gebhart/patrepeval huggingface dataset:
Controlling dielectric loss and ionic conductivity through processing optimization of electrostrictive polymers (2018)

Electro-active polymers (EAPs) such as P(VDF-TrFE-CTFE) was demonstrated to be greatly promising in the field of flexible sensors and actuators[1], but their low dielectric strength driven by ionic conductivity is main concern for achieving high electrostrictive performance. The well-known quadratic dependence of applied electric field on strain response as well as mechanical energy density highlights the importance of improving EAPs electrical breakdown while reducing the leakage current. This paper demonstrates that by controlling processing parameters of polymer synthesis and fabrication procedure, it is possible to drastically increase the electrical breakdown and decrease the ionic conductivity, giving rise to an enhancement in breakdown voltage of around 64% and a reduction in leakage current intensity of 73% at 30V/&mu;m. Effect of polymer crystallinity, molecular mass, as well as crystallization temperature on leakage current were also investigated..
The end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia (2022)

Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.
Implementation of deep neural networks to count dopamine neurons in substantia nigra (2018)

Unbiased estimates of neuron numbers within substantia nigra are crucial for experimental Parkinson's disease models and gene-function studies. Unbiased stereological counting techniques with optical fractionation are successfully implemented, but are extremely laborious and time-consuming. The development of neural networks and deep learning has opened a new way to teach computers to count neurons. Implementation of a programming paradigm enables a computer to learn from the data and development of an automated cell counting method. The advantages of computerized counting are reproducibility, elimination of human error and fast high-capacity analysis. We implemented whole-slide digital imaging and deep convolutional neural networks (CNN) to count substantia nigra dopamine neurons. We compared the results of the developed method against independent manual counting by human observers and validated the CNN algorithm against previously published data in rats and mice, where tyrosine hydroxylase (TH)-immunoreactive neurons were counted using unbiased stereology. The developed CNN algorithm and fully cloud-embedded Aiforia™ platform provide robust and fast analysis of dopamine neurons in rat and mouse substantia nigra.
Treatment with a Cholecystokinin Receptor Antagonist, Proglumide, Improves Efficacy of Immune Checkpoint Antibodies in Hepatocellular Carcinoma (2023)

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-associated deaths worldwide. Treatment with immune checkpoint antibodies has shown promise in advanced HCC, but the response is only 15-20%. We discovered a potential target for the treatment of HCC, the cholecystokinin-B receptor (CCK-BR). This receptor is overexpressed in murine and human HCC and not in normal liver tissue. Mice bearing syngeneic RIL-175 HCC tumors were treated with phosphate buffer saline (PBS; control), proglumide (a CCK-receptor antagonist), an antibody to programmed cell death protein 1 (PD-1Ab), or the combination of proglumide and the PD-1Ab. In vitro, RNA was extracted from untreated or proglumide-treated murine Dt81Hepa1-6 HCC cells and analyzed for expression of fibrosis-associated genes. RNA was also extracted from human HepG2 HCC cells or HepG2 cells treated with proglumide and subjected to RNA sequencing. Results showed that proglumide decreased fibrosis in the tumor microenvironment and increased the number of intratumoral CD8+ T cells in RIL-175 tumors. When proglumide was given in combination with the PD-1Ab, there was a further significant increase in intratumoral CD8+ T cells, improved survival, and alterations in genes regulating tumoral fibrosis and epithelial-to-mesenchymal transition. RNAseq results from human HepG2 HCC cells treated with proglumide showed significant changes in differentially expressed genes involved in tumorigenesis, fibrosis, and the tumor microenvironment. The use of the CCK receptor antagonist may improve efficacy of immune checkpoint antibodies and survival in those with advanced HCC.
What is the Color of Chocolate? &#x2013; Extracting Color Values of Semantic Expressions (2012)

We present a statistical framework to automatically determine an associated color for a given arbitrary semantic expression. The expression can not only be a color name but any word or character string. In addition to the color value, we are also able to compute the result's significance, which determines how meaningful defining the color is for the expression. To demonstrate the framework's strength we apply it to two well known tasks: assessing memory colors and finding the color values for a given color name (color naming). We emphasize that we solve these tasks fully automatic without any psychophysical experiment or human intervention. Further, we outline the potential of our automatic framework and in particular the significance for the imaging community.
Performance Improvement in Local Feature Based Camera-Captured Character Recognition (2014)

Concerning camera-captured Japanese character recognition, we have proposed a method to recognize characters, both simple and complex, that may not be linearly aligned and may be printed with a complex background. Recognition is performed based on local features and their arrangement. The arrangement is validated with an algorithm called local RANSAC. However, at least four corresponding local features are required. To relax that condition, we propose a new recognition method making it possible to recognize a character region with at least three corresponding local features. This method enables recall and precision to be improved with the simpler characters using more corresponding local features and computation times to be reduced by 7%.
REINAS: A Real-Time System for Managing Environmental Data (1998)

