Impact-ionization and noise characteristics of thin III-V avalanche photodiodes

It is, by now, well known that McIntyre\u27s localized carrier-multiplication theory cannot explain the suppression of excess noise factor observed in avalanche photodiodes (APDs) that make use of thin multiplication regions. We demonstrate that a carrier multiplication model that incorporates the effects of dead space, as developed earlier by Hayat et al. provides excellent agreement with the impact-ionization and noise characteristics of thin InP, In/sub 0.52/Al/sub 0.48/As, GaAs, and Al/sub 0.2/Ga/sub 0.8/As APDs, with multiplication regions of different widths. We outline a general technique that facilitates the calculation of ionization coefficients for carriers that have traveled a distance exceeding the dead space (enabled carriers), directly from experimental excess-noise-factor data. These coefficients depend on the electric field in exponential fashion and are independent of multiplication width, as expected on physical grounds. The procedure for obtaining the ionization coefficients is used in conjunction with the dead-space-multiplication theory (DSMT) to predict excess noise factor versus mean-gain curves that are in excellent accord with experimental data for thin III-V APDs, for all multiplication-region widths

A Comparative Assessment of Floating and Submerged Sensor Network Deployments for Monitoring Underwater Sediment Transport Processes

Wireless Sensor Networks (WSNs) are a pioneering technology in many environmental monitoring applications owing to their ability to be deployed for long periods of time in locations that cannot be reached manually. One such use-case is the monitoring of underwater sediment transport, a process that plays a significant role in coastal erosion. Previous examples of WSNs deployed for this purpose have been in the form of underwater sensor networks (UWSNs), which have a number of shortcomings from both a practical and technical viewpoint. As such, this paper provides a comparative assessment of UWSNs and an alternative deployment approach of floating echosounding sensor networks for the purpose of monitoring underwater sediment transport

Generation Scotland: Donor DNA Databank

The Generation Scotland Donor DNA Databank (GS:3D) phenotype was collected from consented blood donors by questionnaire and relates to 4,998 healthy control DNA samples and plasma.Dataset pertaining to the publication “Generation Scotland: Donor DNA Databank; A control DNA resource”. BMC Med Genet 2010 Nov 23;11:166. doi: 10.1186/1471-2350-11-166. URL: http://www.biomedcentral.com/1471-2350/11/166 The data is phenotype information collected from consented donors by questionnaire as described in the research paper and is in an MS Excel table, GS3D phenotype.xls. If you use this dataset, please cite the manuscript in order to acknowledge the contribution of the Generation Scotland: Donor DNA Databank (GS:3D) resource. For information about using GS:3D DNA or plasma samples, or genetic data, please visit http://www.generationscotland.org/ or contact [email protected]. All applications to use Generation Scotland resources will be reviewed by the Generation Scotland Access Committee. GS:3D is an NHS Lothian NRS BioResource, governed as a Research Tissue Bank by the GS Access Committee, and has supported over 20 research projects to date. GS:3D was funded by a project grant from the Scottish Executive Health Department, Chief Scientist Office, grant number CZB/4/285. Shona Kerr, on behalf of all co-authors in the corresponding manuscript

Generation Scotland SFHS Data Dictionary

The GS:SFHS Data Dictionary is a set of information describing the contents, format, and structure of the phenotype data collected during recruitment (2006-2011) to the Generation Scotland Scottish Family Health Study (GS:SFHS), or derived subsequently from study data collected during recruitment. This dataset replaces the one at https://datashare.is.ed.ac.uk/handle/10283/272

Common Genetic Variants Explain the Majority of the Correlation Between Height and Intelligence : The Generation Scotland Study

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