Miracle-dz/UniFAR-FTUs huggingface dataset:
[Developing Japanese version of the eHealth Literacy Scale (eHEALS)].

OBJECTIVES With the rapid developing an internet society, ehealth literacy, defined as the ability to seek, find, understand, and appraise and apply the knowledge gained to addressing or solving a health problem, becomes important to promote and aid health care at the individual level. However, the eHealth Literacy Scale (eHEALS) was only a scale developed to assess the ehealth literacy. Thus, the present study was conducted to evaluated the validity and reliability of a Japanese version of the eHEALS (J-eHEALS), and examine the association of ehealth literacy with demographic attributes and characteristics on health information searching among Japanese adults. METHODS Data were analyzed for 3,000 Japanese adults (males: 50.0%,mean age: 39.6 + 10.9 years) who responded to an Internet-based cross-sectional survey. The J-eHEALS, 6 demographic attributes, resources for obtaining health information (health resources), and contents of health information obtained from internet (ehealth contents) were obtained with a questionnaire. Confirmatory factor analysis and correlation with the communicative and critical health literacy scale were utilized to assess construct validity and criterion validity. Cronbach alpha and correlation coefficients were computed for internal consistency and test-retest reliability. Also, differences in J-eHEALS scores with each demographic attribute were examined with ANOVA and the independent t-test. Finally, chi-square tests were used to determine differences in the proportions of ehealth literacy groups (high or low) classified with a median split within health resources and ehealth contents. RESULTS Principal components analysis produced a single factor solution and confirmatory factor analysis for the 8-items model demonstrated high indices (GFI = .988, CFI = .993, RMSEA= .056). A significant positive correlation was found between the J-eHEALS and communicative and critical health literacy scores. Cronbach alpha was 0.93 (P < .01), and test-retest reliability was r = 0.63 (P < .01). The J-eHEALS scores were significantly higher in women, the 40-and 50-year age group, those with high income, and individuals with a high frequency of internet searching. Furthermore, the high ehealth literacy group used many health resources and obtained a greater variety of ehealth contents as compared with the low literacy group. The most frequent resource was the internet in the high group, and television/radio in the low group. However, these results could be subject to bias because of the non-representative nature of the Internet population. CONCLUSION The results indicate the J-eHEALS to be a highly validated and reliable scale. The present study suggests that enhancement of ehealth literacy will be important to utilize the increasing amount of health information on the internet effectively and appropriately.
1 The Salience of Normative Theory

Democracy as a form of government comes in many forms. Even though supported by most citizens in democratic states, what they cherish are widely different systems. This plurality is crucial when the quality of democratic governance is to be evaluated; it is not a given what the ambitions of a specific system are to be measured against, and accordingly what the relevant variables to be assessed are. However, variation not only concerns strictly political systems as such but also the relationship between political institutions and the social institutions that are not directly part of political processes. Specifying how social institutions constitute a part of democracy is the aim of this chapter. Despite the plurality of democratic forms the present discussion does not take a systematic comparative approach but rather concentrates on the model of democracy common to the Nordic countries, with most empirical specifications taken from the Norwegian context. This does not imply that these societies are exemplary but rather that they represent a special case of well-established democratic governance with a long history of continuous political reformism. The analysis is based on the presumption that in the absence of a comparative study, a strategic study of one case may throw light on other, different cases as well. The chapter concentrates on two properties of Nordic democracy, its institutional and normative aspects. Nordic democracy is discussed by Aakvaag (this volume) with mostly non-normative perspectives on the institutional preconditions for individual freedom, whereas the present chapter sets its focus on democratic norms and the space for democratic deliberation within social institutions. Three basic institutions are surveyed: economy/working life, the welfare state and the media; together they constitute the main components of the general version of the Nordic model (Engelstad, Larsen, & Rogstad, 2017). By contrast, two prominent contributions within what may be termed the mainstream model of the quality of democracy serve as a starting point. The first is the set of criteria listed by Robert Dahl in Democracy and Its Critics (1989, pp. 108ff.): effective participation, voting equality, enlightened understanding and control of agenda constitute the ideal elements of citizens’ equal political opportunities. Despite their obvious value, these criteria are limited in two respects: they concern only political institutions and only implicitly take into account the functioning of these institutions. Recently, Larry Diamond made a salient contribution to the assessment of democracy with In Search of Democracy (2016), with broader and more precise measurements. By synthesizing three well-established measurements of democracy under the headings of political and electoral rights, civil liberties, rule of law and the functioning of government, Diamond and co-workers distil 19 sub-criteria (Diamond, Green, & Galley, 2016, p. 65). Here, a clear focus is set on the functioning of political
Management of the Injured Tendon : Difficulties in Diagnosis and T reatment

