gebhart/patrepeval huggingface dataset:
Neural network image analysis and classification in hybrid lung nodule detection (HLND) system (2002)

A hybrid lung nodule detection (HLND) system based on artificial neural network architectures is developed for improving diagnostic accuracy and speed of lung cancerous pulmonary radiology. The configuration of the HLND system includes the following processing phases: (1) pre-processing to enhance the figure-background contrast; (2) quick selection of nodule suspects based upon the most prominent feature of nodules; and (3) complete feature space determination and neural classification of nodules. The feature analysis, extraction and classification with artificial neural networks (ANN) are described. Preliminary results from the approach are reported.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
On local design and execution of a distributed input and state estimation architecture for heterogeneous sensor networks (2017)

In this paper, we focus on a new distributed input and state estimation architecture, where nodes of a given sensor network are allowed to have heterogeneous information roles in the sense that a subset of nodes can be active (that is, subject to observations of a process of interest) and the rest can be passive (that is, subject to no observations). Moreover, these nodes are allowed to have nonidentical sensor modalities under the common underlying assumption that they have complimentary properties distributed over the sensor network to achieve collective observability. The key feature of our framework is that it utilizes local information not only during the execution of the proposed distributed input and state estimation architecture but also in its design; that is, global stability is guaranteed once each node satisfies given local stability conditions (independent from the graph topology and neighboring information of these nodes). Several examples are provided to demonstrate the efficacy of the proposed approach.
Electro-plasmonic nanoantenna: A nonfluorescent optical probe for ultrasensitive label-free detection of electrophysiological signals (2019)

Harnessing the unprecedented spatiotemporal resolution capability of light to detect electrophysiological signals has been the goal of scientists for nearly 50 years. Yet, progress toward that goal remains elusive due to lack of electro-optic translators that can efficiently convert electrical activity to high photon count optical signals. Here, we introduce an ultrasensitive and extremely bright nanoscale electric-field probe overcoming the low photon count limitations of existing optical field reporters. Our electro-plasmonic nanoantennas with drastically enhanced cross sections (~10<sup>4</sup> nm<sup>2</sup> compared to typical values of ~10<sup>-2</sup> nm<sup>2</sup> for voltage-sensitive fluorescence dyes and ~1 nm<sup>2</sup> for quantum dots) offer reliable detection of local electric-field dynamics with remarkably high sensitivities and signal-to-shot noise ratios (~60 to 220) from diffraction-limited spots. In our electro-optics experiments, we demonstrate high-temporal resolution electric-field measurements at kilohertz frequencies and achieved label-free optical recording of network-level electrogenic activity of cardiomyocyte cells with low-intensity light (11 mW/mm<sup>2</sup>).
Tamoxifen and the isomers of 4-hydroxytamoxifen in tamoxifen-resistant tumors from breast cancer patients. (1992)

This study clearly demonstrates a wide range of tumor tamoxifen levels and accumulation of the less antiestrogenic cis isomer of 4-hydroxytamoxifen in some patients on tamoxifen therapy. Additional study is necessary to determine if these metabolic profiles are related to the development of tamoxifen resistance.
Automated interpretation of medical prescription text. (2008)

Many physicians have been reluctant to adopt error-reducing Computerized Physician Order Entry (CPOE) systems, citing a lack of efficiency. This perceived lack of efficiency is often attributed to the user interface, which is invariably a form-like screen. Research was conducted into an alternative in which the physician enters traditional prescription text into a user interface that is analogous to a prescription pad.
Single-layer graphene membranes by crack-free transfer for gas mixture separation (2018)

