gebhart/patrepeval huggingface dataset:
Real-Time Intravital Imaging of RGD−Quantum Dot Binding to Luminal Endothelium in Mouse Tumor Neovasculature (2008)

Nanoscale materials have increasingly become subject to intense investigation for use in cancer diagnosis and therapy. However, there is a fundamental dearth in cellular-level understanding of how nanoparticles interact within the tumor environment in living subjects. Adopting quantum dots (qdots) for their excellent brightness, photostability, monodispersity, and fluorescent yield, we link arginine-glycine-aspartic acid (RGD) peptides to target qdots specifically to newly formed/forming blood vessels expressing alpha vbeta 3 integrins. Using this model nanoparticle system, we exploit intravital microscopy with subcellular ( approximately 0.5 microm) resolution to directly observe and record, for the first time, the binding of nanoparticle conjugates to tumor blood vessels in living subjects. This generalizable method enabled us to show that in this model qdots do not extravasate and, unexpectedly, that they only bind as aggregates rather than individually. This level of understanding is critical on the path toward ensuring regulatory approval of nanoparticles in humans for disease diagnostics and therapeutics. Equally vital, the work provides a platform by which to design and optimize molecularly targeted nanoparticles including quantum dots for applications in living subjects.
Wettability of naturally aged silicon and EPDM composite insulators (1990)

The wettability of aged surfaces and of the bulk of naturally aged silicone and EPDM (ethylene-propylene diener monomer) insulator housings and silicone elastomer insulator coatings was studied. The samples were taken either directly from the insulators or treated by exposing them to corona discharges and/or to saline pollution. The results show that the contact angles of the silicone rubber insulator surfaces are larger than the contact angles of the RTV (room-temperature vulcanizing) silicone rubber coating and of the EPDM rubber insulator surfaces, especially when the surfaces are aged. When the insulators were exposed to corona discharges, the contact angles of the silicone rubber insulators are reduced but after exposure recover with time. The contact angles of the EPDM rubber insulators, however, continue to reduce after the exposure. When exposed to artificial saline pollution, the silicone rubber insulators show a limited recovery of their contact angles with time, while when exposed to corona discharge after saline pollution, they show a recovery of the contact angle after the exposure. The recovery time is dependent on the exposure time to the corona discharges. The EPDM samples do not show any recovery of their contact angles, either when left to rest after the salt deposition or, when after the salt deposition, they undergo a subsequent exposure to corona discharges. Furthermore, such an exposure may be deleterious for the EPDM polymer and the insulator surface may become completely hydrophylic.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Document Transformation System from Papers to XML Data Based on Pivot XML Document Method (2004)

This paper proposes a new method for document transformation using OCR to generate various XML documents from printed documents. The proposed method adopts a hierarchical transformation strategy based on a pivot XML document. Firstly, document elements such as title, authors, abstract, headings, paragraphs, lists, captions, tables and figures are extracted from document images. Secondly, the hierarchical structure of document elements is extracted and is described using a DOM tree. Thirdly, this document structure is converted into a pivot XML document described as an XHTML document by an XML parser. Finally, this pivot XML document is transformed into the target XML document by the XML parser with XSLT scripts or specific programs. Experimental results show the method is effective in transforming printed documents to various XML documents.
Deep Learning for Consumer Devices and Services: Pushing the limits for machine learning, artificial intelligence, and computer vision (2017)

In the last few years, we have witnessed an exponential growth in research activity into the advanced training of convolutional neural networks (CNNs), a field that has become known as deep learning. This has been triggered by a combination of the availability of significantly larger data sets, thanks in part to a corresponding growth in big data, and the arrival of new graphics-processing-unit (GPU)-based hardware that enables these large data sets to be processed in reasonable timescales. Suddenly, a wide variety of long-standing problems in machine learning, artificial intelligence, and computer vision have seen significant improvements, often sufficient to break through long-standing performance barriers. Across multiple fields, these achievements have inspired the development of improved tools and methodologies leading to even broader applicability of deep learning. The new generation of smart assistants, such as Alexa, Hello Google, and others, have their roots and learning algorithms tied to deep learning. In this article, we review the current state of deep learning, explain what it is, why it has managed to improve on the long-standing techniques of conventional neural networks, and, most importantly, how you can get started with adopting deep learning into your own research activities to solve both new and old problems and build better, smarter consumer devices and services.
Dependence of the distribution constant in liquid–liquid partition equilibria on the van der Waals molecular surface area (2013)

