gebhart/patrepeval huggingface dataset:
Polymer Drag Reduction in Large Pipes and Sewers: Results of Recent Field Trials (1980)

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation R. H. J. Sellin, M. Ollis; Polymer Drag Reduction in Large Pipes and Sewers: Results of Recent Field Trials. J. Rheol. 1 October 1980; 24 (5): 667–684. https://doi.org/10.1122/1.549598 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentThe Society of RheologyJournal of Rheology Search Advanced Search |Citation Search
Interactions of Multiple Heparin Binding Growth Factors with Neuropilin-1 and Potentiation of the Activity of Fibroblast Growth Factor-2 (2005)

The hypothesis that neuropilin-1 (Npn-1) may interact with heparin-binding proteins other than vascular endothelial growth factor has been tested using an optical biosensor-based binding assay. The results show that fibroblast growth factor (FGF) 1, 2, 4, and 7, FGF receptor 1, hepatocyte growth factor/scatter factor (HGF/SF), FGF-binding protein, normal protease sensitive form of prion protein, antithrombin III, and Npn-1 itself are all able to interact with Npn-1 immobilized on the sensor surface. FGF-2, FGF-4, and HGF/SF are also shown to interact with Npn-1 in a solution assay. Moreover, these protein-protein interactions are dependent on the ionic strength of the medium and are inhibited by heparin, and the kinetics of binding of FGF-2, FGF-4 and HGF/SF to Npn-1 are characterized by fast association rate constants (270,000-1,600,000 m(-1) s(-1)). These results suggest that Npn-1 possesses a "heparin" mimetic site that is able to interact at least in part through ionic bonding with the heparin binding site on many of the proteins studied. Npn-1 was also found to potentiate the growth stimulatory activity of FGF-2 on human umbilical vein endothelial cells, indicating that Npn-1 may not just bind but also regulate the activity of heparin-binding proteins.
Efficient scheduling of Internet banner advertisements (2003)

Despite the slowdown in the economy, advertisement revenue remains a significant source of income for many Internet-based organizations. Banner advertisements form a critical component of this income, accounting for 40 to 50 percent of the total revenue. There are considerable gains to be realized through the efficient scheduling of banner advertisements. This problem has been observed to be intractable via traditional optimization techniques, and has received only limited attention in the literature. This paper presents a procedure to generate advertisement schedules under the most commonly used advertisement pricing scheme---the CPM model. The solution approach is based on Lagrangean decomposition and is seen to provide extremely good advertisement schedules in a relatively short period of time, taking only a few hundred seconds of elapsed time on a 450 MHz PC compared to a few thousand seconds of CPU time on a workstation that other approaches need. Additionally, this approach can be incorporated into an actual implementation with minimal alterations and hence is of particular interest.
Enhancements for Authenticated Identity Management in the Session Initiation Protocol (SIP) (2006)

The existing security mechanisms in the Session Initiation Protocol (SIP) are inadequate for cryptographically assuring the identity of the end users that originate SIP requests, especially in an interdomain context.This document defines a mechanism for securely identifying originators of SIP messages.It does so by defining two new SIP header fields, Identity, for conveying a signature used for validating the identity, and Identity-Info, for conveying a reference to the certificate of the signer.
Enhanced Fault Localization Using Probabilistic Fusion With Gas Path Analysis Algorithms (2009)

A method for gas turbine fault identification from gas path data, in situations with a limited number of measurements, is presented. The method consists of a two stage process: (a) localization of the component or group of components with a fault and (b) fault identification by determining the precise location and magnitude of component performance deviations. The paper focuses on methods that allow improved localization of the faulty components. Gas path analysis (GPA) algorithms are applied to diagnostic sets comprising different combinations of engine components. The results are used to derive fault probabilities, which are then fused to derive a conclusion as to the location of a fault. Once the set of possible faulty components is determined, a well defined diagnostic problem is formulated and the faulty parameters are determined by means of a suitable algorithm. It is demonstrated that the method has an improved effectiveness when compared with previous GPA based methods.
A Continuous Learning Framework for Activity Recognition Using Deep Hybrid Feature Models (2015)

Most of the research on human activity recognition has focused on learning a static model, considering that all the training instances are labeled and present in advance, while in streaming videos new instances continuously arrive and are not labeled. Moreover, these methods generally use application- specific hand-engineered and static feature models, which are not suitable for continuous learning. Some recent approaches on activity recognition use deep-learning-based hierarchical feature models, but the large size of these networks constrain them from being used in continuous learning scenarios. In this work, we propose a continuous activity learning framework for streaming videos by intricately tying together deep hybrid feature models and active learning. This allows us to automatically select the most suitable features and take the advantage of incoming unlabeled instances to improve the existing model incrementally. Given the segmented activities from streaming videos, we learn features in an unsupervised manner using deep hybrid networks, which have the ability to take the advantage of both the local hand-engineered features and the deep model in an efficient way. Additionally, we use active learning to train the activity classifier using a reduced amount of manually labeled instances. Retraining the models with a huge amount of accumulated examples is computationally expensive and not suitable for continuous learning. Hence, we propose a method to select the best subset of these examples to update the models incrementally. We conduct rigorous experiments on four challenging human activity datasets to demonstrate the effectiveness of our framework.
A multidot immunobinding assay for autoimmune testing: evaluation for the diagnosis and management of connective tissue diseases. (1985)

