Today 25% of patients listed for liver transplantation die waiting for a liver to become available. The donor organ pool could be expanded by rescuing the 50% of livers donated after cardiac death (DCD) that are discarded due to the injury caused by prolonged periods of warm ischemia during organ retrieval. Mesenchymal Stromal Cells (MSC) reduce inflammation and promote tissue repair.
Organ transplants save patients with severe end stage organ failure but the need for subsequent lifelong immunosuppression can lead to a number of undesired consequences including the reactivation of viruses of donor or recipient origin. Human cytomegalovirus (HCMV) infection is the most common opportunistic infection in transplant patients and can lead to significant morbidity and mortality.
Cloud hosting environments include large scale distributed storage systems. With the advent of Big Data, especially newer biomedical and biometrics data, collected from wearable monitoring devices, there is a high need for Cloud-based solutions for large scale storage and high bandwidth on-the-fly data analysis for such data. A key problem for IT companies that collect large amounts of biometrics data on-the-fly is their need for real-time solutions for anomaly detection in the collected data.
In the evolution of any industry, there are certain turning points which are crucial for the industry to be prepared for them, in advanced. Wireless sector is close to a number of turning points, from technological aspects, emerging operators business models, and customers diverse demands.
"In this project, a new digital platform will be created through which social interactions among the actors involved in the design & construction projects are detected and correlated to the IFC model of the facility. The created system will form the social network of actors involved in the process of design change, and also will semantically understand and archive the change instances in different phases of a project. By matching the two, the knowledge-base of the system will support the change management in BIM-based projects.
It has always been challenging to manage data at large-scale as there are no standards and best practices currently available for modeling and analysis of data. Currently available solutions rely on limited information and are confined to manual processing which makes the process of data handling and management slow, inefficient and hard. This makes modeling and analysis crucial to be able to track, monitor and manage applications that are complex, critical in nature and produce intensive data.
Pathologic changes that occur in the cervical spinal cord as a result of injury and disease are not well characterized with current clinical imaging techniques. Synaptive Medical has recently developed a suite of innovative medical imaging products focused on the brain and image-guided neurosurgery. They are interested in investigating the potential application of these technologies beyond the brain.
Water and wastewater utilities typically represent the single largest municipal consumer of electricity. Previous studies have shown the potential to significantly reduce this use through infrastructure and operational improvements, particularly for water distribution. The proposed research seeks to validate and expand the application of energy metrics, developed by the applicant, that describe how energy is supplied, dissipated, lost, and delivered, throughout water distribution systems.
Significant advances in technologies related to antibody discovery and development have allowed therapeutic antibodies to become the fastest growing class of biopharmaceuticals over the last 20 years. Northern Biologics is a biotechnology company that seeks to develop therapeutic antibodies for the treatment of cancer and fibrosis. Together with Dr.
The objective is to develop a real-time fraud detection algorithm for a large E-commerce company based on construction of a robust reference model from normal multivariate data. To accomplish this, we propose to leverage machine learning techniques, such as reinforcement learning, in combination with stochastic modeling techniques such as Hidden Markov Models, to provide both a comparative study between the approaches and possibly produce an enhanced algorithm which applies both methods appropriately.