Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Two CommonOutpatient Preparations for Colonoscopy in Children and Youth

Colonoscopies are often performed in children for diagnostic and therapeutic purposes. Our study compared two bowel-cleansing solutions: sodium picosulphate, magnesium oxide, and citric acid (Pico-Salax) with liquid magnesium citrate as preparations for colonoscopy. A retrospective chart review of all patients seen in the Gastroenterology outpatient clinic and who underwent bowel cleansing in preparation for colonoscopy from February to December 2006 was undertaken. Thirty-two children received PicoSalax and 36 received liquid magnesium citrate. The tolerability of both solutions was similar. Most children in both groups had liquid stools and complete colonoscopies. Bowel preparation for a colonoscopy can be successfully achieved using either Pico-Salax or liquid magnesium citrate.
Validation of the Aerosol Model in the ISFRA Module for SFR Accident Analysis : Against the ABCOVE AB 5 Tests

The Korea Atomic Energy Research Institute (KAERI) has developed the design and analysis technique of a pool-type sodium-cooled fast reactor as the prototype Gen-IV sodium-cooled fast reactor (PGSFR), since 1987. [1] Main advantage of the PGSFR is to reduce the radioactive nuclear waste amount from operating nuclear power reactors by transmutation. Other advantages of the PGSFR are the high safety level in the design and the efficient electric power generation. In the safety analysis of the PGSFR, it is essential to predict the behavior of the radioactive fission product (FP) released from the core and estimate exactly the released amount to the environment under postulated nuclear power plant accidents. The Fauske & Associates, LLC (FAI) had developed the ISFRA (Integrated Sodium Fast Reactor Analysis) computer software under the contract with the KAERI by 2016. The ISFRA computer software is a best estimate computing tool used to simulate the consequences of beyond design basis accident transients and postulated severe accidents in the PGSFR. This computer program was designed to be a fast running simulation software used to accurately predict the initial transient and the subsequent release and transport of fission products. [2] The ISFRA code tracks mass of FPs in three forms of the deposited, gas, and aerosol, as in LWR severe accident codes. Since aerosol FPs could be widely generated in the containment compartment during postulated PGSFR severe accidents due to the sudden pressure or temperature decreases when entering into the containment atmosphere, it becomes one of the main concerns in event consequence evaluation to predict the aerosol FP behavior inside the containment and the FP release rate to the environment. The purposes of this study are to evaluate the aerosol behavior models of the ISFRA code and to validate the aerosol models against available experimental data. The results of this study will be used as a basis for the improvement of the ISFRA aerosol models in the future.
A Review on Classification of Breast Cancer Using Various ANN Techniques

In the present situation digital image processing involves a dynamic part in each zone of human survival. Image processing alludes to advance the digital images and mine properties from images. Preparing a digital image will be a challenging job. Image processing technology has been very much possessed in medical innovation however the essential hazard is that mortality is raised owed to cancer. Breast Cancer has turn out to be the most imperative reasons for death in women. Image segmentation depicts an image could be partitioned into areas in light of some comparable attributes like color, texture or intensity. There are different imaging strategies that play an essential part in recognizing breast cancer. This investigation is an endeavor to feature different breast cancer recognition methods in light of image processing technique. Keywords— Breast Cancer, Image Processing, Medical Image, Segmentation.
J an 2 01 7 Distributed Hessian-Free Optimization for Deep Neural Network

Training deep neural network is a high dimensional and a highly non-convex optimization problem. In this paper, we revisit Hessian-free optimization method for deep networks with negative curvature direction detection. We also develop its distributed variant and demonstrate superior scaling potential to SGD, which allows more efficiently utilizing larger computing resources thus enabling large models and faster time to obtain desired solution. We show that these techniques accelerate the training process for both the standard MNIST dataset and also the TIMIT speech recognition problem, demonstrating robust performance with upto an order of magnitude larger batch sizes. This increased scaling potential is illustrated with near l inear speed-up on upto 32 CPU nodes for a simple 4-layer network.
Current status of turbulent dynamo theory From large-scale to small-scale dynamos

Several recent advances in turbulent dynamo theory are reviewed. High resolution simulations of small-scale and large-scale dynamo action in periodic domains are compared with each other and contrasted with similar results at low magnetic Prandtl numbers. It is argued that all the different cases show similarities at intermediate length scales. On the other hand, in the presence of helicity of the turbulence, power develops on large scales, which is not present in non-helical small-scale turbulent dynamos. At small length scales, differences occur in connection with the dissipation cutoff scales associated with the respective value of the magnetic Prandtl number. These differences are found to be independent of whether or not there is large-scale dynamo action. However, large-scale dynamos in homogeneous systems are shown to suffer from resistive slow-down even at intermediate length scales. The results from simulations are connected to mean field theory and its applications. Recent work on magnetic helicity fluxes to alleviate large-scale dynamo quenching, shear dynamos, nonlocal effects and magnetic structures from strong density stratification are highlighted. Several insights which arise from analytic considerations of small-scale dynamos are discussed.
Can Sport and Wellness Technology be My Personal Trainer ? – Teenagers and Digital Coaching

