Miracle-dz/UniFAR-FTUs huggingface dataset:
North-South and South-South Trade-Related Technology Diffusion: An Industry-Level Analysis of Direct and Indirect Effects

This Paper examines the impact on TFP of North-South and South-South trade-related RD and ii) R&D-intensive industries benefit mainly from North-South R&D flows while low R&D-intensity industries benefit mainly from South-South R&D flows. These results have implications for the productivity dynamics of North-South and South-South regional integration.
Fabrication of metallic nanowires and nanoribbons using laser interference lithography and shadow lithography

Ordered and free-standing metallic nanowires were fabricated by e-beam deposition on patterned polymer templates made by interference lithography. The dimensions of the nanowires can be controlled through adjustment of deposition conditions and polymer templates. Grain size, polarized optical transmission and electrical resistivity were measured with ordered and free-standing nanowires.
An adaptive user interface based on Spatiotemporal Structure Learning

We developed a user interface prototype for the Android smartphone which recommends a number of applications to best match the user's context. To consider the user's context of use, we utilized 5 prototypical variables; time, location, weather, emotion, and activities. The developed system derives the best three recommended applications based on the results of supervised learning from such data sets. To consider the history of past context information, in addition to the current one, we developed a novel and effective probabilistic learning and inference algorithm named “Spatiotemporal Structure Learning”. By extending Naïve Bayesian Classifier, the spatiotemporal structure learning can create a probability model which represents relationship between time-series contextual variables. We implemented a prototype system which shows the current context and the inferred recommendation of applications. For the prototype system, we developed an Android widget application for the user interface and a Java-based server application which learns structure from training data and provides inference results in real-time. To gather training data and evaluate proposed system, we conducted a pilot study which showed 69% of accuracy in predicting the user's application usage. The prototype demonstrated the feasibility of an adaptive user interface applied to a state of the art smartphone. We also believe that the suggested spatiotemporal structure learning can be applied to number of application areas including healthcare or energy problems.
Harmonic elimination in a five level multilevel inverter

Multilevel inverters are popular for renewable energy applications. This paper presents a technique for harmonic elimination in a five level cascaded H-Bridge multilevel inverter. The technique is based on computation of switching angles using Chebyshev polynomials. The method involves simple mathematical calculations to arrive at the desired switching angles for harmonic elimination. In this paper, Chebyshev polynomials are utilized to calculate the switching angles for eliminating the 3rd and 5th harmonic in a five level multilevel inverter system for a modulation index of 0.8. The work evaluates the reduction in the total harmonic distortion of the five level inverter system by eliminating specific harmonic from the multilevel inverter system. Further, a comparison is established to evaluate the power quality of a selective harmonic eliminated system with a conventional five level multi carrier based pulse width modulated inverter. MATLAB-SIMULINK environment is used to verify the simulation results.
Peptide Receptor Subtypes Recent Developments in Our Understanding of the Physiological Role of PP-Fold 2003

Experimental Biology and Medicine Magnus M. Berglund, Philip A. Hipskind and Donald R. Gehlert Peptide Receptor Subtypes Recent Developments in Our Understanding of the Physiological Role of PP-Fold 2003, 228:217-244. Experimental Biology and Medicine http://ebm.rsmjournals. com/content/228/3/217 Updated information and services can be found at: http://ebm.rsmjournals. com/content/228/3/217#BIBL This article cites 309 articles, 77 of which can be accessed free at: http://ebm.rsmjournals. com/content/228/3/217#otherarticles 30 online articles that cite this articles can be accessed at:
Consistent Approximations of Some Geometric Di ff erential Operators and Their Convergences

The numerical integration of many geometric partial differential equations involves discrete approximations of several firstand second-order geometric differential operators. In this paper, we consider consistent discretized approximations of these operators based on a quadratic fitting scheme. An asymptotic error analysis is conducted which shows that the discrete approximations of the firstand second-order geometric differential operators have the quadratic and linear convergence rates, respectively.
β-Elemene enhances susceptibility to cisplatin in resistant ovarian carcinoma cells via downregulation of ERCC-1 and XIAP and inactivation of JNK

