Miracle-dz/UniFAR-FTUs huggingface dataset:
Software for serial data analysis measured by SEC-SAXS/UV-Vis spectroscopy

Data processing software is commonly utilized for serial measurements in small-angle X-ray scattering with size exclusion chromatography (SEC-SAXS) to effectively process hundreds of scattering data files. However, software to automatically extrapolate SEC-SAXS data to an infinite dilution has yet to be developed. SEC-SAXS/UV-Vis measurements at the Photon Factory not only provide structural information but also give the concentration for each measurement at the sample cell position simultaneously. Since SEC-SAXS data contain various concentration data, the concentration dependence due to the interparticle interference effect can be accurately estimated. Herein we report a new program with a user-friendly interface for multiple automatic data processes to calculate the scattering intensity extrapolated to the infinite dilution. This software provides baseline corrections and a mapping optimization between the serial scattering intensity and the absorbance to obtain the most accurate scattering profile.Data processing software is commonly utilized for serial measurements in small-angle X-ray scattering with size exclusion chromatography (SEC-SAXS) to effectively process hundreds of scattering data files. However, software to automatically extrapolate SEC-SAXS data to an infinite dilution has yet to be developed. SEC-SAXS/UV-Vis measurements at the Photon Factory not only provide structural information but also give the concentration for each measurement at the sample cell position simultaneously. Since SEC-SAXS data contain various concentration data, the concentration dependence due to the interparticle interference effect can be accurately estimated. Herein we report a new program with a user-friendly interface for multiple automatic data processes to calculate the scattering intensity extrapolated to the infinite dilution. This software provides baseline corrections and a mapping optimization between the serial scattering intensity and the absorbance to obtain the most accurate scattering profile.
Tropisms of AAV for Subretinal Delivery to the Neonatal Mouse Retina and Its Application for In Vivo Rescue of Developmental Photoreceptor Disorders

Background Adeno-associated virus (AAV) is well established as a vehicle for in vivo gene transfer into the mammalian retina. This virus is promising not only for gene therapy of retinal diseases, but also for in vivo functional analysis of retinal genes. Previous reports have shown that AAV can infect various cell types in the developing mouse retina. However, AAV tropism in the developing retina has not yet been examined in detail. Methodology/Principal Findings We subretinally delivered seven AAV serotypes (AAV2/1, 2/2, 2/5, 2/8, 2/9, 2/10, and 2/11) of AAV-CAG-mCherry into P0 mouse retinas, and quantitatively evaluated the tropisms of each serotype by its infecting degree in retinal cells. After subretinal injection of AAV into postnatal day 0 (P0) mouse retinas, various retinal cell types were efficiently transduced with different AAVs. Photoreceptor cells were efficiently transduced with AAV2/5. Retinal cells, except for bipolar and Müller glial cells, were efficiently transduced with AAV2/9. Horizontal and/or ganglion cells were efficiently transduced with AAV2/1, AAV2/2, AAV2/8, AAV2/9 and AAV2/10. To confirm the usefulness of AAV-mediated gene transfer into the P0 mouse retina, we performed AAV-mediated rescue of the Cone-rod homeobox gene knockout (Crx KO) mouse, which exhibits an outer segment formation defect, flat electroretinogram (ERG) responses, and photoreceptor degeneration. We injected an AAV expressing Crx under the control of the Crx 2kb promoter into the neonatal Crx KO retina. We showed that AAV mediated-Crx expression significantly decreased the abnormalities of the Crx KO retina. Conclusion/Significance In the current study, we report suitable AAV tropisms for delivery into the developing mouse retina. Using AAV2/5 in photoreceptor cells, we demonstrated the possibility of gene replacement for the developmental disorder and subsequent degeneration of retinal photoreceptors caused by the absence of Crx.
Ontology-based information extraction for market monitoring and technology watch

The h-TechSight Knowledge Management Portal (KMP) enables support for knowledgeintensive industries in monitoring information resources on the Web, as an important factor in business competitiveness. The portal contains tools for identification of concepts and terms from an ontology relevant to the user’s interests, and enables the user to monitor them over time. It also contains tools for ontology management and modification, based on the results of targeted knowledge extraction from the web. The platform provides a means for businesses to keep track of trends and topics of interest in their field, and alert them to changes. In this paper we focus on the tools for targeted search and ontology management, driven by an ontology-based information extraction system, which has been evaluated over a test set of 38 documents and achieves 97% Precision and 92% Recall.
Compressive Estimation of Doubly Selective Channels in Multicarrier Systems: Leakage Effects and Sparsity-Enhancing Processing

