Miracle-dz/UniFAR-FTUs huggingface dataset:
Favipiravir (T-705) Inhibits Junín Virus Infection and Reduces Mortality in a Guinea Pig Model of Argentine Hemorrhagic Fever

Background Junín virus (JUNV), the etiologic agent of Argentine hemorrhagic fever (AHF), is classified by the NIAID and CDC as a Category A priority pathogen. Presently, antiviral therapy for AHF is limited to immune plasma, which is readily available only in the endemic regions of Argentina. T-705 (favipiravir) is a broadly active small molecule RNA-dependent RNA polymerase inhibitor presently in clinical evaluation for the treatment of influenza. We have previously reported on the in vitro activity of favipiravir against several strains of JUNV and other pathogenic New World arenaviruses. Methodology/Principal Findings To evaluate the efficacy of favipiravir in vivo, guinea pigs were challenged with the pathogenic Romero strain of JUNV, and then treated twice daily for two weeks with oral or intraperitoneal (i.p.) favipiravir (300 mg/kg/day) starting 1–2 days post-infection. Although only 20% of animals treated orally with favipiravir survived the lethal challenge dose, those that succumbed survived considerably longer than guinea pigs treated with placebo. Consistent with pharmacokinetic analysis that showed greater plasma levels of favipiravir in animals dosed by i.p. injection, i.p. treatment resulted in a substantially higher level of protection (78% survival). Survival in guinea pigs treated with ribavirin was in the range of 33–40%. Favipiravir treatment resulted in undetectable levels of serum and tissue viral titers and prevented the prominent thrombocytopenia and leucopenia observed in placebo-treated animals during the acute phase of infection. Conclusions/Significance The remarkable protection afforded by i.p. favipiravir intervention beginning 2 days after challenge is the highest ever reported for a small molecule antiviral in the difficult to treat guinea pig JUNV challenge model. These findings support the continued development of favipiravir as a promising antiviral against JUNV and other related arenaviruses.
Following the evolution of distributed Communities of Practice

Symbiotic computing leads to a proliferation of computing devices that in turn allow linking people, favouring the development of Communities of Practice (CoPs). The notion of Communities of Practice is newer than the social organization it describes, but the emergence of technologies based on the Internet like emails, forums, blogs, wikis, conference calls, video-conference facilitated the creation of a new kind of CoP: the distributed CoP. Distributed CoPs are CoPs whose members being dispersed geographically have to rely strongly on technological means to interact. Distributed CoPs face new issues due to the distance among members, the size of the community and the cultural differences. In this context, coordinating distributed CoPs is even more challenging than coordinating their collocated counterparts. Things that happen rather spontaneously in a collocated community must be instigated in a distributed one, overloading the coordination of distributed CoPs. The increasing role of the coordination should be supported by an adequate set of coordination tools. In this paper we present a tool that aims at supporting the coordination of distributed CoPs. This tool lets the coordination follow the evolution of the community. It analyzes the exchanges among members and shows this information in a graphical format in order to help the coordination to follow the evolution of the participation and the domain of the community.
A scheme of MAC/PHY cross-layer design in MIMO ad hoc networks based on random number allocation strategy

It is well known that MIMO technology can provide additional space degrees of freedom and increase the channel capacity greatly. However, it is a challenge to design the MAC layer when using MIMO in ad hoc networks. In FT (Follow Traffic) scheme, RTS/CTSs are sent simultaneously and used to estimate the traffic load. The node allocates the channel estimation resources in order of decreasing received power of RTS. Though FT scheme greatly improves the throughput, the fairness among nodes is declined and the complexity of receivers is increased. To address the problem, this paper presents a scheme of MAC layer based on random number allocation strategy, in which the node allocates the channel estimation resources in an increasing order of random number in each RTS. The throughput performance of the proposed scheme is suboptimal, but it ensures the fairness and reduces the complexity of the receivers.
A Probabilistic Model for Student Knowledge Diagnosis in Learning Environments

Nowadays, the way learners acquire and improve their knowledge has changed compared to several years ago. The use of new technologies, in conjunction with Artificial Intelligence (AI) and psychological research in the field of education, has made it possible to obtain a new generation of learning environments, which are more effective than traditional methods[1]. These intelligent tutoring environments are computer assisted tools capable of both representing knowledge and directing a learning strategy. Thus they are able to mimic the behavior of an expert, teaching the students how to apply knowledge and estimating their knowledge from how they interact with the system. As a result, learners can be redirected to the most appropriate action. To achieve these goals, the maintenance and use of a model that reflects the student knowledge is vital. Such a model allows the student weaknesses and strengths to be ascertained and a pedagogical strategy for appropriate instruction to be developed. We have previous experience in the development of educational tools [2]. Nevertheless, this system is focused on assessing declarative knowledge using tests. We want to extend our previous work to cover both declarative and procedural knowledge assessment. For this reason, the main goal of our current research is to study existing approaches for building student models in problem solving environments, and to develop a novel methodology or framework to facilitate the elicitation of diagnosis modules for such environments. In this line, we have explored existing student modeling techniques and have tried to identify how we could improve them to create a versatile student model (in the context of the application domain), with accurate estimations of the student knowledge.
Spontaneous Facial Behavior Computing in Human Machine Interaction with Applications in Autism Treatment

