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Creating in the digital world
Access to digital tools has made it easier than ever for individuals to be creative with media. This important book gives advice on choosing the appropriate platforms and tools to achieve your creative goal, how to use feedback to improve and grow as a digital creator, and how to make sure you get credit for your work, as well as give credit to others where it is due. Inspiring examples show creative young people contributing to the digital world in a positive way, not just taking from it.
Book
Feature selection for text classification: A review
Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of video, audio, text, and images. This is due to the prevalence of novel applications in recent years, such as social media, video sharing, and location based services (LBS), etc. In many multimedia applications, for example, video/image tagging and multimedia recommendation, text classification techniques have been used extensively to facilitate multimedia data processing. In this paper, we give a comprehensive review on feature selection techniques for text classification. We begin by introducing some popular representation schemes for documents, and similarity measures used in text classification. Then, we review the most popular text classifiers, including Nearest Neighbor (NN) method, Naïve Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT), and Neural Networks. Next, we survey four feature selection models, namely the filter, wrapper, embedded and hybrid, discussing pros and cons of the state-of-the-art feature selection approaches. Finally, we conclude the paper and give a brief introduction to some interesting feature selection work that does not belong to the four models.
Journal Article
Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization
Detecting and localizing image manipulation are necessary to counter malicious use of image editing techniques. Accordingly, it is essential to distinguish between authentic and tampered regions by analyzing intrinsic statistics in an image. We focus on JPEG compression artifacts left during image acquisition and editing. We propose a convolutional neural network that uses discrete cosine transform (DCT) coefficients, where compression artifacts remain, to localize image manipulation. Standard CNNs cannot learn the distribution of DCT coefficients because the convolution throws away the spatial coordinates, which are essential for DCT coefficients. We illustrate how to design and train a neural network that can learn the distribution of DCT coefficients. Furthermore, we introduce Compression Artifact Tracing Network that jointly uses image acquisition artifacts and compression artifacts. It significantly outperforms traditional and deep neural network-based methods in detecting and localizing tampered regions.
Journal Article
Digital data storage on DNA tape using CRISPR base editors
While the archival digital memory industry approaches its physical limits, the demand is significantly increasing, therefore alternatives emerge. Recent efforts have demonstrated DNA’s enormous potential as a digital storage medium with superior information durability, capacity, and energy consumption. However, the majority of the proposed systems require on-demand de-novo DNA synthesis techniques that produce a large amount of toxic waste and therefore are not industrially scalable and environmentally friendly. Inspired by the architecture of semiconductor memory devices and recent developments in gene editing, we created a molecular digital data storage system called “DNA Mutational Overwriting Storage” (DMOS) that stores information by leveraging combinatorial, addressable, orthogonal, and independent in vitro CRISPR base-editing reactions to write data on a blank pool of greenly synthesized DNA tapes. As a proof of concept, this work illustrates writing and accurately reading of both a bitmap representation of our school’s logo and the title of this study on the DNA tapes.
DNA is an alternative to data storage materials for its durability, density, and energetics. Here the authors demonstrate the storage of digital information on DNA molecules using base-editing.
Journal Article
Media and social media attention to retracted articles according to Altmetric
The number of retracted articles has grown fast. However, the extent to which researchers and the public are made adequately aware of these retractions and how the media and social media respond to them remains unknown. Here, we aimed to evaluate the media and social media attention received by retracted articles and assess also the attention they receive post-retraction versus pre-retraction. We downloaded all records of retracted literature maintained by the Retraction Watch Database and originally published between January 1, 2010 to December 31, 2015. For all 3,008 retracted articles with a separate DOI for the original and its retraction, we downloaded the respective Altmetric Attention Score (AAS) (from Altmetric) and citation count (from Crossref), for the original article and its retraction notice on June 6, 2018. We also compared the AAS of a random sample of 572 retracted full journal articles available on PubMed to that of unretracted full articles matched from the same issue and journal. 1,687 (56.1%) of retracted research articles received some amount of Altmetric attention, and 165 (5.5%) were even considered popular (AAS>20). 31 (1.0%) of 2,953 with a record on Crossref received >100 citations by June 6, 2018. Popular articles received substantially more attention than their retraction, even after adjusting for attention received post-retraction (Median difference, 29; 95% CI, 17–61). Unreliable results were the most frequent reason for retraction of popular articles (32; 19%), while fake peer review was the most common reason (421; 15%) for the retraction of other articles. In comparison to matched articles, retracted articles tended to receive more Altmetric attention (23/31 matched groups; P-value, 0.01), even after adjusting for attention received post-retraction. Our findings reveal that retracted articles may receive high attention from media and social media and that for popular articles, pre-retraction attention far outweighs post-retraction attention.
Journal Article
Social media exposure, risk perception, preventive behaviors and attitudes during the COVID-19 epidemic in La Paz, Bolivia: A cross sectional study
To investigate the association among social media exposure, risk perception, preventive behaviors, and attitudes toward the COVID-19 epidemic in Bolivia.