The direct calculation of free energy of interactions between a solute j and two immiscible liquids shows a linear dependence between the (logarithm of) the distribution constant in liquid-liquid partition equilibrium log K(j) and the van der Waals surface area of the solute. The study provides a thermodynamic proof for the formula log K(BA,j) = c1 log K(BC,j) + c2 that describes the linear dependence between (the logarithm of) the distribution constant for a solute j in a solvent system (B/A) and (the logarithm of) the distribution constant for the same solute in a different solvent system (B/C). This relation has been well proven by various experimental studies and it is frequently used in liquid chromatographic separations as well as in liquid-liquid extractions, but was not explained previously based on thermodynamic results. The theory was verified using the prediction of octanol/water distribution constants log K(ow) for a wide range of molecules, including hydrocarbons and compounds with a variety of functional groups. The results have also been verified for the distribution constants in other solvent systems. The expression for the distribution constant obtained in this study also gives a theoretical base for the additive fragment methodology used for the prediction of log K(ow).
Influence of Chemical Equilibria on Oxygen Reduction Reaction in Molten Carbonate (1990)

A good understanding of the melt chemistry is essential for a correct interpretation of electrode kinetic data of oxygen reduction in molten carbonate. The interaction of various species in Li‐K eutectic carbonate melt is investigated by adding small amounts of oxide, peroxide, or superoxide to the equilibrated melt and observing the response of the equilibrium potential. The effect of oxide addition on stationary polarization and on potential step current transients is also studied. Chemical equilibria between oxygen and various oxide species are established rapidly, whereas neutralization reactions involving are remarkably slow.
Study and Analysis of a New Implementation of a Mixed-Signal Cartesian Feedback for a Low Power Zero-IF WCDMA Transmitter (2013)

International audience
Temporal Averaging LSTM-based Channel Estimation Scheme for IEEE 802.11p Standard (2021)

In vehicular communications, reliable channel estimation is critical for the system performance due to the doubly-dispersive nature of vehicular channels. IEEE 802.11p standard allocates insufficient pilots for accurate channel tracking. Consequently, conventional IEEE 802.11p estimators suffer from a considerable performance degradation, especially in high mobility scenarios. Recently, deep learning (DL) techniques have been employed for IEEE 802.11p channel estimation. Neverthe-less, these methods suffer either from performance degradation in very high mobility scenarios or from large computational complexity. In this paper, these limitations are solved using a long short term memory (LSTM)-based estimation. The proposed estimator employs an LSTM unit to estimate the channel, followed by temporal averaging (TA) processing as a noise alleviation technique. Moreover, the noise mitigation ratio is determined analytically, thus validating the TA processing ability in improving the overall performance. Simulation results reveal the performance superiority of the proposed schemes compared to the recently proposed DL-based estimators, while recording a significant reduction in the computational complexity.
Metastasis suppressor gene Raf kinase inhibitor protein (RKIP) is a novel prognostic marker in prostate cancer (2005)

In contrast to increased expression of pro-tumorigenic genes, these results demonstrate decreased protein expression of a gene, for example, RKIP, can serve as a prognostic marker in PCa patients.
Nanostructured Magnesium Composite Coatings for Corrosion Protection of Low-Alloy Steels (2014)

Corrosion of base metals represents a tremendous problem that has spurred a global search for cost-effective and environmentally friendly alternatives to current corrosion-inhibiting technologies. In this work, we report a novel sustainable hybrid Mg/poly(ether imide) (PEI) nanocomposite coating that provides corrosion protection to low-alloy steels at relatively low coating thicknesses and with reduced weight as compared to conventional metallic coatings. The coatings are constituted using Mg nanoplatelets dispersed within a polyamic acid matrix that is subsequently imidized on the steel substrate to form PEI. The coatings function through a combination of sacrificial cathodic protection (afforded by the preferential oxidation of the Mg nanoplatelets), anodic passivation through precipitation of corrosion products, and the inhibitive action of the PEI polymeric matrix. The use of nanostructured Mg allows for reduced coating thicknesses and a smoother surface finish, whereas the PEI matrix provides excellent adhesion to the metal surface. Based on potentiodynamic testing and prolonged exposure to saline environments, the novel coating materials significantly outperform galvanized Zn and Zn-rich primer coatings of comparable thickness.
Flexible Joint Actuator for Patient's Rehabilitation Device (2007)

Rehabilitation devices require a very precise actuating system. In this paper, a flexible joint actuator is proposed as an actuating system of an intelligent active orthosis. To generate joint torque as desired, a spring is installed between a motor and human joint and the motor is controlled to have a proper spring deflection for torque control. When the desired torque is zero, the motor should follow human joint motion which requires that the friction and inertia of the motor are compensated. The human joint and body part represent the load to the flexible joint actuator. They interact with environment and their parameters are not fixed. The controller for the flexible joint actuator must operate under these conditions.
A Breath Ammonia Sensor Based on Conducting Polymer Nanojunctions (2008)

