gebhart/patrepeval huggingface dataset:
Dyed Microspheres for Quantification of UV Dose Distributions: Photochemical Reactor Characterization by Lagrangian Actinometry (2006)

Lagrangian actinometry represents a new method of photochemical reactor characterization. The method is based on an application of dyed microspheres, which were developed by attachment of (E)-5-[2-(methoxycarbonyl)ethenyl]cytidine (hereafter referred to as S) to polystyrene microspheres. S is a nonfluorescent molecule that when subjected to ultraviolet (UV) irradiation yields a single product, 3-β-D-ribofuranosyl-2,7-dioxopyrido[2,3-d]pyrimidine (hereafter referred to as P), which displays a strong fluorescence signal. Dyed microspheres were subjected to UV irradiation under a collimated beam and using a single-lamp, monochromatic (low pressure Hg), continuous-flow reactor. In parallel with these experiments, a biodosimetry experiment was conducted using Bacillus subtilis spores as the challenge organism. Particle-specific fluorescence intensity measurements were conducted on samples from the collimated-beam experiments and the flow-through reactor experiments by flow cytometry. Estimates of the dose distribution delivered by the flow-through reactor for each operating condition were developed by deconvolution of data resulting from flow cytometry analysis of these samples. In conjunction with these experiments, a numerical model was developed to simulate the behavior of the reactor system. A commercially available computational fluid dynamics package was used to simulate the flow field, while line-source integration was used to simulate the irradiance field. A particle-tracking algorithm was employed to interrogate the flow and irradiance field simulations for purposes of developing particle-specific (Lagrangian) estimates of dose delivery. Dose distribution estimates from the microspheres assays and the numerical simulations were combined with the measured dose–response behavior of B. subtilis spores to yield estimates of spore inactivation in the flow-through experiments. For the range of operating conditions used in these experiments, predictions of spore inactivation based on dose distribution estimates from both methods were in good agreement with each other, and with the measured spore inactivation behavior. Lagrangian actinometry is capable of yielding accurate, detailed measurements of dose delivery by continuous-flow UV systems. This method represents a substantial improvement over existing experiment-based methods of UV reactor characterization (e.g., biodosimetry) in that it yields a measurement of the dose distribution for a given operating condition. This method also represents an improvement over existing methods for validation of numerical simulations. Specifically, because this method yields a measurement of the dose distribution, it is possible to compare these measurements with predicted dose distributions from the numerical simulation. The combined application of biodosimetry, numerical modeling, and Lagrangian actinometry represents an extremely robust approach to reactor characterization and validation.
Interaction Between Intelligent Well Applications and Reservoir Management—A Comprehensive Thermal Modeling Technology for IWS Well (2008)

Abstract Can we predict how Intelligent Well Systems (IWS) and equipment operate in various wellbore conditions to meet production enhancement targets? This paper presents a developed modeling technique and demonstrates how this technology can guide IWS equipment operations/design to meet production enhancement targets for a deepwater multiple-zone IWS water injection well. Since IWS solutions typically address multi-zone (commingled) production or injection wells, it is important to develop a well deliverability model. Within this model, several key features include; a.) Multi-zone inflow/delivery including the unique zonal reservoir and fluid properties, b.) Multiple production/injection flowpaths to accommodate tubing flow for one zone and annulus/tubing flow for other zones, c.) Simulation of the effect upon wellbore pressure and flow distribution due to geometry changes within a completion string (i.e., gravel pack system, flow control equipment, etc), d.) Simulation of the fluid temperature profile and the effect on pressure and flow profile. Industry-available nodal analysis products have historically shown limitations in these types of applications. To fill this purpose, a comprehensive thermal model and an integrated analysis tool have been developed. The modeling results provide an insight into how choking of downhole valves and tubing wellhead pressure impacts the injection fluid flow distribution. For any IWS operation scenario, the flow distributions, wellbore pressure profile, fluid temperature profile, and the fluid velocity profile can be predicted. This assists in determining any erosion concerns on equipment, flowing differential pressures through the valves and expected loads from temperature changes. This flexibility is the added value, where operators can choose the operational configuration to achieve their production objectives. The model results have been compared with several third party softwares and real case production data. Analysis and comments of the comparison are provided.
Model-Based Detection of Leaks and Blockages in Pipes (2000)

