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Abstract:

We study the rare decays

\begin{document}$\Lambda_b \rightarrow \Lambda l^+ l^-~(l=e,\mu, \tau)$\end{document}

in the Bethe-Salpeter equation approach. We find that the branching ratio is

${\rm Br}(\Lambda_b \rightarrow \Lambda \mu^+ \mu^-)\times 10^{6} = 1.051 \sim 1.098$

in our model. This result agrees with the experimental data well. In the same parametric region, we find that the branching ratio is

${\rm Br}(\Lambda_b \rightarrow \Lambda e^+ e^-(\tau^+ \tau^-) )\times 10^{6} = 0.252 \sim 0.392 ~(0.286 \sim 0.489)$

.

[Abstract](92) [FullText HTML](48) [PDF 0KB](0)
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Single-photon avalanche diode (SPAD) arrays are solid-state detectors that offer imaging capabilities at the level of individual photons, with unparalleled photon counting and time-resolved performance. This fascinating technology has progressed at a very fast pace in the past 15 years, since its inception in standard CMOS technology in 2003. A host of architectures have been investigated, ranging from simpler implementations, based solely on off-chip data processing, to progressively "smarter" sensors including on-chip, or even pixel level, time-stamping and processing capabilities. As the technology has matured, a range of biophotonics applications have been explored, including (endoscopic) FLIM, (multibeam multiphoton) FLIM-FRET, SPIM-FCS, super-resolution microscopy, time-resolved Raman spectroscopy, NIROT and PET. We will review some representative sensors and their corresponding applications, including the most relevant challenges faced by chip designers and end-users. Finally, we will provide an outlook on the future of this fascinating technology.
[Abstract](9) [FullText HTML](2) [PDF 0KB](0)
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Objectives   China is one of the countries most affected by natural disasters. The emergency surveying and mapping is an important part of the comprehensive disaster prevention and mitigation system in China. It plays an increasingly prominent role in the response system for the major natural disasters and emergencies. However, series of problems are still existing, such as lacking of capacity in the rapid acquirement of field information, lacking of rapid response of data processing. Also, given the emergency response relies on the on-demand service, it faces difficulties on efficiently sharing of geographical information with stakeholder. Thus, it is urgent to improve capacity of rapid geo-informatics support in order to build an efficient and scientific nature hazard rapid response system.  Methods   We propose a technology framework and system architecture of national emergency surveying and mapping. It consists of four key techniques, including:(1)Space-Air-Ground integration observation network, to acquire disaster information and multi-sensors collaborative observation for various disaster emergence response needs; (2) high performance computing and artificial intelligence techniques, which can greatly improve the efficiency of massive data processing; (3) geographic information based on cloud platform, which can provide on-demand service to stakeholder; (4) multi-hazard mapping knowledge that can be comprehensively expressed and distributed crossing multiple media carriers.  Results   Based on the national emergency surveying and mapping capacity developing program, the outcome of this research covers four aspects in order to improve emergence response capabilities. They are: (1) the capability of obtaining latest disaster information using remote sensing technology; (2) the capability of on-site surveying and investigating; (3) the capability of sharing emergency spatial information; and (4) the capability of supporting emergency management and decision.  Conclusions   The program motivated from the national emergency response and disaster relief demands for efficient geographic information service.It integrates state-of-art information technology such as cloud computing, artificial intelligence and block chain.It meets the need of multiple emergency response stages, including disaster monitoring and early-warning, disaster assessment, emergency rescue, and post-disaster reconstruction, the relevant technologies include geo-information acquisition, processing and analysis efficiently.
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2020, 33(3): 296-302.   doi: 10.1063/1674-0068/cjcp1905095
[Abstract](47) [FullText HTML](22) [PDF 3004KB](0)
Abstract:
2020, 33(3): 311-318.   doi: 10.1063/1674-0068/cjcp1907136
[Abstract](13) [FullText HTML](7) [PDF 10885KB](0)
Abstract:
2020, 33(3): 319-326.   doi: 10.1063/1674-0068/cjcp1907145
[Abstract](14) [FullText HTML](12) [PDF 2303KB](0)
Abstract:
2020, 33(3): 327-333.   doi: 10.1063/1674-0068/cjcp1912200
[Abstract](10) [FullText HTML](8) [PDF 12711KB](0)
Abstract:
Metallophilic interaction is a unique type of weak intermolecular interaction, where the electronic configuration of two metal atoms is closed shell. Despite its significance in multidisciplinary fields, the nature of metallophilic interaction is still not well understood. In this work, we investigated the electronic structures and bonding characteristic of bimetallic Au$_{2}$@Cu$_{6}$ nanocluster through density functional theory method, which was reported in experiments recently [Angew. Chem. Int. Ed. 55 , 3611 (2016)]. In general thinking, interaction between two moieties of (CuSH)$_{6}$ ring and (Au$_{2}$PH$_{3}$)$_{2}$ in the Au$_{2}$@Cu$_{6}$ nanocluster can be viewed as a d$^{10}$-$\sigma$ closed-shell interaction. However, chemical bonding analysis shows that there is a ten center-two electron (10c-2e) multicenter bonding between two moieties. Further comparative studies on other bimetallic nanocluster M$_{2}$@Cu$_{6}$ (M = Ag, Cu, Zn, Cd, Hg) also revealed that multicenter bonding is the origin of electronic stability of the complexes besides the d$^{10}$-$\sigma$ closed-shell interaction. This will provide valuable insights into the understanding of closed-shell interactions.
2020, 33(3): 334-342.   doi: 10.1063/1674-0068/cjcp1907132
[Abstract](41) [FullText HTML](18) [PDF 1197KB](1)
Abstract:
The dielectric properties between in-particle/water interface and bulk solution are significantly different, which are ignored in the theories of surface potential estimation. The analytical expressions of surface potential considering the dielectric saturation were derived in mixed electrolytes based on the nonlinear Poisson-Boltzmann equation. The surface potentials calculated from the approximate analytical and exact numerical solutions agreed with each other for a wide range of surface charge densities and ion concentrations. The effects of dielectric saturation became important for surface charge densities larger than 0.30 C/m$^2$. The analytical models of surface potential in different mixed electrolytes were valid based on original Poisson-Boltzmann equation for surface charge densities smaller than 0.30 C/m$^2$. The analytical model of surface potential considering the dielectric saturation for low surface charge density can return to the result of classical Poisson-Boltzmann theory. The obtained surface potential in this study can correctly predict the adsorption selectivity between monovalent and bivalent counterions.
2020, 33(3): 343-348.   doi: 10.1063/1674-0068/cjcp1905109
[Abstract](10) [FullText HTML](8) [PDF 5754KB](0)
Abstract:
A superamphiphobic (SAP) surface was fabricated by electrodepositing Cu-Ni micro-nano particles on aluminum substrate and modifying via 1H, 1H, 2H, 2H-perfluorodecyltrimethoxysilane. Scanning electron microscopy, X-ray diffraction, energy-dispersive X-ray spectroscopy, and Fourier-transform infrared spectroscopy were employed to investigate the morphology and chemical composition. The results showed that the SAP surface had three-dimensional micro-nano structures and exhibited a maximum water contact angle of 160.0$^{\circ}$, oil contact angle of 151.6$^{\circ}$, a minimum water slide angle of 0$^{\circ}$ and oil slide angle of 9$^{\circ}$. The mechanical strength and chemical stability of the SAP surface were tested further. The experimental results showed that the SAP surface presented excellent resistance to wear, prominent acid-resistance and alkali-resistance, self-cleaning and anti-fouling properties.
2020, 33(3): 349-356.   doi: 10.1063/1674-0068/cjcp1911198
[Abstract](14) [FullText HTML](9) [PDF 9049KB](2)
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In view of the high activity of Pt single atoms in the low-temperature oxidation of CO, we investigate the adsorption behavior of Pt single atoms on reduced rutile TiO$_2$(110) surface and their interaction with CO and O$_2$ molecules using scanning tunneling microscopy and density function theory calculations. Pt single atoms were prepared on the TiO$_2$(110) surface at 80 K, showing their preferred adsorption sites at the oxygen vacancies. We characterized the adsorption configurations of CO and O$_2$ molecules separately to the TiO$_2$-supported Pt single atom samples at 80 K. It is found that the Pt single atoms tend to capture one CO to form Pt-CO complexes, with the CO molecule bonding to the fivefold coordinated Ti (Ti$_{5 \rm{c}}$) atom at the next nearest neighbor site. After annealing the sample from 80 K to 100 K, CO molecules may diffuse, forming another type of complexes, Pt-(CO)$_2$. For O$_2$ adsorption, each Pt single atom may also capture one O$_2$ molecule, forming Pt-O$_2$ complexes with O$_2$ molecule bonding to either the nearest or the next nearest neighboring Ti$_{5 \rm{c}}$ sites. Our study provides the single-molecule-level knowledge of the interaction of CO and O$_2$ with Pt single atoms, which represent the important initial states of the reaction between CO and O$_2$.
2020, 33(3): 357-364.   doi: 10.1063/1674-0068/cjcp1907143
[Abstract](17) [FullText HTML](6) [PDF 3948KB](0)
Abstract:

