Aqua MODIS Electronic Crosstalk on SMWIR Bands 20 to 26

Aqua MODIS Moon images obtained with bands 20 to 26 (3.66 - 4.55 and 1.36 - 1.39 $\mu$m) during scheduled lunar events show evidence of electronic crosstalk contamination of the response of detector 1. In this work, we determined the sending bands for each receiving band. We found that the contaminating signal originates, in all cases, from the detector 10 of the corresponding sending band and that the signals registered by the receiving and sending detectors are always read out in immediate sequence. We used the lunar images to derive the crosstalk coefficients, which were then applied in the correction of electronic crosstalk striping artifacts present in L1B images, successfully restoring product quality.Comment: Accepted to be published in the IEEE 2017 International Geoscience & Remote Sensing Symposium (IGARSS 2017), scheduled for July 23-28, 2017 in Fort Worth, Texas, US

MODIS Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level VNIR/SWIR Radiometric Uncertainties

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of optical thickness and effective particle radius for liquid water and ice phase clouds employ a well-known VNIR/ SWIR solar reflectance technique. For this type of algorithm, we evaluate the quantitative uncertainty in simultaneous retrievals of these two cloud parameters to pixel-level radiometric calibration estimates and other fundamental (and tractable) error sources

X-ray ptychography on low-dimensional hard-condensed matter materials

Tailoring structural, chemical, and electronic (dis-)order in heterogeneous media is one of the transformative opportunities to enable new functionalities and sciences in energy and quantum materials. This endeavor requires elemental, chemical, and magnetic sensitivities at the nano/atomic scale in two- and three-dimensional space. Soft X-ray radiation and hard X-ray radiation provided by synchrotron facilities have emerged as standard characterization probes owing to their inherent element-specificity and high intensity. One of the most promising methods in view of sensitivity and spatial resolution is coherent diffraction imaging, namely, X-ray ptychography, which is envisioned to take on the dominance of electron imaging techniques offering with atomic resolution in the age of diffraction limited light sources. In this review, we discuss the current research examples of far-field diffraction-based X-ray ptychography on two-dimensional and three-dimensional semiconductors, ferroelectrics, and ferromagnets and their blooming future as a mainstream tool for materials sciences

Magnetic and Transport Properties in CoSr2Y1−xCaxCu2O7CoSr_2Y_{1-x}Ca_xCu_2O_7 (xx=0∼\sim0.4)

Magnetic and transport properties of $Co Sr_2 Y_{1-x} Ca_x Cu_2 O_7$ ($x=0 \sim 0.4$) system have been investigated. A broad maximum in M(T) curve, indicative of low-dimensional antiferromagnetic ordering originated from $CoO_{1+\delta}$ layers, is observed in Ca-free sample. With increasing Ca doping level up to 0.2, the M(T) curve remains almost unchanged, while resistivity is reduced by three orders. Higher Ca doping level leads to a drastic change of magnetic properties. In comparison with the samples with $x=0.0 \sim 0.2$, the temperature corresponding to the maximum of M(T) is much lowered for the sample $x$=0.3. The sample $x$=0.4 shows a small kink instead of a broad maximum and a weak ferromagnetic feature. The electrical transport behavior is found to be closely related to magnetic properties for the sample $x$=0.2, 0.25, 0.3, 0.4. It suggests that $CoO_{1+\delta}$ layers are involved in charge transport in addition to conducting $CuO_2$ planes to interpret the correlation between magnetism and charge transport. X-ray photoelectron spectroscopy studies give an additional evidence of the the transfer of the holes into the $CoO_{1+\delta}$ charge reservoir

The Microsoft 2016 Conversational Speech Recognition System

We describe Microsoft's conversational speech recognition system, in which we combine recent developments in neural-network-based acoustic and language modeling to advance the state of the art on the Switchboard recognition task. Inspired by machine learning ensemble techniques, the system uses a range of convolutional and recurrent neural networks. I-vector modeling and lattice-free MMI training provide significant gains for all acoustic model architectures. Language model rescoring with multiple forward and backward running RNNLMs, and word posterior-based system combination provide a 20% boost. The best single system uses a ResNet architecture acoustic model with RNNLM rescoring, and achieves a word error rate of 6.9% on the NIST 2000 Switchboard task. The combined system has an error rate of 6.2%, representing an improvement over previously reported results on this benchmark task

Mechanical breakdown of bent silicon nanowires imaged by coherent x-ray diffraction

We have developed a method of coherent x-ray diffractive imaging to surmount its inability to image the structure of strongly strained crystals. We used calculated models from finite–element analysis to guide an iterative algorithm to fit experimental data from a series of increasingly bent wires cut into silicon-on-insulator films. Just before mechanical fracture, the wires were found to contain new phase structures, which are identified as dislocations associated with crossing the elastic limit