Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Monoclonal Antibody HCV1 Effectively Prevents and Treats HCV Infection in Chimpanzees

Hepatitis C virus (HCV) infection is a leading cause of liver transplantation and there is an urgent need to develop therapies to reduce rates of HCV infection of transplanted livers. Approved therapeutics for HCV are poorly tolerated and are of limited efficacy in this patient population. Human monoclonal antibody HCV1 recognizes a highly-conserved linear epitope of the HCV E2 envelope glycoprotein (amino acids 412–423) and neutralizes a broad range of HCV genotypes. In a chimpanzee model, a single dose of 250 mg/kg HCV1 delivered 30 minutes prior to infusion with genotype 1a H77 HCV provided complete protection from HCV infection, whereas a dose of 50 mg/kg HCV1 did not protect. In addition, an acutely-infected chimpanzee given 250 mg/kg HCV1 42 days following exposure to virus had a rapid reduction in viral load to below the limit of detection before rebounding 14 days later. The emergent virus displayed an E2 mutation (N415K/D) conferring resistance to HCV1 neutralization. Finally, three chronically HCV-infected chimpanzees were treated with a single dose of 40 mg/kg HCV1 and viral load was reduced to below the limit of detection for 21 days in one chimpanzee with rebounding virus displaying a resistance mutation (N417S). The other two chimpanzees had 0.5–1.0 log10 reductions in viral load without evidence of viral resistance to HCV1. In vitro testing using HCV pseudovirus (HCVpp) demonstrated that the sera from the poorly-responding chimpanzees inhibited the ability of HCV1 to neutralize HCVpp. Measurement of antibody responses in the chronically-infected chimpanzees implicated endogenous antibody to E2 and interference with HCV1 neutralization although other factors may also be responsible. These data suggest that human monoclonal antibody HCV1 may be an effective therapeutic for the prevention of graft infection in HCV-infected patients undergoing liver transplantation.
KYOTO: an open platform for mining facts

This document describes an open text-mining system that was developed for the Asian-European project KYOTO. The KYOTO system uses an open text representation format and a central ontology to enable extraction of knowledge and facts from large volumes of text in many different languages. We implemented a semantic tagging approach that performs off-line reasoning. Mining of facts and knowledge is achieved through a flexible pattern matching module that can work in much the same way for different languages, can handle efficiently large volumes of documents and is not restricted to a specific domain. We applied the system to an English database on estuaries.
Spectral analysis of brain function network for the classification of motor imagery tasks

In order to deal with the classification for multi-class motor imagery(MI) tasks, a novel approach was presented in this paper. It is different from classical methods which classified the MI task with time-frequency analysis on EEG signals. It employs the brain function network(BFN) as a new characteristic to describe MI tasks. The BFN enlarges the features with respect to traditional time-frequency methods. Unlike analysis of statistical parameters of network such as average clustering coefficient (C) and the average pathlength (L), the proposed method employed spectral decomposition performing on BFNs, and considered the eigenvalue vector of threshold matrix as features for classification by SVM. Hence, it is speedy enough to meet the requirement of real-time in BCI-based application systems. The result of experiment demonstrates that proposed method can achieve satisfied accuracy of classification on multi-class MI tasks.
Decision - delivery interval and perinatal outcome of emergency caesarean sections at a tertiary institution