The single-layer graphene film, when incorporated with molecular-sized pores, is predicted to be the ultimate membrane. However, the major bottlenecks have been the crack-free transfer of large-area graphene on a porous support, and the incorporation of molecular-sized nanopores. Herein, we report a nanoporous-carbon-assisted transfer technique, yielding a relatively large area (1 mm<sup>2</sup>), crack-free, suspended graphene film. Gas-sieving (H<sub>2</sub>/CH<sub>4</sub> selectivity up to 25) is observed from the intrinsic defects generated during the chemical-vapor deposition of graphene. Despite the ultralow porosity of 0.025%, an attractive H<sub>2</sub> permeance (up to 4.1 × 10<sup>-7</sup> mol m<sup>-2</sup> s<sup>-1</sup> Pa<sup>-1</sup>) is observed. Finally, we report ozone functionalization-based etching and pore-modification chemistry to etch hydrogen-selective pores, and to shrink the pore-size, improving H<sub>2</sub> permeance (up to 300%) and H<sub>2</sub>/CH<sub>4</sub> selectivity (up to 150%). Overall, the scalable transfer, etching, and functionalization methods developed herein are expected to bring nanoporous graphene membranes a step closer to reality.
<title>Development Of ZrO<formula><inf><roman>x</roman></inf></formula>N<formula><inf><roman>y</roman></inf></formula> Films For Solar Absorbers</title> (1976)

For maximum effectiveness of solar-thermal conversion, a solar absorber must be a low emitter of thermal radiation. Thin film absorber stacks which possessed such spectrally selective characteristics were developed by the Bureau of Mines. The stacks consisted of zirconium suboxide or subnitride absorber films on a reflective film of silver or copper. The absorber films were prepared by reactively sputtering zirconium in argon with small amounts of oxygen, nitrogen, or both, or by oxidation of zirconium films in air. The solar absorptance and the thermal emittance were calculated from reflectance data. The solar absorptance, a(s), ranged from 0.60 to 0.93 and the emittance, e(T), at 600 K, ranged from 0.024 to 0.28. Ratios of a(s)/e(T) extended from about 2 to 28. The stacks appear relatively stable under vacuum at temperatures up to about 600 K.
A systemic framework of camera motion analysis for home video (2004)

A key factor that results in low quality home video is abnormal camera motion, such as camera shaking and irregular camera motion. Those unwanted camera movements make video content analysis more difficult than that in high quality video, because these abnormal motions usually cannot be well handled by traditional camera motion characterization approaches. In this paper, a systemic framework is proposed for camera motion analysis, which is robust to low quality home videos. The main characters of this framework are: (1) it is a qualitative analysis framework for camera motion, which is based on a novel motion representation instead of traditional motion estimation methods; (2) a robust camera shaking detection module is integrated, which effectively improves the accuracy of camera motion characterization and shot boundary detection; (3) all camera motion related issues, including shot boundary detection, in home videos are considered as a whole; (4) due to adopting qualitative motion representation, the processing speed is much faster than real time. Experiment results have shown the efficiency and robustness of the proposed framework.
Noncontact ultrasonic guided wave inspection of rails (2013)

This article describes a new system for high-speed and noncontact rail integrity evaluation being developed at the University of California at San Diego. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection has been tested at the University of California at San Diego Rail Defect Farm. In addition to a real-time statistical analysis algorithm, the prototype uses a specialized filtering approach due to the inherently poor signal-to-noise ratio of the air-coupled ultrasonic measurements in rail steel. The laboratory results indicate that the prototype is able to detect internal rail defects with a high reliability. Extensions of the system are planned to add rail surface characterization to the internal rail defect detection. In addition to the description of the prototype and test results, numerical analyses of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach algorithm and some of these results are shown. The numerical analysis has helped designing various aspects of the prototype for maximizing its sensitivity to defects.
Anionic porphyrin-grafted porous silicon nanoparticles for photodynamic therapy (2013)

Non-toxic porous silicon nanoparticles carry porphyrin covalently attached to their surface inside breast cancer cells for a more efficient photodynamic effect.
A First Attempt to Predict Reservoir Porosity from Advanced Mud Gas Data (2022)

