Miracle-dz/UniFAR-FTUs huggingface dataset:
Impacts of vigorous and non-vigorous activity on daily energy expenditure

Activity intensity is a potential determinant of activity-induced energy expenditure. Tri-axial accelerometery is the most objective measurement technique for the assessment of activity intensity, in combination with doubly-labelled water for the measurement of energy expenditure under free-living conditions. Data on the effects of subject characteristics, including body size and age, and exercise training on the relationship between activity intensity and daily energy expenditure are reviewed. Average daily metabolic rate and non-basal energy expenditure are positively related to body size. The duration and intensity of physical activities do not need to be equivalent to the energy spent on activity. Obese subjects spend more energy on physical activity but can perform fewer activities, especially high-intensity (weight-bearing) activities, because of their higher body weight. Physical activity generally declines gradually from about 60 years of age onwards. Most subjects >80 years have an activity level well below the level defined for sedentary middle-aged adults. Spending relatively more time on low-intensity activities has a negative effect on the mean physical activity level. To obtain a higher physical activity level does not necessarily imply high-intensity activities. In an average subject 25% of the activity-induced energy expenditure may be attributed to high-intensity activities. Exercise training, as a form of high-intensity activity, affects the physical activity level more in younger subjects than in elderly subjects.
2014 First-trimester ultrasound forum from the Korean Society of Ultrasound in Obstetrics and Gynecology

A first-trimester ultrasound scan has become an essential part of antenatal care. The Korean Society of Ultrasound in Obstetrics and Gynecology held a first-trimester ultrasound forum on April 5, 2014. The forum aimed to present an updated review of the literature on the topic of first-trimester ultrasound in specific lectures and to host a panel discussion on several important issues regarding first-trimester scans. The forum provided evidence- and consensus-based best practice patterns for obstetricians in Korea. Here, we report the review and checklists presented from the forum.
Detection of Scale Intervals in Digital Images

If an image includes a ruler and some objects, we can estimate the size of the objects manually. In order to achieve a more accurate result, we developed a method for detecting scale intervals on the ruler. In our method, we transfer the digital image into a frequency domain by using Discrete Fourier Transform (DFT) so that a specific frequency appears. This requires that the image has a cyclic pattern such as the scale on a ruler. We can subsequently calculate the scale interval from the detected frequency.
Enhancing Positioning Accuracy through Direct Position Estimators Based on Hybrid RSS Data Fusion

In this paper, localization based on Received Signal Strength (RSS) is investigated assuming a path loss log normal shadowing model. On the one hand, indirect RSS-based estimation schemes are investigated; these schemes are based on two steps of estimation: estimation of ranges from RSS and then estimation of position using weighted least square approximation. We show that the performances of this type of schemes depend on the used estimator in the first step. We suggest that typical median estimator must be replaced by maximum likelihood estimator (mode) to enhance the positioning accuracy. On the other hand, a new direct RSS-based estimation scheme of position is proposed; Monte Carlo simulations show that the new estimator performs better than indirect estimators and can be reliable in future hybrid localization systems.
Visuo-Spatial Imagery Impairment in Posterior Cortical Atrophy: A Cognitive and SPECT Study

This study investigated the cognitive profile and the cerebral perfusion pattern in a highly educated 70 year old gentleman with posterior cortical atrophy (PCA). Visuo-perceptual abilities, spatial memory, spatial representation and navigation, visuo-spatial mental imagery, semantic and episodic-autobiographical memory were assessed. Regional cerebral blood flow (rCBF) was imaged with SPECT. Cognitive testing showed visual-perceptual impairment, apperceptive visual and landmark agnosia, topographical disorientation with way-finding deficits, impaired map learning and poor mental image generation. Semantic memory was normal, while episodic-autobiographical memory was impaired. Reduced rCBF was found mainly in the right hemisphere, in the precentral gyrus, posterior cingulate and middle temporal gyri, cuneus and precuneus, in the left superior temporal and lingual gyri and in the parahippocampus bilaterally. Hypoperfusion in occipito-parietal regions was associated with visuo-spatial deficits, whereas deficits in visuo-spatial mental imagery might reflect dysfunction related to hypoperfusion in the parahippocampus and precuneus, structures which are responsible for spatial and imagery processing. Dissociating performance between preserved semantic memory and poor episodic-autobiographical recall is consistent with a pattern of normal perfusion in frontal and anterior temporal regions but abnormal rCBF in the parahippocampi. The present findings indicate that PCA involves visuo-spatial imagery deficits and provide further validation to current neuro-cognitive models of spatial representation and topographical disorientation.
9.2.2 Challenges in supporting the creation of data minable regulatory codes: a literature review

