gebhart/patrepeval huggingface dataset:
Wavelet Method for CT Colonography Computer-Aided Polyp Detection (2006)

The computed tomographic colonography (CTC) computer aided detection (CAD) program is a new method in development to detect colon polyps in virtual colonoscopy. While high sensitivity is consistently achieved, additional features are desired to increase specificity. The CTC CAD program we are developing outputs a 2D projection image for each detected polyp to mimic the radiologist reading. We designed a wavelet-based feature extraction method for the detection images in an attempt to filter out false positives. We computed a wavelet transform at levels 1-5, and extracted 150 features from the wavelet coefficients for each detection image. The feature vectors were then run through a feature and committee selection procedure with a support vector machine (SVM) classifier. We applied the proposed method to 44 patients, where the CTC CAD program identified 42 true detections from 28 polyps and 492 false positives. Three-fold cross-validation results showed that the proposed method could reduce the false positives by 69% while missing only one real polyp [96% sensitivity (27/28)]. If this technique were added to the filtering process of the CTC CAD polyp detector, the number of false positive detections could be reduced significantly
Deactivation of a Platinum Monolithic Carbon Monoxide/Hydrocarbon Oxidation Catalyst (1974)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTDeactivation of a Platinum Monolithic Carbon Monoxide/Hydrocarbon Oxidation CatalystDavid Liederman, Sterling E. Voltz, and Paul W. SnyderCite this: Ind. Eng. Chem. Prod. Res. Dev. 1974, 13, 3, 166–172Publication Date (Print):September 1, 1974Publication History Published online1 May 2002Published inissue 1 September 1974https://pubs.acs.org/doi/10.1021/i360051a003https://doi.org/10.1021/i360051a003research-articleACS PublicationsRequest reuse permissionsArticle Views65Altmetric-Citations3LEARN 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 options Get e-Alerts
DEVELOPMENT OF A SUPERVISED SOFTWARE TOOL FOR AUTOMATED DETERMINATION OF OPTIMAL SEGMENTATION PARAMETERS FOR ECOGNITION (2010)

Image segmentation is one of the most important steps in object-based classification. The commercial software eCognition has been proven to be the most advanced software tool for object-based classification of high resolution remote sensing imagery. However, its segmentation process still relies on trial and error to find proper segmentation parameters. The segmentation process is very time consuming and the segmentation quality directly depends on the experience of the operator. To overcome this problem, a supervised software tool—Fuzzy-based Segmentation Parameter optimizer (FbSP optimizer)—was developed to determine the optimal segmentation parameters through a training process and a fuzzy logic analysis. The optimal segmentation parameters are then used in eCognition to segment the entire image, achieving an optimal segmentation result. The FbSP optimizer can radically increases the efficiency of segmentation parameter selection, and achieve improved segmentation results. It also reduces the influence of the operator’s experience on the quality of segmentation results.
Molecular mimicry of hepatitis B surface antigen by an anti-idiotype-derived synthetic peptide. (1992)

Monoclonal antibody 2F10 is an "internal-image" anti-idiotype (anti-id) antibody capable of mimicking the group-specific "a" determinant of human hepatitis B surface antigen (HBsAg). By mRNA sequencing and computer-assisted molecular modeling of monoclonal antibody 2F10, we identified a 15-amino acid region of the heavy-chain hypervariable region that has partial residue homology with sequences of the "a" determinant epitopes of HBsAg. We have established that a linear 15-mer peptide from a contiguous region on the anti-id antibody can (i) generate anti-HBsAg-specific antibodies when injected into mice, (ii) prime murine lymph node cells for in vitro HBsAg-specific T-cell proliferative responses, and (iii) stimulate in vitro human CD4+ T cells that were primed in vivo to HBsAg by natural infection with hepatitis B virus or vaccination with a commercially available HBsAg vaccine. Significantly, this peptide could also stimulate CD4+ T cells of human hepatitis B virus carriers. We conclude that a 15-mer peptide derived from the anti-id sequence can duplicate the B- and T-cell stimulatory activity of the intact anti-id antibody and the antigen that is mimicked, HBsAg.
Crypt-Delay: Encrypting IP Cores with Capabilities for Gate-level Logic and Delay Simulations (2016)

