Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Use Context on Mobile Payment User Adoption: An Empirical Study in China

The study aims to investigate the factors that affect users’ intention to adopt mobile payment services. Drawing upon the Technology Acceptance Model, the study integrates use context and subjective norm to put forward a theoretical model. 375 valid survey responses were collected. The results show that use context is the strongest predictor of intention to adopt mobile payment services. It has both direct and indirect effects on behavioral intention, and the indirect effects are mediated by perceived ease of use and perceived usefulness. Subjective norm and perceived ease of use significantly influence perceived usefulness. Both theoretical and practical implications are discussed.
Rho mediates cytokinesis and epiboly via ROCK in zebrafish

To study the regulation of embryonic development by Rho, we microinjected Clostridium botulinum C3‐exoenzyme (C3) into zebrafish embryos. We found that C3 inhibited cytokinesis during early cleavages. C3 inhibition appeared to be specific on RhoA, since the constitutively active RhoA could partially rescued the C3‐induced defects. Distributions of actin and the cleavage furrow associated β‐catenin were disrupted by C3. Belbbistatin, a myosin II inhibitor, also caused blastomeres disintegration. It suggested that Rho mediates cytokinesis via cleavage furrow protein assembly and actomyosin ring constriction. Furthermore, C3 blocked cellular movements during epiboly and gastrulation as evident by the impairment on no tail and goosecoid expression in blastoderm front runner cells and the dorsal lip of blastopore, respectively. Y‐27632, an antagonist of Rho‐associated kinase (ROK/ROCK), had the similar inhibitory effects on zebrafish development as the C3 treatments. Taken together, these results suggest that Rho mediates cleavage furrow protein assembly during cytokinesis and cellular migration during epiboly and gastrulation via a ROK/ROCK‐dependent pathway. Mol. Reprod. Dev. 71: 186–196, 2005. © 2005 Wiley‐Liss, Inc.
Cost-efficient Capacitation of Cloud Data Centers for QoS-aware Multimedia Service Provision

Cloud infrastructure is increasingly used for the provision of sophisticated multimedia services, such as cloud gaming or Desktop as a Service, with stringent Quality of Service demands. Serving these service demands results in the need to cost-efficiently select and capacitate data centers. In the work at hand, we introduce the corresponding Cloud Data Center Capacitation Problem and propose two optimization approaches. Through a quantitative evaluation, we demonstrate that an exact solution approach is only practically applicable to small problem instances, whereas a heuristic based on LP relaxation achieves significant reductions in computation time of about 80% while retaining a favorable solution quality, with cost increases of approximately 5% or less.
Defective Expression of Transforming Growth Factor β Receptor Type II Is Associated with CpG Methylated Promoter in Primary Non-Small Cell Lung Cancer

Purpose: Reduced expression of the transforming growth factor β receptor type II (TGFβRII), a key inhibitor of epithelial cell growth and tumor suppressor gene, was reported frequently in many types of tumors including non-small cell lung cancer (NSCLC). This study explored the significance of the TGFβRII gene in NSCLC carcinogenesis. Experimental Design: With 43 independent pairs of tumor and paracarcinoma tissue samples from patients with primary NSCLC, we carried out PCR-denaturing gradient gel electrophoresis screening for DNA variants over the coding sequence of the TGFβRII gene, immunohistochemical assay of TGFβRII expression, methylation-specific PCR analysis, and semiquantitative reverse transcription-PCR. Results: The PCR-denaturing gradient gel electrophoresis did not detect variation in the whole coding sequence of the TGFβRII gene, but the immunohistochemistry experiment revealed reduced or lost expression of the gene in 44% (19 of 43) of the tumor samples. The methylation analysis on the 19 pairs detected the frequent occurrence of methylated TGFβRII promoter in tumor tissues, whereas most of the paracarcinoma tissues were free of methylation. The reduced TGFβRII expression was highly significantly associated with the methylation event (P < 10−4). The reverse transcription-PCR analysis demonstrated a clear agreement between reduced TGFβRII expression and decreased mRNA level of the gene in the tumor tissue samples. Conclusions: TGFβRII plays an important role as a tumor suppressor in NSCLC carcinogenesis. The defective expression may serve as one of most important molecular mechanisms in explaining progression of the disease. In particular, aberrant 5′ CpG methylation of the gene has explained the down-regulation of the gene at a transcriptional level.
Vehicle trajectory prediction based on Hidden Markov Model

