Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution of gestational age – specific rates of preterm cesarean delivery and preterm birth from 1990 through 2004 in United States Variable Rates of preterm cesarean delivery , % 1990 1995 2000

From the Division of Epidemiology and Biostatistics, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Medicine and Dentistry of New Jersey–Robert Wood Johnson Medical School, New Brunswick, NJ (Dr Ananth), and the Department of Obstetrics and Gynecology, Winthrop-University Hospital, Mineola, NY (Dr Vintzileos). Presented, in part, at the 30th Annual Meeting of the Society for Maternal-Fetal Medicine, Chicago, IL, Feb. 1-6, 2010. Received Nov. 18, 2010; revised Jan. 4, 2011; accepted Jan. 31, 2011. Reprints: Cande V. Ananth, PhD, MPH, Division of Epidemiology and Biostatistics, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, 125 Paterson St., New Brunswick, NJ 08901-1977. cande.ananth@umdnj.edu. 0002-9378/$36.00 © 2011 Mosby, Inc. All rights reserved. vaginal birth following a previous cesarean. Such increases in cesarean delivery ave been observed in both low-risk and high-risk populations, including among women who delivered very low birthweight ( 1500 g) and macrosomic infants, breech presentations, multiple irths, and in pregnancies with an aray of maternal and fetal indications for esarean. Concurrent with an increase in cesarean deliveries is the temporal increase in the rate of preterm births in the United States and most other industrialized countries. Obstetrical interventions at preterm gestational ages are performed in the setting of impending fetal compromise (or maternal indications warranting such interventions), and these interventions include either a labor induction or a prelabor cesarean or both. The increase in preterm births in the United States has occurred with a concurrent temporal increase in the rate of indicated preterm births. For instance, from 1989 through 2000, indicated preterm births at 37 weeks among singleton gestations in the United States increased by approximately 50%. In act, some investigators have interpreted birth rate to be
The Effect of Different Doses of Oral Salinomycin on Oxidative Stress Biomarkers in Sheep

Salinomycin is a substance which is able to transport particular substance with antimicrobial properties. It is a dietary additive used as a growth promoter for ruminants and as a Veterinary Medicine in chickens. However, over dosage or misuse situations can lead to a series of toxic syndromes. The purpose of this study is to propose the alteration of oxidative stress markers during experimental toxicosis with salinomycin in sheep. Twenty Iranian mixed breed adult female fat-tailed sheep (BW: 36 ± 3.5 kg) were used in this study. Sheep were randomly divided into five equal groups. Group I (control) received 20 ml normal saline. Groups II, III, IV and V were orally administered 1 mg/kg (twice a day for two days), 2, 3 and 4 mg/kg (once a day for two days) salinomycin, respectively. Following drug administration, blood samples were collected at different time intervals (2, 5, 8, 14 and 21 days) in order to determine oxidative stress markers, SOD, GPX, Catalase, and MDA were measured using validated standard methods. The results indicated a significant decrease in SOD, GPX and Catalase, and an increase in MDA in salinomycin treated groups compared to control group (P<0.05). In addition, salinomycin induced significant decrease in the concentration of vitamin C. Concentrations of vitamin A and vitamin E were also increased, but the increase was not significant. The interaction between times and groups was significant with respect to all vitamins. In conclusion salinomycin intoxication in sheep can cause oxidative stress.
Plant Community Development in a Dryland CREP in Northeastern Oregon