We consider the application of compressed sensing (CS) to the estimation of doubly selective channels within pulse-shaping multicarrier systems (which include orthogonal frequency-division multiplexing (OFDM) systems as a special case). By exploiting sparsity in the delay-Doppler domain, CS-based channel estimation allows for an increase in spectral efficiency through a reduction of the number of pilot symbols. For combating leakage effects that limit the delay-Doppler sparsity, we propose a sparsity-enhancing basis expansion and a method for optimizing the basis with or without prior statistical information about the channel. We also present an alternative CS-based channel estimator for (potentially) strongly time-frequency dispersive channels, which is capable of estimating the ¿off-diagonal¿ channel coefficients characterizing intersymbol and intercarrier interference (ISI/ICI). For this estimator, we propose a basis construction combining Fourier (exponential) and prolate spheroidal sequences. Simulation results assess the performance gains achieved by the proposed sparsity-enhancing processing techniques and by explicit estimation of ISI/ICI channel coefficients.
LOCAl: a personalized cache mechanism for location-based social networks

Recommending nearby Points of Interest (POI) has received growing interest in mobile location-based networks today, where users share content embedded with location information. In this work, we propose a novel caching framework to support personalised proactive caching for mobile location-based social networks. We propose "LOCAI", which uses a probabilistic approach in order to predict the POIs that users will access and retrieve the appropriate data objects that will fulfill user preferences. Our detailed experimental evaluation, using data from the Foursquare location-based social network, illustrates that LOCAI minimizes the user latency to retrieve the data objects they are interested in, is efficient and practical.
Mutual Authentication and Key Agreement for GSM

We propose an efficient identity based mutual authentication scheme for GSM. In the proposed scheme, mobile station (MS) and visitor location register (VLR) authenticate each other and establish a session key to communicate securely for every communication. Our scheme requires less bandwidth and storage. The scheme does not involve certificate management and is resilient to replay and man-in-the middle attacks. We also compare the performance of our scheme with that of the existing schemes.
Making HCI theory work: an analysis of the use of activity theory in HCI research

ABSTRACT This paper reports a study of the use of activity theory in human–computer interaction (HCI) research. We analyse activity theory in HCI since its first appearance about 25 years ago. Through an analysis and meta-synthesis of 109 selected HCI activity theory papers, we created a taxonomy of 5 different ways of using activity theory: (1) analysing unique features, principles, and problematic aspects of the theory; (2) identifying domain-specific requirements for new theoretical tools; (3) developing new conceptual accounts of issues in the field of HCI; (4) guiding and supporting empirical analyses of HCI phenomena; and (5) providing new design illustrations, claims, and guidelines. We conclude that HCI researchers are not only users of imported theory, but also theory-makers who adapt and develop theory for different purposes.
Towards a Simple and Accurate Statistical Approach to Learning Translation Relationships among Words

We report on a project to derive word translation relationships automatically from parallel corpora. Our effort is distinguished by the use of simpler, faster models than those used in previous high-accuracy approaches. Our methods achieve accuracy on single-word translations that seems comparable to any work previously reported, up to nearly 60% coverage of word types, and they perform particularly well on a class of multi-word compounds of special interest to our translation effort.
On the magnetic acceleration and collimation of astrophysical outflows

ABSTRA C T The axisymmetric 3D MHD outflow of cold plasma from a magnetized and rotating astrophysical object is numerically simulated with the purpose of investigating the magnetocentrifugal acceleration and eventual collimation of the outflow. Gravity and thermal pressure are neglected while a split monopole is used to describe the initial magnetic field configuration. It is found that the stationary final state depends critically on a single parameter a expressing the ratio of the corotating speed at the Alfven distance to the initial flow speed along the initial monopole-like magnetic field lines. Several angular velocity laws have been used for relativistic and non-relativistic outflows. The acceleration of the flow is most effective at the equatorial plane and the terminal flow speed depends linearly on a. Significant flow collimation is found in non-relativistic efficient magnetic rotators corresponding to relatively large values of a * 1 while very weak collimation occurs in inefficient magnetic rotators with smaller values of a < 1. Part of the flow around the rotation and magnetic axis is cylindrically collimated while the remaining part obtains radial asymptotics. The transverse radius of the jet is inversely proportional to a while the density in the jet grows linearly with a . F ora * 5 the magnitude of the flow in the jet remains below the fast MHD wave speed everywhere. In relativistic outflows, no collima- tion is found in the supersonic region for parameters typical for radio pulsars. All the above results verify the main conclusions of general theoretical studies on the magnetic accel- eration and collimation of outflows from magnetic rotators and extend previous numerical simulations to large stellar distances.
Pharmacokinetic modeling and Monte Carlo simulation of ondansetron following oral administration in dogs.

