Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of aerobic exercise on home-based sleep among overweight and obese men with chronic insomnia symptoms

Objective: To determine the effect of a six-month aerobic exercise program on home-based sleep quality among overweight and obese men with chronic insomnia symptoms. Methods: Participants were 45 Finnishmen (93% had bodymass index ≥25) aged 30–65 years, with chronic (≥3 months) insomnia symptoms as classified by the DSM-IV criteria. Participants were randomized into an exercise (n = 24) or control group (n = 21). The exercise group received six-month aerobic exercise intervention with one to five sessions per week of 30–60minutes duration. The control group was instructed to maintain habitual lifestyle behaviors during the study period. Seven-night home sleep was measured with a piezoelectric bed sensor and sleep diary. Other assessments included the modified Basic Nordic Sleep Questionnaire, a health and behavior questionnaire, physical activity and diet diaries, anthropometry, fat mass, and physical fitness. Analysis of covariance controlling for baseline values, and repeated-measures analysis of variance were implemented for time-by-group comparisons and withingroup comparisons, respectively. Results: At six months, the exercise group showed reduced objective sleep onset latency (p = 0.010) and lowered frequency of difficulty initiating sleep (p = 0.021) than controls. Although a time-by-group difference was not significant, exercisers showed shorter objective wake after sleep onset (p = 0.004), reduced subjective nocturnal awakenings (p = 0.010), improved objective sleep efficiency (p < 0.001), and improved morning-rated subjective sleep quality (p = 0.042) at six months than baseline. Conclusions: A six-month aerobic exercise can improve sleep, mainly by mitigating difficulty of initiating sleep among overweight and obese men with chronic insomnia symptoms. © 2016 Elsevier B.V. All rights reserved.
Deposition of microcrystalline silicon prepared by hot-wire chemical-vapor deposition: The influence of the deposition parameters on the material properties and solar cell performance

Microcrystalline silicon (μc-Si:H) of superior quality can be prepared using the hot-wire chemical-vapor deposition method (HWCVD). At a low substrate temperature (TS) of 185 °C excellent material properties and solar cell performance were obtained with spin densities of 6×1015cm−3 and solar cell efficiencies up to 9.4%, respectively. In this study we have systematically investigated the influence of various deposition parameters on the deposition rate and the material properties. For this purpose, thin films and solar cells were prepared at specific substrate and filament temperatures and deposition pressures (pD), covering the complete range from amorphous to highly crystalline material by adjusting the silane concentration. The influence of these deposition parameters on the chemical reactions at the filament and in the gas phase qualitatively explains the behavior of the structural composition and the formation of defects. In particular, we propose that the deposition rate is determined by the product.
Fog Architectures and Sensor Location Certification in Distributed Event-Based Systems †

Since smart cities aim at becoming self-monitoring and self-response systems, their deployment relies on close resource monitoring through large-scale urban sensing. The subsequent gathering of massive amounts of data makes essential the development of event-filtering mechanisms that enable the selection of what is relevant and trustworthy. Due to the rise of mobile event producers, location information has become a valuable filtering criterion, as it not only offers extra information on the described event, but also enhances trust in the producer. Implementing mechanisms that validate the quality of location information becomes then imperative. The lack of such strategies in cloud architectures compels the adoption of new communication schemes for Internet of Things (IoT)-based urban services. To serve the demand for location verification in urban event-based systems (DEBS), we have designed three different fog architectures that combine proximity and cloud communication. We have used network simulations with realistic urban traces to prove that the three of them can correctly identify between 73% and 100% of false location claims.
A survey of matrix completion methods for recommendation systems

In recent years, the recommendation systems have become increasingly popular and have been used in a broad variety of applications. Here, we investigate the matrix completion techniques for the recommendation systems that are based on collaborative filtering. The collaborative filtering problem can be viewed as predicting the favorability of a user with respect to new items of commodities. When a rating matrix is constructed with users as rows, items as columns, and entries as ratings, the collaborative filtering problem can then be modeled as a matrix completion problem by filling out the unknown elements in the rating matrix. This article presents a comprehensive survey of the matrix completion methods used in recommendation systems. We focus on the mathematical models for matrix completion and the corresponding computational algorithms as well as their characteristics and potential issues. Several applications other than the traditional user-item association prediction are also discussed.
omatotopical relationships between cortical activity and reflex areas in eflexology : A functional magnetic resonance imaging study