Background and objective: A decision-to-delivery interval (DDI) of 30 minutes for emergency Caesarean sections (CS) has been widely recommended, but there is little evidence to support it. Recent studies however, have questioned not only the practicability of this target but also its anticipated beneficial effect on neonatal outcome and medico-legal implications. Our objective in this study was to find out the time between decision-delivery interval and perinatal outcome of emergency caesarean section at a tertiary care institution in Nigeria Methods: This was a retrospective study of cases of emergency Caesarean section performed over a 12-month period. Relevant data were collected from the labour ward and theatre records and case files of the University of Benin Teaching Hospital, Benin City, Nigeria between January 1 and December 31, 2012. Results: A total of 352 emergency Caesarean sections done during the period were reviewed. Only 20 (5.7%) of these were performed within the recommended 30 minutes DDI. The mean DDI was 106.3 + 79.5 minutes and there was no significant correlation between DDI and perinatal outcome. The major causes of delay were anaesthetic delay and busy theatre suits. Conclusion: This study demonstrated a lack of correlation between DDI and perinatal outcome, which may indicate decision delivery interval of 30 minutes or less may not be applicable to all emergency CS, especially in developing countries with infrastructural challenges. However when faced with acute or catastrophic foetal or maternal conditions, expedited delivery is indicated.
Combined DVFS and mapping exploration for lifetime and soft-error susceptibility improvement in MPSoCs

Energy and reliability optimization are two of the most critical objectives for the synthesis of multiprocessor systems-on-chip (MPSoCs). Task mapping has shown significant promise as a low cost solution in achieving these objectives as standalone or in tandem as well. This paper proposes a multi-objective design space exploration to determine the mapping of tasks of an application on a multiprocessor system and voltage/frequency level of each tasks (exploiting the DVFS capabilities of modern processors) such that the reliability of the platform is improved while fulfilling the energy budget and the performance constraint set by system designers. In this respect, the reliability of a given MPSoC platform incorporates not only the impact of voltage and frequency on the aging of the processors (wear-out effect) but also on the susceptibility to soft-errors - a joint consideration missing in all existing works in this domain. Further, the proposed exploration also incorporates soft-error tolerance by selective replication of tasks, making the proposed approach an interesting blend of reactive and proactive fault-tolerance. The combined objective of minimizing core aging together with the susceptibility to transient faults under a given performance/energy budget is solved by using a multi-objective genetic algorithm exploiting tasks' mapping, DVFS and selective replication as tuning knobs. Experiments conducted with reallife and synthetic application graphs clearly demonstrate the advantage of the proposed approach.
Effective Visual Tracking Using Multi-Block and Scale Space Based on Kernelized Correlation Filters

Accurate scale estimation and occlusion handling is a challenging problem in visual tracking. Recently, correlation filter-based trackers have shown impressive results in terms of accuracy, robustness, and speed. However, the model is not robust to scale variation and occlusion. In this paper, we address the problems associated with scale variation and occlusion by employing a scale space filter and multi-block scheme based on a kernelized correlation filter (KCF) tracker. Furthermore, we develop a more robust algorithm using an appearance update model that approximates the change of state of occlusion and deformation. In particular, an adaptive update scheme is presented to make each process robust. The experimental results demonstrate that the proposed method outperformed 29 state-of-the-art trackers on 100 challenging sequences. Specifically, the results obtained with the proposed scheme were improved by 8% and 18% compared to those of the KCF tracker for 49 occlusion and 64 scale variation sequences, respectively. Therefore, the proposed tracker can be a robust and useful tool for object tracking when occlusion and scale variation are involved.
Toward Dynamic Image Mosaic Generation With Robustness to Parallax

Mosaicing is largely dependent on the quality of registration among the constituent input images. Parallax and object motion present challenges to image registration, leading to artifacts in the result. To reduce the impact of these artifacts, traditional image mosaicing approaches often impose planar scene constraints or rely on purely rotational camera motion or dense sampling. However, these requirements are often impractical or fail to address the needs of all applications. Instead, taking advantage of depth cues and a smooth transition criterion, we achieve significantly improved mosaicing results for static scenes, coping effectively with nontrivial parallax in the input. We extend this approach to the synthesis of dynamic video mosaics, incorporating foreground/background segmentation and a consistent motion perception criterion. Although further additions are required to cope with unconstrained object motion, our algorithm can synthesize a perceptually convincing output, conveying the same appearance of motion as seen in the input sequences.
ON THE USE OF PETRI NETS FOR THE DESCRIPTION OF DIGITAL SYSTEMS

