The effects of supervised versus non-supervised Pilates mat exercises on non-specific chronic low back pain

Includes bibliographical references.Chronic non-specific low back pain (NSCLBP) is a common low back condition affecting a large proportion of the population suffering from low back pain (LBP). Exercise therapy is recommended as the first line treatment for NSCLBP but no type of exercise has been found to be more effective than another in improving pain and function outcomes. Low back pain trials have compared heterogeneous exercise types to date. Pilates mat classes are a popular form of exercise taught by therapists. The aim of this study was to compare outcomes of an eight-week supervised Pilates mat programme with those of a similar non-supervised home exercise programme with regard to pain intensity, function, medication use, health related quality of life, adherence, and participant satisfaction with such exercise programmes in treating NSCLBP. A randomised control trial was done to compare the effect of a supervised Pilates at programme with a non-supervised home programme of similar exercises. The programmes were comparable for both the type of exercise and the participation duration of programmes (per week) and included the same fourteen exercises with gradual progressions. The Pilates classes were held twice a week for a 45 minute class and the home programme required doing the exercises for 30 minutes, three times a week, for an eight-week period. All participants were women who had been suffering from NSCLBP for longer than six weeks and who had volunteered to participate, or were referred by a therapist. The participants were screened and randomly allocated to the respective groups: a supervised exercise group (SEG) and a home exercise group (HEG). All the individual sessions and the supervised classes were held at a multi-disciplinary centre, which housed both a private physiotherapy practice and a Pilates studio. Outcome measures were measured at baseline, four weeks, eight weeks and 12 weeks by an assessor who was blinded to group allocation. The primary outcomes of pain and function were measured using the Pain Intensity Numeric Rating Scale (PINRS) and the Roland Morris Disability Questionnaire (RMDQ) respectively. Change in medication was measured as a percentage change in medication; mobility of the pelvis and lumbar spine was measured using the fingertip-to-floor (FTF) test; health-related quality of life was assessed using the EQ-5D questionnaire, and the confidence to perform certain tasks was measured using the pain self-efficacy questionnaire (PSEQ). Additionally, patient satisfaction was measured at eight weeks using the Better Backs Patient Satisfaction Questionnaire, and adherence was measured by calculating a percentage of the maximum adherence

Adaptive Modeling Language and Its Derivatives

Adaptive Modeling Language (AML) is the underlying language of an object-oriented, multidisciplinary, knowledge-based engineering framework. AML offers an advanced modeling paradigm with an open architecture, enabling the automation of the entire product development cycle, integrating product configuration, design, analysis, visualization, production planning, inspection, and cost estimation

Cardiopulmonary Exercise Testing in Lung Transplantation: A Review

There has been an increase in lung transplantation in the USA. Lung allocation is guided by the lung allocation score (LAS), which takes into account one measure of exercise capacity, the 6-minute walk test (6MWT). There is a paucity of data regarding the role and value of cardiopulmonary stress test (CPET) in the evaluation of lung transplant recipients while on the transplant waiting list and after lung transplantation. While clearly there is a need for further prospective investigation, the available literature strongly suggests a potential role for CPET in the setting of lung transplant

Calcium intake and knowledge among white adolescent girls in Gauteng, South Africa

Objectives. To determine the knowledge and intake of calcium among white adolescent girls in Gauteng, South Africa. Design. A quantitative study using a questionnaire interview conducted over 13 months (1 June 2000 - 31 July 2001). Settings. Sixteen randomly selected private and state schools in the Gauteng area. Subjects. Adolescent white girls aged between 15 and 17 years. Outcome measures. Calcium intake and knowledge using a food frequency questionnaire (FFQ) and 7-day weighed records (WRS). Results. Mean calcium intake according to the FFQ was 811 mg/day (adequate intake (AI) 1 300 mg/day). Fiftyone per cent of participants had not been given any information relating to calcium and its benefits. Teachers and parents are the most noted sources of information and 31% of the participants knew that adolescence was the most important period for calcium absorption and bone building. Conclusions. Adolescents have low intakes of calcium compared with what is recommended. It is important to develop intervention programmes that target children, adolescents, teachers and mothers alike. It is also imperative to develop awareness of the importance of calcium consumption during childhood and adolescence in order to minimise the possibility of osteoporosis in later life. South African Journal of Clinical Nutrition Vol.17(3) 2004: 102-10