We present an ammonia sensor for human breath analysis based on electrically conducting polymer nanojunctions. Each nanojunction is formed by bridging a pair of gold nanoelectrodes on a silicon chip separated by a small gap (<60 nm) with electrodeposited polyaniline. The signal transduction mechanism of the sensor is the change in the nanojunction conductance as a result of polymer dedoping by ammonia. The sensor response to human breath is validated by comparison with a reference method for detection of ammonium ion combined with an optimized breath ammonia trapping system. The nanojunction sensor is capable of in situ detection of parts per billion (ppb) levels of ammonia in human breath.
Dipyranoside precursors for ansamycins. Pyranosidic homologation. 5 (1987)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTDipyranoside precursors for ansamycins. Pyranosidic homologation. 5Bert Fraser-Reid, Leon Magdzinski, Bruce F. Molino, and David R. MootooCite this: J. Org. Chem. 1987, 52, 20, 4495–4504Publication Date (Print):October 1, 1987Publication History Published online1 May 2002Published inissue 1 October 1987https://pubs.acs.org/doi/10.1021/jo00229a013https://doi.org/10.1021/jo00229a013research-articleACS PublicationsRequest reuse permissionsArticle Views415Altmetric-Citations44LEARN 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
Combating Adversarial Attacks Using Sparse Representations (2018)

It is by now well-known that small adversarial perturbations can induce classification errors in deep neural networks (DNNs). In this paper, we make the case that sparse representations of the input data are a crucial tool for combating such attacks. For linear classifiers, we show that a sparsifying front end is provably effective against $\ell_{\infty}$-bounded attacks, reducing output distortion due to the attack by a factor of roughly $K / N$ where $N$ is the data dimension and $K$ is the sparsity level. We then extend this concept to DNNs, showing that a "locally linear" model can be used to develop a theoretical foundation for crafting attacks and defenses. Experimental results for the MNIST dataset show the efficacy of the proposed sparsifying front end.
Immunomodulatory, cytotoxic and antileishmanial activity of phytoconstituents of Croton zambesicus (2013)

The root extract and fractions of Croton zambesicus were investigated for anticancer activity against HeLa cells, DNA interaction, immunomodulatory and antileishmanial activities. The GCMS analysis of the most active fraction against HeLa cell was carried. The root extract was found to exert significant anticancer activity with the hexane fraction exhibiting the most pronounced effect. The crude extract and the fractions did not interact with yeast DNA when investigated using electrophoresis. The extract demonstrated prominent antioxidant activity in whole blood, neutrophils and macrophages. The extract also exhibited moderate antileishmanial activity against promastigotes of Leishmania major in vitro. These results suggest that the root extract/fractions of croton zambesicus possesses anticancer, immunomodulatory and antileishmanial activities and these justify its use in ethnomedicine to treat cancer and microbial infections and can be exploited in primary healthcare.
Mesenchymal Stromal Cells as a Therapeutic Intervention (2019)

Mesenchymal stem cells, also known as mesenchymal stromal cells (MSCs), are a safe and promising biologic therapeutic for inducing tissue repair and regeneration in a broad array of chronic diseases. The mechanisms underlying the beneficial effects of MSCs include immunomodulation, reduction in inflammation and fibrosis, and stimulation of neovascularization and endogenous regeneration. Accumulating evidence from a multitude of clinical trials support the notion that both autologous and allogeneic MSCs are not only safe but also possess the capacity for repair of diverse organ systems and amelioration of multiple chronic disease processes. However, there are many questions regarding the underlying mechanisms of action, the most efficacious cell characteristics, tissue source, dose/concentration, route of delivery, and timing of administration, interactions with concurrent therapies, sustainability of effect, donor and patient characteristics, and adverse effects, including infections and malignancy, that remain to be resolved. Answering these questions will require well-designed and rigorously conducted multicenter clinical trials with well-established and defined clinical endpoints and appropriately defined patient populations, number of patients, and duration of follow-up. This chapter will review the current state of knowledge in the use of MSCs as a therapeutic strategy for organ structural and functional repair in chronic diseases.
Font rendering on a GPU-based raster image processor (2009)

