Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering common motifs in cursor movement data for improving web search

Web search behavior and interaction data, such as mouse cursor movements, can provide valuable information on how searchers examine and engage with the web search results. This interaction data is far richer than traditional search click data, and can be used to improve search ranking, evaluation, and presentation. Unfortunately, the diversity and complexity inherent in this interaction data make it more difficult to capture salient behavior characteristics through traditional feature engineering. To address this problem, we introduce a novel approach of automatically discovering frequent subsequences, or motifs, in mouse cursor movement data. In order to scale our approach to realistic datasets, we introduce novel optimizations for motif discovery, specifically designed for mining cursor movement data. As a practical application, we show that by encoding the motifs discovered from thousands of real web search sessions as features, enables significant improvements on result relevance estimation and re-ranking tasks, compared to a state-of-the-art baseline that relies on extensive feature engineering. These results, complemented with visualization and qualitative analysis, demonstrate that our approach is able to automatically capture key characteristics of mouse cursor movement behavior, providing a valuable new tool for search behavior analysis.
Overview of Self-Reported Measures of Fatigue

ABSTRACT Objective: The purpose of this article is to provide a quick summary of existing measures with reliability and validity data to help researchers select a subjective measure appropriate for their application. Background: Currently, fatigue is measured through self-rating (asking individuals if they are experiencing fatigue, tiredness, or sleepiness), and calculation of fatigue from self-reported sleep and work patterns. Method: Self-rated measures of fatigue are summarized. Results: Extant fatigue scales include the Brief Fatigue Inventory, Chalder Fatigue Scale, Checklist Individual Strength, Chronic Fatigue Scale, Crew Status Survey (also known as the Samn–Perelli Fatigue Scale), Daytime Sleepiness Scale, Epworth Sleepiness Scale, Fatigue, Anergy, Consciousness, Energized and Sleepiness, Fatigue Assessment Inventory, Fatigue Assessment Scale, Fatigue Impact Scale, Fatigue Severity Scale, Fatigue Symptom Inventory, Functional Assessment of Cancer Therapy, Karolinska Sleepiness Scale, Maslach Burnout Inventory Emotional Exhaustion Subscale, Modified Brief Fatigue Inventory, Multidimensional Fatigue Inventory, Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form Fatigue Questionnaire, Piper Fatigue Scale, Sleep Wake Activity Inventory, Samm–Perelli Seven-Point Fatigue Scale (SPS), Stanford Sleepiness Scale, Visual Analog Fatigue Scale, and World Health Organization Quality Of Life Assessment Energy and Fatigue subscale. In addition to the self-rating of fatigue scales, several measures are calculated and predicted from self-reported amount and quality of sleep as well as work schedule. These biomathematical models include the Fatigue Avoidance Scheduling Tool (FAST), Fatigue Audit InterDyne, Fatigue Index Tool (FIT), and the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) Model. Note that the FAST uses the SAFTE model and the combination is sometimes referred to as SAFTE/FAST (Hursh, 2003). These models are also summarized in this article.
Moderated online social therapy: Designing and evaluating technology for mental health

Although the use and prevalence of Web-based mental health applications have grown over the past decade, many of these services suffer high rates of attrition. This is problematic, as face-to-face support for mental health is limited. To determine appropriate design guidelines for increasing engagement, we conducted a study of First-Episode Psychosis (FEP) patients and reviewed theories on the use of existing online services. We produced a set of design goals, developed an online application that combined social networking and online therapy within a clinician-moderated site, and conducted a 6-week trial with a group of young FEP patients. The design goals, based on existing theory including Supportive Accountability and Positive Psychology, are operationlised through a model we call Moderated Online Social Therapy (MOST). The trial results indicate that our implementation achieved the design goals and that the MOST model can inform the development of more effective and engaging online therapies.
A trust evaluation model of electricity customers based on cloud model

In the competitive electricity market, large power customers who consume a large quantity of electricity through the behaviors of malicious arrears of electricity fee and evasion of electricity will seriously affect the normal operation of electricity supply enterprises. Therefore, a trust evaluation model based on the specific characteristics index system of evaluation object' operating environment is constructed, which is based on cloud model, shows experts' opinions with trust vectors. The paper describes the generating method of trust evaluation cloud, and proposes synthetic formula of trust evaluation cloud and decision-making algorithm, which are applied to the trust evaluation of large power customers, provides decision-making basis for the power supply companies choosing trustworthy power customers. Experimental results show that the model is feasible and effective.
Simple Closed-Form Approximation to Ricean Sum Distributions