Immediate implant placement by using natural bovine bone substitute and acellular collagen matrix

Adequate bone and soft tissue volume is important to allow proper implants osseointegration, survival and esthetic result. The aim of this case report was to observe an immediate implant placement by using natural bovine bone substitute and acellular collagen matrix to gain better soft tissue result. Upon screw-retained provisional bridge removal after four months, a successful peri-implant soft tissue healing was observed. Then one year after final bridge, a stable soft and hard tissue situation, as well as sufficient implant stability, granules osteointegration into newly formed bone was recorded

Mesurer la masse de trous noirs supermassifs à l’aide de l’apprentissage automatique

Des percées récentes ont été faites dans l’étude des trous noirs supermassifs (SMBH), grâce en grande partie à l’équipe du télescope de l’horizon des évènements (EHT). Cependant, déterminer la masse de ces entités colossales à des décalages vers le rouge élevés reste un défi de taille pour les astronomes. Il existe diverses méthodes directes et indirectes pour mesurer la masse de SMBHs. La méthode directe la plus précise consiste à résoudre la cinématique du gaz moléculaire, un traceur froid, dans la sphère d’influence (SOI) du SMBH. La SOI est définie comme la région où le potentiel gravitationnel du SMBH domine sur celui de la galaxie hôte. Par contre, puisque la masse d’un SMBH est négligeable face à la masse d’une galaxie, la SOI est, d’un point de vue astronomique, très petite, typiquement de quelques dizaines de parsecs. Par conséquent, il faut une très haute résolution spatiale pour étudier la SOI d’un SMBH et pouvoir adéquatement mesurer sa masse. C’est cette nécessité d’une haute résolution spatiale qui limite la mesure de masse de SMBHs à de plus grandes distances. Pour briser cette barrière, il nous faut donc trouver une manière d’améliorer la résolution spatiale d’objets observés à un plus au décalage vers le rouge. Le phénomène des lentilles gravitationnelles fortes survient lorsqu’une source lumineuse en arrière-plan se trouve alignée avec un objet massif en avant-plan, le long de la ligne de visée d’un observateur. Cette disposition a pour conséquence de distordre l’image observée de la source en arrière-plan. Puisque cette distorsion est inconnue et non-linéaire, l’analyse de la source devient nettement plus complexe. Cependant, ce phénomène a également pour effet d’étirer, d’agrandir et d’amplifier l’image de la source, permettant ainsi de reconstituer la source avec une résolution spatiale considérablement améliorée, compte tenu de sa distance initiale par rapport à l’observateur. L’objectif de ce projet consiste à développer une chaîne de simulations visant à étudier la faisabilité de la mesure de la masse d’un trou noir supermassif (SMBH) par cinéma- tique du gaz moléculaire à un décalage vers le rouge plus élevé, en utilisant l’apprentissage automatique pour tirer parti du grossissement généré par la distorsion d’une forte lentille gravitationnelle. Pour ce faire, nous générons de manière réaliste des observations du gaz moléculaire obtenues par le Grand Réseau d’Antennes Millimétrique/Submillimétrique de l’Atacama (ALMA). Ces données sont produites à partir de la suite de simulations hydrody- namiques Rétroaction dans des Environnements Réalistes (FIRE). Dans chaque simulation, l’effet cinématique du SMBH est intégré, en supposant le gaz moléculaire virialisé. Ensuite, le flux d’émission du gaz moléculaire est calculé en fonction de sa vitesse, température, densité, fraction de H2, décalage vers le rouge et taille dans le ciel. Le cube ALMA est généré en tenant compte de la résolution spatiale et spectrale, qui dépendent du nombre d’antennes, de leur configuration et du temps d’exposition. Finalement, l’effet de la forte lentille gravi- tationnelle est introduit par la rétro-propagation du faisceau lumineux en fonction du profil de masse de l’ellipsoïde isotherme singulière (SIE). L’exploitation de ces données ALMA simulées est testée dans le cadre d’un problème de régression directe. Nous entraînons un réseau de neurones à convolution (CNN) à apprendre à prédire la masse d’un SMBH à partir des données simulées, sans prendre en compte l’effet de la lentille. Le réseau prédit la masse du SMBH ainsi que son incertitude, en supposant une distribution a posteriori gaussienne. Les résultats sont convaincants : plus la masse du SMBH est grande, plus la prédiction du réseau est précise et exacte. Tout comme avec les méthodes conventionnelles, le réseau est uniquement capable de prédire la masse du SMBH tant que la résolution spatiale des données permet de résoudre la SOI. De plus, les cartes de saillance