gebhart/patrepeval huggingface dataset:
Unified Pretraining Framework for Document Understanding (2022)

Document intelligence automates the extraction of information from documents and supports many business applications. Recent self-supervised learning methods on large-scale unlabeled document datasets have opened up promising directions towards reducing annotation efforts by training models with self-supervised objectives. However, most of the existing document pretraining methods are still language-dominated. We present UDoc, a new unified pretraining framework for document understanding. UDoc is designed to support most document understanding tasks, extending the Transformer to take multimodal embeddings as input. Each input element is composed of words and visual features from a semantic region of the input document image. An important feature of UDoc is that it learns a generic representation by making use of three self-supervised losses, encouraging the representation to model sentences, learn similarities, and align modalities. Extensive empirical analysis demonstrates that the pretraining procedure learns better joint representations and leads to improvements in downstream tasks.
Variation in Capsidiol Sensitivity between Phytophthora infestans and Phytophthora capsici Is Consistent with Their Host Range (2014)

Plants protect themselves against a variety of invading pathogenic organisms via sophisticated defence mechanisms. These responses include deployment of specialized antimicrobial compounds, such as phytoalexins, that rapidly accumulate at pathogen infection sites. However, the extent to which these compounds contribute to species-level resistance and their spectrum of action remain poorly understood. Capsidiol, a defense related phytoalexin, is produced by several solanaceous plants including pepper and tobacco during microbial attack. Interestingly, capsidiol differentially affects growth and germination of the oomycete pathogens Phytophthora infestans and Phytophthora capsici, although the underlying molecular mechanisms remain unknown. In this study we revisited the differential effect of capsidiol on P. infestans and P. capsici, using highly pure capsidiol preparations obtained from yeast engineered to express the capsidiol biosynthetic pathway. Taking advantage of transgenic Phytophthora strains expressing fluorescent markers, we developed a fluorescence-based method to determine the differential effect of capsidiol on Phytophtora growth. Using these assays, we confirm major differences in capsidiol sensitivity between P. infestans and P. capsici and demonstrate that capsidiol alters the growth behaviour of both Phytophthora species. Finally, we report intraspecific variation within P. infestans isolates towards capsidiol tolerance pointing to an arms race between the plant and the pathogens in deployment of defence related phytoalexins.
Trilingual Semantic Embeddings of Visually Grounded Speech with Self-Attention Mechanisms (2020)

We propose a trilingual semantic embedding model that associates visual objects in images with segments of speech signals corresponding to spoken words in an unsupervised manner. Unlike the existing models, our model incorporates three different languages, namely, English, Hindi, and Japanese. To build the model, we used the existing English and Hindi datasets and collected a new corpus of Japanese speech captions. These spoken captions are spontaneous descriptions by individual speakers, rather than readings based on prepared transcripts. Therefore, we introduce a self-attention mechanism into the model to better map the spoken captions associated with the same image into the embedding space. We hope that the self-attention mechanism efficiently captures relationships between widely separated word-like segments. Experimental results show that the introduction of a third language improves the average performance in terms of cross-modal and cross-lingual retrieval accuracy, and that the self-attention mechanism added to the model works effectively.
ChemInform Abstract: New Mechanistic Insights into Reductions of Halides and Radicals with Samarium(II) Iodide (1993)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Metabolic Profiling of Human Long-Term Liver Models and Hepatic Clearance Predictions from In Vitro Data Using Nonlinear Mixed-Effects Modeling (2017)