Managing scientific data is a challenging task, and many of the problems it presents have yet to be adequately solved. The Real-time Environmental Information Network and Analysis System (REINAS) is an operational solution to the problem of collecting and distributing environmental data in a real-time context, as well as supporting data acquisition, retrieval, visualization and long-term data maintenance. The system is built around one or more databases and has been developed to support both real-time and retrospective regional scale environmental science. Continuous real-time data is acquired from dispersed sensors and input to a logically integrated but physically distributed system. The database engine provides a powerful structure to handle data management, but current database technology can have difficulty meeting the performance requirements that a large real-time environmental system demands. The REINAS architecture and current status is described in detail, including the challenges that were addressed in the construction of an operational system which includes a regional wireless instrumentation network comprised of over 200 instrument platforms and 1500 sensor streams producing real-time data of interest to thousands of users.
Energy management system for electric vehicle based on user behavior induction (2013)

Electric Vehicles (EV) and charging stations at large commercial centers with solar power generation are focused as a new energy infrastructure. However when many drivers visit to there, the demand of power for charging will be increased and they have to wait in queue until the power recovers. We propose a method to distribute the concentration of charging demand by recommending times for EV charging to the drivers. The charging time for recommendation is determined by each driver's behavior model that is trained as probabilistic model.
Assessment of the Nutraceutical Effects of Oleuropein and the Cytotoxic Effects of Adriamycin, When Administered Alone and in Combination, in MG-63 Human Osteosarcoma Cells (2021)

Oleuropein (OLEU) is the most distinguished phenolic compound found in olive fruit and the leaves of <i>Olea</i> <i>europaea</i> L., with several pharmacological properties, including anti-cancer actions. Adriamycin (ADR) is an anthracycline widely used as a chemotherapeutic agent, although it presents significant side effects. The aim of the present study was to investigate the effect of oleuropein alone (20 μg/mL) and in co-treatment with ADR (50 nM), in MG-63 human osteosarcoma cells. Therefore, cellular and molecular techniques, such as MTT assay, flow cytometry, real-time Polymerase Chain Reaction (PCR), western blot and Elisa method, as well as Nuclear Magnetic Resonance (NMR) spectroscopy, were applied to unveil changes in the signal transduction pathways involved in osteosarcoma cells survival. The observed alterations in gene, protein and metabolite levels denote that OLEU not only inhibits MG-63 cells proliferation and potentiates ADR's cytotoxicity, but also exerts its action, at least in part, through the induction of autophagy.
Novel Mouse Xenograft Models Reveal a Critical Role of CD4+ T Cells in the Proliferation of EBV-Infected T and NK Cells (2011)

Epstein-Barr virus (EBV), a ubiquitous B-lymphotropic herpesvirus, ectopically infects T or NK cells to cause severe diseases of unknown pathogenesis, including chronic active EBV infection (CAEBV) and EBV-associated hemophagocytic lymphohistiocytosis (EBV-HLH). We developed xenograft models of CAEBV and EBV-HLH by transplanting patients' PBMC to immunodeficient mice of the NOD/Shi-scid/IL-2Rγ(null) strain. In these models, EBV-infected T, NK, or B cells proliferated systemically and reproduced histological characteristics of the two diseases. Analysis of the TCR repertoire expression revealed that identical predominant EBV-infected T-cell clones proliferated in patients and corresponding mice transplanted with their PBMC. Expression of the EBV nuclear antigen 1 (EBNA1), the latent membrane protein 1 (LMP1), and LMP2, but not EBNA2, in the engrafted cells is consistent with the latency II program of EBV gene expression known in CAEBV. High levels of human cytokines, including IL-8, IFN-γ, and RANTES, were detected in the peripheral blood of the model mice, mirroring hypercytokinemia characteristic to both CAEBV and EBV-HLH. Transplantation of individual immunophenotypic subsets isolated from patients' PBMC as well as that of various combinations of these subsets revealed a critical role of CD4+ T cells in the engraftment of EBV-infected T and NK cells. In accordance with this finding, in vivo depletion of CD4+ T cells by the administration of the OKT4 antibody following transplantation of PBMC prevented the engraftment of EBV-infected T and NK cells. This is the first report of animal models of CAEBV and EBV-HLH that are expected to be useful tools in the development of novel therapeutic strategies for the treatment of the diseases.
Benchmark Problems and Performance Indicators for Search of Knee Points in Multiobjective Optimization (2019)

