3-D Registration on Carotid Artery imaging data: MRI for different timesteps

A common problem which is faced by the researchers when dealing with arterial carotid imaging data is the registration of the geometrical structures between different imaging modalities or different timesteps. The use of the "Patient Position" DICOM field is not adequate to achieve accurate results due to the fact that the carotid artery is a relatively small structure and even imperceptible changes in patient position and/or direction make it difficult. While there is a wide range of simple/advanced registration techniques in the literature, there is a considerable number of studies which address the geometrical structure of the carotid artery without using any registration technique. On the other hand the existence of various registration techniques prohibits an objective comparison of the results using different registration techniques. In this paper we present a method for estimating the statistical significance that the choice of the registration technique has on the carotid geometry. One-Way Analysis of Variance(ANOVA) showed that the p-values were <0.0001 for the distances of the lumen from the centerline for both right and left carotids of the patient case that was studied.Comment: 4 pages, 4 figures, 1 table, preprint submitted to IEEE-EMBC 201

Biologically Inspired Near Extinct System Reconstruction

Recovery software system operations from a state of extensive damage without human intervention is a challenging problem as it may need to be based on a different infrastructure from the one that the system was originally designed for and deployed on (i.e., computational and communication devices) and significant reorganization of system functionalities. In this paper, we introduce a bio-inspired approach for reconstructing nearly extinct complex software systems. Our approach is based on encoding a computational DNA (co-DNA) of a system and computational analogues of biological processes to enable the transmission of co-DNA over computational devices and, through it, the transformation of these devices into system cells that can realise chunks of the system functionality, and spread further its reconstruction process

Artificial Neural Networks for Solving Ordinary and Partial Differential Equations

We present a method to solve initial and boundary value problems using artificial neural networks. A trial solution of the differential equation is written as a sum of two parts. The first part satisfies the boundary (or initial) conditions and contains no adjustable parameters. The second part is constructed so as not to affect the boundary conditions. This part involves a feedforward neural network, containing adjustable parameters (the weights). Hence by construction the boundary conditions are satisfied and the network is trained to satisfy the differential equation. The applicability of this approach ranges from single ODE's, to systems of coupled ODE's and also to PDE's. In this article we illustrate the method by solving a variety of model problems and present comparisons with finite elements for several cases of partial differential equations.Comment: LAtex file, 26 pages, 21 figs, submitted to IEEE TN

Automatic Seizure Detection Based on Time-Frequency Analysis and Artificial Neural Networks

The recording of seizures is of primary interest in the evaluation of epileptic patients. Seizure is the phenomenon of rhythmicity discharge from either a local area or the whole brain and the individual behavior usually lasts from seconds to minutes. Since seizures, in general, occur infrequently and unpredictably, automatic detection of seizures during long-term electroencephalograph (EEG) recordings is highly recommended. As EEG signals are nonstationary, the conventional methods of frequency analysis are not successful for diagnostic purposes. This paper presents a method of analysis of EEG signals, which is based on time-frequency analysis. Initially, selected segments of the EEG signals are analyzed using time-frequency methods and several features are extracted for each segment, representing the energy distribution in the time-frequency plane. Then, those features are used as an input in an artificial neural network (ANN), which provides the final classification of the EEG segments concerning the existence of seizures or not. We used a publicly available dataset in order to evaluate our method and the evaluation results are very promising indicating overall accuracy from 97.72% to 100%

The preferences of participants in small-scale sport events: A conjoint analysis case study from Taiwan

The primary objective of this study was an investigation of participants\u27 preferences for a cycling orientated sport tourism event using conjoint analysis. Respondents in a survey were presented with a range of different event alternatives related to the characteristics of proposed small-scale cycling events to draw out useful conclusions about the ideal scenario of such a sporting event that would be the most attractive and desirable for those who compete. A questionnaire, in two parts, was developed and distributed to 195 bicyclers during an event in Kaohsiung, Taiwan and the data was analysed using SPSS Conjoint at the aggregate level (pooled data). Based on the preferences expressed by the athletes the three most important factors were: "preferred season to organizing the event", "parallel organised trade shows & exhibitions" and "entertainment & awards". The findings of this study provide event coordinators and sport marketers with practical insights into event planning and possibility of development of effective marketing strategies designed to reach and attract more participants to these types of activities. This investigation is unique since is one of the first to use a full design of seven parameters in the conjoint analysis model to comprehensively examine athlete\u27s preferences

Investigating the feasibility and acceptability of the HOLOBalance system compared with standard care in older adults at risk for falls: study protocol for an assessor blinded pilot randomised controlled study

