AutoDock Vina is one of the most popular molecular docking tools. In the latest benchmark CASF-2016 for comparative assessment of scoring functions, AutoDock Vina won the best docking power among all ...the docking tools. Modern drug discovery is facing a common scenario of large virtual screening of drug hits from huge compound databases. Due to the seriality characteristic of the AutoDock Vina algorithm, there is no successful report on its parallel acceleration with GPUs. Current acceleration of AutoDock Vina typically relies on the stack of computing power as well as the allocation of resource and tasks, such as the VirtualFlow platform. The vast resource expenditure and the high access threshold of users will greatly limit the popularity of AutoDock Vina and the flexibility of its usage in modern drug discovery. In this work, we proposed a new method, Vina-GPU, for accelerating AutoDock Vina with GPUs, which is greatly needed for reducing the investment for large virtual screens and also for wider application in large-scale virtual screening on personal computers, station servers or cloud computing, etc. Our proposed method is based on a modified Monte Carlo using simulating annealing AI algorithm. It greatly raises the number of initial random conformations and reduces the search depth of each thread. Moreover, a classic optimizer named BFGS is adopted to optimize the ligand conformations during the docking progress, before a heterogeneous OpenCL implementation was developed to realize its parallel acceleration leveraging thousands of GPU cores. Large benchmark tests show that Vina-GPU reaches an average of 21-fold and a maximum of 50-fold docking acceleration against the original AutoDock Vina while ensuring their comparable docking accuracy, indicating its potential for pushing the popularization of AutoDock Vina in large virtual screens.
Due to line impedance mismatches, nonlinear loads and other reasons, the traditional droop control algorithms have great limitations on the control of reactive power sharing. Distributed control ...algorithms based on hierarchical structure have become an effective approach for reactive power sharing compared with traditional centralized control methods. In this paper, an event-triggered control algorithm based on stability analysis of Lyapunov method is put forward in order to satisfy the demand of low-bandwidth communication for distributed generator in islanded microgrid. Subsequently, a distributed hierarchical control scheme adopting proposed event-triggered strategy is designed to achieve proportional reactive power sharing in an islanded microgrid. Finally, the feasibility and validity of the proposed algorithm are further verified in MATLAB/Simulink environment.
Superparamagnetic iron oxide nanoparticles (SPIO) have been synthesized and explored for use as carriers of various nanoadjuvants via loading into dendritic cells (DCs). In our study, homogeneous and ...superparamagnetic nanoparticles are susceptible to internalization by DCs and SPIO-pulsed DCs showed excellent biocompatibility and capacity for ovalbumin (OVA) cross-presentation. Herein, we found that SPIO-loaded DCs can promote the maturation and migration of DCs in vitro
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SPIO coated with 3-aminopropyltrimethoxysilane (APTS) and meso-2,3-dimercaptosuccinic acid (DMSA), which present positive and negative charges, respectively, were prepared. We aimed to investigate whether the surface charge of SPIO can affect the antigen cross-presentation of the DCs. Additionally, the formation of interleukin-1β (IL-1β) was examined after treatment with oppositely charged SPIO to identify the nanoadjuvants mechanism. In conclusion, our results suggest that SPIO are biocompatible and can induce the migration of DCs into secondary lymph nodes. SPIO coated with APTS (SPIO/A
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) exhibited excellent adjuvant potentials for the promotion of antigen cross-presentation and T cell activation and surpassed that of DMSA-coated nanoparticles (SPIO/D
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). This process may be related to the secretion of IL-1β. Our study provides insights into the predictive modification of nanoadjuvants, which will be valuable in DC vaccine design and could lead to the creation of new adjuvants for applications in vaccines for humans.
Automatic License Plate Recognition (ALPR) systems have become popular application areas of the Internet of Things (IoT). A typical ALPR system always needs powerful processors such as Cortex-A7. ...However, most known system for Standard Definition (SD) are not suitable for real-time High Definition (HD) image processing and low power consuming requirement in IoT. A HD ALPR accelerator for the IoT endpoint System on Chip (SoC) is proposed in this paper to meet the needs of computations. Based on the programming flexibility of IoT endpoint SoC, it can switch between HD and SD resolutions, which can avoid the specific resolution switching algorithm. A Field Programmable Gate Array (FPGA) chip is transplanted the Cortex-M0 as the IoT endpoint SoC, through the design of ALPR accelerator and Cortex-M0, data communication is achieved by First-In, First-Out (FIFO) with AMBA High-performance Bus (AHB) interface. Heterogeneous implementation of ALPR system has shown that this HD ALPR algorithm can recognize a license plate in 12.5ms, with a success rate of 95.5%. The system utilizes 41,763 Look-Up-Tables (LUTs) without special FPGA IP core. The comparison shows that the system proposed in this paper makes performance of the SoC based on the Cortex-M0 kernel was two times higher than the Cortex-A72 SoC and 39% of the power consumption of Zynq-7000 that is typical heterogeneous ALPR platform.
