Miracle-dz/UniFAR-FTUs huggingface dataset:
The applications of the electronic power transformer in Photovoltaic systems

This paper research the Photovoltaic system accessed to the distribution network through the electronic power transformer (EPT) which is different from the conventional style. So the EPT is been slightly changed which is different from the type already been studied. The paper mainly study the work performance of the EPT when it is used in the Photovoltaic system which can adjust the voltage, current and power easily and make the system more controllable.
Accelerating Sparse Matrix Vector Multiplication in Iterative Methods Using GPU

Multiplying a sparse matrix with a vector (spmv for short) is a fundamental operation in many linear algebra kernels. Having an efficient spmv kernel on modern architectures such as the GPUs is therefore of principal interest. The computational challenges that spmv poses are significantlydifferent compared to that of the dense linear algebra kernels. Recent work in this direction has focused on designing data structures to represent sparse matrices so as to improve theefficiency of spmv kernels. However, as the nature of sparseness differs across sparse matrices, there is no clear answer as to which data structure to use given a sparse matrix. In this work, we address this problem by devising techniques to understand the nature of the sparse matrix and then choose appropriate data structures accordingly. By using our technique, we are able to improve the performance of the spmv kernel on an Nvidia Tesla GPU (C1060) by a factor of up to80% in some instances, and about 25% on average compared to the best results of Bell and Garland [3] on the standard dataset (cf. Williams et al. SC'07) used in recent literature. We also use our spmv in the conjugate gradient method and show an average 20% improvement compared to using HYB spmv of [3], on the dataset obtained from the The University of Florida Sparse Matrix Collection [9].
Oral Contraceptives and Premenopausal Bilateral Breast Cancer: A Case-Control Study

We estimated the effect of oral contraceptive (OC) use on premenopausal bilateral breast cancer in a matched case-control study. One hundred forty-four cases were identified from population-based registries of Los Angeles County, California, and of Connecticut and from the major hospitals in Montreal and Quebec City. Matched controls were the unaffected sisters of the cases. When age \vas included in the model, ever-use of OCs for 1 year or more was associated with an odds ratio of 1.7 (95% confidence interval = 1.0–2.9). The odds ratios associated with 1–2, 3–6, and 7 years of use were 1.2 (0.61–2.4), 2.5 (1.2–5.3), and 2.0 (0.93–4.2), respectively. Too few women had used OCs before their first full-term pregnancy or before age 25 for these estimates to be informative. Restricting the analyses to women who had ever given birth yielded an odds ratio for ever-use of OCs of 2.1 (1.0–4.4). The results indicate an increased risk of premenopausal bilateral breast cancer associated with OC use. (Epidemiology 1992;3:414–419)
Risk factors for non-fatal myocardial infarction in young South Asian adults

Objective: To determine the risk factors for premature myocardial infarction among young South Asians. Design and setting: Case–control study in a hospital admitting unselected patients with non-fatal acute myocardial infarction. Methods and subjects: Risk factor assessment was done in 193 subjects aged 15–45 years with a first acute myocardial infarct, and in 193 age, sex, and neighbourhood matched population based controls. Results: The mean (SD) age of the subjects was 39 (4.9) years and 326 (84.5%) were male. Current smoking (odds ratio (OR) 3.82, 95% confidence interval (CI) 1.47 to 9.94), use of ghee (hydrogenated vegetable oil) in cooking (OR 3.91, 95% CI 1.52 to 10.03), raised fasting blood glucose (OR 3.32, 95% CI 1.21 to 8.62), raised serum cholesterol (OR 1.67, 95% CI 1.14 to 2.45 for each 1.0 mmol/l increase), low income (OR 5.05, 95% CI 1.71 to 14.96), paternal history of cardiovascular disease (OR 4.84, 95% CI 1.42 to 16.53), and parental consanguinity (OR 3.80, 95% CI 1.13 to 1.75) were all independent risk factors for acute myocardial infarction in young adults. Formal education versus no education had an independently protective effect on acute myocardial infarction (OR 0.04, 95% CI 0.01 to 0.35). Conclusions: Tobacco use, ghee intake, raised fasting glucose, high cholesterol, paternal history of cardiovascular disease, low income, and low level of education are associated with premature acute myocardial infarction in South Asians. The association of parental consanguinity with acute myocardial infarction is reported for the first time and deserves further study.
Value-focused objectives for CRM system adoption

