A computational approach to analyze grain structures of semiconductor compound films: Case study of CdTe/CdS multilayers

First principles characterisation of bio–nano interface

Physical Chemistry Chemical Physics ◽

10.1039/d1cp01116b ◽

2021 ◽

Author(s):

Ian Rouse ◽

David Power ◽

Erik G. Brandt ◽

Matthew Schneemilch ◽

Konstantinos Kotsis ◽

...

Keyword(s):

Titanium Dioxide ◽

First Principles ◽

Computational Approach ◽

Titania Nanoparticles ◽

Coarse Grained ◽

First Principles Study

We present a multiscale computational approach for the first-principles study of bio-nano interactions. Using titanium dioxide as a case study, we evaluate the affinity of titania nanoparticles to water and biomolecules through atomistic and coarse-grained techniques.

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Visualising Ostia’s Processional Landscape Through a Multi-Layered Computational Approach: Case Study of the Cult of the Magna Mater

Open Archaeology ◽

10.1515/opar-2019-0028 ◽

2019 ◽

Vol 5 (1) ◽

pp. 444-467

Author(s):

Katherine A. Crawford

Keyword(s):

Network Analysis ◽

Computational Approach ◽

Urban Network ◽

Agent Based ◽

Agent Based Modelling ◽

Existing Problems ◽

Layered Approach ◽

Religious Landscape ◽

Insight Into

AbstractOstia, the ancient port of Rome, had a rich religious landscape. How processional rituals further contributed to this landscape, however, has seen little consideration. This is largely due to a lack of evidence that attests to the routes taken by processional rituals. The present study aims to address existing problems in studying processions by questioning what factors motivated processional movement routes. A novel computational approach that integrates GIS, urban network analysis, and agent-based modelling is introduced. This multi-layered approach is used to question how spectators served as attractors in the creation of a processional landscape using Ostia’s Campo della Magna Mater as a case study. The analysis of these results is subsequently used to gain new insight into how a greater processional landscape was created surrounding the sanctuary of the Magna Mater.

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Development and Validation of an Integrated Computational Approach for the Modeling of cw-ESR Spectra of Free Radicals in Solution: p-(Methylthio)phenyl Nitronylnitroxide in Toluene as a Case Study

Journal of the American Chemical Society ◽

10.1021/ja065475q ◽

2006 ◽

Vol 128 (49) ◽

pp. 15865-15873 ◽

Cited By ~ 25

Author(s):

Vincenzo Barone ◽

Marina Brustolon ◽

Paola Cimino ◽

Antonino Polimeno ◽

Mirco Zerbetto ◽

...

Keyword(s):

Free Radicals ◽

Esr Spectra ◽

Computational Approach ◽

Development And Validation

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Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter

10.1101/2021.04.22.440839 ◽

2021 ◽

Author(s):

Amanda Kowalczyk ◽

Omotola Gbadamosi ◽

Kathryn Kolor ◽

Jahree Sosa ◽

Claudette St Croix ◽

...

Keyword(s):

Evolutionary Rate ◽

Computational Approach ◽

Transport Mechanisms ◽

Mitochondrial Oxidative Phosphorylation ◽

Mitochondrial Localization ◽

Daunting Task ◽

Pairwise Correlations ◽

Functional Context ◽

Predictive Approaches

AbstractRecent advances in genome sequencing have led to the identification of new ion and metabolite transporters, many of which have not been characterized. Due to the variety of subcellular localizations, cargo and transport mechanisms, such characterization is a daunting task, and predictive approaches focused on the functional context of transporters are very much needed. Here we present a case for identifying a transporter localization using evolutionary rate covariation (ERC), a computational approach based on pairwise correlations of amino acid sequence evolutionary rates across the mammalian phylogeny. As a case study, we find that poorly characterized transporter SLC30A9 (ZnT9) uniquely and prominently coevolves with several components of the mitochondrial oxidative phosphorylation chain, suggesting mitochondrial localization. We confirmed this computational finding experimentally using recombinant human SLC30A9. SLC30A9 loss caused zinc mishandling in the mitochondria, suggesting that under normal conditions it acts as a zinc exporter. We therefore propose that ERC can be used to predict the functional context of novel transporters and other poorly characterized proteins.