Ondansetron is a potent antiemetic drug that has been commonly used to treat acute and chemotherapy-induced nausea and vomiting (CINV) in dogs. The aim of this study was to perform a pharmacokinetic analysis of ondansetron in dogs following oral administration of a single dose. A single 8-mg oral dose of ondansetron (Zofran(®) ) was administered to beagles (n = 18), and the plasma concentrations of ondansetron were measured by liquid chromatography-tandem mass spectrometry. The data were analyzed by modeling approaches using ADAPT5, and model discrimination was determined by the likelihood-ratio test. The peak plasma concentration (Cmax ) was 11.5 ± 10.0 ng/mL at 1.1 ± 0.8 h. The area under the plasma concentration vs. time curve from time zero to the last measurable concentration was 15.9 ± 14.7 ng·h/mL, and the half-life calculated from the terminal phase was 1.3 ± 0.7 h. The interindividual variability of the pharmacokinetic parameters was high (coefficient of variation > 44.1%), and the one-compartment model described the pharmacokinetics of ondansetron well. The estimated plasma concentration range of the usual empirical dose from the Monte Carlo simulation was 0.1-13.2 ng/mL. These findings will facilitate determination of the optimal dose regimen for dogs with CINV.
A Combined Dual-Tree Complex Wavelet (DT-CWT) and Bivariate Shrinkage for Ultrasound Medical Images Despeckling

paper, an efficient DT-CWT based method for medical ultrasound images despeckling is presented. The ultrasound images are often deteriorated by speckle noise, this noise is a random granular texture that obscures anatomy in ultrasound images and degrades the detectability of low-contrast lesions. Speckle noise occurrence is often undesirable, since it affects the tasks of human interpretation and diagnosis.Different from many other schemes with wavelet transform are used on one side in which the studies have dealt more with the standard DWT case. However, the Discrete Wavelet Transform (DWT) has some disadvantages that undermine its application in image processing.In this study we investigated a performances complex wavelet transform (DT-CWT) combined with Bivariate Shrinkage.The proposed method was tested on a noisy ultrasound medical image, and the restored images show a great effectiveness of DT-CWT method compared to the classical DWT.
SentimentalITsts at SemEval-2016 Task 4: building a Twitter sentiment analyzer in your backyard

The paper presents the system developed by the SentimentalITsts team for the participation in Semeval-2016 task 4, in the subtasks A, B and C. The developed system uses off the shelf solutions for the development of a quick sentiment analyzer for tweets. However, the lack of any syntactic or semantic information resulted in performances lower than those of other teams.
Real Time Path Predicting for Autonomous Underwater Vehicle Using Support Vector Regression Machines

Autonomous underwater vehicles (AUV) are unmanned underwater vessels to investigate sea environments, oceanography and deep-sea resources autonomously. Navigation of underwater vehicles is a very demanding task, especially in confined environment. In order to avoid different risk, the path information must be communicated between sensors and monitor immediately, but the data transfer rate are very low in the sub-sea acoustic communication channel, it is impossible to receive these information immediately, so a model based on support vector regression machines for real time path predicting is proposed in this paper. This model can update according the new data form the sensors. Experiments show this method can have a good performance to predict the path of AUV.
Vehicle Color Classification Under Different Lighting Conditions Through Color Correction

This paper presents a novel vehicle color classification technique for classifying vehicles into seven categories under different lighting conditions via color correction. First, to reduce lighting effects, a mapping function is built to minimize the color distortions between frames. In addition to color distortions, the effect of specular highlights can also make the window of a vehicle appear white and degrade the accuracy of vehicle classification. To reduce this effect, a window-removal task is performed to make vehicle pixels with the same color more concentrated on the analyzed vehicle. Thus, a vehicle can be more accurately classified into its corresponding category even when it is shone by strong sunlight. One major problem in vehicle color classification is that there are many shade colors; for example, white versus silver and black versus navy. Traditional methods lack the ability to classify vehicles with shade colors because a wrong classifier is designed by putting vehicles with the same label together even though their chromatic attributes are different. To treat this problem, a novel tree-based classifier is designed for classifying vehicles into chromatic/nonchromatic classes with their nonchromatic strengths and then into detailed color classes with their color features. The separation can significantly improve the accuracy of vehicle color classification even that vehicles are with various shade colors and captured under different lighting conditions.
Estimation of constrained parameters in a linear model with multiplicative and additive noise

