scholarly journals FAST-NEPAL: Regionally Calibrated Spectral Method for Reinforced Concrete With Masonry Infills

2022 ◽  
Vol 7 ◽  
Author(s):  
Theodore Cross ◽  
Flavia De Luca ◽  
Gregory E. D. Woods ◽  
Nicola Giordano ◽  
Rama Mohan Pokhrel ◽  
...  
Keyword(s):  
Reinforced Concrete ◽  
Large Scale ◽  
School Design ◽  
Fast Method ◽  
Large Scale Assessment ◽  
Clay Bricks ◽  
Masonry Infills ◽  
Using Data ◽  
Updating Procedure ◽  
Local Material Properties

Reinforced concrete (RC) with masonry infill is one of the most common structural typologies in Nepal, especially in the Kathmandu Valley. Masonry infills are typically made of solid clay bricks produced locally in Nepal. This study aims to calibrate the spectral-based analytical method, namely, FAST, for Nepalese RC-infilled buildings. The FAST method has been initially conceived for Southern European RC buildings with hollow clay brick infills. The calibration is achieved by reviewing code prescriptions and construction practices for RC masonry infills in Nepal and updating the FAST method. The variables of FAST method are calibrated using different information sources and a Bayesian updating procedure to consider the global and local material properties for solid clay bricks. The FAST-NEPAL method obtained is then verified, considering a single school design, for which a detailed state-of-the-art vulnerability assessment is available. Being particularly suitable for large-scale assessment, the method is further validated using data from Ward-35 of Kathmandu Metropolitan City (in the vicinity of Tribhuvan International Airport) obtained from photographic documentation included in a geo-referenced database of buildings collected after the 2015 Nepal earthquake and prepared for census purposes. The comparisons show that the FAST-NEPAL method can be conservative relative to the other data sources for vulnerability and is more accurate at capturing low-level damage. This makes the approach suitable for large-scale preliminary assessment of vulnerability for prioritisation purposes.

scholarly journals Equity, Equality and Diversity in the Nordic Countries—Final Thoughts and Looking Ahead

2020 ◽  
pp. 397-412
Author(s):  
Tove Stjern Frønes ◽  
Andreas Pettersen ◽  
Jelena Radišić ◽  
Nils Buchholtz
Keyword(s):  
World War Ii ◽  
Large Scale ◽  
Scientific Work ◽  
Nordic Countries ◽  
Qualitative Description ◽  
Individual Country ◽  
Large Scale Assessment ◽  
Political Policy ◽  
Using Data ◽  
Further Development

AbstractIn the process of preparing this volume, especially in our review of previous scientific work on the Nordic model of education, it appeared that different researchers approached the topic primarily in the form of historical–political policy analyses (Telhaug, Mediås, & Aasen, 2006) and through the qualitative description of individual country portraits or the differences between these (e.g., Antikainen, 2006; Blossing, Imsen, & Moos, 2014; Lundahl, 2016). In these previous analyses, the question was raised whether a common Nordic model of education can be identified at all and to what extent neoliberal policies and broader globalisation trends affect the further development of education systems in the Nordic countries. The latter has especially been discussed in light of the increased competition between these systems emerging currently, here running against the common thread that was adopted shortly after World War II. In contrast to the works mentioned above, this book explicitly chose a quantitative empirical approach to the topic, linked with the attempt to indicate, measure and evaluate educational equity across the Nordic countries using data from large-scale assessment studies. Thus, the approach of this book was more data driven and descriptive than oriented on the political question of whether a common model exists.

Do higher skill levels lead to better outcomes? The disproportionality between skills and outcomes for women

2020 ◽  
Vol 12 (3-2020) ◽  
pp. 107-123
Author(s):  
Lisanne Heilmann ◽  
Iddo Gal ◽  
Anke Grotlüschen
Keyword(s):  
Large Scale ◽  
Basic Skills ◽  
Gender Pay Gap ◽  
Pay Gap ◽  
Skill Levels ◽  
Men And Women ◽  
Large Scale Assessment ◽  
Managerial Position ◽  
Managerial Positions ◽  
Using Data

This paper looks at men’s and women’s positions in the labour market and relates them to their basic skills. In a meritocratic society higher skills are supposed to relate to higher outcomes. We question whether this relation is equally true for men and women. Using data for 13 countries from the OECD Survey of Adult Skills (PIAAC), an international large-scale assessment, this paper examines monthly wages and a person’s probability to be in a managerial position. Our analyses show that, on average, men with higher skills get higher wages and have a higher probability to be in a managerial position than women with equally high skills. We show that the relation between skills and outcomes is more proportional for men than for women and that the gender pay gap does apply to women and men with similar skills. In addition, the results highlight a gap in managerial positions between men and women with the same basic skills.

Hydrogen storage in porous rocks: the storage capacity of the UK continental shelf

2020 ◽  
Author(s):  
Jonathan Scafidi ◽  
Mark Wilkinson ◽  
Stuart Gilfillan ◽  
Niklas Heinemann
Keyword(s):  
Hydrogen Storage ◽  
Continental Shelf ◽  
Large Scale ◽  
Storage Capacity ◽  
Porous Rocks ◽  
Hydrogen Storage Capacity ◽  
Large Scale Assessment ◽  
Using Data ◽  
The Uk ◽  
Gas Fields

<p>Increasing the amount of renewable energy in the UK reduces greenhouse gas emissions but will also lead to intermittency of supply, especially on a seasonal timescale. Over-producing energy when demand is low and under producing when demand is high requires large-scale storage to redress the balance.  Hydrogen stored over seasonal timescales in subsurface porous rocks can act as a giant battery for the UK and is a flexible energy vector that can be used for heat, transport and electricity generation.</p><p>No large scale assessment of the hydrogen storage capacity of an industrialised region has yet been undertaken. Here, we present a novel method for calculating the hydrogen storage capacity of gas fields and saline aquifers on the UK continental shelf using data previously used to assess carbon-dioxide storage potential.</p>

Using Web-based Testing for Large-Scale Assessment

2013 ◽  
Author(s):  
Laura S. Hamilton ◽  
Stephen P. Klein ◽  
William Lorie
Keyword(s):  
Large Scale ◽  
Web Based ◽  
Large Scale Assessment ◽  
Scale Assessment

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

2020 ◽  
Author(s):  
Christina Schindler ◽  
Hannah Baumann ◽  
Andreas Blum ◽  
Dietrich Böse ◽  
Hans-Peter Buchstaller ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Large Scale ◽  
Active Drug ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Energy Calculation ◽  
Large Scale Assessment ◽  
New Public ◽  
Binding Free Energy Calculations

Here we present an evaluation of the binding affinity prediction accuracy of the free energy calculation method FEP+ on internal active drug discovery projects and on a large new public benchmark set.<br>

Student Perceptions of Community: A Different Perspective

NASPA Journal ◽  
1998 ◽  
Vol 35 (4) ◽  
Author(s):  
Jackie Clark ◽  
Joan Hirt
Keyword(s):  
Student Perceptions ◽  
Large Scale ◽  
Research University ◽  
Small Scale ◽  
Social Environments ◽  
Common Assumption ◽  
Small Communities ◽  
Public Research University ◽  
The Common ◽  
Using Data

The creation of small communities has been proposed as a way of enhancing the educational experience of students at large institutions. Using data from a survey of students living in large and small residences at a public research university, this study does not support the common assumption that small-scale social environments are more conducive to positive community life than large-scale social environments.

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

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