Discover the Blue Letter Bible with Concordance and Its Amazing Features for Free

The Blue Letter Bible is so called because of the blue color of the hyperlinks. The name "Blue Letter Bible" also contrasts with the term "red letter Bible", which is a common form of printed Bible with key words, such as the words of Jesus, highlighted in red.

The STEP Bible stands for Scripture Tools for Every Person, and is a free online resource containing Bibles and commentaries. It offers 50 different English-language translations of the Bible, including the ESV, NIV, and KJV (but not the NRSV or the RSV). The STEP Bible allows users to search by verse, word, and phrase, and one can examine parallel versions. The interface is available in over 90 languages, and has translations in 280 languages. The STEP Bilbe offers a concordance tool, and will help those doing exegetical work. It contains the Vulgate and works with Strong's numbers. The STEP Bible provides YouTube training videos and has a help section containing screenshots.

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The NASA-ADS Abstract Service provides a sophisticated search capability for the literature in Astronomy, Planetary Sciences, Physics/Geophysics, and Space Instrumentation. The ADS is funded by NASA and access to the ADS services is free to anybody worldwide without restrictions. It allows the user to search the literature by author, title, and abstract text. The ADS database contains over 3.6 million references, with 965,000 in the Astronomy/Planetary Sciences database, and 1.6 million in the Physics/Geophysics database. 2/3 of the records have full abstracts, the rest are table of contents entries (titles and author lists only). The coverage for the Astronomy literature is better than 95% from 1975. Before that we cover all major journals and many smaller ones. Most of the journal literature is covered back to volume 1. We now get abstracts on a regular basis from most journals. Over the last year we have entered basically all conference proceedings tables of contents that are available at the Harvard Smithsonian Center for Astrophysics library. This has greatly increased the coverage of conference proceedings in the ADS. The ADS also covers the ArXiv Preprints. We download these preprints every night and index all the preprints. They can be searched either together with the other abstracts or separately. There are currently about 260,000 preprints in that database. In January 2004 we have introduced two new services, full text searching and a personal notification service called "myADS". As all other ADS services, these are free to use for anybody.

Large scale feature searches of accumulated collections of medical imagery are required for multiple purposes, including clinical studies, administrative planning, epidemiology, teaching, quality improvement, and research. To perform a feature search of large collections of medical imagery, one can either search text descriptors of the imagery in the collection (usually the interpretation), or (if the imagery is in digital format) the imagery itself. At our institution, text interpretations of medical imagery are all available in our VA Hospital Information System. These are downloaded daily into an off-line computer. The text descriptors of most medical imagery are usually formatted as free text, and so require a user friendly database search tool to make searches quick and easy for any user to design and execute. We are tailoring such a database search tool (Liveview), developed by one of the authors (Karshat). To further facilitate search construction, we are constructing (from our accumulated interpretation data) a dictionary of medical and radiological terms and synonyms. If the imagery database is digital, the imagery which the search discovers is easily retrieved from the computer archive. We describe our database search user interface, with examples, and compare the efficacy of computer assisted imagery searches from a clinical text database with manual searches. Our initial work on direct feature searches of digital medical imagery is outlined.

The USGS Landsat archive holds an unequaled 36-year record of the Earth's surface that is invaluable to climate change studies, forest and resource management activities, and emergency response operations. An aggressive effort is taking place to provide all Landsat imagery [scenes currently held in the USGS Earth Resources Observation and Science (EROS) Center archive, as well as newly acquired scenes daily] free of charge to users with electronic access via the Web by the end of December 2008. The entire Landsat 7 Enhanced Thematic Mapper Plus (ETM+) archive acquired since 1999 and any newly acquired Landsat 7 ETM+ images that have less than 40 percent cloud cover are currently available for download. When this endeavor is complete all Landsat 1-5 data will also be available for download. This includes Landsat 1-5 Multispectral Scanner (MSS) scenes, as well as Landsat 4 and 5 Thematic Mapper (TM) scenes.

The Alaska Arctic Vegetation Archive (AVA-AK, GIVD-ID: NA-US-014) is a free, publically available database archive of vegetation-plot data from the Arctic tundra region of northern Alaska. The archive currently contains 24 datasets with 3,026 non-overlapping plots. Of these, 74% have geolocation data with 25-m or better precision. Species cover data and header data are stored in a Turboveg database. A standardized Pan Arctic Species List provides a consistent nomenclature for vascular plants, bryophytes, and lichens in the archive. A web-based online Alaska Arctic Geoecological Atlas (AGA-AK) allows viewing and downloading the species data in a variety of formats, and providesmore access to a wide variety of ancillary data. We conducted a preliminary cluster analysis of the first 16 datasets (1,613 plots) to examine how the spectrum of derived clusters is related to the suite of datasets, habitat types, and environmental gradients. Here, we present the contents of the archive, assess its strengths and weaknesses, and provide three supplementary files that include the data dictionary, a list of habitat types, an overview of the datasets, and details of the cluster analysis. less

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