Primary umbilical endometriosis:a cause of a painful umbilical nodule

A female patient presented with a painful swelling in the umbilicus. Ultrasonography demonstrated a hypodense nodule of 1.8 cm. Surgical exploration revealed a subcutaneous, dark discoloured, lobulated swelling at the bottom of the umbilicus, which turned out to be primary umbilical endometriosis (PUE). Primary umbilical endometriosis is a rare and benign disorder, caused by the presence of ectopic endometrial tissue in the umbilicus, which can present as a painful, discoloured swelling in the umbilicus. The clinical distinction between primary umbilical endometrioses and other causes of an umbilical nodule is difficult. Additional imaging modalities do not show any pathognomonic signs for establishing this diagnose. Surgical exploration and excision are a safe and definitive treatment of primary umbilical endometrioses. This case highlights the importance of including PUE in the differential diagnosis of women with a painful umbilical nodule

Towards segmentation and spatial alignment of the human embryonic brain using deep learning for atlas-based registration

We propose an unsupervised deep learning method for atlas based registration to achieve segmentation and spatial alignment of the embryonic brain in a single framework. Our approach consists of two sequential networks with a specifically designed loss function to address the challenges in 3D first trimester ultrasound. The first part learns the affine transformation and the second part learns the voxelwise nonrigid deformation between the target image and the atlas. We trained this network end-to-end and validated it against a ground truth on synthetic datasets designed to resemble the challenges present in 3D first trimester ultrasound. The method was tested on a dataset of human embryonic ultrasound volumes acquired at 9 weeks gestational age, which showed alignment of the brain in some cases and gave insight in open challenges for the proposed method. We conclude that our method is a promising approach towards fully automated spatial alignment and segmentation of embryonic brains in 3D ultrasound

Application of supervisory control synthesis to MRI scannes : improving evolvability

This paper presents an application of Ramadge-Wonham supervisory control theory to a patient support system for MRI scanners. The obtained controller was implemented and tested on real hardware. A distinguishing feature of the proposed application is that the evolvability of the controller is an essential requirement. By evolvability is the ability to adapt the controller to meet modified control objectives. The experiments conducted in the course of the case-study indicate that the use of supervisory control theory improves the evolvability of the controller

Anti-inflammatory and combined antiinflammatory/ analgesic medication in the early management of iliotibial band friction syndrome A clinical trial

Forty-three athletes presenting with unilateral iliotibial band friction syndrome (ITBFS) were randomly divided into three groups for the first 7 days of treatment (placebo-controlled, double-blind): 1 - placebo (N = 13); 2 - anti-inflammatory medication (N = 14) (Voharen; Geigy); and 3 - analgesicl anti-inflammatory combined medication (N =. 16) (Myprodol; Rio Ethicals). All subjects rested from day 0 to day 7 and all groups received the same physiotherapy outpatient treatment programme from day 3 to day 7. On days 0, 3 and 7 the subjects performed a functional treadmill running test (maximum 30 minutes) during which they reported pain (scale 0-10; 0 = no pain, 10 = unbearable pain) each minute. Total running distance, total running time and the area under the pain v. time curve was calculated. Daily 24-hour recall pain scores were also recorded. The 24-hour recall pain scores decreased significantly for all the groups over the treatment period. This method of assessing efficacy of treatment therefore failed to show differences between groups. In contrast, during the running test only group 3 improved their total running time and distance from day 0 to day 7, whereas in all the groups the area under the pain v. time curve decreased from day 0 to day 7. All the other groups improved total running time and running distance from day 3 to day 7. All three treatment modalities are effective in the early. treatment of ITBFS but physiotherapy in combination with analgesicl anti-inflammatory medication is superior. A functional running test, which is more sensitive than conventional pain-recall· methods in assessing efficacy of treatment in this type of clinical trial, is described

