gebhart/patrepeval huggingface dataset:
Control of a Minimally Actuated Biomimetic Vehicle Using Quarter-Cycle Wingbeat Modulation (2015)

This paper describes a technique, called quarter-cycle constant period frequency modulation, to control the motion of wings on a flapping wing micro-air vehicle. This technique allows control over the wingbeat period and three additional points (the two zero crossings and the reversal of wing direction) within a single wingbeat cycle, allowing modulation of the wing’s velocity to provide direct control over six degrees of freedom of overall vehicle motion. Using a blade element based aerodynamic model, both instantaneous and cycle-averaged forces and moments are analytically computed for a specific type of wingbeat motion that enables nearly decoupled, multi-degrees of freedom control of an aircraft. Wing motion is controlled using oscillators whose frequencies and three additional parameters change once per wingbeat cycle. A control oriented dynamic model of the vehicle is derived, which is based on a cycle-averaged representation of the forces and moments, and control derivatives are calculated. A cycle-averaged control law is designed to provide direct control over six degrees of freedom of the vehicle.
Automated Localization of Multiple Pelvic Bone Structures on MRI (2014)

In this paper, we present a fully automated localization method for multiple pelvic bone structures on magnetic resonance images (MRI). Pelvic bone structures are at present identified manually on MRI to locate reference points for measurement and evaluation of pelvic organ prolapse (POP). Given that this is a time-consuming and subjective procedure, there is a need to localize pelvic bone structures automatically. However, bone structures are not easily differentiable from soft tissue on MRI as their pixel intensities tend to be very similar. In this paper, we present a model that combines support vector machines and nonlinear regression capturing global and local information to automatically identify the bounding boxes of bone structures on MRI. The model identifies the location of the pelvic bone structures by establishing the association between their relative locations and using local information such as texture features. Results show that the proposed method is able to locate the bone structures of interest accurately (dice similarity index >0.75) in 87-91% of the images. This research aims to enable accurate, consistent, and fully automated localization of bone structures on MRI to facilitate and improve the diagnosis of health conditions such as female POP.
DETECTION OF FEMUR AND RADIUS FRACTURES IN X-RAY IMAGES (2004)

13 % of men and 30%–40 % of women suffer from osteoporotic bone fractures worldwide. In large hospitals, doctors need to visually inspect a large number of x-ray images to identify the fracture cases, which typically constitute a small fraction of all the x-ray images examined. After looking through many images containing healthy bones, a tired radiologist has been found to miss a fractured case among the many healthy ones. Automated fracture detection can help the doctors by screening for obvious cases and flagging suspicious cases for closer examinations. Since bone fractures can occur in many ways, no one single algorithm can detect all the possible fractures accurately. This paper describes an approach in detecting fractures of the femur and the radius by combining various detection methods. These methods extract different kinds of features for fracture detection. They include neck-shaft angle, which is specifically extracted for femur fracture detection, and Gabor texture, Markov Random Field texture, and intensity gradient, which are general features that can be applied to detecting fractures of various bones. Two types of classifiers are tested, namely, Bayesian classifier and Support Vector Machine. Test results show that the combined approach can improve both the fracture detection rate and the classification accuracy significantly compared to any single method.
Optimizing the Production of Renewable Aromatics via Crop Oil Catalytic Cracking (2015)

While HZSM-5 catalytic cracking of crop oil toward aromatics have been well documented, this work adds to this body of knowledge with a full acid byproduct analysis that provides improved mass balance closure along with a design of experiment optimization of reaction conditions. Fatty acids are an inevitable byproduct when converting any triglyceride oil, but are most often overlooked; despite the impact fatty acids have on downstream processing. Acid analysis verified that only short chain fatty acids, mainly acetic acid, were present in low quantities when all feed oil was reacted. When relatively high fatty acid amounts were present, these were mainly uncracked C16 and C18 fatty acids. Optimization is a balance of aromatics formation vs. unwanted gas products, coke and residual fatty acids. A design of experiments approach was used to provide insight into where the optimal reaction conditions reside for HZSM-5 facilitated reactions. These conditions can then form the basis for further development into a commercially viable process for the production of renewable aromatics and other byproducts.
2,3,4,4a,5,9b-Hexahydro-1H-indeno[1,2-b]pyridines: potential antidepressants (1984)

