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Scimitar syndrome is a rare condition characterized by partial or complete anomalous pulmonary venous drainage of the lung to the inferior vena cava, right lung hypoplasia and dextroposition of the heart. Haemoptysis is uncommon in adults, although the clinical spectrum is wide. We report a case of a 38-year-old male with scimitar syndrome who had low grade haemoptysis persisting over several years secondary to bronchiectatic changes in his hypoplastic right lung. Conservative measures to manage haemoptysis were unsuccessful and the patient proceeded to bronchial artery embolization. The post-procedure course was complicated by lung infarction and the patient ultimately required pneumonectomy. Deformities of the blood vessels and lungs are complex in scimitar syndrome. Bronchial artery embolization should be approached cautiously to protect pulmonary perfusion. [ABSTRACT FROM AUTHOR]

Purpose: To prospectively evaluate four magnetic resonance sequences [ProSet, fluid attenuation inversion recovery (FLAIR), balanced turbo field echo (B-TFE), T2 Drivel for the lumbosacral plexus and its branches. Materials and Methods: Ten healthy volunteers who underwent four MRI sequences on lumbosacral area were evaluated for image quality (ito 5; 1 = poor, 5 = excellent), the number of visualized bilateral spinal nerves from L2 to Si, the overlapping vessels obscuring the plexus (1 = many, 2 = some, 3 = few), and image quality defining spinal nerves (0 = nonvisualized, 1 = poor, 2 = moderate, 3 = good). Results: The ProSet (mean = 4.2, range 3-5) and B-TFE (mean = 3.7, range 3-5) showed better image quality than others. The number of visualized spinal nerves was the largest on ProSet image (mean = 9.2, range 8-10). FLAIR (mean = 2.1, range 1-3) and 12 Drive sequences (mean = 2.1, range 1-3) discriminated the nerves well from the vessels. The main branches of the lumbosacral plexus were well visualized on both ProSet (mean = 2.9, range 2-3) and FLAIR images (mean = 2.6, range 1-3). All of these were statistically significant. Conclusion: ProSet is the best sequence in the evaluation of the lumbosacral plexus and its major branches while FLAIR can be a complementary sequence for the evaluation of nerves overlapping vascular structures. [ABSTRACT FROM AUTHOR]

The IEEE Wireless Access for Vehicular Environment (WAVE) standard consists of the IEEE 802.11p and the IEEE 1609 specifications supporting fast link establishment as well as broadband data communication in vehicular environment. Although the standard has been widely accepted by industry as well as highway authorities in many countries to be used for the radio communication infrastructure of the next-generation Intelligent Transport System (ITS), it remains open for further enhancements such as seamless handover support. This paper presents two proactive caching and forwarding schemes for seamless handover in IEEE WAVE networks: one for straight highway sections and the other for crossroads and junctions. Practical and efficient handover procedures, based on the proposed schemes, are also presented. Specifically, an on-board unit (OBU) informs the old road-side unit (RSU) about its departure from the coverage area such that the old RSU can forward the buffered packets to candidate RSUs for proactive caching. In handover scenarios around crossroads and junctions, the IEEE 802.11f Move-notify message is used by the new RSU to request the rest of candidate RSUs to purge the cached packets in order to prevent the waste of radio resource. Simulation results show that the proposed schemes outperform conventional schemes. [ABSTRACT FROM AUTHOR]

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model. [ABSTRACT FROM AUTHOR]