Miracle-dz/UniFAR-FTUs huggingface dataset:
To Dollarize or De-Dollarize: Consequences for Monetary Policy

The aim of this paper is to review the experience of various dual-currency economies and analyze the main challenges faced by policymakers in formulating and conducting monetary policy. To that end, it distinguishes between countries with growing dollarization and those which have managed to revert such trend. In addition to the Asian countries of interest we look at a number of Latin American countries, Israel and Russia. All of this countries have experienced A¢â‚¬â€œ and in some cases still do A¢â‚¬â€œ a high degree of dollarization. Though there are several other countries within Central and Eastern Europe where a hard currency, i.e. the euro, is frequently used for financing and saving purposes, an important difference of this region and the ASEAN countries in transition, is that the latter are nowhere close to adopting the dollar as an official currency or to enter a monetary union. Israel is chosen as a case study, because it is one of the few countries in the world that were highly dollarized, and could succesfully dedollarize. Also Russia, has been trying to de-dollarize in the last couple of years. However, as we will discuss below they did not manage to lower the deposit dollarization ratio on a sustained basis.
Sampling urban mobility through on-line repositories of GPS tracks

We analyze urban mobility by relying on the short-term mobility traces gathered from a publicly available web-based repository of GPS tracks - the Nokia Sports Tracker service. All mobility traces are obtained from a set of kml files. We show how the data collected voluntarily by individuals, equipped with GPS-enabled mobile phones, can be used to infer accurate, large-scale footprint of urban mobility. This method, unlike others - for example, personal interviewing, is more scalable and less time consuming. It exploits the fact that the on-line masses are willing to share their experience with others. We present a set of heuristics used to filter out bogus tracks from the dataset. We show that the mobility patterns, inferred from the remaining, credible, short-term mobility traces have macroscopic characteristics similar to the characteristics of mobility patterns retrieved from the long-term mobility traces, gathered in different urban environments. The results of our analysis lead to a proposal for creating city-specific mobility profiles. We discuss how such profiles could help improve location privacy and help develop new context-aware applications and services for mobile users.
Controlling on-line adaptation of a prototype-based classifier for handwritten characters

Methods for controlling the adaptation process of an online handwritten character recognizer are studied. The classifier is based on the k-nearest neighbor rule and it is adapted to a new writing style by adding new prototypes, deactivating confusing prototypes, and reshaping existing prototypes in a self-supervised fashion. The dissimilarity measure used for the comparison of characters is a nonlinear curve matching method base on dynamic time warping algorithm. Time needed for the evaluation of the dissimilarity measure for a single character depends linearly on the size of the prototype set. The purpose of the control methods is to increase the classifier's tolerance to malformed or mislabelled learning samples and to limit the growth of the prototype set. The control methods either set an upper limit for the number of prototypes per class or switch the adaptation of a particular character class on or off depending on the earlier performance of the classifier.
ADAPTIVE NEURAL CONTROL OF NPR

Controller adaptation is always a major concern. A controller that meets certain performance design objectives can not be satisfactory unless it can preserve such quality in the presence of system parameters fluctuation. For the nuclear power reactors (NPR) a controller that preserves stability and performance for wide range of operation conditions and fluctuations is especially desirable. This paper presents a design of an adaptive controller using artificial neural networks (ANN) to infinite impulse response IIR model of NPR. The objective is to maintain the stability and robustness of the overall control system against the fluctuation of system parameters during different operation conditions. The adaptive neural controller is systematic, methodical, easy to design, and can give improved system performance over wide range of NPR operation conditions.
Designing generic/reusable functionality based controllers for distributed control using UML

Functionality based control is an approach that improves the quality of the design process in distributed controlled systems (DCSs) by combining object-oriented concepts with re-configurability on function level. The basic functions are implemented in function blocks and then the overall functionality is derived by the use of a supervising scheduler. This paper presents an approach to model the basic functionalities in manufacturing systems using Unified Modeling Language (UML). A transformation of the UML description into an IEC 61499 compliant format is given. The approach is illustrated using the functionality based control (FBC) of a laboratory plant
Autophagy Inhibition Augments the Anticancer Effects of Epirubicin Treatment in Anthracycline-Sensitive and -Resistant Triple-Negative Breast Cancer

