Miracle-dz/UniFAR-FTUs huggingface dataset:
Health risk behaviour of elementary school children in Vojvodina

Aim To determine frequency, mutual correlation of health-risk behavious among elementary school children and their correlation with sources of health-related information and social behaviour models. Methods Rasearch was conducted in the form of cross-sectional study. ASsample included students from 5th to 8th grades of elementary school. Data were collected by interviewing students with a questionnaiie consisted of two parts: Risk Behaviour Scale and set of questions about sources of information, social behaviour models and socio-demographic characteristics. Risk Behaviour Scale measured the following health-risk behavios: use of psychoactive supstances (cigarettes, alcohol, illegal substances), risky behaviour in traffic, unsafe sexual behavior, inadequate nutrition and insufficient physical activity. Values p <0.05 were considered as statistical significant. Results Sample included 445 elementary school students aged 11 to 1e. The most prominent health risk behaviours were unhealthy dietary habits, with 408 (91.1 %) students consumind fast food. Alcohol was the most frequent psiho-active substance used, in 261 (58.2 %) cases. Health-risk behaviours were more frequent among boys, older students, those with low school achievment and those who receive health-related information from peers and media. Statistically significant correlation between inadequate nutrition and physical inactivity was found (p=0.000). Alcohol use was significantly correlated with the use of cigarettes (p=0.00) and illegal substances (p=0.00), risk sexual behaviour (p=0.00), risk behaviour in traffic (p=0.00) and physical inactivity (p=0.00). Conclusion All health-risk behaviours appeared an the same time in elementary school students and that could be a consequence of same individual and social factors which contribute to their occurence.
Manual vs Automatic Bitext Extraction

We compare manual and automatic approaches to the problem of extracting bitexts from the Web in the framework of a case study on building a Russian-Kazakh parallel corpus. Our findings suggest that targeted, site-specific crawling results in cleaner bitexts with a higher ratio of parallel sentences. We also find that general crawlers combined with boilerplate removal tools tend to retrieve shorter texts, as some content gets cleaned out with the markup. When it comes to sentence splitting and alignment we show that investing some effort in data pre-and post-processing as well as fiddling with off-the-shelf solutions pays a noticeable dividend. Overall we observe that, depending on the source, automatic bitext extraction methods may lack severely in coverage (retrieve fewer sentence pairs) and on average are fewer precise (retrieve less parallel sentence pairs). We conclude that if one aims at extracting high-quality bitexts for a small number of language pairs, automatic methods best be avoided, or at least used with caution.
Towards a Simulator for Imitation Learning with Kinesthetic Bootstrapping

This paper presents a physics based simulator that allows kinesthetic interactions between a human and a robot to be recorded, and later used for imitation learning. We argue that kinesthetic interac- tion can be a very important tool for programming robots, if properly supported by a simulation engine. For this, we propose a new scheme for robot motion learning based on kinesthetic bootstrapping. Interactions with the robot are used to create a low-dimensional posture space. The posture space together with the presented simulation engine allow for fast imitation learning of behaviors. Early results of this approach, using Genetic Algorithms as learning technique, will be presented.
Review: Parsing Clothes by Giving Weak Supervision using Pose Estimation in Fashion Photographs

: In this paper we like to describe the problem of parsing clothing items from images crawled from fashion related websites. The The problem is challenging due to clothing look, layering, fashion, and body shape variation and pose. Presenting the problem of automatically parsing the fashion photographs with weak supervision from the user-generated colour-category labels such as “grey-shirt” and “Black-skirt”. Due to immense diversity of fashion items this problem has become very demanding. To solve this problem, the combination of the super pixel-level category classifier learning module, human pose identification module, the Marcov Random Field based colour and category implication module to create multiple well performing category classifiers, which can be applied directly to parse the garments and other items in the images. All the training images are parsed with colour-category tags and the human poses of the images are estimated during the learning phase. Finally, resulting improved pose estimation, providing parsing results with classifier for further use during test.
Is Managerial Work in the Public and Private Sectors Really “Different”? A Comparative Study of Managerial Work Activities

ABSTRACT This article aims to discern the extent to which managerial work is similar and different in the public and private sectors. Using propositions and structured categories for describing what managers do, this article compares results of an observational study conducted in the Canadian public sector with similar studies from the private sector. Through a comparison of work type, hours, location, activities, and contact patterns, this research finds few differences in managerial work activities between the two sectors, despite contextual and situational differences. Possible explanations are explored, implications of the findings are discussed, and future research directions are proposed.
The Role of Organizational Learning Culture to Organizational Citizenship Behavior toward Knowledge Sharing Behavior

