Extraction of Visual Information to Predict Crowdfunding Success

Researchers have increasingly turned to crowdfunding platforms to gain insights into entrepreneurial activity and dynamics. While previous studies have explored various factors influencing crowdfunding success, such as technology, communication, and marketing strategies, the role of visual elements that can be automatically extracted from images has received less attention. This is surprising, considering that crowdfunding platforms emphasize the importance of attention-grabbing and high-resolution images, and previous research has shown that image characteristics can significantly impact product evaluations. Indeed, a comprehensive review of empirical articles (n = 202) that utilized Kickstarter data, focusing on the incorporation of visual information in their analyses. Our findings reveal that only 29.70% controlled for the number of images, and less than 12% considered any image details. In this manuscript, we review the literature on image processing and its relevance to the business domain, highlighting two types of visual variables: visual counts (number of pictures and number of videos) and image details. Building upon previous work that discussed the role of color, composition and figure-ground relationships, we introduce visual scene elements that have not yet been explored in crowdfunding, including the number of faces, the number of concepts depicted, and the ease of identifying those concepts. To demonstrate the predictive value of visual counts and image details, we analyze Kickstarter data. Our results highlight that visual count features are two of the top three predictors of success. Our results also show that simple image detail features such as color matter a lot, and our proposed measures of visual scene elements can also be useful. We supplement our article with R and Python codes that help authors extract image details (https://osf.io/ujnzp/).Comment: 32 pages, 5 figure

Effects of triclosan on host response and microbial biomarkers during experimental gingivitis

AimThis exploratory randomized, controlled clinical trial sought to evaluate anti‐inflammatory and ‐microbial effects of triclosan during experimental gingivitis as assessed by host response biomarkers and biofilm microbial pathogens.Materials and MethodsThirty participants were randomized to triclosan or control dentifrice groups who ceased homecare for 21 days in an experimental gingivitis (EG) protocol. Plaque and gingival indices and saliva, plaque, and gingival crevicular fluid (GCF) were assessed/collected at days 0, 14, 21 and 35. Levels and proportions of 40 bacterial species from plaque samples were determined using checkerboard DNA‐DNA hybridization. Ten biomarkers associated with inflammation, matrix degradation, and host protection were measured from GCF and saliva and analysed using a multiplex array. Participants were stratified as “high” or “low” responders based on gingival index and GCF biomarkers and bacterial biofilm were combined to generate receiver operating characteristic curves and predict gingivitis susceptibility.ResultsNo differences in mean PI and GI values were observed between groups and non‐significant trends of reduction of host response biomarkers with triclosan treatment. Triclosan significantly reduced levels of A. actinomycetemcomitans and P. gingivalis during induction of gingivitis.ConclusionsTriclosan reduced microbial levels during gingivitis development (ClinicalTrials.gov NCT01799226).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134115/1/jcpe12519.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134115/2/jcpe12519_am.pd

A Clustering Approach for Autism based Autistic Trait Classification

Machine learning (ML) techniques can be utilized by physicians, clinicians, as well as other users, to discover Autism Spectrum Disorder (ASD) symptoms based on historical cases and controls to enhance autism screening efficiency and accuracy. The aim of this study is to improve the performance of detecting ASD traits by reducing data dimensionality and eliminating redundancy in the autism dataset. To achieve this, a new semi-supervised ML framework approach called Clustering-based Autistic Trait Classification (CATC) is proposed that uses a clustering technique and validation of the classifiers is done by classification techniques. The proposed method identifies potential autism cases based on their similarity traits as opposed to a scoring function used by many ASD screening tools. Empirical results on different datasets involving children, adolescents, and adults were verified and compared to other common machine learning classification techniques. The results showed that CATC offers classifiers with higher predictive accuracy, sensitivity, and specificity rates than those of other intelligent classification approaches such as Artificial Neural Network (ANN), Random Forest, and Random Trees, and Rule Induction. These classifiers are useful as they are exploited by diagnosticians and other stakeholders involved in ASD screening

I read it on reddit: Exploring the role of online communities in the 2016 US elections news cycle