Digital devices and computing machines such as computers, hand-held devices and robots are becoming an important part of our daily life. To have affect-aware intelligent Human-Machine Interaction (HMI) systems, scientists and engineers have aimed to design interfaces which can emulate face-to-face communication. Such HMI systems are capable of detecting and responding upon users’ emotions and affective states. One of the main challenges for producing such intelligent system is to design a machine, which can automatically compute spontaneous behaviors of humans in real-life settings. Since humans’ facial behaviors contain important non-verbal cues, this dissertation studies facial actions and behaviors in HMI systems. The main two objectives of this dissertation are: 1capturing, annotating and computing spontaneous facial expressions in a Human-Computer Interaction (HCI) system and releasing a database that allows researchers to study the dynamics of facial muscle movements in both posed and spontaneous data. 2developing and deploying a robot-based intervention protocol for autism therapeutic applications and modeling facial behaviors of children with high-functioning autism in a real-world HumanRobot Interaction (HRI) system. Because of the lack of data for analyzing the dynamics of spontaneous facial expressions, my colleagues and I introduced and released a novel database called ”Denver Intensity of Spontaneous Facial Actions (DISFA)” . DISFA describes facial expressions using Facial Action Coding System (FACS) – a gold standard technique which annotates facial
Impact of Manipulated Perceived Efficacy and Self-Affirmation on Measures of Risk, Efficacy, and Intention

In the developed world, the principal sources of morbidity and mortality are diseases of lifestyle, and one of the central goals of health promotion is the encouragement of riskreducing behaviour. In a series of 3 studies, the present program of research examined the effect of self-affirmation and manipulated perceived efficacy on perceptions of efficacy, risk perception, and risk-reducing behavioural intentions. Participants were undergraduate students who were randomly assigned to a self-affirmation manipulation (self-affirmation versus no self-affirmation) and a perceived efficacy manipulation (high versus low versus baseline), followed by exposure to negative health risk information (risk of a heart attack or colorectal cancer). Across the 3 studies, factor analyses indicated 3 distinct categories of risk-reducing intentions: intentions associated with maintaining an active lifestyle, seeking medical advice and assessment, and maintaining a healthy diet. There was little evidence that self-affirmation affected efficacy, risk, or intentions. Structural equation modeling and meta-analytic analyses suggested the presence of a suppression effect for risk perception: a manipulation designed to increase perceived efficacy had direct positive effects on risk, but also had indirect negative effects on risk, with measured efficacy acting as a mediator. These analyses also showed that the 3 categories of behavioural intentions had distinct (and often different) antecedents. These results highlight the complexity of variables in health risk behaviour. Implications and future directions are discussed. Risk, Efficacy, and Intention ii
Isolation and characterization of nuclear envelopes from the yeast Saccharomyces

We have developed a large scale enrichment procedure to prepare yeast nuclear envelopes (NEs). These NEs can be stripped of peripheral proteins to produce a heparin-extracted NE (H-NE) fraction highly enriched in integral membrane proteins. Extraction of H-NEs with detergents revealed previously uncharacterized ring structures associated with the NE that apparently stabilize the grommets of the nuclear pore complexes (NPCs). The high yields obtained throughout the fractionation procedure allowed balance-sheet tabulation of the subcellular distribution of various NE and non-NE proteins. Thus we found that 20% of endoplasmic reticulum (ER) marker proteins are localized at the NE. Using a novel monospecific mAb made against proteins in the H-NE fraction and found to be directed against the pore membrane protein POM152, we showed that while the majority of POM152 is localized in the NE at the NPC, a proportion of this protein is also present in the ER. This ER pool of POM152 is likely to be involved in the duplication of nuclear pores and NPCs during S-phase. Both the NEs and H-NEs were found to be competent for the in vitro posttranslational translocation of prepro-alpha-factor. They may also be suitable to investigate other ER- and NE-associated functions in cell-free systems.
Molecular and genetic evidence for abnormalities in the nodes of Ranvier in schizophrenia.