This research was conducted to examine the role of organizational learning culture in moderating of OCB on knowledge sharing behavior. It was based on survey of 100 community facilitators. Structural equation modeling was used to test the hypothesis. The results showed that OCB had a significant effect on knowledge sharing behavior, but this correlation was weak. It was also found that Organizational learning culture as a strong significant moderator of OCB toward knowledge sharing behavior. Sportmanship to receive a duty from the organization was the main reason for facilitators to share their knowledge. The existence of empowering people from these organizations had encouraged them to receive a duty as a form of responsibility from the organization so they provide to share their knowledge with their colleagues. Therefore, organizational learning culture had an important role to OCB on knowledge sharing behavior. There was another factor determining of knowledge sharing behavior that unreachable in this study so for future research may investigated such as job attitudes, subjective norms and perceived behavioral of control, etc. Moderating role of Organizational learning culture may develop to other variable on knowledge sharing behavior.
Wet Environmental Conditions Affecting Narrow Band On-Body Communication Channel for WBANs

© 2018 Old City Publishing, Inc. Wireless Body Area Networks (WBANs) are rising as the key building blocks of next generation networks in modern health care systems. Research in recent years has focused on channel modelling, energy conservation and design of efficient Medium Access Control (MAC) schemes for WBANs. However, less attention has been paid to the on-body channel propagation analysis. This paper presents the propagation effects of wet clothing on the on-body channel at 0.9GHz, 1.8GHz and 2.5GHz and is germane to signal budgets in body-centric and mobile communication systems. A number of transmission measurements between simple monopoles above a square ground plane, placed on the opposing shoulder and hip, wearing single and multi-layered “rainwater wet” and dry cotton T-Shirts for standing, bending, torso left and right are used to gain insight into general levels of the effect of rainwater on propagation. Measured results are statistically processed to extract the level of transmission enhancement due to a wet on-body channel. Results show that wet clothing is generally beneficial to the channel at popular mobile communications frequencies.
A user mode implementation of filtering rule management plane using key-value store

With the rapid advance of network virtualization technology which realizes SDN (Software Defined Network) and Cloud computing, current networking environment has become more flexible, diversified and complex. At the same time, complex networking environment sometimes imposes a great burden on network administrators for coping with complicated filtering rules. In this paper we present a user mode support for centralized filtering rule management base. Proposed system enables us to handle fine grained traffic engineering functionality for diversified environment of Cloud and SDN. Our architecture adopts KV (Key-Value) based Datastore for handling a large scale of filtering rules. By leveraging Datastore for centralized access control of instances on virtualized environment, we can provide alternative access control framework for reducing the burden of managing complicated and dynamic filtering policy on instances (virtual machine) on virtualized networking environment. Besides, KV representation can simplify the filtering rule set and provide generic interfaces for querying. In experiment, we have prototyped a lightweight management plane for IP filtering. Access filtering rules including target IP address, prefix and gateway is represented as radix tree. It is shown that proposed method can achieve reasonable utilization in filtering IP packets.
Essays on asset pricing in open economies

Essays on Asset Pricing in Open Economies Andreas Stathopoulos Chapter 1 proposes a two-country general equilibrium model with external habits and home-biased preferences that addresses a number of international finance puzzles. Specifically, the model reconciles the high degree of international risk sharing implied by relatively smooth exchange rates with the modest cross-country consumption growth correlations seen in the data, resolving the Brandt, Cochrane and Santa-Clara (2006) puzzle. Furthermore, the model matches the empirically observed low correlation between exchange rate changes and international consumption growth rate differentials. For both effects, the fundamental mechanism is time variation in consumption growth volatility, which is endogenously generated through international trade. Asset prices depend on a weighted average of the two countries' time-varying risk aversion, with the weights determined by the wealth and degree of home bias of each country. Simulation results indicate that the model is successful in matching key empirical asset pricing, exchange rate and international trade moments. Chapter 2 examines international portfolio choice in a two-country general equilibrium setting which features time-varying risk aversion generated by external habit formation. I show that, under complete markets, home bias in the consumption preferences leads to significant portfolio home bias due to differential hedging demands. Domestic (foreign) agents shift their portfolio towards domestic (foreign) assets, so as to better hedge against adverse changes in their conditional risk aversion. Furthemore, the model generates realistic asset pricing moments, thus reconciling international portfolio choice with asset pricing.
Accurate nonlinear mapping between MNI volumetric and FreeSurfer surface coordinate systems

