LI Yanchen, LIU Ziqiang, ZHAO Min, TAN Xin, HUANG Zhipeng, MA Yingfei, YOU Xiaoyan
2022, 11(2):1-11. DOI: 10.12146/j.issn.2095-3135.20210423001
Abstract:Staphylococcus aureus is a gram-positive pathogen. The clinical isolates are usually resistant to multiple antibiotics. Therefore, it is of great significance to find specific phages with high efficiency and broad host spectrum for the treatment of clinical drug-resistant S. aureus infection. Using S. aureus K84 as the host, lytic phage SAK84P was isolated from sewage. The phage has a hexagonal head with 112 nm in diameter and a contractile tail with 200 nm in length. Based on the morphology, the phage can be classified as myovirus. It has the optimal growth pH between 5.0~7.0, growth temperature between 37~50 ℃, the one-step growth curve shows its duration time is 20 min, and burst size of 100 PFU/cell. Whole genome sequencing shows the phage has a total genome length of 141 535 bp with 30% of GC content, and encodes 224 open reading frames and 4 tRNA genes. The phylogenetic tree diagram shows that the phage belongs to the Kayvirus genus in the family of Herelleviridae. The results also shows that phage SAK84P has a broad host range and can lyse multiple clinic isolates of S. aureus with a high activity. Genome annotations indicate no known resistance genes or virulence genesinthe genome of phage SAK84P, suggesting its potential for treatment of clinical multidrug-resistant S. aureus infection.
HUANG Biyan, LUO Qingsong, ZHOU Yimin
2022, 11(2):12-27. DOI: 10.12146/j.issn.2095-3135.20210421001
Abstract:In this paper, an improved susceptible, exposed, infectious, and recovered model has been designed to simulate the complex transmission of Novel Coronavirus Disease 2019 (COVID-19). With the aid of computer simulation, the influence of different preventative measures on epidemic control was analyzed. Comments are put forward based on the analysis for the prevention and control of the epidemic control in the future. The SEIR model is a classical model of virus transmission which has been improved in the paper by adding more parameters such as quarantine and Traditional Chinese Medicine (TCM) intervention measures. With the characteristics of simulating self-replication of living systems, the developed model is applied to simulate the development trend of COVID-19. Furthermore, the key factors affecting the development trend of the disease were considered to discuss the effect on the virus transmission. A simulation model which reflects the transmission, quarantine, and Traditional Chinese Medicine (TCM) intervention measures of COVID-19 has been designed accordingly. The model prediction results have demonstrated that the estimation of quarantine measures and Chinese medicine interventions are basically consistent with the actual situation in the prevention of COVID-19, indicating that quarantine and intervention of Chinese medicine can play a positive role in controlling the epidemic situation.
LI Runhui, GU Liang, YU Zhibin
2022, 11(2):28-40. DOI: 10.12146/j.issn.2095-3135.20210422001
Abstract:Distributed key-value storage is a key component in the distributed storage system, which replicates the key-value pairs to local engines in different storage servers and uses the consensus algorithm to keep replicas consistent. The log-structured merge tree based local key-value engine is the most popular storage algorithm that designed for general purpose. However, the original LSM-tree structure is not suitable for the specific workload of the upper-layer consensus logic. It usually causes performance loss in the write operations and extra spatial amplification during full-node repair. To solve this problem, a local engine named PheonixLSM is designed for distributed key-value storage. PheonixLSM boosts performance by eliminating the double-sync problem for write operations. It also reorganizes the SST file layout to eliminate extra write amplification during full-node repair. Experimental results showed that, compared with distributed key-value storage using default local engine, that PheonixLSM can achieve up to 90.7% write performance gain and reduce the extra write amplification from 65.6% to 6.4%, and the repair time also can be reduced by 72.3%.
SUN Youxiao, FENG Ruicheng, GUAN Weipeng, QIAO Yu, DONG Chao, JING Kun, LIU Chenfei, XU Yeping, CHEN Yingpeng, ZHOU Weidong
2022, 11(2):41-54. DOI: 10.12146/j.issn.2095-3135.20211026002
Abstract:This paper presents a unified framework for various multi-scale structures. With this framework, two factors of multi-scale convolution, i.e. feature propagation and cross-scale communication are explored. A generic and efficient multi-scale convolution unit named Multi-Scale cross-Scale Share-weights Convolution (MS3-Conv) is proposed. Experimental results showed that, the proposed MS3-Conv can achieve better super resolution performance than conventional convolution methods with less parameters and computational cost. By observation of the visual quality, results also showed that the MS3-Conv outperform in the reconstruction of high-frequency image details.
