gebhart/patrepeval huggingface dataset:
Fabrication technology for high light-extraction ultraviolet thin-film\n flip-chip (UV TFFC) LEDs grown on SiC (2018)

The light output of deep ultraviolet (UV-C) AlGaN light-emitting diodes\n(LEDs) is limited due to their poor light extraction efficiency (LEE). To\nimprove the LEE of AlGaN LEDs, we developed a fabrication technology to process\nAlGaN LEDs grown on SiC into thin-film flip-chip LEDs (TFFC LEDs) with high\nLEE. This process transfers the AlGaN LED epi onto a new substrate by\nwafer-to-wafer bonding, and by removing the absorbing SiC substrate with a\nhighly selective SF6 plasma etch that stops at the AlN buffer layer. We\noptimized the inductively coupled plasma (ICP) SF6 etch parameters to develop a\nsubstrate-removal process with high reliability and precise epitaxial control,\nwithout creating micromasking defects or degrading the health of the plasma\netching system. The SiC etch rate by SF6 plasma was ~46 \\mu m/hr at a high RF\nbias (400 W), and ~7 \\mu m/hr at a low RF bias (49 W) with very high etch\nselectivity between SiC and AlN. The high SF6 etch selectivity between SiC and\nAlN was essential for removing the SiC substrate and exposing a pristine,\nsmooth AlN surface. We demonstrated the epi-transfer process by fabricating\nhigh light extraction TFFC LEDs from AlGaN LEDs grown on SiC. To further\nenhance the light extraction, the exposed N-face AlN was anisotropically etched\nin dilute KOH. The LEE of the AlGaN LED improved by ~3X after KOH roughening at\nroom temperature. This AlGaN TFFC LED process establishes a viable path to high\nexternal quantum efficiency (EQE) and power conversion efficiency (PCE) UV-C\nLEDs.\n
Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging (2022)

Details of the designs and mechanisms in support of human-AI collaboration must be considered in the real-world fielding of AI technologies. A critical aspect of interaction design for AI-assisted human decision making are policies about the display and sequencing of AI inferences within larger decision-making workflows. We have a poor understanding of the influences of making AI inferences available before versus after human review of a diagnostic task at hand. We explore the effects of providing AI assistance at the start of a diagnostic session in radiology versus after the radiologist has made a provisional decision. We conducted a user study where 19 veterinary radiologists identified radiographic findings present in patients’ X-ray images, with the aid of an AI tool. We employed two workflow configurations to analyze (i) anchoring effects, (ii) human-AI team diagnostic performance and agreement, (iii) time spent and confidence in decision making, and (iv) perceived usefulness of the AI. We found that participants who are asked to register provisional responses in advance of reviewing AI inferences are less likely to agree with the AI regardless of whether the advice is accurate and, in instances of disagreement with the AI, are less likely to seek the second opinion of a colleague. These participants also reported that the AI advice to be less useful. Surprisingly, requiring provisional decisions on cases in advance of the display of AI inferences did not lengthen the time participants spent on the task. The study provides generalizable and actionable insights for the deployment of clinical AI tools in human-in-the-loop systems and introduces a methodology for studying alternative designs for human-AI collaboration. We make our experimental platform available as open source to facilitate future research on the influence of alternate designs on human-AI workflows.
Matched illumination: using light modulation as a proxy for a color filter that makes a camera more colorimetric (2022)

In previous work, it was shown that a camera can theoretically be made more colorimetric-its RGBs become more linearly related to XYZ tristimuli-by placing a specially designed color filter in the optical path. While the prior art demonstrated the principle, the optimal color-correction filters were not actually manufactured. In this paper, we provide a novel way of creating the color filtering effect without making a physical filter: we modulate the spectrum of the light source by using a spectrally tunable lighting system to recast the prefiltering effect from a lighting perspective. According to our method, if we wish to measure color under a D65 light, we relight the scene with a modulated D65 spectrum where the light modulation mimics the effect of color prefiltering in the prior art. We call our optimally modulated light, the matched illumination. In the experiments, using synthetic and real measurements, we show that color measurement errors can be reduced by about 50% or more on simulated data and 25% or more on real images when the matched illumination is used.
Integrin αvβ8–expressing tumor cells evade host immunity by regulating TGF-β activation in immune cells (2018)

