A dynamic petri net model for iterative and interactive distributed multimedia presentation

Object Composition Petri Nets (OCPN), Priority Petri Nets (P-Net), Dynamic OCPN (DOCPN) and Enhanced P-Nets (EP-Net) have extended the original Petri Net to achieve the modeling of media synchronization and asynchronous user interactions during multimedia playback. Dynamic Petri Net (DPN) has been conceptualized to tackle existing problems in these two areas of modeling distributed multimedia systems. DPN features dynamic modeling elements which allows iteration and hence is able to reduce graph sizes of synchronous playback models while allowing greater details to be shown. DPN also introduces asynchronous event handling techniques that are powerful and effective. DPN was used in the design and modeling of a multimedia orchestration tool which is a typical representation of an application that works in a distributed multimedia system

How does mandibular advancement with or without maxillary procedures affect pharyngeal airways? An overview of systematic reviews

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Past, present and future of Barrett's oesophagus

Barrett's oesophagus is a condition which predisposes towards development of oesophageal adenocarcinoma, a highly lethal tumour which has been increasing in incidence in the Western world over the past three decades. There have been tremendous advances in the field of Barrett's oesophagus, not only in diagnostic modalities, but also in therapeutic strategies available to treat this premalignant disease. In this review, we discuss the past, present and future of Barrett's oesophagus. We describe the historical and new evolving diagnostic criteria of Barrett's oesophagus, while also comparing and contrasting the British Society of Gastroenterology guidelines, American College of Gastroenterology guidelines and International Benign Barrett's and CAncer Taskforce (BOBCAT) for Barrett's oesophagus. Advances in endoscopic modalities such as confocal and volumetric laser endomicroscopy, and a non-endoscopic sampling device, the Cytosponge, are described which could aid in identification of Barrett's oesophagus. With regards to therapy we review the evidence for the utility of endoscopic mucosal resection and radiofrequency ablation when coupled with better characterization of dysplasia. These endoscopic advances have transformed the management of Barrett's oesophagus from a primarily surgical disease into an endoscopically managed condition.The BEST-1 study was funded by the Medical Research Council gap fund. The BEST-2 study was funded by Cancer Research UK

Lymph node density in silicosis: its relationship with lung function and clinical parameters

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Euclidean space data projection classifier with cartesian genetic programming (CGP)

Most evolutionary based classifiers are built based on generated rules sets that categorize the data into respective classes. This research work is a preliminary work which proposes an evolutionary-based classifier using a simplified Cartesian Genetic Programming (CGP) evolutionary algorithm. Instead on using evolutionary generated rule sets, the CGP generates i) a reference coordinate ii) projection functions to project data into a new 3 Dimensional Euclidean space. Subsequently, a distance boundary function of the new projected data to the reference coordinates is applied to classify the data into their respective classes. The evolutionary algorithm is based on a simplified CGP Algorithm using a 1+4 evolutionary strategy. The data projection functions were evolved using CGP for 1000 generations before stopping to extract the best functions. The Classifier was tested using three PROBEN 1 benchmarking datasets which are the PIMA Indians diabetes dataset, Heart Disease dataset and Wisconsin Breast Cancer (WBC) Dataset based on 10 fold cross validation dataset partitioning. Testing results showed that data projection function generated competitive results classification rates: Cancer dataset (97.71%), PIMA Indians dataset (77.92%) and heart disease (85.86%)

Euclidean Space Data Projection Classifier with Cartesian Genetic Programming (CGP)

Most evolutionary based classifiers are built based on generated rules sets that categorize the data into respective classes. This research work is a preliminary work which proposes an evolutionary-based classifier using a simplified Cartesian Genetic Programming (CGP) evolutionary algorithm. Instead on using evolutionary generated rule sets, the CGP generates i) a reference coordinate ii) projection functions to project data into a new 3 Dimensional Euclidean space. Subsequently, a distance boundary function of the new projected data to the reference coordinates is applied to classify the data into their respective classes. The evolutionary algorithm is based on a simplified CGP Algorithm using a 1+4 evolutionary strategy. The data projection functions were evolved using CGP for 1000 generations before stopping to extract the best functions. The Classifier was tested using three PROBEN 1 benchmarking datasets which are the PIMA Indians diabetes dataset, Heart Disease dataset and Wisconsin Breast Cancer (WBC) Dataset based on 10 fold cross validation dataset partitioning. Testing results showed that data projection function generated competitive results classification rates: Cancer dataset (97.71%), PIMA Indians dataset (77.92%) and heart disease (85.86%)

Effects of mandibular setback with or without maxillary advancement osteotomies on pharyngeal airways: An overview of systematic reviews

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Microscopic metallic air-bridge arrays for connecting quantum devices

We present a single-exposure fabrication technique for a very large array of microscopic air-bridges using a tri-layer resist process with electron-beam lithography. The technique is capable of forming air-bridges with strong metal-metal or metal-substrate connections. This was demonstrated by its application in an electron tunneling device consisting of 400 identical surface gates for defining quantum wires, where the air-bridges are used as suspended connections for the surface gates. This technique enables us to create a large array of uniform one-dimensional channels that are open at both ends. In this article, we outline the details of the fabrication process, together with a study and the solution of the challenges present in the development of the technique, which includes the use of water-IPA (isopropyl alcohol) developer, calibration of the resist thickness, and numerical simulation of the development.</jats:p

Harnessing technology and molecular analysis to understand the development of cardiovascular diseases in Asia: a prospective cohort study (SingHEART)

BACKGROUND: Cardiovascular disease (CVD) imposes much mortality and morbidity worldwide. The use of "deep learning", advancements in genomics, metabolomics, proteomics and devices like wearables have the potential to unearth new insights in the field of cardiology. Currently, in Asia, there are no studies that combine the use of conventional clinical information with these advanced technologies. We aim to harness these new technologies to understand the development of cardiovascular disease in Asia. METHODS: Singapore is a multi-ethnic country in Asia with well-represented diverse ethnicities including Chinese, Malays and Indians. The SingHEART study is the first technology driven multi-ethnic prospective population-based study of healthy Asians. Healthy male and female subjects aged 21-69 years old without any prior cardiovascular disease or diabetes mellitus will be recruited from the general population. All subjects are consented to undergo a detailed on-line questionnaire, basic blood investigations, resting and continuous electrocardiogram and blood pressure monitoring, activity and sleep tracking, calcium score, cardiac magnetic resonance imaging, whole genome sequencing and lipidomic analysis. Outcomes studied will include mortality and cause of mortality, myocardial infarction, stroke, malignancy, heart failure, and the development of co-morbidities. DISCUSSION: An initial target of 2500 patients has been set. From October 2015 to May 2017, an initial 683 subjects have been recruited and have completed the initial work-up the SingHEART project is the first contemporary population-based study in Asia that will include whole genome sequencing and deep phenotyping: including advanced imaging and wearable data, to better understand the development of cardiovascular disease across different ethnic groups in Asia