bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Pediatrician’s Role in the Evaluation and Preparation of Pediatric Patients Undergoing Anesthesia
Authors:   SECTION ON ANESTHESIOLOGY AND PAIN MEDICINE, Goldschneider Kenneth R. , Cravero Joseph P. , Anderson Corrie , Bannister Carolyn , Hardy Courtney , Honkanen Anita , Rehman Mohamed , Tobias Joseph 
Published: August 2014

This Policy Statement was reaffirmed February 2021.
Pediatricians play a key role in helping prepare patients and families for anesthesia and surgery. The questions to be answered by the pediatrician fall into 2 categories. The first involves preparation: is the patient in optimal medical condition for surgery, and are the patient and family emotionally and cognitively ready for surgery? The second category concerns logistics: what communication and organizational needs are necessary to enable safe passage through the perioperative process? This revised statement updates the recommendations for the pediatrician’s role in the preoperative preparation of patients.
Cloud-based Remote Visualization of Big Data to Subsurface Exploration
Authors: Delazari Binotto Alécio Pedro , Sultanum Nicole , Cerqueira Renato 
Published: August 2014

AbstractSince the first visualization solutions were explored for O&G, major technical improvements enabled gigabyte-sized models to be rendered and manipulated at interactive speeds. Yet, other fundamental aspects such as data access and distribution are often overlooked in the process, even to date. Data movement may often be prohibitive, either due to legal constraints (data is restricted from departing the country) or practical considerations (data is too large to be moved, is a checkpoint tightly connect to imaging processes, and requires costly resources to be manipulated). Collaborative visualization tends to be performed co-locally, following an explicit, manually conducted, data transfer to a dedicated visualization machine.We propose an alternative based upon data-centric computing. The model offers visualization as-a-service over a multi-tenant cloud-based environment. Remote visualization enables lightweight access and interaction with generated data readily after the processing, dismissing the need to transfer the whole dataset into analyst's machine. It offloads heavy graphics processing to a cloud server featuring the necessary infrastructure to handle such voluminous data, like GPUs, GPFS, and ultimately sends only a reduced output to lightweight clients (rendered images/geometry). Visualization resources can also be shared among concurrent users in a web-based interface and combined with other data sources, like correspondent well information or velocity models, facilitating effective remote collaboration towards knowledge discovery in subsurface exploration. Ubiquitous on-the-go data access (e.g., in the exploration field itself) is thereby made possible through mobile interfaces.Concurrently, several challenges emerge with the aforementioned visualization model. The effective resource distribution of different data sources among several clients needs to benefit from the cloud execution platform. The OpenPower Foundation is an example of the future HPC platform that can be customized to O&G characteristics and be offered as a cloud model.
Spectral Effects of Large Matrices from Oil Reservoir Simulators on Performance of Scalable Direct Solvers
Authors: Duran Ahmet , Tuncel Mehmet 
Published: August 2014

Abstract
It is important to estimate the elapsed time to solve large sparse linear systems for time-restricted real life decision making applications such as oil and gas reservoir simulators. Challenging matrices should be distinguished and handled separately because they may lead to performance bottleneck. Therefore, we need to examine the spectral effects of large matrices on the performance of scalable direct solvers by using eigenvalues. In this work, we check whether there is relationship between the eigenvalue distribution of a matrix and the performance of the solver. We try to examine the eigenvalue distribution of various sparse matrices. We may find all eigenvalues in order to obtain the distribution graph of eigenvalues, if possible. However, it is very expensive to find all eigenvalues. Therefore, Gerschgorin's theorem may be used to bound the spectrum of square matrices. Several behaviors such as being disjoint, overlapped or clustered of Gerschgorin circles may give clue regarding the distribution of the eigenvalues and the performance of the solver for that matrix.
In this paper, we consider a portfolio of test matrices which include randomly populated sparse matrices and various patterned matrices coming from reservoir modeling from single porosity single permeability to dual porosity dual permeability models (see [10]). We examined our modified HELM2D03LOWER_20K matrix and EMILIA_923 matrix from the University of Florida sparse matrix collection (see [17]), in addition to the patterned matrices from 3 phase black-oil model and 7 component EOS model.
We define an optimal minimum number of cores as the number of cores that provides the minimum wall clock time for a given size of problem, where a right match occurs between the problem size, the spectral effects of matrix and the available resources such as memory, in presence of communication overhead. We find that the optimal minimum number of cores required depends on the sparsity level and size of the matrix. As the sparsity level of matrix decreases and the order of matrix increases, we expect that the optimal minimum number of cores increases slightly.
State-of-the-Art Emerging Technology for Technical Data Mining and Analysis
Authors: Kishore Kaushal , Sharma Puneet , Khanapurkar Pooja 
Published: August 2014

