gebhart/patrepeval huggingface dataset:
Bridge model updating using distributed sensor data (2016)

One of the challenges of managing bridge infrastructure is developing numerical models that can be used to accurately assess highly redundant bridge systems. One way to refine the model is to use sensor data to perform model updating. However, conventional sensors provide limited data with which to update the model, given the many degrees of freedom associated with indeterminate structures, resulting in a large potential error. Distributed sensing technologies such as digital image correlation and fibre optic strain sensors have the potential to provide more extensive data sets for model updating. This paper presents a case study of a reinforced concrete bridge that was modelled numerically to predict the bridge performance. The bridge was then load tested, and distributed sensor data were acquired. Using the sensor data, the numerical model was updated and refined estimates of the bridge behaviour were obtained. The initial and final models produced estimates of bridge behaviour that differed by an order of magnitude, illustrating the importance of sensor data for some bridge assessments. Additionally, the model indicated that the stiffness of the bridge had increased with time owing to an increase in the elastic modulus of the concrete and the development of compressive stresses.
Ultrabright Fluorescent and Lasing Microspheres from a Conjugated Polymer (2018)

Abstract Fluorescent microspheres are used for biomarkers, assay substrates, chemical diagnostics, flow cytometry, and biological imaging. These applications demand the highest fluorescence intensity achievable; however, concentration quenching limits the amount of dye that can be practically incorporated in conventional fluorescent microspheres. Conjugated polymers (CPs) can be less susceptible to concentration quenching, suggesting that they can be excellent candidates for a new class of light‐emitting microspheres. Due to their long‐chain‐conjugated backbone, however, CPs can be resistant to forming smoothly curved or spherical structures. Here, strongly fluorescent CP microspheres as large as 100 µm in diameter are synthesized. Whispering gallery modes (WGMs) appear in the fluorescence spectra, and the microspheres show clear evidence of lasing above a threshold pump intensity. These conjugated polymer beads are up to 50 times larger than CP microspheres obtained by other methods, and they exceed the emission intensity of conventional fluorescent microspheres by more than an order of magnitude.
Fast Organic Vapor Phase Deposition of Thin Films in Light-Emitting Diodes (2020)

Fast deposition of thin films is essential for achieving low-cost, high-throughput phosphorescent organic light-emitting diode (PHOLED) production. In this work, we demonstrate rapid and uniform growth of semiconductor thin films by organic vapor phase deposition (OVPD). A green PHOLED comprising an emission layer (EML) grown at 50 Å/s with bis[2-(2-pyridinyl-<i>N</i>)phenyl-<i>C</i>](acetylacetonato)iridium(III) (Ir(ppy)<sub>2</sub>(acac)) doped into 4,4'-bis(<i>N</i>-carbazolyl)-1,1'-biphenyl (CBP) exhibits a maximum external quantum efficiency of 20 ± 1%. The morphology, charge transport properties, and radiative efficiency under optical and electrical excitation of the PHOLED EML are investigated as functions of the deposition rate <i>via</i> both experimental and theoretical approaches. The EML shows no evidence for gas phase nucleation of the organic molecules at deposition rates as high as 50 Å/s. However, the roll-off in quantum efficiency at high current progressively increases with deposition rate due to enhanced triplet-polaron annihilation. The roll-off results from accumulation of stress within the PHOLED EML that generates a high density of defect states. The defects, in turn, act as recombination sites for triplets and hole polarons, leading to enhanced triplet-polaron annihilation at high current. We introduce a void nucleation model to describe the film morphology evolution that is observed using electron microscopy.
[On amino acid antagonists: beta-diketoesters and their corresponding gamma-enolethers]. (1977)

Starting with well known beta-diketoesters the corresponding gamma-enolethers are synthesized and described. Both classes of compounds inhibited the growth of some microorganisms. The inhibition is abolishable by addition of certain amino acids to the definite medium. A possible mechanism of inhibition is discussed and compared with the mechanism of some beta,gamma-unsaturated alpha-amino acids. The known unsaturated alpha-amino acids, their origin and their biological activity are summarized in two tables.
Investigational RNAi Therapeutic Targeting C5 Is Efficacious in Pre-clinical Models of Myasthenia Gravis (2019)