Quantifying the temporal and spatial patterns of impervious surfaces (IS) is important for assessing the environmental and ecological impacts of urbanization. In order to better extract IS, and to ...explore the divergence in urbanization in different regions, research on the regional differentiation features and regional change difference features of IS are required. To extract China’s 2013 urban impervious area, we used the 2013 night light (NTL) data and the Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index and enhanced vegetation index (EVI) temporal series data, and used three urban impervious surface extraction indexes—Human Settlements Index, Vegetation-Adjusted NTL Urban Index, and the EVI-adjusted NTL index (EANTLI)—which are recognized as the best and most widely used indexes for extracting urban impervious areas. We used the classification results of the Landsat-8 images as the benchmark data to visually compare and verify the results of the urban impervious area extracted by the three indexes. We determined that the EANTLI index better reflects the distribution of the impervious area. Therefore, we used the EANTLI index to extract the urban impervious area from 2003 to 2013 in the study area, and researched the spatial and temporal differentiation in urban IS. The results showed that China’s urban IS area was 70,179.06 km2, accounting for 0.73% of the country’s land area in 2013, compared with 20,565.24 km2 in 2003, which accounted for 0.21% of the land area, representing an increase of 0.52%. On a spatial scale, like economic development, the distribution of urban impervious surfaces was different in different regions. The overall performance of the urban IS percentage was characterized by a decreasing trend from Northwest China, Southwest China, the Middle Reaches of the Yellow River, Northeast China, the Middle Reaches of the Yangtze River, Southern Coastal China, and Northern Coastal China to Eastern Coastal China. On the provincial scale, the urban IS expansion showed considerable differences in different regions. The overall performance of the Urban IS Expansion index showed that the eastern coastal areas had higher values than the western inland areas. The cities or provinces of Beijing, Tianjin, Jiangsu, and Shanghai had the largest growth in impervious areas. Spatially and temporally quantifying the change in urban impervious areas can help to better understand the intensity of urbanization in a region. Therefore, quantifying the change in urban impervious area has an important role in the study of regional environmental and economic development, policy formulation, and the rational use of resources in both time and space.
The difference of feeder impedance and the nonlinear load may deteriorate reactive power sharing and worsen the power quality, which may cause the breakdown of power supply in islanded microgrids. An ...enhanced discrete consensus algorithm considering information transmission delay is put forward in order to optimize the convergence dynamic. The proposed algorithm defines the independent iteration number of times variable for every agent, which can be transferred to its adjacent agents together with the communication data to control the times of the iteration calculation. The optimized control strategy is adopted for three-phase distributed generators to balance the reactive power sharing. Eventually, the simulation results show that the reactive power will be evenly shared among distributed generators in proportion to their rated capacity and the proposed algorithm achieves good dynamic performance during the transition.
Molecular docking (MD) is one of the core steps in the expensive and time-consuming process of drug design, which is basically an optimization problem based on scoring functions. AutoDock series MD ...software is widely accepted by academia and industry, among which AutoDock Vina (Vina) is the latest and most popular version due to its accuracy and relatively high speed. However, contrast to its prior version, i.e., AutoDock4, hardware acceleration approaches of Vina are rarely reported. In this article, we propose Vina-field-programmable gate array (FPGA), a hardware-accelerated Vina implementation with FPGA that exploits the low-level parallelism. First, the fixed-point quantization is analyzed and realized to accelerate the MD algorithm with a better energy efficiency in hardware. To boost the performance of the module-level computation, multiple in- module hardware pipelines have been designed and implemented. Besides, a strategy for fast accessing to block RAM (BRAM) is implemented by utilizing the layout of data, which brings four times memory access speed to the intermolecular and intramolecular energy computing modules. Under the same 140 ligand-receptor benchmarks, Vina-FPGA performs up to <inline-formula> <tex-math notation="LaTeX">6.9\times </tex-math></inline-formula> (average <inline-formula> <tex-math notation="LaTeX">3.7\times </tex-math></inline-formula>) faster than a state-of-the-art CPU does while consuming only 2.5% energy with similar docking accuracies. Compared to the GPU-accelerated implementation or Vina-GPU, the average energy consumption of Vina-FPGA is merely 45%.
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