AbstractThe upstream oil and gas industry requires a diverse set of political, personnel, mechanical, and technological capabilities as it possesses innumerable and voluminous data from seismic, drilling, completion, and production. In this competitive field, technical data mining and analysis are key to the creation of intelligent oilfields. However, there are major challenges associated with the generation and consumption of data in intelligent oil and gas fields, including the acquisition, storage, classification, transformation, visualization, and analysis of data.A service company's technical data mining application platform that has built-in analytical tools should aid field engineers in the retrieval of relevant data, as well as the analysis of data for their own requirements. Such an application, when combined with live notification capabilities, can help improve the operational productivity and lessen time lost during a job failure or any other events contributing to nonproductive time (NPT). It also would help standardize the measurement of key performance indicators across different areas or regions. Continuous surveillance and monitoring of wells, which are the basis for intelligent oilfields, help improve productivity and reduce operating costs.This paper discusses one service company's state-of-the-art application for big data archiving algorithms and practices that are distinctive for improving data mining in intelligent oilfields. This application acts as an enabler for extracting relevant information to improve predictive models, making more reliable decisions, and, ultimately, sustaining existing business and creating new business opportunities.
Challenges and Opportunities for HPC Cloud in Natural Resources
Authors: Nogueira Alberto C. , Binotto Alecio , Mantripragada Kiran , Tizzei Leonardo P. , Sultanum Nicole , Netto Marco A. 
Published: August 2014

Abstract
Problems in natural resources are currently handled by applications that require High Performance Computing (HPC) platforms. These applications from areas such as agriculture, oil and gas, weather forecast, mining, among others, require complex mathematical models, which rely heavily on compute-intensive methods. Examples of these methods are partial differential equations (PDEs) discretization techniques (e.g. spectral element, finite difference, and finite volume methods), optimization algorithms, and inverse problems. Most of natural resources applications run on HPC clusters or supercomputers. Generally the Total Ownership Costs (TOC) of these infrastructure resources is very high even for medium to large companies. Moreover, small innovative software companies that specialize in computational modeling may not be able to acquire such clusters. Cloud Computing can come as a technology and business model to enable the execution of scientific applications from all companies, while such infrastructure is rented on demand. Initially used for Web applications, Cloud Computing is currently increasing its maturity to execute different types of workloads, including computing-intensive, data-intensive and networking-intensive, scientific and industry applications on HPC resources. This paper describes the challenges we observed while running natural resources applications that require high performance resources, on a Cloud. It also highlights some of the key opportunities that HPC Cloud brings to the natural resources area.
Reservoir Simulation Prototyping Platform for High Performance Computing
Authors: Jauré S.. , Moncorgé A.. , de Loubens R.. 
Published: August 2014