Background: Tendon injury is a painful and often debilitating affliction, which commonly presents to the sports medicine professional. Researchers have often struggled to determine the most appropriate way to manage this condition. Despite the plethora of literature on management strategies, there appears to be little stemming from sound scientific evidence. Objective: The aim of this is to identify studies that demonstrate a greater understanding of the pathophysiology of tendon injury and evaluate the most effective management strategies for this difficult condition. Methods: A systematic review of the literature was conducted. Results: The current review found support for the early use of corticosteroid injections, despite long term detrimental effects. The review also demonstrated exercise therapy designed to stretch and strengthen will be more effective in the long term. Conclusion: Individuals with tendinopathy should perform a regular strengthening and flexibility regime as early as possible. Patients with pain limiting daily activities may benefit from corticosteroids injections, to allow them to perform activities with reduced pain.
EGFR and HER 2 Expression in Papillary Thyroid Carcinoma

Purpose: The epidermal growth factor receptor (EGFR) family plays a crucial role in the growth of malignant tumors. EGFR and human EGFR 2 (HER2) protein overexpression are associated with an unfavorable prognosis and are important therapeutic targets in breast cancer. The aim of this study was to evaluate the relationship between EGFR and HER2 expression and clinicopathological factors in papillary thyroid carcinoma (PTC) at a single institution. Methods: A total of 129 consecutive patients with PTC were enrolled in this study and underwent thyroid surgery between October 2013 and February 2015. EGFR and HER2 protein expression was evaluated in the 129 primary tumors by immunohistochemistry, and the results were compared with the clinicopathological features. Results: Of the 129 PTC tumors, 20 (15.5%) were HER2 positive, and 109 (84.5%) were HER2 negative. Moreover, EGFR positivity were observed in 111 (86%) tumors. The mean age of the patients was 46.3±11.9 years (range, 20–74 years), and the mean tumor size was 1.08±0.75 cm (range, 0.2–3.5 cm). Tumor size, extrathyroidal extension, histological subtype, and TNM stage were not significantly associated with EGFR or HER2 expression. Meanwhile, high Ki-67 labeling index was significantly associated with EGFR expression (P=0.002), HER2 expression was significantly associated with younger age (≤45 years) and cervical lymph node metastasis. Conclusion: Based on our data, it is not clear whether EGFR and HER2 expression is associated with tumor aggressiveness in PTC.
BLOOD PRESSURE AND FLOW VALUES IN SMALL VESSELS ANGIOARCHITECTURES : APPLICATION FOR DIABETIC RETINOPATHY

Dunarea de Jos University of Galati, Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment, 47 Domneasca St., 800008 Galati, Romania Dumitru Moţoc High School, 15 Milcov St., 800509, Galaţi, Romania Department of Mathematical Sciences, Delaware State University, Dover, DE 19901-2277, USA Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah-21589, Saudi Arabia *Corresponding author: luminita.moraru@ugal.ro
A Bidirectional Processing Receiver for Layered Space-Time MIMO Systems