Complement-mediated damage to the neuromuscular junction (NMJ) is a key mechanism of pathology in myasthenia gravis (MG)<b>,</b> and therapeutics inhibiting complement have shown evidence of efficacy in the treatment of MG. In this study, we describe the development of a subcutaneously administered N-acetylgalactosamine (GalNAc)-conjugated small interfering RNA (siRNA) targeting the C5 component of complement that silences C5 expression in the liver (ALN-CC5). Treatment of wild-type rodents with ALN-CC5 resulted in robust and durable suppression of liver C5 expression. Dose-dependent serum C5 suppression was observed in non-human primates, with a lowering of serum C5 of up to 97.5% and the concomitant inhibition of serum complement activity. C5 silencing was efficacious in ameliorating disease symptoms in two standard rat models of MG<b>,</b> demonstrating the key role of circulating C5 in pathology at the NMJ. Improvement in disease activity scores and NMJ pathology was observed at intermediate levels of complement activity inhibition<b>,</b> suggesting that complete ablation of complement activity may not be required for efficacy in MG. The pre-clinical studies of ALN-CC5 and efficacy of C5 silencing in rat models of MG support further clinical development of ALN-CC5 as a potential therapeutic for the treatment of MG and other complement-mediated disorders.
Fuel Economy Benefit of Cylinder Deactivation - Sensitivity to Vehicle Application and Operating Constraints (2001)

&lt;div class="htmlview paragraph"&gt;A Variable Displacement Engine (VDE) improves fuel economy by deactivating half the cylinders at light load. The actual fuel economy benefit attained in the vehicle depends on how often cylinders can be deactivated, which is a function of test cycle, engine size, and vehicle weight. In practice, cylinder deactivation will also be constrained by NVH (noise, vibration, and harshness).&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;This paper presents fuel economy projections for VDE in several different engine and vehicle applications.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;Sensitivity to NVH considerations is quantified by calculating fuel economy with and without cylinder deactivation in various operating modes: idle, low engine speed, 1st and 2nd gear, and warm-up after cold start. The effects of lug limits and calibration hysteresis are also presented.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;All projections are based on engine dynamometer data with and without cylinder deactivation, in conjunction with a second-by-second computer simulation of various test cycles (EPA City and Highway, European NEDC, and Japanese 10-15 Mode).&lt;/div&gt;
Predicting the Results of Chemical Vapor Deposition Growth of Suspended Carbon Nanotubes (2009)

The successful growth of suspended carbon nanotubes is normally based on purely empirical results. Here we demonstrate the ability to predict the successful suspension of nanotubes across a range of trench widths by combining experimental growth data with a theoretical description of nanotube mechanics at the growth temperature. We show that rare thermal oscillations much larger than the rms amplitude combined with the large nanotube-substrate adhesion energy together are responsible for unsuccessful nanotube suspensions. We derive an upper limit on the number of deleterious nanotube-substrate interactions that can be tolerated before successful growth becomes impossible, and we are able to accurately explain literature reports of suspended nanotube growth. The methodology developed here should enable improved growth yields of suspended nanotubes, and it provides a framework in which to analyze the role of nanotube-substrate interactions during nanotube growth by chemical vapor deposition.
Guest Editorial Introduction to the Focused Section on Adaptive Learning and Control for Advanced Mechatronics Systems (2022)

Mechatronics, which cooperate with or substitute human operators to perform a growing variety of tasks, are getting increasingly complex in order to implement difficult operations with comprehensive utilization of sensors, vision modules, actuators, controllers, etc., and the intelligent algorithms with learning capability running behind. Nowadays, mechatronics task in a wide range of fields requiring intelligent and flexible actions in unstructured/fast-changing working environments, which brought great challenges to decision, planning and control of advanced mechatronics systems. In recent years, the adaptive and learning-based methods have shown their vitality on perception, recognition, situation understanding, communication and trajectory planning, etc., with a great amount of proved successful applications in many cross disciplines [A1]–[A3].
Sorption and transport studies of water in Kapton polymide. I (1985)

