Superconducting joints of Bi-2212/Ag tapes and laminates

Different types of HTS joints of Bi-2212/Ag tapes and laminates, which are fabricated by dip-coating and partial-melt processes, have been investigated. All joints are prepared using green single and laminated tapes and according to the scheme: coating-joining-processing. The heat treated tapes have critical current (Ic) between 7 and 27 A, depending on tape thickness and the number of Bi-2212 ceramic layers in laminated tapes. It is found that the current transport properties of joints depend on the type of laminate, joint configuration and joint treatment, Ic losses in joints of Bi-2212 tapes and laminates are attributed to defects in their structure, such as pores, secondary phases and misalignment of Bi-2212 grains near the Ag edges. By optimizing joint configuration, current transmission up to 100% is achieved for both single tapes and laminated tapes.

Melt-textured YBa2Cu3O7-x wires having plate-like grains

YBCO wires which consist of well oriented plate-like fine grains are fabricated using a moving furnace to achieve higher mechanical strength. Melt-texturing experiments have been undertaken on YBCO wires with two different compositions: YBa1.5Cu2.9O7-x, and YBa1.8Cu3.0O7-x. Wires are extruded from a mixture of precursor powders (formed by a coprecipitation process) then textured by firing in a moving furnace. Size of secondary phases such as barium cuprate and copper oxide, and overall composition of the sample affect the orientation of the fine grains. At zero magnetic field, the YBa1.5Cu2.9O7-x wire shows the highest critical current density of 1,450 Acm-2 and 8,770 Acm-2 at 77K and 4.2K, respectively. At 1 T, critical current densities of 30 Acm-2 and 200 Acm-2, respectively, are obtained at 77K and 4.2K. Magnetisation curves are also obtained for one sample to evaluate critical current density using the Bean model. Analysis of the microstructure indicates that the starting composition of the green body significantly affects the achievement of grain alignment via melt-texturing processes.

Microstructural characterization of quenched melt-textured YBa2Cu3O7-δ materials

The microstructure of YBa2Cu3O7-δ (YBCO) materials, melt-textured in air and quenched from the temperature range 900-990°C, has been characterized using a combination of x-ray diffractometry, optical microscopy, scanning electron microscopy, transmission electron microscopy, and energy dispersive x-ray spectrometry. BaCu2O2 and BaCuO2 were found to coexist in samples quenched from the temperature range 920-960°C. The formation of BaCu2O2 preceded the formation of YBCO. Once the YBCO had formed, BaCu2O2 was present at the solidification front filling the space between nearly parallel platelets of YBCO. Large Y2BaCuO5 particles at the solidification front appeared divided into smaller ones as a result of their dissolution in the liquid that quenched as BaCu2O2.

The formation of YBa2Cu3O7-x in melt-texture heat treatments

A study of the bulk formation of YBa2Cu3O7-x from the Y2BaCuO5 plus liquid regime reveals that phase formation occurs at appreciable rates below 950°C in air. This result has been observed for phase-pure YBa2Cu3O7-x starting material given two types of heat treatment: held at 1100°C and slow-cooled from 1030°C at 6°C/h or heat-treated isothermally. Differential thermal analysis, with a cooling rate of 10°C/min indicates that the degree of undercooling for the peritectic formation of YBa2Cu3O7-x is greater than 100°C. © 1994.

Social signal processing for pain monitoring using a hidden conditional random field

utomatic pain monitoring has the potential to greatly improve patient diagnosis and outcomes by providing a continuous objective measure. One of the most promising methods is to do this via automatically detecting facial expressions. However, current approaches have failed due to their inability to: 1) integrate the rigid and non-rigid head motion into a single feature representation, and 2) incorporate the salient temporal patterns into the classification stage. In this paper, we tackle the first problem by developing a “histogram of facial action units” representation using Active Appearance Model (AAM) face features, and then utilize a Hidden Conditional Random Field (HCRF) to overcome the second issue. We show that both of these methods improve the performance on the task of pain detection in sequence level compared to current state-of-the-art-methods on the UNBC-McMaster Shoulder Pain Archive.

A comparative study on the mineralogy, chemistry and chronology of the Apollo 16 crystalline impact melt breccias. Part II: Chronology.

The controversy on how to interpret the ages of lunar highland breccias has recently been discussed by James [1]. Are the measured ages testimony of true events in lunar history; do they represent the age of the ancient crustal rocks, mixed ages of unequilibrated matrix-phenocryst relationships, or merely thermal events subsequent to the formational event ? It is certain from analyses of terrestrial impact melt breccias that the melt matrix of whole impact melt sheets is isotopically equilibrated due to the extensive mixing process of the early cratering stage [2,3]. It has been shown that isotopic equilibration takes place between impact melt matrix and target rock clasts therein, with the intensity of isotopic exchange depending on the degree of shock metamorphism, thermal metamorphism and the size of the clasts [4]. Therefore, impact melt breccias - if they are relatively clast-poor and mineralogically well studied - can be considered to be the most reliable source for information on the impact history of the lunar highland.

Dermal fibroblast infiltration of poly(ε-caprolactone) scaffolds fabricated by melt electrospinning in a direct writing mode

Melt electrospinning in a direct writing mode is a recent additive manufacturing approach to fabricate porous scaffolds for tissue engineering applications. In this study, we describe porous and cell-invasive poly (ε-caprolactone) scaffolds fabricated by combining melt electrospinning and a programmable x–y stage. Fibers were 7.5 ± 1.6 µm in diameter and separated by interfiber distances ranging from 8 to 133 µm, with an average of 46 ± 22 µm. Micro-computed tomography revealed that the resulting scaffolds had a highly porous (87%), three-dimensional structure. Due to the high porosity and interconnectivity of the scaffolds, a top-seeding method was adequate to achieve fibroblast penetration, with cells present throughout and underneath the scaffold. This was confirmed histologically, whereby a 3D fibroblast-scaffold construct with full cellular penetration was produced after 14 days in vitro. Immunohistochemistry was used to confirm the presence and even distribution of the key dermal extracellular matrix proteins, collagen type I and fibronectin. These results show that melt electrospinning in a direct writing mode can produce cell invasive scaffolds, using simple top-seeding approaches.