Polydiacetylene (PDA) is one kind of the conjugated polymer with layered structure, which can serve as a host to accommodate the guest components through intercalation. In these intercalated PDAs, some of them were reported to have a nearly perfect organized structure and perform completely reversible thermochromism. Till now, these reported intercalated PDAs were made by only introducing a single component for intercalation. Here, we chose 10, 12-pentacosadiynoic acid (PCDA) as the monomer, of which the carboxyl-terminal groups can interact with either Tb

\begin{document}$^{3+}$\end{document}

ions or melamines (MAs). When the feeding molar ratio of PCDA, MA, and Tb

\begin{document}$^{3+}$\end{document}

ion was 3:267:1, only Tb

$^{3+}$

ions were intercalated though excess MAs existed. Such Tb

$^{3+}$

-intercalated poly-PCDA exhibited completely reversible thermochromism, where almost all the carboxyl groups interacted with Tb

$^{3+}$

ions to form the nearly perfect structure. When the feeding molar ratio of PCDA, MA, and Tb

$^{3+}$

ion was 3:267:0.6, both Tb

$^{3+}$

ions and MAs were intercalated. There existed some defects in the imperfect MA-intercalated domains and at the domain boundaries. The MA/Tb

$^{3+}$

-intercalated poly-PCDA exhibits partially reversible thermochromism, where the backbones near the defects are hard to return the initial conformation, while the rest, those at nearly perfect organized domains, are still able to restore the initial conformation.

2020, 33(3): 365-370.   doi: 10.1063/1674-0068/cjcp1907146
[Abstract](13) [FullText HTML](6) [PDF 16446KB](0)
Abstract:
In recent years, flexible pressure sensors have attracted much attention owing to their potential applications in motion detection and wearable electronics. As a result, important innovations have been reported in both conductive materials and the underlying substrates, which are the two crucial components of a pressure sensor. 1D materials like nanowires are being widely used as the conductive materials in flexible pressure sensors, but such sensors usually exhibit low performances mainly due to the lack of strong interfacial interactions between the substrates and 1D materials. In this paper, we report the use of graphene/graphene scrolls hybrid multilayers films as the conductive material and a micro-structured polydimethylsiloxane substrate using Epipremnum aureum leaf as the template to fabricate highly sensitive pressure sensors. The 2D structure of graphene allows to strongly anchor the scrolls to ensure the improved adhesion between the highly conductive hybrid films and the patterned substrate. We attribute the increased sensitivity (3.5 kPa$^{-1}$), fast response time ($<$50 ms), and the good reproducibility during 1000 loading-unloading cycles of the pressure sensor to the synergistic effect between the 1D scrolls and 2D graphene films. Test results demonstrate that these sensors are promising for electronic skins and motion detection applications.
2020, 33(3): 371-375.   doi: 10.1063/1674-0068/cjcp1907142
[Abstract](13) [FullText HTML](11) [PDF 10521KB](2)
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One simple and environmental friendly synthesis strategy for preparing low-cost magnetic Fe$_3$C@C materials has been facilely developed using a modified sol-gel approach, wherein natural magnetite acted as the iron source. A chelating polycarboxylic acid such as citric acid (CA) was employed as the carbon source, and it dissolved Fe very effectively, Fe$_3$O$_4$ and natural magnetite to composite an iron-citrate complex with the assistance of ammonium hydroxide. The core-shell structure of the as-prepared nanocomposites was formed directly by high-temperature pyrolysis. The Fe$_3$C@C materials exhibited superparamagnetic properties (38.09 emu/mg), suggesting potential applications in biomedicine, environment, absorption, catalysis, etc.
2020, 33(3): 376-384.   doi: 10.1063/1674-0068/cjcp1906123
[Abstract](10) [FullText HTML](6) [PDF 7446KB](0)
Abstract:
Smart nanoparticles that respond to pathophysiological parameters, such as pH, GSH, and H$_2$O$_2$, have been developed with the huge and urgent demand for the high-efficient drug delivery systems (DDS) for cancer therapy. Herein, cubic poly(ethylene glycol) (PEG)-modified mesoporous amorphous iron oxide (AFe) nanoparticles (AFe-PEG) have been successfully prepared as pH-stimulated drug carriers, which can combine doxorubicin (DOX) with a high loading capacity of 948 mg/g, forming a novel multifunctional AFe-PEG/DOX nanoparticulate DDS. In an acidic microenvironment, the AFe-PEG/DOX nanoparticles will not only release DOX efficiently, but also release Fe ions to catalyze the transformation of H$_2$O$_2$ to $\cdot$OH, acting as fenton reagents. In vitro experimental results proved that the AFe-PEG/DOX nanoparticles can achieve combination of chemotherapeutic (CTT) and chemodynamic therapeutic (CDT) effects on Hela tumor cells. Furthermore, the intrinsic magnetism of AFe-PEG/DOX makes its cellular internalization efficiency be improved under an external magnetic field. Therefore, this work develops a new and promising magnetically targeted delivery and dual CTT/CDT therapeutic nano-medicine platform based on amorphous iron oxide.
2020, 32(3): 031001.   doi: 10.11884/HPLPB202032.190303
[Abstract](136) [FullText HTML](41) [PDF 0KB](0)
Abstract:

A thermal damage analysis model of scratches and residual polishing particles on the optical surface is established. The thermal damage properties of optical materials under such complex defects are studied. The finite difference method was used to calculate the light field modulation and temperature field distribution of the optical material surface at different positions of the polished particles at different scales. According to the surface temperature distribution, the thermal damage threshold of the optical material under the corresponding conditions is achieved. The results show that in addition to the influence of the polishing particle radius on the material damage threshold, when the polishing particles are located at different positions in the scratch width direction, the thermal damage threshold of the material will also change significantly. Among them, the polishing particles in the center of the scratch have the strongest modulation on the light field, and are more likely to cause melting damage of the material.