The results of most neuroimaging studies are reported in volumetric (e.g., MNI152) or surface (e.g., fsaverage) coordinate systems. Accurate mappings between volumetric and surface coordinate systems can facilitate many applications, such as projecting fMRI group analyses from MNI152/Colin27 to fsaverage for visualization, or projecting resting-state fMRI parcellations from fsaverage to MNI152/Colin27 for volumetric analysis of new data. However, there has been surprisingly little research on this topic. Here, we evaluated three approaches for mapping data between MNI152/Colin27 and fsaverage coordinate systems by simulating the above applications: projection of group-average data from MNI152/Colin27 to fsaverage and projection of fsaverage parcellations to MNI152/Colin27. Two of the approaches are currently widely used. A third approach (registration fusion) was previously proposed, but not widely adopted. Two implementations of the registration fusion (RF) approach were considered, with one implementation utilizing the Advanced Normalization Tools (ANTs). We found that RF-ANTs performed the best for mapping between fsaverage and MNI152/Colin27, even for new subjects registered to MNI152/Colin27 using a different software tool (FSL FNIRT). This suggests that RF-ANTs would be useful even for researchers not using ANTs. Finally, it is worth emphasizing that the most optimal approach for mapping data to a coordinate system (e.g., fsaverage) is to register individual subjects directly to the coordinate system, rather than via another coordinate system. Only in scenarios where the optimal approach is not possible (e.g., mapping previously published results from MNI152 to fsaverage), should the approaches evaluated in this manuscript be considered. In these scenarios, we recommend RF-ANTs (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/registration/Wu2017_RegistrationFusion).
Voltage stability study of micro-grid with asynchronous wind turbine in islanding mode

In islanding mode, the surge current during startup and shutdown of asynchronous wind turbine and its power fluctuations can be a significant challenge to the stable operation of micro-grid. Energy storage based micro-grid stability controller has been proved effective for micro-grid control. This paper analyses the performance of the micro-grid stability controller considering its capacity, the control strategy and the line impedance. The minimum necessary capacity of the energy storage and maximum line impedance limitation for micro-grid voltage stability are presented theoretically and verified by simulation. Finally, the transient process of grid-connection and disconnection of asynchronous wind turbine are studied with the developed micro-grid stability controller by field experiment.
Does Internal Migration Affect Italian Domestic Tourism? A Panel Data Analysis

The authors propose a dynamic panel data investigation into the role of interregional migration in Italian domestic tourism demand, using three panel estimators characterized by different homogeneity assumptions imposed on the parameters. A standard cointegration analysis is performed before proceeding to panel regressions. The results provide ample support for a strong positive relationship between per capita domestic tourism nights and per capita internal migration stock. This evidence extends the migration—tourism nexus, already established at the international level, to the intra-national scale and reinforces the idea that host regions should not overlook the role of migration when designing their tourism policies.
Parallel Evolution of Common Allelic Variants Confers Flowering Diversity in Capsella rubella[OPEN]

This work provides an example of how parallel mutations in the same 5′ UTR region can shape phenotypic evolution in plants. Flowering time is an adaptive life history trait. Capsella rubella, a close relative of Arabidopsis thaliana and a young species, displays extensive variation for flowering time but low standing genetic variation due to an extreme bottleneck event, providing an excellent opportunity to understand how phenotypic diversity can occur with a limited initial gene pool. Here, we demonstrate that common allelic variation and parallel evolution at the FLC locus confer variation in flowering time in C. rubella. We show that two overlapping deletions in the 5′ untranslated region (UTR) of C. rubella FLC, which are associated with local changes in chromatin conformation and histone modifications, reduce its expression levels and promote flowering. We further show that these two pervasive variants originated independently in natural C. rubella populations after speciation and spread to an intermediate frequency, suggesting a role of this parallel cis-regulatory change in adaptive evolution. Our results provide an example of how parallel mutations in the same 5′ UTR region can shape phenotypic evolution in plants.
The Effects of Acute Exercise on Mood, Cognition, Neurophysiology, and Neurochemical Pathways: A Review

A significant body of work has investigated the effects of acute exercise, defined as a single bout of physical activity, on mood and cognitive functions in humans. Several excellent recent reviews have summarized these findings; however, the neurobiological basis of these results has received less attention. In this review, we will first briefly summarize the cognitive and behavioral changes that occur with acute exercise in humans. We will then review the results from both human and animal model studies documenting the wide range of neurophysiological and neurochemical alterations that occur after a single bout of exercise. Finally, we will discuss the strengths, weaknesses, and missing elements in the current literature, as well as offer an acute exercise standardization protocol and provide possible goals for future research.
AMPK regulates energy metabolism through the SIRT1 signaling pathway to improve myocardial hypertrophy.