As standards and regulatory codes are issued by third party organizations and committees, the project organization can neither control the content of all standards that the projects should adhere to, nor negotiate or make changes to them that can make the project development easier. Moreover, large infrastructure projects require compliance with hundreds of standards of regulations coming from different agencies, with different styles and structures. A new approach is needed, one that results in well written, easily mined standard and codes. In this paper, we report on findings from an exhaustive literature survey that reveals that the area of supporting drafting of regulatory codes for the purpose of making them more data minable has not yet been explored.
Low-Intensity Light Therapy (1068 nm) Protects CAD Neuroblastoma Cells from Î²-Amyloid-Mediated Cell Death

Using a simple in vitro amyloidopathy CAD neuronal model, infrared (IR) 1068 nm light treatment (5 x 3 minutes) was investigated as a novel neuroprotection strategy. Synthetic human β-amyloid(1-42) peptide was subjected to aggregation in a test-tube, and shown to form fibrils of a range of sizes (individually ~10 μm), which compromised the cellular nuclear integrity of CAD cells in culture, and elicited a dose-dependent neurotoxicity (β-amyloid(1-42) peptide concentration range 0-25 μM) up to 73%, which was significantly suppressed (up to 24%; p<0.001) by prior treatment with IR1068.
Predicting Axonal Response to Molecular Gradients with a Computational Model of Filopodial Dynamics

Axons are often guided to their targets in the developing nervous system by attractive or repulsive molecular concentration gradients. We propose a computational model for gradient sensing and directed movement of the growth cone mediated by filopodia. We show that relatively simple mechanisms are sufficient to generate realistic trajectories for both the short-term response of axons to steep gradients and the long-term response of axons to shallow gradients. The model makes testable predictions for axonal response to attractive and repulsive gradients of different concentrations and steepness, the size of the intracellular amplification of the gradient signal, and the differences in intracellular signaling required for repulsive versus attractive turning.
Embedded systems in the application of fog computing — Levee monitoring use case

The goal of this paper is to discuss the application of fog computing concept realized with embedded systems for environment monitoring in case of emergency situations such as flood, earthquakes, landslides, etc. We also present a practical realization of a hardware-software platform for such a system by applying the described ideas to a smart levee monitoring station. The realization of our concept is based on a multi-variant embedded platform for an autonomous data acquisition and processing station. The system is being tested in an experimental setup in a life-size artificial levee.
Serum C-Reactive Protein Concentration and Genotype in Relation to Ischemic Stroke Subtype

Background and Purpose— C-reactive protein (CRP) has evolved as an inflammatory risk marker of cardiovascular disease. Several single-nucleotide polymorphisms at the CRP locus have been found to be associated with CRP levels. The aim of the present study was to investigate CRP levels and genetic variants in etiological subtypes of ischemic stroke. Methods— The Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS) comprises 600 consecutive ischemic stroke cases (18 to 69 years) and 600 matched controls from western Sweden. Stroke subtypes were defined by the TOAST classification. Serum CRP levels were determined by a high-sensitivity immunometric assay. Results— CRP levels were significantly higher for all ischemic stroke subtypes compared with controls, both in the acute phase and at the 3-month follow-up. After adjustment for traditional risk factors, CRP at follow-up was related to higher odds ratios (ORs) of overall ischemic stroke (OR, 1.25; 95% CI, 1.09 to 1.43) and large-vessel disease (OR, 1.48; 95% CI, 1.09 to 2.00). The CRP −286C>T>A, 1059G>C, and 1444C>T single-nucleotide polymorphisms showed significant associations with CRP levels. However, neither CRP genotypes nor haplotypes showed an association to overall ischemic stroke. Conclusions— This is the first large study on CRP in different TOAST subtypes in a young ischemic stroke population. CRP levels differed between etiological subtypes of ischemic stroke both in the acute phase and at the 3-month follow-up. CRP at follow-up was associated with overall ischemic stroke and the large-vessel disease subtype. Genetic variants at the CRP locus were associated with CRP levels, but no association was detected for overall ischemic stroke.
Real-time baseline wander removal in ECG signal based on weighted local linear regression smoothing

Removing the baseline wander (BW) is vital in electrocardiogram (ECG) preprocessing steps, since it can severely influence the diagnostic results, especially in computer based diagnoses. This paper presents a method based on weighted local regression smoothing to correct BW in real time. Each signal data sample within a certain window is weighted. The weight of each sample is determined by the distance between the sample and the to-be-predicted sample. Then the regression is adopted by performing linear least-squares and a polynomial model to estimate BW. The ECG signal free from BW is obtained by subtracting the BW from the original ECG signal. The experiment results demonstrate that this method can effectively remove BW in ECG signal in real time and with minimum distortion of ECG waveform.
A Novel Approach to Grid Service Composition with QoS Global Optimization