Purpose: Triple-negative breast cancers (TNBC) are defined by a lack of expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (ERBB2/HER2). Although initially responsive to chemotherapy, most recurrent TNBCs develop resistance, resulting in disease progression. Autophagy is a lysosome-mediated degradation and recycling process that can function as an adaptive survival response during chemotherapy and contribute to chemoresistance. Our goal was to determine whether autophagy inhibition improves treatment efficacy in TNBC cells in tumors either sensitive or refractory to anthracyclines. Experimental Design: We used in vitro and in vivo models of TNBC using cell lines sensitive to epirubicin and other anthracyclines, as well as derivative lines, resistant to the same drugs. We assessed basal autophagy levels and the effects of chemotherapy on autophagy in parental and resistant cells. Applying various approaches to inhibit autophagy alone and in combination with chemotherapy, we assessed the effects on cell viability in vitro and tumor growth rates in vivo. Results: We demonstrated that epirubicin induced autophagic flux in TNBC cells. Epirubicin-resistant lines exhibited at least 1.5-fold increased basal autophagy levels and, when treated with autophagy inhibitors, showed a significant loss in viability, indicating dependence of resistant cells on autophagy for survival. Combination of epirubicin with the autophagy inhibitor hydroxychloroquine resulted in a significant reduction in tumor growth compared with monotherapy with epirubicin. Conclusion: Autophagy inhibition enhances therapeutic response in both anthracycline-sensitive and -resistant TNBC and may be an effective new treatment strategy for this disease. Clin Cancer Res; 20(12); 3159–73. ©2014 AACR.
Error Modeling in the ACT-R Production System

We describe how to extend the ACT-R production system to model human errors in the performance of a high-level cognitive task: to solve simple linear algebra problems while memorizing a digit span. Errors of omission are produced by introducing a cutoff on the latency of memory retrievals. If a memory chunk cannot gather enough activation to be retrieved before the threshold i s reached, retrieval fails. Adding Gaussian noise to chunk activation produces a pattern quantitatively similar to subject errors. Errors of commission are introduced by allowing imperfect matching in the condition side of productions. The wrong memory chunk can be retrieved if its activation is large enough to allow it to overcome the mismatch penalty. This mechanism provides a qualitative and quantitative fit to subject errors. In conclusion, this paper demonstrates that human-like errors, sometimes thought of as the exclusive domain of connectionist models, can be successfully duplicated in production system models.
A 3-D Table-Based Method for Non-Quasi-Static Microwave FET Devices Modeling

A highly accurate method of building a large-signal modeling approach considering dispersive effect of field-effect transistors is presented in this paper. The non-quasi-static effect of the transistor is described through high-order constitutive nonlinear current sources and charge sources. The extraction and building of these sources are executed by polynomial regression, which is fast and determined by unique values. The sources are built by 3-D tables, where the added dimension is a variable integration path used to account for the dispersion effect. The performance up to the millimeter-wave frequency of the model is satisfied. The validity of the proposed technology-independent approach has been verified by both GaAs and GaN devices.
Research on modeling method of water displacing oil physical simulation based on support vector machine

An actual physical simulation model was constructed to simulate the course of water displacing oil Under certain physical property parameter conditions, we simulated the water injection well and the oil withdrawal well on the physical simulation model, and continuous measured online the oil and water content of different areas of physical simulation model in three-dimensional spaces using the 512 routes resistivity measuring circuit, then we can obtain large numbers of simulation samples. Considering the issues that the relationship between the remaining oil and every parameters of water displacing oil is complicated and nonlinear, the support vector machine (SVM) was used to establish the water displacing remaining oil model, in order to obtain the distributing situation of remaining oil in various complicated conditions. We proposed a self-adaptive parameter adjust iterative algorithm to confirm SVM parameters. The experimental results show that this method is feasible and effective.
Weighted sum rate maximization in the underlay cognitive MISO Interference Channel

In this paper we address the problem of Weighted Sum Rate (WSR) maximization for a K-user Multiple-Input Single-Output (MISO) cognitive Interference Channel (IFC) with linear transmit beamforming (BF) vectors in an underlay cognitive radio setting. We consider a set of L single-antenna Primary receivers to which the cognitive system can causes a limited amount of interference. We thus propose an iterative algorithm to determine the BF vectors for the secondary transmission. The optimization of the Lagrange multipliers involved in the optimization problem is based on the subgradient method. The expression of the BF vector can be interpreted as dual Uplink (UL) MMSE receiver that takes into account the interference caused by a fictitious link between the primary user and secondary base station. Finally Deterministic Annealing is applied to make the convergence of the algorithm easier.
Automatic detection of vocal fold paralysis and edema

In this paper we propose a combined scheme of linear prediction analysis for feature extraction along with linear projection methods for feature reduction followed by known pattern recognition methods on the purpose of discriminating between normal and pathological voice samples. Two different cases of speech under vocal fold pathology are examined: vocal fold paralysis and vocal fold edema. Three known classifiers are tested and compared in both cases, namely the Fisher linear discriminant, the -nearest neighbor classifier, and the nearest mean classifier. The performance of each classifier is evaluated in terms of the probabilities of false alarm and detection or the receiver operating characteristic. The datasets used are part of a database of disordered speech developed by Massachusetts Eye and Ear Infirmary. The experimental results indicate that vocal fold paralysis and edema can easily be detected by any of the aforementioned classifiers.
Trio, a Rho Family GEF, Interacts with the Presynaptic Active Zone Proteins Piccolo and Bassoon