The attention towards digital coaching solutions has increased among users of sport and wellness technologies, the related industry, the healthcare and wellness sector, and among scholars. However, as the commercial digital coaching solutions are rather novel, the number of studies about their influence or the usage experiences is still rather limited. Another topic that is lacking research is the relationship of teenagers and sport and wellness technology. Since using the internet and technological devices on a daily basis has become the norm for teenagers, it is worth paying attention to how technology could be developed in order to better motivate them towards a healthier lifestyle. The purpose of this study was to find out the perceptions of teenagers regarding sport and wellness technology and especially of digital coaching. According to the findings, teenagers perceive digital coaching positively. They prefer instructional guidance and advice especially related to physical activity and nutrition.
PARALLEL CONSTRAINED DELAUNAY MESHING ALGORITHM IN THREE DIMENSIONS

Mesh generation is an integral part of the finite element method and as such it has to be scalable and efficient in order to keep the throughput of the simulation pipeline high. We present an initial design of a three dimensional Parallel Constrained Delaunay Meshing Algorithm that uses mesh decomposition techniques to create work units to be executed in parallel and existing sequential meshing software to refine them (ie, maximum possible code re-use). Asynchronous messages are employed to achieve conformity between shared regions of the work units while keeping the overhead low.
Jaysingpur Robust Model For Text Recognition

We present a semi-Markov model for recognizing scene text that integrates character and word segmentation with recognition. Using wavelet features, it requires only approximate location of the text baseline and font size; no binarization or prior word segmentation is necessary. Our system is aided by a lexicon, yet it also allows non-lexicon words. To facilitate inference with a large lexicon, we use an approximate Viterbi beam search. Our system performs robustly on low-resolution images of signs containing text in fonts atypical of documents.
Approach to partition heterogeneous mobile ad hoc network into homogeneous clusters

In heterogeneous system nodes have different architectures, each of which produced different Qua lity of Service ( QoS). Since nodes have different characteristics, communication is a crucial problem. This difference is huge and can sometimes influence the quality of broadcas ts nd communications. Applying proprietary protocols are difficult in heterogeneous environment because qualities of s ervices offered vary from one node to another. It would mak e it far easier to manage quality of service in a network fo rmed by homogeneous nodes (homogeneous architectures) than manage quality of service throughout the network of heterogeneous nodes. This paper draws this problem and addresses approach to partition nodes by proposing a protocol that allows splitting a heterogeneous mobi le ad hoc environment into several homogeneous clusters. We s how how nodes can be partitioned into several groups formed by members who have similar characteristics, a same de gree of similarity, a same patterns and offer the same qual ity of service.
Dependence relationships modelling in financial appraisal under uncertainty

The modelling of dependence relationships is one of the most difficult processes in simulation models, Dependence relationships are especially important in financial problems under uncertainty conditions. Unfortunately, in complex situations we cannot easily assume mathematical functions –technical relationshipsfor relating cash flow components, like revenues or costs, In an attempt to approach this probleq fuzzy logic is used for designing and modelling “fuzzy” relationships between selected financial parameters. A fiwzy inference engine has now been included in the PRAPPIS V2.0 software for project appraisal under risky and uncertainty conditions. This engine can assess relationships using a set of basic fuzzy rules that control their behaviour in a given context, Fuzzy relationships are easily defined by the user or decision maker guided by a natural language system. Mizumoto’s approach is used to obtain fmzy relationship results and standard Monte Carlo simulation is applied to assess the financial project. Statistical distributions of many financial parameters are available in PRAPPIS with or without dependence relationships. In this paper, different results are shown corresponding to different statistical distributions of financial parameters using a first set of fuzzy inference rules called here “neutral” in comparison to standard Monte Carlo simulation assuming independent statistical distributions. In an agricultural environment, which is uncertain, we have chosen some controlled relations between two selected parameters such as, for example, part-time hand labour in harvesting and production, Results show that the variance of the statistical distributions in the project results is reduced if fhzzy relationships are used. © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email witpress@witpress.com Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1
Interactive comment on “ SWAT Modeling of Water Quantity and Quality in the Tennessee River Basin : Spatiotemporal Calibration and Validation ”

