack and the maximum