Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing frequent patterns in large multivariate time series

The detection of previously unknown, frequently occurring patterns in time series, often called motifs, has been recognized as an important task. However, it is difficult to discover and visualize these motifs as their numbers increase, especially in large multivariate time series. To find frequent motifs, we use several temporal data mining and event encoding techniques to cluster and convert a multivariate time series to a sequence of events. Then we quantify the efficiency of the discovered motifs by linking them with a performance metric. To visualize frequent patterns in a large time series with potentially hundreds of nested motifs on a single display, we introduce three novel visual analytics methods: (1) motif layout, using colored rectangles for visualizing the occurrences and hierarchical relationships of motifs in a multivariate time series, (2) motif distortion, for enlarging or shrinking motifs as appropriate for easy analysis and (3) motif merging, to combine a number of identical adjacent motif instances without cluttering the display. Analysts can interactively optimize the degree of distortion and merging to get the best possible view. A specific motif (e.g., the most efficient or least efficient motif) can be quickly detected from a large time series for further investigation. We have applied these methods to two real-world data sets: data center cooling and oil well production. The results provide important new insights into the recurring patterns.
Towards a Descriptive Model of Agent Strategy Search

It is argued that, due to the complexity of most economic phenomena, thechancesof deriving correct models from a priori principles are very small. Instead,a more descriptiveapproach to modelling should be pursued. Agent-based modelling ischaracterised as a step in thisdirection. However many agent-based models use off-theshelf algorithms fromcomputer sciencewithout regard to their descriptive accuracy. This paper attempts an agentmodel that describesas accurately as possible the behaviour of subjects reported in Sonnemans(1998). It takes aframework for learning that is compatible with thinking in cognitive sciencewithin thisframework attempts to identify the specific process that matchs the behaviourof the subjects.This suggests further modelling improvements and experiments.
Predicting post-release defects using pre-release field testing results

Field testing is commonly used to detect faults after the in-house (e.g., alpha) testing of an application is completed. In the field testing, the application is instrumented and used under normal conditions. The occurrences of failures are reported. Developers can analyze and fix the reported failures before the application is released to the market. In the current practice, the Mean Time Between Failures (MTBF) and the Average usage Time (AVT) are metrics that are frequently used to gauge the reliability of the application. However, MTBF and AVT cannot capture the whole pattern of failure occurrences in the field testing of an application. In this paper, we propose three metrics that capture three additional patterns of failure occurrences: the average length of usage time before the occurrence of the first failure, the spread of failures to the majority of users, and the daily rates of failures. In our case study, we use data derived from the pre-release field testing of 18 versions of a large enterprise software for mobile applications to predict the number of post-release defects for up to two years in advance. We demonstrate that the three metrics complement the traditional MTBF and AVT metrics. The proposed metrics can predict the number of post-release defects in a shorter time frame than MTBF and AVT.
Whole Genomic Analysis of an Unusual Human G6P[14] Rotavirus Strain Isolated from a Child with Diarrhea in Thailand: Evidence for Bovine-To-Human Interspecies Transmission and Reassortment Events

An unusual rotavirus strain, SKT-27, with the G6P[14] genotypes (RVA/Human-wt/THA/SKT-27/2012/G6P[14]), was identified in a stool specimen from a hospitalized child aged eight months with severe diarrhea. In this study, we sequenced and characterized the complete genome of strain SKT-27. On whole genomic analysis, strain SKT-27 was found to have a unique genotype constellation: G6-P[14]-I2-R2-C2-M2-A3-N2-T6-E2-H3. The non-G/P genotype constellation of this strain (I2-R2-C2-M2-A3-N2-T6-E2-H3) is commonly shared with rotavirus strains from artiodactyls such as cattle. Phylogenetic analysis indicated that nine of the 11 genes of strain SKT-27 (VP7, VP4, VP6, VP2-3, NSP1, NSP3-5) appeared to be of artiodactyl (likely bovine) origin, while the remaining VP1 and NSP2 genes were assumed to be of human origin. Thus, strain SKT-27 was found to have a bovine rotavirus genetic backbone, and thus is likely to be of bovine origin. Furthermore, strain SKT-27 appeared to be derived through interspecies transmission and reassortment events involving bovine and human rotavirus strains. Of note is that the VP7 gene of strain SKT-27 was located in G6 lineage-5 together with those of bovine rotavirus strains, away from the clusters comprising other G6P[14] strains in G6 lineages-2/6, suggesting the occurrence of independent bovine-to-human interspecies transmission events. To our knowledge, this is the first report on full genome-based characterization of human G6P[14] strains that have emerged in Southeast Asia. Our observations will provide important insights into the origin of G6P[14] strains, and into dynamic interactions between human and bovine rotavirus strains.
PARIS: a system for reusing partially interpreted schemas