Phonene-based topic spotting on the switchboard corpus

Thesis (MScEng)--Stellenbosch University, 2002.ENGLISH ABSTRACT: The field of topic spotting in conversational speech deals with the problem of identifying "interesting" conversations or speech extracts contained within large volumes of speech data. Typical applications where the technology can be found include the surveillance and screening of messages before referring to human operators. Closely related methods can also be used for data-mining of multimedia databases, literature searches, language identification, call routing and message prioritisation. The first topic spotting systems used words as the most basic units. However, because of the poor performance of speech recognisers, a large amount of topic-specific hand-transcribed training data is needed. It is for this reason that researchers started concentrating on methods using phonemes instead, because the errors then occur on smaller, and therefore less important, units. Phoneme-based methods consequently make it feasible to use computer generated transcriptions as training data. Building on word-based methods, a number of phoneme-based systems have emerged. The two most promising ones are the Euclidean Nearest Wrong Neighbours (ENWN) algorithm and the newly developed Stochastic Method for the Automatic Recognition of Topics (SMART). Previous experiments on the Oregon Graduate Institute of Science and Technology's Multi-Language Telephone Speech Corpus suggested that SMART yields a large improvement over ENWN which outperformed competing phoneme-based systems in evaluations. However, the small amount of data available for these experiments meant that more rigorous testing was required. In this research, the algorithms were therefore re-implemented to run on the much larger Switchboard Corpus. Subsequently, a substantial improvement of SMART over ENWN was observed, confirming the result that was previously obtained. In addition to this, an investigation was conducted into the improvement of SMART. This resulted in a new counting strategy with a corresponding improvement in performance.AFRIKAANSE OPSOMMING: Die veld van onderwerp-herkenning in spraak het te doen met die probleem om "interessante" gesprekke of spraaksegmente te identifiseer tussen groot hoeveelhede spraakdata. Die tegnologie word tipies gebruik om gesprekke te verwerk voor dit verwys word na menslike operateurs. Verwante metodes kan ook gebruik word vir die ontginning van data in multimedia databasisse, literatuur-soektogte, taal-herkenning, oproep-kanalisering en boodskap-prioritisering. Die eerste onderwerp-herkenners was woordgebaseerd, maar as gevolg van die swak resultate wat behaal word met spraak-herkenners, is groot hoeveelhede hand-getranskribeerde data nodig om sulke stelsels af te rig. Dit is om hierdie rede dat navorsers tans foneemgebaseerde benaderings verkies, aangesien die foute op kleiner, en dus minder belangrike, eenhede voorkom. Foneemgebaseerde metodes maak dit dus moontlik om rekenaargegenereerde transkripsies as afrigdata te gebruik. Verskeie foneemgebaseerde stelsels het verskyn deur voort te bou op woordgebaseerde metodes. Die twee belowendste stelsels is die "Euclidean Nearest Wrong Neighbours" (ENWN) algoritme en die nuwe "Stochastic Method for the Automatic Recognition of Topics" (SMART). Vorige eksperimente op die "Oregon Graduate Institute of Science and Technology's Multi-Language Telephone Speech Corpus" het daarop gedui dat die SMART algoritme beter vaar as die ENWN-stelsel wat ander foneemgebaseerde algoritmes geklop het. Die feit dat daar te min data beskikbaar was tydens die eksperimente het daarop gedui dat strenger toetse nodig was. Gedurende hierdie navorsing is die algoritmes dus herimplementeer sodat eksperimente op die "Switchboard Corpus" uitgevoer kon word. Daar is vervolgens waargeneem dat SMART aansienlik beter resultate lewer as ENWN en dit het dus die geldigheid van die vorige resultate bevestig. Ter aanvulling hiervan, is 'n ondersoek geloods om SMART te probeer verbeter. Dit het tot 'n nuwe telling-strategie gelei met 'n meegaande verbetering in resultate

Vortex lattices in strong type-II superconducting two-dimensional strips

We show how to calculate semi-analytically the dense vortex state in strong type-II superconducting nanostructures. For the specific case of a strip, we find vortex lattice solutions which also incorporate surface superconductivity. We calculate the energy cost to displace individual vortex rows parallel to the surfaces and find that this energy oscillates with the magnetic field. Remarkably, we also find that, at a critical field $H^*$ below $H_{c2}$, this ''shear'' energy becomes strictly zero for the surface rows due to an unexpected mismatch with the bulk lattice.Comment: Title, abstract, and some text paragraphs have been rewritte

Patterned Geometries and Hydrodynamics at the Vortex Bose Glass Transition

Patterned irradiation of cuprate superconductors with columnar defects allows a new generation of experiments which can probe the properties of vortex liquids by confining them to controlled geometries. Here we show that an analysis of such experiments that combines an inhomogeneous Bose glass scaling theory with the hydrodynamic description of viscous flow of vortex liquids can be used to infer the critical behavior near the Bose glass transition. The shear viscosity is predicted to diverge as $|T-T_{BG}|^{-z}$ at the Bose glass transition, with $z\simeq 6$ the dynamical critical exponent.Comment: 5 pages, 4 figure