Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Consumer Preferences toward M-Commerce Applications Based on an Empirical Study

In this paper, new concept of value proposition for m-commerce is set up based on the study on previous value propositions for m-commerce, and clustering a great number of m-commerce applications by 4 sectors. These 4-sector applications are evaluated by 17 detail propositions. Then these propositions are reorganized structurally by factor analysis, of which result can be used point for drawing perceptual map. This paper identifies the degree of importance in respective propositions through experimental analysis. These experimental analyses are able to hold up objectivity of research methods, and suggest multi-points of view. This result can be used for setting up m-commerce strategy. The implications of this paper are providing diagnostic information to design a new applications or devices. And concretizing value propositions for m-commerce make a operators clear in their decisionmaking
Location of Microaneurysms on Diabetic Retinopathy Images Based on Extraction of Connection Components

In order to quickly and accurately detect microaneurysms of diabetic retinopathy images, a specific method is proposed in this paper, which eliminates useless information based on overall threshold, computes the set of overall connection domain, and precisely orientates microaneurysms by local threshold segmentation and local connection domain identification. Experimental results testify the good accuracy of this method.
Understanding Patients’ Adherence-Related Beliefs about Medicines Prescribed for Long-Term Conditions: A Meta-Analytic Review of the Necessity-Concerns Framework

Background Patients’ beliefs about treatment influence treatment engagement and adherence. The Necessity-Concerns Framework postulates that adherence is influenced by implicit judgements of personal need for the treatment (necessity beliefs) and concerns about the potential adverse consequences of taking it. Objective To assess the utility of the NCF in explaining nonadherence to prescribed medicines. Data sources We searched EMBASE, Medline, PsycInfo, CDSR/DARE/CCT and CINAHL from January 1999 to April 2013 and handsearched reference sections from relevant articles. Study eligibility criteria Studies using the Beliefs about Medicines Questionnaire (BMQ) to examine perceptions of personal necessity for medication and concerns about potential adverse effects, in relation to a measure of adherence to medication. Participants Patients with long-term conditions. Study appraisal and synthesis methods Systematic review and meta-analysis of methodological quality was assessed by two independent reviewers. We pooled odds ratios for adherence using random effects models. Results We identified 3777 studies, of which 94 (N = 25,072) fulfilled the inclusion criteria. Across studies, higher adherence was associated with stronger perceptions of necessity of treatment, OR = 1.742, 95% CI [1.569, 1.934], p<0.0001, and fewer Concerns about treatment, OR = 0.504, 95% CI: [0.450, 0.564], p<0.0001. These relationships remained significant when data were stratified by study size, the country in which the research was conducted and the type of adherence measure used. Limitations Few prospective longitudinal studies using objective adherence measures were identified. Conclusions The Necessity-Concerns Framework is a useful conceptual model for understanding patients’ perspectives on prescribed medicines. Taking account of patients’ necessity beliefs and concerns could enhance the quality of prescribing by helping clinicians to engage patients in treatment decisions and support optimal adherence to appropriate prescriptions.
Quality of DICOM header information for image categorization

The widely used DICOM 3.0 imaging protocol specifies optional tags to store specific information on modality and body region within the header: Body Part Examined and Anatomic Structure. We investigate whether this information can be used for the automated categorization of medical images, as this is an important first step for medical image retrieval. Our survey examines the headers generated by four digital image modalities (2 CTs, 2 MRIs) in clinical routine at the Aachen University Hospital within a period of four months. The manufacturing dates of the modalities range from 1995 to 1999, with software revisions from 1999 and 2000. Only one modality sets the DICOM tag Body Part Examined. 90 out of 580 images (15.5%) contained false tag entries causing a wrong categorization. This result was verified during a second evaluation period of one month one year later (562 images, 15.3% error rate). The main reason is the dependency of the tag on the examination protocol of the modality, which controls all relevant parameters of the imaging process. In routine, the clinical personnel often applies an examination protocol outside its normal context to improve the imaging quality. This is, however, done without manually adjusting the categorization specific tag values. The values specified by DICOM for the tag Body Part Examined are insufficient to encode the anatomic region precisely. Thus, an automated categorization relying on DICOM tags alone is impossible.
PASER: A Pattern-Based Approach to Service Requirements Analysis

Inconsistent specification are an inevitable intermediate product of a service requirements engineering process. In order to reduce requirements inconsistencies, we propose PASER, a Pattern-based Approach to Service Requirements analysis. The PASER approach first extracts the process information from service documents via natural language processing (NLP) techniques, then uses a requirements modeling language – Workflow-Patterns-based Process Language (WPPL) — to build the process model. Finally, through matching with workflow patterns, the inconsistencies in service requirements are identified and resolved by checking against a set of checking rules. We have conducted a preliminary experiment to evaluate it. An ATM service case study is presented as a running example to illustrate our approach.
Regional variation in cardiovascular disease risk factors among American Indians and Alaska Natives with diabetes.

