Miracle-dz/UniFAR-FTUs huggingface dataset:
The roles of lipids and nucleic acids in HIV-1 assembly

During HIV-1 assembly, precursor Gag (PrGag) proteins are delivered to plasma membrane (PM) assembly sites, where they are triggered to oligomerize and bud from cells as immature virus particles. The delivery and triggering processes are coordinated by the PrGag matrix (MA) and nucleocapsid (NC) domains. Targeting of PrGag proteins to membranes enriched in cholesterol and phosphatidylinositol-4,5-bisphosphate (PI[4,5]P2) is mediated by the MA domain, which also has been shown to bind both RNA and DNA. Evidence suggests that the nucleic-acid-binding function of MA serves to inhibit PrGag binding to inappropriate intracellular membranes, prior to delivery to the PM. At the PM, MA domains putatively trade RNA ligands for PI(4,5)P2 ligands, fostering high-affinity membrane binding. Triggering of oligomerization, budding, and virus particle release results when NC domains on adjacent PrGag proteins bind to viral RNA, leading to capsid (CA) domain oligomerization. This process leads to the assembly of immature virus shells in which hexamers of membrane-bound MA trimers appear to organize above interlinked CA hexamers. Here, we review the functions of retroviral MA proteins, with an emphasis on the nucleic-acid-binding capability of the HIV-1 MA protein, and its effects on membrane binding.
SCE based Parallel Processing and Applications in Simulation

In this paper, an overview of SCE based parallel processing is presented, and a new taxonomy for this field is discussed. More than 30 SCE based parallel processing projects are listed and categorized with respect to the new taxonomy. For the Multi-SCE class, performance parameters of several packages are presented in terms of latency and bandwidth. Furthermore, characterization schemes of parallel simulation and optimization applications are presented as well as performance results and characteristics of selected applications being parallelized under usage of Multi-SCE packages.
Design and analysis of frequency adaptive Generalized Integrators for Active Power Filters

Generalized Integrator (GI) used in current control for Active Power Filters (APF) can achieve zero steady-state error for concerned harmonics compensation. This paper presents a controller, based on an array of frequency adaptive GIs, each one for a couple of harmonics, implemented in synchronous reference frame in order to reduce the overall computational effort. In order to eliminate the unexpected loss of gain and mismatch during discretization process, the design work has been directly done in the discrete-time domain. And the frequency adaptive strategy is realized through the use of a special phase-locked loop, thus ensure the good closed-loop performance in spite of the possible grid frequency variation. The experimental results confirm the superiority of the proposed scheme.
Extracting Rules from Neural Networks by Pruning and Hidden-Unit Splitting

An algorithm for extracting rules from a standard three-layer feedforward neural network is proposed. The trained network is first pruned not only to remove redundant connections in the network but, more important, to detect the relevant inputs. The algorithm generates rules from the pruned network by considering only a small number of activation values at the hidden units. If the number of inputs connected to a hidden unit is sufficiently small, then rules that describe how each of its activation values is obtained can be readily generated. Otherwise the hidden unit will be split and treated as output units, with each output unit corresponding to an activation value. A hidden layer is inserted and a new subnetwork is formed, trained, and pruned. This process is repeated until every hidden unit in the network has a relatively small number of input units connected to it. Examples on how the proposed algorithm works are shown using real-world data arising from molecular biology and signal processing. Our results show that for these complex problems, the algorithm can extract reasonably compact rule sets that have high predictive accuracy rates.
Effect of accelerometer-based feedback on physical activity in hospitalized patients with ischemic stroke: a randomized controlled trial