2020, 32(3): 031003.   doi: 10.13374/j.issn2095-9389.2019.06.001
[Abstract](192) [FullText HTML](89) [PDF 0KB](0)
Abstract:

With the rapid development of high-power lasers and electronic technology, higher requirements have been proposed for the structure and material of the heat sink device. Based on the principle of conduction-insulation heat, alternating stack epoxy resin composites with excellent thermal protection were prepared, the hexagonal boron nitride (h-BN: 5%, 15%, 25%) and expanded vermiculite (E-ver: 1%) are used as fillers for heat dissipation layer and thermal insulation layer, respectively. The thermal protection performance experiment was completed. The result shows that the temperature of the top center is 13−16 °C lower than that of the traditional materials, and the thermal delay time is greatly improved. An increase in the h-BN content causes an increase in the thermal protection properties of the composites. The thermal mechanism of the anisotropic stacked composites was explained.

2020, 32(3): 032003.   doi: 10.11884/HPLPB202032.190426
[Abstract](45) [FullText HTML](25) [PDF 0KB](0)
Abstract:
The liquid crystal phase modulators (LCPMs) have applications and prospects in fusion ignition, laser processing, optoelectronic countermeasure, laser radar, laser communication, laser protection and so on. However, owing to the limited laser damage resistance of the materials constituting the LCPMs as well as insufficient system research on the laser damage and the phase modulation performance degradation of LCPMs induced by high power lasers, the laser handling power of LCPMs cannot satisfy the requirements of high power laser developments. To provide guidance for optimizing the fabrication process of LCPMs with high laser handling power, we reviewed the laser damage and the phase modulation performance degradation characteristics of LCPMs irradiated by high-peak-power lasers and high-average-power-lasers and then summarized the methods to improve the laser handling power of LCPMs.
2020, 32(3): 032004.   doi: 10.11884/HPLPB202032.190447
[Abstract](45) [FullText HTML](28) [PDF 0KB](0)
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Ultra-low density SiO2 aerogel as a classic three-dimensional network nano-porous material is widely used in many fields such as thermal insulation and adsorption. In this manuscript, tetramethoxysilane (TMOS) is used as the silicon source and an acid-base two-step method is used. Ultra-low density SiO2 aerogels were prepared by ethanol supercritical drying technology, and a series of studies were performed on the aerogels using SEM\TEM\BET and other characterization methods. When the aerogel density was 0.6 mg/cm3, it had the best comprehensive properties. In addition, this aerogel has the advantages of ultra-low density, high specific surface area, good formability, and short preparation cycle. Thus, it is expected to play a significant role as a frozen target in laser inertial confinement fusion experiments.
2020, 32(3): 033101.   doi: 10.11884/HPLPB202032.190291
[Abstract](29) [FullText HTML](12) [PDF 0KB](0)
Abstract:
In this paper, the plasma electron density and collision frequency are calculated based on the flow field simulation of RAM C-III air vehicle, and an inhomogeneous plasma model is established according to the calculation results. The effects of plasma density, plasma thickness, plasma collision frequency and external magnetic field on the propagation characteristics of terahertz wave in plasma are analyzed using scattering matrix method. The results show that the propagation loss increases with plasma electron density and plasma thickness, while the transmittance decreases first and then increases with the increasing of collision frequency. When an external magnetic field is applied, the propagation characteristics of the left-handed polarized terahertz wave will be improved, while for the right-handed polarized terahertz wave, the application of magnetic field induces an absorption peak, which shifts to high frequency range with the increasing of magnetic induction intensity. This work may make a contribution to solving the problem of communication blackout.
2020, 32(3): 033102.   doi: 10.11884/HPLPB202032.190302
[Abstract](23) [FullText HTML](14) [PDF 0KB](0)
Abstract:
This paper studies the interaction effect between the micro-structure photoconductive antenna (PCA) and femtosecond laser, the control of radiated terahertz (THz) wave, and the radiation regulation mechanism of the THz wave for the photoconductive antenna (PCA). The Drude-Lorentz theory model is used to solve the photocurrent density, which is then iterated to the excitation grid by FDTD method. And then the time-varying electromagnetic fields is solved by Maxwell’s equations. The radiated THz wave from the near field to far field in the multi-layer medium is got through the Green's Function of transmission line, and the relationship between the photocurrent and impedance of the radiation is established. At the same time, the relationship between the photocurrent and the magnetic resonance model is also established. The control mechanism of THz wave radiation from micro-structure S-shaped PCA is analyzed by simulation. The results show that the radiation impedance of the equivalent model is changed after split ring resonator (SRR) is introduced into the H-shaped PCA. Meanwhile, it is known that the coupling effect exists when the coupling coefficient is not zero. With the increasing of the coupling coefficient, and the radiation intensity of the resonance frequency peak increases and shifts. The adjusting range of the center frequency between 0.50−0.80 THz, the frequency modulation degree is 75%, and the peak radiation efficiency increases by 70% after simulating the S-shaped PCA. This work lays an important foundation for the design of THz wave resonance center frequency range and structure of high-power PCA.
2020, 32(3): 033201.   doi: 10.11884/HPLPB202032.190355
[Abstract](183) [FullText HTML](75) [PDF 0KB](0)
Abstract:
The experiments reveal, for the RF filter, the out-off-band transfer property under ultra wide band (UWB) pulses is essentially in agreement with that of continous wave (CW). However, for some frequencies in the in-band of the filter, the transfer function of UWB is much larger than 1. Moreover, the oscillating property is found in the time domain response of the filter. Therefore, based on the nonlinear passive intermodulation (PIM) and the Q-value, the response mechanisms of the filter are studied. The PIM of the filter shows nonlinear effects under the two different field strengths, which results in the limited universality of measurement results. Furthermore, the signal through the filter is predicted by making use of the two measured transfer functions. The predicting results under CW pulse are smaller than the measured ones in energy and peak power. In a word the response mechanisms of the filter under UWB pulse does differ from the that under CW pulse, i. e., the measured results of CW can’t be applied for the UWB effect analysis and evaluation.
2020, 32(3): 033202.   doi: 10.11884/HPLPB202032.190402
[Abstract](41) [FullText HTML](18) [PDF 0KB](0)
Abstract:
This paper presents a high-precision Runge-Kutta (RK) method for solving transmission line equations. This method adopts high-order Taylor expansion in space, which improves the approximation accuracy of spatial differentiation. Compared with the traditional finite element time-domain method, when the number of samples per wavelength is the same, RK method has higher precision. At the same time, according to the Taylor model, researchers use RK method to solve transmission line equation in the external field excitation. The correctness and high precision of the RK method are verified by numerical examples of our study.
2020, 32(3): 035002.   doi: 10.11884/HPLPB202032.190339
[Abstract](35) [FullText HTML](16) [PDF 0KB](0)
Abstract:
Three-electrode field-distortion gas switch is a crucial element of modular fast linear transformer driver (FLTD). Electrode erosion affects the trigger jitter during the lifetime of the switch, which in turn can affect the output characteristics of FLTD. Therefore, studying the impact of electrode erosion on the trigger jitter of the switch is of great significance to optimize the switch structure and predict the switch life. This paper studies the erosion characteristic of intermediate electrode of three-electrode switch, and the electrode materials are stainless steel and brass. The key factors affecting the lifetime of switch are obtained by considering the changing rules of trigger and erosion characteristics, which provides theoretical support for the optimization of the performance of the three-electrode switch. The results show that the erosion area and surface roughness of stainless steel and brass electrodes increase with discharge times. The brass electrode is ablated more seriously and the stainless steel electrode has higher surface roughness. With the increase of discharge times, the breakdown point moves to the electrode edge area, which affects the insulation performance of the switch.
2020, 32(3): 035003.   doi: 10.11884/HPLPB202032.190300
[Abstract](45) [FullText HTML](32) [PDF 0KB](0)
Abstract:
Synchronous induction coil launcher mainly uses pulse current to supply power directly to the coil. The temperature rise of armature and coil will occur in the actual working process, and it is a major factor restricting the development of coil launcher to miniaturization and high speed. In this paper, the temperature rise model of electromagnetic coil is established. For single trigger, Comsol and self-programmed Coilgun are used to calculate, and the corresponding test platform is built to verify the temperature rise. The Comsol method with direct coupling is the most accurate method, and the change of material parameters with temperature can also be considered. The simulation results show that the temperature rise of armature is about 4.2 ℃ and the maximum temperature rise of coil is 7.7 ℃. Because of the limitation of measurement delay and sampling frequency of thermocouple temperature sensor, the armature temperature test curve can not measure the maximum temperature point in the simulation curve, it can record the temperature change curve in the whole test process. The change of temperature and the final stable temperature are basically consistent with that of the simulation. The maximum error is 6.1%, which shows the accuracy of the simulation. This study lays a foundation for subsequent multi-stage coil continuous launching.
2020, 32(3): 035006.   doi: 10.11884/HPLPB202032.190400
[Abstract](32) [FullText HTML](17) [PDF 0KB](0)
Abstract:
This paper presents the design and verification of a portable resonant voltage doubling capacitor charging power supply with an input voltage of 24 V and an output voltage of 3 kV. According to the characteristic of high voltage ratio, this power supply adopts a topology structure combining the series resonant topology and the voltage doubling rectifier, which avoids the adverse effects of excessive number of turns on the secondary side of the high frequency transformer and excessive distributed parameters. The core components such as high frequency transformer, resonant capacitor and switching device were designed and debugged. The power supply was used to conduct the capacitor charging experiment, and the test results have verified the correctness of the design.
2020, 32(3): 035007.   doi: 10.11884/HPLPB202032.190383
[Abstract](36) [FullText HTML](18) [PDF 0KB](0)
Abstract:
To improve the housing lifetime, insulation reliability and assembly consistency, the process and breakdown characteristics of a ceramic packaged multi-gap gas switch used for fast linear transformer driver (FLTD) were studied based on the multi-gap gas switch with stackable insulators and electrodes. The effects of different sealing processes on the electric field distribution of the interface between ceramic and metal were compared and analyzed, then the reasonable sealing structure was optimized. A ceramic packaged multi-gap gas switch was designed and its self-breakdown and triggering characteristics were experimentally tested. The results show that when the switch operates at the charging voltage of ±100 kV, the gas pressure of about 0.3 MPa and the peak current of 30 kA, the average delay time of 5 000 shots is 36.4 ns and the jitter is 2.8 ns. The ceramic package gas switch has the advantages on productization and maintenance-free, and will have broad application prospects in FLTD module.
2020, 37(3): 365-372.   doi: 10.7507/1001-5515.202003045
[Abstract](27) [FullText HTML](19) [PDF 2112KB](6)
Abstract:
The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major public health emergency in human history. In a short period of time, Chinese medical workers have experienced the gradual understanding, evidence accumulation and clinical practice of the unknown virus. So far, National Health Commission of the People’s Republic of China has issued seven trial versions of the “Guidelines for the Diagnosis and Treatment of COVID-19”. However, it is difficult for clinicians and laymen to quickly and accurately distinguish the similarities and differences among the different versions and locate the key points of the new version. This paper reports a computer-aided intelligent analysis method based on machine learning, which can automatically analyze the similarities and differences of different treatment plans, present the focus of the new version to doctors, reduce the difficulty in interpreting the “diagnosis and treatment plan” for the professional, and help the general public better understand the professional knowledge of medicine. Experimental results show that this method can achieve the topic prediction and matching of the new version of the program text through unsupervised learning of the previous versions of the program topic with an accuracy of 100%. It enables the computer interpretation of “diagnosis and treatment plan” automatically and intelligently.
2020, 37(3): 373-379.   doi: 10.7507/1001-5515.202004025
[Abstract](14) [FullText HTML](10) [PDF 0KB](1)
Abstract:
As the COVID-19 pandemic is intensifying globally, more and more people are pinning their hopes on the development of vaccines. At present, there are many research teams who have adopted different vaccine technology routes to develop 2019-nCoV vaccines. This article reviews and analyzes the current development and research status of 2019-nCoV vaccines in different routes, and explores their possible development in the future.
2020, 37(3): 380-388.   doi: 10.7507/1001-5515.201905072
[Abstract](18) [FullText HTML](7) [PDF 0KB](0)
Abstract:
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain stimulation technique that has been paid attention to with increasing interests as a therapeutic neural rehabilitative tool. Studies confirmed that high-frequency rTMS could improve the cognitive performance in behavioral test as well as the excitability of the neuron in animals. This study aimes to investigate the effects of rTMS on the cognition and neuronal excitability of Kunming mice during the natural aging. Twelve young mice, 12 adult mice, and 12 aged mice were used, and each age group were randomly divided into rTMS group and control group. rTMS-treated groups were subjected to high-frequency rTMS treatment for 15 days, and control groups were treated with sham stimulation for 15 days. Then, novel object recognition and step-down tests were performed to examine cognition of learning and memory. Whole-cell patch clamp technique was used to record and analyze resting membrane potential, action potential (AP), and related electrical properties of AP of hippocampal dentate gyrus (DG) granule neurons. Data analysis showed that cognition of mice and neuronal excitability of DG granule neurons were degenerated significantly as the age increased. Cognitive damage and degeneration of some electrical properties were alleviated under the condition of high-frequency rTMS. It may be one of the mechanisms of rTMS to alleviate cognitive damage and improve cognitive ability by changing the electrophysiological properties of DG granule neurons and increasing neuronal excitability.
2020, 37(3): 389-398.   doi: 10.7507/1001-5515.201907011
[Abstract](15) [FullText HTML](8) [PDF 0KB](0)
Abstract:
Anxiety disorder is a common emotional handicap, which seriously affects the normal life of patients and endangers their physical and mental health. The prefrontal cortex is a key brain region which is responsible for anxiety. Action potential and behavioral data of rats in the elevated plus maze (EPM) during anxiety (an innate anxiety paradigm) can be obtained simultaneously by using the in vivo and in conscious animal multi-channel microelectrode array recording technique. Based on maximum likelihood estimation (MLE), the action potential causal network was established, network connectivity strength and global efficiency were calculated, and action potential causal network connectivity pattern of the medial prefrontal cortex was quantitatively characterized. We found that the entries (44.13±6.99) and residence period (439.76±50.43) s of rats in the closed arm of the elevated plus maze were obviously higher than those in the open arm [16.50±3.25, P<0.001; (160.23±48.22) s,P<0.001], respectively. The action potential causal network connectivity strength (0.017 3±0.003 6) and the global efficiency (0.044 2±0.012 8) in the closed arm were both higher than those in the open arm (0.010 4±0.003 2,P<0.01; 0.034 8±0.011 4,P<0.001), respectively. The results suggest that the changes of action potential causal network in the medial prefrontal cortex are related to anxiety state. These data could provide support for the study of the brain network mechanism in prefrontal cortex during anxiety.
2020, 37(3): 399-404.   doi: 10.7507/1001-5515.201910036
[Abstract](13) [FullText HTML](4) [PDF 0KB](0)
Abstract:
Studying the ability of the brain to recognize different odors is of great significance in the assessment and diagnosis of olfactory dysfunction. The wavelet energy moment (WEM) was proposed as a feature of olfactory electroencephalogram (EEG) signal and used for odor classification. Firstly, the olfactory evoked EEG data of 13 odors were collected by an experiment. Secondly, the WEM was extracted from olfactory evoked EEG data as the signal feature, and the power spectrum density (PSD), approximate entropy, sample entropy and wavelet entropy were used as the contrast features. Finally, k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF) and decision tree classifier were used to identify different odors. The results showed that using the above four classifiers, the classification accuracy of WEM feature was higher than other features, and the k-NN classifier combined with WEM feature had the highest classification accuracy (91.07%). This paper further explored the characteristics of different EEG frequency bands, and found that most of the classification accuracy based on the features of γ band was better than that of the full band and other bands, among which the WEM feature of the γ band combined with the k-NN classifier had the highest classification accuracy (93.89 %). The research results of this paper could provide a new objective basis for the evaluation of olfactory function. On the other hand, it could also provide new ideas for the study of olfactory-induced emotions.
2020, 37(3): 405-411, 418.   doi: 10.7507/1001-5515.201905029
[Abstract](6) [FullText HTML](2) [PDF 0KB](0)
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Neuroimaging technologies have been applied to the diagnosis of schizophrenia. In order to improve the performance of the single-modal neuroimaging-based computer-aided diagnosis (CAD) for schizophrenia, an ensemble learning algorithm based on learning using privileged information (LUPI) was proposed in this work. Specifically, the extreme learning machine based auto-encoder (ELM-AE) was first adopted to learn new feature representation for the single-modal neuroimaging data. Random project algorithm was then performed on the learned high-dimensional features to generate several new feature subspaces. After that, multiple feature pairs were built among these subspaces to work as source domain and target domain, respectively, which were used to train multiple support vector machine plus (SVM+) classifier. Finally, a strong classifier is learned by combining these SVM+ classifiers for classification. The proposed algorithm was evaluated on a public schizophrenia neuroimaging dataset, including the data of structural magnetic resonance imaging (sMRI) and functional MRI (fMRI). The results showed that the proposed algorithm achieved the best diagnosis performance. In particular, the classification accuracy, sensitivity and specificity of the proposed algorithm were 72.12% ± 8.20%, 73.50% ± 15.44% and 70.93% ± 12.93%, respectively, on the sMRI data, and it also achieved the classification accuracy of 72.33% ± 8.95%, sensitivity of 68.50% ± 16.58% and specificity of 75.73% ± 16.10% on the fMRI data. The proposed algorithm overcomes the problem that the traditional LUPI methods need the additional privileged information modality as source domain. It can be directly applied to the single-modal data for classification, and also can improve the classification performance. Therefore, it suggests that the proposed algorithm will have wider applications.
2020, 37(3): 412-418.   doi: 10.7507/1001-5515.201905039
[Abstract](10) [FullText HTML](9) [PDF 0KB](0)
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Electroencephalography (EEG) signals are strongly correlated with human emotions. The importance of nodes in the emotional brain network provides an effective means to analyze the emotional brain mechanism. In this paper, a new ranking method of node importance, weighted K-order propagation number method, was used to design and implement a classification algorithm for emotional brain networks. Firstly, based on DEAP emotional EEG data, a cross-sample entropy brain network was constructed, and the importance of nodes in positive and negative emotional brain networks was sorted to obtain the feature matrix under multi-threshold scales. Secondly, feature extraction and support vector machine (SVM) were used to classify emotion. The classification accuracy was 83.6%. The results show that it is effective to use the weighted K-order propagation number method to extract the importance characteristics of brain network nodes for emotion classification, which provides a new means for feature extraction and analysis of complex networks.
2020, 37(3): 419-426.   doi: 10.7507/1001-5515.201904052
[Abstract](9) [FullText HTML](4) [PDF 0KB](0)
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Anesthesia consciousness monitoring is an important issue in basic neuroscience and clinical applications, which has received extensive attention. In this study, in order to find the indicators for monitoring the state of clinical anesthesia, a total of 14 patients undergoing general anesthesia were collected for 5 minutes resting electroencephalogram data under three states of consciousness (awake, moderate and deep anesthesia). Sparse partial least squares (SPLS) and traditional synchronized likelihood (SL) are used to calculate brain functional connectivity, and the three conscious states before and after anesthesia were distinguished by the connection features. The results show that through the whole brain network analysis, SPLS and traditional SL method have the same trend of network parameters in different states of consciousness, and the results obtained by SPLS method are statistically significant (P<0.05). The connection features obtained by the SPLS method are classified by the support vector machine, and the classification accuracy is 87.93%, which is 7.69% higher than that of the connection feature classification obtained by SL method. The results of this study show that the functional connectivity based on the SPLS method has better performance in distinguishing three kinds of consciousness states, and may provides a new idea for clinical anesthesia monitoring.
2020, 37(3): 427-433, 441.   doi: 10.7507/1001-5515.201903042
[Abstract](8) [FullText HTML](18) [PDF 0KB](1)
Abstract:
Increasing the amplitude of event-related potential is one of the key methods to improve the accuracy of the potential-based brain-computer interface, e.g., P300-based brain-computer interface. The brain-computer interface systems often use symbols or controlled objects as vision stimuli, but what visual stimuli can induce more obvious event-related potential is still unknown. This paper designed three kinds of visual stimuli, i.e., a square, an arrow, and a robot attached with an arrow, to analyze the influence of concreteness degree of the graph on the N200 and P300 potentials, and applied a support vector machine to compare the performance of the brain-computer interface under different stimuli. The results showed that, compared with the square, the robot attached with arrow and the arrow both induced larger N200 potential (P = 1.6 × 10−3, P = 4.2 × 10−2) and longer P300 potential (P = 2.2 × 10−3, P = 1.9 × 10−2) in the frontal area, but the amplitude under the arrow condition is smaller than the one under the robot attached with arrow condition. The robot attached with arrow increased the N200 potential amplitude of the square and arrow from 3.12 μV and 5.19 μV to 7.21 μV (P = 1.6 × 10−3, P = 8.9 × 10−2), and improved the accuracy rate from 59.95%, 61.67% to 74.45% (P = 2.1 × 10−2, P = 1.6 × 10−2), and the information transfer rate from 35.00 bits/min, 35.98 bits/min to 56.71 bits/min (P = 2.6 × 10−2, P = 1.6 × 10−2). This study shows that the concreteness of graphics could affect the N200 potential and the P300 potential. The abstract symbol could represent the meaning and evoke potentials, but the information contained in the concrete robot attached with an arrow is more correlated with the human experience, which is helpful to improve the amplitude. The results may provide new sight in modifying the stimulus interface of the brain-computer interface.
2020, 37(3): 434-441.   doi: 10.7507/1001-5515.201910047
[Abstract](17) [FullText HTML](11) [PDF 0KB](0)
Abstract:
Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.
2020, 37(3): 442-449.   doi: 10.7507/1001-5515.201907041
[Abstract](11) [FullText HTML](6) [PDF 0KB](0)
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This study aims to investigate the effect of substances secreted or metabolized by vascular endothelial cells on epithelial-mesenchymal transition (EMT) of hepatocellular carcinoma cells under indirect co-culture condition. Human hepatocellular carcinoma cell line QGY-7703 was cultured in vitro, and then was co-cultured with conditioned medium of human umbilical vein endothelial cells (HUVEC). The morphological changes of QGY-7703 cells were observed by inverted phase contrast microscopy. The migration ability of QGY-7703 cells was analyzed by scratch-wound assays. The effect of conditioned medium on the expression and distribution of EMT related proteins was detected by Western blot and immunofluorescence assays, respectively. The results showed that the QGY-7703 cells gradually changed from polygonal to spindle shape, the migration ability promoted significantly, and both the expression and distribution of EMT related marker changed in a time-dependent manner after co-culturing. The results confirm that vascular endothelial cells can induce EMT in hepatocellular carcinoma cells under indirect co-culture condition.
2020, 37(3): 450-459.   doi: 10.7507/1001-5515.202001052
[Abstract](5) [FullText HTML](1) [PDF 0KB](0)
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Calnexin is a lectin-like molecular chaperone protein on the endoplasmic reticulum, mediating unfolded protein responses, the endoplasmic reticulum Ca2+ homeostasis, and Ca2+ signals conduction. In recent years, studies have found that calnexin plays a key role in the heart diseases. This study aims to explore the role of calnexin in the activation of cardiac fibroblasts. A transverse aortic constriction (TAC) mouse model was established to observe the activation of cardiac fibroblasts in vivo, and the in vitro cardiac fibroblasts activation model was established by transforming growth factor β1 (TGFβ1) stimulation. The adenovirus was respectively used to gene overexpression and silencing calnexin in cardiac fibroblasts to elucidate the relationship between calnexin and cardiac fibroblasts activation, as well as the possible underlying mechanism. We confirmed the establishment of TAC model by echocardiography, hematoxylin-eosin, Masson, and Sirius red staining, and detecting the expression of cardiac fibrosis markers in cardiac tissues. After TGFβ1 stimulation, markers of the activation of cardiac fibroblast, and proliferation and migration of cardiac fibroblast were detected by quantitative PCR, Western blot, EdU assay, and wound healing assay respectively. The results showed that the calnexin expression was reduced in both the TAC mice model and the activated cardiac fibroblasts. The overexpression of calnexin relieved cardiac fibroblasts activation, in contrast, the silencing of calnexin promoted cardiac fibroblasts activation. Furthermore, we found that the endoplasmic reticulum stress was activated during cardiac fibroblasts activation, and endoplasmic reticulum stress was relieved after overexpression of calnexin. Conversely, after the silencing of calnexin, endoplasmic reticulum stress was further aggravated, accompanying with the activation of cardiac fibroblasts. Our data suggest that the overexpression of calnexin may prevent cardiac fibroblasts against activation by alleviating endoplasmic reticulum stress.
2020, 37(3): 460-468, 479.   doi: 10.7507/1001-5515.201908008
[Abstract](11) [FullText HTML](9) [PDF 0KB](0)
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In order to explore the effect of Sipunculus nudus extract (SNE) on skin wound healing in mice and its mechanism, hemostasis effect of SNE was measured, the mouse skin wound model was established by full-thickness excision. The morphological changes of the wound were observed after the treatment with SNE and the healing rate was measured. The changes of wound histology were observed by hematoxylin eosin (HE) staining, Masson staining and transmission electron microscope (TEM). The expression of cell factors and related proteins was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Results showed that the SNE possessed hemostatic function. SNE could obviously improve the healing rate of wound in mouse and shorten time of scab removal compared with the none-treatment (NT) group (P < 0.05).The pathological histology analysis results showed complete epidermal regeneration, with remarkable capillary and collagen fiber observed in the SNE group. The expression level of tumor necrosis factor-α (TNF -α), interleukin-1β (IL-1β) and transforming growth factor-β1 (TGF-β1) in SNE group was significantly lower than that of the NT group on 7 d ( P < 0.05). Moreover, compared with the NT group, the gene expressions level of Smad7 was significantly increased and the level of type II TGF-β receptors (TGF-βRII), collagen I (COL1A1) and α-smooth muscle actin (α-SMA) were significantly reduced in the SNE group on 28 d ( P < 0.05), but the difference was not statistically significant compared to Yunnanbaiyao group (PC group) ( P > 0.05). These results indicated that SNE possessed obvious activity of accelerating wound healing and inhibiting scar formation, and its mechanism was closely related to hemostatic function, regulation of inflammatory factors, collagen deposition, collagen fiber remodeling and intervening TGF-β/Smads signal pathway. Therefore, SNE may have promising clinical applications in skin wound repair and scar inhibition.
2020, 37(3): 469-479.   doi: 10.7507/1001-5515.202004064
[Abstract](8) [FullText HTML](10) [PDF 0KB](0)