OBJECTIVE To compare by region risk factors for cardiovascular disease among American Indian populations with diabetes. RESEARCH DESIGN AND METHODS Trained providers from 185 federal, urban, and tribally operated facilities reviewed the records from systematic random samples of the patients included in the local diabetes registries in the 1998 Indian Health Service (IHS) Diabetes Care and Outcomes Audit. Selected measures of cardiovascular risk were aggregated by region and adjusted to calculate regional rates for patients <45 years of age (n = 2,595) and those aged > or =45 years (n = 8,294). RESULTS Among the younger group of patients with diabetes, the rates of elevated HbA(1c) (> or =9%) and tobacco use varied significantly among regions. High rates of obesity (78%) and elevated HbA(1c) (56%) were found in the Southwest. High rates of tobacco use (55%) but the lowest rates of elevated HbA(1c) (27%) were found in Alaska. Among patients aged > or =45 years, all measures including rates of proteinuria, cholesterol > or =200 mg/dl, and mean blood pressure > or =130/85 varied significantly among all regions. Tobacco use was highest in the Great Lakes (44%) and Great Plains (42%) regions and lowest in the Southwest (14%) and Colorado Plateau (8%) regions. Proteinuria was found most frequently in the Southwest (35%), Colorado Plateau (30%), and Pacific regions (35%). Older individuals with diabetes were more likely than younger individuals to have proteinuria and blood pressure > or =130/85. CONCLUSIONS American Indians and Alaska Natives with diabetes carry a large burden of potentially modifiable cardiovascular risk factors, but there is significant regional variation.
Deletion of the NADPH-Cytochrome P450 Reductase Gene in Cardiomyocytes Does Not Protect Mice against Doxorubicin-Mediated Acute Cardiac Toxicity

A genetic mouse model (designated cardiomyocyte-Cpr-null) with cardiomyocyte-specific deletion of the cytochrome P450 (P450) reductase (Cpr) gene was generated in this study. CPR protein levels, as well the enzyme activity of P450s, were greatly reduced in heart microsomes from the null mice compared with wild-type mice, whereas CPR expression in other organs remained unchanged. Nonetheless, homozygous null mice were normal in appearance, gross anatomy, tissue morphology, and general cardiac functional parameters, and there was no indication of embryonic lethality or premature mortality in contrast to the recognized role of CPR in embryonic development. Thus, this new mouse model should be useful for determination of the in vivo roles of cardiomyocyte CPR and CPR-dependent enzymes, including microsomal P450s, not only in the metabolism and toxicity of numerous xenobiotic compounds but also in cardiac pathophysiology. As a first application, we studied the role of cardiomyocyte CPR and CPR-dependent enzymes in doxorubicin (Dox)-mediated acute cardiotoxicity. Wild-type and null mice were treated with a single i.p. dose of Dox at 5, 10, or 20 mg/kg. The Dox treatment caused apoptosis and vacuolization in cardiomyocytes at the dose of 20 mg/kg and a significant increase in the levels of serum creatine kinase at 10 and 20 mg/kg in both wild-type and null mice. However, there was no significant difference in the extent of Dox-induced cardiac injury between the two strains; this lack of difference suggests that cardiomyocyte CPR and CPR-dependent enzymes do not play critical roles in the acute cardiotoxicity induced by Dox.
Highlight Separation Using Multiple Images with Intensities and Ranges

In this paper, a method for extracting influences of specular reflection and shade from multiple color images is described. As regards extraction, the di-chromatic reflection model is applied. First, the same point on an object is observed from multiple viewpoints, and the pixel values in a window in which the fixation point is being imaged are projected into RGB color space. The shape of each cluster is linear, and, when one of the images observed the specular reflection, the clusters intersect . By using this phenomenon a specular reflection is extracted. To register each color image, range images are measured. Each range image is measured from the same viewpoint with a color image. In this paper, using image extracted specular and shade as texture data, a color object is reconstructed by the use of computer graphics images.
Affective-cognitive dialogue act detection in an error-aware spoken dialogue system