TGF-β is a promising immunotherapeutic target. It is expressed ubiquitously in a latent form that must be activated to function. Determination of where and how latent TGF-β (L-TGF-β) is activated in the tumor microenvironment could facilitate cell- and mechanism-specific approaches to immunotherapeutically target TGF-β. Binding of L-TGF-β to integrin αvβ8 results in activation of TGF-β. We engineered and used αvβ8 antibodies optimized for blocking or detection, which - respectively - inhibit tumor growth in syngeneic tumor models or sensitively and specifically detect β8 in human tumors. Inhibition of αvβ8 potentiates cytotoxic T cell responses and recruitment of immune cells to tumor centers - effects that are independent of PD-1/PD-L1. β8 is expressed on the cell surface at high levels by tumor cells, not immune cells, while the reverse is true of L-TGF-β, suggesting that tumor cell αvβ8 serves as a platform for activating cell-surface L-TGF-β presented by immune cells. Transcriptome analysis of tumor-associated lymphoid cells reveals macrophages as a key cell type responsive to β8 inhibition with major increases in chemokine and tumor-eliminating genes. High β8 expression in tumor cells is seen in 20%-80% of various cancers, which rarely coincides with high PD-L1 expression. These data suggest tumor cell αvβ8 is a PD-1/PD-L1-independent immunotherapeutic target.
A deep neural network for image quality assessment (2016)

This paper presents a no reference image (NR) quality assessment (IQA) method based on a deep convolutional neural network (CNN). The CNN takes unpreprocessed image patches as an input and estimates the quality without employing any domain knowledge. By that, features and natural scene statistics are learnt purely data driven and combined with pooling and regression in one framework. We evaluate the network on the LIVE database and achieve a linear Pearson correlation superior to state-of-the-art NR IQA methods. We also apply the network to the image forensics task of decoder-sided quantization parameter estimation and also here achieve correlations of r = 0.989.
Synthesis of Polyurethanes Using Organocatalysis: A Perspective (2015)

Organocatalysis has become an invaluable tool for polymer synthesis, and its utility has been demonstrated in ring-opening, anionic, zwitterionic, and group-transfer polymerizations. Despite this, the use of organocatalysis in other polymerization reactions such as step-growth polymerizations remains underexplored, relative to more traditional metal-based polymerizations. Recently, the use of organic bases such as guanidines, amidines, N-heterocyclic carbenes, and organic "strong or super-strong" Bronsted acids to catalyze the synthesis of metal-free polyurethanes has shown to be competitive to commercially widely used dibutyltin dilaurate and dibutyltin diacetate catalysts. This Perspective article highlights recent advances in organocatalyst design for isocyanate-based polyurethane synthesis with the aim of comparing the activity and selectivity of each of the new catalytic reactions to each other and the traditional metal-based catalysts. The article also draws attention to new trends in isocyanate-free polyurethane synthesis and the key role that organocatalysis is playing in these innovative polymerization processes.
Variations of light emission and carrier dynamics around V-defects in InGaN quantum wells (2020)

Time- and spectrally-resolved scanning near-field optical microscopy was applied to study spatial variations of photoluminescence (PL) spectra and carrier dynamics in polar InGaN/GaN single quantum wells (QWs) emitting from 410 nm to 570 nm. The main attention was devoted to variations of PL properties and carrier dynamics around V-defects. The PL intensity, peak wavelength, and linewidth, as well as the radiative and nonradiative recombination times, were found to be different in V-defect-rich and defect-free regions. The radiative lifetime close to the defects was longer up to several times, which is attributed to an increased electron and hole wave function separation in the QW plane. PL decay times, measured using excitation and collection through the near-field probe, were one to two orders of magnitude shorter than PL decay times measured in the far field. This shows that the near-field PL decay and the integrated PL intensity are primarily determined by the carrier out-diffusion from under the probe. Only in the immediate vicinity of the V-defects, the near-field PL decays due to the nonradiative recombination at dislocations. The area of such enhanced nonradiative recombination is limited to just a few percent of the total QW area. This shows that recombination via dislocations and V-defects does not play a decisive role in the overall nonradiative recombination and internal quantum efficiency of polar InGaN/GaN QWs.
Deep water sound sources for ocean acoustic tomography and long-range navigation (2016)