System-on-Chip is a promising model for design of complex integrated circuits. In this model, designers may easily incorporate licensed and/or purchased Intellectual Property (IP) modules from other vendors to significantly reduce the design cycle time. However, the need to fulfill the legal obligations in the associated license or purchase contracts usually imposes considerable burden on the design process. The burden is often in the form of design access constraints that have to be imposed on SoC design team and/or in the form of additional costs needed to acquire a less constraining contract. To alleviate these problems, this paper proposes a encryption approach that assures confidentiality of the gate-level circuit information for the module designer while allowing the SoC designers an ability to perform gate-level digital simulations with gate-level delays. Empirical evaluation on benchmark circuits shows that, in addition to not being able to identify the gate types, an attacker cannot decrypt the delays associated with most of the gates in the circuit.
TSH Receptor Antibodies (2007)

The discovery of thyroid-stimulating autoantibodies by Adams and Purves 50 years ago was one of the most important observations in the history of thyroidology. Since that time, the thyroid-stimulating hormone receptor (TSHR) has been shown to be the antigen recognized by these autoantibodies (1974) and the receptor cloned (1989). More recently, different mouse monoclonal antibodies (MAbs) to the TSHR have been produced, culminating in 2002 in the preparation of mouse and hamster MAbs with strong thyroid-stimulating activity. Further, in 2003 a human MAb to the TSHR (M22) with the characteristics of patient thyroid-stimulating autoantibodies was described. M22 has been particularly useful in advancing our knowledge of the TSHR and TSHR autoimmunity, including the development of new assays for TSHR autoantibodies (2004) and determination of a high-resolution (2.55 A) crystal structure of the TSHR leucine-rich domain in combination with M22 (2007). The structure shows that M22 positions itself on the TSHR in an almost identical way to the native hormone TSH but the evolutionary forces that have resulted in production of a common autoantibody that mimics the actions of TSH so well are far from clear at this time. Very recently, a human MAb (5C9) with the characteristics of blocking-type patient serum TSHR autoantibodies has been isolated (2007). Studies on how 5C9 interacts with the TSHR at the molecular level are planned and should provide key insights as to the differences between TSHR autoantibodies with blocking and with stimulating activities. Also, 5C9 and similar MAbs have considerable potential as drugs to inhibit TSHR stimulation by autoantibodies. Further, now the M22-TSHR structure is known at the atomic level, rational design of specific low-molecular-weight inhibitors of the TSHR-TSHR autoantibody interaction is feasible.
Biochemical Characterization of Signal Peptidase I from Gram-Positive <i>Streptococcus pneumoniae</i> (2001)

Bacterial signal peptidase I is responsible for proteolytic processing of the precursors of secreted proteins. The enzymes from gram-negative and -positive bacteria are different in structure and specificity. In this study, we have cloned, expressed, and purified the signal peptidase I of gram-positive Streptococcus pneumoniae. The precursor of streptokinase, an extracellular protein produced in pathogenic streptococci, was identified as a substrate of S. pneumoniae signal peptidase I. Phospholipids were found to stimulate the enzymatic activity. Mutagenetic analysis demonstrated that residues serine 38 and lysine 76 of S. pneumoniae signal peptidase I are critical for enzyme activity and involved in the active site to form a serine-lysine catalytic dyad, which is similar to LexA-like proteases and Escherichia coli signal peptidase I. Similar to LexA-like proteases, S. pneumoniae signal peptidase I catalyzes an intermolecular self-cleavage in vitro, and an internal cleavage site has been identified between glycine 36 and histidine 37. Sequence analysis revealed that the signal peptidase I and LexA-like proteases show sequence homology around the active sites and some common properties around the self-cleavage sites. All these data suggest that signal peptidase I and LexA-like proteases are closely related and belong to a novel class of serine proteases.
Direct conversion of plant biomass to ethanol by engineered <i>Caldicellulosiruptor bescii</i> (2014)