This paper presents an approach to affective-cognitive dialogue act detection in a spoken dialogue. To achieve this goal, the input utterance is decoded as the affective state by an emotion recognizer and a word sequence by an imperfect speech recognizer separately. Besides, four types of evidences are employed to grade the score of each recognized word. The recognized word sequence is used to derive the candidate sentences to alleviate the problem of unexpected language usage for the cognitive state predicted by the vector space-based dialogue act detection. The Boltzmann selection based method is then employed to predict the next possible act in the spoken dialogue system according to the affective-cognitive states. A model of affective anticipatory reward that is assumed to arise from the emotional seeking system is adopted for enhancing the efficacy of dialogue act detection. Finally, the evaluation data are collected and the experimental results confirm the improved performance of the proposed approach compared to the baseline system on the task completion rate.
In-House Solution for the RecSys Challenge 2015

RecSys Challenge 2015 is about predicting the items a user will buy in a given click session. We describe the in-house solution to the challenge as guided by the YOOCHOOSE team. The presented solution achieved 14th place in the challenge's final leaderboard with a score of 51,932 points, while the winner obtained 63,102 points. We suggest two simple and easy to reconstruct approaches for obtaining a prediction in each session. In the first approach we suggest one classifier to determine whether each item in the session will be bought. In the second approach we suggest a two level classification model in which the first level determines whether the session is going to end with a purchase or not, and if it ends with a purchase, the second level classification determines the items that are going to be purchased.
Energy-efficient multi-hop medical sensor networking

Wireless sensor networks represent a key technology enabler for enhanced health care and assisted living systems. Recent standardization eorts to ensure compatibility among sensor network systems sold by dierent vendors have produced the IEEE 802.15. 4 standard, which specifies the MAC and physical layer behavior. This standard has certain draw-backs: it supports only single-hop communication; it does not mitigate the hidden terminal problem; and it does not coordinate node sleeping patterns. The IEEE 802.15. 4 standard design philosophy assumes that higher layer mechanisms will take care of any added functionality. Building on IEEE 802.15. 4, this paper proposes TImezone COordinated Sleep Scheduling (TICOSS), a mechanism inspired by MERLIN [2] that provides multi-hop support over 802.15. 4 through the division of the network into timezones. TICOSS is cross-layer in nature, as it closely coordinates MAC and routing layer behavior. The main contributions of TICOSS are threefold: (1) it allows nodes to alternate periods of activity and periods of inactivity to save energy; (2) it mitigates packet collisions due to hidden terminals belonging to nearby star networks; (3) it provides shortest path routing for packets from a node to the closest gateway. Simulation experiments confirm that augmenting IEEE 802.15. 4 networks with TICOSS doubles the operational lifetime for high trac scenarios. TICOSS has also been implemented on the Phillips AquisGrain modules for testing and eventual deployment in assisted living systems.
Face Recognition Increases during Saccade Preparation

Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.
Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.
2.5K-graphs: From sampling to generation

Understanding network structure and having access to realistic graphs plays a central role in computer and social networks research. In this paper, we propose a complete, practical methodology for generating graphs that resemble a real graph of interest. The metrics of the original topology we target to match are the joint degree distribution (JDD) and the degree-dependent average clustering coefficient (c̅(k)). We start by developing efficient estimators for these two metrics based on a node sample collected via either independence sampling or random walks. Then, we process the output of the estimators to ensure that the target metrics are realizable. Finally, we propose an efficient algorithm for generating topologies that have the exact target JDD and a c̅(k) close to the target. Extensive simulations using real-life graphs show that the graphs generated by our methodology are similar to the original graph with respect to, not only the two target metrics, but also a wide range of other topological metrics. Furthermore, our generator is order of magnitudes faster than state-of-the-art techniques.
Targeting Toll-Like Receptors for Treatment of SLE

Toll-like receptors (TLRs) are important innate immune receptors for the identification and clearance of invading pathogens. Twelve TLRs that recognize various conserved components of microorganisms are currently known. Among these, the endosomal TLRs 3, 7/8, and 9 recognize dsRNA, ssRNA, and CpG DNA, respectively. Nucleic acid-sensing TLRs, TLR 7 in particular, have been implicated in systemic lupus erythematosus (SLE) and are thought to exacerbate disease pathology. Activation of these TLRs results in the production of inflammatory cytokines and type I interferon. Genome-wide association studies, single nucleotide polymorphism analyses as well as experimental mouse models have provided evidence of TLR signaling involvement in SLE and other autoimmune diseases. Since activation of these receptor pathways promotes autoimmune phenotypes, inhibitory drugs that target these pathways constitute important new therapeutic strategies for the treatment of systemic autoimmunity.
New Antibiotic Molecules: Bypassing the Membrane Barrier of Gram Negative Bacteria Increases the Activity of Peptide Deformylase Inhibitors

