Miracle-dz/UniFAR-FTUs huggingface dataset:
Model driven evolution of web applications

Reverse engineering is usually used to recover missing and up to date models of a software system to support its comprehension when changes are required to maintain or evolve it. Model driven engineering approaches have been recently proposed to develop more quickly web applications with a high design quality and maintainability. Integrating reverse engineering techniques with model driven web engineering methods originates evolution approaches that would reduce the evolution effort while improving the quality of the modified web application. Such an evolution process exploits the models recovered by reverse engineering as the inputs of a model driven web engineering approach to design and implement the modified/evolved version of the application. This paper describes a general process for the model driven evolution of web applications, suitable for any model driven web engineering method. An instance of such a process tailored for the Ubiquitous Web Applications (UWA) design methodology is also briefly summarized.
Proteomic analysis of the coagulation reaction in plasma and whole blood using PROTOMAP

Proteases are critical in many physiological processes and the human genome encodes for 566 predicted proteolytic enzymes. Therefore, there is great interest in identifying and characterizing physiologic protease–substrate relationships. The coagulation cascade is a well‐described network of serine proteases. However, new interactions of the coagulation cascade with other biological pathways have been discovered only recently. Therefore, we hypothesized that a non‐biased protease degradomics analysis of the physiologic coagulation reaction would identify new interactions between the coagulation cascade and other pathways. We used the recently described PROTOMAP technique to profile the complete coagulation degradome. This analysis detected virtually all of the proteins of the coagulation cascade and identified a majority of the expected proteolytic events, suggesting significant coverage of the coagulation degradome. Multiple potential new proteolytic cleavages were detected, including two of transmembrane proteins that may be shed from the surface of blood cells. In addition, this analysis was able to identify several new potentially secreted proteins. A significant majority of the newly identified events were of proteins involved in innate immunity (complement and inflammation). This highlights potential new areas of crosstalk between these linked systems. Future studies will elucidate the details and functional consequences of these proteolytic events during coagulation.
Critical Human Hepatocyte-Based In Vitro Assays for the Evaluation of Adverse Drug Effects

A major challenge in drug development is to accurately estimate human adverse drug effects to allow the selection and advancement of drug candidates with the best safety profile for further development. Due to species differences, safety data obtained with the routine in vivo studies with nonhuman laboratory animals do not always correctly predict human outcome. Human liver-derived systems, especially human hepatocytes, represent physiologically-relevant experimental systems for the evaluation of human adverse drug effects. The assays developed with human-based in vitro experimental systems for the assessment of two major adverse drug effects: drug-drug interactions and drug toxicity can be used routinely during drug development to select and optimize drug candidates to enhance the probability of clinical success.
A Reconfigurable PIFA Using a Switchable PIN-Diode and a Fine-Tuning Varactor for USPCS/WCDMA/m-WiMAX/WLAN

A reconfigurable planar inverted-F antenna using a switchable PIN-diode and a fine-tuning varactor is presented for mobile communication applications. Selection of operating modes is achieved by switching the PIN-diode between radiators and tuning the varactor on an antenna's shorting line. Mode I, with the PIN-diode off and tuning the varactor, operates for USPCS (1.85-1.99 GHz), WCDMA (1.92-2.18 GHz), and WLAN (5.15-5.825 GHz). As a result, the varactor used to achieve frequency fine-tuning does not need a DC bias circuit and can expand the bandwidth without increasing the physical size. Mode II, with the PIN diode on and the fixed 0-V varactor, operates for USPCS and m-WiMAX (3.4-3.6 GHz). To optimize the antenna structure, a parametric analysis is performed by sweeping the length and width of the radiators. Furthermore, equivalent models of a PIN diode and a varactor are presented for accurate prediction of antenna performances which are also analyzed by varying diode parameters. All simulated results are confirmed with measured data. The peak gains show 2.84, 2.81, 1.25, and 1.49 dBi at USPCS, WCDMA, m-WiMAX, and WLAN, respectively.
Cooperative regions for decode and forward strategies over Rayleigh fading channels

