Miracle-dz/UniFAR-FTUs huggingface dataset:
A Human Herpesvirus 6A-Encoded MicroRNA: Role in Viral Lytic Replication

ABSTRACT Human herpesvirus 6A (HHV-6A), a member of the betaherpesvirus family, is associated with several human diseases. Like all herpesviruses, HHV-6A establishes a lifelong, latent infection in its host. Reactivation of HHV-6A is frequent within the immunosuppressed and immunocompromised populations and results in lytic viral replication within multiple organs, often leading to severe disease. MicroRNAs (miRNAs) are key regulators of multiple cellular processes that regulate the translation of specific transcripts. miRNAs carried by herpesviruses play important roles in modulating the host cell, thereby facilitating a suitable environment for productive viral infection and/or latency. Currently, there are approximately 150 known human herpesvirus-encoded miRNAs, although an miRNA(s) encoded by HHV-6A has yet to be reported. We hypothesized that HHV-6A, like other members of the human herpesvirus family, encodes miRNAs, which function to promote viral infection. We utilized deep sequencing of small RNA species isolated from cells harboring HHV-6A to identify five novel small noncoding RNA species that originate from the viral genome, one of which has the characteristics of a viral miRNA. These RNAs are expressed during productive infection by either bacterial artificial chromosome (BAC)-derived virus in Jjhan cells or wild-type HHV-6A strain U1102 virus in HSB2 cells and are associated with the RNA induced silencing complex (RISC) machinery. Growth analyses of mutant viruses that lack each individual miRNA revealed that a viral miRNA candidate (miR-U86) targets the HHV-6A IE gene U86, thereby regulating lytic replication. The identification and biological characterization of this HHV-6A-specific miRNA is the first step to defining how the virus regulates its life cycle. IMPORTANCE A majority of the human population is infected with human herpesvirus 6A (HHV-6A), a betaherpesvirus family member. Infections usually occur in young children, and upon resolution, the virus remains in a latent state within the host. Importantly, during times of weakened immune responses, the virus can reactivate and is correlated with significant disease states. Viruses encode many different types of factors that both undermine the host antiviral response and regulate viral replication, including small RNA species called microRNAs (miRNAs). Here we report that HHV-6A encodes at least one miRNA, which we named miR-U86. We have characterized the requirement of this viral miRNA and its impact on the viral life cycle and found that it functions to regulate a viral protein important for efficient viral replication. Our data suggest that viral miRNAs are important for HHV-6A and that they may serve as an important therapeutic target to inhibit the virus.
Efficient incremental validation of XML documents

We discuss incremental validation of XML documents with respect to DTDs and XML schema definitions. We consider insertions and deletions of subtrees, as opposed to leaf nodes only, and we also consider the validation of ID and IDREF attributes. For arbitrary schemas, we give a worst-case n log n time and linear space algorithm, and show that it often is far superior to revalidation from scratch. We present two classes of schemas, which capture most real-life DTDs, and show that they admit a logarithmic time incremental validation algorithm that, in many cases, requires only constant auxiliary space. We then discuss an implementation of these algorithms that is independent of, and can be customized for different storage mechanisms for XML. Finally, we present extensive experimental results showing that our approach is highly efficient and scalable.
Appmon: An Application for Accurate per Application Network Traffic Characterization

Accurate per-application network traffic characterization is becoming increasingly difficult in the face of emerging applications that use dynamically negotiated port numbers. At the same time, information about the contribution of different network applications and services to the traffic mix is highly demanded by network administrators for facilitating effective network management and traffic engineering. In this paper we present appmon , a passive monitoring application for per-application network traffic classification. Appmon uses deep packet inspection to accurately attribute traffic flows to the applications that generate them, and reports in real time the network traffic breakdown through a Web-based GUI. Appmon is easy to configure and deploy, and is publicly available as an open source application.
Determining Word-Emotion Associations from Tweets by Multi-label Classification

