gebhart/patrepeval huggingface dataset:
INHIBITORY EFFECT OF BASSIANOLIDE, A CYCLODEPSIPEPTIDE, ON DRUG-INDUCED CONTRACTIONS OF ISOLATED SMOOTH MUSCLE PREPARATIONS (1982)

Bassianolide (BASS) is a cyclodepsipeptide isolated from cultured mycelia of Beauveria bassiana and is pathogenic to insects. In a longitudinal muscle preparation from guinea pig ileum. 10-6 M BASS almost irreversibly inhibited an isotonic contraction induced by acetylcholine (ACH) and made the dose-response curve shift in parallel to the right (pA2: 7.6). It also inhibited the contractions induced by carbachol, pilocarpine, histamine. 5-hydroxytriptamine (5-HT) and prostaglandin E2, but did not inhibit the contraction induced by barium or a high concentration (40-60 mM) of potassium (high K). When applied to the guinea pig vas deferens, 10-5–10-7 M BASS inhibited an isometric contraction induced by norepinephrine (NE) (3×10-6–10-5M), phenylephrine (3*10-6-10-6M) or ACH (10-6-10-5 M). When the contractions of the three agonists exceeded the concentrations mentioned above, BASS failed to exert an inhibitory effect upon any of these agonists. It also inhibited the contraction caused by carbachol and histamine, but did not inhibit that induced by barium or high K. BASS itself failed to cause the contraction or relaxation of both muscle preparations. From these results, it is suggested that BASS inhibits the contraction induced by an agonist which acts upon selective sites of smooth muscle cells, but which does not inhibit a contraction induced by an agonist that has an effect on non-selective sites of cells.
Thermochromic Polymers—Function by Design (2014)

S.3037-3068
Prostaglandin E synthase: another enzyme in the cyclooxygenase pathway driving epithelial cancer? (2001)

COX-1[2][1] and -2 metabolize AA and other 20-carbon polyunsaturated fatty acids into PGs, which have a wide array of biological roles that are tissue-specific [(1)][2] . A variety of exogenous stimuli increase the expression of COX-2 but not COX-1 as a consequence of their distinct transcriptional
Conducting Shape Memory Polyurethane‐Polypyrrole Composites for an Electroactive Actuator (2005)

Abstract Summary: Electroactive shape memory composites were prepared using polyurethane block copolymer and conducting polypyrrole by chemical oxidative polymerization. The electrical conductivity, thermal and mechanical properties, and morphology of the composites were investigated, and a voltage‐triggered shape memory effect was demonstrated. The polyurethane synthesized had a transition temperature near 46 °C. The presence of polypyrrole increased the conductivity of the composites, and a high conductivity of the order of 10 −2 S/cm was obtained at 6–20 wt.‐% polypyrrole. Such a conductivity of composites was enough to show electroactive shape recovery by heating above the transition temperature of 40–45 °C due to melting of the polycaprolactone soft segment domain. Thus a good shape recovery of 85–90% could be obtained in the shape recovery test with bending mode when an electric field of 40 V was applied. Electroactive shape recovery behavior of PU/PPy composite. image Electroactive shape recovery behavior of PU/PPy composite.
<i>Chlamydia pneumoniae</i>Serology: Interlaboratory Variation in Microimmunofluorescence Assay Results (2000)

The lack of standardization in chlamydia serology has made interpretation of published data difficult. This study was initiated to determine the extent of interlaboratory variation of microimmunofluorescence (MIF) test results for the serodiagnosis of Chlamydia pneumoniae infections. Identical panels of 22 sera were sent to 14 laboratories in eight countries for the determination of IgG and IgM antibodies by MIF. Although there was extensive variation in the numeric titer values, the overall percentage agreement with the reference standard titers from the University of Washington was 80%. For results by serodiagnostic category, the best agreement was for four-fold rise in IgG titers, while the lowest agreement was for negative or low IgG titers. Agreement for IgM titers was 50%-95%. Four laboratories failed to discern false-positive IgM titers possibly because of the presence of rheumatoid factor. Further studies are underway to determine the source of interlaboratory variation for the MIF test.
Customer‐based corporate valuation (2005)

