Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of user ’ s mental model on natural gaze behavior during human-computer interaction

Natural gaze behavior during human-computer interaction provides valuable information about user’s cognitive processes and intentions. Including it as an additional input modality therefore provides great potential to improve humancomputer interaction. However, the relations between natural gaze behavior and underlying cognitive processes still is unexplored to a large extend. In this paper we identify and characterize major factors influencing natural gaze behavior during human-computer interaction with a focus on the role of user’s mental model about the interactive system in that context. In a user study we investigate how natural gaze behavior can be influenced by interaction design and point out implications for usage of gaze as additional modality in gaze-based interfaces. Author
An Efficient Geometric Solution to the Minimum Spanning Circle Problem

We consider the century-old problem of finding the minimum spanning circle MSC of N points in the plane. We propose a computational scheme that incorporates the ideas that motivate three of the best-known primal feasible algorithms. The technique converges in finite time and is extremely fast. In all our experiments that involved digitized and random data, without even a rare exception, the technique converged in exactly two iterations. We conjecture that the algorithm, which is purely geometric, has a linear time complexity.
Design of an analog frontend for a 5.8 GHz RFID transponder

This contribution presents a modulator and demodulator design of a 5.8 GHz Radio Frequency Identification (RFID) transponder. Binary Amplitude Shift Keying (ASK) is used as modulation scheme for the bidirectional data communication. Thus, the transponders analog frontend consists of an envelope detector and a comparator for the upstream (reader to transponder) and a backscatter modulator based on a single transistor for the downstream (transponder to reader).
Therapeutics , Targets , and Chemical Biology Dysregulation of Cholesterol Homeostasis in Human Prostate Cancer through Loss of ABCA 1

Recent epidemiologic data show that low serum cholesterol level as well as statin use is associated with a decreased risk of developing aggressive or advanced prostate cancer, suggesting a role for cholesterol in aggressive prostate cancer development. Intracellular cholesterol promotes prostate cancer progression as a substrate for de novo androgen synthesis and through regulation of AKT signaling. By conducting next-generation sequencing–based DNA methylome analysis, we have discovered marked hypermethylation at the promoter of the major cellular cholesterol efflux transporter, ABCA1, in LNCaP prostate cancer cells. ABCA1 promoter hypermethylation renders the promoter unresponsive to transactivation and leads to elevated cholesterol levels in LNCaP.ABCA1 promoter hypermethylation is enriched in intermediateto high-grade prostate cancers and not detectable in benign prostate. Remarkably, ABCA1 downregulation is evident in all prostate cancers examined, and expression levels are inversely correlated with Gleason grade. Our results suggest that cancer-specific ABCA1 hypermethylation and loss of protein expression direct high intracellular cholesterol levels and hence contribute to an environment conducive to tumor progression. Cancer Res; 73(3); 1211–8. 2012 AACR.
A Naive Bayesian Wind Power Interval Prediction Approach Based on Rough Set Attribute Reduction and Weight Optimization

Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power prediction interval model, combining rough set (RS) theory and particle swarm optimization (PSO), is proposed to further improve wind power prediction performance. First, in the designed prediction interval model, the input variables are identified based on attribute significance using rough set theory. Next, the Naive Bayesian Classifier (NBC) is established to obtain the prediction power class. Finally, the upper and lower output weights of NBC are optimized segmentally by PSO, and are used to calculate the upper and lower bounds of the optimal prediction intervals. The superiority of the proposed approach is demonstrated by comparison with a Naive Bayesian model with fixed output weight, and a rough set-Naive Bayesian model with fixed output weight. It is shown that the proposed rough set-Naive Bayesian-particle swarm optimization method has higher coverage of the probabilistic prediction intervals and a narrower average bandwidth under different confidence levels.
Comparative studies of genes encoding thermostable L-2-halo acid dehalogenase from Pseudomonas sp. strain YL, other dehalogenases, and two related hypothetical proteins from Escherichia coli