The automatic detection of emotions in Twitter posts is a challenging task due to the informal nature of the language used in this platform. In this paper, we propose a methodology for expanding the NRC word-emotion association lexicon for the language used in Twitter. We perform this expansion using multi-label classification of words and compare different word-level features extracted from unlabelled tweets such as unigrams, Brown clusters, POS tags, and word2vec embeddings. The results show that the expanded lexicon achieves major improvements over the original lexicon when classifying tweets into emotional categories. In contrast to previous work, our methodology does not depend on tweets annotated with emotional hashtags, thus enabling the identification of emotional words from any domain-specific collection using unlabelled tweets.
Suicide Prevention Public Service Announcements Impact Help-Seeking Attitudes: The Message Makes a Difference

Suicide continues to be one of the most serious public health challenges. Public service announcements (PSAs) are frequently used to address this challenge, but are rarely sufficiently evaluated to determine if they meet the intended goals, or are associated with potential iatrogenic effects. Although it is challenging to assess the relative impact of different PSA modalities, our group previously noted that one billboard message failed to show the same benefits as one TV ad [e.g., Klimes-Dougan and Lee (1)]. The purpose of this study was to extend these findings to test critical aspects of suicide prevention billboard messaging. Although both simulated billboard messages presented had identical supporting messages, we predicted that the more personal billboard message, focused on saving one’s life, would cause more favorable help-seeking attitudes than the message focused on suicide. Young adult university students (N = 785) were randomly assigned to one of three conditions; one of two billboard simulations or a TV ad simulation. Help-seeking attitudes, maladaptive coping, and reports of concern and distress were evaluated. The results of this study suggest some relative benefits in endorsement of favorable help-seeking attitudes for one of the billboard conditions – stop depression from taking another life. Although further research is needed to determine what methods will alter the risk for suicide in the population, the results of this study provide a useful first step showing that some billboard messaging may favorably influence help-seeking attitudes.
Yet Robust Caching Algorithm Based on Dynamic Access Patterns

An apparatus and method for towing a pipeline in a body of water to a place where the pipeline is to be laid on the bed of the body of water, the pipeline having a positive buoyancy and being provided with trail-ropes distributed therealong which drag on the bed while the pipeline is being towed and maintain it at a certain distance above the bed, wherein some at least of the trail-ropes are connected to the pipeline at points spaced apart therein in such manner that such trail-ropes are formed with arcuate portions extending between the points of attachment to the pipeline so that when said arcuate portions drag upon the bed they are retained substantially parallel to the longitudinal axis of the pipeline thereby to oppose drift by a transverse current, said trail-ropes also optimally comprising means for penetrating the bed so as to offer increased resistance to drift.
Chronic lipopolysaccharide infusion fails to induce depressive-like behaviour in adult male rats

Background Chronic inflammation is implicated in numerous diseases, including major depression and type 2 diabetes mellitus (T2DM). Since depression and T2DM often co-exist, inflammatory pathways are suggested as a possible link. Hence, the establishment of an immune-mediated animal model would shed light on mechanisms possibly linking depression and metabolic alterations. Objective In this study we investigated a behavioural and metabolic paradigm following chronic infusion with low doses of lipopolysaccharide (LPS) using osmotic minipumps in male rats. Methods Behavioural testing consisted of evaluating activity level in the open field and depressive-like behaviour in the forced swim test. Metabolic assessment included measurement of body weight, food and water intake, and glucose and insulin levels during an oral glucose tolerance test. Results LPS-infused rats showed acute signs of sickness behaviour, but chronic LPS infusion did not induce behavioural or metabolic changes. Conclusion These results suggest that although inflammation is immediately induced as indicated by acute sickness, 4 weeks of chronic LPS administration via osmotic minipumps did not result in behavioural changes. Therefore, this paradigm may not be a suitable model for studying the underlying mechanisms that link depression and T2DM.
The Effects of Industry Employment Shifts on the U

Economist, Banking and Regional Section. John DiNardo p r ovided very helpful discussions of the statistical approach used. I am grateful to Fred Furlong, Ken Kasa, and especially Mary Daly for their careful review of this paper. I also thank Nan Maxwell and session participants at the 19 9 6 Western Economic Association Meetings for comments on an early version. Randy O’Toole provided useful research assistance.
Ethinylestradiol and testosterone have divergent effects on circulating IGF system components in adolescents with constitutional tall stature.