Purpose Synthesis of the customer lifetime value and the shareholder value (SHV) approach in order to develop an integrated, marketing‐based method for corporate valuation. Design/methodology/approach Discusses the limitations and assumptions of existing methods to estimate customer value components and examines the limitations of the SHV concept. By linking the customer equity (CE) and the SHV approach, a formal model to calculate corporate value is developed. The discounted cash flow method is used for modelling the profit streams. Findings Provides formulas for the estimation of both the individual lifetime value of a customer and CE. Provides a comprehensive model to estimate corporate value based on customer‐related cash flows and traditional financial metrics. Introduces typical cases, in which the use of a customer‐based valuation seems beneficial. Illustrates how our approach can be applied by using a simple case study on M&A in the telecommunication industry. Gives suggestions on how to obtain the necessary data, partially even from publicly available sources. Research limitations/implications Advancement of the quantitative techniques for modelling the customer value components would allow for relaxing some restrictive assumptions. The explicit modelling of the future growth of the customer base (the acquisition rate) would increase the applicability of the model. Additionally, taking into account heterogeneity within the customer cohorts is a task for future research. Finally, our model needs to be applied more extensively using real data for the input variables. Practical implications A CE‐based valuation approach can guide marketing investments and helps to avoid misallocation of resources. Based on an example in the field of M&A, we demonstrate the usefulness of the approach for obtaining a realistic indicator of firm value. It helps to assess whether an acquisition is economically sensible. We provide evidence for the superiority of a customer‐based approach over traditional financial methods. Originality/value While the traditional SHV method considers cash flows at a highly aggregated level, our approach employs disaggregated cash flows on the level of individual customers. Thereby we do incorporate the lifetime values of future customers by considering different cohorts. We do capture customer defection by incorporating retention rates. Our model enables a more detailed and valid estimation of corporate value by accounting for the single customer activities that drive marketing actions. This enables a better forecasting of the free cash flow. Incorporating customer‐related drivers into financial valuation models makes easier to assess the return on marketing investments.
Nanoparticles as a Potential Cause of Pleural and Interstitial Lung Disease (2010)

Nanotechnology holds the promise of revolutionizing our society, bringing numerous beneficial innovations to improve structural materials, electronics, energy, medical imaging, and drug delivery, among other applications. However, nanomaterials present potential safety concerns, and there is accumulating evidence to suggest that nanoparticles may exert adverse effects on the lung and other organ systems. This article will overview the potential risks of engineered nanoparticles and nanotechnology on the respiratory system and highlight recent findings related to pulmonary and systemic effects of inhaled nanoparticles. Special emphasis will be given to carbon nanotubes and the possibility that these nanoparticles could represent an emerging risk for environmental and occupational lung disease, especially in individuals with pre-existing respiratory diseases such as asthma.
Combining Organometallic Reagents, the Sulfur Dioxide Surrogate DABSO, and Amines: A One‐Pot Preparation of Sulfonamides, Amenable to Array Synthesis (2014)

We describe a method for the synthesis of sulfonamides through the combination of an organometallic reagent, a sulfur dioxide equivalent, and an aqueous solution of an amine under oxidative conditions (bleach). This simple reaction protocol avoids the need to employ sulfonyl chloride substrates, thus removing the limitation imposed by the commercial availability of these reagents. The resultant method allows access to new chemical space, and is also tolerant of the polar functional groups needed to impart favorable physiochemical properties required for medicinal chemistry and agrochemistry. The developed chemistry is employed in the synthesis of a targeted 70 compound array, prepared using automated methods. The array achieved a 93% success rate for compounds prepared. Calculated molecular weights, lipophilicities, and polar surface areas are presented, demonstrating the utility of the method for delivering sulfonamides with drug-like properties.
Modeling And Implementation Of A System For Sucker Rod Downhole Dynamometer Card Pattern Recognition (2003)