Cooperative diversity has the ability of achieving multiplexing and diversity gains by taking advantage of the features and potentials of spatial distribution. Based on the asymptotic outage probability, we define the Cooperative Gain (CG) to evaluate the benefits of cooperation over direct transmission under high Signal-to-Noise Ratio (SNR). With the presence of Rayleigh fading and path loss, our analytical results illustrate the appropriate Cooperative Region (CR), in which the source prefers to coordinately work with the relay rather than transmit directly. Finally, we provide visible CRs and numerical results on the exact outage performance by Monte Carlo simulations.
Metamaterial surface antenna technology: Commercialization through diffractive metamaterials and liquid crystal display manufacturing

For mobile, broadband satellite communications applications such as the connected car, a high-gain, scanning antenna is required. Kymeta® is commercializing an electronically scanned, metamaterial antenna technology achieved through the use of diffractive metasurfaces and high-birefringence liquid crystals. Kymeta's technology is positioned for mass production by leveraging the manufacturing capabilities of the liquid crystal display industry.
Polynomial accelerated algorithm base on minimizing TV for computerized tomographic image reconstruction

Based on total variation minimization (TV) algorithm and the theory of polynomial acceleration, we prompted a modified algorithm, which is called P-TV in this paper. This new algorithm has a better noise immunity and fewer iteration numbers than the traditional TV algorithm. P-TV algorithm can be divided into four steps. Compared to the traditional TV algorithm, the P-TV algorithm applies the theory of polynomials to ART iteration step to enforce data consistency with the projection data and applies the positivity constraint after the GRAD-step too, which accelerate convergence of image reconstruction. Simulation results prove that when the iteration number is the same, the quality of reconstructed image from P-TV algorithm is better than traditional TV algorithm. When the quality of image reconstructed by both algorithms is nearly the same, the iteration number of P-TV algorithm is much less than the number of traditional TV algorithm. At last we applied the two algorithms to CT image reconstruction from the noisy data. All results show that the P-TV algorithm is effective.
Performance Evaluation on the Basis of Energy in NoCs

The classical interconnection network topologies such as point-to-point and bus-based, recently has been replaced by the new approach Network-on-Chip (NoC). NoC can consume significant portions of a chip’s energy budget, so analyzing their energy consumption early in the design cycle becomes important for architectural design decisions. Although numerous studies have examined NoC implementation and performance, few have examined energy. This paper determines the energy efficiency of some of the basic network topologies of NoC. We compared them, and results show that the CMesh topology consumes less energy than Mesh topology.
CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape. org/apps/cytocluster.
Multi-Label Learning. A Review of the State of the Art and Ongoing Research

Multi-label learning is quite a recent supervised learning paradigm. Owing to its capabilities to improve performance in problems where a pattern may have more than one associated class, it has attracted the attention of researchers, producing an increasing number of publications. The paper presents an up-to-date overview about multi-label learning with the aim of sorting and describing the main approaches developed till now. The formal deﬁnition of the paradigm, the analysis of its impact on the literature, its main applications, works developed and ongoing research are presented.
CIAL at the NTCIR-13 STC-2 Task

Short text conversation (STC) has emerged as a prominent research topic and gained considerable attention in recent years. While it is still an open problem whether the retrieval-based method should be replaced by or combined with generative models for STC task, the NTCIR-13 STC-2 Task provides a transparent platform to compare the two aforementioned methods via doing comprehensive evaluations. In this task, we proposed a retrieval-based method with distributed vector representation, and a generation-based method with recurrent neural networks. Overall, we submitted 4 and 1 of-ﬁcial runs for retrieval and generation settings, respectively. We also proposed a data augmentation method for extending the amount of labeled data that is more suﬃcient for training a generative model.
An Enriched Mixture of Trans-10,Cis-12-CLA Inhibits Linoleic Acid Metabolism and PGE2 Synthesis in MDA-MB-231 Cells

