Virtualization Technology to Allocate Data Centre Resources Dynamically Based on Application Demands in Cloud Computing

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A Web-based interactive Student Advising system using Java frameworks

The use of open source frameworks and tools has become popular in Java development. These frameworks and tools have core strengths and weaknesses and are selected accordingly for development. Consequently, one of the key issues that developers face is to integrate and configure these tools together. This paper demonstrates the use of popular Java frameworks and tools to develop a Web-based interactive Student Registration and Advising system

How States Use Medicaid to Cover Key Infant and Early Childhood Mental Health Services: Results of a 50-State Survey (2018 Update)

There is now substantial evidence that young children’s mental health plays a critical role in their early learning and school readiness, long-term school success and self-sufficiency, and future health and mental health outcomes. Fortunately, many states are working to strengthen supports for infants’ and young children’s mental health. This brief examines states’ Medicaid coverage for key infant and early childhood mental health (IECMH) services, along with policies that contribute to service access and quality. It presents the results of an updated 50-state survey that gathered information from state administrators about Medicaid coverage and policies related to the following services for children from birth to age 6: Child screening for social-emotional problems; Maternal depression screening in pediatric and family medicine settings; Developmentally appropriate diagnosis using DC:0–5; Family navigators to help families access services; Mental health services in pediatric, child care and early education, and home settings; Dyadic (parent-child) treatment; Parenting programs to address child mental health need

Structure based rational drug design of selective phosphodiesterase-4 ligands as anti-inflammatory molecules

Phosphodiesterase-4 enzyme (PDE4) has been gaining increasing attention for the last two decades as a pharmacotherapeutic target, as it is involved in the etiology of a variety of pathologies that comprise a majority of inflammation problems concerning respiratory pathway in major aspect. Intense efforts have been directed towards the development of effective and selective PDE4b inhibitors, but not much success has been reported till yet. This is because of the structural similarity between the two isoforms of PDE4, PDE4b (therapeutic effect) and PDE4d (side effect of emesis). Analogues of 1,2-dihydroxy-xanthen-9H-one were designed as selective ligands for PDE4b using the structure based drug design. The selectivity was determined by docking of xanthone analogues in PDE4b and PDE4d active sites respectively using GLIDE docking programme from Schrodinger Inc. ADME properties of the designed ligands were also predicted using QikProp from Schrodinger Inc. Interpretation of protein-ligand interactions and binding modes of xanthone analogues showed that these ligands are more selective for PDE4b than for PDE4d.info:eu-repo/semantics/publishedVersio

Deep-learning based segmentation of challenging myelin sheaths

The segmentation of axons and myelin in electron microscopy images allows neurologists to highlight the density of axons and the thickness of the myelin surrounding them. These properties are of great interest for preventing and anticipating white matter diseases. This task is generally performed manually, which is a long and tedious process. We present an update of the methods used to compute that segmentation via machine learning. Our model is based on the architecture of the U-Net network. Our main contribution consists in using transfer learning in the encoder part of the UNet network, as well as test time augmentation when segmenting. We use the SE-Resnet50 backbone weights which was pre-trained on the ImageNet 2012 dataset. We used a data set of 23 images with the corresponding segmented masks, which also was challenging due to its extremely small size. The results show very encouraging performances compared to the state-of-the-art with an average precision of 92% on the test images. It is also important to note that the available samples were taken from elderly mices in the corpus callosum. This represented an additional difficulty, compared to related works that had samples taken from the spinal cord or the optic nerve of healthy individuals, with better contours and less debri

On the symmetry of the central dome of the Taj Mahal

The Taj Mahal attracts millions of visitors annually. It is renowned for its perfection, symmetry and attention to detail; its beauty and magnificence appeal to almost all viewers. It does, however, possess some slight imperfections that escape most observers. Revisiting both, the appreciations and criticisms, this study analyses possible flaws in the symmetry of the external central dome and discusses likely reasons for the flaws