β-Elemene is a promising new plant-derived drug with broad-spectrum anticancer activity. It also increases cisplatin cytotoxicity and enhances cisplatin sensitivity in resistant human carcinoma cells. However, little is known about the mechanism of its action. To explore the potential therapeutic application of β-elemene as a drug-resistance modulator, this study investigated the underlying mechanism of β-elemene activity in cisplatin-resistant ovarian cancer cells. β-Elemene enhanced cisplatin sensitivity to a much greater extent in chemoresistant A2780/CP70 and MCAS human ovarian carcinoma cells compared to the chemosensitive parental cell line A2780. The dose-modifying factors for cisplatin were between 35 and 60 for A2780/CP70 cells and between 1.6 and 2.5 for A2780 cells. In the cisplatin-resistant ovarian carcinoma cells, β-elemene abrogated cisplatin-induced expression of excision repair cross-complementation group-1 (ERCC-1), a marker gene in the nucleotide excision repair pathway that repairs cisplatin-caused DNA damage. In addition, β-elemene not only reduced the level of X-linked inhibitor of apoptosis protein (XIAP), but also downregulated cisplatin-mediated XIAP expression in chemoresistant cells. Furthermore, β-elemene blocked the cisplatin-stimulated increase in the level of phosphorylated c-Jun NH2-terminal kinase (JNK) in these cells. These novel findings suggest that the β-elemene enhancement of cisplatin sensitivity in human chemoresistant ovarian cancer cells is mediated at least in part through the impairment of DNA repair activity and the activation of apoptotic signaling pathways, thereby making resistant ovarian cancer cells susceptible to cisplatin-induced cell death.
Electron re-scattering from H2 and CO2 using R-matrix techniques

The R-matrix method is being used to investigate electron (re-)scattering for the H2 and CO2 systems. This is being done computationally using the UK molecular R-matrix package. The similarity of re-scattering to electron–molecule scattering off the associated cations at geometries near to those of the neutral molecules forms the basis of our initial model. Preliminary cross-sections and eigenphase sums have been calculated for molecular hydrogen and carbon dioxide. These show highly resonant behaviour in the energy range studied and this is particularly pronounced as channel thresholds are approached. The initial results suggest that inclusion of resonance phenomena could be vital for interpretation of electron re-scattering experiments. Elastic differential cross-sections for symmetries relevant to experiments performed using linear polarization are also presented and prospects for a more realistic model are discussed.
Hubble Space Telescope STIS Ultraviolet Spectral Evidence of Outflow in Extreme Narrow-Line Seyfert 1 Galaxies. I. Data and Analysis

We present Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph observations of two extreme narrow-line Seyfert 1 galaxies (NLS1's), IRAS 13224-3809 and 1H 0707-495. The spectra are characterized by very blue continua; broad, strongly blueshifted high-ionization lines (including C IV and N V); and narrow, symmetric intermediate- (including C III], Si III], and Al III) and low-ionization (e.g., Mg II) lines centered at the rest wavelength. The emission-line profiles suggest that the high-ionization lines are produced in a wind and that the intermediate- and low-ionization lines are produced in low-velocity gas associated with the accretion disk or base of the wind. In this paper, we present the analysis of the spectra from these two objects; in a companion paper, we present photoionization analysis and a toy dynamical model for the wind. The highly asymmetric profile of C IV suggests that it is dominated by emission from the wind, so we develop a template for the wind from the C IV line. We model the bright emission lines in the spectra using a combination of this template and a narrow symmetric line centered at the rest wavelength. We also analyzed a comparison sample of Hubble Space Telescope spectra from 14 additional NLS1's and constructed a correlation matrix of emission-line and continuum properties. A number of strong correlations were observed, including several involving the asymmetry of the C IV line.
Bipartite Editing Prediction in Wikipedia

Link prediction problems aim to project future interactions among members in a social network that have not communicated with each other in the past. Classical approaches for link prediction usually use local information, which considers the similarity of two nodes, or structural information such as the immediate neighborhood. However, when using a bipartite graph to represent activity, there is no straightforward similarity measurement between two linking nodes. However, when a bipartite graph shows two nodes of different types, they will not have any common neighbors, so the local model will need to be adjusted if the users' goal is to predict bipartite relations. In addition to local information regarding similarity, when dealing with link predictions in a social network, it is natural to employ community information to improve the prediction accuracy. In this paper, we address the link prediction problem in the bipartite editing graph used in Wikipedia and also examine the structure of community in this edit graph. As Wikipedia is one of the successful member-maintained online communities, extracting the community information and solving its bipartite link prediction problem will shed light on the process of content creation. In addition, to the best of our knowledge, the problem of using community information in bipartite for predicting the link occurrence has not been clearly addressed. Hence we have designed and integrated two bipartite-specific approaches to predict the link occurrence: First, the supervised learning approach, which is built around the adjusted features of a local model and, second, the community-awareness approach, which utilizes community information. Experiments conducted on the Wikipedia collection show that in terms of F1-measure, our approaches generates an 11% improvement over the general methods based on the K-Nearest Neighbor. In addition to this, we also investigate the structure of communities in the editing network and suggest a different approach to examining the communities involved in Wikipedia.
X-ray wakes in Abell 160