In Intelligent Transportation Systems (ITS), logistics distribution and mobile e-commerce, the real-time, accurate and reliable vehicle trajectory prediction has significant application value. Vehicle trajectory prediction can not only provide accurate location-based services, but also can monitor and predict traffic situation in advance, and then further recommend the optimal route for users. In this paper, firstly, we mine the double layers of hidden states of vehicle historical trajectories, and then determine the parameters of HMM (hidden Markov model) by historical data. Secondly, we adopt Viterbi algorithm to seek the double layers hidden states sequences corresponding to the just driven trajectory. Finally, we propose a new algorithm (DHMTP) for vehicle trajectory prediction based on the hidden Markov model of double layers hidden states, and predict the nearest neighbor unit of location information of the next k stages. The experimental results demonstrate that the prediction accuracy of the proposed algorithm is increased by 18.3% compared with TPMO algorithm and increased by 23.1% compared with Naive algorithm in aspect of predicting the next k phases" trajectories, especially when traffic flow is greater, such as this time from weekday morning to evening. Moreover, the time performance of DHMTP algorithm is also clearly improved compared with TPMO algorithm.
Empirical scatter correction (esc): A new CT scatter correction method and its application to metal artifact reduction

Scatter artifacts impair the CT image quality and the accuracy of CT values. Especially in cases with metal implants and in wide cone-angle flat detector CT scans, scatter artifact removal can be of great value. Typical scatter correction methods try to estimate scattered radiation and subtract the estimated scatter from the uncorrected data. Scatter is found either by time-consuming Monte Carlo-based simulations of the photon trajectories, or by rawdata-based modelling of the scatter content using scatter kernels, whose open parameters have to be determined very accurately and for each scanner and type of object individually, and that sometimes even require a data base of typical objects. The procedures are time-consuming and require intimate knowledge about the scanner, in particular about the spectral properties, for which a correction is designed. We propose an empirical scatter correction (ESC) algorithm which does not need lots of prior knowledge for calibration. ESC assumes that a linear combination of the uncorrected image with various ESC basis images is scatter-free. The coefficients for the linear combination are determined in image domain by maximizing a flatness criterion of the combined volume. Here, we minimized the total variation in soft tissue regions using the gradient descent method with a line search. Simulated data and several patient data sets acquired with a clinical cone-beam spiral CT scanner, where scatter was added using a Monte Carlo scatter calculation algorithm, were used to evaluate ESC. Metal implants were simulated into those data sets, too. Our preliminary results indicate that ESC has the potential to efficiently reduce scatter artifacts in general, and metal artifacts in particular. ESC is computationally inexpensive, highly flexible, and does not require know-how of the scanner properties.
Void fraction measurement of gas-liquid two-phase flow in mini-pipe based on image sequence

Based on image sequence, a void fraction measurement model of gas-liquid two-phase flow in mini-pipe is developed using support vector regression (SVR) and particle swarm optimization (PSO). A high-speed image acquisition system is constructed to capture dynamic gray image sequence of gas-liquid two-phase flow. The area ratio of gas phase in longitudinal section of the pipe for every image of image sequence is calculated and one-dimension time series can be obtained. And then the mean value, the standard deviation and the nonsymmetrical coefficient are extracted from the one-dimension time series as input vector of the void fraction measurement model. The experiment is carried out in the horizontal mini-pipe with inner diameter of 4.0mm. The results show that the presented void fraction measurement model is feasible and effective. The maximum relative errors of void fraction of slug flow and bubbly flow are less than 8%.
Modification of Multichannel Reconstruction Algorithm on the SAR With Linear Variation of PRI

