Miracle-dz/UniFAR-FTUs huggingface dataset:
Lack of Canonical E6 and E7 Open Reading Frames in Bird Papillomaviruses: Fringilla coelebs Papillomavirus and Psittacus erithacus timneh Papillomavirus

ABSTRACT Determination and analyses of the complete sequence of Fringilla coelebs papillomavirus and Psittacus erithacus timneh papillomavirus indicate that they represent a distinct and distant lineage of papillomaviruses. The lack of canonical E6-E7 open reading frames suggests that they serve adaptive functions during papillomavirus evolution.
Unsupervised Word Sense Disambiguation Using Collocation and Measures of Graph Connectivity

Word Sense Disambiguation has been selected as research objectives in natural language processing for a long time, and it is a necessary task used to identify word senses in context. This paper explains the unsupervised graph-based WSD approach and suggests a new WSD approach using collocation and measures of graph connectivity. This approach uses collocation to find the accurate word sense in context, and searches words sense by measuring graph connectivity when the word can’t be found with collocation. The performance evaluation on the standard data set indicates that it has enhanced accuracy compared to the many existing graph-based algorithms.
Research on the Active DDoS Filtering Algorithm Based on IP Flow

Distributed Denial-of-Service flooding attacks against public web servers are increasingly common. It is impossible for the victim servers to work on the individual level of on-going traffic flows. The scheme establishes IP Flow which is used to select proper features for DDoS detection. Five features are analyzed by the experiments. The IP flow statistics is mainly used to allocate the weights for traffic routing by routers. A new algorithm is thus proposed to get efficiently maximum throughput by the traffic filtering, and its feasibility and validity have been verified in real network circumstances. The algorithm shows its advantages that it is with high average detection and with low false alarm and miss alarm. Moreover, it can optimize the network traffic simultaneously with defending against DDoS attack, thus eliminating efficiently the global burst of traffic arising from normal traffic so as to improve greatly the efficiency of servers.
Mechanisms of bradykinin-induced cerebral vasodilatation in rats. Evidence that reactive oxygen species activate K+ channels.

BACKGROUND AND PURPOSE Relatively little is know regarding mechanisms by which reactive oxygen species produce dilatation of cerebral arterioles. The goal of this study was to test the hypothesis that vasodilator responses of cerebral arterioles to bradykinin, which produces endogenous generation of reactive oxygen species, involve activation of calcium-dependent potassium channels. METHODS We used a cranial window in anesthetized rats to examine effects of catalase (which degrades hydrogen peroxide) on responses to bradykinin. In addition, we examined effects of tetraethylammonium (TEA) and iberiotoxin, inhibitors of calcium-dependent potassium channels, on responses of cerebral arterioles to hydrogen peroxide, bradykinin, and papaverine. RESULTS In cerebral arterioles (baseline diameter = 40 +/- 1 microns) (mean +/- SE), hydrogen peroxide (10 and 100 mumol/L) produced concentration-dependent dilatation. TEA (1 mmol/L), an inhibitor of calcium-dependent potassium channels, produced marked inhibition of vasodilatation in response to hydrogen peroxide. For example, 100 mumol/L hydrogen peroxide dilated arterioles by 13 +/- 2% in the absence and 4 +/- 1% (P < .05 versus control) in the presence of TEA. Bradykinin (10 nmol/L to 1 mumol/L) also produced concentration-dependent dilatation of cerebral arterioles that was inhibited completely by catalase (100 U/mL). TEA or iberiotoxin markedly inhibited vasodilatation in response to bradykinin. For example, 100 nmol/L bradykinin dilated arterioles by 21 +/- 3% in the absence and 2 +/- 2% (P < .05 vs control) in the presence of iberiotoxin (50 nmol/L). CONCLUSIONS These findings suggest that dilatation of cerebral arterioles in the rat in response to hydrogen peroxide, or hydrogen peroxide produced endogenously in response to bradykinin, is mediated by activation of calcium-dependent potassium channels. Thus, activation of potassium channels may be a major mechanism of dilatation in response to reactive oxygen species in the cerebral microcirculation.
Speaker Identity and Voice Quality: Modeling Human Responses and Automatic Speaker Recognition