Abstract This paper presents a new method for the downhole dynamometer card pattern creation. This method use artificial intelligence concepts and real card data picked up from the oil fields acquired data. The main idea is to allow field team to generate patterns based on their own experience supported by an intelligent algorithm designed to perform graphical analysis of the card shape. The main idea is to allow pattern recognition and its classification toward the solution of rod pumping problems in oil wells. Successful results were reached when the proposed method was applied in PETROBRAS/UN-BA real databases. Tests performed with real data allowed the development of a new set of patterns used to analyze well performance in Buracica and Balsamo oil fields. These tests showed good results when compared with the ones obtained from empirical patterns only. In addition, this approach allowed to immediately increasing the pattern number from two to a set of eight, improving the sucker-rod pumped wells analysis and management.
Effect of c-kit ligand on in vitro human megakaryocytopoiesis (1991)

An evaluation of the effects of a recombinant, soluble form of the c-kit ligand alone and in combination with either granulocyte-macrophage colony-stimulating factor (GM-CSF) or interleukin-3 (IL-3) on the regulation of human megakaryocytopoiesis was performed using a serum-depleted clonal assay system and a long-term bone marrow culture system. The effects of the c-kit ligand on the primitive megakaryocyte (MK) progenitor cell, the burst-forming unit-megakaryocyte (BFU-MK), and the more differentiated colony-forming unit-megakaryocyte (CFU-MK) were determined. The c-kit ligand alone had no megakaryocyte colony-stimulating activity (MK-CSA) but was capable of augmenting the MK-CSA of both GM-CSF and IL-3. The range of synergistic interactions of c-kit ligand varied with the class of MK progenitor cell assayed. In the case of the BFU-MK, the c-kit ligand synergistically augmented the numbers of colonies formed in the presence of IL-3, but not GM-CSF, but increased the size of BFU-MK-derived colonies cloned in the presence of both of these cytokines. However, at the level of the CFU-MK, c-kit ligand synergized with both GM-CSF and IL-3 by increasing both colony numbers and size. Although the c-kit ligand alone exhibited limited potential in sustaining long-term megakaryocytopoiesis in vitro, it synergistically augmented the ability of IL-3, but not GM-CSF, to promote long-term megakaryocytopoiesis. These data indicate that multiple cytokines are necessary to optimally stimulate the proliferation of both classes of MK progenitor cells and that the c-kit ligand plays a significant role in this process by amplifying the MK-CSA of both GM-CSF and IL-3.
Building Interpretable Models: From Bayesian Networks to Neural Networks (2016)

This dissertation explores the design of interpretable models based on Bayesian networks, sum-product networks and neural networks. \n\nAs briefly discussed in Chapter 1, it is becoming increasingly important for machine learning methods to make predictions that are interpretable as well as accurate. In many practical applications, it is of interest which features and feature interactions are relevant to the prediction task. In Chapter 2, we develop a novel method, Selective Bayesian Forest Classifier (SBFC), that strikes a balance between predictive power and interpretability by simultaneously performing classification, feature selection, feature interaction detection and visualization. It builds parsimonious yet flexible models using tree-structured Bayesian networks, and samples an ensemble of such models using Markov chain Monte Carlo. We build in feature selection by dividing the trees into two groups according to their relevance to the outcome of interest. In Chapter 3, we show that SBFC performs competitively on classification and feature selection benchmarks in low and high dimensions, and includes a visualization tool that provides insight into relevant features and interactions. This is joint work with Prof. Jun Liu. \n\nSum-Product Networks (SPNs) are a class of expressive and interpretable hierarchical graphical models. In Chapter 4, we improve on LearnSPN, a standard structure learning algorithm for SPNs that uses hierarchical co-clustering to simultaneously identifying similar entities and similar features. The original LearnSPN algorithm assumes that all the variables are discrete and there is no missing data. We introduce a practical, simplified version of LearnSPN, MiniSPN, that runs faster and can handle missing data and heterogeneous features common in real applications. We demonstrate the performance of MiniSPN on standard benchmark datasets and on two datasets from Google's Knowledge Graph exhibiting high missingness rates and a mix of discrete and continuous features. This is joint work with Moshe Looks (Google). \n\nIn Chapter 5, we turn our efforts from building interpretable models from the ground up to making neural networks more interpretable. As deep neural networks continue to revolutionize various application domains, there is increasing interest in making these powerful models more understandable, and narrowing down the causes of good and bad predictions. We focus on recurrent neural networks (RNNs), state of the art models in speech recognition and translation. Our approach to increasing interpretability is to combine an RNN with a hidden Markov model (HMM), a simpler and more transparent model. We explore different combinations of RNNs and HMMs: an HMM trained on LSTM states, and a hybrid model where an HMM is trained first, then a small LSTM is given HMM state distributions and trained to fill in gaps in the HMM's performance. We find that the LSTM and HMM learn complementary information about the features in the text, and we also apply the hybrid models to medical time series. This is joint work with Prof. Finale Doshi-Velez.
Multitarget motion analysis in a DSN (1991)