This paper describes PARIS, an implemented system that facilitates the reuse of partially interpreted schemas. A schema is a program and specification with abstract, or uninterpreted, entities. Different interpretations of those entities will produce different programs. The PARIS System maintains a library of such schemas and provides an interactive mechanism to interpret a schema into a useful program by means of partially automated matching and verification procedures.
I Don't Always Have Positive Attitudes, but When I Do It Is Usually About a Robot: Development of the Robot Perception Scale

The increasing use of robots and their role in society has important implications for research and development in human-robot interactions (HRIs). The purpose of the present study was to develop a new measure to assess attitudes toward robots in HRIs. Measures of attitudes humans have “about” robots are relatively uncommon. Those that exist have potential problems limiting utilization in research evaluating the human element in HRIs. The Robot Perception Scale (RPS) was developed to redress this gap by examining a new set of factors in unique ways. The RPS consists of two subscales in which participants rate their agreement with statements concerning general attitudes toward robots and attitudes toward human-robot similarity and attractiveness. Findings provide preliminary support for a robotic perception scale that can be used to further our understanding of robots engaged in a variety of HRI settings.
Combined Trajectory Planning and Gaze Direction Control for Robotic Exploration

In this paper, a control scheme that combines trajectory planning and gaze direction control for robotic exploration is presented. The objective is to calculate the gaze direction and simultaneously plan the trajectory of the robot over a given time horizon, so that localization and map estimation errors are minimized while the unknown environment is explored. Most existing approaches perform a greedy optimization for the trajectory generation only over the next time step and usually neglect the limited field of view of visual sensors and consequently the need for gaze direction control. In the proposed approach an information-based objective function is used, in order to perform multiple step planning of robot motion, which quantifies a trade-off between localization, map accuracy and exploration. Relative entropy is used as an information metric for the gaze direction control. The result is an intelligent exploring mobile robot, which produces an accurate model of the environment and can cope with very uncertain robot models and sensor measurements
Metformin: a modulator of bevacizumab activity in cancer? A case report

Recurrent type I endometrial cancer (EC) has poor prognosis and demands novel therapeutic approaches. Bevacizumab, a VEGF-A neutralizing monoclonal antibody, has shown clinical activity in this setting. To our knowledge, however, although some diabetic cancer patients treated with bevacizumab may also take metformin, whether metformin modulates response to anti-VEGF therapy has not yet been investigated. Here, we report the case of a patient with advanced EC treated, among other drugs, with bevacizumab in combination with metformin. The patient affected by relapsed EC G3 type 1, presented in march 2010 with liver, lungs and mediastinic metastases. After six cycles of paclitaxel and cisplatin she underwent partial response. Later on, she had disease progression notwithstanding administration of multiple lines of chemotherapy. In march 2013, due to brain metastases with coma, she began steroid therapy with development of secondary diabetes. At this time, administration of Bevacizumab plus Metformin improved her performance status. CT scans performed in this time window showed reduced radiologic density of the lung and mediastinic lesions and of liver disease, suggestive of increased tumor necrosis. Strong 18F-FDG uptake by PET imaging along with high levels of monocarboxylate transporter 4 and lack of liver kinase B1 expression in liver metastasis, highlighted metabolic features previously associated with response to anti-VEGF therapy and phenformin in preclinical models. However, clinical benefit was transitory and was followed by rapid and fatal disease progression. These findings—albeit limited to a single case—suggest that tumors lacking LKB1 expression and/or endowed with an highly glycolytic phenotype might develop large necrotic areas following combined treatment with metformin plus bevacizumab. As metformin is widely used among diabetes patients as well as in ongoing clinical trials in cancer patients, these results deserve further clinical investigation.
Synergy of Particle Swarm Optimization with Evolutionary Algorithms for Intelligent Search and Optimization

