Calmodulation meta-analysis: Predicting calmodulin binding via canonical motif clustering

The calcium-binding protein calmodulin (CaM) directly binds to membrane transport proteins to modulate their function in response to changes in intracellular calcium concentrations. Because CaM recognizes and binds to a wide variety of target sequences, identifying CaM-binding sites is difficult, requiring intensive sequence gazing and extensive biochemical analysis. Here, we describe a straightforward computational script that rapidly identifies canonical CaM-binding motifs within an amino acid sequence. Analysis of the target sequences from high resolution CaM-peptide structures using this script revealed that CaM often binds to sequences that have multiple overlapping canonical CaM-binding motifs. The addition of a positive charge discriminator to this meta-analysis resulted in a tool that identifies potential CaM-binding domains within a given sequence. To allow users to search for CaM-binding motifs within a protein of interest, perform the meta-analysis, and then compare the results to target peptide-CaM structures deposited in the Protein Data Bank, we created a website and online database. The availability of these tools and analyses will facilitate the design of CaM-related studies of ion channels and membrane transport proteins

How's My Network - Incentives and Impediments of Home Network Measurements

Gathering meaningful information from Home Networking (HN) environments has presented researchers with measurement strategy challenges. A measurement platform is typically designed around the process of gathering data from a range of devices or usage statistics in a network that are specifically behind the HN firewall. HN studies require a fine balance between incentives and impediments to promote usage and minimize efforts for user participation with the focus on gathering robust datasets and results. In this dissertation we explore how to gather data from the HN Ecosystem (e.g. devices, apps, permissions, configurations) and feedback from HN users across a multitude of HN infrastructures, leveraging low impediment and low/high incentive methods to entice user participation. We look to understand the trade-offs of using a variety of approach types (e.g. Java Applet, Mobile app, survey) for data collections, user preferences, and how HN users react and make changes to the HN environment when presented with privacy/security concerns, norms of comparisons (e.g. comparisons to the local environment and to other HNs) and other HN results. We view that the HN Ecosystem is more than just “the network” as it also includes devices and apps within the HN. We have broken this dissertation down into the following three pillars of work to understand incentives and impediments of user participation and data collections. These pillars include: 1) preliminary work, as part of the How's My Network (HMN) measurement platform, a deployed signed Java applet that provided a user-centered network measurement platform to minimize user impediments for data collection, 2) a HN user survey on preference, comfort, and usability of HNs to understand incentives, and 3) the creation and deployment of a multi-faceted How's My Network Mobile app tool to gather and compare attributes and feedback with high incentives for user participation; as part of this flow we also include related approaches and background work. The HMN Java applet work demonstrated the viability of using a Web browser to obtain network performance data from HNs via a user-centric network measurement platform that minimizes impediments for user participation. The HMN HN survey work found that users prefer to leverage a Mobile app for HN data collections, and can be incentivized to participate in a HN study by providing attributes and characteristics of the HN Ecosystem. The HMN Mobile app was found to provide high incentives, with minimal impediments, for participation with focus on user Privacy and Security concerns. The HMN Mobile app work found that 84\% of users reported a change in perception of privacy and security, 32\% of users uninstalled apps, and 24\% revoked permissions in their HN. As a by-product of this work we found it was possible to gather sensitive information such as previously attached networks, installed apps and devices on the network. This information exposure to any installed app with minimal or no granted permissions is a potential privacy concern

Comparison of axial performance of cone-beam reconstruction algorithms for off-center flat-panel imaging with a SPECT system

In this paper, using Defrise Phantoms, we present our investigations of the axial limitations of an analytical cone-beam reconstruction algorithm (FDK), and the iterative ordered-subset transmission reconstruction (OSTR) iterative algorithm, for an axially extended version of the Philips Brightview XCT cone beam CT (CBCT) geometry. Simulations were preformed for head size and body size Defrise Phantoms of different axial dimensions to investigate limitations on axial extent as a function of these. OSTR yielded overall better axial performance than FDK. It may be possible to reconstruct a larger axial extent for brain studies; however, patients with larger body sizes pose more of a problem. © 2010 IEEE

BISOU: a balloon project for spectral observations of the early universe

International audienceThe BISOU (Balloon Interferometer for Spectral Observations of the Universe) project studies the viability and prospects of a balloon-borne spectrometer, pathfinder of a future space mission dedicated to the measurements of the CMB spectral distortions, while consolidating the instrumental concept and improving the readiness of some of its key sub-systems. A balloon concept based on a Fourier Transform Spectrometer, covering a spectral range from about 90 GHz to 2 THz, adapted from previous mission proposals such as PIXIE and FOSSIL, is being studied and modelled. Taking into account the requirements and conditions of balloon flights (i.e. residual atmosphere, observation strategy for instance), we present here the instrument concept together with the results of the CNES phase 0 study, evaluating the sensitivity to some of its potential observables. For instance, we forecast a detection of the CMB Compton y-distortion monopole with a signal-to-noise ratio of at least