INTRODUCTION: Approximately one in three of all older adults fall each year, with wide ranging physical, psychosocial and healthcare-related consequences. Exercise-based interventions are the cornerstone for falls prevention programmes, yet these are not consistently provided, do not routinely address all components of the balance system and are often not well attended. The HOLOBalance system provides an evidence-based balance training programme delivered to patients in their home environment using a novel technological approach including an augmented reality virtual physiotherapist, exergames and a remote monitoring system. The aims of this proof-of-concept study are to (1) determine the safety, acceptability and feasibility of providing HOLOBalance to community dwelling older adults at risk for falls and (2) provide data to support sample size estimates for a future trial. METHODS: A single (assessor) blinded pilot randomised controlled proof of concept study. 120 participants will be randomised to receive an 8-week home exercise programme consisting of either: (1) HOLOBalance or (2) The OTAGO Home Exercise Programme. Participants will be required to complete their exercise programme independently under the supervision of a physiotherapist. Participants will have weekly telephone contact with their physiotherapist, and will receive home visits at weeks 0, 3 and 6. Outcome measures of safety, acceptability and feasibility, clinical measures of balance function, disability, balance confidence and cognitive function will be assessed before and immediately after the 8 week intervention. Acceptability and feasibility will be explored using descriptive statistics, and trends for effectiveness will be explored using general linear model analysis of variance. ETHICS AND DISSEMINATION: This study has received institutional ethical approvals in Germany (reference: 265/19), Greece (reference: 9769/24-6-2019) and the UK (reference: 19/LO/1908). Findings from this study will be submitted for peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT04053829. PROTOCOL VERSION: V.2, 20 January 2020

Spinal cord compression by a solitary metastasis from a low grade leydig cell tumour: a case report and review of the literature

<p>Abstract</p> <p>Background</p> <p>Leydig tumour is rare and there are only three cases with metastatic disease reported.</p> <p>Case presentation</p> <p>A 52 year-old Caucasian male was admitted, on emergency basis to the Orthopaedic Department with six weeks history of increasing midthoracic back pain, change in gait, poor balance, subjective weakness and numbness of the lower trunk and legs. MRI scan showed change in the signal intensity of T4 and T5 vertebral body but their height were maintained. Urgent T4 and T5 corpectomies, decompression of the spinal cord and reconstruction of the vertebral bodies were performed followed by radiotherapy. Neurological status significantly improved with a mild residual numbness over the dorsum of the right foot. The histology of the excised tumour was identical to the primary. At 2 years follow-up visit the patient is neurologically stable and disease free without other organs metastases.</p> <p>Conclusion</p> <p>This is the first case in English literature, which shows that spinal metastases could occur even in the early stage of Leydig cell tumour, without other organs involvement. Aggressive surgical management of spinal metastases combined with post operative radiotherapy can give a better chance for long survivorship.</p

Progress in the analysis of membrane protein structure and function

Structural information on membrane proteins is sparse, yet they represent an important class of proteins that is encoded by about 30% of all genes. Progress has primarily been achieved with bacterial proteins, but efforts to solve the structure of eukaryotic membrane proteins are also increasing. Most of the structures currently available have been obtained by exploiting the power of X-ray crystallography. Recent results, however, have demonstrated the accuracy of electron crystallography and the imaging power of the atomic force microscope. These instruments allow membrane proteins to be studied while embedded in the bi-layer, and thus in a functional state. The low signal-to-noise ratio of cryo-electron microscopy is overcome by crystallizing membrane proteins in a two- dimensional protein-lipid membrane, allowing its atomic structure to be determined. In contrast, the high signal-to- noise ratio of atomic force microscopy allows individual protein surfaces to be imaged at subnanometer resolution, and their conformational states to be sampled. This review summarizes the steps in membrane protein structure determination and illuminates recent progress. (C) 2002 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies

Empowering Community Dwelling Older Citizens to Improve Their Balance with a Novel Technology Platform

The prevalence of balance deficits increases as the population is ageing. Such deficits are associated with the increased incidence of falls which in turn is linked with substantial limited functionality and morbidity. Vestibular rehabilitation therapy (VRT) as a component of the treatment has been shown to be effective in reducing symptoms and improving balance. HOLOBALANCE is an intervention based on a novel technology platform for providing VRT unsupervised, at home which means that motivating citizens to be compliant and promoting empowerment are the cornerstones for its wide adoption. Here we present how citizens empowerment is being addressed in HOLOBALANCE