The concept of Particle Swarms, although initially introduced for simulating human social behaviors, has become very popular these days as an efficient global optimization technique. On the other hand, a keen observation of the underlying relation between optimization and biological evolution has led to the development of an important paradigm of Computational Intelligence, marked as ‘Evolutionary Algorithms’ (EA). The EA algorithms are ubiquitously used for performing very complex search and optimization. In this article we focus on the possible synergies of these two powerful search techniques in order to enjoy the best of both the worlds i.e. the fast convergence and high diversity. We provide a few computer simulations undertaken for this study to demonstrate the effectiveness of the hybrid algorithms.
Group Target Tracking with the Gaussian Mixture Probability Hypothesis Density Filter

The probability hypothesis density (PHD) filter was originally devised to address non-conventional tracking problems such as group target processing, tracking in high target density, tracking closely spaced targets and detecting targets of interest in a dense multi-target background. The intention was to track overall group behaviour, and then attempt to track individual targets and then attempt to detect and track individual targets only as the quantity and quality of the data permits. Despite this, most practical implementations of the PHD filter have been applied to standard multi-target tracking problems and there have been few implementations of the PHD filter for tackling groups of targets. In this work, we investigate some practical strategies for group tracking with the Gaussian mixture implementation of the PHD filter.
Unsupervised Anomaly Detection Using Light Switches for Smart Nursing Homes

Anomaly detection plays a critical role in various smart living scenarios. However, achieving effective detection while not imposing burdens on users is never an easy task. To solve this problem, an unsupervised anomaly detection algorithm using light switches is proposed. By using an unsupervised approach, care takers in nursing homes do not need to label the collected data. By using information generated by smart switches, senior citizens are not forced to use wearables, change the battery or feel privacy invasion from cameras. Our solution adopts the statistical-based algorithm based on expectation maximization (EM). By adding constrains to reduce the high variances of the mixture model and recursively removing the extremely-low probability data from the model, a more accurate mixture model can be constructed. Our experiments in a real apartment show that the false alarm rate can be reduced by at least 56% compared to the existing cluster-based algorithms when the targeted miss detection rates are low.
A Novel Neuro-Wavelet Based Self-Tuned Wavelet Controller for IPM Motor Drives

This paper presents a hybrid neuro-wavelet scheme for on-line tuning of a wavelet-based multiresolution PID (MRPID) controller in real-time for precise speed control of an interior permanent magnet synchronous motor (IPMSM) drive system under system uncertainties. In the wavelet-based MRPID controller, the discrete wavelet transform (DWT) is used to decompose the error between actual and command speeds into different frequency components at various scales. The MRPID controller parameters are tuned by the wavelet neural network (WNN) to ensure optimum performance of the drive system. The proposed neuro-wavelet based MRPID controller is trained online with adaptive learning rates in the closed-loop vector control of the IPMSM drive system. The adaptive learning rates are derived using discrete Lyapunov stability theorem so that the convergence of the tracking error is guaranteed in the closed-loop system. The performances of the proposed hybrid controller are investigated in both simulation and experiments at different dynamic operating conditions. The complete vector control scheme incorporating the proposed self-tuning MRPID controller is successfully implemented in real-time using the ds1102 digital signal processor board for the laboratory 1-hp IPM motor. The superior performances of the proposed WNN-based self-tuning MRPID controller are also validated over fixed-gain controllers.
Intestinal Dysbiosis Associated with Systemic Lupus Erythematosus

