Optimal Energy-Storage Configuration for Microgrids Based on SOH Estimation and Deep Q-Network

Energy storage is an important adjustment method to improve the economy and reliability of a power system. Due to the complexity of the coupling relationship of elements such as the power source, load, and energy storage in the microgrid, there are problems of insufficient performance in terms of economic operation and efficient dispatching. In view of this, this paper proposes an energy storage configuration optimization model based on reinforcement learning and battery state of health assessment. Firstly, a quantitative assessment of battery health life loss based on deep learning was performed. Secondly, on the basis of considering comprehensive energy complementarity, a two-layer optimal configuration model was designed to optimize the capacity configuration and dispatch operation. Finally, the feasibility of the proposed method in microgrid energy storage planning and operation was verified by experimentation. By integrating reinforcement learning and traditional optimization methods, the proposed method did not rely on the accurate prediction of the power supply and load and can make decisions based only on the real-time information of the microgrid. In this paper, the advantages and disadvantages of the proposed method and existing methods were analyzed, and the results show that the proposed method can effectively improve the performance of dynamic planning for energy storage in microgrids.     

Development of a ~3He Gas Filling Station at the China Spallation Neutron Source

At the China Spallation Neutron Source(CSNS), we have developed a custom gas-filling station, a glassblowing workshop, and a spin-exchange optical pumping(SEOP) system for producing high-quality ~3He-based neutron spin filter(NSF) cells. The gas-filling station is capable of routinely filling ~3He cells made from GE180 glass of various dimensions, to be used as neutron polarizers and analyzers on beamlines at the CSNS. Performance tests on cells fabricated at our gas-filling station are conducted via neutron transmission and nuclear-magneticresonance measurements, revealing nominal filling pressures, and a saturated ~3He polarization in the region of 80%, with a lifetime of approximately 240 hours. These results demonstrate our ability to produce competitive NSF cells to meet the ever-increasing research needs of the polarized neutron research community.     

A molecular mechanics approach for analyzing tensile nonlinear deformation behavior of single-walled carbon nanotubes

In this paper, by capturing the atomic information and reflecting the behaviour governed by the nonlinear potential function, an analytical molecular mechanics approach is proposed. A constitutive relation for single-walled carbon nanotubes (SWCNT’s) is established to describe the nonlinear stress-strain curve of SWCNT’s and to predict both the elastic properties and breaking strain of SWCNT’s during tensile deformation. An analysis based on the virtual internal bond (VIB) model proposed by P. Zhang et al. is also presented for comparison. The results indicate that the proposed molecular mechanics approach is indeed an acceptable analytical method for analyzing the mechanical behavior of SWCNT’s. The project supported by the National Natural Science Foundation of China (10121202, 90305015 and 10328203), the Key Grant Project of Chinese Ministry of Education (0306) and the Research Grants Council of the Hong Kong Special Administrative Region, China (HKU 7195/04E).     

KEADA: Identifying Key Classes in Software Systems Using Dynamic Analysis and Entropy-Based Metrics

Software maintenance is indispensable in the software development process. Developers need to spend a lot of time and energy to understand the software when maintaining the software, which increases the difficulty of software maintenance. It is a feasible method to understand the software through the key classes of the software. Identifying the key classes of the software can help developers understand the software more quickly. Existing techniques on key class identification mainly use static analysis techniques to extract software structure information. Such structure information may contain redundant relationships that may not exist when the software runs and ignores the actual interaction times between classes. In this paper, we propose an approach based on dynamic analysis and entropy-based metrics to identify key classes in the Java GUI software system, called KEADA (identifying KEy clAsses based on Dynamic Analysis and entropy-based metrics). First, KEADA extracts software structure information by recording the calling relationship between classes during the software running process; such structure information takes into account the actual interaction of classes. Second, KEADA represents the structure information as a weighted directed network and further calculates the importance of each node using an entropy-based metric OSE (One-order Structural Entropy). Third, KEADA ranks classes in descending order according to their OSE values and selects a small number of classes as the key class candidates. In order to verify the effectiveness of our approach, we conducted experiments on three Java GUI software systems and compared them with seven state-of-the-art approaches. We used the Friedman test to evaluate all approaches, and the results demonstrate that our approach performs best in all software systems.     

An Encryption Algorithm for Region of Interest in Medical DICOM Based on One-Dimensional eλ-cos-cot Map

Today, with the rapid development of the Internet, improving image security becomes more and more important. To improve image encryption efficiency, a novel region of interest (ROI) encryption algorithm based on a chaotic system was proposed. First, a new 1D eλ-cos-cot (1D-ECC) with better chaotic performance than the traditional chaotic system is proposed. Second, the chaotic system is used to generate a plaintext-relate keystream based on the label information of a medical image DICOM (Digital Imaging and Communications in Medicine) file, the medical image is segmented using an adaptive threshold, and the segmented region of interest is encrypted. The encryption process is divided into two stages: scrambling and diffusion. In the scrambling stage, helical scanning and index scrambling are combined to scramble. In the diffusion stage, two-dimensional bi-directional diffusion is adopted, that is, the image is bi-directionally diffused row by column to make image security better. The algorithm offers good encryption speed and security performance, according to simulation results and security analysis.     