OBJECTIVE Pharmacological doses of estrogens or testosterone are used to limit the final height of girls or boys with constitutional tall stature but the mechanism behind this growth inhibition is still debated. We therefore studied the changes in the circulating components of the insulin-like growth factor (IGF) system during high dose sex steroid therapy. DESIGN AND METHODS Twenty three girls and twenty boys with constitutional tall stature were treated with 100 microg ethinylestradiol per day or 250 mg testosterone ester every 14 days respectively. In 19 girls and 18 boys, the levels of IGF-I, free IGF-I, IGF-II, acid-labile subunit (ALS) and IGF binding proteins (IGFBP)-2 to -6 were measured before and 3-6 months after the start of therapy (group 1). In 18 girls and 11 boys, samples were collected at the end of therapy and 3 to 6 months afterwards (group 2). Fourteen girls and nine boys belonged to both groups. All parameters were measured by radioimmunoassay or ELISA. RESULTS Levels of IGF-I were decreased significantly by estrogen treatment but remained unchanged during testosterone treatment. Free IGF-I decreased during estrogen treatment but increased during testosterone therapy. Estrogens increased IGF-II and testosterone reduced it. The important reduction of IGFBP-2 during estrogen therapy is not reproduced by androgen therapy, neither is the stimulation by estrogens of IGFBP-4. IGFBP-3 is not modulated by either sex steroid. We found that IGFBP-6 is up-regulated by testosterone but not by estrogens; the reverse is true for ALS, which increased during estrogen treatment but remained unchanged during testosterone treatment. CONCLUSIONS Our findings demonstrate that androgens and estrogens exert differential effects on the circulating levels of several IGF components.
Statistical similarity search applied to content-based video copy detection

Content-based copy detection (CBCD) is one of the emerging multimedia applications for which there is a need of a concerted effort from the database community and the computer vision community. Recent methods based on interest points and local fingerprints have been proposed to perform robust CBCD of images and video. They include two steps: the search of similar fingerprints in the database and a voting strategy that merges all the local results in order to perform a global decision. In most image or video retrieval systems, the search of similar features in the database is performed by a geometrical query in a multidimensional index structure. Recently, the paradigm of approximate knearest neighbors query has shown that trading quality for time can be widely profitable in that context. In this paper, we introduce a new approximate search paradigm, called Statistical Similarity Search (S3), dedicated to local fingerprints and we describe the original indexing structure we have developped to compute efficiently the corresponding queries. The key-point relates to the distribution of the relevant fingerprints around a query. Since a video query can result from (a combination of ) more or less transformations of an original one, we modelize the distribution of the distorsion vector between a referenced fingerprint and a candidate one. Experimental results show that these statistical queries allow high performance gains compared to classical e-range queries. By studying the influence of this approximate search on a complete CBCD scheme based on local video fingerprints, we also show that trading quality for time during the search does not degrade seriously the global robustness of the system, even with very large databases including more than 20,000 hours of video.
Improved cepstral mean and variance normalization using Bayesian framework

