Deakin University

About: Deakin University is a education organization based out in Burwood, Victoria, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 12118 authors who have published 46470 publications receiving 1188841 citations. The organization is also known as: Deakin.

Robust, self-healing superamphiphobic fabrics prepared by two-step coating of fluoro-containing polymer, fluoroalkyl silane, and modified silica nanoparticles

Abstract: A robust, superamphiphobic fabric with a novel self-healing ability to autorepair from chemical damage is prepared by a two-step wet-chemistry coating technique using an easily available material system consisting of poly(vinylidene fluoride-co-hexafluoropropylene), fluoroalkyl silane, and modified silica nanoparticles. The coated fabrics can withstand at least 600 cycles of standard laundry and 8000 cycles of abrasion without apparently changing the superamphiphobicity. The coating is also very stable to strong acid/base, ozone, and boiling treatments. After being damaged chemically, the coating can restore its super liquid-repellent properties by a short-time heating treatment or room temperature ageing. This simple but novel and effective coating system may be useful for the development of robust protective clothing for various applications.

Sedentary behavior and depression among adults: a review.

Abstract: Physically inactive lifestyles and sedentary behaviors (SB) are key contributors to ill health. Although the association between SB (e.g., watching TV/using the computer) and physical health has been well documented, increasing research has focused on the possible link between SB and mental health (e.g., depression). This review aims to investigate the effect of SB on the risk of depression in adults. A systematic search for original research articles investigating associations between SB and depression in adults was performed using the several electronic data bases. A total of seven observational and four intervention studies were included in this review. All observational studies found positive associations between SB and risk of depression, while intervention studies showed contradictory results. Evidence for the relationship between SB and risk of depression in adults is limited by methodological weaknesses. However, on balance, this review suggests that SB is associated with an increased risk of depression. Further studies are needed assessing different types of SB and depression; the interrelationship between physical activity, SB, and depression; causal links between SB and depression; and intervention strategies aimed at reducing SB and their effects on risk of depression.

Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data

Abstract: Deep learning techniques for point cloud data have demonstrated great potentials in solving classical problems in 3D computer vision such as 3D object classification and segmentation. Several recent 3D object classification methods have reported state-of-the-art performance on CAD model datasets such as ModelNet40 with high accuracy (~92\%). Despite such impressive results, in this paper, we argue that object classification is still a challenging task when objects are framed with real-world settings. To prove this, we introduce ScanObjectNN, a new real-world point cloud object dataset based on scanned indoor scene data. From our comprehensive benchmark, we show that our dataset poses great challenges to existing point cloud classification techniques as objects from real-world scans are often cluttered with background and/or are partial due to occlusions. We identify three key open problems for point cloud object classification, and propose new point cloud classification neural networks that achieve state-of-the-art performance on classifying objects with cluttered background. Our dataset and code are publicly available in our project page https://hkust-vgd.github.io/scanobjectnn/.