Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect

Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied, their influence on Parkinson's disease (PD) has yet to be well explored. By virtue of the magnetic flux variable, this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal ganglia. We find: (i) The network reproduces five typical waveforms corresponding to the severity of symptoms: weak cluster, episodic, continuous cluster, episodic, and continuous wave. (ii) Magnetic induction is a double-edged sword for the treatment of PD. Although the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity, it also can regulate the pathological intensity firing activity with excessive β-band power transferring to the physiological firing pattern with weak β-band power. (iii) External magnetic radiation could inhibit continuous tremulous firing and β-band power of subthalamic nucleus (STN), which means the severity of symptoms weakened. Especially, the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological oscillation. This work helps to understand the firing activity of the subthalamopallidal network under electromagnetic effect. It may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity.     

椭球粒子声辐射力计算及分析

针对水下椭球粒子,以声散射理论为基础,采用分波序列的方法,建立了椭球粒子声辐射力的理论计算模型。进而根据声辐射力计算公式,以刚性椭球粒子和液体椭球粒子为例,计算并分析不同Bessel波束作用下椭球粒子的轴向声辐射力函数特征。数值仿真计算结果表明,对于刚性椭球粒子,扁平椭球粒子相对于细长椭球粒子更有助于激发负声辐射力；对于液体椭球粒子,细长椭球粒子相对于扁平椭球粒子更加容易产生负声辐射力；对于不同介质的椭球粒子,不同的入射波束激发的负声辐射力的效果也存在明显的差异。该结果为复杂的尺寸和介质粒子声操控技术提供了理论的可行性。     

Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

The accurate prediction of the solar diffuse fraction (DF), sometimes called the diffuse ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse irradiance research is discussed and then three robust, machine learning (ML) models are examined using a large dataset (almost eight years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid adaptive network-based fuzzy inference system (ANFIS), a single multi-layer perceptron (MLP) and a hybrid multi-layer perceptron grey wolf optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various solar and DF irradiance data, from Spain. The results were then evaluated using frequently used evaluation criteria, the mean absolute error (MAE), mean error (ME) and the root mean square error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance in both the training and the testing procedures.     

Accurate correction of arbitrary spin fermion quantum tunneling from non-stationary Kerr-de Sitter black hole based on corrected Lorentz dispersion relation

According to a corrected dispersion relation proposed in the study on the string theory and quantum gravity theory, the Rarita-Schwinger equation was precisely modified, which resulted in the Rarita-Schwinger-Hamilton-Jacobi equation. Using this equation, the characteristics of arbitrary spin fermion quantum tunneling radiation from non-stationary Kerr-de Sitter black holes were determined. A number of accurately corrected physical quantities, such as surface gravity, chemical potential, tunneling probability, and Hawking temperature, which describe the properties of black holes, were derived. This research has enriched the research methods and enabled increased precision in black hole physics research.     

Switching of heating and cooling modes using thermal radiation films

We study emissivity (ε)-dependent radiative heat transfer phenomena in remote and contact configurations. To demonstrate the emissivity-dependent radiative heating mode in a remote configuration, we fabricated miniature greenhouses covered with low (0.34)- and high-ε (0.86) polyethylene films and monitored temperatures on the floors, insides, and covers of the greenhouses during 24 h. The high-ε greenhouse yielded a 9-°C increase in floor temperature relative to the low-ε greenhouse at a one-sun solar irradiance because the high-ε film effectively trapped floor radiation. In contrast, the cover temperature remained lower in the high-ε greenhouse due to intensified radiation released from the high-ε film. This self-cooling effect was more evident when an emissive film was in physical contact with an object. While bare copper heated up to 55 °C, a high-ε film coated copper substrate was kept cooler by 4 and 2 °C compared with the bare and low-ε film coated copper samples, respectively.     

DIOPTAS: a program for reduction of two-dimensional X-ray diffraction data and data exploration

The amount of data collected during synchrotron X-ray diffraction (XRD) experiments is constantly increasing. Most of the time, the data are collected with image detectors, which necessitates the use of image reduction/integration routines to extract structural information from measured XRD patterns. This step turns out to be a bottleneck in the data processing procedure due to a lack of suitable software packages. In particular, fast-running synchrotron experiments require online data reduction and analysis in real time so that experimental parameters can be adjusted interactively. Dioptas is a Python-based program for on-the-fly data processing and exploration of two-dimensional X-ray diffraction area detector data, specifically designed for the large amount of data collected at XRD beamlines at synchrotrons. Its fast data reduction algorithm and graphical data exploration capabilities make it ideal for online data processing during XRD experiments and batch post-processing of large numbers of images.     