The data association problem in multiple target bearings-only motion analysis is considered. The measurements are target bearings obtained from passive sonars in a distributed sensor network. These measurements, after being transmitted to a processing center, are used to estimate the initial states of targets. The overall problem is formulated using the maximum likelihood principle. A two-step iterative method is proposed to maximize the joint likelihood, a nonlinear least-squares method is used to fit the trajectory estimates to the measurements for given data associations, and the linear assignment algorithm is used to solve the data associations for given trajectory estimates. A stochastic relaxation method based on simulated annealing is proposed to augment the second step so that the global maximum of the likelihood function can be located. Monte Carlo simulations are included to evaluate the joint estimator. The Cramer-Rao lower bound of the initial state estimate is derived in the presence of data association uncertainties.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Isolation of human mesenchymal stem cells from third‐trimester amniotic fluid (2008)

Multipotent MSCs can be obtained from AF in the third trimester, which may be less dangerous than the second trimester to women and their fetuses.
Stochastic change detection in uncertain nonlinear systems using reduced-order models: system identification (2008)

The reliable detection of relatively small changes in the characteristics of monitored systems, which simultaneously involve nonlinear phenomena as well as uncertain parameters, is a challenging problem whose resolution is crucial to the development of practical structural health monitoring methodologies slated for use with complex physical systems. This paper reports the results of a comprehensive experimental study involving an adaptive nonlinear component (an actively controlled magnetorheological damper) that was used to investigate the representation and propagation of uncertainties in a probabilistic format that provides a convenient means for reliable detection of small changes in uncertain nonlinear systems. In experimental studies of the MR damper, the uncertainty of the system characteristics was precisely controlled with known input-current statistics. A total of 4000 tests were performed, and the MR damper was identified using the restoring force method with both orthogonal and non-orthogonal basis functions. The identification results show that the identified coefficients involving orthogonal basis functions have several desirable features that are ideal for condition assessment purposes when dealing with complex nonlinear systems whose underlying physics is not amenable to easy modeling: (1) no a priori knowledge of the systems characteristics is required; (2) the orthogonal coefficients are statistically unbiased with respect to model complexity; and (3) the distributions of the orthogonal coefficients can be reliably used to detect changes in uncertain nonlinear systems, even if a reduced-order model is used in the identification process.
Development of the Novel Electron Bombardment Anneal System (EBAS) for SiC Post Ion Implantation Anneal (2005)

This DOI is not currently attached to any metadata records. DOIs can’t actually ever be deleted (they’re persistent), but sometimes our members create DOIs in error. We do have a process to approximate deletion which we follow only in rare cases where the DOI has been genuinely created in error, and most crucially, if the DOI has never been published anywhere online or in print and never otherwise distributed to or communicated with anyone (authors, readers, reviewers, etc.
Dynamic Consideration of DC Microgrids With Constant Power Loads and Active Damping System—A Design Method for Fault-Tolerant Stabilizing System (2014)