We have determined the nucleotide sequence of the gene encoding thermostable L-2-halo acid dehalogenase (L-DEX) from the 2-chloroacrylate-utilizable bacterium Pseudomonas sp. strain YL. The open reading frame consists of 696 nucleotides corresponding to 232 amino acid residues. The protein molecular weight was estimated to be 26,179, which was in good agreement with the subunit molecular weight of the enzyme. The gene was efficiently expressed in the recombinant Escherichia coli cells: the amount of L-DEX corresponds to about 49% of the total soluble proteins. The predicted amino acid sequence showed a high level of similarity to those of L-DEXs from other bacterial strains and haloacetate dehalogenase H-2 from Moraxella sp. strain B (38 to 57% identity) but a very low level of similarity to those of haloacetate dehalogenase H-1 from Moraxella sp. strain B (10%) and haloalkane dehalogenase from Xanthobacter autotrophicus GJ10 (12%). By searching the protein amino acid sequence database, we found two E. coli hypothetical proteins similar to the Pseudomonas sp. strain YL L-DEX (21 to 22%).
User's profile ontology-based semantic model for personalized hotel room recommendation in the web of things: student research abstract

The hotel industry is not exempt from technology disruption and will only keep its competitiveness through strategy [3]including adjusting to the new customers demands, reacting to competitors' innovations and taking advantage of the new technological developments. Personalization can enable an organization to customize its offerings at the individual level. This paper seeks to design and evaluate a novel Web of Things personalization model that effectively utilizes information about a customer's preferences to create a personalized service space.
Mania switch induced by amantadine in bipolar disorder: report of three cases.

467 • Revista Brasileira de Psiquiatria 2010 • vol 32 • no 4 • dez2010 Referências 1. Meloy JR. The nature and dynamics of sexual homicide: an integrative review. Aggression violent behavior. 2000;5(1):1-22. 2. Telles LEB. Perícias de responsabilidade penal realizadas no Instituto Psiquiátrico Forense. Multijuris: Primeiro Grau em Ação. 2007;2(3):44-9. 3. Baltieri DA, Andrade AG. Comparing serial and nonserial sexual offenders: alcohol and street drug consumption, impulsiveness and history of sexual abuse. Rev Bras Psiquiatr. 2008;30(1):25-31.
Detection of Avian Nephritis Virus in Australian Chicken Flocks

Abstract Avian nephritis virus (ANV) is thought to infect poultry flocks worldwide, but no confirmed case has been reported in Australia. The first such case is described in this study. Cases of young chickens with clinical signs of dehydration and diarrhea were submitted to our laboratory and histopathology detected interstitial nephritis. Vaccine strains of infectious bronchitis virus were detected in some of these cases but were not considered to be the causative agent. A total of seven fresh submissions from broiler chicken flocks were collected at 8–11 days of age. Degenerate PCR primers were designed based on published ANV polymerase gene sequences and used to analyze historic cases as well as the fresh submissions. Six of the seven fresh submissions, and one historic case, were positive for ANV with nucleotide sequencing confirming these results. These results establish ANV as an infectious pathogen circulating in Australian poultry.
AwaitViz: a visualizer of JavaScript's async/await execution order

To solve JavaScript's callback hell problem, several language mechanisms like Promise and async/await have already been introduced to JavaScript. Using async/await, which is the most promising one, callback hell code can be rewritten to another simple and shallow nested code with (almost) the same behavior. Unfortunately, however, it is still difficult to precisely understand the execution order of the rewritten async/await code, because the semantics of async/await is difficult. This paper first clarifies that this problem is caused by the difficulty of the async/await semantics. Then, we propose and implement a novel async/await visualizer called AwaitViz, to support for programmers to understand the execution order of async/await. Our contribution is twofold. First, we show the feasibility of implementing the visualizer AwaitViz based on source-code instrumentation, which provides precise information on the JavaScript's asynchronous behavior. Second, we show the difficulties and limitations of implementing AwaitViz.
Recognition of the light buoy for scan the code mission in 2016 Maritime RobotX Challenge

