On the loss mechanisms of radiation belt electron dropouts during the 12 September 2014 geomagnetic storm

Radiation belt electron dropouts indicate electron flux decay to the background level during geomagnetic storms,which is commonly attributed to the effects of wave-induced pitch angle scattering and magnetopause shadowing.To investigate the loss mechanisms of radiation belt electron dropouts triggered by a solar wind dynamic pressure pulse event on 12 September 2014,we comprehensively analyzed the particle and wave measurements from Van Allen Probes.The dropout event was divided into three periods:before the storm,the initial phase of the storm,and the main phase of the storm.The electron pitch angle distributions(PADs)and electron flux dropouts during the initial and main phases of this storm were investigated,and the evolution of the radial profile of electron phase space density(PSD)and the(μ,K)dependence of electron PSD dropouts(whereμ,K,and L^*are the three adiabatic invariants)were analyzed.The energy-independent decay of electrons at L>4.5 was accompanied by butterfly PADs,suggesting that the magnetopause shadowing process may be the major loss mechanism during the initial phase of the storm at L>4.5.The features of electron dropouts and 90°-peaked PADs were observed only for>1 MeV electrons at L<4,indicating that the wave-induced scattering effect may dominate the electron loss processes at the lower L-shell during the main phase of the storm.Evaluations of the(μ,K)dependence of electron PSD drops and calculations of the minimum electron resonant energies of H+-band electromagnetic ion cyclotron(EMIC)waves support the scenario that the observed PSD drop peaks around L^*=3.9 may be caused mainly by the scattering of EMIC waves,whereas the drop peaks around L^*=4.6 may result from a combination of EMIC wave scattering and outward radial diffusion.

Investigation of transport properties of perovskite single crystals by pulsed and DC bias transient current technique

Time-of-flight(ToF)transient current method is an important technique to study the transport characteristics of semiconductors.Here,both the direct current(DC)and pulsed bias ToF transient current method are employed to investigate the transport properties and electric field distribution inside the MAPbI_(3) single crystal detector.Owing to the almost homogeneous electric field built inside the detector during pulsed bias ToF measurement,the free hole mobility can be directly calculated to be about 22 cm^(2)·V^(-1)·s^(-1),and the hole lifetime is around 6.5μs–17.5μs.Hence,the mobility-lifetime product can be derived to be 1.4×10^(-4)cm^(2)·V^(-1)–3.9×10^(-4)cm^(2)·V^(-1).The transit time measured under the DC bias deviates with increasing voltage compared with that under the pulsed bias,which arises mainly from the inhomogeneous electric field distribution inside the perovskite.The positive space charge density can then be deduced to increase from 3.1×10^(10)cm^(-3)to 6.89×10^(10)cm^(-3)in a bias range of 50 V–150 V.The ToF measurement can provide us with a facile way to accurately measure the transport properties of the perovskite single crystals,and is also helpful in obtaining a rough picture of the internal electric field distribution.

An Effective Density Based Approach to Detect Complex Data Clusters Using Notion of Neighborhood Difference

The density based notion for clustering approach is used widely due to its easy implementation and ability to detect arbitrary shaped clusters in the presence of noisy data points without requiring prior knowledge of the number of clusters to be identified. Density-based spatial clustering of applications with noise （DBSCAN） is the first algorithm proposed in the literature that uses density based notion for cluster detection. Since most of the real data set, today contains feature space of adjacent nested clusters, clearly DBSCAN is not suitable to detect variable adjacent density clusters due to the use of global density parameter neighborhood radius Y,.ad and minimum number of points in neighborhood Np~,. So the efficiency of DBSCAN depends on these initial parameter settings, for DBSCAN to work properly, the neighborhood radius must be less than the distance between two clusters otherwise algorithm merges two clusters and detects them as a single cluster. Through this paper： 1） We have proposed improved version of DBSCAN algorithm to detect clusters of varying density adjacent clusters by using the concept of neighborhood difference and using the notion of density based approach without introducing much additional computational complexity to original DBSCAN algorithm. 2） We validated our experimental results using one of our authors recently proposed space density indexing （SDI） internal cluster measure to demonstrate the quality of proposed clustering method. Also our experimental results suggested that proposed method is effective in detecting variable density adjacent nested clusters.

Experimental study on the space charge properties in haze events

In recent years,haze has posed a serious threat to the global climate change,ecological balance and human health.In this study,the laboratory experiments and field observations were performed and a possible charging mechanism was proposed to investigate the space charge properties in haze events.The laboratory experiments showed that the charge polarity of primary aerosol is determined by species of combustion fuels while the magnitude is dependent on the combustion completeness.The field observations revealed that the space charge of atmosphere aerosol in haze events differs from that of fair weather and is closely related to PM2.5 concentration when Relative Humidity(RH)<60%,with 1 to 2 orders of magnitude less than the case when RH≥60%.The analysis of equivalent chargeto-mass ratio(ECTM)suggested that in haze events the space charge is governed by primary aerosol emitted by combustion of fossil fuel in a low relative humidity,whereas it is manipulated by the secondary chemical reaction of atmosphere aerosol in a high relative humidity.And we can identify the main pollutants in haze events according to the polarity of atmosphere aerosol and quickly take measures when RH<60%.Accordingly,the dusthaze of RH<80% can be divided into dry-dust-haze when RH<60%and wet-dust-haze when 60%≤RH<80%.Our study firstly elucidated the space charge properties of atmosphere aerosol in haze events and can provide a new perspective for the prevention and control of air pollution.

Electron densitymap evaluation functions for determining the quality of protein crystal structures

Background Finding methods to judge the quality of X-ray crystallographic information is an active research topic.The quality of electron density maps reconstructed by Fourier transform is always limited by the finite resolution,the amplitude/phase error and the completeness of diffraction data.At present,the R value and effective resolution are common ways of evaluating the quality of electron density maps.Unfortunately,the current evaluation methods are only dependent on diffraction amplitude,without any phase information.Methods Advanced evaluation functions in real space are designed to estimate the electron density map quality.The electron density map definition evaluation function relies on the atomicity of the electron density distribution.We use the power spectrum electron density entropy in protein crystallography for the first time.These two functions include both structure factor amplitudes and phases via the Fourier transform of electron density map.Results We carry out tests on synthetic data sets of known structures,varying the resolution and error,and draw the quality curves of electron density maps with theoretical,noisy and experimental diffraction data by two evaluation functions at different resolutions.The curves reveal the optimum structure and resolution of proteins clearly.Conclusions The work presented here offers new methods to evaluate the qualities of the electron density maps of proteins with slight differences,and brand new indicators to select the optimum diffraction resolution of protein structures.