OBJECTIVE We investigated the correlations of adenosine monophosphate-activated protein kinase (AMPK), Silence information regulator 1 (SIRT1) and energy metabolism with myocardial hypertrophy. MATERIALS AND METHODS Myocardial hypertrophy experimental model was established via transverse aortic constriction (TAC)-induced myocardial hypertrophy and phenylephrine (PE)-induced hypertrophic myocardial cell culture. After activation of AMPK, the messenger ribonucleic acid (mRNA) expressions in myocardial tissue- and myocardial cell hypertrophy-related genes, atrial natriuretic peptide (ANP) and β-myosin heavy chain (β-MHC), were detected. The production rate of 14C-labeled 14CO2 from palmitic acid was quantitatively determined to detect the fatty acid and glucose oxidation of hypertrophic myocardial tissues or cells, and the glucose uptake of myocardial cells was studied using [14C] glucose. Reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting were performed to detect the changes in SIRT1 mRNA and protein expressions in hypertrophic myocardial tissues. Moreover, SIRT1 small interfering ribonucleic acid (siRNA) was used to interfere in SIRT1 expression to further investigate the role of SIRT1 in the effect of AMPK activation on myocardial hypertrophy. RESULTS AMPK activation could significantly reduce the mRNA expressions of ANP and β-MHC in vitro and in vivo. AMPK could increase the ejection fraction (EF) and decrease the protein synthesis rate in myocardial cells in mice with myocardial hypertrophy. Besides, AMPK activation could increase the fatty acid oxidation, improve the glucose uptake and reduce the glucose oxidation. After AMPK activation, both SIRT1 mRNA and protein expressions in hypertrophic myocardial tissues and myocardial cells were increased. After SIRT1 siRNA was further used to interfere in SIRT1 expression in myocardial cells, it was found that mRNA expressions and protein synthesis rates of ANP and β-MHC were increased. CONCLUSIONS The activation of AMPK can inhibit the myocardial hypertrophy, which may be realized through regulating the myocardial energy metabolism via SIRT1 signaling pathway.
L{NG{$_{-}$}FEM}: graded meshes on domains of polygonal structures

We develop LNG FEM, a software package for graded mesh generation and for solving elliptic equations. LNG FEM generates user-speciﬁed graded meshes on arbitrary 2D domains with straight edges for diﬀerent boundary conditions. We shall focus on a detailed exposition on the implementation of the software. In addition, we demonstrate that LNG FEM is equipped with advanced algorithms and data structures to perform eﬃciently in numerical tests. We hope that LNG FEM can broaden the use and understanding of graded mesh in the ﬁnite element approximation of singular solutions.
Improved Hybrid Converter with Simultaneous DC and AC Outputs

This Paper introduces new hybrid converter topologies which can supply simultaneously AC as well as DC from a single DC source. The new Hybrid Converter is derived from the single switch controlled Boost converter by replacing the controlled switch with voltage source inverter (VSI). This new hybrid converter has the advantages like reduced number of switches as compared with conventional design and provides DC as well as AC outputs with an increased reliability resulting from the inherent shoot through protection in the inverter stage. For controlling switches, PWM control based upon unipolar Sine-PWM is described. Simulink model is used to validate the operation of the converter. The proposed Converter can supply DC and AC loads at 220 V and 230V (rms) respectively from a 12V DC source. A 50 W laboratory prototype is used to validate the operation of the converter.
Decomposing variation in immune response in a wild rodent population

Individuals vary in their immune response and, as a result, some are more susceptible to infectious disease than others. Little is known about which components of immune pathways are responsible for this variation, but understanding these underlying processes could allow us to predict the outcome of infection for an individual, and to manage their health more effectively. In this study, we describe transcriptome-wide variation in immune response (to a standardised challenge) in a wild population of field voles (Microtus agrestis). We find that this variation can be categorised into three main types. We also identify markers, across these three categories, which display particularly strong individual variation in response. This work shows how a simple standardised challenge performed on a natural population can reveal complex patterns of natural variation in immune response.
Age-and Sex-Specific Fertility in Germany until the Year 2040 – The Impact of International Migration

Good Forecasts for future fertility developments are of high importance in political planning, especially regarding measures in social insurance. Fertility is the main driver of demographic change, since small fertility rates lead to a shrinking population and together with decreasing mortality rates to an aging of the population structure. Which means an increasing stock of elder people, who have to be financed by less people in the working ages. Parametric time series models based on a quasi-three principal component model are fitted to the ageand sex-specific fertility rates (ASSFR). Age-specific migration, represented by a migration index derived from a previous principal component analysis (PCA), is used as a predictor variable to take into account its impact on fertility. Simulations of Wiener processes are used for estimating the future distributions of each ASSFR as well as the Total Fertility Rate (TFR). The forecast shows, ceteris paribus, a further increase in the TFR, with increases in the ASSFR for older women and decreasing ones for younger females. A test based on squared residuals shows 2 that the model gives better forecast accuracy than the most commonly used methods in Germany. The modeling approach performs better than common projection and forecast methods in Germany while integrating the often discussed link between migration and fertility into a forecasting model. Next to the detailed and stochastic quantification of age-specific fertility it includes the gender of newborns, which allows for easy implementation into regular population updating through a stochastic cohort-component model.