Development of sustainable biodegradable lignocellulosic hemp fiber/polycaprolactone biocomposites for light weight applications

Biocomposites with poly(ε-caprolactone) (PCL) as matrix and lignocellulosic hemp fiber with varying average aspect ratios (19, 26, 30 and 38) as reinforcement were prepared using twin extrusion process. The influence of fiber aspect ratio on the water absorption behavior and mechanical properties are investigated. The percentage of moisture uptake increased with the aspect ratio, following Fickian behavior. The hemp fiber/PCL biocomposites showed enhanced properties (tensile, flexural and low-velocity impact). The biocomposite with 26 aspect ratio showed the optimal properties, with flexural strength and modulus of 169% and 285% respectively, higher than those of neat PCL. However, a clear reduction on the mechanical properties was observed for water-immersed samples, with reduction in tensile and flexural moduli for the aspect ratio of 26 by 90% and 62%, respectively than those of dry samples. Summarily, the optimal sample provides an eco-friendly alternative to conventional, petroleum-based and non-renewable composites for various applications.Peer reviewedFinal Accepted Versio

Dynamical layer decoupling in a stripe-ordered, high T_c superconductor

In the stripe-ordered state of a strongly-correlated two-dimensional electronic system, under a set of special circumstances, the superconducting condensate, like the magnetic order, can occur at a non-zero wave-vector corresponding to a spatial period double that of the charge order. In this case, the Josephson coupling between near neighbor planes, especially in a crystal with the special structure of La_{2-x}Ba_xCuO_4, vanishes identically. We propose that this is the underlying cause of the dynamical decoupling of the layers recently observed in transport measurements at x=1/8.Comment: 4 pages, 3 figures (one with 3 subfigures); ; new edited version; one new reference (Ref.25); to be published in Physical Review Letters (in press

Non-intrusive robust human activity recognition for diverse age groups

Many elderly prefer to live independently at their own homes. However, how to use modern technologies to ensure their safety presents vast challenges and opportunities. Being able to non-intrusively sense the activities performed by the elderly definitely has great advantages in various circumstances. Non-intrusive activity recognition can be performed using the embedded sensors in modern smartphones. However, not many activity recognition models are robust enough that allow the subjects to carry the smartphones in different pockets with unrestricted orientations and varying deviations. Moreover, to the best of our knowledge, no existing literature studied the difference between the youth and the elderly groups in terms of human activity recognition using smartphones. In this paper, we present our approach to perform robust activity recognition using only the accelerometer readings collected from the smartphone. First, we tested our model on two published data sets and found its performance is encouraging when compared against other models. Furthermore, we applied our model on two newly collected data sets: one consists of only young subjects (mean age = 22.5) and the other consists of only elderly subjects (mean age = 70.5). The experimental results show convincing prediction accuracy for both within and across diverse age groups. This paper fills the blank of elderly activity recognition using smartphones and shows promising results, which will serve as the groundwork of our future extensions to the current model.NRF (Natl Research Foundation, S’pore)Accepted versio

Fractionalization in Fractional Correlated Insulating States at n±1/3n\pm 1/3 filled twisted bilayer graphene

Fractionalization without time-reversal symmetry breaking is a long sought-after goal that manifests non-trivial correlation effects. While exactly solvable models offered many new theoretical insights, the physical realization of time-reversal symmetric fractionalization remained out of reach. The earlier proposal of correlated insulating states at $n \pm 1/3$ filling in twisted bilayer graphene and recent experimental observations of insulating states at those fillings strongly suggest that moir\'e graphene systems provide a new platform to realize time-reversal symmetric fractionalized states. However, the nature of fractional excitations and the effect of quantum fluctuation on the fractional correlated insulating states are unknown. We show that excitations of the fractional correlated insulator phases in the strong coupling limit carry fractional charges and exhibit fractonic restricted mobility. Upon introduction of quantum fluctuations, the resonance of ``lemniscate" structured operators drives the system into ``quantum lemniscate liquid (QLL)" or ``quantum lemniscate solid (QLS)". We propose experimental strategies to observe the fractons and discuss the theoretical implications of the QLL/QLS phases.Comment: 6 + 6 pages, 5 + 4 figure

X-ray Imaging of Transplanar Liquid Transport Mechanisms in Single Layer Textiles

Understanding the penetration of liquids within textile fibers is critical for the development of next-generation smart textiles. Despite substantial research on liquid penetration in the plane of the textile, little is known about how the liquid penetrates in the thickness direction. Here we report a time-resolved high-resolution X-ray measurement of the motion of the liquid–air interface within a single layer textile, as the liquid is transported across the textile thickness following the deposition of a droplet. The measurement of the time-dependent position of the liquid meniscus is made possible by the use of ultrahigh viscosity liquids (dynamic viscosity from 10⁵ to 2.5 × 10⁶ times larger than water). This approach enables imaging due to the slow penetration kinetics. Imaging results suggest a three-stage penetration process with each stage being associated with one of the three types of capillary channels existing in the textile geometry, providing insights into the effect of the textile structure on the path of the three-dimensional liquid meniscus. One dimensional kinetics studies show that our data for the transplanar penetration depth Δ<i>x</i>_L vs time do not conform to a power law, and that the measured rate of penetration for long times is smaller than that predicted by Lucas–Washburn kinetics, challenging commonly held assumptions regarding the validity of power laws when applied to relatively thin textiles

Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection

Quality assessment of medical images is essential for complete automation of image processing pipelines. For large population studies such as the UK Biobank, artefacts such as those caused by heart motion are problematic and manual identification is tedious and time-consuming. Therefore, there is an urgent need for automatic image quality assessment techniques. In this paper, we propose a method to automatically detect the presence of motion-related artefacts in cardiac magnetic resonance (CMR) images. As this is a highly imbalanced classification problem (due to the high number of good quality images compared to the low number of images with motion artefacts), we propose a novel k-space based training data augmentation approach in order to address this problem. Our method is based on 3D spatio-temporal Convolutional Neural Networks, and is able to detect 2D+time short axis images with motion artefacts in less than 1ms. We test our algorithm on a subset of the UK Biobank dataset consisting of 3465 CMR images and achieve not only high accuracy in detection of motion artefacts, but also high precision and recall. We compare our approach to a range of state-of-the-art quality assessment methods.Comment: Accepted for MICCAI2018 Conferenc

Extreme Toughness Exhibited in Electrospun Polystyrene Fibers

Polystyrene (PS) commonly exhibits brittle behavior and poor mechanical properties due to the presence of structural heterogeneities promoting localized failure. The removal of this localized failure is shown here by processing PS into fibers with a range of diameters using electrospinning. Mechanical properties of individual electrospun fibers were quantified with atomic force microscopy based nanomechanical tensile testing. The resultant stress–strain behavior of PS fibers highlights considerable enhancement of mechanical properties when fiber diameter decreases below 600 nm such that polystyrene toughness increases significantly by over two orders of magnitude compared to the bulk. Consideration of the network properties of polystyrene is used to demonstrate the increase of draw ratio toward a theoretical limit and is potentially applicable to a range of glassy polymeric materials