This paper describes about the team SNU MACRO'S strategy for scan the code mission in Maritime RobotX Challenge. Before describing the specific algorithm for scan the code mission, our vehicle system which was developed for completing each mission for the competition is outlined briefly. To recognize the LED color of the buoy, image processing algorithm is divided into three step, including preprocessing, extraction and recognition. In preprocessing step, color space conversion is conducted. And then, it extracts the candidate region that's the location of light buoy in whole image using LiDAR information. Finally, recognize the current LED's color using the mean value of hue component. The field experiments and competition's result validate the performance of the proposed approach.
Point-of-interest Recommendation in a City

The recommendation for points of interest has become an important way to help people discover interesting places, especially when users want to visit a city. The purpose of this paper is to provide a recommendation system to help residents of a city or tourists learn about the events/outings available in this city. An evaluation of this system, in terms of precision, is also presented.
Differences in resting state regional cerebral blood flow assessed with 99mTc-HMPAO SPECT and brain atlas matching between depressed patients with and without tinnitus

An increased occurrence of major depressive disorder has been reported in tinnitus patients, and of tinnitus in depressive patients. Involvement of several Brodmann areas (BAs) has been reported in tinnitus perception. The aim of this study was to assess the regional cerebral blood flow (rCBF) changes in depressed patients with and without tinnitus. The rCBF distribution at rest was compared among 45 patients with a lifetime prevalence of major depressive disorder, of whom 27 had severe tinnitus, and 26 normal healthy subjects. 99mTc-hexamethylenepropylene amine oxime (99mTc-HMPAO) single photon emission computed tomography (SPECT), using a three-headed gamma camera, was performed and the uptake in 34 functional sub-volumes of the brain bilaterally was assessed by a computerized brain atlas. Decreased rCBF in right frontal lobe BA 45 (P<0.05), the left parietal lobe BA 39 (P<0.00) and the left visual association cortex BA 18 (P<0.05) was found in tinnitus patients compared with non-tinnitus patients. The proportion of tinnitus patients with pronounced rCBF alterations in one or more of the temporal lobe BAs 41+21+22 was increased compared to gender matched controls (P<0.00) and patients without tinnitus (P<0.05). Positive correlations were found between trait anxiety scales from the Karolinska Scales of Personality and rCBF in tinnitus patients only in three limbic BAs (P<0.01), and inverse correlations in non-tinnitus patients only in five BAs subserving auditory perception and processing (P<0.05). rCBF differences between healthy controls and depressed patients with and without tinnitus were found in this study. The rCBF alterations were distributed in the cortex and were particularly specific in the auditory cortex. These findings suggest that taking audiological symptoms into account may yield more consistent results between rCBF studies of depression.
A Note on ‘Improved Fréchet Bounds and Model-Free Pricing of Multi-Asset Options’ by Tankov (2011)

Tankov (2011) improved the Fréchet bounds for a bivariate copula when its values on a compact subset of [0, 1]2 are given. He showed that the best possible bounds are quasi-copulas and gave a sufficient condition for these bounds to be copulas. In this note we give weaker sufficient conditions to ensure that the bounds are copulas. We also show how this can be useful in portfolio selection. It turns out that finding a copula as a lower bound plays a key role in determining optimal investment strategies explicitly for investors with some type of state-dependent constraints.
Community evolution prediction in dynamic social networks using community features' change rates

In this paper, we investigate the prediction of community future occurring events in dynamic social networks, based on change rates of features that describe a community throughout its evolution life-cycle rather than absolute values of features. Besides, we explore the most predictive features for each event. Our experiments on DBLP and Facebook datasets, using community structural features and its influential members' features, confirm that the prediction of the next event that may occur to an evolving community using change rates of features can be achieved with a very high accuracy. We further observe that the most significant features vary according to each event prediction.
MapReduce algorithms for the K group nearest-neighbor query