 Due to their complexity, nowadays it is virtually unconceivable to design and implement large digital systems without the use of computer-aided design tools. Many petri net extensions have been proposed aiming at describing hardware characteristics as accurately as possible. Among all petri net extensions developed for use with digital systems, only two of them have nearly all characteristics needed to describe such systems in full. They are place chart nets, and petri nets for embedded systems. Using the latter as an example we discuss some issues that may improve the capability of petri nets in dealing with digital systems.
The Dictionary of Alternatives: Utopianism and Organization

Introduction A-Z of Utopian Thought - Over 300 detailed entries, from the familiar to the esoteric. For example: Fictional Utopias The Republic Gulliver's Travels News from Nowhere Island Social Experiments America Bourneville Cuba The Paris Commune Porto Alegre Soviet Union Wikipedia Social Movements The Black Panthers Communism Deep Ecology Fair Trade Levellers New Model Army Romanticism Situtationist Via Campesina The World Social Forum Zapatistas Thinkers Bakunin Castro Marx Gandhi Guevara Illich Nozick Friere Rawls Further Reading
Design of a 50.000 rpm synchronous reluctance machine for an aeronautic diesel engine compressor

This document describes the design procedure followed to realize an high speed synchronous reluctance machine for aeronautical application. The attention is mainly focused on the rotor design that is the most critical part of any synchronous reluctance machine, in particular for high-speed applications. After a preliminary optimization of the rotor geometry, a multiphysical design that considered mechanical, thermal and electromagnetic properties was developed. The main steps of the design procedure together with an extensive analysis of the final design are presented here. The prototype has been realized and tested in order to validate the design procedure.
Throughput driven transformations of Synchronous Data Flows for mapping to heterogeneous MPSoCs

Due to energy efficiency requirements of modern embedded systems, chip vendors are inclined towards multicore architectures with different types of processing engines and non-uniform interconnect fabrics. At the same time multiple applications are intended to run concurrently on the devices with such heterogeneous architectures. This rapid growth in the complexity of the hardware and its use cases imposes new challenges on the software development tools. To overcome this complexity, model of computation based approaches are becoming increasingly promising. Synchronous Data Flow (SDF) is a popular specification formalism for streaming applications with inherently concurrent nature. However, the parallelism expressed in the original representation is often not sufficient to maximally exploit the potential of multicore platforms. In this paper we present a holistic methodology for improving the throughput of streaming applications while mapping them onto heterogeneous architectures. The approach uses transformations that adapt the parallelism in SDF according to available platform resources. We use a genetic algorithm to explore SDF instances with the objective of maximizing throughput on a target platform. Our model supports architecture heterogeneity and multi-application scenarios. The experiments indicate that our approach outperforms other techniques for exploiting parallelism on a single application in most of the test cases and enables concurrent applications optimization.
Application of the Digital Signal Procession in the MEMS Gyroscope De-drift

The Micro Electrics Mechanics System (MEMS) gyroscope has the virtue of lower price, smaller size, lighter weight than of the traditional rate sensors. It can be widely used in the low-price inertial navigation system. But limited by its machining precision, the MEMS gyroscope usually has the large drift. Using the digital signal procession (DSP) of drift signal, the performance of the MEMS gyroscope could be improved effectively. By a new median filtering method, the outlier signal from the drift signal was got rid of. The online implemented wavelet analyzing of the drift signal was used to extract the character of the gyroscope drift. A two-order AR model was built for the residual signal between the original signal and the characteristics drift signal. A group of matrix equations were built for the traditional Kalman filter. By making some improvement on these equations, an adaptive Kalman filter was used to trace the change of the residual signal adaptively and could increase the de-drift effect of the MEMS gyroscope greatly. A 50mm times 50mm circuit board was made to implement the DSP. Standard variance of the dynamics signal measurement was 18.31 deg/h after the gyroscope drift was extracted
Ray Tracing Free-Form B-Spline Surfaces

