2D-barcode for mobile devices

2D-barcodes were designed to carry significantly more data than its 1D counterpart. These codes are often used in industrial information tagging applications where high data capacity, mobility, and data robustness are required. Wireless mobile devices such as camera phones and Portable Digital Assistants (PDAs) have evolved from just a mobile voice communication device to what is now a mobile multimedia computing platform. Recent integration of these two mobile technologies has sparked some interesting applications where 2D-barcodes work as visual tags and/or information source and camera phones performs image processing tasks on the device itself. One of such applications is hyperlink establishment. The 2D symbol captured by a camera phone is decoded by the software installed in the phone. Then the web site indicated by the data encoded in a symbol is automatically accessed and shown in the display of the camera phone. Nonetheless, this new mobile applications area is still at its infancy. Each proposed mobile 2D-barcode application has its own choice of code, but no standard exists nor is there any study done on what are the criteria for setting a standard 2D-barcode for mobile phones. This study intends to address this void. The first phase of the study is qualitative examination. In order to select a best standard 2D-barcode, firstly, features desirable for a standard 2D-barcode that is optimized for the mobile phone platform are identified. The second step is to establish the criteria based on the features identified. These features are based on the operating limitations and attributes of camera phones in general use today. All published and accessible 2D-barcodes are thoroughly examined in terms of criteria set for the selection of a best 2D-barcode for camera phone applications. In the second phase, the 2D-barcodes that have higher potential to be chosen as a standard code are experimentally examined against the three criteria: light condition, distance, whether or not a 2D-barcode supports VGA resolution. Each sample 2D-barcode is captured by a camera phone with VGA resolution and the outcome is tested using an image analysis tool written in the scientific language called MATLAB. The outcome of this study is the selection of the most suitable 2D-barcode for applications where mobile devices such as camera phones are utilized

LABRAD : Vol 41, Issue 1 - March 2015

An Overview of Proficiency Testing Sources of Pre-analytical Variations Five Q-Framework for Implementing Total Quality Management in Laboratory Delta Check in Clinical Laboratory Indicators of Quality Improvement in Surgical Pathology Types of Analytical Errors Method Validation for Quantitative Tests: CAP Recommendations Levey Jenning Chart and a Guide to Use Westgard Rules Quality Control of Vitek-2 System Establishing Quality Control Values for Haematology Parametershttps://ecommons.aku.edu/labrad/1002/thumbnail.jp

MetaBar - a tool for consistent contextual data acquisition and standards compliant submission

Background: Environmental sequence datasets are increasing at an exponential rate; however, the vast majority of them lack appropriate descriptors like sampling location, time and depth/altitude: generally referred to as metadata or contextual data. The consistent capture and structured submission of these data is crucial for integrated data analysis and ecosystems modeling. The application MetaBar has been developed, to support consistent contextual data acquisition. Results: MetaBar is a spreadsheet and web-based software tool designed to assist users in the consistent acquisition, electronic storage, and submission of contextual data associated to their samples. A preconfigured Microsoft Excel spreadsheet is used to initiate structured contextual data storage in the field or laboratory. Each sample is given a unique identifier and at any stage the sheets can be uploaded to the MetaBar database server. To label samples, identifiers can be printed as barcodes. An intuitive web interface provides quick access to the contextual data in the MetaBar database as well as user and project management capabilities. Export functions facilitate contextual and sequence data submission to the International Nucleotide Sequence Database Collaboration (INSDC), comprising of the DNA DataBase of Japan (DDBJ), the European Molecular Biology Laboratory database (EMBL) and GenBank. MetaBar requests and stores contextual data in compliance to the Genomic Standards Consortium specifications. The MetaBar open source code base for local installation is available under the GNU General Public License version 3 (GNU GPL3). Conclusion: The MetaBar software supports the typical workflow from data acquisition and field-sampling to contextual data enriched sequence submission to an INSDC database. The integration with the megx.net marine Ecological Genomics database and portal facilitates georeferenced data integration and metadata-based comparisons of sampling sites as well as interactive data visualization. The ample export functionalities and the INSDC submission support enable exchange of data across disciplines and safeguarding contextual data

Ezh2-dCas9 and KRAB-dCas9 enable engineering of epigenetic memory in a context-dependent manner.

BackgroundRewriting of the epigenome has risen as a promising alternative to gene editing for precision medicine. In nature, epigenetic silencing can result in complete attenuation of target gene expression over multiple mitotic divisions. However, persistent repression has been difficult to achieve in a predictable manner using targeted systems.ResultsHere, we report that persistent epigenetic memory required both a DNA methyltransferase (DNMT3A-dCas9) and a histone methyltransferase (Ezh2-dCas9 or KRAB-dCas9). We demonstrate that the histone methyltransferase requirement can be locus specific. Co-targeting Ezh2-dCas9, but not KRAB-dCas9, with DNMT3A-dCas9 and DNMT3L induced long-term HER2 repression over at least 50 days (approximately 57 cell divisions) and triggered an epigenetic switch to a heterochromatic environment. An increase in H3K27 trimethylation and DNA methylation was stably maintained and accompanied by a sustained loss of H3K27 acetylation. Interestingly, substitution of Ezh2-dCas9 with KRAB-dCas9 enabled long-term repression at some target genes (e.g., SNURF) but not at HER2, at which H3K9me3 and DNA methylation were transiently acquired and subsequently lost. Off-target DNA hypermethylation occurred at many individual CpG sites but rarely at multiple CpGs in a single promoter, consistent with no detectable effect on transcription at the off-target loci tested. Conversely, robust hypermethylation was observed at HER2. We further demonstrated that Ezh2-dCas9 required full-length DNMT3L for maximal activity and that co-targeting DNMT3L was sufficient for persistent repression by Ezh2-dCas9 or KRAB-dCas9.ConclusionsThese data demonstrate that targeting different combinations of histone and DNA methyltransferases is required to achieve maximal repression at different loci. Fine-tuning of targeting tools is a necessity to engineer epigenetic memory at any given locus in any given cell type

The Economic Stimulus Payments of 2008 and the aggregate demand for consumption

Households in the Nielsen Consumer Panel were surveyed about their 2008 Economic Stimulus Payment. In estimates identified by the randomized timing of disbursement, the average household׳s spending rose by 10 percent the week it received a Payment and remained high cumulating to 1.5–3.8 percent of spending over three months. These estimates imply partial-equilibrium increases in aggregate demand of 1.3 percent of consumption in the second quarter of 2008 and 0.6 percent in the third. Spending is concentrated among households with low wealth or low past income; a household׳s spending did not increase significantly when it learned about its Payment.Sloan School of ManagementNorthwestern University (Evanston, Ill.). Kellogg School of ManagementUniversity of Chicago. Initiative for Global MarketsNorthwestern University (Evanston, Ill.). Kellogg School of Management. Zell Center for Risk ResearchHarvard University. Laboratory for Applied Economics and Polic