Characteristic Laplacian in sub-Riemannian geometry

We study a Laplacian operator related to the characteristic cohomology of a smooth manifold endowed with a distribution. We prove that this Laplacian does not behave very well: it is not hypoelliptic in general and does not respect the bigrading on forms in a complex setting. We also discuss the consequences of these negative results for a conjecture of P. Griffiths, concerning the characteristic cohomology of period domains

Forster resonance energy transfer, absorption and emission spectra in multichromophoric systems: III. Exact stochastic path integral evaluation

A numerically exact path integral treatment of the absorption and emission spectra of open quantum systems is presented that requires only the straightforward solution of a stochastic differential equation. The approach converges rapidly enabling the calculation of spectra of large excitonic systems across the complete range of system parameters and for arbitrary bath spectral densities. With the numerically exact absorption and emission operators one can also immediately compute energy transfer rates using the multi-chromophoric Forster resonant energy transfer formalism. Benchmark calculations on the emission spectra of two level systems are presented demonstrating the efficacy of the stochastic approach. This is followed by calculations of the energy transfer rates between two weakly coupled dimer systems as a function of temperature and system-bath coupling strength. It is shown that the recently developed hybrid cumulant expansion is the only perturbative method capable of generating uniformly reliable energy transfer rates and spectra across a broad range of system parameters.Comment: 20 pages, 4 figure

Genes2Networks: Connecting Lists of Proteins by Using Background Literature-based Mammalian Networks

In recent years, in-silico literature-based mammalian protein-protein interaction network datasets have been developed. These datasets contain binary interactions extracted manually from legacy experimental biomedical research literature. Placing lists of genes or proteins identified as significantly changing in multivariate experiments, in the context of background knowledge about binary interactions, can be used to place these genes or proteins in the context of pathways and protein complexes.
Genes2Networks is a software system that integrates the content of ten mammalian literature-based interaction network datasets. Filtering to prune low-confidence interactions was implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “seed” lists of human Entrez gene names. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is available at http://actin.pharm.mssm.edu/genes2networks.
Genes2Network is a powerful web-based software application tool that can help experimental biologists to interpret high-throughput experimental results used in genomics and proteomics studies where the output of these experiments is a list of significantly changing genes or proteins. The system can be used to find relationships between nodes from the seed list, and predict novel nodes that play a key role in a common function

Communication Efficacy Using Technology within Virtual Teams

Technology has given businesses the flexibility to allow employees to collaborate beyond the limitations of geography. Today’s businesses are taking advantage of collaborative teams that are separated by distance, but work together as if they are in the same room

Sensor Planning for Object Pose Estimation and Identification

This paper proposes a novel approach to sensor planning for simultaneous object identification and 3D pose estimation. We consider the problem of determining the next-best-view for a movable sensor (or an autonomous agent) to identify an unknown object from among a database of known object models. We use an information theoretic approach to define a metric (based on the difference between the current and expected model entropy) that guides the selection of the optimal control action. We present a generalized algorithm that can be used in sensor planning for object identification and pose estimation. Experimental results are also presented to validate the proposed algorithm

MOON: MapReduce On Opportunistic eNvironments

Abstract—MapReduce offers a flexible programming model for processing and generating large data sets on dedicated resources, where only a small fraction of such resources are every unavailable at any given time. In contrast, when MapReduce is run on volunteer computing systems, which opportunistically harness idle desktop computers via frameworks like Condor, it results in poor performance due to the volatility of the resources, in particular, the high rate of node unavailability. Specifically, the data and task replication scheme adopted by existing MapReduce implementations is woefully inadequate for resources with high unavailability. To address this, we propose MOON, short for MapReduce On Opportunistic eNvironments. MOON extends Hadoop, an open-source implementation of MapReduce, with adaptive task and data scheduling algorithms in order to offer reliable MapReduce services on a hybrid resource architecture, where volunteer computing systems are supplemented by a small set of dedicated nodes. The adaptive task and data scheduling algorithms in MOON distinguish between (1) different types of MapReduce data and (2) different types of node outages in order to strategically place tasks and data on both volatile and dedicated nodes. Our tests demonstrate that MOON can deliver a 3-fold performance improvement to Hadoop in volatile, volunteer computing environments

Dynamic sensor planning with stereo for model identification on a mobile platform

This paper presents an approach to sensor planning for simultaneous pose estimation and model identification of a moving object using a stereo camera sensor mounted on a mobile base. For a given database of object models, we consider the problem of identifying an object known to belong to the database and where to move next should the object not be easily identifiable from the initial viewpoint. No constraints on the motion of the object nor the robot itself are assumed, which is an improvement on previous methods. Sensor planning is based on the selection of the control action that optimizes a cost metric based on information gain. Experimental results from the implementation of the method on a two-wheeled nonholonomic robot are presented to illustrate and validate the method

The Effect of Submarine Melting on Calving From Marine Terminating Glaciers

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148395/1/jgrf20986.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148395/2/jgrf20986_am.pd

Characterisation of Cryogenic Material Properties of 3D-Printed Superconducting Niobium using a 3D Lumped Element Microwave Cavity

We present an experimental characterisation of the electrical properties of 3D-printed Niobium. The study was performed by inserting a 3D-printed Nb post inside an Aluminium cylindrical cavity, forming a 3D lumped element re-entrant microwave cavity resonator. The resonator was cooled to temperatures below the critical temperature of Niobium (9.25K) and then Aluminium (1.2K), while measuring the quality factors of the electromagnetic resonances. This was then compared with finite element analysis of the cavity and a measurement of the same cavity with an Aluminium post of similar dimensions and frequency, to extract the surface resistance of the Niobium post. The 3D-printed Niobium exhibited a transition to the superconducting state at a similar temperature to the regular Niobium, as well as a surface resistance of $3.1\times10^{-4}$ $\Omega$. This value was comparable to many samples of traditionally machined Niobium previously studied without specialised surface treatment. Furthermore, this study demonstrates a simple new method for characterizing the material properties of a relatively small and geometrically simple sample of superconductor, which could be easily applied to other materials, particularly 3D-printed materials. Further research and development in additive manufacturing may see the application of 3D-printed Niobium in not only superconducting cavity designs, but in the innovative technology of the future.Comment: 5 pages, 4 figure