We present a method for using ray tracing to render spline surfaces¿one that is suitable for any object generated from control vertices via tensor-product B-splines. The method derives from kajiya's work on ray tracing procedurally defined surfaces1 and makes use of two preprocessing steps. One involves the controlvertex refinement recurrences due to Riesenfeld et. al.2, and the second generates a tree of nested bounding boxes. Intersection testing involves running Kajiya's algorithm on the tree, followed by two to three (on the average) iterations of Newton's method.
AN INVESTIGATION OF THE INCREASED RELIANCE ON FAMILIARITY IN ASSOCIATIVE RECOGNITION OF UNITIZED COMPOUND WORD PAIRS

Ahmad and Hockley (2014) found in yes-no associative recognition, both hits and false alarm rates were greater for compound word pairs (CW; e.g., store keeper) compared to noncompound word pairs (NCW; e.g., needle birth) with no difference in discrimination. They concluded increased reliance on familiarity from unitization of CW pairs was responsible for this CW effect. Previous research has also shown that familiarity produced from fluency of processing did not contribute to associative recognition of unrelated pairs that were unitized using a definitional encoding instruction (Lloyd, Hartman, Ngo, Ruser, Westerman & Miller, 2015). The present study examined if fluency of processing contributes to associative recognition of unitized preexperimental associations (i.e., CW pairs). In Experiment 1, when perceptual fluency was minimized by presenting the words of each pair one at a time, the CW effect was not diminished. In Experiments 2A and 2B, conceptual fluency was examined by comparing transparent (e.g., hand bag) and opaque (e.g., rag time) CW pairs in lexical decision and associative recognition tasks. Lexical decision was shown to be faster for transparent compared to opaque CW pairs (Experiment 2A) but in associative recognition, the CW effect did not differ for each pair type (Experiment 2B). The CW effect in yes-no associative recognition is due to a reliance on enhanced familiarity of unitized CW pairs and not based on fluency of processing.
Visualizing health: imagery in diabetes education

In this paper, we describe research designed to impact diabetes education programs. We have tried to connect medical facts and information about diabetes to personal experiences by introducing photography as a tool for data collection. Diabetics typically measure their blood sugar levels to understand their physiological state, but these data cannot explain the causal factors leading to anomalous health. We have introduced additional qualitative data into the diabetes portfolio by having patients photograph their eating, exercise, and stress management habits. We discuss two related projects in the paper: a new approach to diabetes education courses and visualization software that allows photographs of behavior to be synchronized with glucose data. In both cases, our goal is to help diabetics reflect on their health practices, and to use personal imagery as data to explain their conditions.
The NH2-terminal peptide of α–smooth muscle actin inhibits force generation by the myofibroblast in vitro and in vivo

Myofibroblasts are specialized fibroblasts responsible for granulation tissue contraction and the soft tissue retractions occurring during fibrocontractive diseases. The marker of fibroblast-myofibroblast modulation is the neo expression of α–smooth muscle actin (α-SMA), the actin isoform typical of vascular smooth muscle cells that has been suggested to play an important role in myofibroblast force generation. Actin isoforms differ slightly in their NH2-terminal sequences; these conserved differences suggest different functions. When the NH2-terminal sequence of α-SMA Ac-EEED is delivered to cultured myofibroblast in the form of a fusion peptide (FP) with a cell penetrating sequence, it inhibits their contractile activity; moreover, upon topical administration in vivo it inhibits the contraction of rat wound granulation tissue. The NH2-terminal peptide of α–skeletal actin has no effect on myofibroblasts, whereas the NH2-terminal peptide of β–cytoplasmic actin abolishes the immunofluorescence staining for this isoform without influencing α-SMA distribution and cell contraction. The FPs represent a new tool to better understand the specific functions of actin isoforms. Our findings support the crucial role of α-SMA in wound contraction. The α-SMA–FP will be useful for the understanding of the mechanisms of connective tissue remodeling; moreover, it furnishes the basis for a cytoskeleton-dependent preventive and/or therapeutic strategy for fibrocontractive pathological situations.
Niche Filtering of Bacteria in Soil and Rock Habitats of the Colorado Plateau Desert, Utah, USA