This letter focuses on the approximation of Ricean sum distributions of L independent random variables. Although no closed-form expression is available for these exact distributions, a simple but accurate closed-form approximation is proposed. The expression is based on the Central Limit Theorem (CLT) for which an appropriate correction term is added. The result is a rather tight fit with the exact distribution for a wide range of input values and Ricean K-factors.
Structure-function study of maize ribosome-inactivating protein: implications for the internal inactivation region and the sole glutamate in the active site

Maize ribosome-inactivating protein is classified as a class III or an atypical RNA N-glycosidase. It is synthesized as an inactive precursor with a 25-amino acid internal inactivation region, which is removed in the active form. As the first structural example of this class of proteins, crystals of the precursor and the active form were diffracted to 2.4 and 2.5 Å, respectively. The two proteins are similar, with main chain root mean square deviation (RMSD) of 0.519. In the precursor, the inactivation region is found on the protein surface and consists of a flexible loop followed by a long α-helix. This region diminished both the interaction with ribosome and cytotoxicity, but not cellular uptake. Like bacterial ribosome-inactivating proteins, maize ribosome-inactivating protein does not have a back-up glutamate in the active site, which helps the protein to retain some activity if the catalytic glutamate is mutated. The structure reveals that the active site is too small to accommodate two glutamate residues. Our structure suggests that maize ribosome-inactivating protein may represent an intermediate product in the evolution of ribosome-inactivating proteins.
The RWTH Aachen University English-Romanian Machine Translation System for WMT 2016

This paper describes the statistical machine translation system developed at RWTH Aachen University for the English! Romanian translation task of the ACL 2016 First Conference on Machine Translation (WMT 2016). We combined three different state-ofthe-art systems in a system combination: A phrase-based system, a hierarchical phrase-based system and an attentionbased neural machine translation system. The phrase-based and the hierarchical phrase-based systems make use of a language model trained on all available data, a language model trained on the bilingual data and a word class language model. In addition, we utilized a recurrent neural network language model and a bidirectional recurrent neural network translation model for reranking the output of both systems. The attention-based neural machine translation system was trained using all bilingual data together with the backtranslated data from the News Crawl 2015
Missense mutations in dystrophin that trigger muscular dystrophy decrease protein stability and lead to cross-β aggregates

A deficiency of functional dystrophin protein in muscle cells causes muscular dystrophy (MD). More than 50% of missense mutations that trigger the disease occur in the N-terminal actin binding domain (N-ABD or ABD1). We examined the effect of four disease-causing mutations—L54R, A168D, A171P, and Y231N—on the structural and biophysical properties of isolated N-ABD. Our results indicate that N-ABD is a monomeric, well-folded α-helical protein in solution, as is evident from its α-helical circular dichroism spectrum, blue shift of the native state tryptophan fluorescence, well-dispersed amide crosspeaks in 2D NMR 15N-1H HSQC fingerprint region, and rotational correlation time calculated from NMR longitudinal (T1) and transverse (T2) relaxation experiments. Compared to WT, three mutants—L54R, A168D, and A171P—show a decreased α-helicity and do not show a cooperative sigmoidal melt with temperature, indicating that these mutations exist in a wide range of conformations or in a “molten globule” state. In contrast, Y231N has an α-helical content similar to WT and shows a cooperative sigmoidal temperature melt but with a decreased stability. All four mutants experience serious misfolding and aggregation. FT-IR, circular dichroism, increase in thioflavin T fluorescence, and the congo red spectral shift and birefringence show that these aggregates contain intermolecular cross-β structure similar to that found in amyloid diseases. These results indicate that disease-causing mutants affect N-ABD structure by decreasing its thermodynamic stability and increasing its misfolding, thereby decreasing the net functional dystrophin concentration.
Simulations of a Scintillator Compton Gamma Imager for Safety and Security

We are designing an all-scintillator Compton gamma imager for use in security investigations and remediation actions involving radioactive threat material. To satisfy requirements for a rugged and portable instrument, we have chosen solid scintillator for the active volumes of both the scatter and absorber detectors. Using the BEAMnrc/EGSnrc Monte Carlo simulation package, we have constructed models using four different materials for the scatter detector: LaBr3 , NaI, CaF2 , and PVT. We have compared the detector performances using angular resolution, efficiency, and image resolution. We find that while PVT provides worse performance than that of the detectors based entirely on inorganic scintillators, all of the materials investigated for the scatter detector have the potential to provide performance adequate for our purposes.
Stochastic Specification and Verification