Synaptic vesicles (SVs) fuse with the plasma membrane at a precise location called the presynaptic active zone (AZ). This fusion is coordinated by proteins embedded within a cytoskeletal matrix assembled at the AZ (CAZ). In the present study, we have identified a novel binding partner for the CAZ proteins Piccolo and Bassoon. This interacting protein, Trio, is a member of the Dbl family of guanine nucleotide exchange factors (GEFs) known to regulate the dynamic assembly of actin and growth factor dependent axon guidance and synaptic growth. Trio was found to interact with the C-terminal PBH 9/10 domains of Piccolo and Bassoon via its own N-terminal Spectrin repeats, a domain that is also critical for its localization to the CAZ. Moreover, our data suggest that regions within the C-terminus of Trio negatively regulate its interactions with Piccolo/Bassoon. These findings provide a mechanism for the presynaptic targeting of Trio and support a model in which Piccolo and Bassoon play a role in regulating neurotransmission through interactions with proteins, including Trio, that modulate the dynamic assembly of F-actin during cycles of synaptic vesicle exo- and endocytosis.
Ray tracing with cones

A new approach to ray tracing is introduced. The definition of a “ray” is extended into a cone by including information on the spread angle and the virtual origin. The advantages of this approach, which tries to model light propagation with more fidelity, include a better method of anti-aliasing, a way of calculating fuzzy shadows and dull reflections, a method of calculating the correct level of detail in a procedural model and texture map, and finally, a procedure for faster intersection calculation.
Integrity = validity + completeness

Database integrity has two complementary components: validity, which guarantees that all false information is excluded from the database, and completeness, which guarantees that all true information is included in the database. This article describes a uniform model of integrity for relational databases, that considers both validity and completeness. To a large degree, this model subsumes the prevailing model of integrity (i.e., integrity constraints). One of the features of the new model is the determination of the integrity of answers issued by the database system in response to user queries. To users, answers that are accompanied with such detailed certifications of their integrity are more meaningful. First, the model is defined and discussed. Then, a specific mechanism is described that implements this model. With this mechanism, the determination of the integrity of an answer is a process analogous to the determination of the answer itself.
A new method for measuring the imaginary part of the atmospheric refractive index structure parameter in the urban surface layer

Abstract. The atmospheric refractive index consists of both real and imaginary parts. The intensity of refractive index fluctuations is generally expressed as the refractive index structure parameter, with the real part reflecting the strength of atmospheric turbulence and the imaginary part reflecting absorption in the light path. A large aperture scintillometer (LAS) is often used to measure the structure parameter of the real part of the atmospheric refractive index, from which the sensible and latent heat fluxes can further be obtained, whereas the influence of the imaginary part is ignored or considered noise. In this theoretical analysis study, the relationship between logarithmic light intensity variance and the atmospheric refractive index structure parameter (ARISP), as well as that between the logarithmic light intensity structure function and the ARISP, is derived. Additionally, a simple expression for the imaginary part of the ARISP is obtained which can be conveniently used to determine the imaginary part of the ARISP from LAS measurements. Moreover, these relationships provide a new method for estimating the outer scale of turbulence. Light propagation experiments were performed in the urban surface layer, from which the imaginary part of the ARISP was calculated. The experimental results showed good agreement with the presented theory. The results also suggest that the imaginary part of the ARISP exhibits a different diurnal variation from that of the real part. For the wavelength of light used (0.62 μm), the variation of the imaginary part of the ARISP is related to both the turbulent transport process and the spatial distribution characteristics of aerosols.
Non-speech input and speech recognition for real-time control of computer games

This paper reports a comparison of user performance (time and accuracy) when controlling a popular arcade game of Tetris using speech recognition or non-speech (humming) input techniques. The preliminary qualitative study with seven participants shows that users were able to control the game using both methods but required more training and feedback for the humming control. The revised interface, which implemented these requirements, was positively responded by users. The quantitative test with 12 other participants shows that humming excelled in both time and accuracy, especially over longer distances and advanced difficulty levels.
Effects of Position and Time Bias on Understanding Onsite Users' Behavior

The existence of different biases in logged users' behavior makes it difficult to extract realistic topical and social information from users' interaction logs (e.g., query logs). To understand users' behavior and their interests in the cultural heritage domain, we have logged onsite user interaction logs of visits in a museum. This prompts the question on the reliability of the social information being gathered from the onsite logs: How does the position of museum objects affect users' behavior in the museum? How does order of visiting point of interests affect their dwell-time in front of each point of interest? How do different users' characteristics affect their behavior in the museum? In short, what are different kinds of biases that should be considered in the onsite logs? Our main findings are the following: First, there is a considerable position bias, which is due to the design of the exhibition and should be considered during extraction of social signals from the log. Second, there is a bias in the amount of time that users spend for interacting with the point of interests and the order of picking them to visit. This shows a fatigue on users' interactions while they are reaching to the end of the exhibition. Third, we find out some variations among the users' visit, which shows context is an important factor to consider while using onsite logs for different purposes.
Evaluation of Anti-Toxoplasma IgG, IgM, and IgA in Mothers with Spontaneous Abortion in Zanjan, Northwest Iran