This paper focuses on the signal processing for synthetic aperture radar (SAR) with fast linear variation of PRI which was introduced to settle the blind range problem in conventional SAR with constant PRI. Since periodic pulse loss is resulted from the variation of PRI, the distribution of the completely received pulses strongly deviates from the ideal uniform one. To settle the problem of nonuniform sampling, multichannel reconstruction algorithm is employed. As the reconstruction requires a priori knowledge of the precise distribution of the samples, this paper first derives the position of the lost pulses. Further, in order to reduce the nonuniformity, an optimal PRI variation scheme is designed. Moreover, considering the drastic degradation of the AASR and the SNR caused by the conventional multichannel reconstruction, we propose a modification where the number of processed frequency bands is reduced, and then the increased degrees of freedom (DOF) are exploited to minimize the power of the residual ambiguities and the noise via a linear constraint minimum power (LCMP) method. Compared to the conventional reconstruction, the modified one dramatically improves the ISLR, the AASR, and the SNR, which is validated by simulation experiments.
Learning Pedestrian Profiles from Movement Trajectories

Pedestrians are highly heterogeneous with regards to their physical capabilities and preferences, which in turn determine their individual infrastructural needs (Saelens et al. 2003, Millonig 2006). Other than in current pedestrian navigation systems, therefore, the possibility to compute personalized walking routes would be desirable, a precondition of which, however, is to derive detailed user profiles (Gartner et al. 2011, Jonietz 2016a).
Urban Travel Time Prediction using a Small Number of GPS Floating Cars

Predicting the travel time of a path is an important task in route planning and navigation applications. As more GPS floating car data has been collected to monitor urban traffic, GPS trajectories of floating cars have been frequently used to predict path travel time. However, most trajectory-based methods rely on deploying GPS devices and collect real-time data on a large taxi fleet, which can be expensive and unreliable in smaller cities. This work deals with the problem of predicting path travel time when only a small number of GPS floating cars are available. We developed an algorithm that learns local congestion patterns of a compact set of frequently shared paths from historical data. Given a travel time prediction query, we identify the current congestion patterns around the query path from recent trajectories, then infer its travel time in the near future. Experimental results using 10-15 taxis tracked for 11 months in urban areas of Shenzhen, China show that our prediction has on average 5.4 minutes of error on trips of duration 10-75 minutes. This result improves the baseline approach of using purely historical trajectories by 2-30% on regions with various degree of path regularity. It also outperforms a state-of-the-art travel time prediction method that uses both historical trajectories and real-time trajectories.
Improved pose estimation by inlier refinement for visual odometry

Visual odometry is a well-known technique that is used to compute the rotation and translation of any moving vehicle with the help of camera mounted over it. This task of vision-based navigation is used for different applications such as autonomous navigation, motion tracking and obstacle detection, etc. This paper illustrates an approach for estimating vehicle motion by detecting and matching scale invariant SURF feature over consequent image frames. These set of matched feature are passed through an outlier removal and inlier selection methodology sequentially in order to remove the inconsistent features. Additionally, the proposed scheme incorporates the bucketing technique to ensure spatial distribution of feature in the overall image space. The proposed scheme of inlier selection-cum-outlier rejection has been applied on the KITTI dataset available online and is found to work satisfactorily as compared to the individual outlier rejection or inlier selection mechanism.
New Green Synthesis and Antineoplastic Activity of Bis (3-Arylimidazolidinyl-1) Methanes

