scholarly journals Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

2018 ◽  
Vol 20 (26) ◽  
pp. 18082-18088
Author(s):  
H. E. Mason ◽  
E. C. Uribe ◽  
J. A. Shusterman
Keyword(s):  
Statistical Analysis ◽  
Solid State ◽  
Contact Time ◽  
Decomposition Methods ◽  
Tensor Rank ◽  
Data Sets ◽  
Rapid Acquisition ◽  
Nmr Data ◽  
Rank Decomposition ◽  
P Tensor

Tensor-rank decomposition methods have been applied to variable contact time 29Si{1H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

scholarly journals Structural Investigations of C-Nitrosobenzenes. Part 3.1 Solid-state and Solution 13C NMR Studies, and Crystal Structure of E-(4-CIC6H4NO)2

1999 ◽  
Vol 23 (3) ◽  
pp. 202-203
Author(s):  
Daniel A. Fletcher ◽  
Brian G. Gowenlock ◽  
Keith G. Orrell ◽  
David C. Apperley ◽  
Michael B. Hursthouse ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Solid State ◽  
13C Nmr ◽  
Nmr Studies ◽  
Structural Investigations ◽  
Nmr Data ◽  
C Nmr

Solid-state and solution 13C NMR data for the monomers and dimers of 3- and 4-substituted nitrosobenzenes, and the crystal structure of E-(4-CIC6H4NO)2 are reported.

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

Statistical analysis of coastal morphological data sets over seasonal to decadal time scales

2008 ◽  
Vol 55 (7-8) ◽  
pp. 581-600 ◽  
Author(s):  
Aart Kroon ◽  
Magnus Larson ◽  
Iris Möller ◽  
Hiromune Yokoki ◽  
Grzegorz Rozynski ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Time Scales ◽  
Morphological Data ◽  
Data Sets

Applied plant science experimental design and statistical analysis using the SAS® OnDemand for Academics

2021 ◽  
Keyword(s):  
Statistical Analysis ◽  
Agricultural Production ◽  
Science Research ◽  
Plant Science ◽  
Data Sets ◽  
Statistical Analysis System ◽  
Key Topics ◽  
Analysis System ◽  
User Friendly ◽  
Enormous Number

Abstract The correct design, analysis and interpretation of plant science experiments is imperative for continued improvements in agricultural production worldwide. The enormous number of design and analysis options available for correctly implementing, analyzing and interpreting research can be overwhelming. Statistical Analysis System (SAS®) is the most widely used statistical software in the world and SAS® OnDemand for Academics is now freely available for academic insttutions. This is a user-friendly guide to statistics using SAS® OnDemand for Academics, ideal for facilitating the design and analysis of plant science experiments. It presents the most frequently used statistical methods in an easy-to-follow and non-intimidating fashion, and teaches the appropriate use of SAS® within the context of plant science research. This book contains 21 chapters that covers experimental designs and data analysis protocols; is presented as a how-to guide with many examples; includes freely downloadable data sets; and examines key topics such as ANOVA, mean separation, non-parametric analysis and linear regression.

scholarly journals Statistically, Does peer assisted learning make a difference on a UK engineering degree programme? HETL Scotland 2017

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anne Louise Nortcliffe ◽  
Sajhda Parveen ◽  
Cathy Pink-Keech
Keyword(s):  
Academic Performance ◽  
Statistical Analysis ◽  
Positive Impact ◽  
Data Sets ◽  
Social Categories ◽  
Peer Assisted Learning ◽  
Student Records ◽  
Content Type ◽  
Attainment Gap ◽  
The Impact

