Advanced Imaging Techniques for Point-Measurement Analysis of Pharmaceutical Materials

Drugs are an essential element protecting human lives from many diseases such as cancer, diabetes, and cardiovascular disorders. One of the highlights in drug development in recent years is the establishment of rational drug design: a collection of various multi-disciplinary approaches that at the core, focus on designing molecules with specific properties for identified targets and biomolecules with known functional roles and structural information. The candidate molecules will then go through a series of examinations to characterize their physiochemical properties, and an iterative process is used to improve the design of the drug to achieve desirable attributes. The time consuming and highly expensive nature of drug development constantly calls for new analytical techniques that have increasingly higher throughput, faster analysis speed, richer chemical and structural information, and lower risk and cost. Conventional analytical methods for pharmaceutical materials, such as X-ray diffraction analysis and Raman spectroscopy, often suffer from prolonged measurement time. In many cases, the identification of regions of interest within the sample is non-trivial in itself. Nonlinear optical imaging techniques, including second harmonic generation (SHG) microscopy and two-photon excited ultraviolet fluorescence (TPE-UVF) microscopy were developed as fast, real-time, and non-destructive methods for selective identification and characterization of crystalline materials present in pharmaceutical samples. These techniques were integrated with synchrotron X-ray diffraction analysis and Raman spectroscopy to significantly reduce the overall measurement time of these structure characterization techniques. In the meanwhile, with the now increased speed of measurement, the amount of experimental data acquired per unit time has also drastically increased. The rate at which data are analyzed, digested, and interpreted is becoming the bottleneck in data-driving decision-making. Novel electronics that only collect data at the most information-rich time points were employed to significantly increase the signal-to-noise ratio (SNR) during data acquisition, reducing the total amount of data needed for material characterization. Advanced sampling algorithms to reduce the total amount of measurements required for perfect data space reconstruction, automated programs for data acquisition and analysis, and efficient data analysis algorithms based on machine learning were developed for accelerated data processing for nonlinear optical imaging analysis, Raman spectra processing, and X-ray diffraction indexing

Automatic Generation of Grounded Visual Questions

In this paper, we propose the first model to be able to generate visually grounded questions with diverse types for a single image. Visual question generation is an emerging topic which aims to ask questions in natural language based on visual input. To the best of our knowledge, it lacks automatic methods to generate meaningful questions with various types for the same visual input. To circumvent the problem, we propose a model that automatically generates visually grounded questions with varying types. Our model takes as input both images and the captions generated by a dense caption model, samples the most probable question types, and generates the questions in sequel. The experimental results on two real world datasets show that our model outperforms the strongest baseline in terms of both correctness and diversity with a wide margin.Comment: VQ

A Modified Direct Allocation Algorithm with Application to Redundant Actuators

AbstractControl allocation considers the problem of controlling instruction distribution for control systems with multiple and redundant actuators. This paper focuses on the direct allocation method, making the time requirement of the algorithm analogous compared with modified pseudoinverse redistribution methods, linear programming methods solved by simplex method, and sub-gradient optimization method. To reduce off-line computations of constructing the attainable moment set of actuators, a new approach based on the null space of the control effectiveness matrix is proposed, which is superior when the number of actuators is less than 10 compared with traditional method. To decrease on-line computations, an improvement method of searching the facet that is aligned with the desired moment is presented, shortening the search time by checking only the facets that lie around the desired moment. To find such facets, the vertices of the attainable moment set are normalized and saved during off-line computations. Simulation results show that at least 32.22% of off-line computation time would be saved using null space-based construction when the number of actuators is less than 10. In on-line computations, the modified method performs superiorly compared with the three aforementioned methods. Furthermore, it may solve the problem of control allocation efficiently when a remarkable large number of redundant actuators are configured