Ethanol is the most widely used renewable transportation biofuel in the United States, with the production of 13.3 billion gallons in 2012 [John UM (2013) Contribution of the Ethanol Industry to the Economy of the United States]. Despite considerable effort to produce fuels from lignocellulosic biomass, chemical pretreatment and the addition of saccharolytic enzymes before microbial bioconversion remain economic barriers to industrial deployment [Lynd LR, et al. (2008) Nat Biotechnol 26(2):169-172]. We began with the thermophilic, anaerobic, cellulolytic bacterium Caldicellulosiruptor bescii, which efficiently uses unpretreated biomass, and engineered it to produce ethanol. Here we report the direct conversion of switchgrass, a nonfood, renewable feedstock, to ethanol without conventional pretreatment of the biomass. This process was accomplished by deletion of lactate dehydrogenase and heterologous expression of a Clostridium thermocellum bifunctional acetaldehyde/alcohol dehydrogenase. Whereas wild-type C. bescii lacks the ability to make ethanol, 70% of the fermentation products in the engineered strain were ethanol [12.8 mM ethanol directly from 2% (wt/vol) switchgrass, a real-world substrate] with decreased production of acetate by 38% compared with wild-type. Direct conversion of biomass to ethanol represents a new paradigm for consolidated bioprocessing, offering the potential for carbon neutral, cost-effective, sustainable fuel production.
Multifocal motor neuropathy (1997)

IgM anti-GM1 antibodies occur with increased frequency in the serum of patients with multifocal motor neuropathy (MMN). We tested the ability of serum IgM from patients with MMN to bind to GM1 ganglioside covalently bound to secondary amino groups on ELISA plates (Co-GM1). The Co-GM1 technique detected high titer (> 1,800), selective, serum IgM binding to GM1 ganglioside in 85% of our MMN patients (23/27), a significantly greater frequency compared with figures of 37% and 52% found using our previous testing methods. Selective IgM anti-GM1 antibodies showed disease specificity. The only other patients with selective, high-titer IgM anti-GM1 antibodies had either chronic motor neuropathy without conduction block or acute immune neuropathy in China. No patient from the amyotrophic lateral sclerosis, chronic inflammatory demyelinating polyneuropathy, Guillain-Barré, or systemic immune disorder control groups had selective IgM anti-GM1 antibodies at titers greater than 1,800 detected using Co-GM1 ganglioside as ELISA antigen. Titers of IgM anti-GM1 antibodies in MMN (averaging 31,000 +/- 15,000) were more than fourfold higher with Co-GM1 than with previous anti-GM1 assay methods, using conventional ELISA plates with GM-1 antigen alone (7,200 +/- 4,400) or in a lipid environment (3,600 +/- 1,300). We conclude that using ELISA testing with Co-GM1 antigen, serum anti-GM1 autoantibodies are a useful marker for MMN, because they are present in 85% of MMN patients and, at titers greater than 1,800, have strong specificity for immune-mediated motor neuropathies.
Quantum Lithography (2006)

As demonstrated in Boto et al. [quant-ph/9912052], quantum lithography offers an increase in resolution without an upper bound. This procedure makes use of the entangled state (|n,0〉+e inϕ |0,n〉)/√2. It allows us to write evenly spaced lines with sub-wavelength resolution. Here we generalise this procedure in such a way that it enables us to create arbitrary patterns in one dimension. We distinguish two methods: the ‘Fourier method’ and ‘the superposition method’. The Fourier method is conceptually easier since it depends on Fourier series, but it also involves a minimal finite amount of unwanted exposure of the substrate. The superposition method gets around this problem and gives generally better results, but lacks the intuitive clarity of the Fourier method.
Pedestrian Detection Using Stereo Night Vision (2004)