Purpose Black British minority ethnics (BME) students are nationally underachieving in comparison to their Ethnic Chinese and White peers, showing typically a 16 per cent graduate attainment gap in the UK. Previous research has suggested that the attainment gap could be explained by BME student disengagement, as the students typically commute from family home to University, and they work part time. However, peer-assisted learning (PAL) has been shown to have a positive impact on addressing and resolving student alienation and disengagement. However, a question still remains regarding whether student perceptions hold up to statistical analysis when scrutinised in comparison to similar cohorts without PAL interventions. The paper aims to discuss these issues. Design/methodology/approach This paper presents the results of a statistical study for two cohorts of students on engineering courses with a disproportionately high representation of BME students. The research method involved a statistical analysis of student records for the two cohorts to ascertain any effect of correlation between: PAL; student ethnicity; and student parental employment on student academic performance and placement attainment. Findings The results indicate that PAL has no significant impact on the academic performance; however, PAL has a positive impact on the placement/internship attainment for BME students and students from parental households with parents in non-managerial/professional employment. Research limitations/implications The research limitations are that the cohorts are small, but more equal diverse mix of different social categories than any other courses. However, as the cohorts are less than 30 students, comparing social categories the data sets are small to have absolute confidence in the statistical results of academic performance. Even the t-test has its limitations as the subjects are human, and there are multiple personal factors that can impact an individual academic performance; therefore, the data sets are heterostatic. Practical implications The results highlight that there is need for pedagogy interventions to support: ideally all BME students from all social categery to secure placements; BME students who are unable to go on placement to gain supplementary learning that has the same impact on their personal development and learning as placement/internship experience; and White students from managerial/professional family households to engage more in their studies. Social implications Not addressing and providing appropriate pedagogy interventions, in the wider context not addressing/resolving the BME academic and placement attainment gap, a set of students are being disadvantaged to their peers through no fault of their own, and compounding their academic attainment. As academics we have a duty to provide every opportunity to develop our student attainment, and as student entry is generally homogeneous, all students should attain it. Originality/value Previous research evaluation of PAL programmes has focused on quantitative students surveys and qualitative semi-structured research interviews with students on their student engagement and learning experience. On the other hand, this paper evaluates the intervention through conducting a quantitative statistical analysis of the student records to evaluate the impact of PAL on a cohort’s performance on different social categories (classifications) and compares the results to a cohort of another group with a similar student profile, but without PAL intervention implementation.

scholarly journals AI INFLUENCE IN COVID-19 DETECTION

2021 ◽  
Vol 23 (07) ◽  
pp. 1116-1120
Author(s):  
Cijil Benny ◽  
Keyword(s):  
Neural Network ◽  
Statistical Analysis ◽  
Convolutional Neural Network ◽  
Case Reports ◽  
Ct Scans ◽  
Data Sets ◽  
X Rays ◽  
Medical Field ◽  
Primary Key ◽  
Made In

This paper is on analyzing the feasibility of AI studies and the involvement of AI in COVID interrelated treatments. In all, several procedures were reviewed and studied. It was on point. The best-analyzing methods on the studies were Susceptible Infected Recovered and Susceptible Exposed Infected Removed respectively. Whereas the implementation of AI is mostly done in X-rays and CT- Scans with the help of a Convolutional Neural Network. To accomplish the paper several data sets are used. They include medical and case reports, medical strategies, and persons respectively. Approaches are being done through shared statistical analysis based on these reports. Considerably the acceptance COVID is being shared and it is also reachable. Furthermore, much regulation is needed for handling this pandemic since it is a threat to global society. And many more discoveries shall be made in the medical field that uses AI as a primary key source.

scholarly journals A branch and bound algorithm for protein structure refinement from sparse NMR data sets 1 1Edited by F. Cohen

1999 ◽  
Vol 285 (4) ◽  
pp. 1691-1710 ◽  
Author(s):  
Daron M. Standley ◽  
Volker A. Eyrich ◽  
Anthony K. Felts ◽  
Richard A. Friesner ◽  
Ann E. McDermott
Keyword(s):  
Protein Structure ◽  
Branch And Bound ◽  
Structure Refinement ◽  
Branch And Bound Algorithm ◽  
Data Sets ◽  
Protein Structure Refinement ◽  
Nmr Data

Using multivariate methods on solid-state 13C NMR data of complex materials

1995 ◽  
Vol 315 (1-2) ◽  
pp. 1-14 ◽  
Author(s):  
Hans Karlström ◽  
Mats Nilsson ◽  
Bo Nordén
Keyword(s):  
Solid State ◽  
13C Nmr ◽  
Multivariate Methods ◽  
Complex Materials ◽  
Nmr Data ◽  
Solid State 13C Nmr
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