This paper deals with a model-based strategy for detecting leaks and blockages in a network of pipes. The fault detection and isolation (FDI) system uses a Kalman filter and a model of the piping system to decide whether the system is operating in a normal or failed state, and to distinguish the type of fault. While the idea of using Kalman filters is quite old, its application in the present case is novel, as is the formulation of the FDI system that uses only one model. The theory is backed by experimental validation on a test rig.
Development of reagents and assays for the detection of pathogenic Burkholderia species (2010)

Rapid detection of the category B biothreat agents Burkholderia pseudomallei and Burkholderia mallei in acute infections is critical to ensure that appropriate treatment is administered quickly to reduce an otherwise high probability of mortality (ca. 40% for B. pseudomallei). We are developing assays that can be used in clinical laboratories or security applications for the direct detection of surface-localized and secreted macromolecules produced by these organisms. We present our current medium-throughout approach for target selection and production of Burkholderia macromolecules and describe the generation of a Fab molecule targeted to the B. mallei BimA protein. We also present development of prototype assays for detecting Burkholderia species using anti-lipopolysaccharide antibodies.
Scalable clustering and keyword suggestion for online advertisements (2009)

We present an efficient Bayesian online learning algorithm for clustering vectors of binary values based on a well known model, the mixture of Bernoulli profiles. The model includes conjugate Beta priors over the success probabilities and maintains discrete probability distributions for cluster assignments. Clustering is then formulated as inference in a factor graph which is solved efficiently using online approximate message passing. The resulting algorithm has three key features: a) it requires only a single pass across the data and can hence be used on data streams, b) it maintains the uncertainty of parameters and cluster assignments, and c) it implements an automatic step size adaptation based on the current model uncertainty. The model is tested on an artificially generated toy dataset and applied to a large scale real-world data set from online advertising, the data being online ads characterized by the set of keywords to which they have been subscribed. The proposed approach scales well for large datasets, and compares favorably to other clustering algorithms on the ads dataset. As a concrete application to online advertising we show how the learnt model can be used to recommend new keywords for given ads.
Computer-aided detection system for clustered microcalcifications: comparison of performance on full-field digital mammograms and digitized screen-film mammograms (2007)

We have developed a computer-aided detection (CAD) system to detect clustered microcalcifications automatically on full-field digital mammograms (FFDMs) and a CAD system for screen-film mammograms (SFMs). The two systems used the same computer vision algorithms but their false positive (FP) classifiers were trained separately with sample images of each modality. In this study, we compared the performance of the CAD systems for detection of clustered microcalcifications on pairs of FFDM and SFM obtained from the same patient. For case-based performance evaluation, the FFDM CAD system achieved detection sensitivities of 70%, 80% and 90% at an average FP cluster rate of 0.07, 0.16 and 0.63 per image, compared with an average FP cluster rate of 0.15, 0.38 and 2.02 per image for the SFM CAD system. The difference was statistically significant with the alternative free-response receiver operating characteristic (AFROC) analysis. When evaluated on data sets negative for microcalcification clusters, the average FP cluster rates of the FFDM CAD system were 0.04, 0.11 and 0.33 per image at detection sensitivity level of 70%, 80% and 90% compared with an average FP cluster rate of 0.08, 0.14 and 0.50 per image for the SFM CAD system. When evaluated for malignant cases only, the difference of the performance of the two CAD systems was not statistically significant with AFROC analysis.
High-power-factor quasi-resonant flyback converters draw sinusoidal input current (2015)

