SaS-BCI: A New Strategy to Predict Image Memorability and use Mental Imagery as a Brain-Based Biometric Authentication

Security authentication is one of the most important levels of information security. Nowadays, human biometric techniques are the most secure methods for authentication purposes that cover the problems of older types of authentication like passwords and pins. There are many advantages of recent biometrics in terms of security; however, they still have some disadvantages. Progresses in technology made some specific devices, which make it possible to copy and make a fake human biometric because they are all visible and touchable. According to this matter, there is a need for a new biometric to cover the issues of other types. Brainwave is human data, which uses them as a new type of security authentication that has engaged many researchers. There are some research and experiments, which are investigating and testing EEG signals to find the uniqueness of human brainwave. Some researchers achieved high accuracy rates in this area by applying different signal acquisition techniques, feature extraction and classifications using Brain–Computer Interface (BCI). One of the important parts of any BCI processes is the way that brainwaves could be acquired and recorded. A new Signal Acquisition Strategy is presented in this paper for the process of authorization and authentication of brain signals specifically. This is to predict image memorability from the user’s brain to use mental imagery as a visualization pattern for security authentication. Therefore, users can authenticate themselves with visualizing a specific picture in their minds. In conclusion, we can see that brainwaves can be different according to the mental tasks, which it would make it harder using them for authentication process. There are many signal acquisition strategies and signal processing for brain-based authentication that by using the right methods, a higher level of accuracy rate could be achieved which is suitable for using brain signal as another biometric security authentication

Discriminatory protein binding by a library of 96 new affinity resins: A novel dye-affinity chromatography tool-kit

Initial acceptance of Cibacron Blue 3G-A (R) based matrices has made dye-ligand affinity chromatography an attractive proposition. This prompted the synthesis and search for new dye structures. A systematic library of 96 affinity resins was generated using novel analogs of Cibacron Blue 3G-A (R) and also by varying spacer lengths for immobilization. The library was tested in a batch binding and elution mode using seven different proteins - four Aspergillus enzymes namely, NADP-glutamate dehydrogenase, laccase, glutamine synthetase and arginase, bovine pancreatic trypsin and the two serum proteins human serum albumin and immunoglobulin G. Unique binding patterns were observed for each of them indicating that the library displayed discriminatory interactions. The significance of spacer length in the interaction with proteins was discernable. Trypsin interacted best with affinity resins that had no spacer. It was possible to resolve IgG and HSA from a mixture using a combination of resins. There was a good spread of HSA binding capacity in the 96 affinity resins. While some showed better HSA binding capacity than the commercial CB3GA-based matrix, a few with lower capacity were also observed. Subsequent to an initial screen, one affinity resin (CR-017) could be used to enrich Aspergillus terreus NADP-GDH from crude cell extracts. The efficacy of this dye-affinity resin was rationalized by characterizing NADP-GDH inhibition kinetics with the corresponding free dye ligand. In the sum, the library provides a set of dye-ligand affinity matrices with a potential for use in high throughput screening for protein purification. (C) 200