Award Data

Methods for interconversion between cell types (cellular reprogramming) are currently discovered through resource intensive trial and error. Experiments may test a multitude of transcription factors to identify correct combinations that influence cell fate. In addition, reprogramming approaches commonly use stem cell intermediates such as induced pluripotent stem cells (iPSCs), which are generated ...

The objective of this proposal is to examine the feasibility of defining and measuring key dimensions of an urban system to include its essential functions and networks, and whether they can be modelled in a computational framework for assessing robustness and resilience of DUTs (and their tipping points) under conditions of volatility and stress. This proposal will conduct a comprehensive review ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

CONCUR develops a computational framework for assessing and characterizing urban environments stability or fragility in response to volatility and stress, identifying specific weaknesses as well as key tipping points which could lead to rapid systemic failure. CONCUR explicitly models urban environments as emergent complex systems, focusing attention on the critical triggers that could lead to rap ...

The unique scale, population density, complexity, and connectedness of megacities requires new tools for detecting and assessing risks related to civil unrest, rule of law, terrorism, and other sources of instability, and for understanding the underlying dynamics. In addition, gray zone operations pose a new and strategically important class of threats to the stability of nation states and cities ...

Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematical models of u ...

Developing knowledge-driven nanoelectronics for military applications requires understanding the fundamental physics that governs the behavior of the underlying materials. Strongly correlated materials have very desirable properties such as interfacial superconductivity, ferroelectricity, ferromagnetism, and huge magnetoresistance, which make them an ideal set of candidates to integrate with semic ...