Abstract Porosity, a critical property of petroleum reservoirs, is a key controlling factor of the reservoir storage capacity. It has been conventionally measured from core plugs. Empirical correlations, statistical, and machine learning methods have been employed for indirect estimation of porosity. The results obtained from these approaches are available only after acquiring drilling and wireline logs. Obtaining porosity estimates in real time, ahead of wireline logging, can help in making critical decisions and enabling early assessment of reservoir quality. We present the results of a machine learning approach to predicting porosity from advanced mud gas data. Datasets integrating advanced mud gas data with porosity were gathered from seven wells to prove this concept. The mud gas data includes light and heavy flare gas components. Optimized artificial neural network (ANN) models were applied to the datasets and multivariate linear regression (MLR) models were used as benchmarks. Each well dataset was split into training and validation subsets using a randomized sampling approach with the ratio of 70:30. A 100 ppm cut-off was applied to the total normalized gas. To evaluate the performance of the models, we use correlation coefficients (R) and mean squared error (MSE). The ANN models consistently outperformed the MLR models in all the datasets. The ANN models have training and validation correlation coefficients of up to 0.89 and 0.88, respectively, compared to an average of 0.79 and 0.77 for the MLR models. The training and validation MSEs for the ANN models are as low as 0.0135 and 0.021, respectively, compared to those of the MLR models in the range of 0.0007 and 0.03, respectively. These results indicate the nonlinearity of the relationship between porosity and the gas components. Furthermore, it can be deduced that the approach is feasible and better results are achievable. The randomized sampling ensures that each data point has an equal chance to be used for either training or validation without bias. The cut-off applied to the normalized total gas is a standard practice to eliminate the background gas effect in the mud gas data. This study provides an opportunity to utilize mud gas data beyond the traditional fluid typing and petrophysical correlation purposes. The presented approach has the capability to complement existing reservoir characterization approaches in providing reservoir quality assessments at the early stage of exploration. We plan to apply state-of-the-art machine learning models and perform sensitivity analysis on the gas components in the future to increase the accuracy.
Discovery of Tetralones as Potent and Selective Inhibitors of Acyl-CoA:Diacylglycerol Acyltransferase 1 (2018)

Acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) plays an important role in triglyceride synthesis and is a target of interest for the treatment of metabolic disorders. Herein we describe the structure-activity relationship of a novel tetralone series of DGAT1 inhibitors and our strategies for overcoming genotoxic liability of the anilines embedded in the chemical structures, leading to the discovery of a candidate compound, (<i>S</i>)-2-(6-(5-(3-(3,4-difluorophenyl)ureido)pyrazin-2-yl)-1-oxo-2-(2,2,2-trifluoroethyl)-1,2,3,4-tetrahydronaphthalen-2-yl)acetic acid (GSK2973980A, <b>26d</b>). Compound <b>26d</b> is a potent and selective DGAT1 inhibitor with excellent DMPK profiles and <i>in vivo</i> efficacy in a postprandial lipid excursion model in mice. Based on the overall biological and developability profiles and acceptable safety profiles in the 7-day toxicity studies in rats and dogs, compound <b>26d</b> was selected as a candidate compound for further development in the treatment of metabolic disorders.
Novel helical resonator filter structures (2002)

Helical resonator filters are well-known and widely used at lower microwave frequencies. Two novel helical resonator filter configurations for applications in wireless and satellite communication systems are described in this paper. This includes miniature filters utilizing single mode, high dielectric constant material loaded helical resonators, as well as higher order dual mode helical resonator loaded cavities. Both configurations can be used to realize advanced filters with non-adjacent couplings. The basic filter configurations are discussed and experimental results are presented.
Posturography stability score generation for stroke patient using Kinect: Fuzzy based approach (2017)