Automatic service composition is an important issue in the field of grid, which enables individual services to be composed together to provide the end user a more powerful service, which would significantly improve the service reuse. This paper proposes a novel service composition approach based on QoS global optimization which tackles the QoS-aware composition optimization problem using ACO algorithm. The experimental results show that our model is effective and our approach to search the solution outperforms GA.
The dynamics of learning alliances: competition, cooperation, and relative scope

We show how the tension between cooperation and competition affects the dynamics of learning alliances. 'Private benefits' and 'common benefits' differ in the incentives that they create for investment in learning. The competitive aspects of alliances are most severe when a firm's ratio of private to common benefits is high. We introduce a measure, 'relative scope' of a firm in an alliance, to show that the opportunity set of each firm outside an alliance crucially impacts its behavior within the alliance. Finally, we suggest why firms might deviate from the theoretically optimal behavior patterns. 1998 John Wiley & Sons, Ltd.
On cover times for 2 D lattices ∗

We study the cover time τcov by (continuous-time) random walk on the 2D box of side length n with wired boundary or on the 2D torus, and show that in both cases with probability approaching 1 as n increases, √ τcov = √ 2n2[ √ 2/π logn + O(log log n)]. This improves a result of Dembo, Peres, Rosen, and Zeitouni (2004) and makes progress towards a conjecture of Bramson and Zeitouni (2009).
Mobile Software Platform for Rural Health Enhancement

The patients in rural areas lose their lives due to the unavailability of proper healthcare at the right time. This research work aims to develop a system suitable for continuous and real-time monitoring of rural patients to enhance healthcare facilities. The proposed system integrates existing and freely available mobile technology with wearable wireless sensors for patient monitoring. This research work has designed and developed a mobile software platform for continuous and real-time monitoring of rural patients. The prototype platform has been enhanced by integrating power optimizing and risk based data collection and transmitting methodologies. The system also provides an emergency warning message to the doctor's mobile phone. This proposed system collects the patient's health related sensor details in mobile phone, performs a first level analysis of the collected data, and transmits it to a central server for further processing. The system also enables the doctor to receive and view patient's ECG reports to a mobile phone. This paper introduces a dynamic algorithm to increase the battery life of a health monitoring mobile phone.
Low cost design of HF-band RFID system for mobile robot self-localization based on multiple readers and tags

In this paper, we focus on configuring a low cost RFID (Radio Frequency IDentification) system with less RFID readers and low density RFID tag textiles for stable and accurate self-localization for an omni-directional mobile robot. An RFID system using multiple RFID readers and high density RFID tags has already been applied to an indoor mobile robot self-localization. However, the system production cost is relatively high. To reduce the production cost of the system while maintaining the self-localization performance, we redesign two new RFID systems configured with 20 RFID readers and 5 RFID readers enlarging the size of an RFID reader antenna. Particularly, a new likelihood function of the tag detection with the redesigned large size RFID reader antenna is proposed for Monte Carlo Localization (MCL). Furthermore, we come up with a novel arrangement of RFID tags installed in a hexagon pattern. The new arrangement of ID tags enables both low cost ID tag installation and high performance of self-localization. We examine the performances of robot self-localization with less RFID readers and lower density RFID tags installed on the floor based on MCL(Monte Carlo localization). The simulation demonstrates the validity of our proposed configuration of the RFID based self-localization.
Uncertainty and Investment in Electricity Generation: the Case of Hydro-Québec

World wide the electricity industry is undergoing a substantial process of restructuring, with an emphasis on the introduction of competition in the generation sector. Competition is ostensibly going to lead to better incentives, both in the use of existing resources and in future investment decisions. One of the main drivers of this new environment will be the increased opportunity for energy sales between what had been, before the introduction of competition, fairly closed markets. These new opportunities may lead to new investments in generation and transmission capacity which will occur in order to take advantage of cost differentials between regions, one of the driving factors in the call for restructuring. Accounting for some of the underlying complexity of electricity systems, specifically equipment availability and load duration curves, this paper illustrates how uncertainty affects investment in generation. We offer a simple 2-region model to analyse this problem, based on the linear programming model of Chaton (1997). Specifically, we analyse the case where one region has access to four generation technologies, differentiated by cost characteristics as well as construction lead times. A second (neighbouring) region has access to only one of the generation technologies, hence the necessary asymmetry between producing regions. Uncertainty is present in the demand for energy in the first market, as well as in the input fuel prices. Given this uncertainty, and the possibility of electricity sales between regions, we investigate and characterise optimal generation investment in the first market as a function of the problem parameters. The model is calibrated with data from Hydro-Quebec and the northeastern United States. This application is particularly interesting and relevant, given the abundance of relatively cheap hydroelectric power in Quebec, and Hydro-Quebec’s self-proclaimed strategic interests in increasing its exports to the northeastern markets. The numerical example illustrates the importance of appropriately modelling the complexity of the electrical system when considering the impacts of restructuring.
Automatic Definition of Modular Neural Networks