A common feature of microbial colonization in deserts is biological soil crusts (BSCs), and these comprise a complex community dominated by Cyanobacteria. Rock substrates, particularly sandstone, are also colonized by microbial communities. These are separated by bare sandy soil that also supports microbial colonization. Here we report a high-throughput sequencing study of BSC and cryptoendolith plus adjacent bare soil communities in the Colorado Plateau Desert, Utah, USA. Bare soils supported a community with low levels of recoverable DNA and high evenness, whilst BSC yielded relatively high recoverable DNA, and reduced evenness compared to bare soil due to specialized crust taxa. The cryptoendolithic community displayed the greatest evenness but the lowest diversity, reflecting the highly specialized nature of these communities. A strong substrate-dependent pattern of community assembly was observed, and in particular cyanobacterial taxa were distinct. Soils were virtually devoid of photoautotrophic signatures, BSC was dominated by a closely related group of Microcoleus/Phormidium taxa, whilst cryptoendolithic colonization in sandstone supported almost exclusively a single genus, Chroococcidiopsis. We interpret this as strong evidence for niche filtering of taxa in communities. Local inter-niche recruitment of photoautotrophs may therefore be limited and so communities likely depend significantly on cyanobacterial recruitment from distant sources of similar substrate. We discuss the implication of this finding in terms of conservation and management of desert microbiota.
Ambiguous (((Par(t)(it))((ion))(s))(in)) Thai Text

Despite the importance of segmentation to a variety of software applications, almost nothing is known about the characteristics or distribution of ambiguous partitions (eg. to Pend vs. top_end) in Thai text. By using special-purpose code to investigate a large (-400K word) text corpus, we were able to extract 36,267 such sequences, involving 9,253 distinct examples. Of these, a little more than two-fifths involved genuinely ambiguous partitions. We classify partitioning problems into distinct categories, report on many of their statistical and lexical characteristics, and describe heuristics for choosing the correct partition that do not depend on the availability of a large segmented corpus. 1. Introduction Thai writing does not use spaces to segment text into words. While open text contains many obvious separation points (bigdog vs. big dog), and a smaller group of questionable bind points that are usually permissible either way (toolbox vs. toolbox), there is inevitably a residue of ambiguous partition points (to_pend vs. top_end) for which computer segmentation is essentially random. This causes difficulty for many software applications: line-breaking, spell-checking, machine-assisted translation, text-to-speech, optical character recognition, full-text indexing, corpus-based dictionaries, etc. Yet despite the importance of segmentation, little is known about the characteristics of ambiguous partitions in Thai, or its orthographic cousins Khmer, Lao, and Burmese. Work has been slow and progress poor due to a lack of formal, concrete analysis. We know the problem's gross characteristics, and the general direction of solutions, but there are few theories to guide the way or allow comparison of research results. This paper describes experiments carried out on a 2 megabyte (roughly 400,000 word) Thai corpus. We collected nearly ten thousand distinct alternative segmentations of at least two words in length. Of these, a little more than two-fifths involved genuinely ambiguous partitions. We classify partitioning problems into distinct categories, report on statistical and lexical characteristics of ambiguous partitions, and describe heuristics for disambiguating that do not depend on the availability of a large segmented corpus. Our results make several contributions to understanding Thai text segmentation. First, we categorize breakpoints in a way that distinguishes between choices that are and are not semantically significant, and show how to collect them automatically and consistently. Second, we find that ambiguous instances are fairly rare (roughly 5% of word break opportunities), and have a pronounced Zipfian distribution — a relatively small number of circumstances produce a great deal of ambiguity; and show ways of collecting low-frequency items that exhibit the same behavior. Third, we find that contrary to the canonical examples, resolving ambiguity does not usually depend on knowing or understanding the context it occurs in. Finally, we suggest new methods — stop nodes, go collocates, and analysis of hidden 'swing strings' — to aid in automated disambiguation.