Toxoplasma gondii is one of the major agents of infectious abortions and due to its worldwide distribution can threat healthy pregnant women who had no previous exposure to this parasite. The present study was designed to investigate the contribution of T. gondii to spontaneous abortions in Zanjan, Northwest of Iran, using ELISA method. Blood Samples were collected from 264 mothers referred to the provincial hospitals of Zanjan due to spontaneous abortion. The sera were isolated and subjected to evaluate the anti-Toxoplasma IgG, IgM and IgA antibodies. The results showed IgG positive (IgG+) in 99 cases (37.5%). A total of 68 women (25.8%) showed seroconversion with IgM or IgA or both IgM and IgA. They included: IgM+ in 21 (8.0%), IgA+ in 23 (8.7%) and both IgM+ and IgA+ in 24 (9.1%) subjects. In 23 cases, positive titers of IgM and IgG were accompanied. In general, the analysis of anti-Toxoplasma antibody patterns, showed that about 17% of the spontaneous abortions were associated with serological patterns of acute infection. According to these findings, a considerable proportion of spontaneous abortions can be attributed to T. gondii in the study area.
Towards creating a GPGPU-accelerated framework for pattern matching

Model-driven engineering (MDE) is a popular software development methodology in the software industry. Finding a predefined pattern in a domain-specific model can be requested in MDE. This technique can help in optimizing or refactoring the models or to translate from one language to another one. The goal of the current researching is to create a framework for MDE which can find patterns defined by the users. Performance is a key issue. Using heterogeneous computation system (e.g.: CPU+GPU) is a promising way to increase the performance of the calculation. Therefore, we created a solution based on the OpenCL framework which is one of the most popular heterogeneous platforms. In this paper, the new pattern matching framework and the main steps of its creation are presented. The applied conception consists of two main steps. Firstly, a simpler case study is solved and experiences are collected from the occurring challenges. Secondly, the achieved solution was extended for general pattern matching. In both steps, the core algorithms are implemented according to the test-driven development methodology. To elaborate these steps, a new technique is provided which can be useful in creating any GPU-based model transformation and thus MDE approaches are improved in general.
Population-Based Norms for the Korean Mini-Mental State Examination and Korean version of modified Mini-Mental State Examination

Background: Cognitive functioning was known to be affected by socioeconomic conditions including ethnicity. The Korean Mini-Mental State Examination (K-MMSE) and the Korean version of the modified Mini-Mental State Examination (K-modified MMSE; K-mMMSE) scores by age, gender, and educational levels were evaluated. Methods: Screening interviews were conducted with 2251 men and 3267 women aged 45 and over in 3 communities (Namwon-city of Chonbuk province, Younggwang-gun of Chonnam province). Descriptive performances (means, medians and percentile ranks) were calculated to summarize the range of normal performance. Scatterplots of the K-mMMSE scores according to age or educational attainments were performed. Results: Lower age, higher education, and male gender were associated with higher scores of the K-MMSE and K-mMMSE. In women, more than half (50.6%) had no formal education and 546 women (16.7%) were illiterate. In men, the K-MMSE and K-mMMSE median scores ranged from 27 and 88 for individuals aged from 45 to 49 years old, to 25 and 76 for those aged 70 years and over. In women, the K-MMSE and the K-mMMSE median scores ranged from 17 and 53 for illiterate women, to 28 and 90 for women with more than 10 years of education. Conclusions: The use of the reference values will allow the clinician to interpret a patients performance on the K-MMSE and K-mMMSE, in light of the value expected from a group of normal subjects with the same sociodemographic profile. J Korean Neurol Assoc 25(1):1-9, 2007
Subsampling conflicts to construct better fuzzy rules

Many fuzzy rule induction algorithms have been proposed during the past decade or so. Most of these algorithms tend to scale badly with large dimensions of the feature space, because the underlying heuristics tend to constrain suboptimal features. Often, noisy training instances also influence the size of the resulting rule set. In this paper, an algorithm is discussed that extracts a set of so-called mixed fuzzy rules. These rules can be extracted from feature spaces with diverse types of attributes and handle the corresponding different types of constraints in parallel. The underlying heuristic minimizes the loss of coverage for each rule when a conflict occurs. We present the original algorithm, which avoids conflicts for each pattern individually, and demonstrate how a subsampling strategy improves the resulting rule set, both with respect to performance and the interpretability of the resulting rules.