Riparian areas in dryland crop regions of the Intermountain Pacific Northwest have largely been converted to cropland or pasture during the last 140 years. Some formerly cultivated floodplains have become difficult to farm; enrollment of these lands into conservation programs provides the opportunity to use them as wildlife habitat and as buffer areas near streams. Our objective was to evaluate plant community development on an USDA Conservation Reserve Enhan- cement Program site in northeastern Oregon from when the plant was planted in 1999 through 2008. The research was designed as a descriptive study. We established permanent line-transects to quantify vegetation establishment and changes in species composition through time. We collected data in 2000-2001 and 2007-2008. Vegetation cover in 2000-2001 was 100%, dominated by tall wheatgrass. Living plant material cover decreased from 98% in 2000-2001 to 33% in 2007 and 68% in 2008; dead plant residue significantly increased and tall wheatgrass cover decreased. Native species were present in similar percentages from 2000 to 2008, although there was a shift from target to nontarget species. The 1999 seeding can be judged a success because of the ground cover provided and the establishment of one target species, tall wheatgrass. However, the increased ratio of dead to living plant material and shift to non-target annual weed species suggests that more active management (i.e., fire, grazing, or mowing) of the tall wheatgrass stand is needed to maintain its productivity and/or a healthy mix of multiple species.
Improvement of the accuracy of determining movement parameters of cuts on classification humps by methods of video analysis

The study proves that it is necessity to develop and specify the procedures of using a synthesis of the methods of optical flow and background subtraction in the case of controlling objects of complex shapes on a changing background and in the presence of small moving objects that are not subject to tracking. Research in this area can yield significant results to automate the movement parameters control over objects such as railway transport. For the described conditions of practical use, it is most of all advisable to synthesize the classical Lucas-Kanade method of optical flow and the Horn-Schunck method for segmenting the frames and identifying control zones. The study describes the procedures of choosing the size of control zones and analysing a joint movement in these areas, which makes it possible to identify the movement of a cut even if the cut has been formed from different categories of wagons. The suggested algorithms were tested on the classification hump at Odesa – the Classifying Section station (Ukraine). The obtained quantitative characteristics of the accuracy of recognizing cuts show that the conditional probability of correct work of the suggested approach is 0.8332, compared with 0.44 in the case of the classical Horn-Schunck method under the same conditions.
Studying the Motivational Beliefs as Predictor Variables in Math Academic Performance

The aim of this study was to investigate the Motivational Beliefs as Predictor Variables in Math Academic Performance. The statistical population of the study consisted of all junior high school students in Bandar Abbas in the first educational district in the academic years 2015-16. The sample consisted of 418 students, including 191 girls and 227 boys who were selected using multistage cluster sampling method. The required information to explain the three components of motivational beliefs, such as self-efficacy, intrinsic valuing and test anxiety were collected through a series of 25 questions of the Motivational Strategies for Learning questionnaire (MSLQ) (Pintrich and DeGroot, 1990). Results show that the average of continuous score for female students in math is 15.37 and for male students is 13.14. Standard deviation for continuous grades among girls is 3.5 and for boys is 4.19. Since the obtained p-value for all the research variables is a number greater than 0.05, there is no reason to reject the null hypothesis (H0) and the assumption of normality is confirmed for all variables. Also, results show that there is no difference between the aggression reduction pre-test in the test and control groups. But there is a significant difference in the aggression reduction post-test in the test and control groups with the control of aggression reduction pre-test with F value of 2426.21 at p <0.001. Also, the effect size difference between the two groups is 0.97 and that the amount of the difference is extremely high and demonstrates the effectiveness of the experiment
Multiobjective shape optimization of selected coupled problems by means of evolutionary algorithms

In present paper an improved multi-objective evolutionary algorithm is used for Pareto optimization of selected coupled problems. Coupling of mechanical, electrical and thermal fields is considered. Boundary-value problems of the thermo-elasticity, piezoelectricity and electro-thermo-elasticity are solved by means of finite element method (FEM). Ansys Multiphysics and MSC.Mentat/Marc software are used to solve considered coupled problems. Suitable interfaces between optimization tool and the FEM software are created. Different types of functionals are formulated on the basis of results obtained from the coupled field analysis. Functionals depending on the area or volume of the structure are also proposed. Parametric curves NURBS are used to model some optimized structures. Numerical examples for exemplary three-objective optimization are presented in the paper.
Cognitive Dysfunction and Ph ysical Activity After Stroke : The Gothenburg Cognitive Stroke Study in the Elderly Ulrika P ahlman , MSc , * † Marianne S € avborg , MSc , * and