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Tripartite motif 5 (TRIM5) plays a significant function in autophagy and involves in immune and tumor processes. While the function of TRIM5 remains poorly understood in glioma. We purpose to evaluate the possible prognostic role of TRIM5 in glioma via bioinformatics analyses. The database clinical samples of glioma in this study included low grade glioma (LGG) and glioblastoma multiforme (GBM). TRIM5 expression in glioma tissues were explored in Oncomine, GEPIA and The Cancer Genome Atlas (TCGA) databases. Survival analysis and the multivariate Cox regression analysis of TRIM5 based on TCGA were used to evaluate the prognostic role of TRIM5. The protein networks of TRIM5 was detected by STRING database. KEGG enrichment analyses were performed to predict the potential molecular pathways of TRIM5 in glioma. In addition, immune infiltration analysis was conducted by CIBERSORT and TIMER databases. We found that TRIM5 was strongly increased in glioma samples compared with normal samples in Oncomine, GEPIA and TCGA databases. Higher TRIM5 was significantly contributed to worse overall survival (OS) in LGG+GBM patients and LGG patients, while was no correlated with OS of GBM patients. Interaction networks analysis identified that IRF3, IRF7, OAS1, OAS2, OAS3, OASL, GBP1, PML, BTBD1 and BTBD2 proteins were contacted with TRIM5. Moreover, KEGG revealed that apoptosis and cancer- and immune-related pathways were enriched with elevated TRIM5. Specifically, TRIM5 could influence the immune infiltration levels, such as activated NK cells, monocytes, activated mast cells and macrophages in glioma. In conclusion, our data indicated that TRIM5 was upregulated in glioma tissues and associated with poor prognosis and immune infiltration. TRIM5 may be acted as a biomarker in prognosis and immunotherapy guidance of glioma.
2020, 37(3): 480-486.   doi: 10.7507/1001-5515.201905062
[Abstract](3) [FullText HTML](2) [PDF 0KB](0)
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The study aims to investigate whether there is difference in pre-treatment white matter parameters in treatment-resistant and treatment-responsive schizophrenia. Diffusion tensor imaging (DTI) was acquired from 60 first-episode drug-naïve schizophrenia (39 treatment-responsive and 21 treatment-resistant schizophrenia patients) and 69 age- and gender-matched healthy controls. Imaging data was preprocessed via FSL software, then diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted. Besides, structural network matrix was constructed based on deterministic fiber tracking. The differences of diffusion parameters and topology attributes between three groups were analyzed using analysis of variance (ANOVA). Compared with healthy controls, treatment-responsive schizophrenia showed altered white matter mainly in anterior thalamus radiation, splenium of corpus callosum, cingulum bundle as well as superior longitudinal fasciculus. While treatment-resistant schizophrenia patients showed white matter abnormalities in anterior thalamus radiation, cingulum bundle, fornix and pontine crossing tract relative to healthy controls. Treatment-resistant schizophrenia showed more severe white matter abnormalities in anterior thalamus radiation compared with treatment-responsive patients. There was no significant difference in white matter network topological attributes among the three groups. The performance of support vector machine (SVM) showed accuracy of 63.37% in separating the two patient subgroups (P = 0.04). In this study, we showed different patterns of white matter alterations in treatment-responsive and treatment-resistant schizophrenia compared with healthy controls before treatment, which may help guiding patient identification, targeted treatment and prognosis improvement at baseline drug-naïve state.
2020, 37(3): 487-495, 501.   doi: 10.7507/1001-5515.201910005
[Abstract](7) [FullText HTML](10) [PDF 0KB](0)
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Atrial fibrillation (AF) is the most common arrhythmia in clinic, which can cause hemodynamic changes, heart failure and stroke, and seriously affect human life and health. As a self-promoting disease, the treatment of AF can become more and more difficult with the deterioration of the disease, and the early prediction and intervention of AF is the key to curbing the deterioration of the disease. Based on this, in this study, by controlling the dose of acetylcholine, we changed the AF vulnerability of five mongrel dogs and tried to assess it by analyzing the electrophysiology of atrial epicardium under different states of sinus rhythm. Here, indices from four aspects were proposed to study the atrial activation rule. They are the variability of atrial activation rhythm, the change of the earliest atrial activation, the change of atrial activation delay and the left-right atrial dyssynchrony. By using binary logistic regression analysis, multiple indices above were transformed into the AF inducibility, which were used to classify the signals during sinus rhythm. The sensitivity, specificity and accuracy of classification reached 85.7%, 95.8% and 91.7%, respectively. As the experimental results show, the proposed method has the ability to assess the AF vulnerability of atrium, which is of great clinical significance for the early prediction and intervention of AF.
2020, 37(3): 496-501.   doi: 10.7507/1001-5515.201911064
[Abstract](16) [FullText HTML](6) [PDF 0KB](0)
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In this article, based on z-curve theory and position weight matrix (PWM), a model for nucleosome sequences was constructed. Nucleosome sequence dataset was transformed into three-dimensional coordinates, PWM of the nucleosome sequences was calculated and the similarity score was obtained. After integrating them, a nucleosome feature model based on the comprehensive DNA sequences was obtained and named CSeqFM. We calculated the Euclidean distance between nucleosome sequence candidates or linker sequences and CSeqFM model as the feature dataset, and put the feature datasets into the support vector machine (SVM) for training and testing by ten-fold cross-validation. The results showed that the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of identifying nucleosome positioning for S. cerevisiae were 97.1%, 96.9%, 94.2% and 0.89, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.980 1. Compared with another z-curve method, it was found that our method had better identifying effect and each evaluation performance showed better superiority. CSeqFM method was applied to identify nucleosome positioning for other three species, including C. elegans, H. sapiens and D. melanogaster. The results showed that AUCs of the three species were all higher than 0.90, and CSeqFM method also showed better stability and effectiveness compared with iNuc-STNC and iNuc-PseKNC methods, which is further demonstrated that CSeqFM method has strong reliability and good identification performance.
2020, 37(3): 502-511.   doi: 10.7507/1001-5515.201906025
[Abstract](11) [FullText HTML](7) [PDF 0KB](0)
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Brain-controlled wheelchair (BCW) is one of the important applications of brain-computer interface (BCI) technology. The present research shows that simulation control training is of great significance for the application of BCW. In order to improve the BCW control ability of users and promote the application of BCW under the condition of safety, this paper builds an indoor simulation training system based on the steady-state visual evoked potentials for BCW. The system includes visual stimulus paradigm design and implementation, electroencephalogram acquisition and processing, indoor simulation environment modeling, path planning, and simulation wheelchair control, etc. To test the performance of the system, a training experiment involving three kinds of indoor path-control tasks is designed and 10 subjects were recruited for the 5-day training experiment. By comparing the results before and after the training experiment, it was found that the average number of commands in Task 1, Task 2, and Task 3 decreased by 29.5%, 21.4%, and 25.4%, respectively (P < 0.001). And the average number of commands used by the subjects to complete all tasks decreased by 25.4% ( P < 0.001). The experimental results show that the training of subjects through the indoor simulation training system built in this paper can improve their proficiency and efficiency of BCW control to a certain extent, which verifies the practicability of the system and provides an effective assistant method to promote the indoor application of BCW.
2020, 37(3): 512-518, 526.   doi: 10.7507/1001-5515.201812051
[Abstract](6) [FullText HTML](8) [PDF 0KB](0)