Resumo— Neste artigo, é apresentada uma nova estrutura de receptor para sistemas MIMO (do inglês, multiple-input multiple-output) baseados em cancelamento não-linear de interferência. A ideia principal do receptor proposto está no uso de uma abordagem bidirecional para o processamento do sinal, em que filtragem espacial e subtração de interferência iniciam simultaneamente na primeira e última camada de deteção, prosseguindo sucessivamente até a camada central de forma paralelizada. O receptor bidirecional proposto tem duas vantagens principais comparado aos detectores SIC (do inglês, successive interference cancelation): i) o atraso de processamento pode ser reduzido pela metade fazendo-se uso de uma unidade de processamento paralelo e ii) o desempenho em termos de taxa de erro de bits pode ser melhorado consideravelmente em decorrência do maior ganho de diversidade obido nas camadas de detecção. Além disso, o receptor bidirecional proposto exibe desempenho semelhante ao do receptor com retro-processamento recursivo proposto recentemente em [6], mas com um tempo de processamento menor. Resultados de simulação são fornecidos para confirmar o mérito do receptor proposto em termos de taxa de erro de bits não-codificada.
Compressed sensing in hyperpolarized 3He Lung MRI

In this work, the application of compressed sensing techniques to the acquisition and reconstruction of hyperpolarized 3He lung MR images was investigated. The sparsity of 3He lung images in the wavelet domain was investigated through simulations based on fully sampled Cartesian two‐dimensional and three‐dimensional 3He lung ventilation images, and the k‐spaces of 2D and 3D images were undersampled randomly and reconstructed by minimizing the L1 norm. The simulation results show that temporal resolution can be readily improved by a factor of 2 for two‐dimensional and 4 to 5 for three‐dimensional ventilation imaging with 3He with the levels of signal to noise ratio (SNR) (∼19) typically obtained. The feasibility of producing accurate functional apparent diffusion coefficient (ADC) maps from undersampled data acquired with fewer radiofrequency pulses was also demonstrated, with the preservation of quantitative information (mean ADCcs ∼ mean ADCfull ∼ 0.16 cm2 sec−1). Prospective acquisition of 2‐fold undersampled two‐dimensional 3He images with a compressed sensing k‐space pattern was then demonstrated in a healthy volunteer, and the results were compared to the equivalent fully sampled images (SNRcs = 34, SNRfull = 19). Magn Reson Med 63:1059–1069, 2010. © 2010 Wiley‐Liss, Inc.
Contribution for Innovations in Financial and Economic Networks

Determining the effects of labor institutions on macroeconomic performance is a central concern of economic policymakers. Differences in labor institutions have been conjectured to be a key explanation for observed crosscountry differences in the level and persistence of unemployment, in the distribution of income and wealth, and in growth rates for labor productivity and GDP. European OECD countries over the past twenty years have tended to rely on administered wages and legislated job protection and have experienced sluggish job growth and persistently high unemployment. In contrast, the United States has had a relatively 2 1 Evolution of Worker-Employer Networks and Behaviors Under Alternative Non-Employm more flexible, less regulated labor market and has achieved much greater job growth and relatively lower unemployment rates. This has led many Euro-pean policymakers to argue the need for reforms in their labor institutions. it is difficult to obtain conclusive empirical results regarding how labor institutions affect economic performance. Regression methods relating changes in labor institutions to economic outcomes quickly tax degrees of freedom. This problem is compounded if one institution's impact depends on the presence or absence of other institutions. Also, labor institutions are inherently endogenous. For example, governments continually revise labor institutions in response to economic and political pressures. This endogeneity makes it difficult to interpret the validity of empirical investigations. In recognition of these difficulties, Freeman (1998, pp. 19-20) suggests that agent-based computational modeling might offer a promising additional way to study the impact of labor institutions, particularly from a market design perspective. Tesfatsion (1998,2001,2002a) reports some preliminary work along these lines. An agent-based computational economics (ACE) framework is used to study path dependence, market power, and market efficiency outcomes for a labor market under systematically varied concentration and capacity conditions. ACE is the computational study of economies modeled as evolving systems of autonomous interacting agents (Tesfatsion,2002b,2003). 1 In this study we conduct an ACE labor market experiment to test the sensitivity of labor market outcomes to changes in the level of a non-employment payment. Our ultimate objective is to understand how the basic features of real-world unemployment benefit programs affect labor market performance. 2 However, as will be clarified below, a human subject experiment was run in parallel to this computational experiment as a check on the reliability of our findings and the adequacy of the learning representations for our computational workers and employers. To facilitate this initial benchmark check, a deliberately …
A Trace-based Approach to Increased Comprehensibility and Predictability of Bidirectional Graph Transformations ∗