Despite recent breakthroughs in automatic speaker recognition (ASpR), system performance still degrades when utterances are short and/or when within-speaker variability is large. This study used short test utterances (2-3sec) to investigate the effect of within-speaker variability on state-of-the-art ASpR system performance. A subset of a newly-developed UCLA database is used, which contains multiple speech tasks per speaker. The short utterances combined with a speaking-style mismatch between read sentences and spontaneous affective speech degraded system performance, for 25 female speakers, by 36%. Because humans are more robust to utterance length or withinspeaker variability, understanding human perception might benefit ASpR systems. Perception experiments were conducted with recorded read sentences from 3 female speakers, and a model is proposed to predict the perceptual dissimilarity between tokens. Results showed that a set of voice quality features including F0, F1, F2, F3, H1*-H2*, H2*-H4*, H4*-H2k*, H2k*-H5k, and CPP provides information that complements MFCCs. By fusing the feature set with MFCCs, human response prediction RMS error was . 12, which represents a 12% relative error reduction compared to using MFCCs alone. In ASpR experiments with short utterances from 50 speakers, the voice quality feature set decreased the error rate by 11% when fused with MFCCs.
Digital Image Correlation Strain Analysis for the Study of Wrinkle Formation on Facial Skin

The strains around the eye during the blink are measured for four human subjects to investigate the relationship between the wrinkle formation with aging and the strains by daily motion. In addition, the moisture content, the flexibility and the elasticity of the skin surface are measured for investigating the condition of the skin surface. For observing the wrinkle formed on the facial skin, the replicas of the skin surfaces are also collected. Results show that the relationship between the wrinkle and the strain distribution at the inner corner of the eye is different from that at the corner of the eye. The results indicate that different methods for the corner of the eye and the inner corner of the eye are required for avoiding the wrinkle formation.
Using Twitter to Understand Public Interest in Climate Change: The Case of Qatar

Climate change has received an extensive attention from public opinion in the last couple of years, after being considered for decades as an exclusive scientific debate. Governments and world-wide organizations such as the United Nations are working more than ever on raising and maintaining public awareness toward this global issue. In the present study, we examine and analyze Climate Change conversations in Qatar's Twittersphere, and sense public awareness towards this global and shared problem in general, and its various related topics in particular. Such topics include but are not limited to politics, economy, disasters, energy and sandstorms. To address this concern, we collect and analyze a large dataset of 109 million tweets posted by 98K distinct users living in Qatar -- one of the largest emitters of CO2 worldwide. We use a taxonomy of climate change topics created as part of the United Nations Pulse project to capture the climate change discourse in more than 36K tweets. We also examine which topics people refer to when they discuss climate change, and perform different analysis to understand the temporal dynamics of public interest toward these topics.
METROPOLITALIA : A CROWDSOURCING PLATFORM FOR LINGUISTIC FIELD RESEARCH

Traditional linguistic field research employs the costand time-consuming and possibly biased approach of gathering data by sending out researchers and filling in questionnaires. We improve linguistic field research using crowdsourcing techniques to remedy these issues and open research to a wider audience. On the online platform MetropolItalia, going public in August 2012, Italian native speakers are united to gather and assess linguistic data themselves. We focus on the Italian language because it is currently undergoing a divergence and in this aspect it differs from many other languages. In this article, Borsa Parole, the first game made public on this platform, is described and a short evaluation of its exploitation in a beta phase is presented. Two important requirements of game-based crowdsourcing – motivating enough users and gathering the data wanted – necessary for such a platform are discussed. The game Borsa Parole is shown to fulfil these requirements.
BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles

Summary: Non-coding RNAs (ncRNAs) play a vital role in many cellular processes such as RNA splicing, translation, gene regulation. However the vast majority of ncRNAs still have no functional annotation. One prominent approach for putative function assignment is clustering of transcripts according to sequence and secondary structure. However sequence information is changed by post-transcriptional modifications, and secondary structure is only a proxy for the true 3D conformation of the RNA polymer. A different type of information that does not suffer from these issues and that can be used for the detection of RNA classes, is the pattern of processing and its traces in small RNA-seq reads data. Here we introduce BlockClust, an efficient approach to detect transcripts with similar processing patterns. We propose a novel way to encode expression profiles in compact discrete structures, which can then be processed using fast graph-kernel techniques. We perform both unsupervised clustering and develop family specific discriminative models; finally we show how the proposed approach is scalable, accurate and robust across different organisms, tissues and cell lines. Availability: The whole BlockClust galaxy workflow including all tool dependencies is available at http://toolshed.g2. bx.psu. edu/view/rnateam/blockclust_workflow. Contact: backofen@informatik.uni-freiburg.de; costa@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online.
Dynamic Restructuring of Recovery Nets

A Self-Adaptive Recovery Net (SARN) is an extended Petri net model for specifying exceptional behavior in workflow systems. SARN caters for high-level recovery policies that are incorporated either with a single task or a set of tasks, called a recovery region. A recovery region delimits the part of the workflow from which the associated recovery policies take place. In this paper, we assume that SARN is initially partitioned into recovery regions by workflow designers who have a priori expectations for how exceptions will be handled. We propose a pattern-based approach to dynamically restructure SARN partition. The objective is to continuously restructure recovery regions within SARN partition to reflect the dynamic changes in handling exceptions. The restructuring of SARN partition is based on the observation of predefined recovery patterns.
Finite elemental analysis of outer and inner surfaces of the proximal half of an intact femur

