Miracle-dz/UniFAR-FTUs huggingface dataset:
Silencing Viral MicroRNA as a Novel Antiviral Therapy?

Viruses are intracellular parasites that ensure their existence by converting host cells into viral particle producing entities or into hiding places rendering the virus invisible to the host immune system. Some viruses may also survive by transforming the infected cell into an immortal tumour cell. MicroRNAs are small non-coding transcripts that function as posttranscriptional regulators of gene expression. Viruses encode miRNAs that regulate expression of both cellular and viral genes, and contribute to the pathogenic properties of viruses. Hence, neutralizing the action of viral miRNAs expression by complementary single-stranded oligonucleotides or so-called anti-miRNAs may represent a strategy to combat viral infections and viral-induced pathogenesis. This review describes the miRNAs encoded by human viruses, and discusses the possible therapeutic applications of anti-miRNAs against viral diseases.
The implications of NICE guidelines on the management of children presenting with head injury

Background: NICE guidelines for the management of head injury were published in June 2003. Their recommendations differ markedly from previous guidelines published by the Royal College of Surgeons (RCS). In place of skull radiography and admission, computed tomography (CT) is advocated. The impact of these guidelines on service provision in the UK is unknown. Methods: Data on all clinical correlates of children presenting with any severity of head injury was collected in three hospitals in the northwest of England. The current skull radiograph (SXR), CT scan, and admission rates were determined. The rates of SXR, CT scan, and admission that should have occurred when following either the RCS or NICE guidelines were then determined. Results: Data from 10 965 patients who attended three hospitals between February 2000 and August 2002 was studied. Twenty five per cent of patients received a SXR, 0.9% a CT scan, and 3.7% were admitted. Strict adherence to the RCS guidelines would have resulted in a 50% SXR rate, a 1.6% CT scan rate, and a 7.1% admission rate. Adherence to NICE guidelines would result in a 0.3% SXR rate, an 8.7% CT scan rate, and a 1.4% admission rate, although the CT rate would drop to 6.3% if vomiting three or more times in the under 12s was used instead of more than one vomit. Conclusions: The new NICE guidelines do not increase the workload caused by patients attending with head injury but they move their management from the observation ward to the radiology department.
CloudArray: Easing huge image processing

Image processing algorithms require high processing capabilities. Most of these algorithms use linear algebraic operations (BLAS), for instance, through the Combinatorial BLAS [1], and Elemental [2] programming supports. Such operations may require unavailable computer processing resources. CloudArray is funded by Microsoft Azure Research Award, Brazilian National Council for Scientific and Technological Development (CNPq), and Alagoas Research Foundation (FAPEAL).
Immediate and short-term outcomes of the 'COPEing with Toddler Behaviour' parent group.

BACKGROUND Controlling, uninvolved, and rejecting parenting in early childhood are strong predictors of later disruptive behavior disorders. However, there have been no evaluations of non-targeted groups for parents of very young children, despite their potential advantages. METHODS We randomly assigned 79 mothers of 12- to 36-month-olds to an 8-session parent training program (called 'COPEing with Toddler Behaviour') or to a waiting list control condition. We investigated the immediate and short-term impact on parent-reported child behavior problems, observed parent-child interaction, and self-reported parenting behavior and parent functioning. RESULTS In an intent-to-treat design, the program yielded significant effects on child behavior problems, positive parent-child interaction, and parental overreactivity and depression but not observed negative child behavior or parental laxness. Most effects were significant at both post-test and 1-month follow-up and effects sizes were small to medium for the intervention group and inverse to small for the control group. CONCLUSIONS The potential of the program to prevent later behavior problems is supported by improvements in six of the eight outcomes. As part of a community strategy, groups such as COPEing with Toddler Behaviour may promote positive parent-child interaction and children's mental health.
Spontaneous resorption of a large lumbar disc herniation within 4 months.