The first test of the tunable organ-pipe was successfully conducted on 11 Sept. 2001. The sound source was efficient, powerful, and had unlimited operational depth, as well as a minimum level of high frequency harmonic content. The projector uses a narrow-band, highly efficient sound resonator, which is tuned to match the frequency and phase of a reference frequency-modulated signal. Since 2001, many deep-water ocean acoustic experiments have used this type of sound source. The source was successfully used for ocean acoustic tomography and long range navigation. Recently, it was shown that a bottom-deployed swept frequency array can be used for high-resolution seismic imaging of deep geological formations. The long-term operating experience of the sound sources demands the development of an improved sound source system. A finite-element analysis that shows the structural acoustics of the tunable resonator has been conducted to improve the acoustics of the sound source. The analysis gave a better solution for a tuning mechanism with an octave frequency range. The development of the electric and mechanical systems of the sound source will be discussed. Teledyne Marine Systems continues innovating promising solutions for ocean acoustic tomography, navigation, and seismo-acoustic applications.
Stabilization and improved functionality of three-dimensional perfusable microvascular networks in microfluidic devices under macromolecular crowding (2023)

Application of MMC to MVNs in microfluidic devices provides a reliable, flexible and versatile approach to stabilize engineered microvessels under simulated physiological conditions.
Dynamic Kinetic Resolution in Cu-Catalyzed Conjugate Hydride Addition (2005)

A dynamic kinetic resolution (DKR) of α,β-unsaturated lactones via a Cu-catalyzed conjugate hydride addition was reported. This highly efficient approach afforded excellent yields and good ee’s in the formation of β,γ-disubstituted γ-lactones from racemic starting materials. The methodology was demonstrated in an extremely concise enantioselective total synthesis of Eupomatilone-3, which was achieved in six steps and 48% overall yield.
Molecular and physiological approaches to maize improvement for drought tolerance (2002)

Average maize yields have increased steadily over the years in the USA and yet the variations in harvestable yield have also markedly increased. Much of the increase in yield variability can be attributed to (1) varying environmental stress conditions; (2) improved nitrogen inputs and better weed control; and (3) continuing sensitivity of different maize lines to the variation in input supply, especially rainfall. Drought stress alone can account for a significant percentage of average yield losses. Yet despite variable environments, new commercially available maize hybrids continue to be produced each year with ever‐increasing harvestable yield. Since many factors contribute to high plant performance under water deficits, efforts are being made to elucidate the nature of water‐stress tolerance in an attempt to improve maize hybrids further. Such factors include better partitioning of biomass to the developing ear resulting in faster spikelet growth and improved reproductive success. An emphasis on faster spikelet growth rate may result in a reduction in the number of spikelets formed on the ear that facilitates overall seed set by reducing water and carbon constraints per spikelet. To understand the molecular mechanisms for drought tolerance in improved maize lines better, a variety of genomic tools are being used. Newer molecular markers and comprehensive gene expression profiling methods provide opportunities to direct the continued breeding of genotypes that provide stable grain yield under widely varied environmental conditions.
Self-Consistency: A Novel Approach to Characterizing the Accuracy and Reliability of Point-Correspondence Algorithms (1999)

Reference CVLAB-CONF-1999-005 URL: http://cvlab.epfl.ch/publications/publications/1999/LeclercTF99.pdf Record created on 2006-02-03, modified on 2016-08-08
Figure S5 from A Novel Theranostic Strategy for <i>MMP-14</i>–Expressing Glioblastomas Impacts Survival (2023)

&lt;p&gt;Effect of CLIO-ICT on mouse body weight&lt;/p&gt;
Imaging with terahertz radiation (2007)