‘Wakes’ of X-ray emission have now been detected trailing behind a few (at least seven) elliptical galaxies in clusters. To quantify how widespread this phenomenon is, and what its nature might be, we have obtained a deep (70 ks) X-ray image of the poor cluster Abell 160 using the ROSAT HRI. Combining the X-ray data with optical positions of confirmed cluster members, and applying a statistic designed to search for wake-like excesses, we confirm that this phenomenon is observed in galaxies in this cluster. The probability that the detections arise from chance is less than 3.8×10−3. Further, the wakes are not randomly distributed in direction, but are preferentially oriented pointing away from the cluster centre. This arrangement can be explained by a simple model in which wakes arise from the stripping of the interstellar media of their host galaxies as a result of ram pressure against the intracluster medium through which they travel.
Concurrent distinct choices

An injective finite mapping is an abstraction common to many programs. We describe the design of an injective finite mapping and its implementation in Curry, a functional logic language. Curry supports the concurrent asynchronous execution of distinct portions of a program. This condition prevents passing from one portion to another a structure containing a partially constructed mapping to ensure that a new choice does not violate the injectivity condition. We present some motivating problems and we show fragments of programs that solve these problems using our design and implementation.
Exploring the concept of legitimacy in a transition economy : The case of the Swedish banking industry in Latvia

This thesis examines the concept of legitimacy and its evolution over time in the context of the banking sector of the transition economy of Latvia, where Swedish banks are the dominant player. After an economic boom starting at the turn of the millennia, which was to a great extent financed by the Swedish banks, the Latvian economy has now completely turned around, in the wake of numerous unanswered signs of overheating and the global economic crisis. Although they acted within legal limits, the Swedish banks and their behavior have become the object of criticism in Latvia as well as in Sweden. To study the evolution of the legitimacy granted by their stakeholders, we make use of Suchman's legitimacy theory and rely on a mix of interviews and secondary data to obtain an overview of the events that occurred and understand what the public opinion is regarding these. We then propose an empirical framework to define the aspects of legitimacy that have been damaged, before suggesting strategies to repair it. Our main conclusions are that cognitive and moral legitimacy are the types that were harmed the most, although some ways exist to repair this damage. The results also show that the processes of legitimation are somewhat different in the case of a transition economy, but that the general public's expectations from the banking sector remain similar to that of Western countries. Furthermore, it seems pointless to try to seek a scapegoat for what went wrong; instead, it would be more useful to look for means to prevent this type of events from repeating in the future.
Open Modules : Modular Reasoning in Aspect-Oriented Programming

Aspect-oriented programming (AOP) is a new programming paradigm whose goal is to more cleanly modularize crosscutting concerns such as logging, synchronization, and event notification which would otherwise be scattered throughout the system and tangled with functional code. However, while AOP languages provide promising ways to separate crosscutting concerns, they can also break conventional encapsulation mechanisms, making it difficult to reason about code without the aid of external tools. We investigate modular reasoning in the presence of aspects through TinyAspect, a small functional language that directly models aspect-oriented programming constructs. We define Open Modules, a module system for TinyAspect that enforces Reynolds’ abstraction theorem, a strong encapsulation property. Open Modules are “open” in that external aspects can advise functions and pointcuts in their interface, providing significant aspect-oriented expressiveness that is missing in non-AOP systems. In order to guarantee modular reasoning, however, our system places limits on advice: external aspects may not advise function calls internal to a module, except for calls explicitly exposed through pointcuts in the module’s interface. The abstraction property of our system ensures that a module’s implementation can be changed without affecting clients, and provides insight into formal reasoning, modular analysis, and tool support for aspect-oriented programming. 1
Using a hybrid approach for the development of an ontology in the hydrographical domain

This work presents a hybrid approach for domain ontology development, which merges top-down and bottom-up techniques. In the topdown approach the concepts in the ontology are derived from an analysis and study of relevant information sources about the domain (e.g., hydrographic features). In the bottom-up approach the concepts in the ontology are the result of applying formal methods on a analysis of the data instances on the repositories (e.g., repositories containing hydrographical features)
Belief Formation and Evolution in Public Good Games.

We analyze first-order beliefs in a variation of the Public Good Game. We show that (1) the role that belief elicitation plays in the experiment affects both the contribution behavior and beliefs, and (2) framing influences stated beliefs, as much as contribution behavior. In the second part of the paper, we study the role of heterogeneity in the formation of initial beliefs, and provide an empirical model of the belief up-dating process. Subjects use the past experience, stressing the role of experience that comes from situations similar to the current ones.
A Model of DENV-3 Infection That Recapitulates Severe Disease and Highlights the Importance of IFN-γ in Host Resistance to Infection