Historically, in the 35 years of digital printing research, raster image processing has always lagged behind marking engine technology, i.e., we have never been able to deliver rendered digital pages as fast as digital print engines can consume them. This trend has resulted in products based on throttled digital printers or expensive raster image processors (RIP) with hardware acceleration. The current trend in computer software architecture is to leverage graphic processing units (GPU) for computing tasks whenever appropriate. We discuss the issues for rendering fonts on such an architecture and present an implementation.
Analysis of abdominal injuries caused by the submarining phenomenon in the rear seat occupants (2015)

Improvements to vehicle safety have targeted mainly the front seating positions, where the rate of seat belt usage was high and there were many casualties. Recently, rear seat occupant protection become an important challenge, with an increase in usage of seat belts by rear occupants due to new regulations and new performance criteria defined by Japanese and European vehicle assessment programs for rear seating occupants. Some prior analyses of accident data indicate that rear seat belted occupants tend to be injured in abdominal regions in comparison with front seat occupants. Due to this, the need to study the cause of abdominal injuries and how to countermeasure it is becoming indispensable for improving the protection performance of the rear seat occupants. The following two phenomenons are considered as factors which great impacts on abdominal injuries: the submarining phenomenon, lap belt intruding into abdominal region, and the incorrect routing of the belt, lap belt existing initially on abdominal region. However, the relationship between these probable causes and the abdominal injuries in the real world accident is not expressly described in prior studies. Therefore, first, the frequency of the abdominal injuries caused by the submarining phenomenon was estimated by micro analysis of the accident data. Second, the influence on abdominal internal organs, to which the lap belt load was applied, was analyzed using human body finite element (FE) model THUMS. The results of this analysis indicated that the effect might be applied to abdominal internal organs. As the routing of the lap belt on the pelvis was shown as being very important in this study, a parametric study using Madymo was conducted to determine additional factors that might influence the proper routing of the belt on pelvis. This study narrowed down the factors with big contribution and explains how they were determined.
Therapeutic Remodeling of the Tumor Microenvironment Enhances Nanoparticle Delivery (2019)

Abstract A major challenge in the development of cancer nanomedicine is the inability for nanomaterials to efficiently penetrate and deliver therapeutic agents into solid tumors. Previous studies have shown that tumor vasculature and extracellular matrix regulate the transvascular and interstitial transport of nanoparticles, both critical for successfully delivering nanomedicine into solid tumors. Within the malignant tumor microenvironment, blood vessels are morphologically abnormal and functionally exhibit substantial permeability. Furthermore, the tumor extracellular matrix (ECM), unlike that of the normal tissue parenchyma, is densely packed with collagen. These pathophysiological properties greatly impede intratumoral delivery of nanomaterials. By using an antivascular endothelial growth factor receptor antibody, DC101, and an antitransforming growth factor β1 (TGF‐β1) antibody, normalization of the tumor vasculature and ECM is achieved, respectively, in a syngeneic murine glioma model. This normalization effect results in a more organized vascular network, improves tissue perfusion, and reduces collagen density, all of which contribute to enhanced nanoparticle delivery and distribution within tumors. These findings suggest that combined vascular and ECM normalization strategies can be used to remodel the tumor microenvironment and improve nanomedicine delivery into solid tumors, which has significant implications for developing more effective combinational therapeutic strategies using cancer nanomedicine.
ε -optimization schemes and L-bit precision (extended abstract) (2000)

Motivated by the need to deal with imprecise data in realworld optimization problems, we introduce two new models for algorithm design and analysis. The first model, called the L-bit precision model leads to an alternate concept of polynomial-time solvability. Expressing numbers in L-bit precision reflects the format in which large numbers are stored in computers today. The second concept, called eoptimization provides an alternative approach to approximation schemes for measuring distance from optimality. In contrast to the worst-case relative error, the notion of an eoptimal solution is invariant under subtraction of a constant from the objective function, and it is properly defined even if the objective function takes on negative values. Besides discussing the relation between these two models and preexisting concepts, we focus on designing polynomialtime algorithms for solving NP-hard problems in which some or all of the data is expressed with L-bit precision, and on designing fully polynomial-time e-optimization schemes for NP-hard problems including those that do not possess fully polynomial-time approximation schemes, unless P = NP.
Designs for broad-band cavity-coupled microstrip directional couplers (2011)

Cavity-coupled designs for microstrip directional couplers are presented in this paper. Different coupling coefficients are pursued. All the designs feature a cavity in an electrically thick ground plane, which serves as a common ground for two back-to-back microstrip lines. These cavity-coupled designs can offer more bandwidth compared to their corresponding slot-coupled designs. Finite element method is chosen to carry out the required simulations for the proposed designs because of its accuracy. The validity of the simulation results is verified experimentally and good agreement is observed.