We examined the somatotopical relationship between cortical activity and sensory stimulation of reflex areas in reflexology using functional magnetic resonance imaging. Three reflex areas on the left foot, relating to the eye, shoulder, and small intestine were stimulated during the experiment. A statistical 9 September 2008 ccepted 1 October 2008
Fusion of multiple features to produce a segmentation algorithm for remote sensing images

This letter presents an edge direction adaptive watershed segmentation method for remote sensing images. First, the maximum gradient value among different directions is chosen as the single band gradient value of the pixel, and a compound gradient value is then calculated based on the gradient value in each band. Second, the marker-based watershed segmentation is implemented to produce initial over-segmentation result to avoid under-segmentation. Finally, the adjacent objects with high similarity values are merged to reduce over-segmentation, which improves segmentation accuracy. The performance of the proposed method is validated on two satellite images. Experimental results show that, compared with the multi-resolution segmentation method embedded in the eCognition software and the traditional multi-band watershed segmentation method, the proposed method can decrease over-/under-segmentation and thus produce satisfactory segmentation results.
Molecular Speciation of Phosphorus Present in Readily Dispersible Colloids from Agricultural Soils

Soil Sci. Soc. Am. J. 78:47–53 doi:10.2136/sssaj2013.05. 0159 Received 2 May 2013. *Corresponding author (liang410@zju.edu.cn). Supplemental materials are available online. © Her Majesty the Queen in Right of Canada, as represented by the Minister of Agriculture and AgriFood Canada All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Molecular Speciation of Phosphorus Present in Readily Dispersible Colloids from Agricultural Soils The 11th Dahlia Greidinger Memorial Symposium: Advanced Methods for Investigating Nutrient Dynamics in Soils and Ecosystems
Molecules in the Cynomolgus Monkey ( Macaca fascicularis ) The Placenta in Toxicology . Part I : Animal Models in Toxicology : Placental Morphology and Tolerance

The immune system represents a key defense mechanism against potential pathogens and adverse non-self materials. During pregnancy, the placenta is the point of contact between the maternal organism and non-self proteins of the fetal allograft and hence undoubtedly fulfils immune functions. In the placenta bacteria, foreign (non-self) proteins and proteins that might be introduced in toxicological studies or by medication are barred from reaching the progeny, and the maternal immune system is primed for acceptance of non-maternal fetal protein. Both immunologic protection of the fetus and acceptance of the fetus by the mother require effective mechanisms to prevent an immunologic fetomaternal conflict and to keep both organisms in balance. This is why the placenta requires toxicological consideration in view of its immune organ function. The following articles deal with placenta immune-, control-, and tolerance mechanisms in view of both fetal and maternal aspects. Furthermore, models for experimental access to placental immune function are addressed and the pathological evaluation is elucidated. ‘‘The Placenta as an Immune Organ and Its Relevance in Toxicological Studies’’ was subject of a continuing education course at the 2012 Society of Toxicologic Pathology meeting held in Boston, MA.
Separation of Concerns : Requirements Vs Business Processes

Software editors concerned to produce faster, better and cheaper, are irreversibly affected by the development of product lines (software factory). The software product line approach offers techniques to increase reuse by explicitly modelling the common and variable characteristics. Considering this approach, the variability is modelled and managed throughout all stages of development. Thus, models of variable business processes are part of the design artefacts in analysis stage. Several models have been proposed to represent variable business processes. However, these models are far from being directly usable in real industrialization of production in software factory. Indeed, deficiencies such as non-representation of variability on all entities of business processes, not taking into account all the possible types of variability, or use proprietary languages, prevent those models to be operational. In this paper, we present these barriers to the operationalization and propose solutions to overcome each of them. The result is an operational model of variable business process, actually used and integrated in a software factory approach.
An Automatic Evaluation Method for Conversational Agents Based on Affect-as-Information Theory

This paper presents a method for automatic evaluation of conversational agents. The method consists of several steps. First, an affect analysis system is used to detect users' general emotional engagement in the conversation and classify their specific emotional states. Next, we interpret this data with the use of reasoning based on Affect-as-Information Theory to obtain information about users' general attitudes to the conversational agent and its performance. The affect analysis system was also enhanced with a procedure for analysis of Contextual Valence Shifters to help determine the semantic orientation of emotive expressions. The method is used as a background procedure during users' conversations with two Japanese-speaking conversational agents. To verify the usability of the method, the users' attitudes to the conversational agents determined automatically during the conversations were compared to the results of a questionnaire taken after the conversations. The results provided by the system revealed similar tendencies to the questionnaire. Therefore we can say that the method is applicable as a means of evaluation for Japanese-speaking conversational agents.
Medical Image Analysis , Assignment 1 : Registration . 1