There are few animal models of dengue infection, especially in immunocompetent mice. Here, we describe alterations found in adult immunocompetent mice inoculated with an adapted Dengue virus (DENV-3) strain. Infection of mice with the adapted DENV-3 caused inoculum-dependent lethality that was preceded by several hematological and biochemical changes and increased virus dissemination, features consistent with severe disease manifestation in humans. IFN-γ expression increased after DENV-3 infection of WT mice and this was preceded by increase in expression of IL-12 and IL-18. In DENV-3-inoculated IFN-γ−/− mice, there was enhanced lethality, which was preceded by severe disease manifestation and virus replication. Lack of IFN-γ production was associated with diminished NO-synthase 2 (NOS2) expression and higher susceptibility of NOS2−/− mice to DENV-3 infection. Therefore, mechanisms of protection to DENV-3 infection rely on IFN-γ-NOS2-NO-dependent control of viral replication and of disease severity, a pathway showed to be relevant for resistance to DENV infection in other experimental and clinical settings. Thus, the model of DENV-3 infection in immunocompetent mice described here represents a significant advance in animal models of severe dengue disease and may provide an important tool to the elucidation of immunopathogenesis of disease and of protective mechanisms associated with infection.
Memristor Crossbar Architecture for Synchronous Neural Networks

This paper focuses on suitable architecture and neural network training using crossbar connections of memristive elements. We developed a novel memristor training scheme that preserves high density of synaptic connections in the crossbar organization. We designed supporting circuits and performed time domain analog simulation of the architecture, to demonstrate that it properly adjusts memristor values during neural network training. A single sensing and winner-takes-all circuit is used to adjust strength of synaptic connections implemented by all memristors. We present results of HSPICE simulation of the developed architecture, generated control signals and resulting changes of memristor values. We used crosstalk test and Monte Carlo analysis to demonstrate robustness of the proposed architecture. Tests performed on MNIST character recognition benchmark confirmed functionality of the proposed circuit and training scheme in a practical and demanding application. The proposed approach improves available in the literature architecture and training methods for memristive neural networks.
Developing a part-of-speech tagger for Dutch tweets

In this article we describe the design and creation of a part-of-speech tagger specifically for Dutch data from the popular microblogging service Twitter. Starting from the D-Coi part-of-speech tag set, which is also used in the SoNaR project, we added several Twitter-specific tags to allow the tagging of hashtags, @ mentions, emoticons and URLs. The tagger consists of the Frog tagger combined with a post-processing module that incorporates the new, Twitter-specific tags in the Frog part-of-speech output. Running the Frog tagger and the post-processing module sequentially leads to a part-of-speech tagger for Dutch tweets. Approximately 1 million tweets collected in the context of the SoNaR project were tagged by Frog and the post-processor combined. A sub-set of annotated tweets have been manually checked. Lastly, we evaluated the adapted part-of-speech tagger. This project was accomplished by eight Master’s students from Tilburg University, who had just completed a course in natural language processing. In addition to the theoretical knowledge they acquired during the course, this project, which took approximately a week, offered them hands-on experience.
Design and implementation of a mobile system for lung cancer patient follow-up in China and initial report of the ongoing patient registry

Introduction Management of lung cancer remains a challenge. Although clinical and biological patient data are crucial for cancer research, these data may be missing from registries and clinical trials. Biobanks provide a source of high-quality biological material for clinical research; however, linking these samples to the corresponding patient and clinical data is technically challenging. We describe the mobile Lung Cancer Care system (mLCCare), a novel tool which integrates biological and clinical patient data into a single resource. Methods mLCCare was developed as a mobile device application (app) and an internet website. Data storage is hosted on cloud servers, with the mobile app and website acting as a front-end to the system. mLCCare also facilitates communication with patients to remind them to take their medication and attend follow-up appointments. Results Between January 2014 and October 2015, 5,080 patients with lung cancer have been registered with mLCCare. Data validation ensures all the patient information is of consistently high-quality. Patient cohorts can be constructed via user-specified criteria and data exported for statistical analysis by authorized investigators and collaborators. mLCCare forms the basis of establishing an ongoing lung cancer registry and could form the basis of a high-quality multisite patient registry. Integration of mLCCare with SMS messaging and WeChat functionality facilitates communication between physicians and patients. Conclusion It is hoped that mLCCare will prove to be a powerful and widely used tool that will enhance both research and clinical practice.
Nonparametric Estimation of Risk-Neutral Densities

This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk neutral density. The first estimator is a kernel smoother of the second derivative of call prices, while the second procedure applies kernel type smoothing in the implied volatility domain. In the conceptually different third approach we assume the existence of a stochastic discount factor (pricing kernel) which establishes the risk neutral density conditional on the physical measure of the underlying asset. Via direct series type estimation of the pricing kernel we can derive an estimate of the risk neutral density by solving a constrained optimization problem. The methods are compared using European call option prices. The focus of the presentation is on practical aspects such as appropriate choice of smoothing parameters in order to facilitate the application of the techniques.