Aim of this paper is to formulate a posturography stability score for stroke patients using fuzzy logic. Postural instability is one of the prominent symptoms of stroke, dementia, parkinsons disease, myopathy, etc. and is the major precursor of fall. Conventional scoring techniques used to assess postural stability require manual intervention and are dependent on live interaction with physiotherapist. We propose a novel scoring technique to calculate static stability of a person using posturography features acquired by Kinect sensor, which do not require any manual intervention or expert guidance, is cost effective and hence are ideal for tele rehabilitation purpose. Stability analysis is done during Single Limb Stance (SLS) exercise. Kinect sensor is used to calculate three features, naming SLS duration, vibration index, calculated from mean vibration of twenty joints and sway area of Centre of Mass (CoM). Based on the variation of these features, a fuzzy rule base is generated which calculates a static stability score. One way analysis of variance (Anova) between a group of stroke population and healthy individuals under study validates the reliability of the proposed scorer. Generated fuzzy score are comparable with standard stability scorer like Berg Balance scale and fall risk assessment tool like Johns Hopkins scale. Stability score, besides providing an index of overall stability can also be used as a fall predictability index.
Recover Alum to Reduce Waste‐Disposal Costs (1974)

Alum is widely used in water treatment, but there are now investigations of other coagulants to be used instead because it is difficult to dispose of alum sludge. There is a relatively easy and inexpensive method available now, however, that makes possible pretreatment of alum sludge in such a way that it can be dewatered and reused.
Geometrically enhanced magnetoresistance in ferromagnet–insulator–ferromagnet tunnel junctions (1996)

Ferromagnetic–insulator–ferromagnetic trilayer tunnel junctions show magnetoresistance (JMR) effects of about 14% or greater at room temperature. Much larger values of the JMR (100% or more) are observed when the actual tunneling resistance (RT) is comparable to electrode film resistance (RL) over the junction area. This latter apparent JMR is an artifact of the nonuniform current flow over the junction in the cross geometry of the electrodes. The ferromagnetic films were CoFe and Co or Ni0.8Fe0.2, and the tunnel barrier was AlN or Al2O3. These junctions show nonvolatile memory effects. The geometrically enhanced large JMR in junctions can be effectively used as magnetic sensors and memory elements.
Triple-Band Cavity Bandpass Filters (2018)

This paper presents a new class of cavity-based triple-band filters employing resonators that support three operation modes. The proposed triple-band filters do not require junctions and can achieve an equivalent Chebyshev performance with fewer cavities, thus significantly reducing the footprint when compared to traditional approaches. The filter facilitates a systematic design approach starting from the coupling-matrix generation to the overall response optimization. The concept is potentially applicable to most triple-mode resonators and is demonstrated in this paper using waveguide and dielectric resonators. The first design is an inline structure employing elliptical waveguide cavities, whereas the second design is a folded structure using rectangular waveguide cavities. The third design is implemented by dielectric loaded cavity resonators. All the proposed triple-band filter designs offer high Q and allow for independent control of each frequency and coupling parameter. To verify the concept, three triple-band filter examples with different realizations are designed, manufactured, and tested to allow comparisons.
Niche applications of magnetically responsive photonic structures (2010)

Magnetically responsive photonic crystal structures have been produced by self-assembling superparamagnetic colloidal particles under the balance of repulsive and attractive interactions. The optical properties can be tuned rapidly, widely, and reversibly in the entire visible spectrum. By taking advantage of many unique features of the field responsive systems, we demonstrate in this article some of their niche applications for various display purposes, including antifraud devices, rewritable photonic papers, and full colour high resolution printing systems.
Designing Bessel Filters Based on Coupled-Resonator Optical Waveguides for Dispersion-Free Slow Light (2011)

We have developed a formalism for designing Bessel filters based on coupled-resonator optical waveguides (CROWs). The CROWs feature maximally flat group delay and can be realized on different types of resonators.
Recovery of a Recombinant Salmonid Alphavirus Fully Attenuated and Protective for Rainbow Trout (2006)