Estimation of a Hilbert-space valued parameter in a linear model with compact linear transformation is considered with both multiplicative and additive noise present. The unknown parameter is assumed a priori to lie in a compact rectangular parallelepiped oriented in a certain way in the Hilbert space. Linear estimators are devised that minimize reasonable upper bounds on mean-squared error depending on conditions on the noise. Under prescribed conditions the estimators are minimax in the class of linear estimators. With the prior constraint on the unknown parameter removed, the estimation problem is ill-posed. Restricting the unknown provides a regularization of the basically ill-posed estimation. It turns out the estimators developed here belong to a well-known class of regularized estimators. With the interpretation that the constraint is soft, the procedure is applicable to many signal-processing problems. >
ON STOCHASTIC DYNAMIC PREDICTION: I. The Energetics of Uncertainty and the Question of Closure

I n this, the first part of a two-part study, we examine the rationale of the stochastic dynamic approach to numerical weather prediction. Advantages of the stochastic dynamic method are discussed along with problems associated with the method. This method deals with the initial uncertainty by considering a n infinite ensemble of initial states in phase space, relative frequencies within the ensemble being proportional to probability densities. The evolution of this ensemble in time, given by the stochastic dynamic equation set, is based upon the original deterministic hydrodynamic equation set. One may consider the latter set as a subset of t h e former. Insight into the nature of these equations is obtained by deriving the energy transformations associated with them. A simple baro-clinic model is used to isolate the energy concepts and relations. The energetics yield qualitative and quantitative information on the nature of the growth of uncertainty. It is found that the baroclinic instability mechanism is responsible for most of the error growth as would be expected. Previous predictability studies have considered that the simulation of the forces governing the atmosphere has been perfect. The effects of imperfect forcing can be viewed with the stochastic dynamic equations by adding another dimension to phase space for each parameter considered to be uncertain. The effect of the inclusion of this imperfect forcing is shown by the new energetic relations that result, and by numerical calculation of the changes in the growth of uncertainty. The stochastic dynamic equations are faced with the same mathematical problem of " closure " found in analytical treatments of homogeneous isotroFic turbulence; that is, an approximation concerning higher order moments must be made t o close the system. A number of closure schemes are studied and it is found that the third moments, which are individually small, should nevertheless be retained. It is shown in the equations and verified by numerical calculations that the third moments do not affect energy conservation but affect energy conversion between uncertain components, with the eventual result of altering the forecast of the mean. An eddy-damped third moment scheme is found to give extremely accurate results when compared to Monte Carlo calculations.
Characteristics of ASTER GDEM version 2

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was released to the public in July 2009. The GDEM version 2, currently under development, is reproduced using an updated algorithm and contains new ASTER data observed after September 2008. Validation study of the trial and beta version of GDEM version 2 was carried out to investigate its characteristics such as geolocation error, elevation error and horizontal resolution. The results of the study confirmed that elevation offset and horizontal resolution will be greatly improved in version 2 and the enhanced horizontal resolution will serve to reduce the standard deviation of elevation and geolocation error.
Determinants of Satisfaction with an Automated Alcohol Evaluation Program

High rates of untreated mental illness cause serious health problems in the United States and worldwide. The use of computer-administered therapy has the potential to increase access to mental health care for certain patient populations. An online version of an alcohol check-up was developed that guided subjects through a series of standardized questionnaires, and provided them with feedback designed to enhance their appreciation of the negative aspects of their alcohol use. Ratings of the helpfulness of the questionnaires were evaluated in order to determine the characteristics of individuals who would potentially benefit from an automated substance abuse intervention, and to learn which aspects of an automated program would be most useful. Over a period of 25 months, 1,455 individuals participated in the study, 83% of whom had an Alcohol Use Disorders Identification Test (AUDIT) score indicative of problem drinking. Subjects with alcohol problems found the on-line program more useful than other subjects. The questionnaire which compared subjects' alcohol use to national norms, provided the most helpful and also the most unexpected information. Alcohol abusers with high levels of ambivalence about their drinking and other measures of motivation for change found the program more helpful than those with lower motivation. Automated therapy made available to the general public via the Internet can be accessed by large numbers of individuals. The interaction can be useful to patients with significant levels of substance abuse.
PARO robot affects diverse interaction modalities in group sensory therapy for older adults with dementia

We evaluated the seal-like robot PARO in the context of multi-sensory behavioral therapy in a local nursing home. Participants were 10 elderly nursing home residents with varying levels of dementia. We report three principle findings from our observations of interactions between the residents, PARO, and a therapist during seven weekly therapy sessions. Firstly, we show PARO provides indirect benefits for users by increasing their activity in particular modalities of social interaction, including visual, verbal, and physical interaction, which vary between primary and non-primary interactors. Secondly, PARO's positive effects on older adults' activity levels show steady growth over the duration of our study, suggesting they are not due to short-term “novelty effects. ” Finally, we show a variety of ways in which individual participants interacted with PARO and relate this to the “interpretive flexibility” of its design.