652 This study explored the association between cognitive and executive dysfunction and level ofphysical activity 1 year after stroke.Cognitionbefore stroke and cognitive andexecutive function in the acutephase andat 1year after strokewere assessed in 74 subjects. Physical activitywas assessed at 1 year after stroke. Factors that appeared to predict low level of physical activity at 1 year after stroke were impaired global cognition before stroke, visual neglect and impaired logical deductive ability in the acute phase, and impaired global cognition, executive function, and visual memory 1 year after stroke. Our findings underscore the importance of identifying stroke patients with impaired cognitive and executive function who are at risk for developing inactivity.
Effective algorithm for constructing associative rules@@@Effective algorithm for constructing associative rules

Constructing associative rules is one of the most important algorithms for extracting knowledge from databases. All modern algorithms are somehow connected with Apriori algorithm proposed in R. Agrawal’s and his co-authors’ works published more than 20 years ago and now considered classical. The known effective implementations of the algorithm are connected with database compression and presentation of data structure as a tree, which allows effective evaluation of support and other characteristics of associative rules. The proposed ConApriori algorithm does not use the above idea. We regard database transactions as enumeration given by a scale. This allows instant calculation of the basic algorithm operation determining whether some set is a subset of another set or not. The calculations are reduced to several logical computer commands. Enumeration also allows us to treat the transaction in the internal presentation as a number, preserving the meaning of the transaction elements in their external presentation at the same time. Another idea used in the algorithm allows us to construct most of the confident rules on the basis of those previously built. This article provides evidence for correctness of the algorithm as well as evaluate its complexity. We analyze its effectiveness compared with other known algorithm implementations. Possibility of parallelization is also considered.
Author ’ s Accepted Manuscript Efficient k NN Classification Algorithm for Big Data

K nearest neighbors (kNN) is an efficient lazy learning algorithm and has successfully been developed in real applications. It is very natural to scale the previous kNN method to the large scale datasets. In this paper, we propose to first conduct a k-means clustering to separate the whole dataset into several parts, each of which is then conducted kNN classification. We conduct sets of experiments on big data and medical imaging data. The experimental results show that the proposed kNN classification works well in terms of accuracy and efficiency.
Author ' s personal copy Two temporal channels in human V 1 identi fi ed using fMRI

a Psychology Department, Stanford University, Stanford, CA 94305-2130, USA b Department of Ophthalmology, Jikei University, School of Medicine, Tokyo, Japan c Department of Functional Training III, National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Japan d Kobe Advanced ICT Research Center, National Institute of Information and Communications Technology, Japan e Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institute of Health, USA
Model of Massive Rotator Cuff Tear : Importance of Margin Convergence and Posterior Cuff Fixation Restoration of Shoulder Biomechanics According to Degree of Repair Completion in a Cadaveric

http://ajs.sagepub. com/content/40/11/2448 The online version of this article can be found at: DOI: 10.1177/0363546512458775 2012 40: 2448 originally published online September 13, 2012 Am J Sports Med Joo Han Oh, Michelle H. McGarry, Bong Jae Jun, Akash Gupta, Kyung Chil Chung, James Hwang and Thay Q. Lee Model of Massive Rotator Cuff Tear: Importance of Margin Convergence and Posterior Cuff Fixation Restoration of Shoulder Biomechanics According to Degree of Repair Completion in a Cadaveric
Unfairness towards subjective opinions in Machine Learning

Despite the high interest for Machine Learning (ML) in academia and industry, many issues related to the application of ML to real-life problems are yet to be addressed. Here we put forward one limitation which arises from a lack of adaptation of ML models and datasets to specific applications. We formalise a new notion of unfairness as exclusion of opinions. We propose ways to quantify this unfairness, and aid understanding its causes through visualisation. These insights into the functioning of ML-based systems hint at methods to mitigate unfairness.
Color blending based on viewpoint and surface normal for generating images from any viewpoint using multiple cameras