ABSTRACT Systemic lupus erythematosus (SLE) is the prototypical systemic autoimmune disease in humans and is characterized by the presence of hyperactive immune cells and aberrant antibody responses to nuclear and cytoplasmic antigens, including characteristic anti–double-stranded DNA antibodies. We performed a cross-sectional study in order to determine if an SLE-associated gut dysbiosis exists in patients without active disease. A group of 20 SLE patients in remission, for which there was strict inclusion and exclusion criteria, was recruited, and we used an optimized Ion Torrent 16S rRNA gene-based analysis protocol to decipher the fecal microbial profiles of these patients and compare them with those of 20 age- and sex-matched healthy control subjects. We found diversity to be comparable based on Shannon’s index. However, we saw a significantly lower Firmicutes/Bacteroidetes ratio in SLE individuals (median ratio, 1.97) than in healthy subjects (median ratio, 4.86; P < 0.002). A lower Firmicutes/Bacteroidetes ratio in SLE individuals was corroborated by quantitative PCR analysis. Notably, a decrease of some Firmicutes families was also detected. This dysbiosis is reflected, based on in silico functional inference, in an overrepresentation of oxidative phosphorylation and glycan utilization pathways in SLE patient microbiota. IMPORTANCE Growing evidence suggests that the gut microbiota might impact symptoms and progression of some autoimmune diseases. However, how and why this microbial community influences SLE remains to be elucidated. This is the first report describing an SLE-associated intestinal dysbiosis, and it contributes to the understanding of the interplay between the intestinal microbiota and the host in autoimmune disorders. Growing evidence suggests that the gut microbiota might impact symptoms and progression of some autoimmune diseases. However, how and why this microbial community influences SLE remains to be elucidated. This is the first report describing an SLE-associated intestinal dysbiosis, and it contributes to the understanding of the interplay between the intestinal microbiota and the host in autoimmune disorders.
Optimizing sparse matrix computations through compiler-assisted programming

Existing high-performance implementations of sparse matrix codes are intricate and result in large code bases. In fact, a single floating-point operation requires 400 to 600 lines of additional code to "prepare" this operation. This imbalance severely obscures code development, thereby complicating maintenance and portability. In this paper, we propose a drastically different approach in order to continue to effectively handle these codes. We propose to only specify the essence of the computation on the level of individual matrix elements. All additional source code to embed these computations are then generated and optimized automatically by the compiler. This approach is far superior to existing library approaches and allows code to perform scatter/gather operations, matrix reordering, matrix data structure handling, handling of fill-in, etc., to be generated automatically. Experiments show that very efficient data structures can be generated and the resulting codes can be very competitive.
Reduction in northward incursions of the South Asian monsoon since ∼1400 AD inferred from a Mt. Everest ice core

A highly resolved Mt. Everest ice core reveals a decrease in marine and increase in continental air masses related to relatively high summer surface pressure over Mongolia, and reduction in northward incursions of the summer South Asian monsoon since ∼1400 AD. Previously published proxy records from lower sites south of the Himalayas indicate strengthening of the monsoon since this time. These regional differences are consistent with a south–north seesaw in convective activity in the Asian monsoon region, and reflect a southward shift in the mean summer position of the monsoon trough since ∼1400 AD. The change in monsoonal circulation at 1400 AD is synchronous with a reduction in solar irradiance and the onset of the LIA. This demonstrates a hemispheric scale circulation reorganization at this time, and the potential for future large shifts in monsoonal circulation.
MORPHOMETRIC ANALYSIS OF NONADULT CHARACTERS OF COMMON SPECIES OF AMERICAN GORDIIDS (NEMATOMORPHA: GORDIOIDEA)