The synthesis of various diastereoisomeric H4a,H5-cis,H4a,H9b-cis- and H4a,H5-trans,H4a,H9b-cis-2,3,4,4a,5,9b-hexahydro -1H-indeno[1,2-b]pyridines is described, as well as the evaluation of their antidepressant potency. Elucidation of structure-activity relationships revealed the H4a,H5-trans compounds as being by far the more active of the two series of diastereoisomers. Pharmacological and biochemical data suggest that these compounds are potential antidepressants with central stimulating properties, which are characterized by strong norepinephrine and dopamine reuptake inhibition.
A Method to Selectively Observe a Desired Linear Combination of Chemical Shifts in GFT Projection NMR Spectroscopy (2008)

In recent years, several new methods have emerged for rapid NMR data collection. One class of methods is projection NMR spectroscopy, which involves phase sensitive joint sampling of two or more chemical shifts in an indirect dimension of a multidimensional NMR experiment. In the current implementations of this method, cosine/sine modulation of all chemical shifts involved in the joint sampling are collected and stored as separate FIDs. A post-acquisition data processing step (application of G-matrix) then separates the different inter-modulations of chemical shifts. Thus, joint sampling of K+1 spins results in 2 K combination of chemical shifts (also representing 2 K projection angles). One limitation of this approach is that even if only a few of the 2 K components of the multiplet (or projection angles) is desired, an entire data set containing information for all 2 K shift combinations is collected. We propose here a simple method which releases this restriction and allows one to selectively detect only the desired linear combination of chemical shifts/projection angles out of 2 K combinations in a phase sensitive manner. The method involves selecting the appropriate cosine/sine modulations of chemical shifts and forming the desired linear combination by phase cycling of the radiofrequency pulses and receiver. This will benefit applications where only certain linear combination of shifts are desired or/and are sufficient. Further, G-matrix transformation required for forming the linear combination is performed within the pulse sequence. This avoids the need for any post-acquisition data processing. Taken together, this mode of data acquisition will foster new applications in projection NMR spectroscopy for rapid resonance assignment and structure determination.
A New Approach Formation Tester Interval Pressure Transient Test Design (2012)

Abstract Increased deepwater drilling today requires that expensive and risky drillstem testing operations be optimized by other technologies that provide dynamic information about the formations to be tested. Wireline-conveyed interval pressure transient tests (IPTTs) are becoming a common practise today for optimizing and designing these expensive tests. Typically, prior to an IPTT, there is only a limited amount of information available about the reservoir and fluids properties and it tends to be generally probabilistic. Therefore, the optimal design of IPTT tests is a necessary challenge for a successful and reliable test. IPTT is found to be dependent on the noise and on observable flow regimes associated with the pressure buildups. Success and reliability are not only a function of gauge metrology but also of the formation deliverability and geometry. This paper describes a new methodology for IPTT design that allows estimation of the reliability of these transient tests. A normally distributed random noise is superimposed on the analytical pressure profile computed for a given formation, fluid PVT properties, and gauge metrology. The success of an IPTT in a particular environment is estimated based on the theoretical pressure derivative and noise-superimposed pressure derivative. This approach is repeated for a range of rock, and fluid properties and practical limits to identify what is a successful. Two field examples are presented to validate this methodology.
SADHAN (2019)