In multiobjective optimization, it is nontrivial for decision makers to articulate preferences without a priori knowledge, which is particularly true when the number of objectives becomes large. Depending on the shape of the Pareto front, optimal solutions such as knee points may be of interest. Although several multi- and many-objective optimization test suites have been proposed, little work has been reported focusing on designing multiobjective problems whose Pareto front contains complex knee regions. Likewise, few performance indicators dedicated to evaluate an algorithm's ability of accurately locating all knee points in high-dimensional objective space have been suggested. This paper proposes a set of multiobjective optimization test problems whose Pareto front consists of complex knee regions, aiming to assess the capability of evolutionary algorithms to accurately identify all knee points. Various features related to knee points have been taken into account in designing the test problems, including symmetry, differentiability, and degeneration. These features are also combined with other challenges in solving the optimization problems, such as multimodality, linkage between decision variables, nonuniformity, and scalability of the Pareto front. The proposed test problems are scalable to both decision and objective spaces. Accordingly, new performance indicators are suggested for evaluating the capability of optimization algorithms in locating the knee points. The proposed test problems, together with the performance indicators, offer a new means to develop and assess preference-based evolutionary algorithms for solving multi- and many-objective optimization problems.
Chemical separations with liquid membranes : developed from a symposium sponsored by the Division of Industrial and Engineering Chemistry, Inc. (1996)

Chemical Separations with Liquid Membranes: An Overview A Tribute to Norman N. Li J.D. Way and W.S.W. Ho Mechanistic Studies of Carrier-Mediated Transport Through Supported Liquid Membranes Rational Design of Liquid Membrane Separation Systems Facilitated Transport of Alkali Metal Cations Through Supported Liquid Membranes with Fatty Acids Emulsions for Liquid Membrane Extraction: Properties and Peculiarities Preparation and Splitting of Emulsions for Liquid Membranes Mathematical Modeling of Carrier-Facilitated Transport in Emulsion Liquid Membranes Design of Macrocyclic Carriers for Liquid Membranes New Tactics in Design of Ion-Specific Carriers: Approaches Based on Computer Chemistry and Rare Earth Complex Chemistry New Multidentate Ligand Carriers for Macrocycle-Facilitated Metal Ion Transport Across Liquid Membranes Highly Selective Transport of Heavy Metal Ions by Novel Amide Compounds Transition Metal Cation Separations by Organophosphorus Compounds in Liquid Membrane Processes Sugar Separation Using Liquid Membranes and Boronic Acid Carriers Recent Advances in Emulsion Liquid Membranes Hollow Fiber-Contained Liquid Membranes for Separations: An Overview Facilitated Transport of Carbon Dioxide Through Supported Liquid Membranes of Aqueous Amine Solutions Facilitated Transport of Carbon Dioxide Through Functional Membranes Prepared by Plasma Graft Polymerization Using Amines as Carrier Separation of Ethylene from Ethane Using Perfluorosulfonic Acid Ion-Exchange Membranes Facilitated Transport of Unsaturated Hydrocarbons in Perfluorosulfonic Acid (Nafion) Membranes Heavy Metal Ion Separation by Functional Polymeric Membranes Use of Emulsions, Microemulsions, and Hollow Fiber Contactors as Liquid Membranes Field Testing of a Liquid-Emulsion Membrane System for Copper Recovery from Mine Solutions Removal of Selenium from Contaminated Waters Using Emulsion Liquid Membranes Supported Liquid Membranes in Metal Separations Cesium Removal from Nuclear Waste Water by Supported Liquid Membranes Containing Calix-bis-crown Compounds Separation of Radiotoxic Actinides from Reprocessing Wastes with Liquid Membranes
The effect of felbamate on valproic acid disposition (1994)

When felbamate is added to a regimen of valproic acid, valproic acid doses may require reduction because coadministration of felbamate decreased steady-state valproic acid clearance (28% and 54%, respectively; p < 0.01).
Mathematical Model for Three-Phase Compressible Dual Porosity Streamline Simulation (2006)

Flow simulation of fractured reservoirs usually is performed using a dual porosity model. The dual porosity system is modeled by using two coupled grids: one for matrix and one for fracture. These two continua communicate by transfer functions. Until now, there were no mathematical models of dual porosity, three-phase, compressible flow for streamline simulators. To realize this model, it was necessary to reformulate the matrix and fracture pressure equations The conventional transfer function has been incorporated as a source/sink term, not only in the streamline saturation equations (as it was in incompressible case), but also in the pressure equation.&lt;br&gt;&lt;br&gt;The dual porosity model has been implemented into a streamline simulator. This tool has its main application in the geological modeling domain for analyzing uncertainty, model ranking and screening of geologically detailed models, including fractures.&lt;br&gt;&lt;br&gt;This paper describes the mathematical model for a three-phase compressible dual porosity streamline simulator and compares the results and run times of the streamline-based approach with a conventional dual porosity grid-based commercial simulator. The results from the streamline simulator for dual porosity show good agreement with those produced by a commercial finite difference simulator with order of magnitude improvement in simulation time.&lt;br&gt;Streamline methods as a reservoir simulation tool have generated much interest in petroleum engineering because of the capability to calculate fluid flow in multi-million cell geological models with reasonable CPU times. However, important physical properties of geo-scale fluid flow models are still not properly modeled by streamline methods. Enhancing the range of physical properties that can be simulated accurately in a timely manner will enable improved workflows in the geological modeling domain.&lt;br&gt;&lt;br&gt;
Supplementary Methods, Tables 1 - 3 from Identification and Analysis of <i>In Vivo</i> VEGF Downstream Markers Link VEGF Pathway Activity with Efficacy of Anti-VEGF Therapies (2023)