This paper presents a novel control methodology that enables high-power-factor quasi-resonant flyback converters with peak current mode control to ideally draw a sinusoidal current from the input source, thus performing like boost converters operated in the same way. It is a well-known fact that the traditional quasi-resonant control methodology, used in a number of control chips commercially available, when applied to high-power-factor flyback converters provides an inherently distorted input current. Although the resulting distortion level is such that compliancy with IEC61000-3-2 regulation on the limits for harmonic current emissions can be easily achieved, recently this inherent distortion is becoming a problem in Solid-state Lighting (SSL), where this topology is extremely popular. In fact with the traditional method it is difficult to meet the Total Harmonic Distortion (THD) target (<; 10% or even lower) that is becoming a market requirement in some geographical areas [1]-[3]. The novel control method aims to overcome this issue.
Adaptive reshaping for next generation video codec (2018)

Various earlier work in MPEG/JCTVC have shown that out-loop reshaping, which modifies the video signal in preprocessing before encoding and post-processing after decoding in an end-to-end video compression workflow, can improve subjective quality of coded High Dynamic Range (HDR) and Wider Color Gamut (WCG) content compressed using HEVC. However, the requirement of not making normative changes to the HEVC specification has significantly constrain the design and optimization of the reshaper. In April 2018, The Joint Video Experts Team (JVET) has launched a project to develop a new video coding standard to be known as Versatile Video Coding (VVC). This opens the door to exploit possibilities of the reshaper design inside of the core video codec. In this paper, an in-loop architect of reshaper is presented. Preliminary results suggest that the in-loop reshaping architect can retain the functionality of out-loop reshaper. In addition, the in-loop design can resolve many limitations of the out-loop design and can be used as a general coding tool for general video content not limited to HDR.
Cryogenic Memory Architecture Integrating Spin Hall Effect based Magnetic Memory and Superconductive Cryotron Devices (2020)

One of the most challenging obstacles to realizing exascale computing is minimizing the energy consumption of L2 cache, main memory, and interconnects to that memory. For promising cryogenic computing schemes utilizing Josephson junction superconducting logic, this obstacle is exacerbated by the cryogenic system requirements that expose the technology's lack of high-density, high-speed and power-efficient memory. Here we demonstrate an array of cryogenic memory cells consisting of a non-volatile three-terminal magnetic tunnel junction element driven by the spin Hall effect, combined with a superconducting heater-cryotron bit-select element. The write energy of these memory elements is roughly 8 pJ with a bit-select element, designed to achieve a minimum overhead power consumption of about 30%. Individual magnetic memory cells measured at 4 K show reliable switching with write error rates below 10<sup>-6</sup>, and a 4 × 4 array can be fully addressed with bit select error rates of 10<sup>-6</sup>. This demonstration is a first step towards a full cryogenic memory architecture targeting energy and performance specifications appropriate for applications in superconducting high performance and quantum computing control systems, which require significant memory resources operating at 4 K.
Broad beam ultrasonic transducer (1995)

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Valentin Magori, Thomas Möckl; Broad beam ultrasonic transducer. J. Acoust. Soc. Am. 1 August 1995; 98 (2): 683. https://doi.org/10.1121/1.413591 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAcoustical Society of AmericaThe Journal of the Acoustical Society of America Search Advanced Search |Citation Search
Control of ripening. (1994)