Multidot immunobinding assays were evaluated for applicability to connective tissue diseases. Four groups of human sera [(a) healthy, (b) miscellaneous diseases, (c) rheumatoid arthritis and (d) other connective tissue diseases] were used to obtain profiles comprising antibodies against DNA, various subcellular components and rheumatoid factor (RF). Qualitative correlation with standard tests for antinuclear factor and RF was shown. Statistically significant ranges of titer for groups (c) and (d) were obtained, and monitoring individual patients during the progression of disease was demonstrated.
Evaluating Classical Airplane Boarding Methods Considering COVID-19 Flying Restrictions (2020)

The novel coronavirus (SARS-CoV-2) has imposed the need for a series of social distancing restrictions worldwide to mitigate the scourge of the COVID-19 pandemic. This applies to many domains, including airplane boarding and seat assignments. As airlines are considering their passengers’ safety during the pandemic, boarding methods should be evaluated both in terms of social distancing norms and the resulting efficiency for the airlines. The present paper analyzes the impact of a series of restrictions that have been imposed or mooted worldwide on the boarding methods used by the airlines, featuring the use of jet-bridges and one-door boarding. To compare the efficacy of classical airplane boarding methods with respect to new social distancing norms, five metrics were used to evaluate their performance. One metric is the time to complete the boarding of the airplane. The other four metrics concern passenger health and reflect the potential exposure to the virus from other passengers through the air and surfaces (e.g., headrests and luggage) touched by passengers. We use the simulation platform in NetLogo to test six common boarding methods under various conditions. The back-to-front by row boarding method results in the longest time to complete boarding but has the advantage of providing the lowest health risk for two metrics. Those two metrics are based on passengers potentially infecting those passengers previously seated in the rows they traverse. Interestingly, those two risks are reduced for most boarding methods when the social distance between adjacent passengers advancing down the aisle is increased, thus indicating an unanticipated benefit stemming from this form of social distancing. The modified reverse pyramid by half zone method provides the shortest time to the completing boarding of the airplane and—along with the WilMA boarding method—provides the lowest health risk stemming from potential infection resulting from seat interferences. Airlines have the difficult task of making tradeoffs between economic productivity and the resulting impact on various health risks.
Passwords: Do User Preferences and Website Protocols Differ From Theory? (2010)

Despite the availability of superior authentication tools, password security continues to be an important access control in modern, computer-based systems. Are strong passwords used in these systems? Under what conditions are users willing to adopt stronger passwords? To answer these questions, the authors examined the websites of 154 organizations and additionally, analyzed 240 responses from a separate survey of password users. In terms of password length and duration, the answer to our first question was “No, strong passwords are not used.” The answer to our second question regarding willingness to adopt stronger passwords appears to depend upon how often users must change them.
Effects of theophylline on human eosinophil functions: comparative study with neutrophil functions (2000)

The understanding of theophylline as a bronchodilator has been reconsidered in recent years. We undertook to determine its immunomodulatory actions in granulocytes and elucidate their mechanism. Preincubation of neutrophils with theophylline (10(-5) to 5 x 10(-3) M) had a biphasic effect on O2(-) production stimulated with N-formyl-methionyl-leucyl-phenylalanine or C5a. Theophylline potentiates O2(-) production via adenosine A(2A) receptor antagonism induced by receptor-linked agonists from neutrophils, but not from eosinophils. The addition of theophylline caused a significant decline in neutrophil chemotaxis at lower concentrations than those for eosinophil motility. Theophylline reduces neutrophil chemotaxis via adenosine A1 receptor antagonism. At high concentrations, with an intracellular cAMP accumulation as a result of phosphodiesterase (PDE) inhibition, theophylline also exerts an inhibitory effect on the O2(-) production and chemotaxis of both types of cells. The difference in theophylline's effect on neutrophils and eosinophils appears to depend on the existence of specific adenosine receptors. Theophylline thus modulates granulocyte functions in association with specific adenosine receptor antagonism and cAMP-PDE inhibition.
Classification of hyperspectral data using support vector machine (2002)