Sorption isotherms and diffusion coefficients of water in a 0.3-mil Kapton polyimide film at 30, 45, and 60°C are reported. The data are well described by the dual mode sorption and transport models at low activities. At high penetrant activities, clustering of water is suggested by a Zimm–Lundberg analysis of the sorption data and the fact that the diffusion coefficient for water decreases with increasing external vapor activity. The effect of temperature on the diffusion coefficients at infinite dilution and the dual mode sorption parameters kD, b, and C are presented and discussed. The magnitude of the activation energy of the diffusion coefficient at infinite dilution, 5.4 kcal/mol, is smaller than the corresponding activation energy in more flexible chain polymers, perhaps suggesting that rather small backbone motions are associated with diffusion of water through the Kapton matrix. The predictions for the isosteric enthalpy of sorption from the dual mode model are presented and compared with the values determined from graphical analysis of the sorption isotherms performed independently without reference to the dual mode sorption model.
A Blue-Luminescent Dendritic Rod:  Poly(phenyleneethynylene) within a Light-Harvesting Dendritic Envelope (1999)

ADVERTISEMENT RETURN TO ISSUEPREVCommunicationNEXTA Blue-Luminescent Dendritic Rod: Poly(phenyleneethynylene) within a Light-Harvesting Dendritic EnvelopeTakafumi Sato, Dong-Lin Jiang, and Takuzo AidaView Author Information Department of Chemistry and Biotechnology Graduate School of Engineering The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo 113-8656, Japan Cite this: J. Am. Chem. Soc. 1999, 121, 45, 10658–10659Publication Date (Web):October 30, 1999Publication History Received5 July 1999Revised30 September 1999Published online30 October 1999Published inissue 1 November 1999https://pubs.acs.org/doi/10.1021/ja9922983https://doi.org/10.1021/ja9922983rapid-communicationACS PublicationsCopyright © 1999 American Chemical SocietyRequest reuse permissionsArticle Views1856Altmetric-Citations268LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-AlertscloseSupporting Info (1)»Supporting Information Supporting Information SUBJECTS:Absorption,Dendrons,Ethers,Fluorescence,Luminescence Get e-Alerts
Implant Survivorship and Complication Rates after Total Knee Arthroplasty with a Third-Generation Cemented System (2005)

To the Editor: The cited manuscript that appeared in the January 2005 issue of Clinical Orthopaedics and Related Research (430:117-124, 2005) contained a spelling error in the name of an author, R. Michael Meneghini. The error was present on all versions of the manuscript throughout the publication process and inadvertently missed by the authors. Therefore, the error was not a fault of the journal editorial department and was not noticed until final publication occurred. The authors appreciate the cooperation of the editorial department in noting the correct spelling of the author’s name.
Wheeler's current sheet concept and Munk's wideband arrays (2012)

About 60 years ago, Wheeler proposed the current sheet as a means to study (infinite) array impedance variations during scanning. The current sheet, viewed as the limiting case of an array of very small and closely spaced dipoles, was proposed by Wheeler as a way to model the array's scanning properties and matching issues. Much later, Ben Munk noted that realization of the current sheet in presence of a ground plane was critical to developing conformal wideband arrays. Wheeler's 1965 paper therefore provided vital inspiration that influenced future wideband antenna designers.
Memory organization for video algorithms on programmable signal processors (2002)

In this paper, several DSP system design principles are presented which are valid for a large class of memory-intensive algorithms. Our main focus lies on the optimization of the memory and I/O, since these are dominant cost factors in the domain of video and imaging applications. This has resulted in several formalizable mapping principles, which allow to prevent the memory from becoming a bottleneck. First, it as shown that for this class of applications, compile-time data caching decisions not only have a large effect on the performance, but also can have an even larger effect on the overall system cost and power consumption. This is illustrated by means of experiments in which the whole range of no cache up to large cache sizes is scanned. Next, it is shown that when enforcing constant I/O rates to reduce buffer sizes, the area gain may be far more important than the small performance decrease associated with it. A technique to achieve this in an efficient way is proposed. The main test-vehicle which is used throughout the paper to demonstrate our approach is the class of motion estimation type algorithms.
Joint Heterogeneous Feature Learning and Distribution Alignment for 2D Image-Based 3D Object Retrieval (2019)

2D image-based 3D object retrieval is a novel but challenging task for 3D object retrieval. In this paper, we propose a 2D image-based 3D object retrieval method via joint heterogeneous feature learning and distribution alignment. Specifically, we propose to learn a mapping function in the Grassmann manifold to reduce the divergence of heterogeneous features of 2D images and 3D objects. We further employ the data distribution alignment method to adaptively integrate both marginal and conditional distributions. We embed both terms into the objective function to learn a domain-invariant classifier based on structural risk minimization. The output domain-invariant features of 2D images and 3D objects can be utilized for 2D image-based 3D object retrieval. Since there is lack of large-scale dataset for the evaluation of this task, we build two new datasets, MI3DOR and MI3DOR-2. We compare the proposed method against the representative methods for domain adaption and explore the influence of different components of the objective functions and key parameter. Comparison experiments show the superiority of this method.
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects (2023)