Sleeping disease virus (SDV) is a member of the new Salmonid alphavirus genus within the Togaviridae family. The single-stranded RNA genome of SDV is 11,894 nucleotides long, excluding the 3' poly(A) tail. A full-length cDNA has been generated; the cDNA was fused to a hammerhead ribozyme sequence at the 5' end and inserted into a transcription plasmid (pcDNA3) backbone, yielding pSDV. By transfection of pSDV into fish cells, recombinant SDV (rSDV) was successfully recovered. Demonstration of the recovery of rSDV was provided by immunofluorescence assay on rSDV-infected cells and by the presence of a genetic tag, a BlpI restriction enzyme site, introduced into the rSDV RNA genome. SDV infectious cDNA was used for two kinds of experiments (i) to evaluate the impact of various targeted mutations in nsP2 on viral replication and (ii) to study the virulence of rSDV in trout. For the latter aspect, when juvenile trout were infected by immersion in a water bath with the wild-type virus-like rSDV, no deaths or signs of disease appeared in fish, although they were readily infected. In contrast, cumulative mortality reached 80% in fish infected with the wild-type SDV (wtSDV). When rSDV-infected fish were challenged with wtSDV 3 and 5 months postinfection, a long-lasting protection was demonstrated. Interestingly, a variant rSDV (rSDV14) adapted to grow at a higher temperature, 14 degrees C instead of 10 degrees C, was shown to become pathogenic for trout. Comparison of the nucleotide sequences of wtSDV, rSDV, and rSDV14 genomes evidenced several amino acid changes, and some changes may be linked to the pathogenicity of SDV in trout.
Nuclear Magnetic Resonance Imaging in Medicine (1982)

With the stated goal of providing a general introduction to nuclear magnetic resonance (NMR) imaging for practicing radiologists, the book is one of the first such works on this exciting new development in diagnostic medicine. The book comprises ten well-integrated chapters authored by reputable workers in the field. The chapters are grouped into four sections encompassing the "Principles" of NMR imaging, NMR "Imaging" results, imaging of "Elements Other Than Hydrogen," and "Potential Hazards" associated with the technique, plus a glossary and an introductory chapter on potential applications. The principles section describes the basic physics of NMR, the different techniques used for obtaining images, and the required instrumentation. The fundamental dilemma faced by the editors is one of interfacing the complexities and intricacies of this technique with the stated goal as an introduction. Too often, the solution is to skirt important, complex issues with broad explanations. Examples are combining quantum mechanical
Gold Seed Removal from the Tips of Silicon Nanorods (2009)

A chemical method was developed to remove the gold (Au) seed particles from the tips of solution-liquid-solid (SLS) grown silicon (Si) nanorods. The nanorods are capped with hydrophobic ligands during the synthesis, which made it necessary to perform the Au etching in an aqua regia and chloroform emulsion. Preliminary etching experiments revealed that a thin Si shell coated the Au seeds and prevented Au removal. Therefore, a rapid thermal quench of the reaction mixture was needed to crack this shell and provide etchant access to the Au seed. More than 95% of the Au seeds could be removed from the tips of thermally quenched samples without damaging the crystalline Si nanorods.
Word spotting in scanned images using hidden Markov models (1993)

A hidden-Markov-model (HMM)-based system for font-independent spotting of user-specified keywords in a scanned image is described. Word bounding boxes of potential keywords are extracted from the image using a morphology-based preprocessor. Feature vectors based on the external shape and internal structure of the word are computed over vertical columns of pixels in a word bounding box. For each user-specified keyword, an HMM is created by concatenating appropriate context-dependent character HMMs. Nonkeywords are modeled using an HMM based on context-dependent subcharacter models. Keyword spotting is performed using a Viterbi search through the HMM network created by connecting the keyword and nonkeyword HMMs in parallel. Applications of word-image spotting include information filtering in images from facsimile and copy machines, and information retrieval from text image databases.< <ETX>></ETX>