Cepstral Mean and Variance Normalization (CMVN) is a computationally efficient normalization technique for noise robust speech recognition. The performance of CMVN is known to degrade for short utterances, due to insufficient data for parameter estimation and loss of discriminable information as all utterances are forced to have zero mean and unit variance. In this work, we propose to use posterior estimates of mean and variance in CMVN, instead of the maximum likelihood estimates. This Bayesian approach, in addition to providing a robust estimate of parameters, is also shown to preserve discriminable information without increase in computational cost, making it particularly relevant for Interactive Voice Response (IVR)-based applications. The relative WER reduction of this approach w.r. t. Cepstral Mean Normalization, CMVN and Histogram Equalization are (i) 40.1%, 27% and 4.3% with the Aurora2 database for all utterances, (ii) 25.7%, 38.6% and 30.4% with the Aurora2 database for short utterances, and (iii) 18.7%, 12.6% and 2.5% with the Aurora4 database.
Automating human based negotiation processes for autonomic logistics

Affordability and responsiveness are two key requirements for the next generation of aircraft support systems. Aircraft have to be repaired with minimum downtime and the support process has to be economical and efficient. The vision of autonomic logistics (AL) entails a maintenance and support system that can autonomously respond to "events", e.g. problems detected on-board the aircraft. The response includes identifying the source of the problem, acquiring the correct parts and tools, locating and scheduling the right maintenance personnel. Currently, software tools and packages are available that can provide functional components for an AL system, but the integration of these does not exist yet. The paper discusses how agent technology in general and negotiation processes in particular can be applied to build an AL system. We envision a system where existing, "legacy" packages are integrated via an agent framework: a higher-level layer that ties together the packages. Agents represent tasks that need to be performed in an AL system, and they autonomously exist, navigate, and negotiate within the framework. This approach, while emphasizing automation, is not that different from existing, human processes. Even in existing maintenance organizations human negotiation is an accepted practice, which, in many cases, "makes the system work", in spite of rigid, formal rules. Thus, we envision that the autonomous, negotiation-based system will provide the required capabilities for an AL system to increase readiness and turn-around rates, and to decrease costs.
Lightweight Memory Tracing

Memory tracing (executing additional code for every memory access of a program) is a powerful technique with many applications, e.g., debugging, taint checking, or tracking dataflow. Current approaches are limited: software-only memory tracing incurs high performance overhead (e.g., for Libdft up to 10×) because every single memory access of the application is checked by additional code that is not part of the original application and hardware is limited to a small set of watched locations. This paper introduces memTrace, a lightweight memory tracing technique that builds on dynamic on-the-fly cross-ISA binary translation of 32-bit code to 64-bit code. Our software-only approach enables memory tracing for unmodified, binary-only ×86 applications using the ×64 extension that is available in current CPUs; no OS extensions or special hardware is required. The additional registers in ×64 and the wider memory addressing enable a low-overhead tracing infrastructure that is protected from the application code (i.e., uses disjunct registers and memory regions). MemTrace handles multi-threaded applications. Two case studies discuss a framework for unlimited read and write watchpoints and an allocation-based memory checker similar in functionality to memgrind. The performance evaluation of memTrace shows that the time overhead is between 1.3× and 3.1× for the SPEC CPU2006 benchmarks, with a geometric mean of 1.97×.
TIDDIT, an efficient and comprehensive structural variant caller for massive parallel sequencing data

Reliable detection of large structural variation ( > 1000 bp) is important in both rare and common genetic disorders. Whole genome sequencing (WGS) is a technology that may be used to identify a large proportion of the genomic structural variants (SVs) in an individual in a single experiment. Even though SV callers have been extensively used in research to detect mutations, the potential usage of SV callers within routine clinical diagnostics is still limited. One well known, but not well-addressed problem is the large number of benign variants and reference errors present in the human genome that further complicates analysis. Even though there is a wide range of SV-callers available, the number of callers that allow detection of the entire spectra of SV at a low computational cost is still relatively limited.
Detection of Orthopoxvirus DNA by Real-Time PCR and Identification of Variola Virus DNA by Melting Analysis

