Electrical data release for the Owens Peak Wilderness Study Area (CA-010-026) Tulare and Kern counties, California

Abstract The paper reports the investigation on the root cause of source-drain leakage in bulk FinFET devices. While the failing device was readily isolated by nanoprobing technique and the electrical analysis pinpointed the potential defect location inside the Fin channel, the identification of physical root cause went through extreme challenges imposed by the tiny-sized device and the unique FinFET 3D architecture. The initial TEM analysis was misled by the projection of a species in the lamella surface and thus could not explain the electrical data. Careful analysis on the device structure was able to identify the origin of the species and led to the discovery of the actual root cause. This paper will provide the analysis details leading to the findings, and highlight the role of electrical understanding in not only providing guidance for physical analysis but also revealing the true root cause of failure in FinFET devices.

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Исследование кинематики звезд каталога GAIA Data Release 2 with Radial Velocities с помощью скалярных и векторных сферических функций

Письма в астрономический журнал Астрономия и космическая астрофизика ◽

10.31857/s0320010819110093 ◽

2020 ◽

Vol 46 (01) ◽

pp. 61-75

Author(s):

А. С. Цветков ◽

Ф. А. Амосов ◽

Д. А. Трофимов ◽

С. Д. Петров

Keyword(s):

Radial Velocities ◽

Data Release

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The SAMI Galaxy Survey: reconciling strong emission line metallicity diagnostics using metallicity gradients

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stab205 ◽

2021 ◽

Vol 502 (3) ◽

pp. 3357-3373

Author(s):

Henry Poetrodjojo ◽

Brent Groves ◽

Lisa J Kewley ◽

Sarah M Sweet ◽

Sebastian F Sanchez ◽

...

Keyword(s):

Emission Line ◽

Electron Temperature ◽

Gas Phase ◽

Mass Range ◽

Accurate Method ◽

Emission Lines ◽

Mass Relation ◽

Strong Emission ◽

Data Release ◽

Accurate Comparison

ABSTRACT We measure the gas-phase metallicity gradients of 248 galaxies selected from Data Release 2 of the SAMI Galaxy Survey. We demonstrate that there are large systematic discrepancies between the metallicity gradients derived using common strong emission line metallicity diagnostics. We determine which pairs of diagnostics have Spearman’s rank coefficients greater than 0.6 and provide linear conversions to allow the accurate comparison of metallicity gradients derived using different strong emission line diagnostics. For galaxies within the mass range 8.5 < log (M/M⊙) < 11.0, we find discrepancies of up to 0.11 dex/Re between seven popular diagnostics in the metallicity gradient–mass relation. We find a suggestion of a break in the metallicity gradient–mass relation, where the slope shifts from negative to positive, occurs between 9.5 < log (M/M⊙) < 10.5 for the seven chosen diagnostics. Applying our conversions to the metallicity gradient–mass relation, we reduce the maximum dispersion from 0.11 dex/Re to 0.02 dex/Re. These conversions provide the most accurate method of converting metallicity gradients when key emission lines are unavailable. We find that diagnostics that share common sets of emission line ratios agree best, and that diagnostics calibrated through the electron temperature provide more consistent results compared to those calibrated through photoionization models.

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An Efficient Neural Network-Based Method for Diagnosing Faults of PV Array

Sustainability ◽

10.3390/su13116194 ◽

2021 ◽

Vol 13 (11) ◽

pp. 6194

Author(s):

Selma Tchoketch_Kebir ◽

Nawal Cheggaga ◽

Adrian Ilinca ◽

Sabri Boulouma

Keyword(s):

Neural Network ◽

Neural Networks ◽

Modeling Process ◽

Photovoltaic Arrays ◽

Mode Of Operation ◽

Different Types ◽

The Neural Networks ◽

Operational Modes ◽

Types Of Faults ◽

Electrical Data

This paper presents an efficient neural network-based method for fault diagnosis in photovoltaic arrays. The proposed method was elaborated on three main steps: the data-feeding step, the fault-modeling step, and the decision step. The first step consists of feeding the real meteorological and electrical data to the neural networks, namely solar irradiance, panel temperature, photovoltaic-current, and photovoltaic-voltage. The second step consists of modeling a healthy mode of operation and five additional faulty operational modes; the modeling process is carried out using two networks of artificial neural networks. From this step, six classes are obtained, where each class corresponds to a predefined model, namely, the faultless scenario and five faulty scenarios. The third step involves the diagnosis decision about the system’s state. Based on the results from the above step, two probabilistic neural networks will classify each generated data according to the six classes. The obtained results show that the developed method can effectively detect different types of faults and classify them. Besides, this method still achieves high performances even in the presence of noises. It provides a diagnosis even in the presence of data injected at reduced real-time, which proves its robustness.