It is known that constant power loads (CPLs) can yield instability in dc-power systems under certain operating conditions. This instability phenomenon is due to the interaction between the dc-grid and the negative input impedance characteristic of the CPLs. Dynamic behavior and stability analysis of a dc-microgrid with CPLs is presented in this paper. Then, a method to design a fault-tolerant stabilizing system for a dc-microgrid with CPLs is presented. It consists in implementing a local stabilizing agent on each CPL. Then, a method to design the stabilizing system is proposed. The method is based on the definition and resolution of a constrained optimization problem. It permits to consider several fault scenarios, such as the electrical reconfiguration of the dc-microgrid, or the failure of an agent. To illustrate the method's effectiveness, it has been implemented and experimentally tested on a test bed.
A Simple Isolation Method for the Major Catechins in Green Tea Using High-Speed Countercurrent Chromatography (2001)

An efficient protocol for the preparative purification of the major tea catechins (-)-epicatechin gallate (3) and epigallocatechin gallate (5) has been developed, employing liquid-liquid partitioning, high-speed countercurrent chromatography, and gel chromatography for final purification. The method is suitable for scale-up to significantly larger quantities.
The role of protein kinase-C theta in control of epithelial to mesenchymal transition and cancer stem cell formation (2014)

The protein kinase C (PKC) activator phorbol 12-myristate 13-acetate (PMA) induces transition of the epithelial MCF-7 cell line to a mesenchymal phenotype. A subset of the resulting mesenchymal cells has surface markers characteristics of a cancer stem cell (CSC) population. We profiled the transcriptome changes associated with the epithelial to mesenchymal transition and those that occurred in the CSC subset. Using a siRNA knockdown strategy, we examined the extent to which these changes were dependent on the PKC family member, PKC-θ. The importance of the cytoplasmic signaling role of this kinase is well established and in this study, we have shown by PKC-θ ChIP-sequencing analysis that this kinase has a dual role with the ability to also associate with chromatin on a subset of PKC-θ dependent genes. In the associated manuscript (Zafar et al., 2014 [5]) we presented evidence for the first time showing that this nuclear role of PKC-θ is also important for gene induction and mesenchymal/CSC phenotype. Here we describe the analysis associated with the transcriptome and ChIP-seq data presented in Zafar et al. (2014) [5] and uploaded to NCBI Gene Expression Omnibus (GSE53335).
National High Blood Pressure Education Program Working Group Report on Hypertension in the Elderly. National High Blood Pressure Education Program Working Group. (1994)

Raised blood pressures in the elderly and the increased prevalence of hypertension in this population are not benign occurrences and should not be viewed as a normal or inevitable consequence of aging. In fact, the relation of systolic and diastolic blood pressures to cardiovascular events is generally more pronounced in people aged 65 years and older when compared with those aged 35 to 64. The relative risk of cardiovascular disease is greater among the elderly at every level of blood pressure. Furthermore, the absolute likelihood that an older individual will have a cardiovascular event is substantially greater than for someone younger, reflecting the increased prevalence of other cardiovascular disease risk factors in this age group. Thus, equivalent blood pressure reduction is likely to produce a greater benefit in the elderly than in younger patients at every level of blood pressure. This report, an update of the 1985 Working Group Report on Hypertension in the Elderly, has two aims: to guide clinicians in their care of elderly patients with hypertension and to assist health care professionals participating in high blood pressure control programs that serve the elderly. The role of lifestyle modifications--weight loss, dietary sodium restriction, alcohol reduction, and exercise--as definitive or adjunctive therapy to drug treatment is discussed. In addition, the report reviews the relative advantages and disadvantages of the specific classes of antihypertensive medications.
Simple mixed Fe–Zn catalysts for the Suzuki couplings of tetraarylborates with benzyl halides and 2-halopyridines (2009)

Employing co-catalytic zinc reagents facilitates the iron-catalysed Suzuki cross-coupling of tetraarylborates with both benzyl and 2-heteroaryl halides.