AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning

We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable precursors. The tree search is guided by an artificial neural network policy that suggests possible precursors by utilizing a library of known reaction templates. The software is fast and can typically find a solution in less than 10 s and perform a complete search in less than 1 min. Moreover, the development of the code was guided by a range of software engineering principles such as automatic testing, system design and continuous integration leading to robust software with high maintainability. Finally, the software is well documented to make it suitable for beginners. The software is available at http://www.github.com/MolecularAI/aizynthfinder.

AiZynthFinder: A Fast Robust and Flexible Open-Source Software for Retrosynthetic Planning

We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable precursors. The tree search is guided by an artificial neural network policy that suggests possible precursors by utilizing a library of known reaction templates. The software is fast and can typically find a solution in less than 10 seconds and perform a complete search in less than 1 minute. Moreover, the writing of the code was guided by a range of software engineering principles such as automatic testing, system design and continuous integration leading to robust software. The object-oriented design makes the software very flexible and can straightforwardly be extended to support a range of new features. Finally, the software is clearly documented and should be easy to get started with. The software is available at http://www.github.com/MolecularAI/aizynthfinder.

AiZynthFinder: A Fast Robust and Flexible Open-Source Software for Retrosynthetic Planning

We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable precursors. The tree search is guided by an artificial neural network policy that suggests possible precursors by utilizing a library of known reaction templates. The software is fast and can typically find a solution in less than 10 seconds and perform a complete search in less than 1 minute. Moreover, the writing of the code was guided by a range of software engineering principles such as automatic testing, system design and continuous integration leading to robust software. The object-oriented design makes the software very flexible and can straightforwardly be extended to support a range of new features. Finally, the software is clearly documented and should be easy to get started with. The software is available at http://www.github.com/MolecularAI/aizynthfinder.

Novel Detection of Norovirus and Double Clostridium difficile in a Closed Cartridge System

Clostridium difficile infection (CDI) has become the main cause of diarrhea-related diseases in domestic (China) inpatients. High-sensitivity and high-specificity detection methods for CDI must be applied clinically for CDI supervisory control. In this paper, we introduce a detection method for C. difficile and Norovirus based on real-time PCR. We developed and optimized a primer–probe for Norovirus targets tcdA and tcdB with remarkably increased detection sensitivity. We then used this method in an integrated cassette, and found increased detection efficiency for Norovirus standards in the cassette compared to C. difficile samples. These results provide a basis for further exploration of automatic testing system design.

Automatic testing system to evaluate the energy efficiency of electric storage water heaters

Background: The energy efficiency of electric storage water heaters is a concern for enterprises and customers because it is beneficial for energy saving. To decrease the workload of testing personnel and improve the testing efficiency, an automatic testing system for evaluating the energy efficiency performance of electric storage water heaters has been designed. Methods: The complete testing system includes a water supply subsystem, hot water outlet subsystem, hardware subsystem, and software subsystem. An application program was developed using Visual Basic to acquire the sensor data and transmit it in real time to a database server. The energy efficiency evaluating process was controlled by the application software,by combining the data acquisition technology, communication technology, and program logical control technology. Results: The designed system can run automatically and achieve reliable tests, two important parameters including the standing loss per 24 h and the hot water withdrawal rate were obtained. Conclusion: This system can be applied to evaluate the energy efficiency grades of electric storage water heaters.