Early prediction of human clearance is often challenging, in particular for the growing number of low-clearance compounds. Long-term in vitro models have been developed which enable sophisticated hepatic drug disposition studies and improved clearance predictions. Here, the cell line HepG2, iPSC-derived hepatocytes (iCell®), the hepatic stem cell line HepaRG™, and human hepatocyte co-cultures (HμREL™ and HepatoPac®) were compared to primary hepatocyte suspension cultures with respect to their key metabolic activities. Similar metabolic activities were found for the long-term models HepaRG™, HμREL™, and HepatoPac® and the short-term suspension cultures when averaged across all 11 enzyme markers, although differences were seen in the activities of CYP2D6 and non-CYP enzymes. For iCell® and HepG2, the metabolic activity was more than tenfold lower. The micropatterned HepatoPac® model was further evaluated with respect to clearance prediction. To assess the in vitro parameters, pharmacokinetic modeling was applied. The determination of intrinsic clearance by nonlinear mixed-effects modeling in a long-term model significantly increased the confidence in the parameter estimation and extended the sensitive range towards 3% of liver blood flow, i.e., >10-fold lower as compared to suspension cultures. For in vitro to in vivo extrapolation, the well-stirred model was used. The micropatterned model gave rise to clearance prediction in man within a twofold error for the majority of low-clearance compounds. Further research is needed to understand whether transporter activity and drug metabolism by non-CYP enzymes, such as UGTs, SULTs, AO, and FMO, is comparable to the in vivo situation in these long-term culture models.
All-fiber multimodal CARS microscopy of live cells (2009)

Coherent anti-Stokes Raman scattering (CARS) microscopy is a promising tool for live cell imaging and has been applied to the study of diseases such as multiple sclerosis, atherosclerosis and hepatitis. Combining PCFs with optimally chirped fs pulses, high performance multimodal (i.e. simultaneous two-photon fluorescence (TPF), second harmonic generation (SHG) and CARS) imaging of live cells and tissues is possible using only a single laser. Here the paper demonstrates a fully operational multimodal live cell and tissue imaging system based on a compact fs Er fiber oscillator system. A key component is a newly developed ultra-highly nonlinear silica fiber (UHNLF) which greatly reduces the peak power requirement for Stokes pulse generation. A commercial fully integrated frequency doubled fs Er fiber laser (IMRA F100) was the pump for TPF and SHG imaging. Here, in this paper a multimodal image of a fixed rabbit atherosclerotic arterial sample where TPF (elastin), SHG (collagen) and CARS (lipid) signals were collected simultaneously. This demonstrates for the first time the feasibility of a compact all-fiber source for multimodal CARS microscopy of live cells and tissue.
Evolving synaptic connections for a silicon neuromorph (2002)

Our VLSI neuromorphs possess extensive dendritic trees with hundreds of excitatory and inhibitory synaptic sites. Useful signal processing can be achieved by evolving the appropriate connections to the synapses using genetic algorithms. In order to reduce the very large solution space, schemes for specifying connections have been borrowed from neural development. Results show the evolution of connections to a single neuromorph for the discrimination of temporal and spatio-temporal patterns.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Hexacoordinated carbon or tetracovalent silicon? (1998)

Hexacoordinate silicon has been claimed to occur in bis(8-dimethylamino-naphth-1-yl)silanes on the basis of X-ray data and NMR spectra. Very much the same effects are shown by a bis(8-dimethylamino-naphth-1-yl)carbinol, pointing to essentially the same bonding in the Si and C compounds. Faced with the choice that either the carbon in the carbinol is hexacoordinate, too, or that the silicon in the silanes is, in fact, tetracovalent, we prefer the latter conclusion. Chirality 10:180–189, 1998. © 1998 Wiley-Liss, Inc.
Tuning electricity generation throughout the year with PV module technology (2020)

Currently, photovoltaic (PV) installations target a maximization of annual energy yield. In the future however, electricity generation may need to match better with the load profiles in a given environment and climate. In particular this will be a challenge for generation across the seasons, where electrical storage is less suitable, and in the built environment, where wind turbines for generation are much more difficult to integrate. In this paper we discuss how this challenge may be addressed with climate- and consumption-specific PV module technology. In particular, we demonstrate how the temperature coefficient of a PV system can impact the energy yield throughout the year. After explaining the concept, we apply our electrical-optical-thermal model to do very accurate physics-based bottom-up simulations in different climates. As such, depending on the climate and latitude, a higher temperature coefficient of the PV module may lead to higher energy yields, mostly during the colder season. We also demonstrate that, if higher temperature coefficients are accompanied by improved low-light performance (tunable using the module’s series resistance), the seasonal gain can be much higher. We indicate the relevance of our assumptions by basing the module performance in the simulations on (datasheets of) commercial modules.
Power-Efficient OFDM via Quantized Channel State Information (2006)