This article illustrates an artificial developmental system that is a computationally efficient technique for the automatic generation of complex artificial neural networks (ANNs). The artificial developmental system can develop a graph grammar into a modular ANN made of a combination of simpler subnetworks. A genetic algorithm is used to evolve coded grammars that generate ANNs for controlling six-legged robot locomotion. A mechanism for the automatic definition of neural subnetworks is incorporated Using this mechanism, the genetic algorithm can automatically decompose a problem into subproblems, generate a subANN for solving the subproblem, and instantiate copies of this subANN to build a higher-level ANN that solves the problem. We report some simulation results showing that the same problem cannot be solved if the mechanism for automatic definition of subnetworks is suppressed. We support our argument with pictures that describe the steps of development, how ANN structures are evolved, and how the ANNs compute.
‘Won't get fooled again’: How personal values shape leadership purpose, behavior and legacy

While much has been documented about the construction of an individual's personal values, very little attention has been paid to how personal values connect with core aspects of leadership such as purpose, behavior and legacy. Through an expansion of Ken's recent work on this topic, the authors explore the impact of personal values-led leadership. A model of how personal values shape leadership purpose, behavior and legacy is introduced. These dimensions are then illuminated through interview data from senior managers from the financial services sector. The personal value impacts are examined in the context of the literature and implications for organizations and managers are drawn together.
A Portrait of Race and Ethnicity in California: An Assessment of Social and Economic Well-Being.

The Public Policy Institute of California (PPIC) is a private operating foundation established in 1994 with an endowment from William R. Hewlett. The Institute is dedicated to improving public policy in California through independent, objective, nonpartisan research. PPIC's research agenda focuses on three program areas: population, economy, and governance and public finance. Studies within these programs are examining the underlying forces shaping California's future, cutting across a wide range of public policy concerns, including education, Arjay Miller—recognized the need for linking objective research to the realities of California public policy. Their goal was to help the state's leaders better understand the intricacies and implications of contemporary issues and make informed public policy decisions when confronted with challenges in the future. A portrait of race and ethnicity in California : an assessment of social and economic well-being / Belinda I. Short sections of text, not to exceed three paragraphs, may be quoted without written permission provided that full attribution is given to the source and the above copyright notice is included. iii Foreword I n 1999, a team of PPIC research fellows led by Belinda I. Reyes began preparing a demographic portrait of California with special attention to the social and economic well-being of its major racial and ethnic groups. This volume is the result of that effort. It depicts an increasingly diverse California whose residents have experienced broad though uneven progress in health, educational attainment, crime reduction, and political participation. The volume's impressive scope and consistent format allow its readers to follow both the progress of—and persistent inequalities among—California's racial and ethnic groups in these and other areas. Its clear, graphic, and colorful presentation will serve the state's business, policy, media, and scholarly communities equally well. This volume would not have been possible without the expertise developed by PPIC research fellows over the institution's first six years. Dozens of databases, substantial computer capability, and a good deal of knowledge-sharing were required to compile the data and complete the portrait in less than a year and a half. PPIC's goal has been to replace clichés and caricatures with reliable information about the state's population and policies. This useful reference volume is a notable example of that effort. v vii Summary T his book documents differences in socioeconomic status by racial and ethnic groups and explores how patterns have changed over time. The data in this compendium will provide us with a …
Characterizing Physical Activity in a Health Social Network

New horizons are emerging within healthcare delivery, education, intervention provision, and tracking. We study a health social network that has tracked physical activities, biomarkers, and posts the participants have shared, throughout a one-year program. The program was aimed at helping people to adopt healthy behaviors and to lose weight. In this paper, we focus on users' posts that relate to physical activities. Prior papers characterize health based solely on users' information disclosed through natural language or questionnaires. The drawback of these works is their lack of medical records or health-related information to validate their findings. By contrast, with our direct access to users' physical and medical data, we investigate the implication of users' posts at both individual and group levels. We are able to validate our hypotheses about the effects of certain social network activities, by contextualizing them in the specific users' actual medical progress and documented levels of exercise. Our findings show that activity self-disclosure posts are good indicators of one's real-world physical activity, which makes them good resources for monitoring the participants. In addition, using a physical activity propagation model, we show how these posts can influence the physical activity behavior at the network level. Further, posts exhibit distinctive affective, biological, and linguistic style markers. We observe that these characteristics can be used in a predictive capacity, to detect positive activity signals with ~88% accuracy, which can be utilized for an unobtrusive monitoring solution.