Ripening of fleshy fruits involves major changes in physiology and biochemistry that alter their colour, flavour, texture, aroma and nutritional value. These changes affect all cell compartments and require the expression of new genes encoding enzymes that catalyse reactions essential for the development of quality attributes. In climacteric fruits, such as tomato, ethylene functions as a hormone to stimulate changes in gene expression required for ripening. Molecular cloning experiments have led to the isolation of cDNAs encoding many ripening proteins. This has enabled the identification and manipulation of novel plant genes encoding enzymes involved in cell wall texture change, carotenoid biosynthesis, ethylene synthesis and the identification of gene control regions involved in fruit-specific, ripening-specific, and ethylene-regulated gene expression. Antisense and partial sense gene techniques have been developed to generate genetically modified plant lines in which specific genes have been permanently inactivated. These fundamental studies have led to production and evaluation of genetically modified tomato lines with improved colour, texture, storage life, and processing characteristics. Zeneca Seeds has established a new business division, the aim of which is to utilize these techniques for the development of improved fruit and vegetable varieties. In collaboration with Petoseed, Zeneca Seeds is in the process of transferring the genes leading to quality im provement of tomatoes to Petoseed’s elite tomato germplasm. The primary focus is on the development of improved processing hybrids. These are being evaluated in collaboration with Hunt Wesson, a large and diversified tomato processing company. It is planned that products based on this research will be introduced in the USA in 1995.
Synthesis of cross-linked polymer microspheres in supercritical carbon dioxide (1998)

Herein we report the synthesis of highly cross-linked polymers based on divinylbenzene by heterogeneous polymerization in supercritical CO2 (scCO2). The polymers were isolated in the form of discrete microspheres (diameter = 1.5–5 μm) in good yields (≥90%), in the absence of any stabilizers. In the presence of a CO2-soluble polymeric stabilizer, much smaller particles (diameter <0.5 μm) were formed in high yields (≥95%) by emulsion polymerization in scCO2.
Epidermal growth factor receptor is a preferred target for treating Amyloid-β–induced memory loss (2012)

Current understanding of amyloid-β (Aβ) metabolism and toxicity provides an extensive list of potential targets for developing drugs for treating Alzheimer's disease. We took two independent approaches, including synaptic-plasticity-based analysis and behavioral screening of synthetic compounds, for identifying single compounds that are capable of rescuing the Aβ-induced memory loss in both transgenic fruit fly and transgenic mouse models. Two clinically available drugs and three synthetic compounds not only showed positive effects in behavioral tests but also antagonized the Aβ oligomers-induced activation of the epidermal growth factor receptor (EGFR). Such surprising converging outcomes from two parallel approaches lead us to conclude that EGFR is a preferred target for treating Aβ-induced memory loss.
Central role of mitochondrial aldehyde dehydrogenase and reactive oxygen species in nitroglycerin tolerance and cross-tolerance (2004)

Recent studies suggest that mitochondrial aldehyde dehydrogenase (ALDH-2) plays a central role in the process of nitroglycerin (glyceryl trinitrate, GTN) biotransformation in vivo and that its inhibition accounts for mechanism-based tolerance in vitro. The extent to which ALDH-2 contributes to GTN tolerance (impaired relaxation to GTN) and cross-tolerance (impaired endothelium-dependent relaxation) in vivo remain to be elucidated. Rats were treated for three days with GTN. Infusions were accompanied by decreases in vascular ALDH-2 activity, GTN biotransformation, and cGMP-dependent kinase (cGK-I) activity. Further, whereas in control vessels, multiple inhibitors and substrates of ALDH-2 reduced both GTN-stimulation of cGKI and GTN-induced vasodilation, these agents had little effect on tolerant vessels. A state of functional tolerance (in the GTN/cGMP pathway) was recapitulated in cultured endothelial cells by knocking down mitochondrial DNA (rho(0) cells). In addition, GTN increased the production of reactive oxygen species (ROS) by mitochondria, and these increases were associated with impaired relaxation to acetylcholine. Finally, antioxidants/reductants decreased mitochondrial ROS production and restored ALDH-2 activity. These observations suggest that nitrate tolerance is mediated, at least in significant part, by inhibition of vascular ALDH-2 and that mitochondrial ROS contribute to this inhibition. Thus, GTN tolerance may be viewed as a metabolic syndrome characterized by mitochondrial dysfunction.
Combined Systemic and Intratumoral Administration of Human Papillomavirus Vaccine to Treat Multiple Cutaneous Basaloid Squamous Cell Carcinomas (2018)