Bidirectional graph transformation is expected to play an important role in model-driven software engineering, where artifacts are often refined through compositions of model transformations, from high level specifications down to concrete ones closer to implementation. In such a setting, changes in the artifacts are reflected not only from upstream to downstream, but also the other way round. However, it is often difficult to understand the correlation between the transformed artifacts. It is equally hard to predict to which part a change will eventually be propagated, and whether the propagation will succeed at all. That comprehensibility and predictability is crucial for more complex transformations. In this paper, we propose a well-defined tracing mechanism between source, transformation and target, as well as edge classification mechanism on the target artifacts, in a compositional framework of bidirectional graph transformation. We implemented these mechanisms in our GUI so that users are informed if an edit on the target is propagable to the source, where to be propagated, if the edit affects other parts in the target, or where in the transformation should be changed to accommodate the edit, without executing a backward transformation. We demonstrate the effectiveness of our approach using non-trivial bidirectional graph transformations.
COMPRESSIVE SENSING APPROACH TO HYPERSPECTRAL IMAGE COMPRESSION

Hyperspectral image (HSI) processing is one of the key processes in satellite imaging applications. Hyperspectral imaging spectrometers collect huge volumes of data since the image is captured across different wavelength bands in the electromagnetic spectrum. As a result, compression of hyperspectral images is one of the active area in research community from many years. The research work proposes a new compressive sensing based approach for the compression of hyperspectral images called SHSIR (Sparsification of hyperspectral image and reconstruction). The algorithm computes the coefficients of fractional abundance map in matrix setup, which is used to reconstruct the hyperspectral image. To optimize the problem with non-smooth term existence along with large dimensionality, Bregman iterations method of multipliers is used, which converts the difficult optimization problem into simpler cyclic sequence problem. Experimental result demonstrates the supremacy of the proposed method over other existing techniques.
Wear Properties of Some W / Cu Materials Prepared by Powder Metallurgy

The aim of the paper is to present experimental research in the field of W/Cu materials processed by Powder Metallurgy (PM) technologies. In order to fabricate W/Cu materials, mechanical alloying (MA) technique was used to obtain nanocomposite powders with the following compositions (85W/Cu, 80W/Cu and 75W/Cu). For the MA process was used a high energy vario planetary ball mill, Pulverisette 4 made by Fritsch and the milling times were between 2 and 8 hours. Green billets were obtained by die pressing at 600 MPa and then were sintered at 1180 o C for two hours. Scanning electron microscopy (SEM), ball on disk tribometer, profilometer were used in order to study the morphology and wear behaviour of the samples.
Anxiety in College Students across Majors : A Cross-Cultural Study

This study used survey data collected from two countries, Egypt and The United States of America (USA). There were 330 participants (162 males and 168 females), all of whom were undergraduate students. 169 participants were studying at Tanta University, Egypt, and 161 participants at the University of Arkansas, USA. The study aimed to investigate maths anxiety in undergraduates with different main subjects of study and across cultures. A 4x2 ANOVA was conducted to evaluate the effects of the student’s country and main subject of study (major) on maths anxiety. The results of the 4x2 ANOVA indicated a significant main effect for country, a non-significant effect for major, and a nonsignificant interaction effect between country and major. Furthermore, the study used a two-way ANOVA between two factors (gender and country and maths anxiety). The analysis revealed a significant main effect for country, a significant effect for gender, and a non-significant interaction effect between country and gender.
Influence of the synthesis conditions of γ-alumina on its hydrocarbons and water adsorption properties