Recently false claims and misinformation have become rampant in the web, affecting election outcomes, societies and economies. Consequently, fact checking websites such as snopes.com and politifact.com are becoming popular. However, these websites require expert analysis which is slow and not scalable. Many recent works try to solve these challenges using machine learning models trained on a variety of features and a rich lexicon or more recently, deep neural networks to avoid feature engineering. In this paper, we propose hierarchical deep attention networks to learn embeddings for various latent aspects of news. Contrary to existing solutions which only apply word-level self-attention, our model jointly learns the latent aspect embeddings for classifying false claims by applying hierarchical attention. Using several manually annotated high quality datasets such as Politifact, Snopes and Fever we show that these learned aspect embeddings are strong predictors of false claims. We show that latent aspect embeddings learned from attention mechanisms improve the accuracy of false claim detection by up to 13.5% in terms of Macro F1 compared to a state-of-the-art attention mechanism guided by claim-text DeClarE. We also extract and visualize the evidence from the external articles which supports or disproves the claims
COLLOIDAL NICKEL BORIDE WITHOUT PROTECTIVE AGENT AND ITS CATALYTIC ACTIVITY FOR OLEFIN HYDROGENATION (1981)

Abstract A stable dispersion of colloidal nickel boride was prepared from a dilute solution of nickel(II) chloride in ethanol by sodium borohydride reduction in the absence of protective colloid polymers. The colloid is superior to the conventional poly(vinylpyrrolidone)-protected one in the catalytic activity for the hydrogenation of styrenes and unsaturated carbonyl compounds.
Distributed turbo coding with hybrid relaying protocols (2008)

Distributed turbo coding (DTC) has been shown to be an effective coding scheme to approach the capacity of a wireless relay network. However, most of existing DTC schemes only consider a relay network with single relay node and assume that relay can perform an error free decoding, which we refer to as a perfect DTC scheme. In this paper, we consider a general 2-hop relay network with an arbitrary number of relays and design the DTC for such a network when taking into account imperfect decoding at each relay. We propose a generalized distributed turbo coding (GDTC) scheme with hybrid relaying protocol for such relay networks. In each transmission, based on whether relays can decode correctly or not, each relay is included into one of two relay groups, referred to as a decode and forward (DAF) relay group and an amplify and forward (AAF) relay group. Each relay in the DAF relay group decodes the received signals from the source, interleaves, re-encodes and forwards it to the destination, while each relay in the AAF relay group amplifies the received signals and forwards it to the destination. At the destination, all signals transmitted from the relays in the DAF relay group are combined into one signal and that in the AAF relay group are combined into another signal. These two signals form a generalized DTC codeword. Theoretical analysis and simulation results show that the proposed GDTC scheme benefits from a significant coding gain contributed from the DTC relay group compared to the distributed coding with pure AAF relaying and simultaneously overcome the detrimental effects of error propagation due to the imperfect decoding at relays in the conventional DTC schemes. It also approaches the perfect DTC as the signal to noise ratio (SNR) increases.
Gas path seal (1979)

A gas path seal suitable for use with a turbine engine or compressor is described. A shroud wearable or abradable by the abrasion of the rotor blades of the turbine or compressor shrouds the rotor bades. A compliant backing surrounds the shroud. The backing is a yieldingly deformable porous material covered with a thin ductile layer. A mounting fixture surrounds the backing.
Conversion of a Putative Agrobacterium Sugar-binding Protein into a FRET Sensor with High Selectivity for Sucrose (2006)