The purpose of this assignment is to perform landmark-based image registration. Both rigid registration, using Euclidean transformations, and Procrustes alignment, using similarity transformations, are considered. The landmarks will be generated automatically using SIFT and RANSAC, and are therefore to be considered as mathematical landmarks. Landmark-based methods are especially interesting when dealing with image pairs having different modalities. This is illustrated clearly in the second part of the assignment.
Strati cation and weighting via the propensity score in estimation of causal treatment e ects : a comparative study

Estimation of treatment e ects with causal interpretation from observational data is complicated because exposure to treatment may be confounded with subject characteristics. The propensity score, the probability of treatment exposure conditional on covariates, is the basis for two approaches to adjusting for confounding: methods based on strati cation of observations by quantiles of estimated propensity scores and methods based on weighting observations by the inverse of estimated propensity scores. We review popular versions of these approaches and related methods o ering improved precision, describe theoretical properties and highlight their implications for practice, and present extensive comparisons of performance that provide guidance for practical use. Copyright ? 2004 John Wiley & Sons, Ltd.
Optimization of Synthetic Inertial Response from Wind Power Plants

In this paper the emphasis is on the optimization of synthetic inertial response of wind power plants (WPPs) for power systems with high wind power penetration levels, considering different wind speed operating conditions. The synthetic inertial response of wind power plants can play an important role in the resilience of future power systems with low inertia during large frequency disturbances. In order to investigate this role, a generic optimization methodology employing the genetic algorithm is proposed, taking into consideration the frequency nadir, second frequency dip, and time to reach the quasi–steady-state frequency. This optimization methodology comprehends the inertial response capability of WPPs and the frequency control dynamics of the power system. Accordingly, offline parameter tuning of synthetic inertial response is performed at the power system level with the proposed methodology. Based on the optimization results, the relevant aspects to be considered by transmission system operators and wind power plant developers in the process of designing and planning synthetic inertia are identified and analyzed. Additionally, sensitivity analyses are carried out to assess the impact of synthetic inertial response parameters on power system frequency control performance under different contingencies and wind power penetration levels.
Molecular Theory for Mixed Micelles

A molecular theory for the formation of mixed micelles is developed here as an extension of our earlier theory for single-component micelles. The theory permits the calcuiation of the cmc, the average micelle size, and the average micelle composition as well as the size and the composition distribution of micelles in mixed surfactant systems. Central to the theory is an explicit molecular thermodynamic expression for the Gibbs energy of formation of the mixed micelle. This Gibbs energy of micelle formation, which is composition dependent, can be decomposed into bulk and interfacial components. The bulk component includes the free energy contributions arising from the transfer of the surfactant tail from water to th'e micelle. The interfacial component includes the free energy contributions due to the micellar core-water interfacial energy, the steric repulsions between the head groups at the micelle surface, and the electrostatic repulsions between the head groups at the micelle surface. If the Gibbs energy of micelle formation is a linear function of the micelle composition, then the excess Gibbs energy is zero and the surfactant mixture behaves ideally. On the other hand, if the Gibbs energy of micelle formation has a nonlinear dependence on the micelle composition, then the excess Gibbs energy is nonzero and the surfactant mixture displays nonideal micellization behavior. It is shown that the bulk component of the Gibbs energy of micelle formation depends linearly on the micelle composition and hence does not account for any nonideal behavior displayed by the mixed micelles. In contrast, the interfacial component has a nonlinear dependence on the composition of the mixed micelle and thus constitutes the source of the observed nonidealities in mixed micellar systems. Therefore, surfactant mixtures displaying markedly nonideal micellization behavior are those for which the interfacial interactions show significant composition dependence. Illustrative results based on this molecular theory are obtained for a number of binary mixtures and are compared against the available experimental data.
Impact of Income on Calorie and Nutrient Intakes: A Cross-Country Analysis

The relationship between income and nutrient intake is explored. Nonparametric, panel, and quantile regressions are used. Engle curves for calories, fat, and protein are approximately linear in logs with carbohydrate intakes exhibiting diminishing elasticities as incomes increase. Elasticities range from 0.10 to 0.25, with fat having the highest elasticities. Countries in higher quantiles have lower elasticities than those in lower quantiles. Results predict significant cumulative increases in calorie consumption which are increasingly composed of fats. Though policies aimed at poverty alleviation and economic growth may assuage hunger and malnutrition, they may also exacerbate problems associated with obesity.
Predicting and Analyzing Language Specificity in Social Media Posts

