Evaluation of a multidisciplinary Tier 3 weight management service for adults with morbid obesity, or obesity and comorbidities, based in primary care

A multidisciplinary Tier 3 weight management service in primary care recruited patients with a body mass index ≥40 kg·m−2, or 30 kg·m−2 with obesity-related co-morbidity to a 1-year programme. A cohort of 230 participants was recruited and evaluated using the National Obesity Observatory Standard Evaluation Framework. The primary outcome was weight loss of at least 5% of baseline weight at 12 months. Diet was assessed using the two-item food frequency questionnaire, activity using the General Practice Physical Activity questionnaire and quality of life using the EuroQol-5D-5L questionnaire. A focus group explored the participants' experiences. Baseline mean weight was 124.4 kg and mean body mass index was 44.1 kg·m−2. A total of 102 participants achieved 5% weight loss at 12 months. The mean weight loss was 10.2 kg among the 117 participants who completed the 12-month programme. Baseline observation carried forward analysis gave a mean weight loss of 5.9 kg at 12 months. Fruit and vegetable intake, activity level and quality of life all improved. The dropout rate was 14.3% at 6 months and 45.1% at 1 year. Focus group participants described high levels of satisfaction. It was possible to deliver a Tier 3 weight management service for obese patients with complex co-morbidity in a primary care setting with a full multidisciplinary team, which obtained good health outcomes compared with existing services

Lithological Discrimination of Anorthosite using ASTER data in Oddanchatram Area, Dindigul district, Tamil Nadu, India

The present study applies with hyperspectral remote sensing techniques to map the lithology of the Oddanchatram anorthosite. The hyperspectral data were subjected to Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Minimum Noise Fraction (MNF), Pixel Purity Index (PPI) and n-Dimensional Visualization for better lithology mapping. The proposed study area has various typical rock types. The PCA, ICA and MNF have been proposed best band combination for effectiveness of lithological mapping such as PCA (R: G: B=2:1:3), MNF (R: G: B=4:3:2) and ICA (R: G: B=3:1:2). The derived lithological map has compared with published geological map from Geological Survey of India and validated with field investigation. Therefore, ASTER data based lithological mapping are fast, cost-effective and more accurate

Analysis and Measurement of Wave Guides Using Poisson Method

The Poisson equation is used to analyze and measure the waveguide in quick and exact calculation of Green's capacity. For this reason, Green's capacity is composed as far as Jacobian elliptic capacities including complex contentions. Another calculation for the quick and precise assessment of such Green's capacity is definite. The principle advantage of this calculation is effectively appeared inside the casing of the Limit Integral Resonant Mode Expansion technique, where a generous decrease of the computational exertion identified with the assessment of the referred to Green's capacity is gotten

THERMAL ANALYSIS OF AUTOMOTIVE CYLINDER HEAD MADE BY ALUMINIUM METAL MATRIX COMPOSITE REINFORCED WITH NANO ALUMINA

Metal Matrix Nano Composites (MMNC’s) have been developed to meet the demand for lighter materials with significant improvements in mechanical and physical properties like high strength, excellent wear resistance, good thermal conductivity, low thermal expansion coefficient with particulate reinforcements. Aluminium based nano composites (AA356 – nano Al2O3) with three different percentage (1%, 1.5%, 2.5% Wt) of nano – alumina particulate reinforcement (~40 nm) were fabricated using in-situ stir casting technique. Mechanical properties characterization which strongly depends on microstructural properties of reinforcement revealed that the presence of nano – alumina particulates lead to simultaneous increase in hardness, UTS, wear behaviour. The results revealed that UTS, Hardness, Wear behaviour increases with the increase in the percentage of reinforcement of nano – Al2O3 whereas the thermal conductivity drops with increasing percentage of reinforcement when compared to the base alloy AA356. An attempt is made in the present study to review the opportunities of using such a MMNC developed in automotive brake drum replacing the current system using cast iron

Effect of Inorganic Fillers on the Friction Properties of Polyamide 66

Organic materials are those which  have carbon elements in them and the inorganic materials are those which  do not have carbon  elements and those obtained from earth materials such as minerals and the atmosphere.  The inorganic materials have advantages such as high thermal stability, chemical stability etc.  Fly ash and silica fume are inorganic industrial wastes which are produced in large quantities during production of power and silicon respectively. These are the sources of land pollution and this pollution could be minimized if they are successfully reused in appropriate applications.  . The polymer composites are becoming suitable alternative materials for metals in various tribological applications and so wear and friction studies of these materials gain significance. Polyamide 66, also known as Nylon 66 are engineering polymers used in such applications. Nylon was reinforced with these fillers in 5 to 25 % weight fraction increasing in steps of 5%, using a twin- screw extruder. The friction tests were carried out under dry sliding conditions in a pin-on-disc type friction and wear monitoring test rig at different normal loads and at a constant sliding distance and velocity. Friction coefficient of both composites have found to be decreased than pure Nylon. The friction coefficient of fly ash reinforced Nylon is lesser than the silica fume filled nylon at all the tested conditions

Cluster Based Image Retrieval

ABSTRACT: Typical content-based image retrieval (CBIR) system query results are a set of images sorted by feature similarities with respect to the query. However, images with high feature similarities to the query may be very different from the query in terms of semantics. This is known as the semantic gap. We introduce a novel image retrieval scheme CLUster-based rEtrieval of images by unsupervised learning which tackles the semantic gap problem based on a hypothesis: semantically images tend to be clustered in some feature space. CLUE attempts to capture semantic concepts by learning the way that images of the same semantics are similar and retrieving image clusters instead of a set of ordered images. Clustering in CLUE is dynamic. In particular, clusters formed depend on which images are retrieved in response to the query therefore; clusters give the algorithm as well as the user's semantic relevant clues as to where to navigate. CLUE is a general approach that can be combined with any real-valued symmetric similarity measure. Thus it may be embedded in many current CBIR systems. Experimental results based on a database of about 60,000 images from COREL demonstrate improved performance