Modern distributed systems include a class of applications in which non-functional requirements are important. In particular, these applications include multimedia facilities where real time constraints are crucial to their correct functioning. In order to specify such systems it is necessary to describe that events occur at times given by probability distributions. Stochastic process algebras have emerged as a useful technique by which such systems can be specified and verified. However, stochastic descriptions are very general, in particular they allow the use of general probability distribution functions, and therefore their verification can be complex. In this paper we define a translation from stochastic process algebras to timed automata. By doing so we aim to use the simpler verification methods for timed automata (e.g. reachability properties) for the more complex stochastic descriptions.
Information Security Solution Decision-Making Based on Entropy Weight and Gray Situation Decision

To determine the choice of information security solutions, the method based on entropy weight was given to compute the weights of indexes of the solutions. And then, the weights were used to evaluate the solutions by multi-attributes decision and ideal indexes method. The gray situation decision-making was introduced for solutions decision, and entropy weights were also used with gray solution decision to choose the solutions. The characteristics of diverse methods mentioned were analyzed.
Image Denoising Based on Adaptive Filtering and Multi-frame Averaging Filtering

To deal with some problem of existing single- frame denoising methods, a adaptive spatial filtering method for denoising of multi-fame images is presented. Firstly each frame is processed by adaptive filters to suppressive noise and to preserve the edge simultaneity. Then each frame of image is filtered by averaging the same pixels of multi-frame to denoise fartherly and alleviate the cartoon-like impacts. Three filters including adaptive filtering on signal-frame, simple mean filtering of multi-frame, and adaptive filtering combined with averaging filtering, are tested by two experiments. The results show that the latter improved the performance of denoising compared with the former two methods.
Finite-SNR Outage Analysis for Non-coherent MIMO Channels

In this paper, a point-to-point non-coherent multiple-inp ut multiple-output channel withMT transmit antennas andMR receive antennas is considered. For a communication system using a training-based channel estimation scheme, we obtain an analytical express ion for an upper bound on the outage probability. Using this expression, we show that the optimu m number of active transmit antennas topt to minimize the outage bound depends on the signal to noise ra tio (SNR), multiplexing gain, coherence time and the number of receive antennas. Our results give ins ights on the behavior of topt with respect to these parameters. Specifically, we show that, in the high SNR regime, as the multiplexing gain increases, the value oftopt decreases when MT > MR. However, this behavior does not happen in the moderate SNR regimeor whenMT ≤ MR. We also compute the achievable finite-SNR diversity multip lexing tradeoff of these channels. Index Terms Training signals, Channel estimation, Outage probability , Diversity-Multiplexing Tradeoff Nandita Lavanis is with the Dept. of ECE, SSN College of Engineering, Chenn ai. Devendra Jalihal, Arun Pachai Kannu and Srikrishna Bhashyam are with the Dept. of Electrical Engineering, IIT Ma dras, Chennai, India. This work was done while the first author was a PhD student at IIT Madras. e-mail: nandita.lavanis@ gmail.com, {dj,arunpachai,skrishna }@ee.iitm. ac.in
Inulin-type fructans and bone health: state of the art and perspectives in the management of osteoporosis

If the primary role of diet is to provide sufficient nutrients to meet the metabolic requirements of an individual, there is an emerging rationale to support the hypothesis that, by modulating specific target functions in the body, it can help achieve optimal health. Regarding osteoporosis prevention, since Ca is most likely to be inadequate in terms of dietary intake, every strategy targeting an improvement in Ca absorption is very interesting. Actually, this process may be susceptible to manipulation by fermentable substrates. In this light, inulin-type fructans are very interesting, even if we need to gather more data targeting bone metabolism before health professionals can actively advocate their consumption to prevent senile osteoporosis. Besides targeting the prevention of postmenopausal osteoporosis, inulin-type fructans still remain a source for putative innovative dietary health intervention. Indeed, given in combination with isoflavones, they may have a potential for maintaining or improving the bone mass of human subjects, by modulating the bioavailability of phyto-oestrogens.
3D Object Reconstruction from Swissranger Sensor Data using a Spring-mass Model

We register close-range depth images of objects using a Swissranger sensor and apply a spring-mass model for 3D object reconstruction. The Swissranger sensor delivers depth images in real time which have, compared with other types of sensors, such as laser scanners, a lower resolution and are afflicted with larger uncertainties. To reduce noise and remove outliers in the data, we treat the point cloud as a system of interacting masses connected via elastic forces. We investigate two models, one with and one without a surface-topology preserving interaction strength. The algorithm is applied to synthetic and real Swissranger sensor data, demonstrating the feasibility of the approach. This method represents a preliminary step before fitting higher-level surface descriptors to the data, which will be required to define object-action complexes (OACS) for robot applications.
A combination of quantitative and qualitative maps in an evaluative bibliometric context