Synthesis of Halopyrazole Matrine Derivatives and Their Insecticidal and Fungicidal Activities

Matrine is a traditional botanical pesticide with a broad-spectrum biological activity that is widely applied in agriculture. Halopyrazole groups are successfully introduced to the C13 of matrine to synthesize eight new derivatives with a yield of 78–87%. The insecticidal activity results show that the introduction of halopyrazole groups can significantly improve the insecticidal activity of matrine on Plutella xylostella, Mythimna separata and Spodoptera frugiperda with a corrected mortality rate of 100%, which is 25–65% higher than matrine. The fungicidal activity results indicate that derivatives have a high inhibitory effect on Ceratobasidium cornigerum, Cibberella sanbinetti, Gibberrlla zeae and Collectot tichum gloeosporioides. Thereinto, 4-Cl-Pyr-Mat has the best result, with an inhibition rate of 23–33% higher than that of matrine. Therefore, the introduction of halogenated pyrazole groups can improve the agricultural activity of matrine.     

Adaptive coordination assemblies based on a flexible tetraazacyclododecane ligand for promoting carbon dioxide fixation

Coordination hosts based on flexible ligands have received increasing attention due to their inherent adaptive cavities that often show induced-fit guest binding and catalysis like enzymes. Herein, we report the controlled self-assembly of a series of homo/heterometallic coordination hosts (Me₄enPd)_2n(ML)_n [n = 2/3; M = Zn(ii)/Co(ii)/Ni(ii)/Cu(ii)/Pd(ii)/Ag(i); Me₄en: N,N,N′,N′-tetramethylethylenediamine] with different shapes (tube/cage) from a flexible tetraazacyclododecane-based pyridinyl ligand (L) and cis-blocking Me₄enPd(ii) units. While the Ag(i)-metalated ligand (AgL) gave rise to the formation of a (Me₄enPd)₄(ML)₂-type cage, all other M(ii) ions led to isostructural (Me₄enPd)₆(ML)₃-type tubular complexes. Structural transformations between cages and tubes could be realized through transmetalation of the ligand. The buffering effect on the ML panels endows the coordination tubes with remarkable acid–base resistance, which makes the (Me₄enPd)₆(ZnL)₃ host an effective catalyst for the CO₂ to CO₃²⁻ conversion. Control experiments suggested that the integration of multiple active Zn(ii) sites on the tubular host and the perfect geometry match between CO₃²⁻ and the cavity synergistically promoted such a conversion. Our results provide an important strategy for the design of adaptive coordination hosts to achieve efficient carbon fixation.

A series of coordination hosts were prepared and their applications in CO₂ fixation were studied.     

一种高性能太阳敏感器复合光学系统设计

以夫朗禾费衍射理论为基础,结合微透镜,设计了一种高性能的数字式太阳敏感器复合光学系统。分析了光学系统的组成,建立了光学系统的数学模型,设计了光学系统的焦距、孔径和微透镜参量,并进行了成像的数值仿真。仿真结果表明,与基于掩模的光学系统相比,这种新型的复合光学系统成像光斑能量分布集中,保证计算光斑中心位置的高精度,使敏感器具有大视场和高精度的特点。     

The Antioxidant and Hypolipidemic Effects of Mesona Chinensis Benth Extracts

In this study, the antioxidant and hypolipidemic effects of Mesona Chinensis Benth (MCB) extracts were evaluated. Seven fractions (F0, F10, F20, F30, F40, F50 and MTF) were obtained from the MCB ethanol extracts. Compared to the commercial antioxidants (vitamin C), MTF and F30 exhibited higher antioxidant activities in the antiradical activity test and the FRAP assay. The half-inhibition concentration (IC50) for MTF and F30 were 5.323 µg/mL and 5.278 µg/mL, respectively. MTF at 200 µg/mL significantly decreased the accumulation of TG in oleic acid (OA)-induced HepG2 cells and reversed the inhibitory effect of Compound C on AMPK (MTF and F30 significantly increased the glucose utilization of insulin-induced HepG2 cells). In addition, the components of MTF were identified by HPLC-MS, which were caffeic acid, quercetin 3-O-galactoside, isoquercetin, astragalin, rosmarinic acid, aromadendrin-3-O-rutinoside, rosmarinic acid-3-O-glucoside and kaempferol-7-O-glucoside. Through statistical correlations by Simca P software, it was found that the main antioxidant and hypolipidemic components of MCB might be caffeic acid, kaempferol-7-O-glucoside, rosmarinic acid-3-O-glucoside and aromadendrin-3-O-rutinoside, which may play important roles in the AMPK pathway. MTF and F30 in MCB could be potential health products for the treatment of hyperlipidemia.