Novel high energy density materials N14 (1,6-dihydro-1,2,3,3a,4,5,5a,6,7,8,8a,9,10,10a-tetradecazapyrene) and N18 (1,2,2a,3,4,4a,5,6,6a,7,8,8a,9,10,10a,11,12a-octadecazacoronene) were designed, and their structures, detonation performance and stabilities were calculated employing density functional theory (DFT). Calculations reveals that they have a good balance between high energy and stability. Their energy gaps between LUMO and HOMO are all lower than that of TATB, while their impact sensitivity h_50% is estimated close to that of RDX. Concerning energy, detonation performance of the N14 (P = 43.6 GPa, D = 10040 m/s, Q = 2214 cal/g) and the N18 (P = 37.4 GPa, D = 9400 m/s, Q = 2114 cal/g) are comparable to CL-20.

To explore the characteristics of the concentric eyewall of a typhoon during its formation and replacement processes, with Super Typhoon Muifa in 2011 as the example case, the Weather Research and Forecast (WRF) mode was used to carry out a numerical simulation to reproduce the entire formation and replacement processes of the concentric eyewall. The physical quantities such as the tangential wind speed, radar echo, radial wind speed, vertical wind speed, and potential vortex were diagnosed and analyzed. The results of the analysis show that the outward expansion of the isovelocity in the lower troposphere was the early signal of the formation of the outer eyewall. After the outer eyewall formed, there was a center of second-highest tangential wind speed in the corresponding area. The second-highest wind speed increased as the strength of the outer eyewall increased, and the position of the second-highest wind speed center was retracted with the retraction of the outer eyewall. The tangential wind speed of the moat area was smaller than that corresponding to the concentric eyewall and this feature gradually disappeared with the increase of the height. The echo in the moat area was weak, and this characteristic was particularly evident when the moat area was relatively wide and the outer eyewall was relatively strong. With the formation and development of the outer eyewall, the intensity of the inflow in the boundary layer corresponding to the inner eyewall was reduced, the intensity of the outflow in the upper layers declined, and the intensities of the inflow and outflow corresponding to the outer eyewall were enhanced. After the second outer eyewall matured, there was a significant inflow in the upper layer of the moat area. Once the outer eyewall formed, a large amount of hydrometeors appeared in the corresponding area, and there was a strong ascending motion inside that area. The strength of the ascending motion and the content of hydrometeors increased as the outer eyewall increased. When the moat area was relatively wide, the divergent airflow generated by the developed outer eyewall in the upper layer would produce a significant descending motion in the moat area.

This research uses ARM-based FPGA to implement the computation of a virtual-real fusion hardware system. It also evaluates the acceleration effect of virtual-real fusion execution speed after connecting related hardware acceleration and provides a reference for real-time information fusion system design. The hardware uses Xilinx Zynq UltraScale+ MPSoC ZCU102 Evaluation Kit. It also obtains color and depth images with Intel® RealsenseTM D435i depth cameras. This system receives image data through the Linux system built on the ARM and fed to the FPGA for object detection using CNN models. In addition, it develops a module for rapidly performing registration between the color images and the depth images. It can calculate the size and position of the display information on the transparent display according to the pixel coordinates and depth values of the human eye and the object. The fusion took about 47ms on a personal computer with a GPU RTX2060 and 25ms on the ZCU102. The acceleration is nearly 168%. Finally, the results were successfully transplanted into the retail display system for demonstration.

Cancer immunotherapy reaches a remarkable achievement in various cancer types and brings new possibilities to improve cancer patients’ long-term survival. However, outcomes vary from case to case, and the present protocol benefits a small fraction of patients. One notable factor is the tumor microenvironment, especially the immune cell components, that may reflect the immune response's status quo on site. Thus, understanding the content of infiltrating immune cells in tumors is not only for research interesting but also a crucial subject toward precision medicine. We implement an algorithm for resolving relative proportions of twenty-one immune cell subclasses from a human tissue profiled transcriptome by microarray technology to reach the goal above. By selecting gene features and then adopting ?-Support Vector Regression, we can construct a deconvolution model and resolve the immune cell context. The excellent consistency between the estimated values and the correct immune-cell composition further demonstrates this approach provides a more natural alternative to revealing samples' immune cell content and reliable results like recent single-cell technologies. Based on this algorithm, the web-based deconvolution tool implemented named mySORT provides a user-friendly interface for estimating the immune cell content by uploading gene expression profiling. We also present comprehensive visualization 2D/3D plots in mySORT so that users can easily make a comparison between different samples. Finally, we synthesized pseudo-bulk expression data from single-cell transcriptomic datasets of 17 melanoma and 16 head and neck cancer patients. The deconvolution results of microarray-based data in the previous study and synthetic pseudo-bulk data all proved the excellent performance of mySORT. We believe that mySORT can help researchers in all fields easily understand complex immune microenvironment. The website of mySORT is freely accessible on https://symbiosis.iis.sinica.edu.tw/mySORT/.

Global warming may increase the potential evapotranspiration (Etp), thereby affecting the amount of clean water resources available in a region. In this study, the systematic biases in temperature outputs of 24 global climate models (GCMs) under 3 emission scenarios are corrected by using 8 bias correction methods. The trend of Etp in Yangzi River Delta in the 21st century is projected by using 4 Etp calculation formulas. The uncertainty of the projections is estimated and decomposed by using multi-way analysis of variance. The influence of uncertainty on the projected change signal is quantified by using the signal-to-noise ratio. The results show that, relative to the reference period (1971~2000), the annual mean daily Etp in Yangzi River Delta will increase by 0.14~0.17mm/d during the period 2021~2050 and by 0.21~0.41mm/d during the period 2061~2090, respectively. During 2021~2050, the uncertainty of Etp increase projections is dominantly contributed by the main effects of GCM (63%) and Etp calculation formula (24%). During 2061~2090, it is mainly contributed by the main effect of GCM (36%), followed by the main effects of emission scenario (34%) and Etp calculation formula (18%). The increase projections of Etp are generally reliable and robust during the two projection periods.