– The purpose of this paper is to define objectives for Customer Relationship Management (CRM) system adoption. The objectives provide a theoretical basis for strategizing about CRM system adoption. The objectives also provide managers to clearly direct CRM system adoption, thus ensuring a highly successful outcome. , – The authors conducted a sequential multi-method research in Europe. The initial qualitative phase constituted 62 in-depth interviews. Using Keeney’s (1992) value-focused thinking approach, the authors defined 102 CRM system adoption objectives. Quantitative purification techniques, using a sample of 210 organisations, a more parsimonious set of objectives were developed. The complete set of objectives were classified into fundamental and means objectives. , – Results present three fundamental and three means objectives. These objectives allow for successful CRM system adoption. The three fundamental objectives are: maximise CRM organisational culture; ensure an effective relationship with CRM providers; and minimise CRM project risks. The three means objectives are: maximise CRM usage, maximise relational marketing capabilities, maximise CRM orientation. , – This study provides strategic objectives that can be used by companies to plan adoption of a CRM system. Hence the fundamental and means objectives take the form a strategic planning template. , – Although technology adoption has been well researched and has also been extended to address CRM systems, the focus has largely been behavioural. The strategic objectives for CRM system adoption, presented in this paper, are novel. Objectives enable decision making and resource planning. The combination of fundamental and means objectives provide a theoretical basis for ensuring successful CRM system adoption.
Enhancement of UVB radiation-mediated apoptosis by knockdown of cytosolic NADP+-dependent isocitrate dehydrogenase in HaCaT cells

Ultraviolet B (UVB) radiation induces the production of reactive oxygen species (ROS) that promote apoptotic cell death. We showed that cytosolic NADP+-dependent isocitrate dehydrogenase (IDPc) plays an essential role in the control of cellular redox balance and defense against oxidative damage, by supplying NADPH for antioxidant systems. In this study, we demonstrated that knockdown of IDPc expression by RNA interference enhances UVB-induced apoptosis of immortalized human HaCaT keratinocytes. This effect manifested as DNA fragmentation, changes in cellular redox status, mitochondrial dysfunction, and modulation of apoptotic marker expression. Based on our findings, we suggest that attenuation of IDPc expression may protect skin from UVB-mediated damage, by inducing the apoptosis of UV-damaged cells. [BMB Reports 2014; 47(4): 209-214]
Exploring interest correlation for peer-to-peer socialized video sharing

The last five years have witnessed an explosion of networked video sharing, represented by YouTube, as a new killer Internet application. Their sustainable development however is severely hindered by the intrinsic limit of their client/server architecture. A shift to the peer-to-peer paradigm has been widely suggested with success already shown in live video streaming and movie-on-demand. Unfortunately, our latest measurement demonstrates that short video clips exhibit drastically different statistics, which would simply render these existing solutions suboptimal, if not entirely inapplicable. Our long-term measurement over five million YouTube videos, on the other hand, reveals interesting social networks with strong correlation among the videos, thus opening new opportunities to explore. In this article, we present NetTube, a novel peer-to-peer assisted delivering framework that explores the user interest correlation for short video sharing. We address a series of key design issues to realize the system, including a bi-layer overlay, an efficient indexing scheme, a delay-aware scheduling mechanism, and a prefetching strategy leveraging interest correlation. We evaluate NetTube through both simulations and prototype experiments, which show that it greatly reduces the server workload, improves the playback quality and scales well.
Separating Wheat from the Chaff: A Deployable Approach to Counter Spam

Unsolicited bulk email, aka spam is a persistent threat to the usefulness of the Internet. The fight against spam today relies solely on filtering at the recipient's mail server, which can delay mail delivery. We present a spam countering approach consisting of two complementary techniques. The first, token-based authentication, can identify emails from valid senders that a user expects to hear from. This identification prevents much of the good mail from being subjected to the filtering process. The second technique, history-based prioritization, is designed for the rest of the email. It utilizes past information about the sending mail servers and their domains to prioritize email filtration, thus reducing delays in the delivery of good email over spam. The proposed techniques do not rely on any infrastructure, deployed or otherwise, and any mail server can choose to deploy them independent of the choice made by the any other mail server.
False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review