Classification is one of the most important tasks for remote sensing image processing. Most of the existing supervised classification methods are based on traditional statistics, which can provide ideal results when sample size is tending to infinity. However, only finite samples can be acquired in practice. In addition, many methods are constrained by high data dimension of hyperspectral images. In this paper, a novel learning method, the support vector machine (SVM), is applied to hyperspectral data classification. This method does not suffer the limitations of data dimensionality and limited samples. The foundations of the SVM have been developed by Vapnik (1995) and are gaining popularity in field of machine learning due to many attractive features and promising empirical performance. In our experiment, the support vectors, which are critical for classification, are obtained by learning from the training samples. Choosing appropriate kernel function and suitable parameters, better classification results are obtained.
A Functional Nuclear Localization Sequence in the C-terminal Domain of SHP-1 (2001)

The Src homology 2 domain-containing protein tyrosine phosphatases SHP-1 and SHP-2 play an important role in many intracellular signaling pathways. Both SHP-1 and SHP-2 have been shown to interact with a diverse range of cytosolic and membrane-bound signaling proteins. Generally, SHP-1 and SHP-2 perform opposing roles in signaling processes; SHP-1 acts as a negative regulator of transduction in hemopoietic cells, whereas SHP-2 acts as a positive regulator. Intriguingly, SHP-1 has been proposed to play a positive regulating role in nonhemopoietic cells, although the mechanisms for this are not understood. Here we show that green fluorescent protein-tagged SHP-1 is unexpectedly localized within the nucleus of transfected HEK293 cells. In contrast, the highly related SHP-2 protein is more abundant within the cytoplasm of transfected cells. In accordance with this, endogenous SHP-1 is localized within the nucleus of several other nonhemopoietic cell types, whereas SHP-2 is distributed throughout the cytoplasm. In contrast, SHP-1 is confined to the cytoplasm of hemopoietic cells, with very little nuclear SHP-1 evident. Using chimeric SHP proteins and mutagenesis studies, the nuclear localization signal of SHP-1 was identified within the C-terminal domain of SHP-1 and found to consist of a short cluster of basic amino acids (KRK). Although the KRK motif resembles half of a bipartite nuclear localization signal, it appears to function independently and is absolutely required for nuclear import. Our findings show that SHP-1 and SHP-2 are distinctly localized within nonhemopoietic cells, with the localization of SHP-1 differing dramatically between nonhemopoietic and hemopoietic cell lineages. This implies that SHP-1 nuclear import is a tightly regulated process and indicates that SHP-1 may possess novel nuclear targets.
Comparison of different characterization methods for nanoparticle dispersions before and after aerosolization (2014)

A well-known and accepted aerosol measurement technique, the scanning mobility particle sizer (SMPS), is applied to characterize colloidally dispersed nanoparticles. To achieve a transfer from dispersed particles to aerosolized particles, a newly developed nebulizer (N) is used that, unlike commonly used atomizers, produces significantly smaller droplets and therefore reduces the problem of the formation of residual particles. The capabilities of this new instrument combination (N + SMPS) for the analysis of dispersions were investigated, using three different dispersions, <i>i.e.</i> gold-PVP nanoparticles (∼20 nm), silver-PVP nanoparticles (∼70 nm) and their 1 : 1 (<i>m</i> : <i>m</i>) mixture. The results are compared to scanning electron microscopy (SEM) measurements and two frequently applied techniques for characterizing colloidal systems: Dynamic light scattering (DLS) and analytical disc centrifugation (ADC). The differences, advantages and disadvantages of each method are discussed, especially with respect to the size resolution of the techniques and their ability to distinguish the particle sizes of the mixed dispersion. While DLS is, as expected, unable to resolve the binary dispersion, SEM, ADC and SMPS are able to give quantitative information on the two particle sizes. However, while the high-resolving ADC is limited due to the dependency on a predefined density of the investigated system, the transfer of dispersed particles into an aerosol and subsequent analysis with SMPS are an adequate way to characterize binary systems, independent of the density of concerned particles, but matching the high resolution of the ADC. We show that it is possible to use the well-established aerosol measurement technique (N + SMPS) in colloid science with all its advantages concerning size resolution and accuracy.
Design and analysis of a gracefully degrading interleaved memory system (1990)