Objective: To evaluate the effect of accelerometer-based feedback on physical activity in hospitalized patients with ischemic stroke. Design: Randomized controlled trial. Setting: Acute care hospital. Subjects: A total of 55 patients with ischemic stroke who could walk without assistance were randomly assigned to the intervention group (n = 27) or the control group (n = 28). Interventions: At the baseline measurement, patients did not receive accelerometer-based feedback. At follow-up, a physical therapist provided instruction on accelerometer-based feedback, discussed physical activity targets and encouraged the patients to walk more until discharge. Main measures: The average daily number of steps taken was used as the index of daily hospitalized physical activity. Results: The study sample consisted of 48 patients, of whom 23 patients comprised the intervention group and 25 patients comprised the control group. Although there were no significant differences in physical activity values between the two groups at the baseline measurement, the values in the intervention group at follow-up were significantly higher than those in the control group (5180.5 ± 2314.9 vs. 3113.6 ± 1150.9 steps/day, P = 0.0003). The effect size of physical activity values (Cohen’s d = 1.15) at follow-up was large between the two groups. Conclusion: Exercise training combined with accelerometer-based feedback effectively increased physical activity in hospitalized patients with ischemic stroke.
Timelines Revisited: A Design Space and Considerations for Expressive Storytelling

There are many ways to visualize event sequences as timelines. In a storytelling context where the intent is to convey multiple narrative points, a richer set of timeline designs may be more appropriate than the narrow range that has been used for exploratory data analysis by the research community. Informed by a survey of 263 timelines, we present a design space for storytelling with timelines that balances expressiveness and effectiveness, identifying 14 design choices characterized by three dimensions: representation, scale, and layout. Twenty combinations of these choices are viable timeline designs that can be matched to different narrative points, while smooth animated transitions between narrative points allow for the presentation of a cohesive story, an important aspect of both interactive storytelling and data videos. We further validate this design space by realizing the full set of viable timeline designs and transitions in a proof-of-concept sandbox implementation that we used to produce seven example timeline stories. Ultimately, this work is intended to inform and inspire the design of future tools for storytelling with timelines.
On the Evolution of Coordinated Multi-Point (CoMP) Transmission in LTE-Advanced

Inter-cell interference is a serious issue in Long Term Evolution (LTE/LTE-Advanced) system. Coordinated Multi-Point (CoMP) operation has been considered as a powerful technology targeted for LTE-A standard to reduce interference, improve spectrum efficiency, increase data throughput and enhance effective coverage area, in particular for cell-edge users, by exploiting the interference signals from different transmission points. In this context, this paper provides a holistic overview of CoMP operation in LTE-A system. Here, we consider the downlink operation, e.g. CoMP transmission, as it is more convenient to explain the system effectively. The technical operation challenges, advantages and operation complexities of different CoMP schemes, CoMP architectures and CoMP sets are described in details in terms of backhaul traffic, synchronization effect and feedback design. Moreover, this article provides clear evidence of CoMP benefits in terms of throughput gain and compares the results with no-CoMP scenario. In addition, it is intended for a wide range of readers as it covers the topic from basics to advanced aspects.
The Convex Hull of Points on a Sphere is a Spanner

Let S be a finite set of points on the unit-sphere S. In 1987, Raghavan suggested that the convex hull of S is a Euclidean t-spanner, for some constant t. We prove that this is the case for t = 3π(π/2 + 1)/2. Our proof consists of generalizing the proof of Dobkin et al. [2] from the Euclidean Delaunay triangulation to the spherical Delaunay triangulation.
Expectation and complex event handling in BDI-based intelligent virtual agents (demonstration)

When operating in virtual communities, intelligent agents should maintain a high-level awareness of the physical and social environment around them in order to be more believable and capable. However, due to the inherent differences between virtual worlds and agent systems such as BDI, such a high-level of awareness has not been achieved for IVAs. In this paper we present a system that enables IVAs to maintain a high-level awareness of their environment by identifying complex events taking place in their environment, as well as by being able to monitor for the fulfilment and violation of their expectations.
Dynamic leadership protocol for S-nets

Smart Sensor Networks (S-nets) are groups of stationary agents (S-elements) which provide distributed sensing, computation, and communication in an environment. In order to integrate information from individual agents and to efficiently transmit this information to other agents, these devices must be able to create local groups (S-clusters). A leadership protocol that creates static clusters has been previously proposed. Here, we further develop this protocol to allow for dynamic cluster updating. This accommodates on-the-fly network re-organization in response to environmental disturbances or the gain or loss of S-elements. We outline an informal argument for the correctness of this revised protocol. We describe our embedded system implementation of the leadership protocol in simulation and using a colony of robots. Finally, we present results demonstrating both implementations.
Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description-four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity (to different behaviors, to function vs. structure), to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene-environment interactions. We argue that gene-behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description.
Biodegradable composites: Morphological, chemical, thermal, and mechanical properties of composites of poly(hydroxybutyrate‐co‐hydroxyvalerate) with curaua fibers after exposure to simulated soil