Featureless visual processing for SLAM in changing outdoor environments

Vision-based SLAM is mostly a solved problem providing clear, sharp images can be obtained. However, in outdoor environments a number of factors such as rough terrain, high speeds and hardware limitations can result in these conditions not being met. High speed transit on rough terrain can lead to image blur and under/over exposure, problems that cannot easily be dealt with using low cost hardware. Furthermore, recently there has been a growth in interest in lifelong autonomy for robots, which brings with it the challenge in outdoor environments of dealing with a moving sun and lack of constant artificial lighting. In this paper, we present a lightweight approach to visual localization and visual odometry that addresses the challenges posed by perceptual change and low cost cameras. The approach combines low resolution imagery with the SLAM algorithm, RatSLAM. We test the system using a cheap consumer camera mounted on a small vehicle in a mixed urban and vegetated environment, at times ranging from dawn to dusk and in conditions ranging from sunny weather to rain. We first show that the system is able to provide reliable mapping and recall over the course of the day and incrementally incorporate new visual scenes from different times into an existing map. We then restrict the system to only learning visual scenes at one time of day, and show that the system is still able to localize and map at other times of day. The results demonstrate the viability of the approach in situations where image quality is poor and environmental or hardware factors preclude the use of visual features.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Abstract: Texture enhancement is an important component of image processing, with extensive application in science and engineering. The quality of medical images, quantified using the texture of the images, plays a significant role in the routine diagnosis performed by medical practitioners. Previously, image texture enhancement was performed using classical integral order differential mask operators. Recently, first order fractional differential operators were implemented to enhance images. Experiments conclude that the use of the fractional differential not only maintains the low frequency contour features in the smooth areas of the image, but also nonlinearly enhances edges and textures corresponding to high-frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we applied the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other fractional differential operators, our new algorithms provide higher signal to noise values, which leads to superior image quality.

Digital social signal processing - theorectical underpinning and research agenda

Organizations make increasingly use of social media in order to compete for customer awareness and improve the quality of their goods and services. Multiple techniques of social media analysis are already in use. Nevertheless, theoretical underpinnings and a sound research agenda are still unavailable in this field at the present time. In order to contribute to setting up such an agenda, we introduce digital social signal processing (DSSP) as a new research stream in IS that requires multi-facetted investigations. Our DSSP concept is founded upon a set of four sequential activities: sensing digital social signals that are emitted by individuals on social media; decoding online data of social media in order to reconstruct digital social signals; matching the signals with consumers’ life events; and configuring individualized goods and service offerings tailored to the individual needs of customers. We further contribute to tying loose ends of different research areas together, in order to frame DSSP as a field for further investigation. We conclude with developing a research agenda.

Composites for delivery of therapeutics : combining melt electrospun scaffolds with loaded electrosprayed microparticles

A novel strategy is reported to produce biodegradable microfiber-scaffolds layered with high densities of microparticles encapsulating a model protein. Direct electrospraying on highly porous melt electrospun scaffolds provides a reproducible scaffold coating throughout the entire architecture. The burst release of protein is significantly reduced due to the immobilization of microparticles on the surface of the scaffold and release mechanisms are dependent on protein-polymer interactions. The composite scaffolds have a positive biological effect in contact with precursor osteoblast cells up to 18 days in culture. The scaffold design achieved with the techniques presented here endorses these new composite scaffolds as promising templates for growth factor delivery.

High resolution melt analysis : a novel method for studying the genetic relatedness of Pseudomonas aeruginosa isolates from clinical and environmental sources

A novel method was developed for studying the genetic relatedness of Pseudomonas aeruginosa isolates from clinical and environmental sources. This bacterium is ubiquitous in the natural environment and is an important pathogen known to infect Cystic Fibrosis (CF) patients. The transmission route of strains has not yet been defined; current theories include acquisition from an environmental source or through patient-to-patient spread. A highly discriminatory, bioinformatics based, DNA typing method was developed to investigate the relatedness of clinical and environmental isolates. This study found a similarity between the environmental and several CF clonal strains and also highlighted occurrence of environmental P. aeruginosa strains in CF infections.

Melt-electrospun polycaprolactone-strontium substituted bioactive glass scaffolds for bone regeneration

Polycaprolactone (PCL) is a resorbable polymer used extensively in bone tissue engineering owing to good structural properties and processability. Strontium substituted bioactive glass (SrBG) has the ability to promote osteogenesis and may be incorporated into scaffolds intended for bone repair. Here we describe for the first time, the development of a PCL-SrBG composite scaffold incorporating 10% (weight) of SrBG particles into PCL bulk, produced by the technique of melt-electrospinning. We show that we are able to reproducibly manufacture composite scaffolds with an interconnected porous structure and, furthermore, these scaffolds were demonstrated to be non-cytotoxic in vitro. Ions present in the SrBG component were shown to dissolve into cell culture media and promoted precipitation of a calcium phosphate layer on the scaffold surface which in turn led to noticeably enhanced alkaline phosphatase activity in MC3T3-E1 cells compared to PLC-only scaffolds. These results suggest that melt-electrospun PCL-SrBG composite scaffolds show potential to become effective bone graft substitutes.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.