Finite element (FE) simulation has become increasingly important to analyze the behavior of the femoral bone when it is subjected to external loads. The aim of the present study was to validate FE simulation with experimental work using surface strain at the outer surface of the femur, and to subsequently, evaluate von Mises strain for its inner surface. A standardized femur from the bone repository in the Biomechanics European Laboratory (BEL) in Italy was used for the analysis as a base for finite element modeling. The material model used for the analysis was assumed to be isotropic and linearly elastic, and the external loads applied comprised of a head load and an abductor load. The values of stress and strain in the anterior, posterior, medial, and lateral positions of the femur have been presented in this report. The results from the present study show that strain distribution is not uniform across the section of the femur, suggesting the occurrence of circumferential bending. Thus, better understanding of von Mises strain on the inner surface of the femur is important for total hip replacements (THRs).
Analysis of human cytomegalovirus secondary envelopment by advanced electron microscopy

Electron microscopy (EM) allows visualization of viruses in fixed cells with high resolution. High‐pressure freezing for sample fixation in combination with freeze substitution and embedding in resin improves significantly the preservation of cellular structures and specifically of membranes. This advancement allows better visualization of human cytomegalovirus (HCMV) morphogenesis occurring at membranes. To obtain comprehensive information on viral phenotypes from ultrastructural images it is important to also quantify morphological phenotypes. This again can be much refined by three‐dimensional visualization after serial sectioning. For elucidation of dynamic processes three‐dimensional tomography is extremely helpful. We analysed interaction of HCMV particles with host cell membranes during final envelopment. Both wild‐type virus and a viral mutant with impaired envelopment were analysed in fibroblasts, but also using in vivo relevant human endothelial cells and macrophages. The quantification of the EM data showed similar ultrastructural phenotypes regarding the envelopment efficiency in the different cell types indicating similar mechanisms in late stages of virus morphogenesis. Furthermore, thorough analysis of the viral assembly complex (AC) – a virus‐induced cytosolic structure – by using three‐dimensional visualization techniques combined with a quantitative analysis revealed that the events of final envelopment are equally distributed within the AC irrespective of different local membrane composition.
Anticipatory deaccenting in language comprehension

We evaluated the hypothesis that listeners can generate expectations about upcoming input using anticipatory deaccenting, in which the absence of a nuclear pitch accent on an utterance-new noun is licensed by the subsequent repetition of that noun (e.g. Drag the SQUARE with the house to the TRIangle with the house). The phonemic restoration paradigm was modified to obscure word-initial segmental information uniquely identifying the final word in a spoken instruction, resulting in a stimulus compatible with two lexical alternatives (e.g. mouse/house). In Experiment 1, we measured participants' final interpretations and response times. In Experiment 2, we used the same materials in a crowd-sourced gating study. Sentence interpretations at gated intervals, final interpretations and response times provided converging evidence that the anticipatory deaccenting pattern contributed to listeners' referential expectations. The results illustrate the availability and importance of sentence-level accent patterns in spoken language comprehension.
Three-Dimensional Head Tracking and Facial Expression Recovery Using an Anthropometric Muscle-Based Active Appearance Model

This paper describes a novel 3-D model-based tracking algorithm allowing the real-time recovery of 3-D position, orientation, and facial expressions of a moving head. The method uses a 3-D anthropometric muscle-based active appearance model (3-D AMB AAM), a feature-based matching algorithm, and an extended Kalman filter (EKF) pose and expression estimator. Our model is an extension of the classical 2-D AAM and uses a generic 3-D wireframe model of the face based on two sets of controls: the anatomically motivated muscle actuators to model facial expressions and the statistically based anthropometrical controls to model different facial types.
Trust Evaluation Model for Composite Service Based on Subjective Logic

There is little research on the trust evaluation for composite service in the pervasive computing environment. On the basis of SOA (service-oriented architecture), this paper recommends a model SCTRUST, which introduces subjective logic into the trust evaluation for services. In SCTRUST, a composite service evaluation algorithm (CSEA) is offered to solve the trust evaluation over composite service and is verified by simulated experiments in the end. SCTRUST can give trust computation with the dynamic services composition, providing assurance to protect the consumers' interest.
Area-efficient floorplans and interconnects for homogeneous multi-core architectures