du réseau confirment que celui-ci utilise l’information contenue dans la SOI pour prédire la masse du SMBH. Dans les travaux à venir, l’effet des lentilles gravitationnelles fortes sera introduit dans les données pour évaluer s’il devient possible de mesurer la masse de ces mêmes SMBHs, mais à un décalage vers le rouge plus élevé.Recent breakthroughs have been made in the study of supermassive black holes (SMBHs), thanks largely to the Event Horizon Telescope (EHT) team. However, determining the mass of these colossal entities at high redshifts remains a major challenge for astronomers. There are various direct and indirect methods for measuring the mass of SMBHs. The most accurate direct method involves resolving the kinematics of the molecular gas, a cold tracer, in the SMBH’s sphere of influence (SOI). The SOI is defined as the region where the gravitational potential of the SMBH dominates that of the host galaxy. However, since the mass of a SMBH is negligible compared to the mass of a galaxy, the SOI is, from an astronomical point of view, very small, typically a few tens of parsecs. As a result, very high spatial resolution is required to study the SOI of a SMBH and adequately measure its mass. It is this need for high spatial resolution that limits mass measurements of SMBHs at larger distances. To break this barrier, we need to find a way to improve the spatial resolution of objects observed at higher redshifts. The phenomenon of strong gravitational lensing occurs when a light source in the back- ground is aligned with a massive object in the foreground, along an observer’s line of sight. This arrangement distorts the observed image of the background source. Since this distor- tion is unknown and non-linear, analysis of the source becomes considerably more complex. However, this phenomenon also has the effect of stretching, enlarging and amplifying the image of the source, enabling the source to be reconstructed with considerably improved spatial resolution, given its initial distance from the observer. The aim of this project is to develop a chain of simulations to study the feasibility of measuring the mass of a supermassive black hole (SMBH) by kinematics of molecular gas at higher redshift, using machine learning to take advantage of the magnification generated by the distortion of a strong gravitational lens. To this end, we realistically generate observations of molecular gas obtained by the Atacama Large Millimeter/Submillimeter Antenna Array (ALMA). These data are generated from the Feedback in Realistic Environments (FIRE) suite of hydrodynamic simulations. In each simulation, the kinematic effect of the SMBH is integrated, assuming virialized molecular gas. Next, the emission flux of the molecular gas is calculated as a function of its velocity, temperature, density, H2 fraction, redshift and sky size. The ALMA cube is generated taking into account spatial and spectral resolution, which depend on the number of antennas, their configuration and exposure time. Finally, the effect of strong gravitational lensing is introduced by back-propagating the light beam according to the mass profile of the singular isothermal ellipsoid (SIE). The exploitation of these simulated ALMA data is tested in a direct regression problem. We train a convolution neural network (CNN) to learn to predict the mass of an SMBH from the simulated data, without taking into account the effect of the lens. The network predicts the mass of the SMBH as well as its uncertainty, assuming a Gaussian a posteriori distribution. The results are convincing: the greater the mass of the SMBH, the more precise and accurate the network’s prediction. As with conventional methods, the network is only able to predict the mass of the SMBH as long as the spatial resolution of the data allows the SOI to be resolved. Furthermore, the network’s saliency maps confirm that it uses the information contained in the SOI to predict the mass of the SMBH. In future work, the effect of strong gravitational lensing will be introduced into the data to assess whether it becomes possible to measure the mass of these same SMBHs, but at a higher redshift

Immediate implant placement by using natural bovine bone substitute with hyaluronate

Sufficient bone volume is important to allow proper implants osseointegration. The aim of this case report was to observe an immediate implant placement by using xenograft granules with hyaluronate and without any membrane coverage. The augmentation areas were assessed 3 months later during final crown installation and after 1 year and 6 months of implant loading. Satisfactory implant stability, granules osteointegration into newly formed bone, as well as stable soft tissue supported by the granules were observed