Composites produced from biodegradable polymeric matrixes reinforced with vegetable fibers have attractive mechanical properties and are environmentally friendly. This work is directed to the biodegradation of a composite made of a poly(hydroxybuty- rate-co-hydroxyvalerate) matrix reinforced with curaua fibers (with and without alkaline treatment) in simulated soil. The composites were developed by extrusion and injection and were later buried in simulated soil according to the ASTM G160-03 method. Scanning electron microscopy showed evidence of microbial attack on the samples surfaces. Infrared spectra showed that the composites biode- gradation was mainly caused by erosion of the surface layer resulting from microorganisms activity. Thermogravimetric analysis pointed out reduced thermal stability of the samples, and results of differential scanning calorimetry showed that the degree of crys- tallinity increases and then decreases progressively throughout the degradation period, indicating that enzymatic degradation primar- ily occurs in the amorphous phase material and thereafter in the crystalline phase. For curaua composite fibers, reductions in tensile strength and elastic modulus are more significant, indicating that the presence of fibers promotes biodegradation of the curaua fiber. V C 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40712.
Advances in pneumococcal antibiotic resistance

Antimicrobial resistance and serotypes in Streptococcus pneumoniae have been evolving with the widespread use of antibiotics and the introduction of pneumococcal conjugate vaccines (PCV). Particularly, among various types of antimicrobial resistance, macrolide resistance has most remarkably increased in many parts of the world, which has been reported to be >70% among clinical isolates from Asian countries. Penicillin resistance has dramatically decreased among nonmeningeal isolates due to the changes in resistance breakpoints, although resistance to other β-lactams such as cefuroxime has increased. Multidrug resistance became a serious concern in the treatment of invasive pneumococcal diseases, especially in Asian countries. After PCV7 vaccination, serotype 19A has emerged as an important cause of invasive pneumococcal diseases which was also associated with increasing prevalence of multidrug resistance in pneumococci. Widespread use of PCV13, which covers additional serotypes 3, 6A and 19A, may contribute to reduce the clonal spread of drug-resistant 19A pneumococci.
Fuzzy paraphrases in learning word representations with a corpus and a lexicon

There is a not carefully addressed issue in the previous work s using lexicons or ontologies to train or improve distributed word representa tions: For polysemous words and utterances changing meaning in different context s, their paraphrases or related entities in a lexicon or an ontology are unreliabl e and sometimes deteriorate the learning of word representations. Thus, we pr opose an approach to address the problem. We consider each paraphrase of a word in a lexicon not fully a paraphrase, but a fuzzy member (fuzzy paraphrase) in the paraphrase set whose membership (i.e., degree of truth) depends on the cont xts. Then we propose an efficient method to use the fuzzy paraphrases to learn word embeddings. We approximately estimate the local membership of paraphra ses, and train word embeddings using a lexicon jointly by replacing the words in the contexts with their paraphrases randomly subjected to the membership of e ach paraphrase. The experimental results show that our method is efficient, over comes the weakness of the previous related works in extracting semantic inform ation and outperforms the previous works of learning word representations using l exicons.
Rough Set Model for Constraint-based Multi-dimensional Association Rule Mining

This paper presents a rough set model for constraint-based multi-dimensional association rule mining. It first overviews the progress in constraint-based multi-dimensional association rule mining. It then applies the constraints on the rough set model. To set up a decision table, it adopts the user voting and the thresholds on condition granules and decision granules. Finally it employs the extended random sets to generate interesting rules. It shows that this rough set model will effectively improve the quality of association rule mining by reducing the attributes greatly in the vertical direction and clustering the records clearly in the horizontal direction. To describe the association among the attributes, it constructs an ontology and presents a new concept of an association table. The construction of a tuple in an association table indicates the relationship among different levels on the ontology towards decision support.
A new analysis of recovery, recrystallisation, and grain growth