2022, 11(2):55-66. DOI: 10.12146/j.issn.2095-3135.20210413001
Abstract:With the ever-increasing size of legal cases in China, relevant legal case retrieval given a user query has attracted considerable attention. Conventional keyword-based retrieval systems look for matching cases that contain one or more words specified by the user. However, keyword searching is sharply focused on finding the exact terms specified in the query, making the retrieval systems miss many relevant documents. On the other hand, semantic-aware information retrieval methods usually rely heavily
2022, 11(2):67-78. DOI: 10.12146/j.issn.2095-3135.20211122001
Abstract:Machine reading comprehension models based on deep learning have achieved remarkable success recently. However, these models have significant defects in constructing long-distance and global semantic relationships, which affect their performance in reading comprehension tasks. Moreover, when reasoning over passage text, most of them simply regard it as a word sequence without exploring rich semantic relationships between words. In order to solve this problem, this paper proposes a new system effective graph structure named Dynamic Conversational Graph Network (DCGN). Firstly, named entities are extracted from the text, and the semantic relationship between syntactic structure and sentence is used for modeling. Then, the context-embedded representation based on serialization structure and the entity node embedded representation based on graph structure are fused by semantic fusion module. Finally, dynamic graph neural network is used to realize machine reading comprehension. The model dynamically builds inference graphs of questions and session history during each round of conversation, which can effectively capture the semantic structure information and the history flow of the conversation. Experimental results show that the model performs well on two recent session challenges (CoQA and QuAC).
LI Kun, ZHANG Lei, GUO Rui, YU Shuhui, CAO Xiuhua, FU Zhenxiao, SUN Rong
2022, 11(2):79-88. DOI: 10.12146/j.issn.2095-3135.20211020001
Abstract:As a key and foundational component for modern electronic devices, the multilayer ceramic capacitors with excellent temperature stability are desirable for the next generation of high-temperature capacitors. Herein, authors fabricated Nd-doped BaTiO 3 -(Bi 1/2 Na 1/2 )TiO 3 dielectric ceramics with Electronic Industries Association specification of X9R by solid-state reaction process. It is shown that the 0.9BT-0.1BNT exhibits a homogeneous solid solution with the ferroelectric domain structure. With an increase in the Nd concentration and temperature, the tetragonality decreases while the peak of dielectric permittivity curve becomes more broaden and stable. In particular, Nb-doped 0.9BT-0.1BNT samples imply a typical core-shell structure with nano-sized domain in the core to increase the dielectric constant. In addition, 0.9BT-0.1BNT-2.0Nb ceramic demonstrates the dielectric constant of 1 800 and dielectric loss of 2.0% from -55 ℃ to 200 ℃. This work not only provides a promising candidate material, but also provides an attractive method to design new family of high-performance dielectric ceramics for high temperature MLCCs applications.
HU Xiangjian, FENG Song, FENG Lulu, WANG Di, LIU Yong, CHEN Menglin, DING Binbin, HAN Chao, HAN Xiaoxiang
2022, 11(2):89-106. DOI: 10.12146/j.issn.2095-3135.20210707001
Abstract:Photonic?modulator?is?the?core?component?of?optical?fiber?communication?system,?which?mainly modulates the optical signal and realizes the conversion of the signal from the electrical domain to the optical domain. With the development of silicon based semiconductor technology, silicon based photonic modulator has gradually become the mainstream silicon photonic devices, and the realization of gigahertz bandwidth?modulator?based?on?silicon?technology?has?laid?a?foundation?for?the?development?of?silicon photonics. At present, the modulation speed of silicon-based photonic modulator has exceeded 50 GHz, which?basically?meets?the?bandwidth?requirements?of?modulation?format.?However,?silicon-based?photonic modulators?with?low?driving?voltage?and?low?insertion?loss?are?still?a?field?worthy?of?research.?More?and more research institutions have joined the research of silicon-based photonic modulators and have made great progress. This paper mainly analyzes the research progress of silicon-based photonic modulators at home and abroad, discusses the research status of silicon-based photonic modulators based on SOI materials,?SiGe?materials,?Ge?materials,?ferroelectric?materials,?organic?photoelectric?materials,?Ⅲ-Ⅴ?group materials and graphene materials, and compares and analyzes the performance of relevant modulators. It provides?ideas?for?further?research?and?development?of?photonic?modulator?with?high?speed?and?low?loss?in the future.
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