We present the evaluation methodology, datasets and results of the BOP Challenge 2022, the fourth in a series of public competitions organized with the goal to capture the status quo in the field of 6D object pose estimation from an RGB/RGB-D image. In 2022, we witnessed another significant improvement in the pose estimation accuracy – the state of the art, which was 56.9 AR <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> in 2019 (Vidal et al.) and 69.8 AR <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> in 2020 (CosyPose), moved to new heights of 83.7 AR <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> (GDRNPP). Out of 49 pose estimation methods evaluated since 2019, the top 18 are from 2022. Methods based on point pair features, which were introduced in 2010 and achieved competitive results even in 2020, are now clearly outperformed by deep learning methods. The synthetic-to-real domain gap was again significantly reduced, with 82.7 AR <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> achieved by GDRNPP trained only on synthetic images from BlenderProc. The fastest variant of GDRNPP reached 80.5 AR <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> with an average time per image of 0.23s. Since most of the recent methods for 6D object pose estimation begin by detecting/segmenting objects, we also started evaluating 2D object detection and segmentation performance based on the COCO metrics. Compared to the Mask R-CNN results from CosyPose in 2020, detection improved from 60.3 to 77.3 AP <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> and segmentation from 40.5 to 58.7 AP <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</inf> . The online evaluation system stays open and is available at: bop.felk.cvut.cz.
Enantio- and Regioselective CuH-Catalyzed Hydroamination of Alkenes (2013)

A highly enantio- and regioselective copper-catalyzed hydroamination reaction of alkenes has been developed using diethoxymethylsilane and esters of hydroxylamines. The process tolerates a wide variety of substituted styrenes, including trans-, cis-, and β,β-disubstituted styrenes, to yield α-branched amines. In addition, aliphatic alkenes coupled to generate exclusively the anti-Markovnikov hydroamination products.
Using historical click data to increase interleaving sensitivity (2013)

Interleaving is an online evaluation method to compare two alternative ranking functions based on the users' implicit feedback. In an interleaving experiment, the results from two ranking functions are merged in a single result list and presented to the users. The users' click feedback on the merged result list is analysed to derive preferences over the ranking functions. An important property of interleaving methods is their sensitivity, i.e. their ability to reliably derive the comparison outcome with a relatively small amount of user behaviour data. This allows testing of changes in the search engine ranking functions frequently and, as a result, rapid iterations in developing search quality improvements can be achieved. In this paper we propose a novel approach to further improve interleaving sensitivity by using pre-experimental user behaviour data. In particular, the click history is used to train a click model, which is then used to predict which interleaved result pages are likely to contribute to the experiment outcome. The probabilities of presenting these interleaved result pages to the users are then optimised, such that the sensitivity of interleaving is maximised. In order to evaluate the proposed approach, we re-use data from six actual interleaving experiments, previously performed by a commercial search engine. Our results demonstrate that the proposed approach outperforms a state-of-the-art baseline, achieving up to a median of 48% reduction in the number of impressions for the same level of confidence.
Health benefits of barley for diabetes (2020)

Type 2 diabetes (T2D) is one of the most prevalent metabolic disorders in the United States. Increased blood glucose levels and improper crucial metabolism ensuing from insulin action, insulin secretion defect, or both are characteristics of this disease. The risk of developing T2D is associated with many factors, including obesity, race, inactivity, and genetics. Increased whole-grain (WG) consumption has been reported to lower the risk of obesity and T2D. Among WGs, barley shows a comparative advantage in its fiber content, especially the soluble fiber, beta-glucan (β-glucan), an active component credited for this benefit. Barley also contains important phytochemicals, mostly intertwined with its fiber, reported to also offer glycemic response benefits. The mechanism by which barley exerts these changes in glycemic response is not entirely understood. However, the physical properties of barley fiber, the function of microbial metabolites of fiber, short chain fatty acids, and the beneficial effects of its phytochemicals through multiple pathways have all been reported as the potential mechanisms for its antidiabetic effects. This review summarizes recent studies concerning the health-promoting benefit of barley in preventing and moderating the risk factors associated with diabetes and the potential underlying mechanisms.