A 48-year-old man presented in March 2013 with a 20-day history of low back and right leg pain with no obvious cause. There was no history of surgical trauma. Neurological examination showed no deficits. A straight leg-raising test was positive at 30° on the right side. The Japanese Orthopaedic Association (JOA) score for low back pain was 4 points (1). Magnetic resonance imaging (MRI) of the lumbar spine suggested the presence of a large intervertebral disc herniation at L4/L5, a typical site for this abnormality (Fig. 1). Surgery to remove the herniated disc was recommended, but the patient declined. Consequently, the patient was treated conservatively, which included bed rest, with steroidal anti-inflammatory drugs for 2 months and oral administration of Chinese medicine for 4 months. In July 2013, he was re-examined and had no complaints, with a JOA score of 28 points. A second MRI study showed com-
Application of Dynamic Slicing in Program Debugging

A dynamic program slice is an executable part of a program whose behavior is identical, for the same program input, to that of the original program with respect to a variable(s) of interest at some execution position. In the existing dynamic slicing tools dynamic slices are represented in a textual form, i.e., a dynamic slice is displayed to programmers in the form of highlighted statements or in the form of a subprogram. Although dynamic slicing does narrow the size of the program, it is still up to the programmer to analyze the text of a dynamic slice and identify a faulty part in the program. The textual representation of a dynamic slice does not provide much guidance in program debugging and understanding of program behavior, which frequently is a major factor in efficient debugging. During dynamic slice computation different types of information are computed and then discarded after computation of the dynamic slice. In this paper we propose new dynamic slicing related features that exploit this information to improve the process of program debugging. These features were implemented in our dynamic slicing tool that can be used for program debugging.
A Sub-ppm Acetone Gas Sensor for Diabetes Detection Using 10 nm Thick Ultrathin InN FETs

An indium nitride (InN) gas sensor of 10 nm in thickness has achieved detection limit of 0.4 ppm acetone. The sensor has a size of 1 mm by 2.5 mm, while its sensing area is 0.25 mm by 2 mm. Detection of such a low acetone concentration in exhaled breath could enable early diagnosis of diabetes for portable physiological applications. The ultrathin InN epilayer extensively enhances sensing sensitivity due to its strong electron accumulation on roughly 5–10 nm deep layers from the surface. Platinum as catalyst can increase output current signals by 2.5-fold (94 vs. 37.5 μA) as well as reduce response time by 8.4-fold (150 vs. 1,260 s) in comparison with bare InN. More, the effect of 3% oxygen consumption due to breath inhalation and exhalation on 2.4 ppm acetone gas detection was investigated, indicating that such an acetone concentration can be analyzed in air.
Learning Attributes Equals Multi-Source Domain Generalization

Attributes possess appealing properties and benefit many computer vision problems, such as object recognition, learning with humans in the loop, and image retrieval. Whereas the existing work mainly pursues utilizing attributes for various computer vision problems, we contend that the most basic problem-how to accurately and robustly detect attributes from images-has been left under explored. Especially, the existing work rarely explicitly tackles the need that attribute detectors should generalize well across different categories, including those previously unseen. Noting that this is analogous to the objective of multi-source domain generalization, if we treat each category as a domain, we provide a novel perspective to attribute detection and propose to gear the techniques in multi-source domain generalization for the purpose of learning cross-category generalizable attribute detectors. We validate our understanding and approach with extensive experiments on four challenging datasets and three different problems.
Analysis of Iterative Methods in Photoacoustic Tomography with Variable Sound Speed