Within the last several years, the field of terahertz science and technology has changed dramatically. Many new advances in the technology for generation, manipulation, and detection of terahertz radiation have revolutionized the field. Much of this interest has been inspired by the promise of valuable new applications for terahertz imaging and sensing. Among a long list of proposed uses, one finds compelling needs such as security screening and quality control, as well as whimsical notions such as counting the almonds in a bar of chocolate. This list has grown in parallel with the development of new technologies and new paradigms for imaging and sensing. Many of these proposed applications exploit the unique capabilities of terahertz radiation to penetrate common packaging materials and provide spectroscopic information about the materials within. Several of the techniques used for terahertz imaging have been borrowed from other, more well established fields such as x-ray computed tomography and synthetic aperture radar. Others have been developed exclusively for the terahertz field, and have no analogies in other portions of the spectrum. This review provides a comprehensive description of the various techniques which have been employed for terahertz image formation, as well as discussing numerous examples which illustrate the many exciting potential uses for these emerging technologies.
Low-Temperature Aluminum-Aluminum Wafer Bonding (2016)

Aluminum-aluminum thermo-compression wafer bonding is becoming increasingly important in the production of microelectromechanical systems (MEMS) devices. As the chemically highly stable aluminum oxide layer acts as a diffusion barrier between the two aluminum metallization layers, up to now the process has required bonding temperatures of 300°C or more. By using the EVG ® 580 ComBond ® system, in which a surface treatment and subsequent wafer bonding are both performed in a high vacuum cluster, for the first time successful Al-Al wafer bonding was possible at a temperature of 100°C. The bonded interfaces of blank Al wafers and Al wafers with patterned frames were characterized using C-mode scanning acoustic microscopy (C-SAM) and transmission electron microscopy (TEM) as well as dicing yield and pull tests representative for the bonding strength. The investigations revealed areas of oxide-free, atomic contact at the Al-Al bonded interface.
Predictive Modeling of Aircraft Dynamics Using Neural Networks (2022)

&lt;div&gt;Fighter pilots must study models of aircraft dynamics before learning complex maneuvers and tactics. Similarly, autonomous fighter aircraft applications may benefit from a model-based learning approach. Instead of using a preexisting physics model of a given aircraft, a machine learning system can learn a predictive model of the aircraft physics from training data. Furthermore, it can model interactions between multiple friendly aircraft, enemy aircraft, and the environment. Such a system can also learn to represent state variables that are not directly observable, as well as dynamics that are not hard coded. Existing model-based methods use a deep neural network that takes observable state information and agent actions as input and provides predictions of future observations as output. The proposed method builds upon this approach by adding a residual feedforward skip connection from some of the inputs to all of the outputs of the deep neural network. Further innovations address numerical conditioning issues as well as periodic discontinuities of angular quantities such as bearing or heading. The methods in this article also extend techniques from model-based reinforcement learning control to the domain of adversarial multi-agent environments. In previous literature, these model-based methods have only been used for controlling individual agents. Instead of using a traditional Recurrent Neural Network (RNN) to learn a representation of the world state, the novel method also uses a compressive encoding scheme. This is based on an augmented version of the same neural network that is used for predictive modeling.&lt;/div&gt;
A Multi-Factor QoE Model for Adaptive Streaming over Mobile Networks (2016)

In the context of HTTP Adaptive Streaming (HAS), a main challenge is how to evaluate the quality of experience (QoE) of a session. In general, the QoE of a streaming session is affected by three key factors, namely initial delay, varying perceptual quality, and interruptions. In this paper, in order to investigate the impacts of quality variations and interruptions on the QoE of a session, we propose to use histograms, which represent the frequency distributions of these recurrent factors in a session. The QoE of a session is modeled by pooling the statistics of the recurrent factors and the initial delay. Evaluation results show that the proposed model has a high prediction performance. Especially, the proposed model provides insights into the impacts of different influence factors, thus leading to suggestions to improve the quality of streaming video.
Using minimal spanning tree based ICA optimization for volcanic unrest determination (2021)