A new green synthesis and anti-tumor activity of the series of bis (3-arylimidazolidinyl-1) methanes 1 - 6 are described. The compounds were synthesized from the corresponding N-arylethylenediamine and trioxane as sources of formaldehyde and the reactions were performed in heterogeneous phase catalyzed by an acidic ion-exchange resin (Amberlyst 15). The compounds were tested with the Sulforhodamine B assay according to the protocol of the National Cancer Institute for several cell lines. The results were expressed as percentage inhibition of growth cell in comparison with the full growth of the cells without treatment. Cytotoxicity on normal cells using the Annexing-PI staining and flow cytometry has been evaluated. The parent compound, bis(3-phenylimidazolidinyl-1)methane 1 and the monohalogenated derivatives 4-chlorophenyl 3 and 3-bromophenyl 5 showed antineoplastic activity, 60%, 82% and 89% inhibition growth cell respectively on the human colon cell line (HCT116). The 4-tolyl derivative 6 presented inhibitory activity (73% inhibition of growth cell) on human lung adenocarcinoma cell line (A549) and 62% on human mammary cell line MCF-7.
Silibinin Improves the Anti-arthritic Activity of Methotrexate in Zymosan-Induced Arthritis in Rats

Because of low toxic effects of plant-derived drugs, it has become a research focus in disease prevention and treatment, especially those chronic diseases requiring long-term treatment. The present study was designed to evaluate the effects of silibinin (SIL) when administered with methotrexate (MTX) in animal model of zymosan-induced arthritis in rats. Male Wistar rats are used for induction and arthritic inflammation in the knee joint and hind paw using zymosan. The animals are treated with MTX alone (10 mg/kg), SIL (10mg/kg) or their combination. The effect was followed through edema formation, tissue cytokines release (IL-1β, IL-8, TNF-α) and infiltration of leukocytes in synovial fluid. The results showed that SIL has weak antiarthritic activity when used alone, and improves the antiarthitic activity of MTX when both are concomitantly administered before challenge with zymosan. In conclusion, although SIL has a relatively weak anti-arthritic activity, it strongly augments the effect of MTX in animal model of zymosan-induced arthritis.
Design and Development of Gliclazide Mucoadhesive Microcapsules: In Vitro and In Vivo Evaluation

In this study an attempt was made to prepare mucoadhesive microcapsules of gliclazide using various mucoadhesive polymers designed for oral controlled release. Gliclazide microcapsules were prepared using sodium alginate and mucoadhesive polymer such as sodium carboxymethyl cellulose (sodium CMC), carbopol 934P or hydroxy propylmethyl cellulose (HPMC) by orifice-ionic gelation method. The microcapsules were evaluated for surface morphology and particle shape by scanning electron microscope. Microcapsules were also evaluated for their microencapsulation efficiency, in vitro wash-off mucoadhesion test, in vitro drug release and in vivo study. The microcapsules were discrete, spherical and free flowing. The microencapsulation efficiency was in the range of 65–80% and microcapsules exhibited good mucoadhesive property in the in vitro wash off test. The percentage of microcapsules adhering to tissue at pH 7.4 after 6 h varied from 12–32%, whereas the percentage of microcapsules adhering to tissue at pH 1.2 after 6 h varied from 35–68%. The drug release was also found to be slow and extended for more than 16 h. In vivo testing of the mucoadhesive microcapsules in diabetic albino rats demonstrated significant antidiabetic effect of gliclazide. The hypoglycemic effect obtained by mucoadhesive microcapsules was for more than 16 h whereas gliclazide produced an antidiabetic effect for only 10 h suggesting that mucoadhesive microcapsules are a valuable system for the long term delivery of gliclazide.
Opportunities in low-level radiocarbon microtracing: applications and new technology

14C-radiolabeled (radiocarbon) drug studies are central to defining the disposition of therapeutics in clinical development. Concerns over radiation, however, have dissuaded investigators from conducting these studies as often as their utility may merit. Accelerator mass spectrometry (AMS), originally designed for carbon dating and geochronology, has changed the outlook for in-human radiolabeled testing. The high sensitivity of AMS affords human clinical testing with vastly reduced radiative (microtracing) and chemical exposures (microdosing). Early iterations of AMS were unsuitable for routine biomedical use due to the instruments’ large size and associated per sample costs. The situation is changing with advances in the core and peripheral instrumentation. We review the important milestones in applied AMS research and recent advances in the core technology platform. We also look ahead to an entirely new class of 14C detection systems that use lasers to measure carbon dioxide in small gas cells.
Identification and Functional Characterization of the BAG Protein Family in Arabidopsis thaliana*

