Prediction and prevention of pandemics via graphical model inference and convex programming.

Hard-to-predict bursts of COVID-19 pandemic revealed significance of statistical modeling which would resolve spatio-temporal correlations over geographical areas, for example spread of the infection over a city with census tract granularity. In this manuscript, we provide algorithmic answers to the following two inter-related public health challenges of immense social impact which have not been adequately addressed (1) Inference Challenge assuming that there are N census blocks (nodes) in the city, and given an initial infection at any set of nodes, e.g.

On Channel-Discontinuity-Constraint Routing in Wireless Networks.

Multi-channel wireless networks are increasingly deployed as infrastructure networks, e.g. in metro areas.

Healthcare Supported by Data Mule Networks in Remote Communities of the Amazon Region.

This paper investigates the feasibility of using boats as data mule nodes, carrying medical ultrasound videos from remote and isolated communities in the Amazon region in Brazil, to the main city of that area. The videos will be used by physicians to perform remote analysis and follow-up routine of prenatal examinations of pregnant women. Two open source simulators (the ONE and NS-2) were used to evaluate the results obtained utilizing a CoDPON (continuous displacement plan oriented network).

Robust spatiotemporal matching of electronic slides to presentation videos.

We describe a robust and efficient method for automatically matching and time-aligning electronic slides to videos of corresponding presentations. Matching electronic slides to videos provides new methods for indexing, searching, and browsing videos in distance-learning applications. However, robust automatic matching is challenging due to varied frame composition, slide distortion, camera movement, low-quality video capture, and arbitrary slides sequence.

NeuronMetrics: software for semi-automated processing of cultured neuron images.

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity.

Phenotypes of Drosophila brain neurons in primary culture reveal a role for fascin in neurite shape and trajectory.

Subtle cellular phenotypes in the CNS may evade detection by routine histopathology. Here, we demonstrate the value of primary culture for revealing genetically determined neuronal phenotypes at high resolution. Gamma neurons of Drosophila melanogaster mushroom bodies (MBs) are remodeled during metamorphosis under the control of the steroid hormone 20-hydroxyecdysone (20E).

Geometric algorithms for the analysis of 2D-electrophoresis gels.

In proteomics, two-dimensional gel electrophoresis (2-DE) is a separation technique for proteins. The resulting protein spots can be identified either by using picking robots and subsequent mass spectrometry or by visual cross inspection of a new gel image with an already analyzed master gel. Difficulties especially arise from inherent noise and irregular geometric distortions in 2-DE images.