The phenomenal increase in technological capabilities that allow the design and training of systems to cope with the complexities of natural language and visual representation in order to develop other formats is remarkable. It has made it possible to make use of image to image and text to image technologies to support those with disabilities in ways not previously explored. It has opened the world of adaptations from one picture to another in a design style of a user's choosing. Automated text simplification alongside graphical symbol representations to enhance understanding of complex content is already being used to support those with cognitive impairments and learning difficulties. Symbol sets have become embedded within applications as dictionaries and look up systems, but the need for flexibility and personalization remains a challenge. Most pictographic symbols are created over time within the bounds of a certain style and schema for particular groups such as those who use augmentative and alternative forms of communication (AAC). By using generative artificial intelligence, it is proposed that symbols could be produced based on the style of those already used by an individual or adapted to suit different requirements within local contexts, cultures and communities. This paper explores these ideas at the start of a small six-month pilot study to adapt a number of open licensed symbols based on the symbol set's original style. Once a collection has been automatically developed from image to image and text descriptions, potential stakeholders will evaluate the outcomes using an online voting system. Successful symbols will be made available and could potentially be added to the original symbol set offering a flexible personalized approach to AAC symbol generation hitherto not experienced by users.
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http://dx.doi.org/10.3233/SHTI230622 | DOI Listing |
J Biol Chem
July 2010
State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, 15 Da Tun Road, Chao Yang District, Beijing 100101, China.
Enzymatic catalysis of biochemical reactions is essential to all living systems. The "lock and key" and "induced fit" models were early contributions to our understanding of the mechanisms involved in the reaction between an enzyme and its substrate. However, whether a given substrate-induced conformation is rigid or remains flexible has not yet been determined.
View Article and Find Full Text PDFJ Biol Chem
July 2010
Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, California 90095, USA.
The fungal iterative nonreducing polyketide synthases (NRPKSs) synthesize aromatic polyketides, many of which have important biological activities. The product template domains (PT) embedded in the multidomain NRPKSs mediate the regioselective cyclization of the highly reactive polyketide backbones and dictate the final structures of the products. Understanding the sequence-activity relationships of different PT domains is therefore an important step toward the prediction of polyketide structures from NRPKS sequences and can enable the genome mining of hundreds of cryptic NRPKSs uncovered via genome sequencing.
View Article and Find Full Text PDFJ Biol Chem
June 2010
Department of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.
gamma-Secretase is a multimeric membrane protein complex composed of presenilin (PS), nicastrin, Aph-1, and Pen-2, which mediates intramembrane proteolysis of a range of type I transmembrane proteins. We previously analyzed the functional roles of the N-terminal transmembrane domains (TMDs) 1-6 of PS1 in the assembly and proteolytic activity of the gamma-secretase using a series of TMD-swap PS1 mutants. Here we applied the TMD-swap method to all the TMDs of PS1 for the structure-function analysis of the proteolytic mechanism of gamma-secretase.
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