The research on pharmacology usually focuses on the structure-activity relationships of drugs, such as antibiotics, to enhance their activity, but often ignores their optical properties. However, investigating the photophysical properties of drugs is of great significance because they could be used to in situ visualize their positions and help us to understand their working metabolism. In this work, we identified a class of commercialized antibiotics, such as levofloxacin, norfloxacin, and moxifloxacin (MXF) hydrochloride, featuring the unique aggregation-induced emission (AIE) characteristics. By taking advantage of their AIE feature, antibiotic metabolism in cells could be in situ visualized, which clearly shows that the luminescent aggregates accumulate in the lysosomes. Moreover, after a structure-activity relationship study, we found an ideal site of MXF to be modified with a triphenylphosphonium and an antibiotic derivative MXF-P was prepared, which is able to specifically differentiate bacterial species after only 10 min of treatment. Moreover, MXF-P shows highly effective broad-spectrum antibacterial activity, excellent therapeutic effects and biosafety for S. aureus-infected wound recovery. Thus, this work not only discovers the multifunctionalities of the antibiotics but also provides a feasible strategy to make the commercialized drugs more powerful.

In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up to 2048 cores on KTH\'s Beskow Cray XC40 supercomputer and assess in situ visualization\'s impact on the Nek5000 performance. In our study case, a high-fidelity simulation of turbulent flow, we observe that in situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only ≈ 21 % on 2048 cores (the relative efficiency of Nek5000 without in situ operations is ≈ 99 % ). Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses the Radix-kr algorithm) where a majority of the time is spent on MPI communication. We also identified an imbalance of in situ processing time between rank 0 and all other ranks. In our case, better scaling and load-balancing in the parallel image composition would considerably improve the performance of Nek5000 with in situ capabilities. In general, the result of this study highlights the technical challenges posed by the integration of high-performance simulation codes and data-analysis libraries and their practical use in complex cases, even when efficient algorithms already exist for a certain application scenario.

Electrodeposition is a fundamental technology in modern society and has been widely used in metal plating and extraction, etc. However, extreme reaction conditions, including wide operation temperature ranges and corrosive media (molten salt/oxide systems as a particular example), inhibit direct in situ observation of the electrodeposition process. To visualize the electrode kinetics in such \"black box,\" X-ray tomography is employed to monitor the electrochemical processes and three-dimensional (3D) evolution of morphology. Benefiting from the excellent penetration of X-ray, a non-destructive and non-contact in situ four-dimensional (4D) visualization of Ti deposition is realized. Real-time 3D reconstructed images reveal that the counterintuitive nucleation and growth process of a mesoscale Ti dendrite at both solid and liquid cathodes. According to 3D morphology evolution, unusual mechanism based on synergetic effect of the diffusion of metallic Ti and local field enhancement is achieved utilizing a simulation method based on a finite element method. This approach allows for timely and accurately regulating the electrodeposition process upon in situ monitored parameters. More importantly, the 4D technique upon operando X-ray tomography and numerical simulation can be easily applied to other electrodeposition systems, which will help deeply understand the internal kinetics and the precise optimization of the electrodeposition conditions.

We propose a new visualization method for massive supercomputer simulations. The key idea is to scatter multiple omnidirectional cameras to record the simulation via in situ visualization. After the simulations are complete, researchers can interactively explore the data collection of the recorded videos by navigating along a path in four-dimensional spacetime. We demonstrate the feasibility of this method by applying it to three different fluid and magnetohydrodynamics simulations using up to 1,000 omnidirectional cameras.

We have studied the influence of different SiC powder size distributions and the sublimation behavior during physical vapor transport growth of SiC in a 75 mm and 100 mm crystal processing configuration. The evolution of the source material as well as of the crystal growth interface was carried out using in situ 3D X-ray computed tomography (75 mm crystals) and in situ 2D X-ray visualization (100 mm crystals). Beside the SiC powder size distribution, the source materials differed in the maximum packaging density and thermal properties. In this latter case of the highest packaging density, the in situ X-ray studies revealed an improved growth interface stability that enabled a much longer crystal growth process. During process time, the sublimation-recrystallization behavior showed a much smoother morphology change and slower materials consumption, as well as a much more stable shape of the growth interface than in the cases of the less dense SiC source. By adapting the size distribution of the SiC source material we achieved to significantly enhance stable growth conditions.

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed.

A facile and efficient approach is demonstrated to visualize the polymerization in situ. A group of tetraphenylethylene (TPE)-containing dithiocarbamates were synthesized and screened as agents for reversible addition fragmentation chain transfer (RAFT) polymerizations. The spatial-temporal control characteristics of photochemistry enabled the RAFT polymerizations to be ON and OFF on demand under alternating visible light irradiation. The emission of TPE is sensitive to the local viscosity change owing to its aggregation-induced emission characteristic. Quantitative information could be easily acquired by the naked eye without destroying the reaction system. Furthermore, the versatility of such a technique was well demonstrated by 12 different polymerization systems. The present approach thus demonstrated a powerful platform for understanding the controlled living radical polymerization process.

We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.

Root-triggered processes (growth, uptake and release of solutes) vary in space and time, and interact with heterogeneous soil microenvironments that provide habitats for (micro)biota on various scales. Despite tremendous progress in method development in the past decades, finding a suitable experimental set-up to investigate processes occurring at the dynamic conjunction of biosphere, hydrosphere, and pedosphere in the close vicinity of active plant roots still represents a major challenge. We discuss recent methodological developments in rhizosphere research with a focus on imaging techniques. We further review established concepts that have been updated with novel techniques, highlighting the need for combinatorial approaches to disentangle rhizosphere processes on relevant scales.

Manual localization of bone fragments on the ground or on complex surfaces in relation to accidents or criminal activity may be time-consuming and challenging. It is here investigated whether combining a near-infrared hyperspectral camera and chemometric modeling with false color back-projection can be used for rapid localization of bone fragments. The approach is noninvasive and highlights the spatial distribution of various compounds/properties to facilitate manual inspection of surfaces. Discriminant partial least squares regression is used to classify between bone and nonbone spectra from the hyperspectral camera. A predictive model (>95% prediction ability) is constructed from raw chicken bones mixed with stone, sand, leaves, moss, and wood. The model uses features in the near-infrared spectrum which may be selective for bones in general and is able to identify a wide variety of bones from different animals and contexts, including aged and weathered bone.