A Peeling Art

Action is greater than words, interaction is greater than viewing, and experience is greater than theory. So I came up with a way to make my art into an act of criticism toward consumerism. My art resembles colorful Pop Art on the surface but follows the defiant spirit of Dadaism at the core. It reveals the content full of dark humor and cynicism once the viewer “peels off” the appealing surface by interacting with it. The four artworks analyzed in the paper — Hole, The Twelephone and Alarming Alarm, Self-Destructive Ashtray, and Heavenly Cow — are designed to discomfort viewers by betraying the expectation that comes from how playful they look. So, let me introduce my set of absurd products that will help you actively experience the problem of consumerism and raise awareness about your consumption

Life

This project is about offering a solution to nationally displaced populations. Our group has created a system that will not only provide people with housing but a piece of mind. Nexus Maximus IV The Challenge: Innovation for Refugees and Displaced Populations One of the great challenges of our time is how to help refugees and displaced populations, and how to prevent the causes in the first place. Every minute, 24 people around the world are forced to flee their homes. That’s 34,000 people a day who leave everything behind in the hope of finding safety and a better tomorrow. The impact of war, political, racial and religious conflict, and environmental crises of famine and climate change, have caused great suffering and there is a great opportunity to do better. The issues these populations and the countries who receive them face are diverse and complex. They include public health, housing/built environment, cultural integration, public safety, employment/economic and more. How can innovation address these challenges? How do we create the social systems and products to support a healthy, safe and integrated program for refugees? How do we address the physical, emotional, and social needs of refugees to restore hope and opportunity? The solutions may be as far ranging as the challenges, exploring the acute needs during a crisis, as well as the chronic needs of the permanently displaced; looking at immigration and adjustments to new cultures. We encourage participants to draw upon all disciplines, from health professions to architecture, engineering to design, ethics, communication and every way of thinking we have, to find better ways to innovate on physical solutions, processes, policies, systems, and more. Recap of poster presentations.https://jdc.jefferson.edu/nexusmaximus/1021/thumbnail.jp

Impact of surface ozone interactions on indoor air chemistry : a modelling study

An INdoor air Detailed Chemical Model was developed to investigate the impact of ozone reactions with indoor surfaces (including occupants), on indoor air chemistry in simulated apartments subject to ambient air pollution. The results are consistent with experimental studies showing that approximately 80% of ozone indoors is lost through deposition to surfaces. The human body removes ozone most effectively from indoor air per square meter of surface, but the most significant surfaces for C6-C10 aldehyde formation are soft furniture and painted walls owing to their large internal surfaces. Mixing ratios of between 8 and 11 ppb of C6-C10 aldehydes are predicted to form in apartments in various locations in summer, the highest values are when ozone concentrations are enhanced outdoors. The most important aldehyde formed indoors is predicted to be nonanal (5-7 ppb), driven by oxidation-derived emissions from painted walls. In addition, ozone-derived emissions from human skin were estimated for a small bedroom at nighttime with concentrations of nonanal, decanal, and 4-oxopentanal predicted to be 0.5, 0.7, and 0.7 ppb, respectively. A detailed chemical analysis shows that ozone-derived surface aldehyde emissions from materials and people change chemical processing indoors, through enhanced formation of nitrated organic compounds and decreased levels of oxidants

Chimpanzee lip-smacking facilitates cooperative behaviour

Signalling plays an important role in facilitating and maintaining affiliative or cooperative interactions in social animals. Social grooming in primates is an example of an interaction that requires coordination between partners but little is known about communicative behaviours facilitating this activity. In this study, we analysed the communication of wild chimpanzees of Budongo Forest, Uganda, as they entered and maintained a naturally occurring cooperative interaction: social grooming. We found that lip-smacking, a distinct multimodal oral gesture produced during grooming, coordinated this activity. Lip-smacking at the beginning of grooming bouts was significantly more often followed by longer and reciprocated bouts than silent grooming initiations. Lip-smacks were more likely to be produced when the risk of termination of the interaction by the recipient was high, for instance when grooming vulnerable body parts. Groomers were also more likely to produce lip-smacks during face-to-face grooming where the visual aspect of the signal could be perceived. Data are consistent with the hypothesis that chimpanzee lip-smacks function to coordinate and prolong social grooming, suggesting that this oral signal is an example of a communicative behaviour facilitating cooperative behaviour in chimpanzees

Genetic ancestry is associated with colorectal adenomas and adenocarcinomas in Latino populations

Colorectal cancer rates in Latin American countries are less than half of those observed in the United States. Latin Americans are the resultant of generations of an admixture of Native American, European, and African individuals. The potential role of genetic admixture in colorectal carcinogenesis has not been examined. We evaluate the association of genetic ancestry with colorectal neoplasms in 190 adenocarcinomas, 113 sporadic adenomas and 243 age- and sex-matched controls enrolled in a multicentric case–control study in Colombia. Individual ancestral genetic fractions were estimated using the STRUCTURE software, based on allele frequencies and assuming three distinct population origins. We used the Illumina Cancer Panel to genotype 1,421 sparse single-nucleotide polymorphisms (SNPs), and Northern and Western European ancestry, LWJ and Han Chinese in Beijing, China populations from the HapMap project as references. A total of 678 autosomal SNPs overlapped with the HapMap data set SNPs and were used for ancestry estimations. African mean ancestry fraction was higher in adenomas (0.13, 95% confidence interval (95% CI)=0.11–0.15) and cancer cases (0.14, 95% CI=0.12–0.16) compared with controls (0.11, 95% CI=0.10–0.12). Conditional logistic regression analysis, controlling for known risk factors, showed a positive association of African ancestry per 10% increase with both colorectal adenoma (odds ratio (OR)=1.12, 95% CI=0.97–1.30) and adenocarcinoma (OR=1.19, 95% CI=1.05–1.35). In conclusion, increased African ancestry (or variants linked to it) contributes to the increased susceptibility of colorectal cancer in admixed Latin American population

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database

<div><p>Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen’s kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.</p></div