In this article, we revisit iterative methods for solving the inverse source problem of photoacoustic tomography in free space. Recently, there have been interesting developments on explicit formulations of the adjoint operator, demonstrating that iterative methods are an attractive choice for photoacoustic image reconstruction. In this work, we propose several modifications of current formulations of the adjoint operator which help speed up the convergence and yield improved error estimates. We establish a stability analysis and show that, with our choices of the adjoint operator, the iterative methods can achieve a linear rate of convergence, in the $L^2$-norm as well as $H^1$-norm. In addition, we analyze the normal operator from the microlocal analysis point of view. This gives insight into the convergence speed of the iterative methods and choosing proper weights for the mapping spaces. Finally, we present numerical results using various iterative reconstruction methods for full as well as limited vi.
Blood‐induced joint disease: the pathophysiology of hemophilic arthropathy

Summary. Arthropathy is a frequent and serious complication of repeated joint bleeding in patients with hemophilia, resulting in pain, deformity, and disability. Although the pathogenesis of hemophilic arthropathy has not been fully elucidated, it appears to have similarities with the degenerative joint damage that occurs in osteoarthritis and the inflammatory processes associated with rheumatoid arthritis. This article reviews the potential actions of various blood constituents on joint components that culminate in the development of hemophilic arthropathy.
Roll-Plate Alone Does Not Demonstrate Colonization In Silicone Neonatal Catheters

We compared roll-plate, sonication and slicing for the detection of colonization and catheter-related bloodstream infection (C-RBSI) in 90 silicone neonatal peripherally inserted central catheters. Colonization was detected by roll-plate, sonication and slicing in 3.4%, 6.9% and 10.3% of catheters, respectively. C-RBSI was detected by roll-plate, sonication and slicing only in 4.8% of each. The roll-plate technique was not a good predictor of colonization and C-RBSI in silicone neonatal peripherally inserted central catheters. Detecting intraluminal colonization was required.
Ethanolic Extract of Melia Fructus Has Anti-influenza A Virus Activity by Affecting Viral Entry and Viral RNA Polymerase

Meliae Fructus (MF) is the dried ripe fruit of Melia toosendan Siebold et Zuccarini, Meliaceae family. MF is widely used in traditional medicine to treat inflammation and helminthic infection and has anti-bacterial, anti-oxidant, anti-cancer, anti-inflammatory, and analgesic activities. However, potential anti-influenza properties of MF have yet to be investigated. We determined whether an ethanolic extract of MF (EMF) has anti-viral activity via an EMF pre-, co-, and post-treatment assay, using the Influenza A/PR/8/34 and H3N2 virus on Madin-Darby canine kidney (MDCK) cells. The EMF had anti-influenza virus activity in pre- and co-treated cells in a dose-dependent manner, but not in post-treated cell. EMF inhibited the activity of hemagglutinin (HA) and neuraminidase (NA) of influenza virus. EMF inhibited viral HA, nucleoprotein (NP), matrix protein 2 (M2), non-structural protein 1 (NS1), polymerase acidic protein (PA), polymerase basic protein 1 (PB1), and polymerase basic protein 2 (PB2) mRNA synthesis at 5 h post infection (hpi), however, the levels of PA, PB1, and PB2 mRNA were increased in pre- and co-EMF treated cells compared with control virus-infected and EMF post-treated cells at 18 hpi. The level of M2 protein expression was also decreased upon pre- and co-treatment with EMF. The PA protein was accumulated and localized in not only the nucleus but also the cytoplasm of virus-infected MDCK cells at 18 hpi. Pre-EMF treatment inhibited the expression of pAKT, which is induced by influenza virus infection, at the stage of virus entry. We also found that treatment of EMF up-regulated the antiviral protein Mx1, which may play a partial role in inhibiting influenza virus infection in pre- and co-EMF treated MDCK cells. In summary, these results strongly suggested that an ethanolic extract of Meliae Fructus inhibited influenza A virus infection by affecting viral entry, PA proteins of the RNA polymerase complex, and Mx1 induction and may be a potential and novel anti-influenza agent.
Reconstruction of the neuromuscular junction connectome