In response to the growing demand for low-cost low-power wireless sensor networks and related applications, we develop bit and power loading algorithms that minimize transmit-power for orthogonal frequency division multiplexing (OFDM) under rate and error probability constraints. Our novel algorithms exploit one of three types of channel state information at the transmitter (CSIT): deterministic (per channel realization) for slow fading links, statistical (channel mean) for fast fading links, and quantized (Q-) CSIT whereby a limited number of bits are fed back from the transmitter to the receiver. By adopting average transmit-power as a distortion metric, a channel quantizer is also designed to obtain a suitable form of Q-CSI. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with a few bits of Q-CSIT.
Robust data transmission with eddy current sensor system (2008)

Nowadays railway supervision systems use information carriers installed along the track to define the train position or to provide information about the track as for example maximum velocities. Current data transmission devices are electronic systems, which are expensive to install and maintain. This paper proposes a novel approach to use an eddy current sensor system, mounted on trains for speed measurements, to receive data coded in a metal bar on the track. The transmission is realized with a quadrature amplitude modulation in combination with the given eddy current sensor system to show a cost-efficient and robust alternative to common railway supervision systems.
Progressive intercarrier and co‐channel interference mitigation for underwater acoustic multi‐input multi‐output orthogonal frequency‐division multiplexing (2012)

ABSTRACT Multi‐input multi‐output orthogonal frequency‐division multiplexing (MIMO‐OFDM) has been actively studied for high data rate communications over the bandwidth‐limited underwater acoustic (UWA) channels. Unlike existing receivers that treat the intercarrier interference (ICI) as additive noise, in this paper, the proposed receiver considers ICI explicitly together with the co‐channel interference (CCI) due to parallel transmissions in MIMO‐OFDM. Using a recently developed progressive receiver framework, the proposed receiver starts with low‐complexity ICI‐ignorant processing and then progresses to ICI‐aware processing with increasing ICI levels. The key components of the proposed receiver include the following: (1) compressed sensing‐based sparse channel estimation, (2) soft‐input soft‐output minimum mean square error/Markov chain Monte Carlo detector for interference mitigation, and (3) soft nonbinary low‐density parity check decoding. In addition to simulation, we use real data from the Surface Processes and Acoustic Communications Experiment 2008 (SPACE08) and the Mobile Acoustic Communications Experiment 2010 (MACE10) to verify the system performance, where the transmitter in SPACE08 was stationary and that in MACE10 was slowly moving. Simulation and experimental results show that explicitly addressing ICI and CCI significantly improves the performance of MIMO‐OFDM in UWA systems. Copyright © 2012 John Wiley &amp; Sons, Ltd.
A 31.5dBm outphasing class-D power amplifier in 45nm CMOS with back-off efficiency enhancement by dynamic power control (2011)

A transformer-combined fully Integrated outphasing class-D PA In 45nm CMOS achieves 31.5dBm peak output power at 2.4GHz with 27% efficiency, and supports over 86dB of output power range. The PA employs Dynamic Power Control (DPC) whereby sections of the PA are turned on-off dynamically according to the OFDM amplitude to reduce power dissipation at backoff. The PA delivers 24.8dBm average power while meeting 64-QAM WLAN requirements. PAE is 16% when using DPC, which represents a 33% efficiency enhancement compared to the DPC-disabled mode. At lower average power of 20.5dBm, DPC enables a 140% enhancement in average efficiency, hence battery life.
Figure S2 from Kindlin-2 Regulates the Growth of Breast Cancer Tumors by Activating CSF-1–Mediated Macrophage Infiltration (2023)

