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September 4, 2007 marked the release of a deluxe package of the song Rise exclusively to the Internet music and video download service iTunes. The deluxe edition featured the album version of the track, an acoustic version, and a live in-studio video.
6. TERM AND TERMINATION. The license granted in this Agreement is effective in perpetuity, as long as you own the Software License and adhere to the terms and conditions of this Agreement. In cases of fixed-term or leased licenses, the term of this Agreement coincides with the term of the license, which is specified on the order confirmation. The term of this Agreement and the license grant herein shall commence on the date you agree to this Agreement and install the Software. In the event you install a Software upgrade, this license agreement terminates. This license shall also terminate automatically on your failure to comply with any of the other terms of this Agreement. On termination of this Agreement, you agree to promptly discontinue use of the Software, deactivate the license key per instructions provided by Vendor, destroy all printed copies and delete all electronic copies of any documentation that you have downloaded, printed, or created relating to the Software, and to ensure that no copies of any of the Software screens, data, or other content remain archived or otherwise stored on your computers. Notwithstanding termination, the provisions of Sections 3, 6, 7, 8, 9, and 10 of this Agreement shall survive and continue to apply.
10. LIMITED WARRANTY AND DISCLAIMER. Vendor warrants that, as of the date on which the Software is purchased and for sixty (60) days thereafter (\"Warranty Period\"), the Software will provide the general features and functions described in the Documentation in effect on the date of purchase. Vendor's entire liability and your exclusive remedy during the Warranty Period (\"Limited Warranty\") will be, with the exception of any statutory warranty or remedy that cannot be excluded or limited under law, at Vendor's option, (i) to attempt to correct or work around errors, if any, or (ii) to refund the license fees, if any, paid by you and terminate this Agreement or the license specific to such Software. Such refund is subject to the discontinuance of the use of the Software, deactivation of the license key per instructions provided by Vendor, destroying all printed copies and deleting all electronic copies of any documentation that you have downloaded, printed, or created relating to the Software, and ensuring that no copies of any of the Software screens, data, or other content remain archived or otherwise stored on your computers, during the Warranty Period, and providing declaration of same to Vendor. THE LIMITED WARRANTY SET FORTH IN THIS SECTION GIVES YOU SPECIFIC LEGAL RIGHTS. YOU MAY HAVE ADDITIONAL LEGAL RIGHTS UNDER LAW WHICH VARY FROM JURISDICTION TO JURISDICTION. VENDOR DOES NOT SEEK TO LIMIT YOUR WARRANTY RIGHTS TO ANY EXTENT NOT PERMITTED BY LAW.
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CSI NY 1.2.2 was available to download from the developer's website when we last checked. We cannot confirm if there is a free download of this software available. This program is an intellectual property of Ubisoft Entertainment.
This PC program was developed to work on Windows XP, Windows Vista, Windows 7, Windows 8, Windows 10 or Windows 11 and is compatible with 32-bit systems. We cannot guarantee that the program is safe to download as it will be downloaded from the developer's website. Before launching the program, check it with any free antivirus software.
This study aims to classify abstract content based on the use of the highest number of words in an abstract content of the English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10% -90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.
The function of a non-protein-coding RNA is often determined by its structure. Since experimental determination of RNA structure is time-consuming and expensive, its computational prediction is of great interest, and efficient solutions based on thermodynamic parameters are known. Frequently, however, the predicted minimum free energy structures are not the native ones, leading to the necessity of generating suboptimal solutions. While this can be accomplished by a number of programs, the user is often confronted with large outputs of similar structures, although he or she is interested in structures with more fundamental differences, or, in other words, with different abstract shapes. Here, we formalize the concept of abstract shapes and introduce their efficient computation. Each shape of an RNA molecule comprises a class of similar structures and has a representative structure of minimal free energy within the class. Shape analysis is implemented in the program RNAshapes. We applied RNAshapes to the prediction of optimal and suboptimal abstract shapes of several RNAs. For a given energy range, the number of shapes is considerably smaller than the number of structures, and in all cases, the native structures were among the top shape representatives. This demonstrates that the researcher can quickly focus on the structures of interest, without processing up to thousands of near-optimal solutions. We complement this study with a large-scale analysis of the growth behaviour of structure and shape spaces. RNAshapes is available for download and as an online version on the Bielefeld Bioinformatics Server. 2ff7e9595c
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