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Automated extraction of revision events from keystroke data

Reading and Writing ◽

10.1007/s11145-021-10222-w ◽

2021 ◽

Author(s):

Rianne Conijn ◽

Emily Dux Speltz ◽

Evgeny Chukharev-Hudilainen

Keyword(s):

Writing Process ◽

High Accuracy ◽

Computational Approach ◽

Automatic Extraction ◽

Manual Annotation ◽

Automated Extraction ◽

Computational Approaches ◽

Process Dynamics ◽

Writing Task

AbstractRevision plays an important role in writing, and as revisions break down the linearity of the writing process, they are crucial in describing writing process dynamics. Keystroke logging and analysis have been used to identify revisions made during writing. Previous approaches include the manual annotation of revisions, building nonlinear S-notations, and the automated extraction of backspace keypresses. However, these approaches are time-intensive, vulnerable to construct, or restricted. Therefore, this article presents a computational approach to the automatic extraction of full revision events from keystroke logs, including both insertions and deletions, as well as the characters typed to replace the deleted text. Within this approach, revision candidates are first automatically extracted, which allows for a simplified manual annotation of revision events. Second, machine learning is used to automatically detect revision events. For this, 7120 revision events were manually annotated in a dataset of keystrokes obtained from 65 students conducting a writing task. The results showed that revision events could be automatically predicted with a relatively high accuracy. In addition, a case study proved that this approach could be easily applied to a new dataset. To conclude, computational approaches can be beneficial in providing automated insights into revisions in writing.

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High Fidelity Computational Approach to Validate Spine Biomechanics Measurements: A Case Study to Correct Scoliosis

Volume 2: Biomedical and Biotechnology Engineering ◽

10.1115/imece2009-10426 ◽

2009 ◽

Author(s):

B. Addison ◽

N. Sarigul-Klijn ◽

R. Roberto ◽

A. Jamali ◽

M. Thompson

Keyword(s):

Computational Analysis ◽

Spinous Process ◽

Computational Approach ◽

Experimental Results ◽

High Fidelity ◽

Spine Biomechanics ◽

Biomechanical Behavior ◽

Spinous Processes ◽

Experimental Values

This paper presents a high fidelity computational approach to be used in validation of biomechanics experimental measurements. As a demonstration, a case study involving a spinous process implant to correct scoliosis is presented. The biomechanical behavior of the spinous process and implant under tensile loading is investigated using experiments and computations. The experimental study examined the ultimate strength of calf thoracic and lumbar spinous processes in three pullout directions. A statistical analysis was performed on the experimental results to reveal relationships and variations between pullout direction and vertebral type. The finite element high fidelity computational analysis was performed to validate the experimental results. In the process, the material properties of cortical and trabecular bone were elucidated for calf spinous processes. Good comparisons are obtained. The high fidelity computational approach detailed here should serve useful in validation of experimental values from spine biomechanics experimental.

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A generalized computational approach to predict high-frequency acoustic pressure response of cavity structures for structural health monitoring of wind turbine blades

Wind Engineering ◽

10.1177/0309524x211060552 ◽

2021 ◽

pp. 0309524X2110605

Author(s):

Caleb Traylor ◽

Murat Inalpolat

Keyword(s):

Structural Health Monitoring ◽

Wind Turbine ◽

Health Monitoring ◽

Turbine Blades ◽

Computational Approach ◽

Key Factors ◽

Wind Turbine Blades ◽

Structural Health ◽

Geometrical Acoustics

This paper details the development of a generalized computational approach that enables prediction of cavity-internal sound pressure distribution due to flow-generated noise at high frequencies. The outcomes of this research is of particular interest for development of an acoustics-based structural health monitoring system for wind turbine blades. The methodology builds from existing reduced-order aeroacoustic modeling techniques and ray tracing based geometrical acoustics and is demonstrated on the model NREL 5 MW wind turbine blade as a case study. The computational predictions demonstrated that damage could be successfully detected in the first half of the blade cavity near the root and that the change in frequency content may be indicative of the type of damage that has occurred. This study provides a foundation to analyze specific blades and likely damage cases for determining key factors of system design such as number and placement of sensors as well as for hardware selection.

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Paranoid Transformer: Reading Narrative of Madness as Computational Approach to Creativity

Future Internet ◽

10.3390/fi12110182 ◽

2020 ◽

Vol 12 (11) ◽

pp. 182

Author(s):

Yana Agafonova ◽

Alexey Tikhonov ◽

Ivan P. Yamshchikov

Keyword(s):

Mental State ◽

Computational Approach ◽

Computational Creativity ◽

Chance Discovery ◽

Text Generation ◽

Technical Details ◽

The Impact ◽

Generative System

This paper revisits the receptive theory in the context of computational creativity. It presents a case study of a Paranoid Transformer—a fully autonomous text generation engine with raw output that could be read as the narrative of a mad digital persona without any additional human post-filtering. We describe technical details of the generative system, provide examples of output, and discuss the impact of receptive theory, chance discovery, and simulation of fringe mental state on the understanding of computational creativity.

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