We launched an online survey in La Paz and El Alto, Bolivia, during April and May 2020. The questionnaire examined: Socio-demographic factors, Social media use, Risk Perception, Preventive behaviors, attitudes and the willingness to use a vaccine if it were available in the context of the COVID-19 epidemic. A logistic regression was used to evaluate factors associated with risk perception and a structural equation model (SEM) was performed to explore the pathway of the relationship among social media exposure, risk perception and preventive behaviors and attitudes.
Among 886 participants, the most were young adults, between 18-25 years old (73.4%) and 577 (65.1%) were female. During the the week before the survey 387 (43.7%) reported be exposure to social media Covid-19 information almost always or always. Moreover 304 (34.3%) were categorized as with a high risk perception. The multivariable analyses show that being female (aOR = 1.5, CI 95% 1.1-2.1) and having high exposure to Covid-19 information on social media (aOR = 2.5, CI 95% 1.3-5.3) were associated with a higher risk perception for Covid-19. Furthermore, SEM results indicated that risk perception is associated with the adoption of preventive behaviors and attitudes (β = 0.605, p < 0.001) including the acceptance of a vaccine if one were available (β = 0.388, p < 0.001).
Social media exposure to COVID-19 information influences the adoption of preventive attitudes and behaviors through shaping risk perception. Understanding the role of social media during the pandemic could help policymakers and communicators to develop better communication strategies that enable the population to adopt appropriate attitudes and behaviors.
Journal Article
Modeling the spread of fake news on Twitter
Fake news can have a significant negative impact on society because of the growing use of mobile devices and the worldwide increase in Internet access. It is therefore essential to develop a simple mathematical model to understand the online dissemination of fake news. In this study, we propose a point process model of the spread of fake news on Twitter. The proposed model describes the spread of a fake news item as a two-stage process: initially, fake news spreads as a piece of ordinary news; then, when most users start recognizing the falsity of the news item, that itself spreads as another news story. We validate this model using two datasets of fake news items spread on Twitter. We show that the proposed model is superior to the current state-of-the-art methods in accurately predicting the evolution of the spread of a fake news item. Moreover, a text analysis suggests that our model appropriately infers the correction time, i.e., the moment when Twitter users start realizing the falsity of the news item. The proposed model contributes to understanding the dynamics of the spread of fake news on social media. Its ability to extract a compact representation of the spreading pattern could be useful in the detection and mitigation of fake news.
Journal Article
Callus and endosperm green fluorescence reporter‐assisted selection system in maize CRISPR/Cas9 gene editing
Background
Genome editing using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) has emerged as a promising approach for functional gene analysis and genetic improvement. Since stable transformation remains the primary method for implementing this system, the ultimate goal in crop breeding programs would require the selection of transgene-free plants with the CRISPR/Cas expression cassette removed.
Results
In this study, we developed an endosperm-specific fluorescence reporter-assisted selection system for CRISPR/Cas9 gene editing (pAZS22-eGFP/CRISPR/Cas9) in maize (
Zea mays
L.), utilizing enhanced green fluorescent protein (eGFP) expressed specifically in the endosperm to facilitate the easy identification of transgenic and transgene-free plants from the T
1
generation on. In addition, the 22 kDa alpha zein (
z1C1_10
) promoter from maize, employed in this system, has been shown to be active in both callus and endosperm, thereby being able to enhance the accuracy of transformant identification during the tissue culture process by reducing false positives compared to the traditional selective media methods. Our studies targeting the
ZmSnRK2.1
or
Dwarf1
(
D1
) genes demonstrated a reasonable editing efficiency, with rates ranging from 56.3% for T
0
plants targeting
ZmSnRK2.1,
to 87.5% and 100% for T
1
plants targeting
D1
and
ZmSnRK2.1
, respectively. In addition, we successfully identified 1 transgene-free homozygous
d1
mutant in the T
1
generation and 7 transgene-free homozygous
snrk2.1
mutants in the T
2
generation.
Conclusions
The pAZS22-eGFP/CRISPR/Cas9 system provides an efficient tool for gene editing, transformant selection and transgene status identification in maize breeding.
Journal Article
Comparison of public discussions of gene editing on social media between the United States and China
The world’s first gene-edited babies event has stirred controversy on social media over the use of gene editing technology. Understanding public discussions about this controversy will provide important insights about opinions of science and facilitate informed policy decisions. This study compares public discussion topics about gene editing on Twitter and Weibo, as wel asthe evolution of these topics over four months. Latent Dirichlet allocation (LDA) was used to generate topics for 11,244 Weibo posts and 57,525 tweets from September 25, 2018, to January 25, 2019. Results showed a difference between the topics on Twitter versus Weibo: there were more nuanced discussions on Twitter, and the discussed topics between platforms focused on different areas. Temporal analysis showed that most discussions took place around gene-edited events. Based on our findings, suggestions were provided for policymakers and science communication practitioners to develop more effective communication strategies toward audiences in China and the U.S.
Journal Article