Abstract: Conjugated linoleic acid (CLA) isomers are potent inhibitors of mammary tumor cell growth. Evidence suggests that CLA modulates essential fatty acid (EFA) metabolism; however, it is not clear which parts of this pathway are important regulatory points modulated by CLA. Enriched mixtures of D9-cis,11-trans (D9c,11t)- and D10-trans,12-cis (D10t,12c)-18:2 were used to assess outcome measures of EFA metabolism pertaining to membrane phospholipid incorporation, tumor cell growth, and prostaglandin E2 (PGE2) synthesis in the MDA-MB-231 mammary tumor cell line. Tumor cells were treated with linoleic acid (LA), an equal mixture (Mix), or enriched preparations of D9c,11t- or D10t,12c-18:2. Treatment with Mix or the enriched mixture of D10t,12c-18:2 significantly inhibited the synthesis of arachidonic acid (AA) from LA, resulting in increased levels of LA and decreased levels of AA in membrane phosphatidylcholine and phosphatidylethanolamine (P < 0.05). LA and AA levels were not altered in cells treated with enriched D9c,11t-18:2 and were similar to those in LA control treated cells. All CLA treatments reduced [3H]thymidine uptake, an indicator of tumor cell growth, by more than one-half relative to LA controls. MDA-MB-231 cells challenged with AA in the presence of all CLA mixtures resulted in significantly reduced PGE2 synthesis relative to controls treated with LA (P < 0.05). It is evident that individual isomers exert inhibitory effects at specific steps of EFA metabolism, which correspondingly leads to a reduction in PGE2 synthesis and, ultimately, tumor growth.
Semi-clustering That Scales: An Empirical Evaluation of GraphX

GraphX is a distributed graph processing framework build on top of Spark Core. This work investigates the two questions, whether GraphX is an appropriate environment for the implementation of graph algorithms and how the computation of graph algorithms based on GraphX scales. This paper examines a graph algorithm for semi-clustering as used in social network analysis. We describe the implementation process of this algorithm beginning with a graph-oriented modeling tailored for GraphX up to an executable program. Based on our implementation, we have performed empirical evaluations regarding the scalability of our implementation and the GraphX platform. The experiments evidence that different kind of graph algorithms are supported by GraphX and that the execution of our algorithm can scale almost linearly when properly designed.
Providing Professional Development Approaches for Novice Lecturers: A Case of One Chinese University

In the higher education field, professional development helps novice lecturers transform their identities and familiarize themselves with their work to become more comfortable teaching at the university. The task of university management in the professional development of novice lecturers is to supervise their professional growth and to design and continuously improve professional development approaches aimed at enhancing their capabilities. The purpose of this qualitative case study is from the university management perspective to explore the various approaches employed by a particular university in fostering the professional development of novice lecturers and what the benefits of these approaches bring to novice lecturers. To achieve this, in-depth interviews were conducted with six members of the university management, and documentary data was also gathered. A thematic analysis was subsequently conducted to extract key themes from the collected data. This study revealed that in this selected university, the university management assists and supports the professional development of novice lecturers through a range of approaches such as workshops and lectures, teaching competitions, mentorship programs, and participation in university-enterprise collaborations. These diversified professional development approaches enable novice lecturers to enhance their professional skills and competencies, as well as self-confidence, laying a strong base for them to grow into outstanding educators. It is recommended that the university management maintain and improve existing professional development approaches and innovate other activities and programs to support novice lecturers on an ongoing basis.
Does marital status and marital status change predict physical health in older adults?

Background. Evidence for the effects of marital status and marital status change on physical health is equivocal. Method. Structural equation models examined whether marital status predicted physical health. Six groups were examined simultaneously: married (M); widowed (W); divorced (D); never married (NM); newly widowed (NW); and newly divorced (ND). There were four annual measures (T1–T4). Both NW and ND were married at T1, but had lost their partners by T2. Four physical health variables were examined: Problems, Limitations, Service use, and Self-rated health (SRH). Age and gender were included. Results. Previous health predicted future for all measures and for all groups. However, the specific strengths and time-courses varied between marital status groups and between health measures. The most marked patterns were associated with marital status change. Service use was influenced most strongly by NW, whilst Limitations was influenced by ND. Problems distinguished NW and ND from stable marital status groups but also from each other. SRH was influenced by W and not by recent marital status change. The effects of age and gender were modest and restricted to specific health variables and specific marital statuses. Conclusions. The results demonstrate that marital status and marital status change, in particular, influence health longitudinally. The impact of a change to divorced or to widowed status is not the same. No two health variables responded in the same way, suggesting that marital status has a differential effect on health.
Uric Acid Therapy Improves Clinical Outcome in Women With Acute Ischemic Stroke

