scholarly journals Response to The Challenges of Polydisperse SAXS Data Analysis: Two Different SAXS Studies of PICK1 Produce Different Structural Models

Structure ◽  
2015 ◽  
Vol 23 (11) ◽  
pp. 1969-1970 ◽  
Author(s):  
Simon Erlendsson ◽  
Lise Arleth ◽  
Kenneth Lindegaard Madsen
Keyword(s):  
Data Analysis ◽  
Structural Models ◽  
Saxs Data

scholarly journals The Challenges of Polydisperse SAXS Data Analysis: Two SAXS Studies of PICK1 Produce Different Structural Models

Structure ◽  
2015 ◽  
Vol 23 (11) ◽  
pp. 1967-1968 ◽  
Author(s):  
Malgorzata Boczkowska ◽  
Grzegorz Rebowski ◽  
Roberto Dominguez
Keyword(s):  
Data Analysis ◽  
Structural Models ◽  
Saxs Data

scholarly journals BioXTAS RAW 2.0: the latest in SAXS data analysis

2020 ◽  
Vol 76 (a1) ◽  
pp. a27-a27
Author(s):  
Jesse Hopkins ◽  
Richard Gillilan ◽  
Soren Skou
Keyword(s):  
Data Analysis ◽  
Saxs Data

An Empirical Study to Validate the Technology Acceptance Model in Explaining the Intention to Use Technology among Educational Users

2012 ◽  
pp. 282-294 ◽  
Author(s):  
Timothy Teo
Keyword(s):  
Data Analysis ◽  
Empirical Study ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Structural Models ◽  
Intention To Use ◽  
Acceptance Model ◽  
Acceptance Research ◽  
Study Offer

This study examines a sample (N=239) of pre-service teachers’ self-reported intention to use technology. The Technology Acceptance Model (TAM) was used as a research framework in which findings contribute to technology acceptance research by demonstrating the suitability of the TAM to explain the intention to use technology among educational users. Using the structural equation modelling for data analysis, a good fit was found for both the measurement and structural models. Overall, the results of this study offer evidence that the TAM is effective in predicting pre-service teachers’ intention to use technology. This paper concludes with a discussion of the limitations and recommendations for further study.

An Empirical Study to Validate the Technology Acceptance Model (TAM) in Explaining the Intention to Use Technology among Educational Users

2010 ◽  
Vol 6 (4) ◽  
pp. 1-12 ◽  
Author(s):  
Timothy Teo
Keyword(s):  
Data Analysis ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Structural Models ◽  
Intention To Use ◽  
Equation Modelling ◽  
Acceptance Model ◽  
Acceptance Research ◽  
Study Offer

This study examines a sample (N=239) of pre-service teachers’ self-reported intention to use technology. The Technology Acceptance Model (TAM) was used as a research framework in which findings contribute to technology acceptance research by demonstrating the suitability of the TAM to explain the intention to use technology among educational users. Using the structural equation modelling for data analysis, a good fit was found for both the measurement and structural models. Overall, the results of this study offer evidence that the TAM is effective in predicting pre-service teachers’ intention to use technology. This paper concludes with a discussion of the limitations and recommendations for further study.

Visualizing the elusive open shape of G-actin in solution by SAXS data analysis

2013 ◽  
Vol 435 (4) ◽  
pp. 740-744 ◽  
Author(s):  
Amin Sagar ◽  
Nagesh Peddada ◽  
Ashish k. Solanki ◽  
Vikas Choudhary ◽  
Renu Garg ◽  
...  
Keyword(s):  
Data Analysis ◽  
Saxs Data ◽  
Open Shape

Pitfalls of data mining: triclinic polymorph of 2,2-aziridinedicarboxamide revisited

2007 ◽  
Vol 63 (1) ◽  
pp. 118-123 ◽  
Author(s):  
Marcin Podsiadło ◽  
Kamil Dziubek ◽  
Andrzej Katrusiak
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Powder Diffraction ◽  
Structural Models ◽  
Poor Quality ◽  
Single Crystal Diffraction ◽  
Atom Type ◽  
Acta Cryst ◽  
Diffraction Patterns ◽  
Intermolecular Distances

Several procedures have been employed for validating structural models refined on poor quality single-crystal diffraction data. Analysis of intra- and intermolecular distances in the structures of 2,2-aziridinedicarboxamide polymorphs proved to be a robust means, and a means independent of the chosen unit cell and symmetry, of detecting several incorrect atom-type assignments in the reported structure of the triclinic polymorph of 2,2-aziridinedicarboxamide [Brückner (1982). Acta Cryst. B38, 2405–2408]. The corrected model, refined in the space group P\overline 1, rules out the existence of any conformational polymorphism in this compound. Small differences in the powder-diffraction patterns calculated for the original and corrected structures of the triclinic polymorph illustrate the sensitivity of the above method for polymorph validation.

scholarly journals Masa Kerja: Pemoderasi Pengawasan dan Budaya Organisasi Terhadap Kinerja Karyawan

2021 ◽  
Vol 23 (3) ◽  
pp. 223
Author(s):  
Resty Nurachmi Handayani ◽  
Donny Abdul Rojaq ◽  
Iman Hadi Pamungkas ◽  
Jen Zainal Asyikin Hans
Keyword(s):  
Data Analysis ◽  
Structural Models

Penelitian bermaksud menganalisis masa kerja sebagai pemoderasi pengawasan dan budaya orgaisasi terhadap kinerja. Data diperoleh dari kuesioner yang diberikan kepada 50 karyawan PT. Anugerah Analisis Sempurna melalui google form. Analisis data dengan model struktur diolah menggunakan WarpPLS. Temuan penelitian adalah adanya peran masa kerja dalam memoderasi pengawasan terhadap kinerja tetapi tidak memoderasi budaya organisasi terhadap kinerja.Research intends to analyze working period as a moderation of supervision and a culture of performance. The data was obtained from questionnaires given to 50 employees of PT. Anugerah Analisis Sempurna through google form. Data analysis with structural models is processed using WarpPLS. The study's findings were that there was a role for the work in moderating oversight of performance but not as moderating of the organization's culture toward performance.

Examples of Data Collection and Processing

2018 ◽  
Author(s):  
Eaton E. Lattman ◽  
Thomas D. Grant ◽  
Edward H. Snell
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Crystal Packing ◽  
Real Space ◽  
Quality Data ◽  
Oligomeric State ◽  
Saxs Data ◽  
High Quality Data ◽  
Space Modeling ◽  
Data Collection Procedure

This chapter provides a detailed example of SAXS data analysis from a well behaving system. After collecting the SAXS data, several data analysis procedures are illustrated to ensure the data were of sufficient quality. Many of these steps are performed by comparing multiple concentrations from a dilution series, demonstrating the importance of this step in the data collection procedure for ensuring high quality data. Finally, real space modeling and shape reconstructions are shown to determine the oligomeric state as a tetramer, and identify the correct oligomeric assembly from crystal packing predictions.

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