Background Multi-drug resistant (MDR) bacteria have become a major concern in hospitals worldwide and urgently require the development of new antibacterial molecules. Peptide deformylase is an intracellular target now well-recognized for the design of new antibiotics. The bacterial susceptibility to such a cytoplasmic target primarily depends on the capacity of the compound to reach and accumulate in the cytosol. Methodology/Principal Findings To determine the respective involvement of penetration (influx) and pumping out (efflux) mechanisms to peptide deformylase inhibitors (PDF-I) activity, the potency of various series was determined using various genetic contexts (efflux overproducers or efflux-deleted strains) and membrane permeabilizers. Depending on the structure of the tested molecules, two behaviors could be observed: (i) for actinonin the first PDF-I characterized, the AcrAB efflux system was the main parameter involved in the bacterial susceptibility, and (ii), for the lastest PDF-Is such as the derivatives of 2-(5-bromo-1H-indol-3-yl)-N-hydroxyacetamide, the penetration through the membrane was a important limiting step. Conclusions/Significance Our results clearly show that the bacterial membrane plays a key role in modulating the antibacterial activity of PDF-Is. The bacterial susceptibility for these new antibacterial molecules can be improved by two unrelated ways in MDR strains: by collapsing the Acr efflux activity or by increasing the uptake rate through the bacterial membrane. The efficiency of the second method is associated with the nature of the compound.
Exploring the Limits of Tag Reduction for Energy Saving on a Multi-core Processor

Saving energy usually leads to performance degradation. We explore the limits of tag reduction on a multi-core processor with guaranteed performance effect. In our previous work, tag reduction is applied to multi-core processors and shows significant energy savings, meanwhile it causes performance overhead. In this paper, we have found out that when tag reduction is used on multi-core processors, the number of cores is the key factor that affects both energy and performance. More specifically, when tag reduction is applied to multi-core processors, as the number of core integrated into the chip increases, tag reduction can save more energy, while causes more performance degradation. Tag reduction has the limits that are represented by the number of cores. In order to derive the limits, we study the relationship between energy consumption and performance overhead and propose a decision model. We build up an experiment platform that is composed of Linux Physical Memory Monitor (LPMM), Trace Recorder (TR), Scalable Multi-core Simulator (SMS) and Data Analysis Module (DAM). We evaluate benchmarks from SPEC CPU2006 on a real operating system with help of LPMM and TR; and then get the raw results about energy and performance using SMS; finally, DAM analyzes the raw results and finds out the limits. Experimental results show that tag reduction should be applied to the multi-core processor which integrates no more than 6 cores; otherwise, the energy- and performance-efficiency of tag reduction degrades.
Catalysis of Protein Folding by an Immobilized Small‐Molecule Dithiol

The isomerization of non‐native disulfide bonds often limits the rate of protein folding. Small‐molecule dithiols can catalyze this process. Here, a symmetric trithiol, tris(2‐mercaptoacetamidoethyl)amine, is designed on the basis of criteria known to be important for efficient catalysis of oxidative protein folding. The trithiol is synthesized and attached to two distinct solid supports via one of its three sulfhydryl groups. The resulting immobilized dithiol has an apparent disulfide E°′ = –208 mV, which is close to that of protein disulfide isomerase (E°′ = –180 mV). Incubation of the dithiol immobilized on a TentaGel resin with a protein containing non‐native disulfide bonds produced only a 2‐fold increase in native protein. This dithiol appeared to be inaccessible to protein. In contrast, incubation of the dithiol immobilized on styrene‐glycidyl methacrylate microspheres with the non‐native protein produced a 17‐fold increase in native protein. This increase was 1.5‐fold greater than that of a monothiol immobilized on the microspheres. Thus, the choice of both the solid support and thiol can affect catalysis of protein folding. The use of dithiol‐decorated microspheres is an effective new strategy for preparative protein folding in vitro.
$G$-Band Distributed Microelectromechanical Components Based on CMOS Compatible Fabrication

Microelectromechanical systems (MEMS) technology has been used for realizing G-band (140-220 GHz) distributed MEMS transmission line components. Novel dielectric-less MEMS components, as well as switched MEMS capacitors, have been fabricated with CMOS compatible surface micromachining, and experimental results are presented up to 220 GHz.