Abstract
The size and complexity of reservoir simulation models are growing continuously to better capture the heterogeneities of geological models and to simulate advanced physics. Generally reservoir simulators' speed and efficiency are still major bottlenecks requiring, in many cases, the simplification of the models by the user. We present here some recent insights of High Performance Computing (HPC) prototyping in an In-House Research Reservoir Simulator (IHRRS). Firstly, we explain how we build a cache-efficient Jacobian matrix in the case of a general multi-phase multi-component simulator using numerical discretizations based on Two-Point Flux Approximation (TPFA) or Multi-Point Flux Approximation (MPFA). Secondly, we describe the implementation of two levels of distributed memory parallelism (MPI) in addition to one level of shared memory parallelism (OpenMP). Two levels of distributed memory parallelism are used because some algorithms like AMG-coarsening or parallel I/O of grid data have difficulties to scale with a large number of distributed memory processes, while other parts of the simulator still scale with additional processes. A second level of shared memory parallelism is used in each distributed process. Some numerical validation is presented to investigate the optimum ratio of MPI and OpenMP processes. In addition we test our algorithms on the simulation of a coreflood experiment at an adverse mobility ratio using about 30 million gridblocks in 3D, and on a large-scale model of nearly half a billion cells.
The Impact of Eliminating the Form 20-F Reconciliation on Shareholder Wealth: Evidence from U.S. Cross-Listed Firms
Authors: Chen Lucy Huajing , Khurana Inder K. 
Published: August 2014

ABSTRACT
This paper examines shareholder wealth effects in U.S. and home-country markets relating to the Securities and Exchange Commission's (SEC) decision to eliminate the Form 20-F reconciliation. During the period of examined events, we find positive cumulative abnormal returns for the treatment sample of U.S. cross-listed firms that prepare financial statements under International Financial Reporting Standards (IFRS), but no such effects for our control sample comprising cross-listed non-IFRS, U.S. domestic, or home-country firms. We find the stock market impact for our treatment sample to be positively related to our proxy for cost savings and negatively related to the pre-adoption reconciliation magnitude from IFRS to U.S. GAAP. This suggests shareholders place some value on reconciliation information, but the costs of preparing and auditing reconciliations generally outweigh concern about information loss. Moreover, we find that information loss is less pronounced for firms having used IFRS for a longer period, suggesting the learning effect mitigates information loss.
Data Availability: Data are publicly available from sources identified in the article.
Effects of tibial plateau angle and spacer thickness applied during in vitro canine total knee replacement on three-dimensional kinematics and collateral ligament strain
Authors: Baker Katherine M. , Foutz Timothy L. , Johnsen Kyle J. , Budsberg Steven C. 
Published: August 2014

Abstract
Objective—To quantify the 3-D kinematics and collateral ligament strain of stifle joints in cadaveric canine limbs before and after cranial cruciate ligament transection followed by total knee replacement (TKR) involving various tibial plateau angles and spacer thicknesses.
Sample—6 hemi-pelvises collected from clinically normal nonchondrodystrophic dogs (weight range, 25 to 35 kg).
Procedures—Hemi-pelvises were mounted on a modified Oxford knee rig that allowed 6 degrees of freedom of the stifle joint but prevented mechanical movement of the hip and tarsal joints. Kinematics and collateral ligament strain were measured continuously while stifle joints were flexed. Data were again collected after cranial cruciate ligament transection and TKR with combinations of 3 plateau angles (0°, 4°, and 8°) and spacer thicknesses (5, 7, and 9 mm).
Results—Presurgical (ie, normal) stifle joint rotations were comparable to those previously documented for live dogs. After TKR, kinematics recorded for the 8°, 5-mm implant most closely resembled those of unaltered stifle joints. Decreasing the plateau angle and increasing spacer thickness altered stifle joint adduction, internal rotation, and medial translation. Medial collateral ligament strain was minimal in unaltered stifle joints and was unaffected by TKR. Lateral collateral ligament strain decreased with steeper plateau angles but returned to a presurgical level at the flattest plateau angle.
Conclusions and Clinical Relevance—Among the constructs tested, greatest normalization of canine stifle joint kinematics in vitro was achieved with the steepest plateau angle paired with the thinnest spacer. Furthermore, results indicated that strain to the collateral ligaments was not negatively affected by TKR.
Use of an inertial measurement unit to assess the effect of forelimb lameness on three-dimensional hoof orientation in horses at a walk and trot
Authors: Moorman Valerie J. , Reiser Raoul F. , Mahaffey Christie A. , Peterson Michael L. , McIlwraith C. Wayne , Kawcak Christopher E. 
Published: August 2014

