This Girl is on Fire: Seeking a Home for the Narrative

2018 ◽  
Vol 25 (2) ◽  
pp. 163-165 ◽  
Author(s):  
Geraldine Gorman
Keyword(s):  
Nursing Practice ◽  
Personal Narrative ◽  
Evidence Based Practice ◽  
Large Data ◽  
Large Data Sets ◽  
Evidence Based ◽  
Data Sets ◽  
Academic Ethics ◽  
The Relationship

Using memory as the bridge between two related encounters separated by decades, the author explores the relationship between the narrative and nursing practice and education. Do academic ethics belong in the realm inhabited by the interpersonal encounter? In this era of evidence-based practice and large data sets, is there a place for the personal narrative? These questions impact the values which inform the education we offer our future practitioners.

scholarly journals Importance of Skeletal Staging in Chondrosarcoma of Bone: Results of Survey on Current Practices Among Musculoskeletal Oncologists

2020 ◽  
Author(s):  
Ashish Gulia ◽  
Srinath Gupta ◽  
Vineet Kurisunkal ◽  
Ajay Puri
Keyword(s):  
Bone Scan ◽  
Online Survey ◽  
Large Data ◽  
Skeletal Metastasis ◽  
Large Data Sets ◽  
Evidence Based ◽  
Data Sets ◽  
Online Portal ◽  
Grade 3 ◽  
Current Practices

Abstract Purpose There are no clear guidelines for staging of conventional chondrosarcoma. We conducted an online survey to determine the current practices for skeletal staging for conventional chondrosarcoma among practicing oncologists and to assess any discrepancy in practices and with the published literature. Methodology A simple ten-question online survey (e-mails and WhatsApp) was conducted among practicing oncologists over a period of 3 weeks using online portal (surveymonkey.com). It was followed by analysis based on each question to find current practices. Results 139 members participated in the survey (84% surgeons, 9% radiologists, 3% medical and 3% radiation oncologists and 1% nuclear medicine). 65% have been treating chondrosarcoma for more than 5 years. 88% opined that biopsy is mandatory even if the radiology is suggestive of a chondrosarcoma. 66% said that solitary skeletal metastasis is seen in less than 2% of the cases but 84% of participants were in favour of performing an investigation (bone scan/PET scan) for skeletal survey. While 43% opined skeletal metastasis is more common in recurrent chondrosarcoma, 26% said that performing a bone scan was likely to impact management, 28% said it will not impact management and 46% were unsure. Of the group who thought that a bone scan would impact management or were unsure, the majority (56%) opined that this was relevant only in grade 2 and grade 3 chondrosarcoma. Conclusion There was lack of consensus regarding staging for chondrosarcoma. Only 26% of respondents were convinced that performing a bone scan was likely to impact management of chondrosarcoma. There is a need to analyze large data sets (retrospective/prospective) to arrive at an evidence-based staging algorithm for chondrosarcoma.

The applying of machine learning methods to improve the quality of well casing

2020 ◽  
pp. 81-93
Author(s):  
D. V. Shalyapin ◽  
D. L. Bakirov ◽  
M. M. Fattakhov ◽  
A. D. Shalyapina ◽  
A. V. Melekhov ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
New Approach ◽  
Geological Conditions ◽  
Expert Assessments ◽  
The Impact ◽  
The Relationship

The article is devoted to the quality of well casing at the Pyakyakhinskoye oil and gas condensate field. The issue of improving the quality of well casing is associated with many problems, for example, a large amount of work on finding the relationship between laboratory studies and actual data from the field; the difficulty of finding logically determined relationships between the parameters and the final quality of well casing. The text gives valuable information on a new approach to assessing the impact of various parameters, based on a mathematical apparatus that excludes subjective expert assessments, which in the future will allow applying this method to deposits with different rock and geological conditions. We propose using the principles of mathematical processing of large data sets applying neural networks trained to predict the characteristics of the quality of well casing (continuity of contact of cement with the rock and with the casing). Taking into account the previously identified factors, we developed solutions to improve the tightness of the well casing and the adhesion of cement to the limiting surfaces.

scholarly journals A Proposal for Certification in Nursing Theory

Aquichan ◽  
2016 ◽  
Vol 16 (1) ◽  
pp. 7-14 ◽  
Author(s):  
Debra R. Hanna
Keyword(s):  
Health Care ◽  
Health Care System ◽  
Formal Education ◽  
Nursing Practice ◽  
Evidence Based Practice ◽  
Evidence Based ◽  
Nursing Theory ◽  
The Relationship ◽  
Different Levels ◽  
Contemporary Health Care

The author proposes the development of different levels of certification in the knowledge of nursing theory that would be based on the level of formal education attained. At present, nurses are being required to obtain higher levels of formal education in order to serve patients safely in a technologically complex health care system. Although evidence-based practice is strongly desired in contemporary health care, less consideration has been given to the value of theory-based nursing practice or the relationship between theory and research. The author explains multiple background issues and then highlights several questions that are important for disciplinary discussion at this point in time.

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

NVESTIGATION OF THE EFFICIENCY OF DISTRIBUTED INFORMATION SYSTEMS BASED ON THE PROCESSING OF LARGE AMOUNTS OF DATA

2019 ◽  
Author(s):  
Mykhajlo Klymash ◽  
Olena Hordiichuk — Bublivska ◽  
Ihor Tchaikovskyi ◽  
Oksana Urikova
Keyword(s):  
Distributed Systems ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Data Decomposition ◽  
Distributed Information ◽  
Software Model ◽  
Computing Performance ◽  
Mapreduce Model ◽  
Singular Data

In this article investigated the features of processing large arrays of information for distributed systems. A method of singular data decomposition is used to reduce the amount of data processed, eliminating redundancy. Dependencies of com­putational efficiency on distributed systems were obtained using the MPI messa­ging protocol and MapReduce node interaction software model. Were analyzed the effici­ency of the application of each technology for the processing of different sizes of data: Non — distributed systems are inefficient for large volumes of information due to low computing performance. It is proposed to use distributed systems that use the method of singular data decomposition, which will reduce the amount of information processed. The study of systems using the MPI protocol and MapReduce model obtained the dependence of the duration calculations time on the number of processes, which testify to the expediency of using distributed computing when processing large data sets. It is also found that distributed systems using MapReduce model work much more efficiently than MPI, especially with large amounts of data. MPI makes it possible to perform calculations more efficiently for small amounts of information. When increased the data sets, advisable to use the Map Reduce model.

Using Large Data Sets and Statistical Tools to Define “Failure” and Demonstrate the Safety of DPR

2018 ◽  
Vol 2018 (6) ◽  
pp. 38-39
Author(s):  
Austa Parker ◽  
Yan Qu ◽  
David Hokanson ◽  
Jeff Soller ◽  
Eric Dickenson ◽  
...  
Keyword(s):  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Statistical Tools
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