CONTEXT Genetic, neuroimaging, and molecular neurobiological evidence support the hypothesis that the disconnectivity syndrome in schizophrenia (SZ) could arise from failures of saltatory conduction and abnormalities at the nodes of Ranvier (NOR) interface where myelin and axons interact. OBJECTIVE To identify abnormalities in the expression of oligodendroglial genes and proteins that participate in the formation, maintenance, and integrity of the NOR in SZ. DESIGN The messenger RNA (mRNA) expression levels of multiple NOR genes were quantified in 2 independent postmortem brain cohorts of individuals with SZ, and generalizability to protein expression was confirmed. The effect of the ANK3 genotype on the mRNA expression level was tested in postmortem human brain. Case-control analysis tested the association of the ANK3 genotype with SZ. The ANK3 genotype's influence on cognitive task performance and functional magnetic resonance imaging activation was tested in 2 independent cohorts of healthy individuals. SETTING Research hospital. Patients Postmortem samples from patients with SZ and healthy controls were used for the brain expression study (n = 46) and the case-control analysis (n = 272). Healthy white men and women participated in the cognitive (n = 513) and neuroimaging (n = 52) studies. MAIN OUTCOME MEASURES The mRNA and protein levels in postmortem brain samples, genetic association with schizophrenia, cognitive performance, and blood oxygenation level-dependent functional magnetic resonance imaging. RESULTS The mRNA expression of multiple NOR genes was decreased in schizophrenia. The ANK3 rs9804190 C allele was associated with lower ANK3 mRNA expression levels, higher risk for SZ in the case-control cohort, and poorer working memory and executive function performance and increased prefrontal activation during a working memory task in healthy individuals. CONCLUSIONS These results point to abnormalities in the expression of genes and protein associated with the integrity of the NOR and suggest them as substrates for the disconnectivity syndrome in SZ. The association of ANK3 with lower brain mRNA expression levels implicates a molecular mechanism for its genetic, clinical, and cognitive associations with SZ.
Modelling sustainable urban development by the integration of constrained cellular automata and GIS

Cellular Automata (CA) have attracted growing attention in urban simulation because their capability in spatial modelling is not fully developed in GIS. This paper discusses how cellular automata (CA) can be extended and integrated with GIS to help planners to search for better urban forms for sustainable development. The cellular automata model is built within a grid-GIS system to facilitate easy access to GIS databases for constructing the constraints. The essence of the model is that constraint space is used to regulate cellular space. Local, regional and global constraints play important roles in affecting modelling results. In addition, 'grey' cells are defined to represent the degrees or percentages of urban land development during the iterations of modelling for more accurate results. The model can be easily controlled by the parameter k using a power transformation function for calculating the constraint scores. It can be used as a useful planning tool to test the effects of different urban development scenarios.
Semantic analysis for tomorrow's audio-visual digital archives

PrestoSpace is a European-funded research project that aims at addressing the problem of decaying audio-visual archives throughout Europe by means of digitisation for preservation and access. One of the work areas within the project is Metadata Access and Delivery (MAD) which employs innovative methods of generating metadata for the digitised media in order to enhance the resulting archives and to ease access to the stored material. One such method is the use of automatic semantic analysis using natural language processing techniques in the process of creating analytical metadata for the preserved essence.
The Effect of Using What Is It? Technique on Students’ Writing Achievement and Their Motivation

The purpose of the study was to find out the effect of using What is it? Technique on students’ writing achievement and their motivation on descriptive paragraphs at state Junior High School 1 Kampar. This study was an experimental research which was intended to find out the effect of using What is it? Technique on the students’ writing achievement and their motivation. The participants of the study comprised 57 students found in 2 classes randomized from seven classes. Treatment by using What is it? Technique was given to an experimental class (n=29) but a control class (n=28) was not given treatment by using What is it? Technique. Data were collected using a writing test for writing achievement and a questionnaire for writing motivation. The data were analyzed by using inferential statistics. The findings showed that there was a significant effect of using What is it Technique on their achievement in writing descriptive paragraphs and there was a significant effect of using What is it? Technique on their motivation in writing descriptive paragraphs.
Performance-driven analog placement considering monotonic current paths

Although modern analog placement algorithms aimed to minimize area and wirelength while satisfying symmetry, proximity, and other placement constraints, the generated layout does not reflect the circuit performance very well because of the routing-induced parasitics on the critical current/signal paths. This paper introduces the current-path constraints in analog placement, demonstrates their impact on circuit performance, and derives new problem formulation and algorithms to find placement solutions with monotonic current paths. Experimental results show that the proposed formulation and algorithms can generate compact layouts resulting in the even better circuit performance after performing post-layout simulation.
An Automated Model to Identify Heart Failure Patients at Risk for 30-Day Readmission or Death Using Electronic Medical Record Data