A color blending method for generating a high quality image of human motion is presented. The 3D (three-dimensional) human shape is reconstructed by volume intersection and expressed as a set of voxels. As each voxel is observed as different colors from different cameras, voxel color needs to be assigned appropriately from several colors. We present a color blending method, which calculates voxel color from a linear combination of the colors observed by multiple cameras. The weightings in the linear combination are calculated based on both viewpoint and surface normal. As surface normal is taken into account, the images with clear texture can be generated. Moreover, since viewpoint is also taken into account, high quality images free of unnatural warping can be generated. To examine the effectiveness of the algorithm, a traditional dance motion was captured and new images were generated from arbitrary viewpoints. Compared to existing methods, quality at the boundaries was confirmed to improve.
Towards a Fully Modular Power System Architecture for DC-DC Converters

Abstract : Fully modular power system architecture for dc-dc conversion, where low-power, low-voltage (input and output) building block dc- dc converters can be connected in any combination of series/parallel configurations at the output and/or at the input sides, has several advantages including increased reliability, standardization of design and components, higher power density and efficiency. An important component of such architecture is the autonomous, input series configuration with active input voltage and load current sharing, towards which this research project has made significant contributions. The major research tasks accomplished in this project are: Development of control methods for input-series and output-series (ISOS) configuration with active voltage sharing; Development of input-voltage share bus scheme for input-series, output parallel (ISOP) connection that makes the converter modules self-contained and identical, leading to fault tolerant capability; Study on magnetic approaches to input-voltage sharing for input-series connected converters and development of interleaving techniques for input series connected.
1022 A STUDY OF FLY ASH-CEMENT HYDRATION BY RIETVELD ANALYSIS AND SELECTIVE DISSOLUTION

Recent improvements in concrete research have shown the importance of durable concrete with environmental materials such as fly ash. Mechanical properties and durability of cementitious material are related to its microstructure. In order to understand the microstructure of concrete, it is necessary to quantitatively determine its cementitious hydration. However, until now there is no proper method to measure hydration degree of fly ash-cement system. In this paper, we purpose the new method; superposition between quantitative XRD analysis/ Rietveld analysis and selective dissolution. By using this method the amount of unhydrated cement, unhydrated fly ash, Ca(OH)2 and hydrated gel can be estimated.
Nutritional composition of vegetables grown in organic and conventional cultivation systems in Uberlndia, MG

There is a growing concern about the presence of pesticides in food and the health problem they may cause. Awareness of this issue, consumers opt for organic food consumption. Organic agriculture is a farming system ecologically sustainable, economically viable and socially just, capable of integrating man and environment. This study evaluated the nutritional composition of some crops grown in an organic (Org) and conventional (Con) systems, produced in Uberlândia-MG. Samples of lettuce, collard greens and carrots from both certified farming systems were gathered from local supermarkets and moisture, lipids, ash, dietary fiber, carbohydrates, protein and energy were obtained from them. Moisture was greater and the amounts of lipids, proteins and ashes were lower in conventional vegetables. Dietary fiber content in organic collard greens was significantly greater (4.37% ± 0.28 Org) than in conventional ones (3.15% ± 0.12 Con). Differences in nutrient composition of crops grown organically and conventionally were observed and more studies are needed for better understanding of nutritional value differences. Key words: Nutrients, organic farming system, conventional farming system.
Author ’ s Accepted Manuscript Encoding of Contextual fear Memory Requires de novo Proteins in the Prelimbic CortexEncoding contextual fear memory storage

Cite this article as: Valerio Rizzo, Khalid Touzani, Bindu L. Raveendra, Supriya Swarnkar, Joan Lora, Beena M. Kadakkuzha, Xin-An Liu, Chao Zhang, Doron Betel, Robert W. Stackman and Sathyanarayanan V. Puthanveettil, Encoding of Contextual fear Memory Requires de novo Proteins in the Prelimbic CortexEncoding contextual fear memory storage, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, http://dx.doi. org/10.1016/j.bpsc. 2016.10. 002
Market Thinness, List Price Revisions and Time to Sell: Evidence from a large-scale housing dataset