The genes that control mammalian programmed cell death are conserved across wide evolutionary distances. Although plant cells can undergo apoptosis-like cell death, plant homologs of mammalian regulators of apoptosis have, in general, not been found. This is in part due to the lack of primary sequence conservation between animal and putative plant regulators of apoptosis. Thus, alternative approaches beyond sequence similarities are required to find functional plant homologs of apoptosis regulators. Here, we present the results of using advanced bioinformatic tools to uncover the Arabidopsis family of BAG proteins. The mammalian BAG (Bcl-2-associated athanogene) proteins are a family of chaperone regulators that modulate a number of diverse processes ranging from proliferation to growth arrest and cell death. Such proteins are distinguished by a conserved BAG domain that directly interacts with Hsp70 and Hsc70 proteins to regulate their activity. Our searches of the Arabidopsis thaliana genome sequence revealed seven homologs of the BAG protein family. We further show that plant BAG family members are also multifunctional and remarkably similar to their animal counterparts, as they regulate apoptosis-like processes ranging from pathogen attack to abiotic stress and development.
Effect of a modulator deletion on transcription of the human cytomegalovirus major immediate-early genes in infected undifferentiated and differentiated cells

Differentiation-dependent expression of the human cytomegalovirus (HCMV) major immediate-early (MIE) genes, encoding IE1 and IE2, may partly govern virus replication in monocytic THP-1 and embryonal carcinoma (Tera-2) cells. The modulator of the MIE promoter was shown previously in transient transfection assays to repress transcription from promoter segments in undifferentiated THP-1 and Tera-2 cells but not in differentiated cells. To determine the biological importance of these findings, we constructed a recombinant HCMV (r delta MSVgpt) without a modulator. In comparison to wild-type (WT) virus, r delta MSVgpt exhibits a slight delay in growth in human fibroblasts, but there is no appreciable change in IE1 and IE2 transcription. Moreover, there is no appreciable change in the early/late kinetics of transcription of RNAs colinear with the predicted UL128 coding region, which is adjacent to the modulator, although the size distribution and abundance of these RNAs are altered. In infected undifferentiated THP-1 and Tera-2 cells, WT and r alpha MSVgpt viruses produce minimal but comparable amounts of IE1 RNAs. The genomes of both viruses are detectable in similar amounts within these undifferentiated cells. Induction of cellular differentiation before infection overcomes the block in MIE gene transcription. WT and r alpha MSVgpt infections of differentiated THP-1 cells produce similar levels of IE1 and IE2 RNAs. Thus, differentiation-dependent control of MIE gene transcription involves regulatory mechanisms other than the modulator. Possible alternative functions of the modulator are discussed.
Randomization effect on iterative-based speaker diarization system for telephone conversations

The primary objective of speaker diarization system is to designate speech segments to one of K speakers in the conversation. We use a hidden-distortion-model (HDM)-based system. HDM allows using different emission models as speaker models. We investigate the effect of randomization in two different levels. One level is stochastic training versus deterministic training and the other, random model initialization versus preserving initialization from the previous iteration. The emission models were codebooks (CBs) trained using K-means algorithm, both, batch and stochastic versions, as well as a self-organizing map (SOM) in its stochastic version. The evaluation performed on 108 telephone conversations from the LDC CallHome corpus. We will show that randomizing is always outperforming the deterministic training. Stochastic training demonstrated relative improvement of 3.5%. Random initialization achieved relative improvement of 7.28% comparing to preservation of initialization from the previous iteration.
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information

We study the misclassification error for community detection in general heterogeneous stochastic block models (SBM) with noisy or partial label information. We establish a connection between the misclassification rate and the notion of minimum energy on the local neighborhood of the SBM. We develop an optimally weighted message passing algorithm to reconstruct labels for SBM based on the minimum energy flow and the eigenvectors of a certain Markov transition matrix. The general SBM considered in this paper allows for unequal-size communities, degree heterogeneity, and different connection probabilities among blocks. We focus on how to optimally weigh the message passing to improve misclassification.