The organization of interleaved memories in such a way that faults in the memory system degrade the performance in a graceful manner is studied. Attention is restricted to an interleaved memory system that starts out with 2/sup q/ memory banks and uses a low-order interleaving scheme. The motivation and design objectives of the memory system are described. A new reconfiguration scheme and the design of the hardware needed to implement it are presented. The reconfiguration scheme is evaluated using trace-driven simulation for a number of benchmarks. The ideas presented can easily be extended to other interleaved memory schemes.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Role of pICLn in Methylation of Sm Proteins by PRMT5 (2009)

pICln is an essential, highly conserved 26-kDa protein whose functions include binding to Sm proteins in the cytoplasm of human cells and mediating the ordered and regulated assembly of the cell's RNA-splicing machinery by the survival motor neurons complex. pICln also interacts with PRMT5, the enzyme responsible for generating symmetric dimethylarginine modifications on the carboxyl-terminal regions of three of the canonical Sm proteins. To better understand the role of pICln in these cellular processes, we have investigated the properties of pICln and pICln.Sm complexes and the effects that pICln has on the methyltransferase activity of PRMT5. We find that pICln is a monomer in solution, binds with high affinity (K(d) approximately 160 nm) to SmD3-SmB, and forms 1:1 complexes with Sm proteins and Sm protein subcomplexes. The data support an end-capping model of pICln binding that supports current views of how pICln prevents Sm oligomerization on illicit RNA substrates. We have found that by co-expression with pICln, recombinant PRMT5 can be produced in a soluble, active form. PRMT5 alone has promiscuous activity toward a variety of known substrates. In the presence of pICln, however, PRMT5 methylation of Sm proteins is stimulated, but methylation of histones is inhibited. We have also found that mutations in pICln that do not affect Sm protein binding can still have a profound effect on the methyltransferase activity of the PRMT5 complex. Together, the data provide insights into pICln function and represent an important starting point for biochemical analyses of PRMT5.
Optimizing Gate Assignments at Airport Terminals (1985)

The airport flight-to-gate assignment problem is solved using two methods: (1) a linear programming relaxation of an integer program formulation and (2) a heuristic. The objective is to minimize passenger walking distances within the airport terminal area through a judicious gate assignment policy. An actual flight schedule for an average day at Toronto International Airport is used to compare existing walking distances, obtained from the original assignment, with results from the two methods. The results indicated that the original assignment had a 32% higher average per passenger walking distance than the minimum possible distance given by the LP solution. The heuristic’s performance was near optimal; it gave an average walking distance which was only 3.9% greater than the minimum. Computation times for the heuristic are 3.4 CPU seconds per run, while the linear program consumes 386 seconds per run on an IBM 370/168. In addition, if the heuristic is solved first and its solution is used as an initial feasible basis for the LP relaxation of the IP, the total CPU used to obtain optimality is reduced to 42 seconds.
Optimal nutrition: vitamin A and the carotenoids (1999)

There are two major dietary sources of vitamin A: easily absorbed retinyl palmitate in foods of animal origin, and poorly bioavailable carotenoids from plant foods. Plasma retinol is tightly controlled, probably by regulation of retinol-binding protein (RBP) formation in the liver, and only hormonal factors (e.g. oral contraceptives) and infection will alter the homeostasis. Delivery of retinol to the tissues is facilitated by the RBP-retinol complex; however, there is evidence that this mechanism can be bypassed when very high doses of vitamin A are given. Some retinyl ester may be released to tissues from chylomicrons when the latter bind to tissue lipoprotein receptors during their passage from the gut to the liver following a meal. High-dose vitamin A therapy is a means of rapidly improving vitamin A status in persons with sub-optimal vitamin A nutrition but there are dangers of toxic symptoms (e.g. teratogenicity) from excess vitamin A usage. Evidence is presented to suggest that the plasma retinol: RBP may be a guide to optimal vitamin A status, since values less than one frequently occur in less-developed countries and during infection. In contrast to plasma retinol, plasma carotenoids reflect the dietary intake of plant foods. However, absorption is limited by poor bioavailability and a saturable uptake mechanism in competition with other phytochemicals. Recent work on bioavailability suggests that the calculation of plant food vitamin A activity should be re-examined. Illness has little influence on plasma levels except by suppressing appetite. Carotenoids are generally regarded as non-toxic yet intervention studies with beta-carotene in smokers have been associated with increased lung cancer and heart disease. Some carotenoids are important as vitamin A precursors, but the physiological importance of their antioxidant properties is not known and consequently the amount needed for optimal nutrition is uncertain.
Wiener filter-based channel predictor performance improvement using polinomial extrapolation (2013)

The widely used channel predictor today is Wiener filter-based channel predictor, where the channel is assumed to be random and has time invariant correlation value. Based on the quasi static principle, in the interval of short observation time the channel tends to be deterministic and has time variant correlation value. This makes Wiener filter-based channel predictor can not yield minimum mean squared error. To solve this problem the filter should accommodate the deterministic property and the correlation fluctuation of the channel. This can be achieved by polinomially extrapolating the channel correlation value. This work conducted performance evaluation of conventional Wiener filter and Wiener filter with polinomial extrapolation modification. The performance was evaluated by varying the symbol rates, Doppler frequency and the filter orders. However, the performance of polinomial extrapolation method for the noise was also observed.