&lt;p&gt;PDF file - 180K, Table S1. Genes in the VDV signature, ordered by anti-VEGF response in human IBC trial. Table S2. Gene Ontology terms over-represented in VDV signature. Table S3. Summary of tumors models tested.&lt;/p&gt;
Calreticulin chaperones regulate functional expression of vomeronasal type 2 pheromone receptors (2011)

A variety of social behaviors like intermale aggression, fear, and mating rituals are important for sustenance of a species. In mice, these behaviors have been implicated to be mediated by peptide pheromones that are sensed by a class of G protein-coupled receptors, vomeronasal receptor type 2 (V2Rs), expressed in the pheromone detecting vomeronasal organ. Matching V2Rs with their cognate ligands is required to learn what receptors the biologically relevant pheromones are acting on. However, this feat has been greatly limited by the unavailability of appropriate heterologous tools commonly used to study ligand receptor specificity, because this family of receptors fails to traffic to the surface of heterologous cells. Here we show that calreticulin, a housekeeping chaperone commonly expressed in most eukaryotic cells, is sparsely expressed in the vomeronasal sensory neurons (VSNs). Correspondingly, knockdown of calreticulin in commonly available cell lines enables V2Rs to efficiently target to the cell membrane. Using this knowledge, we have now been able to successfully surface express receptors and functionally identify cognate ligands. Additionally, calreticulin4, a homolog of calreticulin shows restricted and enriched expression in the VSNs. Interestingly, in heterologous cells, calreticulin4 does not inhibit surface expression of V2Rs and can in part carry out functions of calreticulin. On the basis of our data, we postulate that V2Rs may use a unique trafficking mechanism whereby an important and more commonly expressed chaperone is deleterious for membrane export and is replaced by a functionally equivalent homolog that does not inhibit export while carrying out its functions.
Polymer Chain Length Effects on Fibroblast Attachment on Nylon-3-Modified Surfaces (2012)

Nylon-3 polymers have a polyamide backbone reminiscent of that found in proteins (β- vs α-amino acid residues, respectively), which makes these materials interesting for biological applications. Because of the versatility of the ring-opening polymerization process and the variety of β-lactam starting materials available, the structure of nylon-3 copolymers is highly amenable to alteration. A previous study showed that relatively subtle changes in the structure or ratio of hydrophobic and cationic subunits that comprise these polymers can result in significant changes in the ability of nylon-3-bearing surfaces to support cell adhesion and spreading. In the present study, we have exploited the highly tailorable nature of these polymers to synthesize new versions possessing a wide range of chain lengths, with the intent of optimizing these materials for use as cell-supportive substrates. We find that longer nylon-3 chains lead to better fibroblast attachment on modified surfaces and that at the optimal chain lengths less hydrophobic subunits are superior. The best polymers we identified are comparable to an RGD-containing peptide in supporting fibroblast attachment. The results described here will help to focus future efforts aimed at refining nylon-3 copolymer substrates for specific tissue engineering applications.
Multilayers for 6.8 nm Wavelength (2012)

Lithography based on the wavelength of 6.x nm is considered to be a potential extension of the current 13.5 nm EUV lithography. Light sources might be based on Tb or Gd. The published spectra of plasmas created from these materials show highest intensities at 6.5 and 6.8 nm respectively. Multilayer mirrors (MLMs) based on La and B show the highest optical contrast for the 6.6-7 nm wavelength range and a maximum reflectance at 6.64 nm, where the B absorption is minimal. It is not possible to design high reflective B-based mirrors for 6.5 nm because this would be below the B-K absorption edge. In theory the reflectivity of La/B MLMs at 6.8 nm is only a few percent lower than at the optimal wavelength of 6.64 nm, but measurements of real multilayer mirrors show a significantly larger reduction of reflectivity at 6.8 nm. The origin of this larger drop is the reduced optical contrast of the deposited La/B mirror with respect to theoretical case. In the presentation we will discuss how the multilayer structure influences its reflectivity profile and the ways to optimize La/B mirrors for 6.8 nm.