Glucose is the main sugar transport form in animals, whereas plants use sucrose to supply non-photosynthetic organs with carbon skeletons and energy. Many aspects of sucrose transport, metabolism, and signaling are not well understood, including the route of sucrose efflux from leaf mesophyll cells and transport across vacuolar membranes. Tools that can detect sucrose with high spatial and temporal resolution in intact organs may help elucidate the players involved. Here, FRET sensors were generated by fusing putative sucrose-binding proteins to green fluorescent protein variants. Plant-associated bacteria such as Rhizobium and Agrobacterium can use sucrose as a nutrient source; sugar-binding proteins were, thus, used as scaffolds for developing sucrose nanosensors. Among a set of putative sucrose-binding protein genes cloned in between eCFP and eYFP and tested for sugar-dependent FRET changes, an Agrobacterium sugar-binding protein bound sucrose with 4 mum affinity. This FLIPsuc-4mu protein also recognized other sugars including maltose, trehalose, and turanose and, with lower efficiency, glucose and palatinose. Homology modeling enabled the prediction of binding pocket mutations to modulate the relative affinity of FLIPsuc-4mu for sucrose, maltose, and glucose. Mutant nanosensors showed up to 50- and 11-fold increases in specificity for sucrose over maltose and glucose, respectively, and the sucrose binding affinity was simultaneously decreased to allow detection in the physiological range. In addition, the signal-to-noise ratio of the sucrose nanosensor was improved by linker engineering. This novel reagent complements FLIPs for glucose, maltose, ribose, glutamate, and phosphate and will be used for analysis of sucrose-derived carbon flux in bacterial, fungal, plant, and animal cells.
Uterus-targeted liposomes for preterm labor management: studies in pregnant mice (2016)

Preterm labor caused by uterine contractions is a major contributor to neonatal morbidity and mortality. Treatment intended to reduce uterine contractions include tocolytic agents, such as indomethacin. Unfortunately, clinically used tocolytics are frequently inefficient and cross the placenta causing fetal side effects. Here we show for the first time in obstetrics the use of a targeted nanoparticle directed to the pregnant uterus and loaded with a tocolytic for reducing its placental passage and sustaining its efficacy. Nanoliposomes encapsulating indomethacin and decorated with clinically used oxytocin receptor antagonist were designed and evaluated in-vitro, ex-vivo and in-vivo. The proposed approach resulted in targeting uterine cells in-vitro, inhibiting uterine contractions ex-vivo, while doubling uterine drug concentration, decreasing fetal levels, and maintaining the preterm birth rate in vivo in a pregnant mouse model. This promising approach opens new horizons for drug development in obstetrics that could greatly impact preterm birth, which currently has no successful treatments.
Interaction of monoclonal antibodies with soybean trypsin inhibitors (1987)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTInteraction of monoclonal antibodies with soybean trypsin inhibitorsDavid L. Brandon, Sakhina Haque, and Mendel FriedmanCite this: J. Agric. Food Chem. 1987, 35, 2, 195–200Publication Date (Print):March 1, 1987Publication History Published online1 May 2002Published inissue 1 March 1987https://pubs.acs.org/doi/10.1021/jf00074a008https://doi.org/10.1021/jf00074a008research-articleACS PublicationsRequest reuse permissionsArticle Views101Altmetric-Citations24LEARN 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-Alertsclose Get e-Alerts
Circulating tumor cell detection using a parallel flow micro-aperture chip system (2015)

We report on-chip isolation and detection of circulating tumor cells (CTCs) from blood samples using a system that integrates a microchip with immunomagnetics, high-throughput fluidics and size-based filtration. CTCs in a sample are targeted via their surface antigens using magnetic beads functionalized with antibodies. The mixture is then run through a fluidic chamber that contains a micro-fabricated chip with arrays of 8 μm diameter apertures. The fluid runs parallel to the microchip while a magnetic field is generated underneath to draw the beads and cells bound to them toward the chip surface for detection of CTCs that are larger than the apertures and clear out free beads and other smaller particles bound to them. The parallel flow configuration allows high volumetric flow rates, which reduces nonspecific binding to the chip surface and enables multiple circulations of the sample fluid through the system in a short period of time. In this study we first present models of the magnetic and fluidic forces in the system using a finite element method. We then verify the simulation results experimentally to determine an optimal flow rate. Next, we characterize the system by detecting cancer cell lines spiked into healthy human blood and show that on average 89% of the spiked MCF-7 breast cancer cells were detected. We finally demonstrate detection of CTCs in 49 out of 50 blood samples obtained from non-small cell lung cancer (NSCLC) patients and pancreatic cancer (PANC) patients. The number of CTCs detected ranges from 2 to 122 per 8 mL s of blood. We also demonstrate a statistically significant difference between the CTC counts of NSCLC patients who have received therapy and those who have not.
A Practical and Efficient Process for the Preparation of Tazarotene (2005)