In computational linguistics, specificity quantifies how much detail is engaged in text. It is an important characteristic of speaker intention and language style, and is useful in NLP applications such as summarization and argumentation mining. Yet to date, expert-annotated data for sentence-level specificity are scarce and confined to the news genre. In addition, systems that predict sentence specificity are classifiers trained to produce binary labels (general or specific). We collect a dataset of over 7,000 tweets annotated with specificity on a fine-grained scale. Using this dataset, we train a supervised regression model that accurately estimates specificity in social media posts, reaching a mean absolute error of 0.3578 (for ratings on a scale of 1-5) and 0.73 Pearson correlation, significantly improving over baselines and previous sentence specificity prediction systems. We also present the first large-scale study revealing the social, temporal and mental health factors underlying language specificity on social media.
Assessing Complexity of Neuronal Multiunit Activity by Information Theoretic Measure

Abstract—This paper provides a quantitative measure of the time-varying multiunit neuronal spiking activity using an entropy based approach. To verify the status embedded in the neuronal activity of a population of neurons, the discrete wavelet transform (DWT) is used to isolate the inherent spiking activity of MUA. Due to the de-correlating property of DWT, the spiking activity would be preserved while reducing the non-spiking component. By evaluating the entropy of the wavelet coefficients of the de-noised MUA, a multiresolution Shannon entropy (MRSE) of the MUA signal is developed. The proposed entropy was tested in the analysis of both simulated noisy MUA and actual MUA recorded from cortex in rodent model. Simulation and experimental results demonstrate that the dynamics of a population can be quantified by using the proposed entropy.
A fuzzy approach for tracking of low-altitude target in the presence of multipath propagation

To process tracking low-altitude targets with the multipath propagation is a difficult task. The difficulty derives from a large number of uncertain knowledge (parameters) such as the radar waveform frequency, the specific signal processing, the surface reflectivity, and the actual target elevation and range, . etc. This paper offers a technique based on the fuzzy logic to solve the uncertain measurement error by the multipath propagation. And we apply the quantitative analysis presenting the degree of multipath effect to achieve the goal we mentioned ahead. Meanwhile, the tracking filter estimation is used to reduce the measurement error by the multipath propagation. After the simulation, the fuzzy-logic-base technique not only can simplify the process of the model building by IMM but also can promote the tracking accuracy.
The Impact of a Local Development Project on Social Capital: Evidence from the Bohol Irrigation Scheme in the Philippines

The purpose of this paper is to investigate the connection between local development projects and the residents’ social capital in Bohol, The Philippines. From this perspective, we hypothesized that social behaviors of local farmers are influenced by the availability of canal irrigation due to the collective water management required in irrigated societies. By combining the results of the ultimatum game (UG) with a household survey on 245 villagers in Bohol, this paper (1) measures the degree of social capital at the individual level and (2) quantifies the effects of irrigation on social capital by controlling household as well as individual characteristics. Moreover, we employed a Spatial Autoregressive model to explore the spatial effects and social contexts of farmers’ behavioral patterns. The empirical results show that the level of measured social behavior is strongly associated with access to community irrigation water and asset holdings. Additionally, increased physical distance between residents leads to a decrease in social capital, or interdependency, among them. The results suggest that community engagement (e.g., irrigation management committee and turnout service association) with local development projects would not only improve agricultural productivity but also enhance social relationships among farmers, highlighting its importance.
Photogrammetry-Based Automated Measurements for Tooth Shape and Occlusion Analysis

Tooth measurements (odontometry) are performed for various scientific and practical applications, including dentistry. Present-day techniques are being increasingly based on 3D model use that provides wider prospects in comparison to measurements on real objects: teeth or their plaster copies. The main advantages emerge through application of new measurement methods which provide the needed degree of non-invasiveness, precision, convenience and details. Tooth measurements have been always regarded as a time-consuming research, even more so with use of new methods due to their wider opportunities. This is where automation becomes essential for further development and implication of measurement techniques. In our research automation in obtaining 3D models and automation of measurements provided essential data that was analysed to suggest recommendations for tooth preparation – one of the most responsible clinical procedures in prosthetic dentistry – within a comparatively short period of time. The original photogrammetric 3D reconstruction system allows to generate 3D models of dental arches, reproduce their closure, or occlusion, and to perform a set of standard measurement in automated mode.