Nanotechnology and the Developing World

How nanotechnology can be harnessed to address some of the world's most critical development problem

Calibration strategies for use of the nanoDot OSLD in CT applications.

Aluminum oxide based optically stimulated luminescent dosimeters (OSLD) have been recognized as a useful dosimeter for measuring CT dose, particularly for patient dose measurements. Despite the increasing use of this dosimeter, appropriate dosimeter calibration techniques have not been established in the literature; while the manufacturer offers a calibration procedure, it is known to have relatively large uncertainties. The purpose of this work was to evaluate two clinical approaches for calibrating these dosimeters for CT applications, and to determine the uncertainty associated with measurements using these techniques. Three unique calibration procedures were used to calculate dose for a range of CT conditions using a commercially available OSLD and reader. The three calibration procedures included calibration (a) using the vendor-provided method, (b) relative to a 120 kVp CT spectrum in air, and (c) relative to a megavoltage beam (implemented with 60 Co). The dose measured using each of these approaches was compared to dose measured using a calibrated farmer-type ion chamber. Finally, the uncertainty in the dose measured using each approach was determined. For the CT and megavoltage calibration methods, the dose measured using the OSLD nanoDot was within 5% of the dose measured using an ion chamber for a wide range of different CT scan parameters (80-140 kVp, and with measurements at a range of positions). When calibrated using the vendor-recommended protocol, the OSLD measured doses were on average 15.5% lower than ion chamber doses. Two clinical calibration techniques have been evaluated and are presented in this work as alternatives to the vendor-provided calibration approach. These techniques provide high precision for OSLD-based measurements in a CT environment

The Evolution of X-ray Bursts in the "Bursting Pulsar" GRO J1744-28

GRO J1744-28, commonly known as the `Bursting Pulsar', is a low mass X-ray binary containing a neutron star and an evolved giant star. This system, together with the Rapid Burster (MXB 1730-33), are the only two systems that display the so-called Type II X-ray bursts. These type of bursts, which last for 10s of seconds, are thought to be caused by viscous instabilities in the disk; however the Type II bursts seen in GRO J1744-28 are qualitatively very different from those seen in the archetypal Type II bursting source the Rapid Burster. To understand these differences and to create a framework for future study, we perform a study of all X-ray observations of all 3 known outbursts of the Bursting Pulsar which contained Type II bursts, including a population study of all Type II X-ray bursts seen by RXTE. We find that the bursts from this source are best described in four distinct phenomena or `classes' and that the characteristics of the bursts evolve in a predictable way. We compare our results with what is known for the Rapid Burster and put out results in the context of models that try to explain this phenomena.Comment: Accepted to MNRAS Aug 17 201

Predictive Modeling Using Shape Statistics for Interpretable and Robust Quality Assurance of Automated Contours in Radiation Treatment Planning

Deep learning methods for image segmentation and contouring are gaining prominence as an automated approach for delineating anatomical structures in medical images during radiation treatment planning. These contours are used to guide radiotherapy treatment planning, so it is important that contouring errors are flagged before they are used for planning. This creates a need for effective quality assurance methods to enable the clinical use of automated contours in radiotherapy. We propose a novel method for contour quality assurance that requires only shape features, making it independent of the platform used to obtain the images. Our method uses a random forest classifier to identify low-quality contours. On a dataset of 312 kidney contours, our method achieved a cross-validated area under the curve of 0.937 in identifying unacceptable contours. We applied our method to an unlabeled validation dataset of 36 kidney contours. We flagged 6 contours which were then reviewed by a cervix contour specialist, who found that 4 of the 6 contours contained errors. We used Shapley values to characterize the specific shape features that contributed to each contour being flagged, providing a starting point for characterizing the source of the contouring error. These promising results suggest our method is feasible for quality assurance of automated radiotherapy contours

Development of an Augmented Reality Equipped Composites Bonded Assembly and Repair for Aerospace Applications

The prosperity of aircraft transportation together with revolutionary promotion of composite components used in commercial aircraft pose enormous challenges to the aircraft composite assembly and repair (especially uncertainties associated with polymer process parameters control, barely visible defects and non-destructive inspection capability to inspect zero-thickness defects). Therefore, an industry solution owning merits on reliability and repeatability of assembly process is at high demand. Augmented Reality (AR), a human computer interaction technology, possesses its exclusive superiority on its capability of inflicting digital mock-up into physical environment. The above property of AR provides colossal opportunities to be utilised into industrial applications to contribute the realisation of automated, efficient, streamlined and reliable process and assembly. The current ongoing research aims at developing an AR System integrated into aircraft composite bonded assembly and repair as a guidance tool to instruct technicians’ repairing operation, mitigate human errors, and reduce duration of repair and assembly. Upon the accomplishment of the System, the researchers would aim to investigate the incorporation of machine learning and deep network algorithms to enable and significantly improve the interactions between the multitude of process parameters involved in the composites assembly control procedures, solely relying upon the AR geometric data. This will ultimately lead to dramatic reduction of sensors in aircraft assembly, mitigation of in-process analysis time, reduction of process and post-process inspection time, and a higher quality assembly. Stepped scarf composite repair embedded with soft composite patches was selected as the archetype to be brought into effect though hard patches were partially examined as well. The AR System has focused on composite patches assembly and vacuum bagging process to address the predicament of miscellaneous steps and fibre directions

