A Feedforward Neural Network Approach for the Detection of Optically Thin Cirrus From IASI-NG

The identification of optically thin cirrus is crucial for their accurate parameterization in climate and Earth's system models. This study exploits the characteristics of the infrared atmospheric sounding interferometer-new generation (IASI-NG) to develop an algorithm for the detection of optically thin cirrus. IASI-NG has been designed for the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar system second-generation program to continue the service of its predecessor IASI from 2024 onward. A thin-cirrus detection algorithm (TCDA) is presented here, as developed for IASI-NG, but also in parallel for IASI to evaluate its performance on currently available real observations. TCDA uses a feedforward neural network (NN) approach to detect thin cirrus eventually misidentified as clear sky by a previously applied cloud detection algorithm. TCDA also estimates the uncertainty of "clear-sky" or "thin-cirrus" detection. NN is trained and tested on a dataset of IASI-NG (or IASI) simulations obtained by processing ECMWF 5-generation reanalysis (ERA5) data with the s-IASI radiative transfer model. TCDA validation against an independent simulated dataset provides a quantitative statistical assessment of the improvements brought by IASI-NG with respect to IASI. In fact, IASI-NG TCDA outperforms IASI TCDA by 3% in probability of detection (POD), 1% in bias, and 2% in accuracy, and the false alarm ratio (FAR) passes from 0.02 to 0.01. Moreover, IASI TCDA validation against state-of-the-art cloud products from Cloudsat/CPR and CALIPSO/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) real observations reveals a tendency for IASI TCDA to underestimate the presence of thin cirrus (POD = 0.47) but with a low FAR (0.07), which drops to 0.0 for very thin cirrus

Competition in the postsynaptic density for PDZ domains of PSD-95

Molecular mechanisms of synaptic plasticity are of great interest because derangement of synaptic plasticity contributes to neural diseases such as autism, schizophrenia, cognitive impairment, neuropathic pain, epilepsy, and stroke. This work addresses the molecular mechanisms underlying NMDA‐type glutamate receptor‐triggered plasticity at excitatory synapses. A critical step in this process is a change in the rate of trapping of AMPA‐type receptors (AMPARs) in the postsynaptic density (PSD), which increases the number of AMPARs and strengthens the electrical signal at the synapse. Our work aims to determine whether trapping of AMPARs in the PSD is mediated by rearrangement of the PSD scaffold caused by changes in the affinity of different PSD proteins for the PDZ domains of the major synaptic scaffold protein, PSD‐95. Our earlier publication (1) supports this notion by showing that: 1. Phosphorylation of the abundant PSD protein synGAP by CaMKII reduces its affinity for the PDZ domains of PSD‐95; and 2. The composition of the PSD is altered in synGAP deficient mice such that AMPAR-binding proteins with PDZ ligands, including TARPs and LRRTM2, are increased in concentration relative to PSD‐95. We have now replicated these finding in synGAP‐deficient rats. These findings suggest that the extent of binding of particular synaptic proteins to the PDZ domains of PSD‐95 is regulated by activity‐dependent phosphorylation of synGAP. We are testing this hypothesis in cultured rat neurons. We have isolated PSDs from neuronal cultures before and after induction of synGAP phosphorylation by pharmacological activation of NMDARs. The ratios of AMPAR‐associated proteins to PSD‐95 in the PSDs are determined by quantitative immunoblotting. We have found that the ratio of TARPs to PSD‐95 is consistently increased in PSDs after chemical activation of synaptic NMDARs. We are using cultures from synGAP‐deficient rats to determine if synGAP deficiency alters the composition of the PSD in rat cultures. We plan to transfect with a variety of synGAP mutant proteins in order to determine which domains or phosphorylation sites on synGAP are important for regulating PSD composition

Spectrum Synergy for Investigating Cloud Microphysics

Observations from spaceborne microwave (MW) and infrared (IR) passive sensors are the backbone of current satellite meteorology, essential for data assimilation into modern numerical weather prediction and for climate benchmarking. While MW and IR observations from space offer complementary features with respect to cloud properties, their synergy for cloud investigation is currently underexplored, despite the presence of both MW and IR sensors on operational meteorological satellites such as the EUMETSAT Polar System (EPS) MetOp series. As such, several key cloud microphysical properties are not part of the operational products available from EPS MetOp sensors. In addition, the EPS Second Generation (EPS-SG) series, scheduled for launch starting from 2024 onward, will carry sensors such as the Microwave Sounder (MWS) and IASI Next Generation (IASI-NG), enhancing spatial and spectral resolutions and thus capacity to retrieve cloud properties. This article presents the Combined MWS and IASI-NG Soundings for Cloud Properties (ComboCloud) project, funded by EUMETSAT with the overall objective to specify, prototype, and validate algorithms for the retrieval of cloud microphysical properties (e.g., water content and drop effective radius) from the synergy of passive MW and IR observations. The article presents the synergy rationale, the algorithm design, and the results obtained exploiting simulated observations from EPS and EPS-SG sensors, quantifying the benefits to be expected from the MW-IR synergy and the new generation sensors

Effect of GaN surface treatment on Al2O3/n-GaN MOS capacitors

Citation: Hossain, T., Wei, D., Edgar, J. H., Garces, N. Y., Nepal, N., Hite, J. K., . . . Meyer H.M, III. (2015). Effect of GaN surface treatment on Al2O3/n-GaN MOS capacitors. Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics, 33(6). doi:10.1116/1.4931793The surface preparation for depositing Al2O3 for fabricating Au/Ni/Al2O3/n-GaN (0001) metal oxide semiconductor (MOS) capacitors was optimized as a step toward realization of high performance GaN MOSFETs. The GaN surface treatments studied included cleaning with piranha (H2O2:H2SO4 = 1:5), (NH4)2S, and 30% HF etches. By several metrics, the MOS capacitor with the piranha-etched GaN had the best characteristics. It had the lowest capacitance–voltage hysteresis, the smoothest Al2O3 surface as determined by atomic force microscopy (0.2 nm surface roughness), the lowest carbon concentration (∼0.78%) at the Al2O3/n-GaN interface (from x-ray photoelectron spectroscopy), and the lowest oxide-trap charge (QT = 1.6 × 1011 cm−2eV−1). Its interface trap density (Dit = 3.7 × 1012 cm−2eV−1), as measured with photon-assisted capacitance– voltage method, was the lowest from conduction band-edge to midgap

A model for regulation by SynGAP-α1 of binding of synaptic proteins to PDZ-domain 'Slots' in the postsynaptic density

SynGAP is a Ras/Rap GTPase-activating protein (GAP) that is a major constituent of postsynaptic densities (PSDs) from mammalian forebrain. Its α1 isoform binds to all three PDZ (PSD-95, Discs-large, ZO-1) domains of PSD-95, the principal PSD scaffold, and can occupy as many as 15% of these PDZ domains. We present evidence that synGAP-α1 regulates the composition of the PSD by restricting binding to the PDZ domains of PSD-95. We show that phosphorylation by Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII) and Polo-like kinase-2 (PLK2) decreases its affinity for the PDZ domains by several fold, which would free PDZ domains for occupancy by other proteins. Finally, we show that three critical postsynaptic signaling proteins that bind to the PDZ domains of PSD-95 are present in higher concentration in PSDs isolated from mice with a heterozygous deletion of synGAP