33 research outputs found
Demo Abstract: NILMTK v0.2: A Non-intrusive Load Monitoring Toolkit for Large Scale Data Sets
In this demonstration, we present an open source toolkit for evaluating
non-intrusive load monitoring research; a field which aims to disaggregate a
household's total electricity consumption into individual appliances. The
toolkit contains: a number of importers for existing public data sets, a set of
preprocessing and statistics functions, a benchmark disaggregation algorithm
and a set of metrics to evaluate the performance of such algorithms.
Specifically, this release of the toolkit has been designed to enable the use
of large data sets by only loading individual chunks of the whole data set into
memory at once for processing, before combining the results of each chunk.Comment: 1st ACM International Conference on Embedded Systems For
Energy-Efficient Buildings, 201
NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring
Non-intrusive load monitoring, or energy disaggregation, aims to separate
household energy consumption data collected from a single point of measurement
into appliance-level consumption data. In recent years, the field has rapidly
expanded due to increased interest as national deployments of smart meters have
begun in many countries. However, empirically comparing disaggregation
algorithms is currently virtually impossible. This is due to the different data
sets used, the lack of reference implementations of these algorithms and the
variety of accuracy metrics employed. To address this challenge, we present the
Non-intrusive Load Monitoring Toolkit (NILMTK); an open source toolkit designed
specifically to enable the comparison of energy disaggregation algorithms in a
reproducible manner. This work is the first research to compare multiple
disaggregation approaches across multiple publicly available data sets. Our
toolkit includes parsers for a range of existing data sets, a collection of
preprocessing algorithms, a set of statistics for describing data sets, two
reference benchmark disaggregation algorithms and a suite of accuracy metrics.
We demonstrate the range of reproducible analyses which are made possible by
our toolkit, including the analysis of six publicly available data sets and the
evaluation of both benchmark disaggregation algorithms across such data sets.Comment: To appear in the fifth International Conference on Future Energy
Systems (ACM e-Energy), Cambridge, UK. 201
Demo abstract: NILMTK v0.2: A Non-intrusive Load Monitoring Toolkit for Large Scale Data Sets
Abstract In this demonstration, we present an open source toolkit for evaluating non-intrusive load monitoring research; a field which aims to disaggregate a household's total electricity consumption into individual appliances. The toolkit contains: a number of importers for existing public data sets, a set of preprocessing and statistics functions, a benchmark disaggregation algorithm and a set of metrics to evaluate the performance of such algorithms. Specifically, this release of the toolkit has been designed to enable the use of large data sets by only loading individual chunks of the whole data set into memory at once for processing, before combining the results of each chunk
Characterization of Sulfolobus islandicus rod-shaped virus 2 gp19, a single-strand specific endonuclease
The hyperthermophilic Sulfolobus islandicus rod-shaped virus 2 (SIRV2) encodes a 25-kDa protein (SIRV2gp19) annotated as a hypothetical protein with sequence homology to the RecB nuclease superfamily. Even though SIRV2gp19 homologs are conserved throughout the rudivirus family and presumably play a role in the viral life cycle, SIRV2gp19 has not been functionally characterized. To define the minimal requirements for activity, SIRV2gp19 was purified and tested under varying conditions. SIRV2gp19 is a single-strand specific endonuclease that requires Mg2+ for activity and is inactive on double-stranded DNA. A conserved aspartic acid in RecB nuclease superfamily Motif II (D89) is also essential for SIRV2gp19 activity and mutation to alanine (D89A) abolishes activity. Therefore, the SIRV2gp19 cleavage mechanism is similar to previously described RecB nucleases. Finally, SIRV2gp19 single-stranded DNA endonuclease activity could play a role in host chromosome degradation during SIRV2 lytic infection
SMN deficiency disrupts brain development in a mouse model of severe spinal muscular atrophy
Reduced expression of the survival motor neuron (SMN) gene causes the childhood motor neuron disease spinal muscular atrophy (SMA). Low levels of ubiquitously expressed SMN protein result in the degeneration of lower motor neurons, but it remains unclear whether other regions of the nervous system are also affected. Here we show that reduced levels of SMN lead to impaired perinatal brain development in a mouse model of severe SMA. Regionally selective changes in brain morphology were apparent in areas normally associated with higher SMN levels in the healthy postnatal brain, including the hippocampus, and were associated with decreased cell density, reduced cell proliferation and impaired hippocampal neurogenesis. A comparative proteomics analysis of the hippocampus from SMA and wild-type littermate mice revealed widespread modifications in expression levels of proteins regulating cellular proliferation, migration and development when SMN levels were reduced. This study reveals novel roles for SMN protein in brain development and maintenance and provides the first insights into cellular and molecular pathways disrupted in the brain in a severe form of SMA