Abstract
Objective—To determine intralimb orientation changes with an inertial measurement unit (IMU) in hooves of horses at a walk and trot after induction of weight-bearing single forelimb lameness and to determine whether hoof orientations are similar to baseline values following perineural anesthesia.
Animals—6 clinically normal horses.
Procedures—3-D hoof orientations were determined with an IMU mounted on the right forelimb hoof during baseline conditions, during 3 grades of lameness (induced by application of pressure to the sole), and after perineural anesthesia. Linear acceleration profiles were used to segment the stride into hoof breakover, stance, initial swing, terminal swing, and total swing phases. Intralimb data comparisons were made for each stride segment. A repeated-measures mixed-model ANOVA was used for data analysis.
Results—Lameness resulted in significant changes in hoof orientation in all planes of rotation. A significant increase in external rotation and abduction and a significant decrease in sagittal plane rotation of the hoof were detected at hoof breakover during lameness conditions. For sagittal plane orientation data, the SDs determined following perineural anesthesia were higher than the SDs for baseline and lameness conditions.
Conclusions and Clinical Relevance—Results of this study indicated the IMU could be used to detect 3-D hoof orientation changes following induction of mild lameness at a walk and trot. An increase in data variability for a sagittal orientation may be useful for assessment of local anesthesia for hooves. The IMU should be further evaluated for use in clinical evaluation of forelimb lameness in horses.
Microcirculatory effects of intravenous fluid administration in anesthetized dogs undergoing elective ovariohysterectomy
Authors: Silverstein Deborah C. , Cozzi Elizabeth M. , Hopkins Amber S. , Keefe Thomas J. 
Published: August 2014

Abstract
Objective—To assess the microcirculatory effects of IV fluid administration in healthy anesthetized dogs undergoing elective ovariohysterectomy.
Animals—49 client-owned dogs.
Procedures—Dogs were sedated, and anesthesia was induced with propofol and diazepam and maintained with isoflurane in oxygen. Dogs received lactated Ringer's solution (LRS) IV at rates of 0, 10, or 20 mL/kg/h. Videomicroscopy was used to assess and record effects of LRS administration on microcirculation in the buccal mucosa. Measurements of microcirculatory (total vessel density, proportion of perfused vessels, microcirculatory flow index, and perfused vessel density by vessel size [< 20 μm, ≥ 20 μm, and all diameters]) and other physiologic variables (heart rate, Doppler-measured blood pressure, oxygen saturation as measured by pulse oximetry, capillary refill time, and body temperature) were compared among groups at baseline (immediately after anesthetic induction), 30 and 60 minutes afterward, and overall.
Results—Neither the proportion of perfused vessels nor microcirculatory flow index varied among treatment groups at any time point, regardless of vessel size. For vessels < 20 μm in diameter and for all vessels combined, total and perfused vessel density were similar among groups. For vessels ≥ 20 μm in diameter, total vessel density was significantly greater in the 20 mL/kg/h group than in other groups, and perfused vessel density was significantly greater in the 20 mL/kg/h group than in the 0 mL/kg/h group, when all time points were considered. Other physiologic variables were similar among groups.
Conclusions and Clinical Relevance—Total and perfused vessel density of vessels ≥ 20 μm in diameter (mostly venules) were greatest in dogs that received 20 mL of LRS/kg/h. Further research is required to evaluate clinical importance of these findings.
Evaluation of DNA methylation profiles of the CpG island of the ABCB1 gene in dogs with lymphoma
Authors: Tomiyasu Hirotaka , Fujiwara-Igarashi Aki , Goto-Koshino Yuko , Fujino Yasuhito , Ohno Koichi , Tsujimoto Hajime 
Published: August 2014