The manuscript outlines a framework for modeling water quantity and quality applying the Soil and Water Assessment tool (SWAT) to large river basins in the United States. The authors demonstrate their procedure with a case study in the Tennessee River Basin. To overcome shortcomings that are typical in such studies, for instance limitations in calibration data in terms of temporal and spatial resolution or the type of measured parameters, the authors state three innovations implemented in the study: 1) A parameter optimization framework was set up incorporating Shuffled Complex Evolution (SCE) as an optimization routine for SWAT that can provide intermediate response variables (variables that would not be recorded in the SWAT output files) for calibration.
Spectroscopic Analysis and Antimicrobial Studies for New Metal Oxytetracycline Drug Complexes

Metals and metal complexes have played a key role in the development of modern chemotherapy[1, 2],For example, complexation of non-steroidal anti-inflammatory drugs to copper overcomes some of the gastric side effects of these drugs[3-7]. A number of drugs and potential pharmaceutical agents also contain metal-binding or metal-recognition sites, which can bind or interact with metal ions and potentially influence their bioactivities and might also cause damages on their target biomolecules. Numerous examples of these metallo drugs and metallo pharmaceuticals and their actions can be found in the literature, for instance: (a) several anti-inflammatory drugs, such as aspirin and its metabolite salicylglycine [8-11], suprofen[12], and paracetamol [13], are known to bind metal ions and affect their antioxidant and anti-inflammatory activities; (b) the potent histamine-H2-receptor antagonist cimetidine [14] can form complexes with Cu 2+
Neuromuscular Fatigue and Biomechanical Alterations during High-Intensity, Constant-Load Cycling

i DECLARATION . v COPYRIGHT AND ACCESS STATEMENT . vi ACKNOWLEDGMENTS . viii TABLE OF CONTENTS . x LIST OF TABLES . xiv LIST OF FIGURES . xv LIST OF PUBLICATIONS . xvi CHAPTER ONE .
HER 1 R 497 K and HER 2 I 655 V polymorphisms are linked to development of breast cancer

BACKGROUND: Polymorphism of the genes of Human Epidermal growth factor receptor1 (HER1) and receptor2 (HER2) have been reported to be linked to pathogenesis of several malignant tumors but still there is contradiction regarding their association with breast cancer. OBJECTIVE: In this case control study we aimed to analyze the frequency of HER1 R497K (rs 11543848) and HER2 I655V (rs 1136201) Polymorphisms in breast cancer. SUBJECT AND METHOD: The frequency of HER1 Arg(R) 497Lys (K) and HER2 Ile (I) 655Val (V) polymorphisms were tested in 64 breast cancer patients and 86 normal control by polymerase chain reaction followed by restriction fragment polymorphism detection. Immunohistochemical analysis was done for HER2 protein on the available 18 malignant tissue samples. RESULTS: HER1 497K and HER2 655V variant had significantly increased breast cancer risk (OR = 2.6, 95% CI 1.6–4.2, OR = 2.2, 95% CI 1.2–4.1, p < 0.05) respectively. Moreover, combined HER1K497 and HER2 V655 variant was detected in 26.6% malignant in comparison to 8.14% of control group (OR = 4.1, 95% CI 1.58–10.57), but, no significant association was noticed between both Polymorphisms and clinicopathological features of the disease. As regard HER2 immunohistochemical expression no significant correlation was revealed with HER2 655V polymorphism. CONCLUSIONS: Our findings suggest that HER1 497K and HER2 655V polymorphisms are potential risk factor for development of breast cancer.
Using Multi-Layer Perceptrons for Analysis of Labour Data

This paper presents a case study, which explores factors affecting employment of Irish population, using data from quarterly national household survey containing 199,264 records and 115 variables. After data clensing and variable selection, predictor variables were grouped as demographic, educational, and occupational. We used MLP neural network to buid predictive models that fit data in order to explore interactions between the variables and to provide insight on their role in employment. We estimated variable significance, reduced dimensionality, and selected optimal neural network architecture. The model predictive abilities were esimated by accuracy, ROC analysis, and AUC. In order to provide solid results, we applied rigorous testing procedure combining two testing partitions, crossvlidation and iterations. Our results show that the MLP model outperforms logistic regression and linear discriminant analysis. We also did VEC analysis of the most significant factors of employment and commented on their characteristics.
CONVERGENCE RATES FOR `-REGULARIZATION WITHOUT THE HELP OF A VARIATIONAL INEQUALITY∗