Homogeneous multi-core architectures come in a variety of floorplans. A large portion of the chip area is occupied by the second level cache memories and the interconnect. Usually, the floorplan is dictated by the interconnect type and the second level cache memory size and by whether large resources on the chip are shared or private. We consider floorplans for a 16-core architecture consisting of identical cores and estimate their areas based on two different processor cores. Then, we focus on an area-efficient and performance-scaling four-partition crossbar-interconnected architecture with third level cache memory and conduct performance modelling and evaluation of the multi-core architecture's memory system. With a database workload and a first level cache miss rate under 20%, the Average Memory Access Time (AMAT) is estimated to be under 20 processor cycles. With higher memory contention resulting into longer bridge queue wait times, the various cache miss rates rate make a more pronounced effect on the Chip Multiprocessors AMAT, necessitating design measures like proper cache sizing. When the size of shared resources becomes too large, recent work in sharing and partitioning large resources in CMP architectures becomes crucial.
MOTION ESTIMATION BASED ON A TEMPORAL MODEL OF FLUID FLOWS

In algorithmic fluid flow estimation, regularization of neighboring flow vectors has become an important approach employing prior knowledge on resulting flow fields. Up to now, the main focus has been spatial regularization by means of either analytic terms or parametric models. In this paper we propose a new method for estimating flow fields using parametric models of temporal trajectories, which are acquired by unsupervised learning techniques. The new method can be implemented using highly parallel local optimization techniques. It is compared to a well-known combined local-global method, which is one of the most accurate flow estimation techniques in the field of computer vision and is closely related to some recent work in fluid mechanics. The described method lies between PTV and PIV and is therefore highly suitable for methods with fewer tracers than usually visualized by PIV techniques but can deal with more tracers as in PTV while still yielding highly accurate results. Experiments show that our method yields superior results in sequences containing large displacements and difficult occlusions. In the case of small displacements (one pixel and less) almost perfect results can be obtained on ground truth test sequences. Both, our method and the combined local-global approach are equally robust against Gaussian noise.
Sparse appearance model-based algorithm for automatic segmentation and identification of articulated hand bones

Automatic and precise segmentation of hand bones is important for many medical imaging applications. Although several previous studies address bone segmentation, automatically segmenting articulated hand bones remains a challenging task. The highly articulated nature of hand bones limits the effectiveness of atlas-based segmentation methods. The use of low-level information derived from the image-of-interest alone is insufficient for detecting bones and distinguishing boundaries of different bones that are in close proximity to each other. In this study, we propose a method that combines an articulated statistical shape model and a local exemplar-based appearance model for automatically segmenting hand bones in CT. Our approach is to perform a hierarchical articulated shape deformation that is driven by a set of local exemplar-based appearance models. Specifically, for each point in the shape model, the local appearance model is described by a set of profiles of low-level image features along the normal of the shape. During segmentation, each point in the shape model is deformed to a new point whose image features are closest to the appearance model. The shape model is also constrained by an articulation model described by a set of pre-determined landmarks on the finger joints. In this way, the deformation is robust to sporadic false bony edges and is able to fit fingers with large articulations. We validated our method on 23 CT scans and we have a segmentation success rate of ~89.70 %. This result indicates that our method is viable for automatic segmentation of articulated hand bones in conventional CT.
Web path recommendations based on page ranking and Markov models

Markov models have been widely used for modelling users' navigational behaviour in the Web graph, using the transitional probabilities between web pages, as recorded in the web logs. The recorded users' navigation is used to extract popular web paths and predict current users' next steps. Such purely usage-based probabilistic models, however, present certain shortcomings. Since the prediction of users' navigational behaviour is based solely on the usage data, structural properties of the Web graph are ignored. Thus important - in terms of pagerank authority score - paths may be underrated. In this paper we present a hybrid probabilistic predictive model extending the properties of Markov models by incorporating link analysis methods. More specifically, we propose the use of a PageRank-style algorithm for assigning prior probabilities to the web pages based on their importance in the web site's graph. We prove, through experimentation, that this approach results in more objective and representative predictions than the ones produced from the pure usage-based approaches.
Spatial and Temporal Variation in the Effects of Climatic Variables on Dugong Calf Production

Knowledge of the relationships between environmental forcing and demographic parameters is important for predicting responses from climatic changes and to manage populations effectively. We explore the relationships between the proportion of sea cows (Dugong dugon) classified as calves and four climatic drivers (rainfall anomaly, Southern Oscillation El Niño Index [SOI], NINO 3.4 sea surface temperature index, and number of tropical cyclones) at a range of spatially distinct locations in Queensland, Australia, a region with relatively high dugong density. Dugong and calf data were obtained from standardized aerial surveys conducted along the study region. A range of lagged versions of each of the focal climatic drivers (1 to 4 years) were included in a global model containing the proportion of calves in each population crossed with each of the lagged versions of the climatic drivers to explore relationships. The relative influence of each predictor was estimated via Gibbs variable selection. The relationships between the proportion of dependent calves and the climatic drivers varied spatially and temporally, with climatic drivers influencing calf counts at sub-regional scales. Thus we recommend that the assessment of and management response to indirect climatic threats on dugongs should also occur at sub-regional scales.