KnowMore: an automated knowledge discovery tool for the FAIR SPARC datasets

Background: This manuscript provides the methods and outcomes of KnowMore, the Grand Prize winning automated knowledge discovery tool developed by our team during the 2021 NIH SPARC FAIR Data Codeathon. The National Institutes of Health Stimulating Peripheral Activity to Relieve Conditions (NIH SPARC) program generates rich datasets from neuromodulation researches, curated according to the Findable, Accessible, Interoperable, and Reusable (FAIR) SPARC data standards. Currently, the process of simultaneously comparing and analyzing multiple SPARC datasets is tedious because it requires investigating each dataset of interest individually and downloading all of them to conduct cross-analyses. It is crucial to enhance this process to enable rapid discoveries across SPARC datasets. Methods: To fill this need, we created KnowMore, a tool integrated into the SPARC Portal that only requires the user to select their datasets of interest to launch an automated discovery process. KnowMore uses several SPARC resources (Pennsieve, o²S²PARC, SciCrunch, protocols.io, Biolucida), data science methods, and machine learning algorithms in the back end to generate various visualizations in the front end intended to help the user identify potential similarities, differences, and relations across the datasets. These visualizations can lead to a new discovery, new hypothesis, or simply guide the user to the next logical step in their discovery process. Results: The outcome of this project is a SPARC portal-ready code architecture that helps researchers to use SPARC datasets more efficiently and fully leverages their FAIR characteristics. The tool has been built and documented such that more data analysis methods and visualization items could be easily added. Conclusions: The potential for automated discoveries from SPARC datasets is huge given the unique SPARC data ecosystem promoting FAIR data practices, and KnowMore has only demonstrated a small highlight of what could be achieved to speed up discoveries from SPARC datasets.

KnowMore: An Automated Knowledge Discovery Tool for the FAIR SPARC Datasets

This manuscript provides the methods and outcomes of KnowMore, the Grand Prize winning automated knowledge discovery tool developed by our team during the 2021 NIH SPARC FAIR Data Codeathon. The NIH SPARC program generates rich datasets from neuromodulation researches, curated according to the Findable, Accessible, Interoperable, and Reusable (FAIR) SPARC data standards. These datasets are publicly available through the SPARC Data Portal at sparc.science. Currently, the process of simultaneously comparing and analyzing multiple SPARC datasets is tedious because it requires investigating each dataset of interest individually and downloading all of them to conduct cross-analyses. It is crucial to enhance this process to enable rapid discoveries across SPARC datasets. To fill this need, we created KnowMore, a tool integrated into the SPARC Portal that only requires the user to select their datasets of interest to launch an automated discovery process. KnowMore uses several SPARC resources (Pennsieve, o2S2PARC, SciCrunch, protocols.io, Biolucida), data science methods, and Machine Learning algorithms in the back end to generate various visualizations in the front end intended to help the user identify potential similarities, differences, and relations across the datasets. These visualizations can lead to a new discovery, new hypothesis, or simply guide the user to the next logical step in their discovery process. The outcome of this project is a SPARC portal-ready code architecture that helps researchers to use SPARC datasets more efficiently and fully leverages their FAIR characteristics. The tool has been built and documented such that more data analysis methods and visualization items could be easily added. The potential for automated discoveries from SPARC datasets is huge given the unique SPARC data ecosystem promoting FAIR data practices, and KnowMore has only demonstrated a small highlight of what could be achieved to speed up discoveries from SPARC datasets.

Yellow Squash and Zucchini Cultivar Selection for Resistance to Cucurbit Leaf Crumple Virus in the Southeastern United States

Large populations of sweetpotato whiteflies (Bemisia tabaci) have become more regular occurrences during the fall months in parts of the southeastern United States. Large populations of sweetpotato whiteflies have resulted in a significant increase in the incidence of sweetpotato whitefly-transmitted viruses, particularly the cucurbit leaf crumple virus (CuLCrV), which has the potential to cause complete yield loss of fall-planted yellow squash and zucchini (Cucurbita pepo). This study evaluated commercial cultivars of yellow squash and zucchini for resistance against CuLCrV and estimated the yield and fruit quality under environmental conditions during the fall growing season in the southeastern United States. A factorial experimental design was conducted with nine yellow squash and 11 zucchini cultivars during Fall 2017, Fall 2018, and Fall 2019 in Tifton, GA. In situ weather stations monitored the weather conditions during growing seasons, and yellow pest monitor cards monitored the sweetpotato whitefly populations in 2018 and 2019. During all growing seasons, yellow squash and zucchini plants were rated weekly for the severity of CuLCrV. Harvests were conducted 12 times during each season, and fruit were graded as fancy, medium, and culls. Rainfall distribution directly affected the sweetpotato whitefly populations during the production year. In 2018, frequent rainfall events created field conditions that reduced the sweetpotato whitefly populations compared with those during 2017 and 2019. The severity of CuLCrV negatively impacted both the yield and quality of fruit of yellow squash and zucchini, and no resistant commercial cultivars of yellow squash or zucchini were identified. Nonetheless, the yellow squash cultivars Lioness, Gold Prize, and Grand Prize, and the zucchini cultivars SV6009YG and SV0914YG had the highest yields when subjected to the highest sweetpotato whitefly populations during the study.