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Masticatory robots have a broad application prospect in the field of denture material tests and mandible rehabilitation. Mechanism type of temporomandibular joint structure is an important factor influencing the performance of the masticatory robot. In view of the wide application of elastic components in the field of the biomimetic robot, an elastic component was adopted to simulate the buffering characteristics of the temporomandibular joint disc and formed the elastic temporomandibular joint structure on the basis of point-contact high pair. Secondly, the influences of the elastic temporomandibular joint structure (on mechanism degree, kinematics, dynamics, etc.) were discussed. The position and velocity of the temporomandibular joint were analyzed based on geometric constraints of the joint surface, and the dynamic analysis based on the Lagrange equation was carried out. Finally, the influence of the preload and stiffness of the elastic component was analyzed by the response surface method. The results showed that the elastic temporomandibular joint structure could effectively guarantee the flexible movement and stable force of the joint. The elastic joint structure proposed in this paper further improves the biomimetic behavior of masticatory robots. It provides new ideas for the biomimetic design of viscoelastic joint discs.
2020, 37(3): 519-526.   doi: 10.7507/1001-5515.201909040
[Abstract](8) [FullText HTML](4) [PDF 0KB](1)
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The number of white blood cells in the leucorrhea microscopic image can indicate the severity of vaginal inflammation. At present, the detection of white blood cells in leucorrhea mainly relies on manual microscopy by medical experts, which is time-consuming, expensive and error-prone. In recent years, some studies have proposed to implement intelligent detection of leucorrhea white blood cells based on deep learning technology. However, such methods usually require manual labeling of a large number of samples as training sets, and the labeling cost is high. Therefore, this study proposes the use of deep active learning algorithms to achieve intelligent detection of white blood cells in leucorrhea microscopic images. In the active learning framework, a small number of labeled samples were firstly used as the basic training set, and a faster region convolutional neural network (Faster R-CNN) training detection model was performed. Then the most valuable samples were automatically selected for manual annotation, and the training set and the corresponding detection model were iteratively updated, which made the performance of the model continue to increase. The experimental results show that the deep active learning technology can obtain higher detection accuracy under less manual labeling samples, and the average precision of white blood cell detection could reach 90.6%, which meets the requirements of clinical routine examination.
2020, 37(3): 527-532, 540.   doi: 10.7507/1001-5515.201909044
[Abstract](8) [FullText HTML](10) [PDF 0KB](0)
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Total lumbar disc replacement is an alternative to interbody fusion for the effective treatment of symptomatic degenerative disc disease. This paper reviewed the history of ball-on-socket type artificial lumbar disc (ALD) prosthesis, which is a typical ALD prosthesis and summarized the ALD prosthesis research progress, according to different materials such as metal-on-metal, metal-on-polymer, and polymer-on-polymer prosthesis. The structural design factors of ball-on-socket type ALD prosthesis were analyzed and its prospect of development was also presented. The purpose of this paper is to provide a theoretical reference for the design of the ball-on-socket ALD prosthesis by reviewing the current state of ball-on-socket type ALD prosthesis.
2020, 37(3): 533-540.   doi: 10.7507/1001-5515.201906067
[Abstract](6) [FullText HTML](4) [PDF 0KB](0)
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With the rapid development of network structure, convolutional neural networks (CNN) consolidated its position as a leading machine learning tool in the field of image analysis. Therefore, semantic segmentation based on CNN has also become a key high-level task in medical image understanding. This paper reviews the research progress on CNN-based semantic segmentation in the field of medical image. A variety of classical semantic segmentation methods are reviewed, whose contributions and significance are highlighted. On this basis, their applications in the segmentation of some major physiological and pathological anatomical structures are further summarized and discussed. Finally, the open challenges and potential development direction of semantic segmentation based on CNN in the area of medical image are discussed.
2020, 37(3): 541-548.   doi: 10.7507/1001-5515.201908044
[Abstract](15) [FullText HTML](4) [PDF 0KB](0)
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Changes in the intrinsic characteristics of brain neural activities can reflect the normality of brain functions. Therefore, reliable and effective signal feature analysis methods play an important role in brain dysfunction and relative diseases early stage diagnosis. Recently, studies have shown that neural signals have nonlinear and multi-scale characteristics. Based on this, researchers have developed the multi-scale entropy (MSE) algorithm, which is considered more effective when analyzing multi-scale nonlinear signals, and is generally used in neuroinformatics. The principles and characteristics of MSE and several improved algorithms base on disadvantages of MSE were introduced in the article. Then, the applications of the MSE algorithm in disease diagnosis, brain function analysis and brain-computer interface were introduced. Finally, the challenges of these algorithms in neural signal analysis will face to and the possible further investigation interests were discussed.
2020, 37(3): 365-372.   doi: 10.7507/1001-5515.202003045
[Abstract](27) [FullText HTML](19) [PDF 2112KB](19)
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The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major public health emergency in human history. In a short period of time, Chinese medical workers have experienced the gradual understanding, evidence accumulation and clinical practice of the unknown virus. So far, National Health Commission of the People’s Republic of China has issued seven trial versions of the “Guidelines for the Diagnosis and Treatment of COVID-19”. However, it is difficult for clinicians and laymen to quickly and accurately distinguish the similarities and differences among the different versions and locate the key points of the new version. This paper reports a computer-aided intelligent analysis method based on machine learning, which can automatically analyze the similarities and differences of different treatment plans, present the focus of the new version to doctors, reduce the difficulty in interpreting the “diagnosis and treatment plan” for the professional, and help the general public better understand the professional knowledge of medicine. Experimental results show that this method can achieve the topic prediction and matching of the new version of the program text through unsupervised learning of the previous versions of the program topic with an accuracy of 100%. It enables the computer interpretation of “diagnosis and treatment plan” automatically and intelligently.
2020, 33(3): 371-375.   doi: 10.1063/1674-0068/cjcp1907142
[Abstract](13) [FullText HTML](11) [PDF 10521KB](11)
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One simple and environmental friendly synthesis strategy for preparing low-cost magnetic Fe$_3$C@C materials has been facilely developed using a modified sol-gel approach, wherein natural magnetite acted as the iron source. A chelating polycarboxylic acid such as citric acid (CA) was employed as the carbon source, and it dissolved Fe very effectively, Fe$_3$O$_4$ and natural magnetite to composite an iron-citrate complex with the assistance of ammonium hydroxide. The core-shell structure of the as-prepared nanocomposites was formed directly by high-temperature pyrolysis. The Fe$_3$C@C materials exhibited superparamagnetic properties (38.09 emu/mg), suggesting potential applications in biomedicine, environment, absorption, catalysis, etc.