A method is presented for pedestrian detection using a stereo night-vision system installed on the vehicle. Much of the work in this area makes use of shape information. The proposed method detects moving objects whose motions are not consistent with the movement of the background and is considered to be complementary to shape-based approaches. In this paper, two new techniques are introduced for this task for night vision, namely a two-stage method for stereo correspondence and motion detection without explicit ego-motion calculation. These techniques make use of characteristics of night-vision video data, in which humans appear as hotspots. This method works well in cases where the camera motion has a dominant translational motion with a small amount of rotational motion, which is suitable for the camera on the vehicle. Error analysis as well as experimental results are presented to validate our approach and comparisons have been carried out between our approach and frame-by-frame based pattern-recognition approaches.
What Are Optimal Coding Functions for Time-of-Flight Imaging? (2018)

The depth resolution achieved by a continuous wave time-of-flight (C-ToF) imaging system is determined by the coding (modulation and demodulation) functions that it uses. Almost all current C-ToF systems use sinusoid or square coding functions, resulting in a limited depth resolution. In this article, we present a mathematical framework for exploring and characterizing the space of C-ToF coding functions in a geometrically intuitive space. Using this framework, we design families of novel coding functions that are based on Hamiltonian cycles on hypercube graphs. Given a fixed total source power and acquisition time, the new Hamiltonian coding scheme can achieve up to an order of magnitude higher resolution as compared to the current state-of-the-art methods, especially in low signal-to-noise ratio (SNR) settings. We also develop a comprehensive physically-motivated simulator for C-ToF cameras that can be used to evaluate various coding schemes prior to a real hardware implementation. Since most off-the-shelf C-ToF sensors use sinusoid or square functions, we develop a hardware prototype that can implement a wide range of coding functions. Using this prototype and our software simulator, we demonstrate the performance advantages of the proposed Hamiltonian coding functions in a wide range of imaging settings.
Chiral tunneling of topological states for giant longitudinal spin Hall angle (2014)

We show that the interplay between chiral tunneling and spin-momentum locking of helical surface states leads to spin amplification and filtering in a 3D Topological Insulator (TI). Chiral tunneling across a TI pn junction allows normally incident electrons to transmit, while the rest are reflected with their spins flipped due to spin-momentum locking. The net result is that the spin current is enhanced while the dissipative charge current is simultaneously suppressed, leading to an extremely large, gate tunable spin to charge current ratio (~20) at the reflected end. At the transmitted end, the ratio stays close to one and the electrons are completely spin polarized.
Development of Bioactive Patch for Maintenance of Implanted Cells at the Myocardial Infarcted Site (2015)

Ischemia produced as a result of myocardial infarction might cause moderate or severe tissue death. Studies under development propose grafting stem cells into the affected area and we hypothesize that this mechanism could be enhanced by the application of a “bioactive implant.” The implant herein proposed consists of a thin porous elastomeric membrane, filled with self‐assembling nanofibers and human subcutaneous adipose tissue derived progenitor cells. We describe the development and characterization of two elastomeric membranes: poly(ethyl acrylate) (PEA) and poly(caprolactone 2‐(methacryloyloxy)ethyl ester) (PCLMA). Both are a good material support to deliver cells within a soft self‐assembling peptide and are elastic enough to withstand the stresses arising from the heartbeat. Both developed composites (PEA and PCLMA, combined with self‐assembling peptide) equally facilitate the propagation of electrical pulses and maintain their genetic profile of the seeded cells. Preliminary studies with small animal models suggest that, at short times, the bioimplant shows good adhesion with the myocardium. After three days cells loaded in the patch remain alive at the implanted site. We propose that the bioactive patch (elastomeric membranes with self‐assembling peptide and cells) could increase the efficacy of future cardiac cell therapy by improving cell immobilization and survival at the affected site.
Biofuel from algae photobiological hydrogen production and CO<SUB align=right>2-fixation (2007)