We describe an efficient process for the preparation of tazarotene starting from 4,4-dimethyl-6-bromothiochromane S-oxide (9), 2-methyl-3-butyn-2-ol (10), and 6-chloronicotinic acid ethyl ester (8). Our synthetic pathway compares favorably over the previously reported procedures since tazarotene was prepared straightforwardly using cheap reagents and without the employment of hazardous organometallic compounds. The process is based on the use of sulfoxide 9 as key starting material. The C-15 framework of the target was built up by means of two different approaches based on a palladium-mediated coupling reaction. The molecular structure of compound has been confirmed by X-ray crystallography.
Tobamovirus‐resistant tobacco generated by RNA interference directed against host genes (2005)

Two homologous Nicotiana tabacum genes NtTOM1 and NtTOM3 have been identified. These genes encode polypeptides with amino acid sequence similarity to Arabidopsis thaliana TOM1 and TOM3, which function in parallel to support tobamovirus multiplication. Simultaneous RNA interference against NtTOM1 and NtTOM3 in N. tabacum resulted in nearly complete inhibition of the multiplication of Tomato mosaic virus and other tobamoviruses, but did not affect plant growth or the ability of Cucumber mosaic virus to multiply. As TOM1 and TOM3 homologues are present in a variety of plant species, their inhibition via RNA interference should constitute a useful method for generating tobamovirus-resistant plants.
Measuring optical waveforms with fiber frequency combs (2009)

A stabilized frequency comb provides a broadband array of highly resolved comb lines. Using a multiheterodyne technique, we measure the amplitude and phase of every comb line, allowing for massively parallel, high-resolution optical sampling.
Fc Optimization of Therapeutic Antibodies Enhances Their Ability to Kill Tumor Cells <i>In vitro</i> and Controls Tumor Expansion <i>In vivo</i> via Low-Affinity Activating Fcγ Receptors (2007)

Monoclonal antibodies (mAb) are widely used in the treatment of non-Hodgkin's lymphoma and autoimmune diseases. Although the mechanism of action in vivo is not always known, the therapeutic activity of several approved mAbs depends on the binding of the Fcgamma regions to low-affinity Fcgamma receptors (FcgammaR) expressed on effector cells. We did functional genetic screens to identify IgG1 Fc domains with improved binding to the low-affinity activating Fc receptor CD16A (FcgammaRIIIA) and reduced binding to the low-affinity inhibitory Fc receptor, CD32B (FcgammaRIIB). Identification of new amino acid residues important for FcgammaR binding guided the construction of an Fc domain that showed a dramatically enhanced CD16A binding and greater than a 100-fold improvement in antibody-dependent cell-mediated cytotoxicity. In a xenograft murine model of B-cell malignancy, the greatest enhancement of an Fc-optimized anti-human B-cell mAb was accounted for by improved binding to FcgammaRIV, a unique mouse activating FcgammaR that is expressed by monocytes and macrophages but not natural killer (NK) cells, consistent with experimental and clinical data suggesting that mononuclear phagocytes, effector cells expressing both activating and inhibitory FcgammaR, are critical mediators of B-cell depletion in vivo. By using mice transgenic for human CD16A, enhanced survival was observed due to expression of CD16A-158(phe) on monocytes and macrophages as well as on NK cells in these mice. The design of new generations of improved antibodies for immunotherapy should aim at Fc optimization to increase the engagement of activating FcgammaR present on the surface of tumor-infiltrating effector cell populations.