Given two datasets of points (called Query and Training), the Group (K) Nearest Neighbor (GNN) query retrieves (K) points of the Training dataset with the smallest sum of distances to every point of the Query one. This spatial query has been studied during the recent years and several performance improving techniques and pruning heuristics have been proposed. But this is the first time a parallel and distributed algorithm, using the MapReduce programming framework, is ever used. In this work, we present a multi phased algorithm, consisting of alternating local and parallel phases, which can be used to effectively process the GNN query when the Query dataset fits in memory, but the Training one belongs to the Big Data category. We make use of some of the pruning heuristics and effective calculation techniques of the literature, as well as different indexing methods and finally perform some comparative benchmarks with several datasets.
Effects of Hepatitis C and HIV on Cognition in Women: Data From the Women's Interagency HIV Study

Objective:To compare neuropsychological scores in women infected with HIV, women infected with both HIV and hepatitis C, and uninfected subjects. Background:Some, but not all, studies have demonstrated that dual infection with Hepatitis C virus (HCV) and HIV has worse effects on cognition than infection with HIV alone. Design/Methods:The Women's Interagency HIV Study is an ongoing prospective study of the natural history of HIV in women where participants are reevaluated every 6 months. In a cross-sectional analysis, we evaluated the effects of active HIV and HCV infections on scores on symbol-digit modalities test, the Stroop interference test, and trails A and B after controlling for age, ethnicity, education, depression, liver disease, and current or past substance abuse. Results:Data were available for 1338 women—17.8 % had detectable hepatitis C virus and 67% were HIV seropositive. In fully adjusted general linear models, HCV viremia was not associated with scores on any of the cognitive tests. Conclusions:In this large sample of women, active HCV infection was not associated with scores on a small battery of neuropsychological tests.
New Method for Spectral Data Classification: Two-Way Moving Window Principal Component Analysis

Two-way moving window principal component analysis (TMWPCA), which considers all possible variable regions by using variable and sample moving windows, is proposed as a new spectral data classification method. In TMWPCA, the similarity between model function and the index obtained by variable and sample moving windows is defined as “fitness”. For each variable region selected by a variable moving window, the fitness is obtained through the use of a model function. By maximizing the fitness, an optimal variable region can be searched. A remarkable advantage of TMWPCA is that it offers an optimal variable region for the classification. To demonstrate the potential of TMWPCA, it has been applied to the classification of visible–near-infrared (Vis-NIR) spectra of mastitic and healthy udder quarters of cows measured in a nondestructive manner. The misclassification rate of TMWPCA has been compared with those of other chemometric methods, such as principal component analysis (PCA), soft independent modeling of class analogies (SIMCA), and principal discriminant variate (PDV). TMWPCA has yielded the lowest misclassification rate. The result indicates that TMWPCA is a powerful tool for the classification of spectral data.
retreatment measures of brain structure and reward-processing rain function in cannabis dependence : An exploratory study of elationships with abstinence during behavioral treatment 1