Reddit has developed into a significant platform for political discussion among Millennials. In this exploratory study, we examine subscription trends on three political sub-forums on Reddit during the 2016 US presidential elections: /The_Donald, /SandersForPresident, and /HillaryClinton. As a theoretical framework, we draw from work on online communities’ group identity and cohesion. Concretely, we investigate how subscription dynamics relate to positive, negative and neutral news events occurring during the election cycle. We classify news events using a sentiment analysis of event-related news headlines. We observe that users who supported Sanders displayed no consolidation of support for Clinton after she won the Democratic Party’s presidential nomination. Secondly, we show that negative news events affected Sanders and Clintons subscription trends negatively, while showing no effect for Donald Trump. This gives empirical credence to Trump’s controversial claim that he could “stand in the middle of 5th Avenue and shoot somebody and not lose any voters”. We offer a number of explanations for the observed phenomena: the nature of the content of the three subreddits, their cultural dynamics, and changing dynamics of partisanship. We posit that the ‘death of expertise’ expresses itself on Reddit as a switch in persuasion tactics from a policy-based to an emotions-based approach, and that group members’ agreement on policy proved a weak marker for online communities’ group identity and cohesion. We also claim that strong partisanship coupled with weak party affiliation among Millennials contributed to the low levels of Democratic support consolidation after Clinton won the nomination

Identification and Characterization of the Lamprey High-Mobility Group Box 1 Gene

High-mobility group box 1 (HMGB1), a highly conserved DNA-binding protein, plays an important role in maintaining nucleosome structures, transcription, and inflammation. We identified a homolog of HMGB1 in the Japanese lamprey (Lampetra japonica). The Lampetra japonica HMGB1 gene (Lj-HMGB1) has over 70% sequence identity with its homologs in jawed vertebrates. Despite the reasonably high sequence identity with other HMGB1 proteins, Lj-HMGB1 did not group together with these proteins in a phylogenetic analysis. We examined Lj-HMGB1 expression in lymphocyte-like cells, and the kidneys, heart, gills, and intestines of lampreys before and after the animals were challenged with lipopolysaccharide (LPS) and concanavalin A (ConA). Lj-HMGB1 was initially expressed at a higher level in the heart, but after treatment with LPS and ConA only the gills demonstrated a significant up-regulation of expression. The recombinant Lj-HMGB1 (rLj-HMGB1) protein bound double-stranded DNA and induced the proliferation of human adenocarcinoma cells to a similar extent as human HMGB1. We further revealed that Lj-HMGB1 was able to induce the production of tumor necrosis factor-α (TNF-α), a pro-inflammatory mediator, in activated human acute monocytic leukemia cells. These results suggest that lampreys use HMGB1 to activate their innate immunity for the purpose of pathogen defense

The Changes in China's Forests: An Analysis Using the Forest Identity

Changes in forest carbon stocks are a determinant of the regional carbon budget. In the past several decades, China has experienced a pronounced increase in forest area and density. However, few comprehensive analyses have been conducted. In this study, we employed the Forest Identity concept to evaluate the changing status of China's forests over the past three decades, using national forest inventory data of five periods (1977–1981, 1984–1988, 1989–1993, 1994–1998, and 1999–2003). The results showed that forest area and growing stock density increased by 0.51% and 0.44% annually over the past three decades, while the conversion ratio of forest biomass to growing stock declined by 0.10% annually. These developments resulted in a net annual increase of 0.85% in forest carbon sequestration, which is equivalent to a net biomass carbon uptake of 43.8 Tg per year (1 Tg = 1012 g). This increase can be attributed to the national reforestation/afforestation programs, environmentally enhanced forest growth and economic development as indicated by the average gross domestic product

Somatic diversification of variable lymphocyte receptors in the agnathan sea lamprey

Although jawless vertebrates are apparently capable of adaptive immune responses, they have not been found to possess the recombinatorial antigen receptors shared by all jawed vertebrates. Our search for the phylogenetic roots of adaptive immunity in the lamprey has instead identified a new type of variable lymphocyte receptors (VLRs) composed of highly diverse leucine-rich repeats (LRR) sandwiched between amino- and carboxy-terminal LRRs. An invariant stalk region tethers the VLRs to the cell surface by means of a glycosyl-phosphatidyl-inositol anchor. To generate rearranged VLR genes of the diversity necessary for an anticipatory immune system, the single lamprey VLR locus contains a large bank of diverse LRR cassettes, available for insertion into an incomplete germline VLR gene. Individual lymphocytes express a uniquely rearranged VLR gene in monoallelic fashion. Different evolutionary strategies were thus used to generate highly diverse lymphocyte receptors through rearrangement of LRR modules in agnathans ( jawless fish) and of immunoglobulin gene segments in gnathostomes ( jawed vertebrates).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62870/1/nature02740.pd