Summary
The need for an efficient and cost-effective method is compelling in biomolecular NMR. To tackle this problem, we have developed the Poky suite, the revolutionized platform with boundless possibilities for advancing research and technology development in signal detection, resonance assignment, structure calculation, and relaxation studies with the help of many automation and user interface tools. This software is extensible and scalable by scripting and batching as well as providing modern graphical user interfaces and a diverse range of modules right out of the box.
Availability
Poky is freely available to non-commercial users at https://poky.clas.ucdenver.edu.
Supplementary information
Supplementary data are available at Bioinformatics online.
In this paper, a comparison of reinforcement learning algorithms and their performance on a robot box pushing task is provided. The robot box pushing problem is structured as both a singleagent problem and also a multi-agent problem. A Q-learning algorithm is applied to the single-agent box pushing problem, and three different Q-learning algorithms are applied to the multi-agent box pushing problem. Both sets of algorithms are applied on a dynamic environment that is comprised of static objects, a static goal location, a dynamic box location, and dynamic agent positions. A simulation environment is developed to test the four algorithms, and their performance is compared through graphical explanations of test results. The comparison shows that the newly applied reinforcement algorithm out-performs the previously applied algorithms on the robot box pushing problem in a dynamic environment.
Electrotactile displays can open a new sensory substitution channel to be utilized in a vast array of applications. But there are still challenges in different aspects of such systems. One of the most crucial concerns, is the effects of receptor fatigue. Our tests show that during prolonged exposure of receptors to the electrical signals, their sensitivity to the signal level changes gradually and adjustments in the signal's power are required to keep the receptors is the stimulated state. This was confirmed by monitoring the electrical current passing through the skin and calculating the corresponding impedance. More interestingly, the rates of the impedance changes are different for each part of the skin, indicating inconsistent rates of receptor fatigue for each region of the skin. These electrical properties of the skin were addressed in this research for the purpose of rendering consistent sensations for the users regardless of the person or skin conditions. To solve these challenges, two methods are employed: a voltage control system based on pulsewidth modulation is used to adjust the signal power; and Kalman filtering is used to predict impedance changes in advance and supply the skin with the proper signal. The result is a self-contained automated system capable of managing the signal power for any user at any given time or skin condition.
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