ABSTRACT Although variola virus was eradicated by the World Health Organization vaccination program in the 1970s, the diagnosis of smallpox infection has attracted great interest in the context of a possible deliberate release of variola virus in bioterrorist attacks. Obviously, fast and reliable diagnostic tools are required to detect variola virus and to distinguish it from orthopoxviruses that have identical morphological characteristics, including vaccinia virus. The advent of real-time PCR for the clinical diagnosis of viral infections has facilitated the detection of minute amounts of viral nucleic acids in a fast, safe, and precise manner, including the option to quantify and to genotype the target reliably. In this study a complete set of four hybridization probe-based real-time PCR assays for the specific detection of orthopoxvirus DNA is presented. Melting analysis following PCR enables the identification of variola virus by the PCR product's characteristic melting temperature, permitting the discrimination of variola virus from other orthopoxviruses. In addition, an assay for the specific amplification of variola virus DNA is presented. All assays can be performed simultaneously in the same cycler, and results of a PCR run are obtained in less than 1 h. The application of more than one assay for the same organism significantly contributes to the diagnostic reliability, reducing the risk of false-negative results due to unknown sequence variations. In conclusion, the assays presented will improve the speed and reliability of orthopoxvirus diagnostics and variola virus identification.
Resistance to levamisole resolved at the single‐channel level

Levamisole is commonly used to treat nematode parasite infections but therapy is limited by resistance. The purpose of this study was to determine the mechanism of resistance to this selective nicotinic drug. Levamisole receptor channel currents in muscle patches from levamisole‐sensitive and levamisole‐resistant isolates of the parasitic nematode Oesophagostomum dentatum were compared. The number of channels present in patches of sensitive and resistant isolates was similar at 10 µM levamisole, but at 30 µM and 100 µM the resistant isolate contained fewer active patches, suggesting desensitization. Mean Po and open times were reduced in resistant isolates. The distribution of conductances of channels in the sensitive isolate revealed a heterogeneous receptor population and the presence of G25, G35, G40, and G45 subtypes. A G35 subtype was missing in the resistant isolate. Resistance to levamisole was produced by changes in the averaged properties of the levamisole receptor population, with some receptors from sensitive and resistant isolates having indistinguishable characteristics. —Robertson, A. P., Bjorn, H. E. , Martin, R. J. Resistance to levamisole resolved at the single‐channel level. FASEB J. 13, 749–760 (1999)
A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning

Existing action detection algorithms usually generate action proposals through an extensive search over the video at multiple temporal scales, which brings about huge computational overhead and deviates from the human perception procedure. We argue that the process of detecting actions should be naturally one of observation and refinement: observe the current window and refine the span of attended window to cover true action regions. In this paper, we propose an active action proposal model that learns to find actions through continuously adjusting the temporal bounds in a self-adaptive way. The whole process can be deemed as an agent, which is firstly placed at a position in the video at random, adopts a sequence of transformations on the current attended region to discover actions according to a learned policy. We utilize reinforcement learning, especially the Deep Q-learning algorithm to learn the agent's decision policy. In addition, we use temporal pooling operation to extract more effective feature representation for the long temporal window, and design a regression network to adjust the position offsets between predicted results and the ground truth. Experiment results on THUMOS 2014 validate the effectiveness of the proposed approach, which can achieve competitive performance with current action detection algorithms via much fewer proposals.
The relationship between an elevated serum amino acid ratio and the development of other biological abnormalities in the experimentally malnourished pig

1. Weanling pigs were fed under three dietary regimens, control, low protein and total calorie restricted. 2. In the protein-deficient group the amino acid ratio did not start to become elevated until growth was impaired and total serum protein and albumin concentration began to fall. 3. In the protein-deficient group, but not in the control or undernourished animals, the magnitude of the ratio was statistically correlated with the rate of growth, appetite, serum protein and albumin concentration and hydroxyproline excretion. 4. The results provide information on the relationship between the serum amino acid ratio and nutritional status.