Improved CTA Coronary Segmentation with a Volume-Specific Intensity Threshold

State-of-the-art CTA imaging equipment has increased increased clinician's ability to make non-invasive diagnoses of coronary heart disease; however, an effective interpretation of the cardiac CTA becomes cumbersome due to large amount of imaged data. Intensity based background suppression is often used to enhance the coronary vasculature but setting a fixed threshold to discriminate coronaries from fatty muscles could be misleading due to non-homogeneous response of contrast medium in CTA volumes. In this work, we propose a volumespecific model of the contrast medium in the coronary segmentation process to improve the segmentation accuracy. The influence of the contrast medium in a CTA volume was modelled by approximating the intensity histogram of the descending aorta with Gaussian approximation. It should be noted that a significant variation in Gaussian mean for 12 CTA volumes validates the need of volume-wise exclusive intensity threshold for accurate coronary segmentation. Moreover, the effectiveness of the adaptive intensity threshold is illustrated with the help of qualitative and quantitative results

Are all metal-on-metal hip revision operations contributing to the National Joint Registry implant survival curves? : a study comparing the London Implant Retrieval Centre and National Joint Registry datasets

AIMS: The National Joint Registry for England, Wales and Northern Ireland (NJR) has extended its scope to report on hospital, surgeon and implant performance. Data linkage of the NJR to the London Implant Retrieval Centre (LIRC) has previously evaluated data quality for hip primary procedures, but did not assess revision records. METHODS: We analysed metal-on-metal hip revision procedures performed between 2003 and 2013. A total of 69 929 revision procedures from the NJR and 929 revised pairs of components from the LIRC were included. RESULTS: We were able to link 716 (77.1%) revision procedures on the NJR to the LIRC. This meant that 213 (22.9%) revision procedures at the LIRC could not be identified on the NJR. We found that 349 (37.6%) explants at the LIRC completed the full linkage process to both NJR primary and revision databases. Data completion was excellent (> 99.9%) for revision procedures reported to the NJR. DISCUSSION: This study has shown that only approximately one third of retrieved components at the LIRC, contributed to survival curves on the NJR. We recommend prospective registry-retrieval linkage as a tool to feedback missing and erroneous data to the NJR and improve data quality. TAKE HOME MESSAGE: Prospective Registry - retrieval linkage is a simple tool to evaluate and improve data quality on the NJR. Cite this article: Bone Joint J 2016;98-B:33-9

A Hybrid Energy Model for Region Based Curve Evolution - Application to CTA Coronary Segmentation

Background and Objective: State-of-the-art medical imaging techniques have enabled non-invasive imaging of the internal organs. However, high volumes of imaging data make manual interpretation and delineation of abnormalities cumbersome for clinicians. These challenges have driven intensive research into efficient medical image segmentation. In this work, we propose a hybrid region-based energy formulation for effective segmentation in computed tomography angiography (CTA) imagery. Methods: The proposed hybrid energy couples an intensity-based local term with an efficient discontinuity-based global model of the image for optimal segmentation. The segmentation is achieved using a level set formulation due to the computational robustness. After validating the statistical significance of the hybrid energy, we applied the proposed model to solve an important clinical problem of 3D coronary segmentation. An improved seed detection method is used to initialize the level set evolution. Moreover, we employed an auto-correction feature that captures the emerging peripheries during the curve evolution for completeness of the coronary tree. Results: We evaluated the segmentation accuracy of the proposed energy model against the existing techniques in two stages. Qualitative and quantitative results demonstrate the effectiveness of the proposed framework with a consistent mean sensitivity and specificity measures of 80% across the CTA data. Moreover, a high degree of agreement with respect to the inter-observer differences justifies the generalization of the proposed method. Conclusions: The proposed method is effective to segment the coronary tree from the CTA volume based on hybrid image based energy, which can improve the clinicians ability to detect arterial abnormalities