Motivation: Unraveling the structure and behavior of the brain and central nervous system (CNS) has always been a major goal of neuroscience. Understanding the wiring diagrams of the neuromuscular junction connectomes (full connectivity of nervous system neuronal components) is a starting point for this, as it helps in the study of the organizational and developmental properties of the mammalian CNS. The phenomenon of synapse elimination during developmental stages of the neuronal circuitry is such an example. Due to the organizational specificity of the axons in the connectomes, it becomes important to label and extract individual axons for morphological analysis. Features such as axonal trajectories, their branching patterns, geometric information, the spatial relations of groups of axons, etc. are of great interests for neurobiologists in the study of wiring diagrams. However, due to the complexity of spatial structure of the axons, automatically tracking and reconstructing them from microscopy images in 3D is an unresolved problem. In this article, AxonTracker-3D, an interactive 3D axon tracking and labeling tool is built to obtain quantitative information by reconstruction of the axonal structures in the entire innervation field. The ease of use along with accuracy of results makes AxonTracker-3D an attractive tool to obtain valuable quantitative information from axon datasets. Availability: The software is freely available for download at http://www.cbi-tmhs.org/AxonTracker/ Contact: stwong@tmhs.org
On the Power Allocation of MIMO Channels

In this paper we consider MIMO system with Mt transmitting and Mr receiving antennas, when channel state information (CSI) is known on the transmitter side. The Reyleigh fading channel propagation condition is assumed. In this case, the optimum transmission consists of allocating the transmitted power for each virtual sub-channel related to the corresponding eigenvalue of the channel matrix. The optimum power allocation is computed using the water pouring algorithm (WPA). However, a real-time implementation of the algorithm requires serious computational work, which is O(M t ). We propose a modification to WPA that reduces the computational complexity to O(Mt).
Comprehensive Approach to Analyzing Rare Genetic Variants

Recent findings suggest that rare variants play an important role in both monogenic and common diseases. Due to their rarity, however, it remains unclear how to appropriately analyze the association between such variants and disease. A common approach entails combining rare variants together based on a priori information and analyzing them as a single group. Here one must make some assumptions about what to aggregate. Instead, we propose two approaches to empirically determine the most efficient grouping of rare variants. The first considers multiple possible groupings using existing information. The second is an agnostic “step-up” approach that determines an optimal grouping of rare variants analytically and does not rely on prior information. To evaluate these approaches, we undertook a simulation study using sequence data from genes in the one-carbon folate metabolic pathway. Our results show that using prior information to group rare variants is advantageous only when information is quite accurate, but the step-up approach works well across a broad range of plausible scenarios. This agnostic approach allows one to efficiently analyze the association between rare variants and disease while avoiding assumptions required by other approaches for grouping such variants.
Heterogeneity Coefficients for Mahalanobis' D as a Multivariate Effect Size

ABSTRACT The Mahalanobis distance D is the multivariate generalization of Cohen's d and can be used as a standardized effect size for multivariate differences between groups. An important issue in the interpretation of D is heterogeneity, that is, the extent to which contributions to the overall effect size are concentrated in a small subset of variables rather than evenly distributed across the whole set. Here I present two heterogeneity coefficients for D based on the Gini coefficient, a well-known index of inequality among values of a distribution. I discuss the properties and limitations of the two coefficients and illustrate their use by reanalyzing some published findings from studies of gender differences.
Risk Pooling, Risk Preferences, and Social Networks

Using data from an experiment conducted in 70 Colombian communities, we investigate who pools risk with whom when trust is crucial to enforce risk pooling arrangements. We explore the roles played by risk attitudes and social networks. Both theoretically and empirically, we find that close friends and relatives group assortatively on risk attitudes and are more likely to join the same risk pooling group, while unfamiliar participants group less and rarely assort. These findings indicate that where there are advantages to grouping assortatively on risk attitudes those advantages may be inaccessible when trust is absent or low.
Imaging Methods for MEG/EEG Inverse Problem