The nonadult stages, egg strings, eggs, larvae, and cysts of Gordius robustus, Paragordius varius, and Chordodes morgani are described morphometrically. The goal was to document the differences between species and to evaluate the usefulness of morphometrics in species identification. In concert, multivariate analysis of variance (MANOVA) and univariate analysis of variance (ANOVA, a posteriori contrasts) statistical tests demonstrated that each species is morphometrically distinguishable from all others. Additionally, discriminant function analysis indicated that postseptum length, pseudointestine length, and stylet width were the most important variables in the discrimination of species based on larval characters. Finally, differences in oviposition behaviors among these 3 species were found. It is suggested that ovipositioning differences may place larvae into distinct niches and may ultimately lead to the use of different paratenic hosts by different gordiid species.
Towards Providing Cloud Functionalities for Grid Users

Grid computing uses a job submission model that requires the users to perform a set of interactive operations for executing an application on the Grid. Grid users are therefore burdened with the tasks of understanding the basic concept of Grid computing and the details of job management. Cloud computing, on the other hand, applies a utility model that allows the user to access the underlying platform via Web services. This work brings the Cloud concept to the Grid with a result of replacing the job submission model with a service infrastructure. In this case, Grid applications are presented as Web services that can be executed on the Grid automatically without user interactions. All issues related to job management are performed by the system. The service infrastructure significantly simplifies the users' task in accessing the Grid.
Comparisons of nonlinear estimators for wastewater treatment plants

This paper deals with five existing nonlinear estimators (filters), which include Extended Kalman Filter (EKF), Extended H-infinity Filter (EHF), State Dependent Filter (SDF), State Dependent H-Infinity Filter (SDHF) and Unscented Kalman Filter (UKF) that are formulated and implemented to estimate unmeasured states of a typical biological wastewater system. The performance of these five estimators of different complexities, behaviour and advantages are demonstrated and compared via nonlinear simulations. This study shows promising application of UKF for monitoring and control of the process variables, which are not directly measurable.
The ArfGAP2/3 Glo3 and ergosterol collaborate in transport of a subset of cargoes

ABSTRACT Proteins reach the plasma membrane through the secretory pathway in which the trans Golgi network (TGN) acts as a sorting station. Transport from the TGN to the plasma membrane is maintained by a number of different pathways that act either directly or via the endosomal system. Here we show that a subset of cargoes depends on the ArfGAP2/3 Glo3 and ergosterol to maintain their proper localization at the plasma membrane. While interfering with neither ArfGAP2/3 activity nor ergosterol biosynthesis individually significantly altered plasma membrane localization of the tryptophan transporter Tat2, the general amino acid permease Gap1 and the v-SNARE Snc1, in a Δglo3 Δerg3 strain those proteins accumulated in internal endosomal structures. Export from the TGN to the plasma membrane and recycling from early endosomes appeared unaffected as the chitin synthase Chs3 that travels along these routes was localized normally. Our data indicate that a subset of proteins can reach the plasma membrane efficiently but after endocytosis becomes trapped in endosomal structures. Our study supports a role for ArfGAP2/3 in recycling from endosomes and in transport to the vacuole/lysosome.
The ZRTP Protocol - Analysis on the Diffie-Hellman mode

ZRTP is a key agreement protocol by Philip Zimmermann, Alan Johnston and Jon Callas, which relies on a Diffie-Hellman exchange to generate SRTP session parameters, providing confidentiality and protecting against Man-in-the-Middle attacks even without a public key infrastructure or endpoint certificates. This is an analysis of the protocol performed with ProVerif, which tests security properties of ZRTP; in order to perform the analysis, the protocol has been modeled in the applied π-calculus.
EducMap Pour une cartographie dynamique des recherches en éducation

Le projet EducMap vise une meilleure comprehension des communautes scientifiques impliquees dans les recherches en education, et de leurs interrelations, a partir d’une demarche exploratoire de cartographie des productions scientifiques par le recours a des outils bibliometriques appliques a des corpus representatifs de la litterature scientifique en education. Cette demarche sera appuyee par un seminaire epistemologique et methodologique rassemblant des representants significatifs des communautes scientifiques concernees, aux niveaux national et international.