This is the first report, to our knowledge, of complete regression of a cutaneous malignant tumor after combined systemic and direct intratumoral injection of the 9-valent HPV vaccine. This report suggests that the HPV vaccine may have therapeutic utility for SCCs in patients who are poor surgical candidates, have multiple lesions, or defer surgery.
An active set quadratic programming algorithm for real-time model predictive control (2006)

On-board model predictive control of a nonlinear dynamical system often involves linearizing the nonlinear dynamics and posing a quadratic program to stay close to a desired profile of outputs. As on-board control requires computing a reliable solution in a robust manner in real time, the quadratic programming algorithm needs to use linear algebra optimally. This article describes an active set algorithm which exploits a ‘hot start’ for the set of binding constraints at optimality along with efficient linear algebra to make rapid progress towards the solution. Furthermore, the linear algebra is designed to deal with degenerate constraints, because the required factorizations are performed and because degeneracy emerges, and not via a mostly unnecessary pre-process step. Computational results are presented for controlling the deceleration of a large commercial aircraft engine.
Quadrature Mach–Zehnder interferometer with application in optical coherence tomography (2007)

NRC publication: Yes
Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic (2020)

Recently, a backdoor data poisoning attack was proposed, which adds mislabeled examples to the training set, with an embedded backdoor pattern, aiming to have the classifier learn to classify to a target class whenever the backdoor pattern is present in a test sample. We address post-training detection of innocuous perceptible backdoors in DNN image classifiers, wherein the defender does not have access to the poisoned training set. This problem is challenging because without the poisoned training set, we have no hint about the actual backdoor pattern used during training. We identify two properties of perceptible backdoor patterns - spatial invariance and robustness - based upon which we propose a novel detector using the maximum achievable misclassification fraction (MAMF) statistic. We detect whether the trained DNN has been backdoor-attacked and infer the source and target classes. Our detector outperforms other existing detectors experimentally.
Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the\n Wild (2020)

One major challenge for monocular 3D human pose estimation in-the-wild is the\nacquisition of training data that contains unconstrained images annotated with\naccurate 3D poses. In this paper, we address this challenge by proposing a\nweakly-supervised approach that does not require 3D annotations and learns to\nestimate 3D poses from unlabeled multi-view data, which can be acquired easily\nin in-the-wild environments. We propose a novel end-to-end learning framework\nthat enables weakly-supervised training using multi-view consistency. Since\nmulti-view consistency is prone to degenerated solutions, we adopt a 2.5D pose\nrepresentation and propose a novel objective function that can only be\nminimized when the predictions of the trained model are consistent and\nplausible across all camera views. We evaluate our proposed approach on two\nlarge scale datasets (Human3.6M and MPII-INF-3DHP) where it achieves\nstate-of-the-art performance among semi-/weakly-supervised methods.\n
The polymerase domain of <i>Streptococcus pneumoniae</i> DNA polymerase I (1991)

The 3'-terminal two-thirds of the Streptococcus pneumoniae polA gene was cloned in an Escherichia coli genefusion vector with inducible expression. The resulting recombinant plasmid (pSM10) directs the hyperproduction of a polypeptide of 70.6 kDa corresponding to the C-terminal fragment of pneumococcal DNA polymerase I. Induced cells synthesized catalytically active protein to the extent of 7% of the total soluble protein in the cells. The polymerase fragment was purified to greater than 90% homogeneity with a yield of 1.5 mg pure protein/l culture. The protein has DNA polymerase activity, but no exonuclease activity. The enzyme requires a divalent cation (MgCl2 or MnCl2) for polymerization of DNA. Comparison of the mutant and wild-type pneumococcal polymerases shows that the construction did not affect the enzymatic affinity for the various substrates. The mutant protein, like its parent DNA polymerase I, exhibited an intermediate level of activity with primed single-stranded DNA. At high molar ratio of enzyme/DNA substrate, the polymerase fragment catalyzes strand displacement and switching after completing the replication of a primed single-stranded M13 DNA molecule.