&amp;lt;p&amp;gt;Over the years, various satellites like ERS-1, ERS-2 and Envisat has been in use for the interferometric capability for a wide range of geophysical and environmental applications. With the launches of Sentinel-1A and 1B satellites in 2014 and 2016 respectively, the availability of SAR data from every part of the world has been increased many folds. With short revisit times of 1-6 days, the Sentinel-1 and the planned Tandem-Land NISAR missions provide an unprecedented wealth of topography and surface change data using InSAR technique. Utilizing these Synthetic Aperture Radar (SAR) acquisitions, repeated approximately from the same point in space at different times, it is possible to produce measurements of ground deformations at some of the world&amp;amp;#8217;s active volcanoes and can be used to detect signs of volcanic unrest. Most of the existing traditional algorithms like Permanent Scatterer (PS) analysis and Small Baseline Subset (SBAS) technique are computationally extensive and cannot be applied in near real time to detect&amp;amp;#160; precursory deformation and transient deformations. To overcome this problem, we have adapted a minimum spanning tree (MST) based spatial independent component analysis (ICA) method to automatically detect deformation signals of volcanic unrest. We utilize the algorithm&amp;amp;#8217;s capability to isolate signals of geophysical interest from atmospheric artifacts, topography and other noise signals, before monitoring the evolution of these signals through time in order to detect the onset of a period of volcanic unrest, in near real time. We demonstrate our approach on synthetic datasets having different signal strengths, varying temporally. We also present the results of our approach on the volcanic unrest of Mt. Thorbj&amp;amp;#246;rn in Iceland on 2020 and also the volcanic unrest of a volcano in Mexico from 2017 to 2019.&amp;lt;/p&amp;gt;
Direct growth of a 40 nm InAs thin film on a GaAs/Ge heterostructure by metalorganic chemical vapor deposition (2014)

In this paper, the authors directly grew an InAs thin film (40 nm) by metalorganic chemical vapor deposition on GaAs/Ge substrates by using flow-rate modulation epitaxy with an appropriate V/III ratio. The growth of a high-quality InAs thin film with periodic 90° misfit dislocations was related to a uniform monolayer In atom distribution at the InAs/GaAs interface. The In monolayer effectively minimized the difference between surface energy and strain energy, producing a stable interface during material growth. The authors also found that a tightly controlled V/III ratio can improve the quality of the InAs islands on the GaAs/Ge heterostructures, though it is not the key factor in InAs thin-film growth.
Glutenin and Gliadin, a Piece in the Puzzle of their Structural Properties in the Cell Described through Monte Carlo Simulations (2020)

Gluten protein crosslinking is a predetermined process where specific intra- and intermolecular disulfide bonds differ depending on the protein and cysteine motif. In this article, all-atom Monte Carlo simulations were used to understand the formation of disulfide bonds in gliadins and low molecular weight glutenin subunits (LMW-GS). The two intrinsically disordered proteins appeared to contain mostly turns and loops and showed "self-avoiding walk" behavior in water. Cysteine residues involved in intramolecular disulfide bonds were located next to hydrophobic peptide sections in the primary sequence. Hydrophobicity of neighboring peptide sections, synthesis chronology, and amino acid chain flexibility were identified as important factors in securing the specificity of intramolecular disulfide bonds formed directly after synthesis. The two LMW-GS cysteine residues that form intermolecular disulfide bonds were positioned next to peptide sections of lower hydrophobicity, and these cysteine residues are more exposed to the cytosolic conditions, which influence the crosslinking behavior. In addition, coarse-grained Monte Carlo simulations revealed that the protein folding is independent of ionic strength. The potential molecular behavior associated with disulfide bonds, as reported here, increases the biological understanding of seed storage protein function and provides opportunities to tailor their functional properties for different applications.
Toward Unusual‐High Hole Mobility of p‐Channel Field‐Effect‐Transistors (Small 37/2021) (2021)

Field-Effect-Transistors Metal-semiconductor junction is an efficient structure to control the carrier concentration of channel semiconductors, benefiting to the regulation of carrier mobility. In article number 2102323, Lei Liao, Johnny C. Ho, Zai-xing Yang, and co-workers demonstrate that by simply constructing the metal-semiconductor junctions, the peak hole mobility of GaSb nanowire field-effect-transistor can be enhanced to the highest value of 3372 cm2 V−1 s−1 in the atmosphere, showing three times than the un-deposited one.