Radiation damage in polymer films from grazing‐incidence X‐ray scattering measurements

Grazing‐incidence X‐ray scattering (GIXS) is widely used to analyze the crystallinity and nanoscale structure in thin polymer films. However, ionizing radiation will generate free radicals that initiate crosslinking and/or chain scission, and structural damage will impact the ordering kinetics, thermodynamics, and crystallinity in many polymers. We report a simple methodology to screen for beam damage that is based on lithographic principles: films are exposed to patterns of X‐ray radiation, and changes in polymer structure are revealed by immersing the film in a solvent that dissolves the shortest chains. The experiments are implemented with high throughput using the standard beam line instrumentation and a typical GIXS configuration. The extent of damage (at a fixed radiation dose) depends on a range of intrinsic material properties and experimental variables, including the polymer chemistry and molecular weight, exposure environment, film thickness, and angle of incidence. The solubility switch for common polymers is detected within 10–60 s at ambient temperature, and we verified that this first indication of damage corresponds with the onset of network formation in glassy polystyrene and a loss of crystallinity in polyalkylthiophenes. Therefore, grazing‐incidence X‐ray “patterning” offers an efficient approach to determine the appropriate data acquisition times for any GIXS experiment. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 1074–1086     

MHD flow and heat transfer of a hybrid nanofluid past a permeable stretching/shrinking wedge

The steady flow and heat transfer of a hybrid nanofluid past a permeable stretching/shrinking wedge with magnetic field and radiation effects are studied. The governing equations of the hybrid nanofluid are converted to the similarity equations by techniques of the similarity transformation. The bvp4c function that is available in MATLAB software is utilized for solving the similarity equations numerically. The numerical results are obtained for selected different values of parameters. The results discover that two solutions exist, up to a certain value of the stretching/shrinking and suction strengths. The critical value in which the solution is in existence decreases as nanoparticle volume fractions for copper and wedge angle parameter increase. It is also found that the hybrid nanofluid enhances the heat transfer rate compared with the regular nanofluid. The reduction of the heat transfer rate is observed with the increase in radiation parameter. The temporal stability analysis is performed to analyze the stability of the dual solutions, and it is revealed that only one of them is stable and physically reliable.     

表面效应对铁<100>间隙型位错环的影响

在材料辐照损伤过程中,间隙型位错环的形成及动力学行为严重影响材料在辐照条件下的服役行为.在常用的以体心立方铁为基的合金材料中,1/2<111>和<100>是两种主要的位错环,其对辐照损伤的影响一直都是核材料领域研究的热点之一.在之前的研究中,人们对{111}面与单个1/2<111>位错环的相互作用进行了深入研究,发现表面对位错环性质确实有重要的影响.采用分子动力学方法,在原子尺度详细研究了另一个重要的表面铁{100}面对<100>间隙型位错环动力学过程的影响.模拟发现位错环伯格斯矢量与表面法线方向的关系、距表面的深度、位错环之间的相互作用以及温度等,都对位错环与表面的相互作用产生重要影响,其中,表面作用下的伯格斯矢量的演化以及<100>位错环在此过程中的一维运动首次被发现.基于这些模拟结果,就<100>位错环对表面辐照损伤结构的影响进行详细地研究,给出<100>位错环对表面凹凸结构的贡献,这些结果为理解辐照过程中材料表面的演化提供一种可能的解释.     

质子辐照硼硅酸盐玻璃盖片的物理效应分析

作为航天器电源系统的重要组成部分,太阳电池需要更高的转换效率和可靠性以及更长的使用寿命。通过在太阳电池表面覆盖抗辐照玻璃盖片,可以增强太阳电池对粒子辐射的防护,延长太阳电池的服役寿命,使航天器获得可靠的能源供应。硼硅酸盐玻璃就是一种理想的太阳电池玻璃盖片材料。采用蒙特卡罗方法,结合SRIM软件模拟研究质子辐照硼硅酸盐玻璃的损伤物理机理。基于粒子与物质相互作用的理论以及基本公式,通过分析不同入射能量的质子在硼硅酸盐玻璃中的阻止本领、电离能损、位移能损、空位的产生情况,对辐照损伤的物理机制进行研究。结果表明:能量为30~120 keV的质子辐照损伤主要发生在硼硅酸盐玻璃表面;质子沉积、空位分布等均为Bragg峰型分布;电离能损是能量损失的主要部分,随入射能量的增加而增大,导致电子的电离和激发;位移能损在玻璃内部随能量降低而增大,导致硼、氧和硅等空位缺陷的产生;电离效应和缺陷的产生是硼硅酸盐玻璃色心形成的重要原因。