AbstractThe traditional classification of annealing processes into the categories of recovery, recrystallisation, and grain growth is no longer adequate, and a new analytical approach to the stability and growth of cellular microstructures such as subgrain and grain structures has recently been developed. The theory is based on consideration of the stability and growth of cellular microstructures in which the energy and mobility of the cell boundaries are variables. Such a model has the advantages of considering all annealing phenomena in a unified manner, enabling the analysis of processes which do not readily fall into any of the three traditional categories. In addition, the effects of important materials variables such as texture and second phase particles may be readily incorporated into the theory. The application of the basic theory to the recovery, recrystallisation, and grain growth of both single phase and particle containing metals is considered and further refinements of the theory which are r.
Model for developing a database for risk analysis

The aim of this paper is to propose a new systemic modelling approach in order to model a complex task of maintenance and analyses its risks. This model combines Emmanuel two different tools belonging to systemic approach: UML (Unified Model Language) and MOSAR (Method Organized for a Systemic Analysis of Risk). The objective of this new model is to identify and to model the mechanism of hazard between sources of hazard and targets in maintenance activity. In addition, this methodology allows to quantify the criticality of risks and to treat them on a hierarchical basis according to several risk factors (human, technical, organizational and environmental). The UML-MOSAR methodology allows creating a database as an information system for learning from accidents and provides a comprehensive view that facilitates the understanding of the organization of a maintenance activity and leads to more effective analysis of its safety.
Increased susceptibility to otitis media in a Splunc1-deficient mouse model

ABSTRACT Otitis media (inflammation of the middle ear) is one of the most common diseases of early childhood. Susceptibility to otitis is influenced by a number of factors, including the actions of innate immune molecules secreted by the epithelia lining the nasopharynx, middle ear and Eustachian tube. The SPLUNC1 (short palate, lung, nasal epithelial clone 1) protein is a highly abundant secretory product of the mammalian nasal, oral and respiratory mucosa that is thought to play a multifunctional role in host defense. In this study we investigated Splunc1 expression in the ear of the mouse, and examined whether this protein contributes to overall host defense in the middle ear and/or Eustachian tube. We found that Splunc1 is highly expressed in both the surface epithelium and in submucosal glands in these regions in wild-type mice. In mice lacking Splunc1, we noted histologically an increased frequency of otitis media, characterized by the accumulation of leukocytes (neutrophils with scattered macrophages), proteinaceous fluid and mucus in the middle ear lumens. Furthermore, many of these mice had extensive remodeling of the middle ear wall, suggesting a chronic course of disease. From these observations, we conclude that loss of Splunc1 predisposes mice to the development of otitis media. The Splunc1−/− mouse model should help investigators to better understand both the biological role of Splunc1 as well as host defense mechanisms in the middle ear. Summary: We document expression of the innate immune factor Splunc1 in the murine middle ear and Eustachian tube, and describe spontaneous development of otitis media in mice lacking functional Splunc1.
Standard Methods for Unnotched Tension Testing of Textile Composites

An investigation was conducted by researchers at the Boeing Defense & Space Group to investigate the effects of specimen sizing on several braided textile materials. Test results from this and other test programs were compared in an effort to determine what effect, if any, specimen size has on elastic property measurements of unnotched tension test. In general, the unnotched tensile strength of 2-D braids was found to be insensitive to specimen width, length, or thickness effects. The results from this study suggest that standard testing methods used for tape materials may be sufficient for tension testing of textile composite materials. Specifically, the straight sided specimen geometry described in ASTM 3034, and used by Boeing, should provide acceptable results. Further experiments performed at Boeing and by other investigators on other textile architectures suggest similar results. Although specimen size studies were not conducted, failing stresses varied on the same order as those obtained with the 2-D materials. This suggests that the accuracy of the results were consistent with those obtained with the 2-D materials.
A video text detection and recognition system

In this paper, we propose a new system for text information extraction from news videos. First of all, a method that integrates text detecting and text tracking is developed to locate text areas in the key-frames (images), together with a scheme to evaluate the performance of this approach. To get better recognition results, we then enhance the quality of the detected text blocks by multi-frame averaging. Finally, we use an adaptive thresholding method to binarize the text blocks and recognize the text using an off-the-shelf OCR module. The detection and recognition rate of the proposed system are 94.7% and 67.5% respectively.