The surface properties of γ-alumina can be modulated by its synthesis conditions. Since water adsorbs dissociatively on the surface of γ-alumina, its surface state will depend also on the water partial pressure of the atmosphere. However, those surface properties have never been clearly correlated to the adsorption properties of γ-alumina. Adsorption is the first step of every catalytic cycle, and thus this could be interesting information to get, being the objective of this study. To reach this objective, different γ-alumina samples were synthesized: a reference one, one that differed in the nature of the synthesis gas, and another one that differed in the boehmite morphology. They were all characterized in terms of water adsorption and, for the reference sample, of hydrocarbons adsorption by thermogravimetry. The adsorption isotherms for the reference sample (obtained from boehmite Pural SB3 decomposed under air) could only be obtained through adsorption measurements, which were simulated by a model based on DFT, and by a normal-like distribution model, with good fittings. Changing the synthesis gas from air to nitrogen resulted in an unstable sample. On the other hand, starting from a boehmite with proportionally less edges lead to a sample with less adsorption capacities, suggesting that edges are important adsorption sites for water. Finally, a preliminary hydrocarbons adsorption study was conducted on the first sample, showing that ethylene adsorbs more than ethane, and that its adsorption capacity increases with the decrease in hydroxyl content. In particular, desorbing the last hydroxyl seems to free a specific site that has now to be identified.
Optimization of Clay Core Dimensions in Earth Fill Dams Using Particle Swarm Algorithm

The flow rate from earth fill dam body mainly depends on the dimensions and characteristics of the clay core. Thus, finding the optimized dimensions for clay core in non-homogeneous earth fill dam is essential. In order to decrease water loss, the clay core should be expanded this leads to dramatic increment in construction volume and costs. The novelty of this issue could be expressed as an optimization material in which the total cost of lost water and earthwork should be minimized. The method serves us a simpler and an accurate solution for an earth fill dam to be in optimised dimensions. The objective function is consisting of two parts. The first part is to calculate the water seepage volume through the dam core with a combination of finite element method and artificial neural network (ANN) and the second part encounters the costs regarding to the volume of earth works. Finally the best answer from the economical view will be chosen according to the amount of seepage and core volume. Since calculating water seepage through soil using finite element method is time consuming, first a combination of 600 different potential shapes of the core has been modelled by finite element and then the result have been used to train an artificial neural network. Comparing this model with linear and logarithmic regression models proved that ANN evaluates water flow rate with more precession. Output data, including flow rate, entered to the particle swarm optimization (PSO) algorithm and the optimized dimensions were achieved. The proposed model for optimizing the clay core dimension can be applied for non-homogeneous earth fill dams with impervious foundation. Allavian earth fill dam was chosen to show the benefit of using the proposed optimization method in a real world case study. The results indicated that the construction cost could be dramatically less than what has been already spent on the case study.
The dynamics of deep neural networks

Since Hinton et al. [1] introduced new learning algorithms for multilayered feed-forward networks, now commonly known as deep neural networks (DNN), many people have started to investigate this potential capabilities and applications. For example, Google Inc. showed that deep learning can automatically extract cat faces and human body images from millions of randomly selected Youtube images [2]. In other work, Szegedy et al. [3] obtained high recognition rates at human like ability by using very deep multi layered neural networks. In this study, we computed the information flow within a DNN in order to reveal its underlying dynamical systems properties. Our results support the hypothesis that DNN get their high performance by removing and expanding feature information as the layers goes up and compresses a high dimensional data set’s distribution onto low dimensional manifolds.