Maps of science provide visualizations of scientific knowledge domains by quantitatively grouping elements from scientific papers. In evaluative bibliometric studies these quantitative maps have proven a useful tool Representation schemes such as mental maps or cognitive maps provide a tool to structure qualitative reasoning about, for instance, strategies, learning and politics. A combination of bibliometric maps with these qualitative structures may provide new ways for attacking science-policy related problems using bibliometric data. A design is presented on how to create, visualize and use the correspondence between elements in both types of maps.
Eosinophil Granule Proteins ECP and EPX as Markers for a Potential Early-Stage Inflammatory Lesion in Female Genital Schistosomiasis (FGS)

Background Genital granulomas induced by Schistosoma haematobium eggs can manifest as different lesion types visible by colposcopy; rubbery papules (RP), homogenous sandy patches (HSP) and grainy sandy patches (GSP). Pronounced tissue eosinophilia is a candidate marker for active S. haematobium pathology, as viable schistosome egg granulomas often are eosinophil rich. Here it was investigated whether eosinophil granule proteins ECP (eosinophil cationic protein) and EPX (eosinophil protein-X) in urine and genital lavage can be used as markers for active FGS lesions. Methods Uro-genital samples from 118 Malagasy women were analysed for ECP and EPX by standard sandwich avidin/biotin amplified ELISA. Principal findings The women with RP lesions had significantly higher levels of ECP and EPX in both lavage and urine. Furthermore, women with RP lesions were significantly younger than those with GSP. This could indicate that RP lesions might be more recently established and thus represent an earlier inflammatory lesion stage. Conclusion ECP in genital lavage might be a future tool aiding the identification of FGS pathology at a stage where reversibility remains a possibility following praziquantel treatment.
Chapter Four Simple models of ensemble-averaged precipitation and surface wind , given the sea surface temperature

In this chapter, we will address the following problem. Consider the sea surface temperature (SST) field as given, and find the quasi-steady component of the tropical surface wind and precipitation field over the tropical oceans. We do not explicitly address precipitation over land. By " quasi-steady " we mean, in principle, ensemble averaged over all possible realizations associated with that SST, taking deep convection to have a stochas-tic component. In practice monthly climatologies, or perhaps individual monthly means, will have to be good enough. We are interested in the total fields, not just deviations from the time or zonal means. We further specify that the problem must be solved without running a general circulation model (GCM). The model must be considerably simpler than that. More specifically, all the models we will discuss here have severely truncated vertical structure, to just one or two vertical modes or layers. Their physical parameter-izations are also all greatly reduced in complexity from what would appear in a GCM. Our goals are to review the various sorts of models of this type that have been constructed, and to assess both the degree to which these models are successful, and to which they are similar to or different from one another. Models constructed on different principles seem to produce qualitatively similar results; we will try to explain this and to ascertain where differences in the results do exist which might be used to test the theoretical ideas underlying the models. The figures of merit here will be the precipitation and surface wind. The surface wind is important particularly because of its influence on the ocean. Much effort on models of the sort discussed here has been expended in the context of the prediction of the El Niño-Southern Oscillation (ENSO) phenomenon. In such models the precipitation , being proportional to the vertical integral of the convective heating, is of 2 CHAPTER 4 interest primarily through the influence of that heating on the winds. In the present discussion we are also interested in precipitation for its own sake. The questions of to what degree the heating associated with precipitation drives the surface winds, and to what degree convergence of the surface winds drives precipitating convec-tion, will be closely considered. The discussion will focus in particular on what controls the strength and position of intertropical convergence zones (ITCZs). The limitation to the surface wind means that we do not …
Using directional statistics to learn cast shadows from a multi-spectral light sources physical model

In this paper is proposed a novel statistical learning approach, to identify cast shadows, and model their generation. We exploit the theoretically well-founded directional statistics field, in order to formulate the generation of cast shadows as a Mixture of Von Mises-Fisher distributions (MovMF) on the unit sphere. This formulation is based on a bi-illuminant physical model of cast shadows, where no prior assumptions of the spectral power distribution (SPD) of the direct light sources and ambient illumination in the scene are made. Founded on a rigorous directional statistics approach, this parametric framework is capable of modelling the shaded surface behavior in complex illumination scenes and meet real time requirements. This better model discriminating cast shadows provides a more compact representation, and achieve better accuracy, with less data and much less computation time, compared with non-parametric models previously proposed. Theoretic analysis and experimental evaluations demonstrate the effectiveness of the proposed framework