Quantifying the Effect of Non-Larmor Motion of Electrons on the Pressure Tensor

In space plasma, various effects of magnetic reconnection and turbulence cause the electron motion to significantly deviate from their Larmor orbits. Collectively these orbits affect the electron velocity distribution function and lead to the appearance of the "non-gyrotropic" elements in the pressure tensor. Quantification of this effect has important applications in space and laboratory plasma, one of which is tracing the electron diffusion region (EDR) of magnetic reconnection in space observations. Three different measures of agyrotropy of pressure tensor have previously been proposed, namely, $A\varnothing_e$, $D_{ng}$ and $Q$. The multitude of contradictory measures has caused confusion within the community. We revisit the problem by considering the basic properties an agyrotropy measure should have. We show that $A\varnothing_e$, $D_{ng}$ and $Q$ are all defined based on the sum of the principle minors (i.e. the rotation invariant $I_2$) of the pressure tensor. We discuss in detail the problems of $I_2$-based measures and explain why they may produce ambiguous and biased results. We introduce a new measure $AG$ constructed based on the determinant of the pressure tensor (i.e. the rotation invariant $I_3$) which does not suffer from the problems of $I_2$-based measures. We compare $AG$ with other measures in 2 and 3-dimension particle-in-cell magnetic reconnection simulations, and show that $AG$ can effectively trace the EDR of reconnection in both Harris and force-free current sheets. On the other hand, $A\varnothing_e$ does not show prominent peaks in the EDR and part of the separatrix in the force-free reconnection simulations, demonstrating that $A\varnothing_e$ does not measure all the non-gyrotropic effects in this case, and is not suitable for studying magnetic reconnection in more general situations other than Harris sheet reconnection.Comment: accepted by Phys. of Plasm

Quantification of effects of climate variations and human activities on runoff by a monthly water balance model: A case study of the Chaobai River basin in northern China

The Chaobai River basin in northern China consists of two major tributaries, the Chao River and Bai River. Monthly observations of precipitation, streamfiow, and panevaporation data are available for 35 years (1961-1966 and 1973-2001). Using the annual time series of the observed streamfiow, one break point at 1979 is detected and is adopted to divide the data set into two study periods, the "before" and "after" periods marking the onset of significant anthropogenic alteration of the flow (reservoirs and silt retention dams, five times increase in population) and significant changes in land use (conversion to terraced fields versus sloping fields). The distributed time-variant gain model (DTVGM) was used to evaluate the water resources of the area. Furthermore, the Bayesian method used by Engeland et al. (2005) was used in this paper to evaluate two uncertainty sources (i.e., the model parameter and model structure) and for assessing the DTVGM's performance over the Chaobai River basin. Comparing the annual precipitation means over 13 years (1961-1966 and 1973-1979), the means of the second period (1980-2001) decreased by 5.4% and 4.9% in the Chao River and Bai River basins, respectively. However, the related annual runoff decreased by 40.3% and 52.8%, respectively, a much greater decline than exhibited by precipitation. Through the monthly model simulation and the fixing-changing method, it is determined that decreases in runoff between the two periods can be attributed to 35% (31%) from climate variations and 68% (70%) from human activities in the Chao River (Bai River). Thus, human impact exerts a dominant influence upon runoff decline in the Chaobai River basin compared to climate. This study enhances our understanding of the relative roles of climate variations and human activities on runoff. © 2009 by the American Geophysical Union.published_or_final_versio

Optical Interferometry of early-type stars with PAVO@CHARA. I. Fundamental stellar properties

We present interferometric observations of 7 main-sequence and 3 giant stars with spectral types from B2 to F6 using the PAVO beam combiner at the CHARA array. We have directly determined the angular diameters for these objects with an average precision of 2.3%. We have also computed bolometric fluxes using available photometry in the visible and infrared wavelengths, as well as space-based ultraviolet spectroscopy. Combined with precise \textit{Hipparcos} parallaxes, we have derived a set of fundamental stellar properties including linear radius, luminosity and effective temperature. Fitting the latter to computed isochrone models, we have inferred masses and ages of the stars. The effective temperatures obtained are in good agreement (at a 3% level) with nearly-independent temperature estimations from spectroscopy. They validate recent sixth-order polynomial (B-V)-$T_\mathrm{eff}$ empirical relations \citep{Boyajian2012a}, but suggest that a more conservative third-order solution \citep{vanBelle2009} could adequately describe the (V-K)-$T_\mathrm{eff}$ relation for main-sequence stars of spectral type A0 and later. Finally, we have compared mass values obtained combining surface gravity with inferred stellar radius (\textit{gravity mass}) and as a result of the comparison of computed luminosity and temperature values with stellar evolutionary models (\textit{isochrone mass}). The strong discrepancy between isochrone and gravity mass obtained for one of the observed stars, $\gamma$\,Lyr, suggests that determination of the stellar atmosphere parameters should be revised.Comment: 13 pages, 9 figures, accepted for publication in MNRA

Extraction of Principle Knowledge from Process Patents for Manufacturing Process Innovation

Process patents contain substantial knowledge of the principles behind manufacturing process problems-solving; however, this knowledge is implicit in lengthy texts and cannot be directly reused in innovation design. To effectively support systematic manufacturing process innovation, this paper presents an approach to extracting principle innovation knowledge from process patents. The proposed approach consists of (1) classifying process patents by taking process method, manufacturing object and manufacturing feature as the references; (2) extracting generalized process contradiction parameters and the principles behind solving such process contradictions based on patent mining and technology abstraction of TRIZ (the theory of inventive problem solving); and (3) constructing a domain process contradiction matrix and mapping the relationship between the matrix and the corresponding process patents. Finally, a case study is presented to illustrate the applicability of the proposed approach

Effects of nano-void density, size, and spatial population on thermal conductivity: a case study of GaN crystal

The thermal conductivity of a crystal is sensitive to the presence of surfaces and nanoscale defects. While this opens tremendous opportunities to tailor thermal conductivity, a true "phonon engineering" of nanocrystals for a specific electronic or thermoelectric application can only be achieved when the dependence of thermal conductivity on the defect density, size, and spatial population is understood and quantified. Unfortunately, experimental studies of effects of nanoscale defects are quite challenging. While molecular dynamics simulations are effective in calculating thermal conductivity, the defect density range that can be explored with feasible computing resources is unrealistically high. As a result, previous work has not generated a fully detailed understanding of the dependence of thermal conductivity on nanoscale defects. Using GaN as an example, we have combined physically-motivated analytical model and highly-converged large scale molecular dynamics simulations to study effects of defects on thermal conductivity. An analytical expression for thermal conductivity as a function of void density, size, and population has been derived and corroborated with the model, simulations, and experiments

Coulomb scattering inducing time lag in strong-field tunneling ionization

We study ionization of atoms in strong elliptically-polarized laser fields. We focus on the physical origin of the offset angle in the photoelectron momentum distribution and its possible relation to a specific time. By developing a model which is based on strong-field approximation and considers the classical Coulomb scattering, we are able to quantitatively explain recent attoclock experiments in a wide region of laser and atomic parameters. The offset angle can be understood as arising from the scattering of the electron by the ionic potential when the electron exits the laser-Coulomb-formed barrier through tunneling. The scattering time is manifested as the Coulomb-induced ionization time lag and is encoded in the offset angle.Comment: 5 pages, 4 figure