Activation of the Unfolded Protein Response Enhances Motor Recovery after Spinal Cord Injury

Spinal cord injury (SCI) is a major cause of paralysis, and involves multiple cellular and tissular responses including demyelination, inflammation, cell death and axonal degeneration. Recent evidence suggests that perturbation on the homeostasis of the endoplasmic reticulum (ER) is observed in different SCI models; however, the functional contribution of this pathway to this pathology is not known. Here we demonstrate that SCI triggers a fast ER stress reaction (1–3 h) involving the upregulation of key components of the unfolded protein response (UPR), a process that propagates through the spinal cord. Ablation of X-box-binding protein 1 (XBP1) or activating transcription factor 4 (ATF4) expression, two major UPR transcription factors, leads to a reduced locomotor recovery after experimental SCI. The effects of UPR inactivation were associated with a significant increase in the number of damaged axons and reduced amount of oligodendrocytes surrounding the injury zone. In addition, altered microglial activation and pro-inflammatory cytokine expression were observed in ATF4 deficient mice after SCI. Local expression of active XBP1 into the spinal cord using adeno-associated viruses enhanced locomotor recovery after SCI, and was associated with an increased number of oligodendrocytes. Altogether, our results demonstrate a functional role of the UPR in SCI, offering novel therapeutic targets to treat this invalidating condition

Integration of professional judgement and decision-making in high-level adventure sports coaching practice

This study examined the integration of professional judgement and decision-making processes in adventure sports coaching. The study utilised a thematic analysis approach to investigate the decision-making practices of a sample of high-level adventure sports coaches over a series of sessions. Results revealed that, in order to make judgements and decisions in practice, expert coaches employ a range of practical and pedagogic management strategies to create and opportunistically use time for decision-making. These approaches include span of control and time management strategies to facilitate the decision-making process regarding risk management, venue selection, aims, objectives, session content, and differentiation of the coaching process. The implication for coaches, coach education, and accreditation is the recognition and training of the approaches that“create time” for the judgements in practice, namely“creating space to think”. The paper concludes by offering a template for a more expertise-focused progression in adventure sports coachin

Key worker services for disabled children: what characteristics of services lead to better outcomes for children and families?

Background: Research has shown that families of disabled children who have a key worker benefit from this service and recent policy initiatives emphasize the importance of such services. However, research is lacking on which characteristics of key worker schemes for disabled children are related to better outcomes for families. Methods: A postal questionnaire was completed by 189 parents with disabled children who were receiving a service in seven key worker schemes in England and Wales. Path analysis was used to investigate associations between characteristics of the services and outcomes for families (satisfaction with the service, impact of key worker on quality of life, parent unmet need, child unmet need). Results: The four path models showed that key workers carrying out more aspects of the key worker role, appropriate amounts of contact with key workers, regular training, supervision and peer support for key workers, and having a dedicated service manager and a clear job description for key workers were associated with better outcomes for families. Characteristics of services had only a small impact on child unmet need, suggesting that other aspects of services were affecting child unmet need. Conclusions: Implications for policy and practice are discussed, including the need for regular training, supervision and peer support for key workers and negotiated time and resources for them to carry out the role. These influence the extent to which key workers carry out all aspects of the key worker's role and their amount of contact with families, which in turn impact on outcomes

A GPU-based finite-size pencil beam algorithm with 3D-density correction for radiotherapy dose calculation

Targeting at the development of an accurate and efficient dose calculation engine for online adaptive radiotherapy, we have implemented a finite size pencil beam (FSPB) algorithm with a 3D-density correction method on GPU. This new GPU-based dose engine is built on our previously published ultrafast FSPB computational framework [Gu et al. Phys. Med. Biol. 54 6287-97, 2009]. Dosimetric evaluations against Monte Carlo dose calculations are conducted on 10 IMRT treatment plans (5 head-and-neck cases and 5 lung cases). For all cases, there is improvement with the 3D-density correction over the conventional FSPB algorithm and for most cases the improvement is significant. Regarding the efficiency, because of the appropriate arrangement of memory access and the usage of GPU intrinsic functions, the dose calculation for an IMRT plan can be accomplished well within 1 second (except for one case) with this new GPU-based FSPB algorithm. Compared to the previous GPU-based FSPB algorithm without 3D-density correction, this new algorithm, though slightly sacrificing the computational efficiency (~5-15% lower), has significantly improved the dose calculation accuracy, making it more suitable for online IMRT replanning