The reduction of CO2-emissions that are damaging our climate is one of the major challenges of contemporary energy management. Nature itself offers us possibilities to produce energy CO2-neutrally with the help of hydrogen producing micro-algae. Under certain conditions the light energy collected by photosynthesis is used to transfer electrons to hydrogen producing proteins called hydrogenases. A new type of hydrogenase that produces molecular hydrogen with high rates was isolated (Happe and Naber, 1993) and characterised on genomic level (Happe and Kaminski, 2002) for the first time in green algae. Processes were recently developed that allow a long-term production of hydrogen by micro-algae (Melis et al., 2000). Under sulphur deprivation the green alga Chlamydomonas reinhardtii adapts its metabolism from oxygen production and CO2-fixation towards hydrogen production. Therefore the biotechnological process is divided into the growth, the hydrogen production and the utilisation and treatment of the available energy in the form of hydrogen and biomass.
An Ultra Low Loss THz Waveguide (2008)

We demonstrate a new concept for guiding THz radiation with dB/km attenuation, by exploiting the unique properties of the TE 1 mode of a parallel-plate-waveguide. This represents a thousand-fold decrease of the attenuation over existing waveguides.
Doppler-Free Resonance Ionization Mass Spectrometry of Beryllium (1987)

As originally conceived, resonance ionization mass spectrometry (RIMS) combined the elemental selectivity of resonance ionization (1) with the isotopic selectivity of mass spectrometry to improve the accuracy and sensitivity of conventional mass spectrometry (2). For many applications, especially quantitation by isotope dilution (3) , it is important that no isotopic selectivity accompany the resonance ionization process. This condition is easily met for all but a few elements of the periodic table (4), since the great majority of optical isotope shifts are small with respect to typical dye laser bandwidths and Doppler-broadened linewidths in common atom reservoirs. However, another class of problem exists for which it is desirable to achieve isotopically selective resonance ionization. These applications involve the detection of extremely, rare stable or radioactive isotopes in the presence of the major isotopic species of an element. Miller et al. (5) have explored the optical isotopic selectivity of the isotopes of Lu using a RIMS spectrometer equipped with a high-resolution (single-mode) continuous-wave (cw) laser. Cannon et al. (6) have measured an optical selectivity (defined below) of 800 for isotopes of Ba, using a RIMS spectrometer with two cw lasers. We have proposed the use of pulsed, two-photon, Doppler-free resonance ionization to extend the capability of conventional mass spectrometers to measure isotope ratios in excess of 10 12 (7). Initial experimental results using this approach, for the isotopes 9 Be and 10 Be, are reported here.
Unsupervised Learning of Interpretable Dialog Models (2020)

Recently several deep learning based models have been proposed for end-to-end learning of dialogs. While these models can be trained from data without the need for any additional annotations, it is hard to interpret them. On the other hand, there exist traditional state based dialog systems, where the states of the dialog are discrete and hence easy to interpret. However these states need to be handcrafted and annotated in the data. To achieve the best of both worlds, we propose Latent State Tracking Network (LSTN) using which we learn an interpretable model in unsupervised manner. The model defines a discrete latent variable at each turn of the conversation which can take a finite set of values. Since these discrete variables are not present in the training data, we use EM algorithm to train our model in unsupervised manner. In the experiments, we show that LSTN can help achieve interpretability in dialog models without much decrease in performance compared to end-to-end approaches.
Atmosphere response to pre-earthquake processes revealed by satellite and ground observations. Case study for few strong earthquakes in Xinjiang, China (2008-2014) (2020)

We are presenting the latest results of multi-sensor observations of short-term pre-earthquake phenomena preceding significant earthquakes. We study satellite thermal infrared radiation (OLR) anomalous signals in association with three major earthquakes, which occurred in Xinjiang province, China at different periods M7.3 of 02.12.2014; M6.2 of 08.12.2012; and M7.2 of 03.20.2008. We systematically apply multi-sensor satellite thermal data and ground temperature /humidity and estimates of the atmospheric chemical potential (ACP) parameter. Data analyses include NOAA NPOESS, the Chinese geostationary satellite FY-2D, and in-situ hourly NOAA data from the Hotan weather station. In all three cases, we detected atmospheric satellite OLR anomalies developed near the epicenter area and ACP increases (significant change for 2008 and 2014, weak for 2012) over the major Altyn Tagh fault lines within 10-20 days before the earthquake event. These findings demonstrate the occurrence and reoccurrence of transient variations of these parameters, implying their connection with the earthquake preparation process.