Laurel Tangyuan and Fuwan Chocolate Incident - How to do better people-oriented external communication

The "Fuwan Chocolate", which originated in Pingtung, Taiwan, is a world-famous chocolate brand. In 2020, “Fuwan” won the gold medal during the “World Chocolate Competition”, which known as the "Oscar Award” in the chocolate industry. After winning the grand prize, "Fuwan Chocolate" took advantage of the momentum and launched joint products with well-known brands, such as Laurel Corp (Tangyuan). Unexpectedly, the father of Fuwan’s CEO sexually harassed a female intern five years ago, and the CEO also scolded the victim for the chaotic private life after his father being accused. This old matter that has been 5 years was brought up to the stage again this year. Although Fuwan apologized on their Facebook fan page afterwards, it was not accepted by netizens. After three weeks of uproar, its co-branded manufacturer Laurel announced the suspension of production of chocolate flavor tangyuan in collaboration with Fuwan. Many well-known Taiwanese manufacturers also followed the step in the meanwhile. The established credibility and image are now seriously damaged. This study is mainly to discuss the external communication methods and processing results of "Fuwan" and "Laurel" by comparing the pros and cons of their processing methods. We hope this research will be able to provide a better people-oriented communication method that may combined with local condition as a reference when same incident once happened in the future.

Interdependent lotteries and the jackpot model of lottery demand

Bettors may view different gambles either as substitutes or complements. Assuming that the grand prize is the main driver of the demand for multi-prize lottery bets, this paper presents a theory of lottery sales maximization considering possible complementarity or substitutability among different lottery gambles offered by a single operator. Optimal payout ratios are derived accounting not only for interrelation among games but also for their relative popularity. The new profit optimization rule is then applied to a dataset of two Greek lotteries.

Berni, Antonio (1905–1981)

Antonio Berni is a central figure in 20th-century Argentinean art who employed a number of diverse mediums in his work, experimenting with a wide variety of techniques, from oil painting to collages to large sculptures. Berni frequently incorporated trash and other industrialized, humble materials, into his pieces. The artist’s complex prints, which combined traditional printmaking techniques and collage with found materials, secured him the Grand Prize for Drawing and Printmaking at the 1962 Venice Biennal. Berni’s works usually addressed the inequality and injustices he witnessed in Argentina as a result of the rapid growth in industrialization and consumerism. His works, predominantly figurative, have a cluttered, grimy aspect. At the beginning of his career in the 1920s and early 1930s, Berni was influenced by the Surrealists, with whom he became familiar on a study trip to Europe. During the 1930s, the artist created monumental paintings; he also delineated the movement "Nuevo Realismo" ("New Realism"), an attempt to bring art to a broader audience. In 1933, Berni worked with David Alfaro Siqueiros, Lino Spilimbergo, Juan Castagnino, and Enrique Lázaro on the mural Ejercícioplástico [Plastic Exercise]. He later criticized this experience on the grounds that mural painting could only exist in Argentina with the collaboration of the bourgeoisie.

Højholt, Per (1928–2004)

Per Højholt was one of the most productive and influential Danish writers of the 20th century. He made his debut in 1948 at the age of twenty, when the modernist journal Heretica published his cycle of poems De nøgne. Højholt proceeded to elaborate his own form of radical modernism rooted in the work of, for example, Stéphane Mallarmé, with his first collection of poetry, Poetens hoved (1963). Whereas in the work of Mallarmé the suggestiveness of the language reaches towards a more elevated (truer) form of reality, Højholt’s poetry is postmodern play with language. The oeuvre spans widely, ranging from collections of poems, short prose and essays, to the novel Auricula (2001) and the posthumous fragment Hans Henrik Mattesen—En monografi (2007). Højholt by no means confined himself to the writing desk and the written page. A large part of his work comprised performance and artistic expression in other media: radio readings of poetry, radio montage, radio plays, as well as a variety of public happenings. Højholt was born on 22 July 1928 and died on 15 October 2004. A trained librarian, he worked in that capacity until 1966, subsequently devoting himself to his artistic endeavor until the time of his death. He was awarded the Danish Academy’s Grand Prize in 1982.