Variation in pelvic morphology may prevent the identification of anterior pelvic tilt

Pelvic tilt is often quantified using the angle between the horizontal and a line connecting the anterior superior iliac spine (ASIS) and the posterior superior iliac spine (PSIS). Although this angle is determined by the balance of muscular and ligamentous forces acting between the pelvis and adjacent segments, it could also be influenced by variations in pelvic morphology. The primary objective of this anatomical study was to establish how such variation may affect the ASIS-PSIS measure of pelvic tilt. In addition, we also investigated how variability in pelvic landmarks may influence measures of innominate rotational asymmetry and measures of pelvic height. Thirty cadaver pelves were used for the study. Each specimen was positioned in a fixed anatomical reference position and the angle between the ASIS and PSIS measured bilaterally. In addition, side-to-side differences in the height of the innominate bone were recorded. The study found a range of values for the ASIS-PSIS of 0–23 degrees, with a mean of 13 and standard deviation of 5 degrees. Asymmetry of pelvic landmarks resulted in side-to-side differences of up to 11 degrees in ASISPSIS tilt and 16 millimeters in innominate height. These results suggest that variations in pelvic morphology may significantly influence measures of pelvic tilt and innominate rotational asymmetry

Optical tweezers: wideband microrheology

Microrheology is a branch of rheology having the same principles as conventional bulk rheology, but working on micron length scales and micro-litre volumes. Optical tweezers have been successfully used with Newtonian fluids for rheological purposes such as determining fluid viscosity. Conversely, when optical tweezers are used to measure the viscoelastic properties of complex fluids the results are either limited to the material's high-frequency response, discarding important information related to the low-frequency behavior, or they are supplemented by low-frequency measurements performed with different techniques, often without presenting an overlapping region of clear agreement between the sets of results. We present a simple experimental procedure to perform microrheological measurements over the widest frequency range possible with optical tweezers. A generalised Langevin equation is used to relate the frequency-dependent moduli of the complex fluid to the time-dependent trajectory of a probe particle as it flips between two optical traps that alternately switch on and off.Comment: 13 pages, 6 figures, submitted to Special Issue of the Journal of Optic

Managerial Skills and Small Business Start-ups in the Rural Food Sector

The research is intended as an initial study to address managerial skills of small business start-ups to minimise small-business failures. Primary data from 126 respondents have been collected, consisting of stakeholders in the rural food sector in North Wales. Primary data was analysed by using mixed-methods research. The findings will be employed to design an online syllabus and virtual learning environment (VLE) to support the small-business community in the rural food sector including start-ups in North Wales. This research has received funding through the Welsh Government Rural Communities –Rural Development Programme 2014-2020 (Cadwyn Clwyd), which is funded by the European Agricultural Fund for Rural Development and the Welsh Government

Leading from the engine room

© Springer International Publishing AG, part of Springer Nature 2018. This paper explores relationships and challenges facing teams creating simulation-based learning environments. Drawing on our experience of governance within Australian Indigenous cultures and specific work incidents as case studies, we explore tensions, triumphs and insights occurring during collaborative ventures intended to produce online learning activities. Our view is ‘from the engine room’ - at that point where technology and design expertise reframe creative ‘story boards’ into ‘interactive learning experiences’ requiring productive harnessing of diversity. Creation of scenario-based learning environments requires an understanding of specific content, along with the array of available learning pathways. Appreciating pitfalls likely to hinder the design process is vital. Scenarios use specific, and specialized artefacts and technologies to create interactive learning environments; computer-based technologies make the process even more complex, requiring highly specialized skills to contribute particular elements. More and more people are involved, and a greater number of specializations contribute to the final product. We draw on Human Computer Interaction practices to explore designer - developer interfaces and explore what may be involved in developing aware, conscious leadership of this emergent complexity. Words penned by Harrison (1967) aptly encapsulate our theme - “We were talking about the space between us all”

Energy efficient spiking neural network neuromorphic processing to enable decentralised service workflow composition in support of multi-domain operations

Future Multi-Domain Operations (MDO) will require the coordination of hundreds—even thousands—of devices and component services. This will demand the capability to rapidly discover the distributed devices/services and combine them into different workflow configurations, thereby creating the applications necessary to support changing mission needs. Motivated by neuromorphic processing models, in previous work it was shown that this can be achieved by using hyperdimensional symbolic semantic vector representations of the services/devices and workflows. Using a process of vector exchange the required services are dynamically discovered and inter-connected to achieve the required tasks. In network edge environments, the capability to perform these tasks with minimum energy consumption is critical. This paper describes how emerging spiking neural network (SNN) neuromorphic processing devices can be used to perform the required hyperdimensional vector computation (HDC) with significant energy savings compared to what can be achieved using traditional CMOS implementations

Enabling discoverable trusted services for highly dynamic decentralized workflows

Fifth generation (5G) mobile networks will revolutionize edge-based computing by providing fast and reliable network capabilities to remote sensors, devices and microservices. This heralds new opportunities for researchers, allowing remote instrumentation and analytic capabilities to be as accessible as local resources. The increased availability of remote data and services presents new opportunities for collaboration, yet introduces challenges for workflow orchestration, which will need to adapt to consider an increased choice of available services, including those from trusted partners and the wider community. In this paper we outline a workflow approach that provides decentralized discovery and orchestration of verifiably trustable services in support of multi-party operations. We base this work on the adoption of standardised data models and protocols emerging from hypermedia research, which has demonstrated success in using combinations of Linked Data, Web of Things (WoT) and semantic technologies to provide mechanisms for autonomous goal-directed agents to discover, execute and reuse new heterogeneous resources and behaviours in large-scale, dynamic environments. We adopt Verifiable Credentials (VCs) to securely share information amongst peers based on prior service usage in a cryptographically secure and tamperproof way, providing a trust-based framework for ratifying service qualities. Collating these new service description channels and integrating with existing decentralized workflow research based on vector symbolic architecture (VSA) provides an enhanced semantic search space for efficient and trusted service discovery that will be necessary for 5G edge-computing environments

Hyperdimensional computing using time-to-spike neuromorphic circuits

Vector Symbolic Architectures (VSA) can be used to encode complex objects, such as services and sensors, as hypervectors. Such hypervectors can be used to perform efficient distributed service discovery and workflow orchestration in communications constrained environments typical of the Internet of Things (IoT). In these environments, energy efficiency is of great importance. However, most hypervector representations use dense i.i.d element values and performing energy efficient hyperdimensional computing operations on such dense vectors is challenging. More recently, a sparse binary VSA scheme has been proposed based on a slot encoding having M slots with B bit positions per slot, in which only one bit per slot can be set. This paper shows for the first time that such sparse encoded hypervectors can be mapped into energy-efficient time-to-spike Spiking Neural Network (SNN) circuits, such that all the required VSA operations can be performed. Example VSA SNN circuits have been implemented in the Brian 2 SNN simulator, showing that all VSA binding, bundling, unbinding, and clean-up memory operations execute correctly. Based on these circuit implementations, estimates of the energy and processing time required to perform the different VSA operations on typical SNN neuromorphic devices are estimated. Recommendations for the design of future SNN neuromorphic processor hardware that can more efficiently perform VSA processing are also made