![]() (2006) favoring a high mass solution for the absorbed grad + power law model. We also note that very deep observations allow a breaking of the degeneracy noted by Stobbart et al. We comment on the physical implications of these different model fits. Veusz can now switch between native and US formatting and program locales. LaTeX superscripts and subscripts appear at the same horizontal position and works in key text. A self test program is now provided to check output. We tested the abundances obtained from the XSPEC models bbody, diskbb, grad, and diskpn along with a power law, finding that the abundances were independent of the thermal model used. When fitting data, Veusz can now use PyMinuit for better minimization. In order to obtain the column density and abundance values, we fit the X-ray spectra of the ULXs with a combined power law and one of several accretion disk models. I prepared a simpler example plugin like below to reproduce the error. The X-ray model n_H values are in good agreement with the H I n_H values, implying that the hydrogen absorption towards the ULXs is not local to the source (with the exception of the source M81 XMM1). Ubuntu 20.04 (WSL) + binary package ( or built from the latest source I will report pure Linux results and MacOS detailed environments later. Also, we compare the X-ray hydrogen column densities (n_H) for 8 ULX sources with column densities obtained from radio H I observations. We found that the oxygen abundances closely matched recent solar abundances for all of our sources, implying that ULXs live in similar local environments despite the wide range of galaxy host properties. We determined oxygen and iron abundances of the host galaxy's interstellar medium (ISM) using K-shell (O) and L-shell (Fe) X-ray photo-ionization edges towards these ULXs. Future efforts can be directed to automatically capture images when the smartphone is inclined to the desired angle.(abridged) In this paper, we examined XMM Newton EPIC spectra of 14 ultra-luminous X-ray sources (ULXs)in addition to the XMM RGS spectra of two sources (Holmberg II X-1 and Holmberg IX X-1). The attraction of the proposed method is that it does not rely on the empiric al G value or MTA, providing an affordable alternative to traditional commercial instruments. The success of the MTA estimates and thus LAI measurements is attributed to the enlarged VZA ranging from 4° to 60°, and this VZA is comparable with that of the LAI-2200 instrument. A good agreement between the LAI measurements from the proposed method and those from the LAI-2200 supports the accurate estimation of MTAs. The results reveal that an inclination angle of 30° from zenith is superior to other angles of 0, 45 and 60°. The proposed method is validated using data collected over crops and trees by a LAI-2200 instrument and a Huawei Honor 7 smartphone. The MTAs corresponding to the matched G functions are selected as ancillary parameters to help calculate the LAI. functions of mean tilt angle (MTA) and VZA. With the directional gap fractions extracted from the images taken by the inclined smartphone camera, a curve matching algorithm is used to iteratively search for the simulated G functions, i.e. To overcome this limitation, we propose a method to estimate LAI from an inclined smartphone camera that can enlarge the range of the sensor’s effective VZA. However, the narrow full field of view (FOV) of the common smartphones offer only an effective viewing zenith angle (VZA) of less than 35° when the camera is pointing straight up. It can also be easily scripted (the saved file formats are similar to Python scripts) or used as module inside Python. The program features a graphical user interface (GUI), which works under Unix/Linux, Windows or Mac OS. It is designed to be easy to use, easily extensible, but powerful. Among the instruments for measuring the LAI, smartphone cameras are becoming an attractive alternative to special LAI instruments. Veusz is a 2D and 3D scientific plotting package. ![]() Measurements of leaf area index (LAI) are important for modeling microclimate in vegetation research.
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