Background:A real-time electronic predictive model that identifies hospitalized heart failure (HF) patients at high risk for readmission or death may be valuable to clinicians and hospitals who care for these patients. Methods:An automated predictive model for 30-day readmission and death was derived and validated from clinical and nonclinical risk factors present on admission in 1372 HF hospitalizations to a major urban hospital between January 2007 and August 2008. Data were extracted from an electronic medical record. The performance of the electronic model was compared with mortality and readmission models developed by the Center for Medicaid and Medicare Services (CMS models) and a HF mortality model derived from the Acute Decompensated Heart Failure Registry (ADHERE model). Results:The 30-day mortality and readmission rates were 3.1% and 24.1% respectively. The electronic model demonstrated good discrimination for 30 day mortality (C statistic 0.86) and readmission (C statistic 0.72) and performed as well, or better than, the ADHERE model and CMS models for both outcomes (C statistic ranges: 0.72–0.73 and 0.56–0.66 for mortality and readmissions respectively; P < 0.05 in all comparisons). Markers of social instability and lower socioeconomic status improved readmission prediction in the electronic model (C statistic 0.72 vs. 0.61, P < 0.05). Conclusions:Clinical and social factors available within hours of hospital presentation and extractable from an EMR predicted mortality and readmission at 30 days. Incorporating complex social factors increased the model's accuracy, suggesting that such factors could enhance risk adjustment models designed to compare hospital readmission rates.
A proposed framework for segment transmission scheduling in P2P video streaming

Segment transmission scheduling is essential in peer to peer video streaming. Transmission of the video segments faces some difficulties. Long playback buffering delay and high chunk miss ratio are the major ones of these difficulties. This paper introduces a proposed framework to overcome these difficulties. Moreover, it improves the overall performance of the streaming system. The framework is described in terms of four phases; in the first phase, unavailable segments and the partners for each segment are specified. By the end of the second phase, the priorities of unavailable segments are estimated according to segments' deadline time and number of available partners. In the third phase, the available partners are evaluated according to the bandwidth and the reputation estimation. Finally, the segment's sender is selected from the available partners according to the considerations that improve the performance of P2P video streaming. A simulation results are achieved to compare the performance of the proposed framework algorithms with respect to previous algorithms. The simulation results showed that proposed framework algorithms outperform previous algorithms.
A Requirement Framework for Automatic Generation of Domain Model to Physical Level Implementation

The requirement analysis is a key component of Model Driven Development (MDD). The wrong information captured in the requirement specification document may lead to faulty development that needs additional cost for correction. The development of the domain model, based on the specified requirement, is a manual activity done by highly skilled architects. This adds huge amount of labor cost in the project. In real world scenario where the requirement gets updated frequently by the client to meet the global market trend, development project gets highly affected due to considerable amount of time, resource and cost involvement for the respective changes. In this paper, a simple word processor based requirement framework is proposed for our object-oriented graph-based conceptual model Extended Graph Data Model (EGDM) [1, 2]. Moreover the methodology for automatic generation of domain model from the requirement framework is also proposed here. The entire concept is being crystallized in the form of a three-phase integrated tool called “e-synthesis”. The domain model is designed through a model designing tool Generic Modeling Environment (GME) [3] using the constructs defined in EGDM. The proposed requirement framework also automates the iterative development process exploiting several consistency checking and validation. This makes the domain model more efficient in terms of cost effectiveness. Further, the necessary mapping rules to convert EGDM based domain model into Product Specific Model (PSM) using SQL: 2003 standard [4] and development of an interpreter based on those rules have been proposed here.
Interval Computations No 2 , 1994 Solving the Tolerance Problem for Interval Linear Systems

For the interval linear system Ax = b, we consider the linear tolerance problem, requiring inner evaluation of the tolerable solution set Σ∀∃(A,b) = {x∈ R|(∀A∈A)(Ax∈b)} formed by all point vectors x such that the product Ax remains within b for all possible A∈A. We develop solvability theory for the linear tolerance problem that not only settles whether Σ∀∃ is empty or not, but also enables modification of the problem to ensure its desired properties. The paper concludes with a survey of new methods for construction of an interval solution to the linear tolerance problem around a given center.
Features of the 27-Day Variations of the Galactic Cosmic Ray Intensity and Anisotropy

We study the 27-day variations of the galac- tic cosmic ray (GCR) intensity and three dimensional (3-D) anisotropy in different polarity periods of the solar magnetic cycle. We found that the larger amplitudes of the 27-day vari- ations of the galactic cosmic ray anisotropy and intensity in the minimum epochs of solar activity for the A> 0 polarity period than for the A 0 polarity period. The 27-day variation of the GCR 3-D anisotropy has a sporadic character; it appears and disappears as wave packages (wave oscillations) with an average duration of 4-6 solar rotations. We found that the rigidity R power law spectrum of the am- plitudes (A27) of the 27-day variation of the GCR intensity (A27/R ) is hard ( = 0.54± 0.11) in the A> 0 polar- ity period (1996-1997) and is soft ( = 0.95± 0.12) in the A< 0 period (1986-1987).