1,720,964 research outputs found
Dataset of Scanning Tunneling Microscopy (STM) images of model surfaces for elementary steps in catalytic reactions
No full textSTM images presented in the dataset were recorded by the STRAS research group using a Omicron Variable Temperature STM (VT-STM) microscope, in the TASC laboratory of the CNR-IOM in Trieste
Optimization of SEM Instrumental Parameters for Enhanced Imaging Applying Machine Learning
No full textThe scanning electron microscope (SEM) is one of the most versatile instruments available for
characterizing the micro- and nanostructural properties of solid samples. A major reason is the high
resolution that can be achieved when examining bulk objects which makes SEM indispensable in various
fields ranging from materials science to biology.
Although scanning electron microscopy (SEM) is a well-established technology, there is still room for
improvement in both imaging quality and automation. The goal is to achieve an optimal balance between
ease of use and performance while minimizing hardware complexity and instrumentation costs, which
remain a key advantage of SEM. In this context, the implementation of advanced algorithmic methods
for automating acquisition settings is essential to enhance efficiency and reproducibility in analyses.
Given the versatility of SEM and its application to a wide range of materials and samples, we have
developed a generalized approach that is not limited to a specific sample type, maximizing adaptability
and effectiveness across various experimental settings. Instrumental SEM parameters should be
carefully optimized for high-quality SEM imaging. The key parameters that influence image quality can
be recognized as: Electron beam parameters including acceleration voltage, beam current, and spot size;
Geometrical and imaging parameters, which encompass working distance, aperture size, magnification,
focus, and stigmation. Detection and image acquisition settings cover detector type, scan speed (dwell
time), and drift correction. Sample preparation and environmental conditions include sample coating
and chamber pressure.
Optimization of the acquisition parameters is crucial for obtaining high-quality images and accurate
data. Operator-based adjusting of these parameters presents several challenges, including the
interdependence of settings, the risk of sample damage, time-consuming operations, and operator skill
dependencies. Moreover, the sample dependency of the acquisition parameters becomes crucial due to
the wide range of possible applications of SEM characterization. These difficulties underscore the
importance of automation in optimizing operations of SEM settings, making the process more efficient,
consistent, and less prone to error. We developed an algorithm-based approach that can identify the
optimum conditions for accelerating voltage, working distance, and aperture size for each type of
sample.
SEM experiments on target sample are conducted based on a full-factorial design in which parameters
are varied simultaneously, to explore also the cross-correlation of the considered parameters. To assess
image quality, we needed a suitable metric. Since the reference image—obtained under optimum
conditions—served as the goal of our investigation, we chose a no-reference image quality metric. The
acquired images were analyzed using this metric. A polynomial regression model—a type of supervised
learning—was employed as a baseline to determine the optimal operating conditions within the selected
SEM parameter space. By predicting the no‐reference image quality metric for any given setting, the
model guides the identification of parameter adjustments that minimize NIQE (thus maximizing image
quality). Given the small training set, at each new image acquisition, the predicted NIQE is compared
with the computed value, and the model is updated with every new data point, continuously refining its
predictions and enabling fully autonomous optimization while significantly reducing operator
intervention. This approach not only streamlines the SEM imaging process but also significantly reduces
the time required for each imaging session by automating the optimization of key parameters. The
proposed algorithm promises to enhance the efficiency of SEM operations, minimize operatorintervention, and ensure more consistent, accurate, and faster sample characterization across a wide
range of applications
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Towards the FAIRification of Scanning Tunneling Microscopy Images, Data Intelligence (2023) 5 (1): 27–42
Full text linkPublished version
Abstract: In this paper, we describe the data management practices and services developed for making FAIR compliant a scientific archive of Scanning Tunneling Microscopy (STM) images. As a first step, we extracted the instrument metadata of each image of the dataset to create a structured database. We then enriched these metadata with information on the structure and composition of the surface by means of a pipeline that leverages human annotation, machine learning techniques, and instrument metadata filtering. To visually explore both images and metadata, as well as to improve the accessibility and usability of the dataset, we developed “STM explorer” as a web service integrated within the Trieste Advanced Data services (TriDAS) website. On top of these data services and tools, we propose an implementation of the W3C PROV standard to describe provenance metadata of STM images
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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