We show that convergence rates for `1-regularization can be obtained in an elementary way without requiring a classical source condition and without the help of a variational inequality. For the specific case of a diagonal operator we improve the convergence rate found in the literature and conduct numerical experiments that illustrate the predicted rate. The idea of the proof is rather generic and might be used in other settings as well.
Active Sampling for Planetary Rover Exploration

Planetary Robotics research has expanded beyond simply developing robust navigation strategies for rovers to providing them with the capability of performing intelligent actions so as to develop a better interpretation and understanding of the environment. This will become essential in the future, when rovers explore regions far away from Earth, at distances that would significantly throttle communication with human operators. This research focuses on two problems of interest: Spatio-Spectral Exploration and Active Spectral Reconstruction. For both of these problems we develop a Markov Decision Process framework reliant on using remote sensing measurements that circumvents the partial observability present in these problems. Further, we propose a Monte-Carlo Tree Search based approach for efficiently sampling relevant locations so as to solve these problems. We demonstrate our approach in simulation as well as testing it with the rover Zoë at a Mars-analogous terrain located at Cuprite, NV and highlight its advantages compared to traditional planning strategies.
Management of the critically ill child with the sepsis/hemophagocytic lymphohistiocytosis/macrophage activation syndrome overlap syndrome

Abstract Hemophagocytic lymphohistiocytosis (HLH) or macrophage activation syndrome (MAS) is a frequently fatal disease, which can result in end-organ damage and death. This condition shares features with sepsis and systemic inflammatory response syndrome. Making a diagnosis of HLH can be challenging since most of the clinical and laboratory features of HLH are quite nonspecific. Timely diagnosis is critical to start therapy before damage by hypercytokinemia becomes irreversible. The treatment for patients with suspected acquired HLH/sepsis/systemic inflammatory response syndrome/multi organ dysfunction syndrome/ MAS overlap syndrome should be guided primarily by the severity of signs and symptoms, age of the patient, and underlying conditions. It is critical that the risks of treatment or non-treatment be weighed according to the clinical presentation of each patient. In this article, the authors discuss the diagnostic similarities between sepsis/HLH/MAS and management of the critically ill child with sepsis/HLH/MAS overlap syndrome.
Effects of Consumer Lifestyles on Purchasing Behavior on the Internet : A Conceptual Framework and Empirical Validation

The purpose of this research is (1) to develop a theoretical model for consumer purchasing behavior on the Internet and (2) to test the effects of consumer lifestyles in the form of price-oriented, net-oriented, and timeoriented lifestyles, and perceived benefit and perceived risk on purchasing behavior. Structural equation modeling is applied to test a hypothesized research model using Graphics Visualization and Usability Center (GVUC) online survey data. Results show that a consumer whose lifestyle is more net-oriented will perceive more benefits and fewer risks to online purchasing. Consumers who are more time-oriented will perceive more benefits to buying goods online than less time-oriented ones. Consumers who have more disposable income are also more prone to purchase online.
Robots Induce Mimicry in Humans

This study explores human-robot interaction in terms of behavioral mimicry the imitation of gestures, postures, mannerisms, and other motor movements. We conducted an experiment looking at how much humans mimicked a robot during the task of describing paintings. We compared the time a participant performed a behavior (hands on hips or hands behind back) before and after observing a robot perform that behavior. We identified two groups of people, those who spontaneously performed the behaviors before seeing a robot display them and those who did not. We find that humans mimic a robot more after observing it perform a behavior if they did not spontaneously display that behavior before seeing the robot do so. Interestingly, we also find that humans spontaneously performing a behavior before seeing a robot do so actually display that behavior less after seeing the robot perform it.
Traffic Analysis Attacks on Skype VoIP Calls

Follow this and additional works at: https://engagedscholarship.csuohio. edu/enece_facpub Part of the Digital Communications and Networking Commons How does access to this work benefit you? Let us know! Publisher's Statement NOTICE: this is the author’s version of a work that was accepted for publication in Computer Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Communications, 34, 10, (07-01-2011); 10.1016/j.comcom. 2010.12. 007
24 48 v 1 [ gr-q c ] 1 0 Se p 20 13 Rotating Wormholes in Five Dimensions

Vladimir Dzhunushaliev, Vladimir Folomeev, Burkhard Kleihaus , Jutta Kunz1, and Eugen Radu 1 Institut für Physik, Universität Oldenburg, Postfach 2503, D-26111 Oldenburg, Germany 2 Dept. Theor. and Nucl. Phys., KazNU, Almaty, 010008, Kazakhstan Institute of Physicotechnical Problems and Material Science of the NAS of the Kyrgyz Republic, 265 a, Chui Street, Bishkek, 720071, Kyrgyz Republic (Dated: September 11, 2013)