&lt;p&gt;This figure contains tumor staining additional markers to support Figure 3F and Figure 3I&lt;/p&gt;
ChemInform Abstract: Nazarov Cyclization of 4‐Cycloalkylidene‐5‐(trimethylsilyl)pent‐1‐en‐3‐one Derivatives. Synthesis of Spiro[4.5]decane, Spiro[4.4]nonane, and Their Derivatives. (2000)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Room temperature midinfrared electroluminescence from InAs quantum dots (2009)

We demonstrate room temperature midinfrared electroluminescence from intersublevel transitions in self-assembled InAs quantum dots. The dots are grown in GaAs/AlGaAs heterostructures designed to maximize current injection into dot excited states while preferentially removing electrons from the ground states. As such, these devices resemble quantum cascade lasers. However, rigorous modeling of carrier transport through the devices indicates that the current transport mechanism for quantum dot active regions differs from that of quantum-well-based midinfrared lasers. We present the calculated energy states and transport mechanism for an intersublevel quantum dot emitter, as well as experimental electroluminescence data for these structures.
Extracting collective motions underlying nucleosome dynamics via nonlinear manifold learning (2019)

The identification of effective collective variables remains a challenge in molecular simulations of complex systems. Here, we use a nonlinear manifold learning technique known as the diffusion map to extract key dynamical motions from a complex biomolecular system known as the nucleosome: a DNA-protein complex consisting of a DNA segment wrapped around a disc-shaped group of eight histone proteins. We show that without any a priori information, diffusion maps can identify and extract meaningful collective variables that characterize the motion of the nucleosome complex. We find excellent agreement between the collective variables identified by the diffusion map and those obtained manually using a free energy-based analysis. Notably, diffusion maps are shown to also identify subtle features of nucleosome dynamics that did not appear in those manually specified collective variables. For example, diffusion maps identify the importance of looped conformations in which DNA bulges away from the histone complex that are important for the motion of DNA around the nucleosome. This work demonstrates that diffusion maps can be a promising tool for analyzing very large molecular systems and for identifying their characteristic slow modes.
Boosting 4G Networks with Spatial Interference Management Under Feedback Constraints : A Noncooperative Downlink Transmission Scheme (2013)

In this article, we focus on the downlink direction of cellular multiuser multiple-input, multiple-output (MIMO) systems based on orthogonal frequency division multiplex (OFDM) waveforms. Our target system is operated in the frequency division duplex (FDD) mode, while all base stations (BSs) use the same frequency spectrum for downlink transmission. State-of-the-art literature proved that the system performance is mainly limited by the existing cochannel interference (CCI). Hence, mitigating these effects would improve the achievable system throughput beyond current benchmarks of cellular systems.
Confluence of pattern recognition and signal processing: application of Al‐Alaoui pattern recognition algorithm to digital filters design (2015)

A weighted mean square error (WMSE) approach to optimising digital filters is delineated. It is applied in the current work to optimising the classical Al‐Alaoui IIR differentiators to obtain new improved wideband differentiators of varying orders. These can be directly used for analog to digital conversion and in many digital signal processing applications. The weighted MSE approach is motivated by the Al‐Alaoui WMSE approach to pattern recognition. In addition, the differentiators are converted to integrators of similar orders that are further optimised. Various examples and comparisons are presented to demonstrate the viability of the proposed approach.
Assessment of prevalence of anatomical variations and pathosis of the maxillary sinuses using cone-beam computed tomography in a sample of the population of Saudi Arabia (2018)