Purpose A number of recent publications have proposed that a family of image-derived indices, called texture features, can predict clinical outcome in patients with cancer. However, the investigation of multiple indices on a single data set can lead to significant inflation of type-I errors. We report a systematic review of the type-I error inflation in such studies and review the evidence regarding associations between patient outcome and texture features derived from positron emission tomography (PET) or computed tomography (CT) images. Methods For study identification PubMed and Scopus were searched (1/2000–9/2013) using combinations of the keywords texture, prognostic, predictive and cancer. Studies were divided into three categories according to the sources of the type-I error inflation and the use or not of an independent validation dataset. For each study, the true type-I error probability and the adjusted level of significance were estimated using the optimum cut-off approach correction, and the Benjamini-Hochberg method. To demonstrate explicitly the variable selection bias in these studies, we re-analyzed data from one of the published studies, but using 100 random variables substituted for the original image-derived indices. The significance of the random variables as potential predictors of outcome was examined using the analysis methods used in the identified studies. Results Fifteen studies were identified. After applying appropriate statistical corrections, an average type-I error probability of 76% (range: 34–99%) was estimated with the majority of published results not reaching statistical significance. Only 3/15 studies used a validation dataset. For the 100 random variables examined, 10% proved to be significant predictors of survival when subjected to ROC and multiple hypothesis testing analysis. Conclusions We found insufficient evidence to support a relationship between PET or CT texture features and patient survival. Further fit for purpose validation of these image-derived biomarkers should be supported by appropriate biological and statistical evidence before their association with patient outcome is investigated in prospective studies.
QProber: A system for automatic classification of hidden-Web databases

The contents of many valuable Web-accessible databases are only available through search interfaces and are hence invisible to traditional Web "crawlers. " Recently, commercial Web sites have started to manually organize Web-accessible databases into Yahoo! -like hierarchical classification schemes. Here we introduce QProber, a modular system that automates this classification process by using a small number of query probes, generated by document classifiers. QProber can use a variety of types of classifiers to generate the probes. To classify a database, QProber does not retrieve or inspect any documents or pages from the database, but rather just exploits the number of matches that each query probe generates at the database in question. We have conducted an extensive experimental evaluation of QProber over collections of real documents, experimenting with different types of document classifiers and retrieval models. We have also tested our system with over one hundred Web-accessible databases. Our experiments show that our system has low overhead and achieves high classification accuracy across a variety of databases.
Performance Analysis of Location-Dependent Cache Invalidation Schemes for Mobile Environments

Mobile location-dependent information services are gaining increasing interest in both academic and industrial communities. In these services, data values depend on their locations. Caching frequently accessed data on mobile clients can help save wireless bandwidth and improve system performance. However, since client location changes constantly, location-dependent data may become obsolete not only due to updates performed on data items but also because of client movements across the network. To the best of the authors' knowledge, previous work on cache invalidation issues focused on data updates only. This paper considers data inconsistency caused by client movements and proposes three location-dependent cache invalidation schemes. The performance for the proposed schemes is investigated by both analytical study and simulation experiments in a scenario where temporal- and location-dependent updates coexist. Both analytical and experimental results show that, in most cases, the proposed methods substantially outperform the NSI scheme, which drops the entire cache contents when hand-off is performed.
Sketch of Big Data Real-Time Analytics Model

Big Data has drawn huge attention from researchers in information sciences, decision makers in governments and enterprises. However, there is a lot of potential and highly useful value hidden in the huge volume of data. Data is the new oil, but unlike oil data can be refined further to create even more value. Therefore, a new scientific paradigm is born as data-intensive scientific discovery, also known as Big Data. The growth volume of real-time data requires new techniques and technologies to discover insight value. In this paper we introduce the Big Data real-time analytics model as a new technique. We discuss and compare several Big Data technologies for real-time processing along with various challenges and issues in adapting Big Data. Real-time Big Data analysis based on cloud computing approach is our future research direction.
Workplace Mentoring: The Roles of Humor Style Agreement Humor Frequency and Positive Mentor Humor Style

The purpose of the current study was to investigate the roles of humor style agreement humor frequency and positive mentor humor style in workplace mentoring relationships. The author hypothesizes that the aforementioned humor variables contribute to mentoring satisfaction which subsequently affects four work-related outcomes including: (1) Job satisfaction (2) affective commitment (3) work stress and (4) turnover intentions. Path analysis was used to test a series of nine hypotheses in order to determine the fit of the hypothesized model (N = 54). The results of the path analysis revealed significantly positive path coefficients for all three humor variables on mentoring satisfaction (H1 H2 and H3) mentoring satisfaction on affective commitment and job satisfaction (H4 and H5) and job satisfaction on affective commitment (H6). Additionally the results revealed a significantly negative path coefficient for affective commitment on turnover intentions (H7). The remaining two hypothesized negative paths including job satisfaction on turnover intentions (H8) and work stress on job satisfaction (H9) were not statistically significant. Several fit indices were employed including RMSEA (0.00) SRMR (0.06) CFI (1.00) and TLI (1.01) which unanimously indicated excellent fit of the model with the data. The implications of the study include: (1) The precedent for humor variables as antecedents of mentoring satisfaction (2) the support for humor as an important work-related variable and (3) increased knowledge regarding the effectiveness of workplace mentoring.
Methodological Framework for Estimating the Correlation Dimension in HRV Signals