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The bimodal [Mg/Fe] versus [Fe/H] bulge sequence as revealed by APOGEE DR14

Astronomy and Astrophysics ◽

10.1051/0004-6361/201834126 ◽

2019 ◽

Vol 626 ◽

pp. A16 ◽

Cited By ~ 10

Author(s):

A. Rojas-Arriagada ◽

M. Zoccali ◽

M. Schultheis ◽

A. Recio-Blanco ◽

G. Zasowski ◽

...

Keyword(s):

Fundamental Parameters ◽

Elemental Abundances ◽

Data Release ◽

Bulge Region ◽

Solar Metallicity ◽

Inner Region ◽

Clean Sample ◽

Metallicity Distribution ◽

Single Sequence

Context. The Galactic bulge has a bimodal metallicity distribution function: different kinematic, spatial, and, potentially, age distributions characterize the metal-poor and metal-rich components. Despite this observed dichotomy, which argues for different formation channels for those stars, the distribution of bulge stars in the α-abundance versus metallicity plane has been found so far to be a rather smooth single sequence. Aims. We use data from the fourteenth data release of the APOGEE spectroscopic survey (DR14) to investigate the distribution in the Mg abundance (as tracer of the α-elements)-versus-metallicity plane of a sample of stars selected to be in the inner region of the bulge. Methods. A clean sample has been selected from the DR14 using a set of data- and pipeline-flags to ensure the quality of their fundamental parameters and elemental abundances. An additional selection made use of computed spectro-photometric distances to select a sample of likely bulge stars as those with RGC ≤ 3.5 kpc. We adopt magnesium abundance as an α-abundance proxy for our clean sample as it has been proven to be the most accurate α-element as determined by ASPCAP, the pipeline for data products from APOGEE spectra. Results. From the distribution of our bulge sample in the [Mg/Fe]-versus-[Fe/H] plane, we found that the sequence is bimodal. This bimodality is given by the presence of a low-Mg sequence of stars parallel to the main high-Mg sequence over a range of ∼0.5 dex around solar metallicity. The two sequences merge above [Fe/H] ∼ 0.15 dex into a single sequence whose dispersion in [Mg/Fe] is larger than either of the two sequences visible at lower metallicity. This result is confirmed when we consider stars in our sample that are inside the bulge region according to trustworthy Gaia DR2 distances.

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The SAMI Galaxy Survey: the third and final data release

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stab229 ◽

2021 ◽

Author(s):

Scott M Croom ◽

Matt S Owers ◽

Nicholas Scott ◽

Henry Poetrodjojo ◽

Brent Groves ◽

...

Keyword(s):

Large Scale ◽

Resolving Power ◽

Stellar Kinematics ◽

New Era ◽

Optical Wavelength ◽

Astronomical Optics ◽

Data Release ◽

Gas Ionization ◽

Release Data ◽

First Time

Abstract We have entered a new era where integral-field spectroscopic surveys of galaxies are sufficiently large to adequately sample large-scale structure over a cosmologically significant volume. This was the primary design goal of the SAMI Galaxy Survey. Here, in Data Release 3 (DR3), we release data for the full sample of 3068 unique galaxies observed. This includes the SAMI cluster sample of 888 unique galaxies for the first time. For each galaxy, there are two primary spectral cubes covering the blue (370–570 nm) and red (630–740 nm) optical wavelength ranges at spectral resolving power of R = 1808 and 4304 respectively. For each primary cube, we also provide three spatially binned spectral cubes and a set of standardized aperture spectra. For each galaxy, we include complete 2D maps from parameterized fitting to the emission-line and absorption-line spectral data. These maps provide information on the gas ionization and kinematics, stellar kinematics and populations, and more. All data are available online through Australian Astronomical Optics (AAO) Data Central.

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