Background: Cannabis is widely abused, and efficacies of therapeutics for cannabis dependence remain suboptimal. Magnetic resonance imaging (MRI) may aid in the identification of biological markers for successful treatment outcomes (i.e., abstinence). Methods: Twenty men with cannabis dependence and twenty non-substance-using healthy comparison (HC) men underwent MRI scanning. Cannabis-dependent individuals then participated in a 12-week randomized clinical trial of behavioral treatments (contingency management (CM), cognitive behavioral therapy (CBT) or both). Pretreatment functional and structural data were compared between the cannabis-dependent and HC participants. In addition, individuals with cannabis dependence were subdivided based on the successful achievement of 21 days of consecutive abstinence during treatment to assess whether abstinent versus non-abstinent cannabis-dependent participants displayed different pretreatment functional and structural characteristics when compared to HC participants. Results: In comparison to HC participants, cannabis-dependent participants demonstrated greater ventral striatal activation during the receipt of losing outcomes and smaller putamenal volumes. Cannabisdependent participants who did not subsequently achieve 21 days of consecutive abstinence had increased activity within the striatum during the receipt of losing outcomes, relative to HC participants. Cannabis-dependent participants who did not achieve 21 days of abstinence had decreased bilateral putamen volumes prior to treatment, relative to HC participants. Conclusions: Individual differences in pretreatment striatal function and structure may relate to individual differences in treatment responses for cannabis dependence. While mechanisms underlying these associations require further exploration, the striatum might mediate treatment responses via its role in associative reward-learning (e.g., through skills training in CBT or reinforcement of abstinence in CM). © 2014 Elsevier Ireland Ltd. All rights reserved.
Voltage control in distribution networks using fast model predictive control

Voltage control is a growing issue in distribution networks operation, due to the increase in load and also distributed generation. In this work model predictive control (MPC) is proposed as a better solution as compared to conventional ones to deal with this problem. A fast MPC algorithm is used to allow online optimization of voltage profile. the algorithm is tested on a 20 kV distribution network.
USE OF MEDICATIONS FOR INSOMNIA IN THE HOSPITALIZED GERIATRIC POPULATION

ACKNOWLEDGMENTS Conflict of Interest: The editor in chief has reviewed the personal and financial checklist provided by the authors and has determined that none of the authors have any conflicts related to this letter. Dr. Teramoto was supported by a research grant from Mitsui Life Social Welfare Foundation Japan fund and by research grant from Mitsukoshi Health and Welfare Foundation in Japan. Author Contributions: Shinji Teramoto: study concept and design. Yoshinosuke Fukuchi, Hidetada Sasaki, Koichi Sato, Kiyoihsa Sekizawa, Takeshi Matsuse: acquisition of subjects and/or data, analysis. Hidetada Sasaki and Kiyoihsa Sekizawa: interpretation of data. Shinji Teramoto: preparation of manuscript. Sponsor’s Role: Pfizer Japan Inc. supported the data collection and analysis. The sponsor had no role in the design, methods, recruitment, or preparation of this letter. REFERENCES
Stroke extraction from grayscale images of financial documents based on figures of importance

This paper describes a new method for stroke extraction from grayscale images based on an effective local adaptive kernel technique that assigns a mark for each pixel in the image signifying its relative importance with respect to neighboring pixels. The assigned marks are based on accumulating evidence of the relative importance of each pixel based on multiple comparisons with neighboring pixels under different windows. A global threshold is then applied to the marks produced in the first step to reach a conclusion as to whether a pixel ought to be preserved as part of a stroke or be dropped as part of the background. This technique effectively combines local and global thresholding techniques and shows promising performance especially on images with non-uniform backgrounds or embedded light strokes. The advantage of this scheme is also demonstrated in terms of superior overall amount recognition performance for financial document processing systems utilizing it.
Paired box 7 (Pax7) gene: molecular characterisation, polymorphism and its association with growth performance in goose (Anser cygnoides)

ABSTRACT 1. Paired box (Pax7) gene is a member of the paired box family and plays a critical role in animal growth and muscle development. However, the molecular characterisation of the goose Pax7 gene is unknown. 2. The open-reading frame of goose Pax7 is composed of 1509 bp, which encodes a protein of 503 amino acids and shares high homology with Pax7 of other birds. 3. Ten single-nucleotide polymorphisms were identified in the genomic DNA sequence, 8 located in the intron region and two located in the exon region. 4. Association analysis showed the C122T locus was significantly associated with the body weight of Zhedong-White geese in week 4, 6, 8, 10 and 12. 5. It was concluded that the goose Pax7 gene may be an important candidate gene for goose growth traits and marker-assisted selection.