Abstract
Objective—To examine the DNA methylation status of the ABCB1 gene in tumor cells of dogs with lymphoma.
Animals—27 dogs with multicentric B-cell high-grade lymphoma (19 chemotherapy-sensitive dogs and 8 chemotherapy-resistant dogs).
Procedures—The DNA methylation profile of the CpG island of the ABCB1 gene was analyzed by use of bisulphite sequencing and real-time methylation-specific PCR assay in lymphoma cells. Quantitative reverse transcriptase PCR assay of the ABCB1 gene was conducted to measure the amount of mRNA. Correlation between the amount of ABCB1 mRNA and the methylation rate was examined.
Results—The CpG island of the ABCB1 gene was hypomethylated in most dogs in both the chemotherapy-sensitive and -resistant groups. No significant difference was detected in the methylation rate between the 2 groups, and no significant correlation was detected between the methylation rate and the mRNA expression level.
Conclusions and Clinical Relevance—Expression of the ABCB1 gene was not suppressed by hypermethylation of its CpG island in most dogs with lymphoma regardless of their chemotherapy sensitivity status.
A Study on the Evolution of Tax Pressure in Romania
Authors: Vintilă Georgeta , Ţibulcă Ioana Laura 
Published: August 2014

Abstract
Fiscal pressure is often considered a barometer for the impact and level of taxation experienced by individual taxpayers and businesses. In Romania, the study of the tax burden has been and will remain a highly debated topic in a national as well as European context. Thus, in this article, we conducted a descriptive statistical analysis of the evolution of the tax burden in Romania, and showcased the research results in different graphically expressive ways (maps, tables, graphs), all presented from a dual perspective. On the one hand, we followed the impact of taxation on households, and on the other hand, in a broader approach, we highlighted the tax burden reflected at the county and regional level
On Determining the Optimal Sampling Frequency for Feedback Quality Control Systems
Authors: Kartha C. P. 
Published: August 2014

Abstract
This paper considers the choice of the most profitable sampling frequency for a feedback quality control system. It is assumed that the disturbance can be adequately modeled by a first-order Integrated Moving Average (IMA (0, 1, 1)) process. The cost model includes two terms, one for the cost of being off-target and one for the cost of sampling and adjustment. An analytical solution is obtained and the sensitivity of parameters examined
Variation in Growth Performance and Carcass Yield of Pure and Reciprocal Crossbred Turkeys
Authors: Damaziak Krzysztof , Michalczuk Monika , Zdanowska-Sąsiadek Żaneta , Niemiec Jan , Gozdowski Dariusz 
Published: August 2014

Abstract
This study compared growth, feed conversion ratio (FCR), mortality rate and results of slaughter analysis of slow-growing Bronze turkeys (SG), fast-growing Big 6 turkeys (FG), and their reciprocal crosses (SF and FS). Until 6 weeks of age the birds were kept indoors and afterwards they were allowed to use free ranges. Toms were reared until 21 and hens until 15 weeks of age. The FS turkeys were characterized by higher (P≤0.05) BW and dressing percentage and by lower FCR compared to the SF crosses of both sexes. The analysis of orthogonal contrasts demonstrated that values of most of the slaughter analysis parameters were due to the additive effect of genes. Only weight of skin with fat and of gizzard could result from heterosis. Study results demonstrate that FS crosses constitute better material for the alternative production of turkeys compared to the other analysed groups (SG, SF, FG).
Significance of Nutrient Digestibility in Horse Nutrition – A Review
Authors: Cichorska Barbara , Komosa Marcin , Nogowsk Leszek , Maćkowiak Paweł , Józefia Damian 
Published: August 2014

Abstract
The aim of the review is to present mechanisms of digestion in horses through a functional description of the digestive system’s structure with emphasis on nutrient digestibility. In the era of an increasingly intensive and specialised sport usage of horses, also the significance of balancing their dietary nutrient value in accordance with individual requirements of these animals is gaining in importance. At the same time, it is not possible to meet nutritional requirements of a sport horse without knowledge about feed utilisation. In many farm animal species, digestibility is measured postmortem or via complicated and expensive cannulation of the digestive system. In horses, these methods are not applied due to ethical approaches or other limitations (e.g. sport horses); therefore, the importance of marker-based techniques is growing, although not much data is published in the available literature (Sales, 2012). Moreover, in contrast to other non-ruminants, horses are naturally adapted to a constant intake of large quantities of roughages. However, during intensive sport training, they are primarily fed concentrated diets with high amounts of easily digestible, non-structural carbohydrates and reduced amounts of dietary fibre fractions. Therefore, the risk of metabolic diseases and behavioural disorders in the horse increases.