This paper uses a large dataset, covering more than 70% of the Dutch housing market, to analyze the relationship between market thinness, price setting behavior and time to sell. Our findings confirm the typical result that overpricing increases the time on market. In addition, we find evidence of quicker list price reductions suggesting that overpricing is part of a strategy to search for the opportunity of high revenues and to learn about the market. Moreover, we are able to confirm the theory put forward by Lazear (1986) on the relation between atypical goods and the speed of price adjustments. Sellers of atypical houses are more uncertain about the price buyers want to pay and take time to learn about the market, thereby increasing the expected time on market and the time to price revisions. Market liquidity has a positive, i.e. shortening, effect on the time to sale and leads to quicker price revisions due to the increased opportunities for learning.
Intensive Reading Interventions for Inadequate Responders in Grades K–3: A Synthesis

A subset of students fail to respond adequately to reading interventions. This synthesis systematically reviews studies in which students in grades K–3 responded inadequately to a Tier 2 reading intervention and were provided with a Tier 3 intervention. Descriptions of the Tier 3 reading interventions and effects are provided. To meet inclusion criteria, studies were required to (a) provide documented, multi-tiered reading interventions with at least one reading outcome measured; (b) include students in grades K–3 who previously responded inadequately to a Tier 2 intervention; (c) use experimental, quasi-experimental, or multiple-group designs; and (d) be peer reviewed and conducted in English. Twelve studies met inclusion criteria. Results demonstrate that students who responded inadequately to Tier 2 interventions can make significant growth from Tier 3 interventions compared with a control group of peers who were also inadequate responders, but often fail to catch up to their more responsive peers.
Neocogn i t ron Using Hierarchical Self-Organizing Maps

Abst rac t . The sequential recognition method using the selective attention mechanism of Neocognitron (NC) is realizable and very effective for images of multiple targets. NC, however, is not applicable to general (large-scale, gray or color complex object) images, because of both a low reduction rate of coding scheme and an initial state dependency of competitive learning. In this paper, "hypercolumn model (HCM)" is introduced to modify NC and to apply the sequential recognition to general images. Two properties of the hierarchical self-organizing maps proposed by Lampinen: a coding scheme using topographic mapping and an initial state independence of learning resolve the two disadvantages of NC, respectively. Experimental results will show that a recognition accuracy of HCM for general images was from 10 percent to 30 percent higher than one of NC, and a sequential recognition performed well.
Inkjet printing of silver and carbon conductive functional coatings

III ACKNOWLEDGEMENTS . IV LIST OF ABBREVIATIONS . V TABLE OF CONTENTS . VII MOTIVATION . 1 RESEARCH OBJECTIVES . 3 1 BACKGROUND . 5 2 SILVER PRINTING: THE CONDUCTIVE PROPERTIES OF COATED AND PRINTED SILVER LAYERS ON A PAPER SUBSTRATE . 10 2.1 MATERIALS AND METHODS . 10 2.1. 1 Materials . 10 2.1. 2 Conductivity measurements . 13 2.1. 3 Image analysis . 13 2.2 RESULTS AND DISCUSSION . 14 2.2.1 Microstructure . 14 2.2.2 Electrical conductivity . 16 2.2.3 Ink flow dynamics and its influence on the conductive properties of the layers . 18 2.2. 4 Taguchi method . 23 2.3 CONCLUSIONS . 30 3 METAL PARTICLE COMPACTION EXPERIMENTS DURING DROP-SUBSTRATE IMPACT . 31 3.1 PROPOSED EXPERIMENTAL METHOD . 31 3.2 RESULTS . 32 3.3 CONCLUSIONS . 34 4 MODELLING OF THE DROP-SUBSTRATE IMPACT . 35 4.