Recovering electrical activity of the brain from MEG/EEG measurements is known as the MEEG inverse prob- lem. It is an ill-posed problem in several senses. One is that there is further less data observed than data to recover. One way to address this issue is to search for regular solutions. We present here a framework for applying image processing filtering techniques to the MEEG inverse problem. Exprimentations are presented on synthetic dara and validation is carried out on one real MEG data set. I. I NTRODUCTION The MEG/EEG inverse problem of reconstructing electrical sources in human brain is an ill-posed and under-determined problem. There are many classes of methods for solving this problem, each one having its advantages and drawbacks. The most used one is the moving dipole(7). Among the other ones, Imaging methods are sometimes addressed with a Bayesian stochastic framework (4). Minimum norm solutions and Tikhonov regularization can also be seen as variational regularization methods for removing this undetermination. These methods tend to produce a well-know scaterring and blurring effect on the reconstructed sources. We propose a framework for applying more sophisticated regularization techniques arrising from image processing field.
Disturbance of zinc and glucose homeostasis by methyl tert-butyl ether (MTBE); evidence for type 2 diabetes

Abstract 1. The prevalence of diabetes and the other metabolic disorders has noticeably increased worldwide. A causal link between increasing risk of type 2 diabetes and exposure to environmental pollutants has been reported. 2. We hypothesized that exposure to methyl tert-butyl ether (MTBE), an oxygenate additive to gasoline would hinder zinc and glucose homeostasis in rats. 3. Male Sprague–Dawley rats received MTBE in drinking water for 90 days. At the end of the treatment, pancreas and blood samples were collected for biochemical and molecular examinations. Expression of four candidate genes, including Insulin1, Insulin2, MT1A, SLC30A8 by Real-Time Quantitative PCR (Q-PCR) as well as biochemical parameters, including fasting blood glucose (FBS), triglycerides (TG), cholesterol (CHO), low-density lipoprotein (LDL), high-density lipoprotein (HDL), copper (Cu2+) and calcium (Ca2+) levels as well as High-sensitive C-reactive protein were assessed as endpoints. 4. This study suggested that MTBE exposure can be associated with disruption in zinc homeostasis and glucose tolerance.
NON-SPEECH ENVIRONMENTAL SOUND CLASSIFICATION USING SVMS WITH A NEW SET OF FEATURES

Mel Frequency Cepstrum Coeﬃcients (MFCCs) are considered as a method of stationary/pseudo-stationary feature extraction. They work very well for the classi(cid:12)-cation of speech and music signals. MFCCs have also been used to classify non-speech sounds for audio surveillance systems, even though MFCCs do not completely re(cid:13)ect the time-varying features of non-stationary non-speech signals. We introduce a new 2D-feature set, used with a feature extraction method based on the pitch range (PR) of non-speech sounds and the Autocorrelation Function. We compare the classi(cid:12)cation accuracies of the proposed features of this new method to MFCCs by using Support Vector Machines (SVMs) and Radial Basis Function Neural Network classi(cid:12)ers. Non-speech environmental sounds: gunshot, glass breaking, scream, dog barking, rain, engine, and restaurant noise, were studied. The new feature set provides high accuracy rates when used as a classi(cid:12)er. Its usage with MFCCs signi(cid:12)cantly improves the accuracy rates of the given classi(cid:12)ers in the range of 4% to 35% depending on the classi(cid:12)er used, suggesting that both feature sets are complementary. SVM classi(cid:12)er using the Gaussian kernel provided the highest accuracy rates among the classi(cid:12)ers used in this study.
On estimating the lattice security of NTRU

This report explicitly refutes the analysis behind a recent claim that NTRUEncrypt has a bit security of at most 74 bits. We also sum up some existing literature on NTRU and lattices, in order to help explain what should and what should not be classed as an improved attack against the hard problem underlying NTRUEncrypt. We also show a connection between Schnorr’s RSR technique and exhaustively searching the NTRU lattice.