This paper presents a methodological framework for robust estimation of the correlation dimension in HRV signals. It includes (i) a fast algorithm for on-line computation of correlation sums; (ii) log-log curves fitting to a sigmoidal function for robust maximum slope estimation discarding the estimation according to fitting requirements; (iii) three different approaches for linear region slope estimation based on latter point; and (iv) exponential fitting for robust estimation of saturation level of slope series with increasing embedded dimension to finally obtain the correlation dimension estimate. Each approach for slope estimation leads to a correlation dimension estimate, called D^2, D^2⊥, and D^2max. D^2 and D^2max estimate the theoretical value of correlation dimension for the Lorenz attractor with relative error of 4%, and D^2⊥ with 1%. The three approaches are applied to HRV signals of pregnant women before spinal anesthesia for cesarean delivery in order to identify patients at risk for hypotension. D^2 keeps the 81% of accuracy previously described in the literature while D^2⊥ and D^2max approaches reach 91% of accuracy in the same database.
Tangible remote controllers for wall-size displays

We explore the use of customizable tangible remote controllers for interacting with wall-size displays. Such controllers are especially suited to visual exploration tasks where users need to move to see details of complex visualizations. In addition, we conducted a controlled user study suggesting that tangibles make it easier for users to focus on the visual display while they interact. We explain how to build such controllers using off-the-shelf touch tablets and describe a sample application that supports multiple dynamic queries.
Embedded Distributed Capacitive Tactile Sensor

A novel embedded distributed capacitive tactile sensor system designed to be installed on humanoid robots is presented. It provides pressure and shape information about the contacts with objects and the environment. The system is based on conformable mesh of sensors having triangular shape, interconnected in order to form a networked structure. Each triangle is a flexible substrate allowing the sensor to be conformed to smooth curved surfaces. It provides 12 capacitive measurements and it has three communications ports placed along its sides: one for the input from an adjacent triangle, and the others as outputs toward adjacent triangles. Each triangle is therefore a single sensor module implementing 12 taxels. The measurements are sent to microcontroller boards using serial bus communication links. A microcontroller board set-up and reads the data coming from a group of modules. Every microcontroller board has a CAN-bus link. The spatial resolution of the skin is one sensor every 5mm. The aim of the project is to install the artificial skin on the humanoid robot iCub, for studying control strategy using tactile feedback coming from the whole body, but it can be used for many other different mechatronic applications where distributed pressure information along a surface are required.
Preserving Differential Privacy for Similarity Measurement in Smart Environments

Advances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people's life and living styles. However, collecting and storing user's data in the smart environments pose severe privacy concerns because these data may contain sensitive information about the subject. Hence, privacy protection is now an emerging issue that we need to consider especially when data sharing is essential for analysis purpose. In this paper, we consider the case where two agents in the smart environment want to measure the similarity of their collected or stored data. We use similarity coefficient function (FSC) as the measurement metric for the comparison with differential privacy model. Unlike the existing solutions, our protocol can facilitate more than one request to compute FSC without modifying the protocol. Our solution ensures privacy protection for both the inputs and the computed FSC results.
Shrinking solid-state nanopores using electron-beam-induced deposition

Solid-state nanopores of only a few nanometres in size show a great potential for applications such as molecule detection and DNA sequencing. In most cases, the fabrication of such a nanopore requires the high energy beam of a transmission electron microscope (TEM) or focused ion beam (FIB) tool to drill or reshape a small hole in a freestanding membrane. Here, we present a novel method to reduce the size of existing nanopores using electron-beam-induced deposition (EBID) of carbon in a conventional scanning electron microscope (SEM). The existing nanopores are etched in a silicon membrane using anisotropic wet etching and can be shrunk down to a few nanometres using EBID. This paper discusses the parameters that influence the rate of shrinking and provides an insight into the underlying mechanism.
Neuronal Computations with Stochastic Network States

Neuronal networks in vivo are characterized by considerable spontaneous activity, which is highly complex and intrinsically generated by a combination of single-cell electrophysiological properties and recurrent circuits. As seen, for example, during waking compared with being asleep or under anesthesia, neuronal responsiveness differs, concomitant with the pattern of spontaneous brain activity. This pattern, which defines the state of the network, has a dramatic influence on how local networks are engaged by inputs and, therefore, on how information is represented. We review here experimental and theoretical evidence of the decisive role played by stochastic network states in sensory responsiveness with emphasis on activated states such as waking. From single cells to networks, experiments and computational models have addressed the relation between neuronal responsiveness and the complex spatiotemporal patterns of network activity. The understanding of the relation between network state dynamics and information representation is a major challenge that will require developing, in conjunction, specific experimental paradigms and theoretical frameworks.