Background and Purpose— It is unknown whether women and men with acute ischemic stroke respond similar to an antioxidant regimen administered in combination with thrombolysis. Here, we investigated the independent effect of sex on the response to uric acid (UA) therapy in patients with acute stroke treated with alteplase. Methods— In the Efficacy Study of Combined Treatment With Uric Acid and rtPA in Acute Ischemic Stroke (URICO-ICTUS) trial, 206 women and 205 men were randomized to UA 1000 mg or placebo. In this reanalysis of the trial, the primary outcome was the rate of excellent outcome at 90 days (modified Rankin Scale, 0–1, or 2, if premorbid score of 2) in women and men using regression models adjusted for confounders associated with sex. The interaction of UA levels by treatment on infarct growth was assessed in selected patients. Results— Excellent outcome occurred in 47 of 111 (42%) women treated with UA, and 28 of 95 (29%) treated with placebo, and in 36 of 100 (36%) men treated with UA and 38 of 105 (34%) treated with placebo. Treatment and sex interacted significantly with excellent outcome (P=0.045). Thus, UA therapy doubled the effect of placebo to attain an excellent outcome in women (odd ratio [95% confidence interval], 2.088 [1.050–4.150]; P=0.036), but not in men (odd ratio [95% confidence interval], 0.999 [0.516–1.934]; P=0.997). The interactions between treatment and serum UA levels (P<0.001) or allantoin/UA ratio (P<0.001) on infarct growth were significant only in women. Conclusions— In women with acute ischemic stroke treated with alteplase, the administration of UA reduced infarct growth in selected patients and was better than placebo to reach excellent outcome. Clinical Trial Registration— URL: https://clinicaltrials.gov. Unique identifier: NCT00860366.
Comparative Analysis and Optimization of Dynamic Charging Coils for Roadway-Powered Electric Vehicles

Roadway-powering systems can effectively improve the driving distance of electric vehicles (EVs) while releasing the overdependence on batteries. As the key technical issue, the design of primary and pickup coils determines the dynamic charging performance. In recent years, the double-D-quadrature (DDQ) pickup coil has been increasingly utilized in EV dynamic charging systems by means of the persistence and stability of move-and-charge. However, the impact of primary coils with various topologies on DDQ pickup coils has been nearly unexplored in previous studies. Accordingly, this paper presents a comparative analysis of the circular-shaped, rectangle-shaped and multi-thread primary coils for DDQ-based roadway-powering systems with an emphasis on the transmission power, energization persistence, thermal analysis, and initial investment that aims to provide technical references for further research and development of EV dynamic wireless charging systems.
Automatic hyperparameter estimation in probabilistic image restoration algorithm based on Gibbs microcanonical distribution

For an original image given as an 8-gray-level image, the framework for image restoration is composed of Bayes statistics for the a priori probability distribution based on the microcanonical distribution. In this process, the a priori probability distribution serving as the microcanonical distribution is formulated on the basis of the variables characterizing the spatial flatness and smoothness of the image in terms of the number of nearest pixel pairs with different gray levels and the number of nearest pixel pairs with gray levels differing by 1. In the present paper, we propose a new method of estimation, from a degraded image, of the number of nearest pixel pairs with different gray levels and the number of nearest pixel pairs with gray levels differing by 1 in the original image. Then, based on that formulation, an iterative computation algorithm for the restoration of a 256-gray-level image is presented from the viewpoint of statistical mechanics. Through some numerical experiments, we investigate how the proposed method can improve the quality of the restored image. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 36(1): 68–78, 2005; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/scj.10365
HiroPoseEstimation: A Dataset of Pose Estimation for Kid-Size Humanoid Robot

Pose estimation is a field of computer vision research that involves detecting, associating, and tracking data points on body parts. It is used for health monitoring, sign language understanding, human gesture control, elderly activities, sports, and humanoid robot pose estimation. The anatomy of a humanoid robot is similar to a human, which forms the basis for utilizing humanoid robot pose estimation. The Humanoid League is a major domain of the RoboCup competition, featuring soccer matches between humanoid robots. Pose estimation is used to measure the robot’s performance. Nevertheless, there have not been many research done on this subject. A new dataset model needs to be developed to solve the proposed problem. This work introduces HiroPoseEstimation, a kid-size humanoid robot dataset with several types of robots used in various poses based on movements in a soccer game. It is evaluated with both bottomup and top-down approaches using keypoint mask R-CNN and single-stage encoder-decoder model. Both methods demonstrate good performance on the proposed dataset.