Background: Cone-beam computed tomography (CBCT) technology has been a useful tool for decreasing dental treatment complications and ensuring more predictable treatment outcomes. Objectives: This study aimed to assess the prevalence of maxillary sinuses status in regard to anatomical variations and pathosis using CBCT as a diagnostic tool, in asymptomatic patients who are willing to receive dental implants at King Abdulaziz University Dental Hospital in Jeddah, Saudi Arabia. Materials and Methods: Both sinuses in 263 patients (140 females and 96 males) were evaluated using iCAT Classic scanner to acquire the total of 526 CBCT images. Two calibrated dental radiology consultants evaluated the CBCT of the maxillary sinuses images using the Vision software (Imaging Sciences International, Hatfield, PA, USA) for the following finding: number of teeth in intimate relation with the maxillary sinus and the presence of septa (as anatomical variations) and the presence, extent, and configuration of mucosal thickening (MT) as sign of pathosis (mucositis). Results: The highest prevalence of dental proximity to the sinus wall was between the first left premolars and the anterior sinus wall (57.14%) followed by the second right premolars (56.14%). The presence of septa in both right and left maxillary sinuses was 54.37% and 57.41%, respectively. The prevalence of sinus pathosis was 52.7%. Interestingly, 87.07% of the MT cases were due to nonodontogenic origin compared to 12.93% of odontogenic-related pathosis. Conclusions: Preoperative radiographic assessment using CBCT is highly recommended before dental implant placement in our population due to the high anatomical variations and pathosis rates, to allow proper assessment and diagnosis of maxillary sinus disease, if present. The assessment of maxillary sinus disease before surgical intervention will provide a higher standard of care and decrease the risk of complications and failures of dental implants.
Impact of electrostriction in single-channel 40 Gbit/s undersea systems in the presence of dispersion-management or optical 3R regeneration (2002)

We demonstrate that electrostriction-induced interaction is responsible for limitations in 40 Gbit/s single-channel transmission systems performance even in presence of dispersion-management and that periodic optical 3R regeneration totally suppresses the phenomenon.
Diamonds with a high density of nitrogen-vacancy centers for magnetometry applications (2009)

Nitrogen-vacancy (NV) centers in millimeter-scale diamond samples were produced by irradiation and subsequent annealing under varied conditions. The optical and spin-relaxation properties of these samples were characterized using confocal microscopy, visible and infrared absorption, and optically detected magnetic resonance. The sample with the highest ${\text{NV}}^{\ensuremath{-}}$ concentration, approximately 16 ppm $(2.8\ifmmode\times\else\texttimes\fi{}{10}^{18}\text{ }{\text{cm}}^{\ensuremath{-}3})$, was prepared with no observable traces of neutrally charged vacancy defects. The effective transverse spin-relaxation time for this sample was ${T}_{2}^{\ensuremath{\ast}}=118(48)\text{ }\text{ns}$, predominately limited by residual paramagnetic nitrogen which was determined to have a concentration of 49(7) ppm. Under ideal conditions, the shot-noise limited sensitivity is projected to be $\ensuremath{\sim}150\text{ }\text{fT}/\sqrt{\text{Hz}}$ for a $100\text{ }\ensuremath{\mu}\text{m}$-scale magnetometer based on this sample. Other samples with ${\text{NV}}^{\ensuremath{-}}$ concentrations from 0.007 to 12 ppm and effective relaxation times ranging from 27 to over 291 ns were prepared and characterized.
Improved rendition of text and lines in inkjet and electrophotographic printers (2006)

In this work, we investigate the perception of artifacts introduced by specific printing technologies on the quality of printed text and lines. In the first part, we investigate the effect of the dot characteristics on the quality of line-based images produced by an inkjet printer. We develop an image processing algorithm for analyzing printed dots and study the effect of the dot characteristics on perceived printalignment. We establish the perceptual preferences of human observers with respect to alignment via a set of psychophysical experiments. In the second part, we study artifacts introduced by the electrophotographic process that make certain edges appear blurred. We design image processing algorithms to pre-compensate for the effects of the artifacts on the printed image quality.\nWe base the design of the image processing tools on psychophysical theory regarding perception of blur and on empirical models of the electrophotographic process. We develop a memory efficient algorithm that is readily implementable in a typical printer's hardware.