gebhart/patrepeval huggingface dataset:
Differences in Interferon α and β Signaling (1996)

All Type I interferons (IFNalpha, IFNbeta, IFNomega) bind to the Type I IFN receptor (IFNR) and elicit a common set of signaling events, including activation of the Jak/Stat and IRS pathways. However, IFNbeta selectively induces the association of the alpha subunit of the Type I IFNR with p100, a tyrosyl phosphoprotein, to transduce IFNbeta-specific signals. Using antibodies raised against the different components of the Type I IFNR, we identified p100 as the long form of the beta subunit (betaL subunit) of the Type I IFNR. This was also confirmed in experiments with mouse L-929 cells transfected with truncated forms of betaL. Thus, IFNbeta stimulation of human cells or mouse L-929 transfectants expressing the human alpha and betaL subunits, selectively induces the formation of a signaling complex containing the alpha and betaL subunits of the receptor. The IFNbeta-regulated interaction of the alpha and betaL chains is rapid and transient and follows a similar time course with the tyrosine phosphorylation of these receptor components. These data demonstrate that the signaling specificity for different Type I IFNs is established early in the signaling cascade, at the receptor level, and results from distinct interactions between components of the Type I IFNR.
Turnover of LeACS2, a wound-inducible 1-aminocyclopropane-1-carboxylic acid synthase in tomato, is regulated by phosphorylation/dephosphorylation (2010)

1-aminocyclopropane-1-carboxylic acid (ACC) synthase (ACS) is the rate-limiting enzyme of the ethylene biosynthesis pathway. ACS is regulated both transcriptionally and post-translationally. We previously reported that LeACS2, a wound-inducible ACS in tomato (Solanum lycopersicum), is phosphorylated in vivo, and suggested that phosphorylation regulates protein stability rather than enzymatic activity. In this report, we demonstrate that phosphorylation/dephosphorylation of LeACS2 regulates its turnover upstream of the ubiquitin-26S-proteasome degradation pathway. Pulse-chase experiments coupled with treatment with protein kinase/phosphatase inhibitors demonstrated that LeACS2 is stabilized by phosphorylation and degraded after dephosphorylation. The amount of LeACS2 affected by the protein kinase/phosphatase inhibitors significantly influenced cellular ACS activity, ACC content, and ethylene production levels in tomato fruit tissue, suggesting that post-translational regulation by phosphorylation plays an important role in the control of ethylene production. A calcium-dependent protein kinase (CDPK), LeCDPK2, was isolated as one of the protein kinases that are able to phosphorylate LeACS2 at Ser-460. LeACS2 was immediately phosphorylated after translation by CDPK and mitogen-activated protein kinase at different sites in response to wound signaling and almost all functional LeACS2 molecules are phosphorylated in the cell. Phosphorylation at both sites was required for LeACS2 stability.
Measuring user experience of websites (2010)

To develop simple yet effective methods for eliciting user experience of websites and other interactive technologies, we explored the use of two techniques: an emotional think aloud protocol and an emotion word prompt list (EWPL). A study of four websites with 16 participants found that a retrospective emotional think aloud protocol produced significantly more emotion words than an equivalent concurrent protocol; plus, with on average 40 emotion words per website, it appears an effective technique for eliciting users emotional reactions to websites. Surprisingly, the use of the EWPL did not produce more emotion words per website, but may still help users overcome their difficulties in expressing emotional reactions to websites when unprompted. Further research will explore the use of these methods with other interactive technologies.
Software defined network traffic measurement: Current trends and challenges (2015)

Next generation networks such as Software Defined Networks (SDN) must support the integration of new paradigms of service offerings such as virtual cloud computing, big data applications, data centers services, and rich multimedia content. Operators of next generation SDNs are responsible for configuring policies that employ traffic monitoring tools and measurement mechanisms to detect and react to a wide range of network events and applications. In this article, we take a look at traffic measurement methods in SDNs, cover their strengths and weaknesses, point to open issues, and remaining future challenges.
Neutralization of transforming growth factor-β attenuates hypertension and prevents renal injury in uremic rats (2005)

Neutralization of TGF-beta attenuates hypertension and renal failure progression in uremic animals, in part, by preventing renal injury processes. These effects may be related to the modulation of the ET system, preventing renal ET-1 overproduction and the reduction of ETB receptor expression. Our data also suggest that TGF-beta1 is involved, at least in part, in the pathological effects related to angiotensin II in chronic renal failure.
Antigen-Specific Antibody Glycosylation Is Regulated via Vaccination (2016)

Antibody effector functions, such as antibody-dependent cellular cytotoxicity, complement deposition, and antibody-dependent phagocytosis, play a critical role in immunity against multiple pathogens, particularly in the absence of neutralizing activity. Two modifications to the IgG constant domain (Fc domain) regulate antibody functionality: changes in antibody subclass and changes in a single N-linked glycan located in the CH2 domain of the IgG Fc. Together, these modifications provide a specific set of instructions to the innate immune system to direct the elimination of antibody-bound antigens. While it is clear that subclass selection is actively regulated during the course of natural infection, it is unclear whether antibody glycosylation can be tuned, in a signal-specific or pathogen-specific manner. Here, we show that antibody glycosylation is determined in an antigen- and pathogen-specific manner during HIV infection. Moreover, while dramatic differences exist in bulk IgG glycosylation among individuals in distinct geographical locations, immunization is able to overcome these differences and elicit antigen-specific antibodies with similar antibody glycosylation patterns. Additionally, distinct vaccine regimens induced different antigen-specific IgG glycosylation profiles, suggesting that antibody glycosylation is not only programmable but can be manipulated via the delivery of distinct inflammatory signals during B cell priming. These data strongly suggest that the immune system naturally drives antibody glycosylation in an antigen-specific manner and highlights a promising means by which next-generation therapeutics and vaccines can harness the antiviral activity of the innate immune system via directed alterations in antibody glycosylation in vivo. .
The cell graphs of cancer (2004)

We report a novel, proof-of-concept, computational method that models a type of brain cancer (glioma) only by using the topological properties of its cells in the tissue image. From low-magnification (80x) tissue images of 384 x 384 pixels, we construct the graphs of the cells based on the locations of the cells within the images. We generate such cell graphs of 1000-3000 cells (nodes) with 2000-10,000 links, each of which is calculated as a decaying exponential function of the Euclidean distance between every pair of cells in accordance with the Waxman model. At the cellular level, we compute the graph metrics of the cell graphs, including the degree, clustering coefficient, eccentricity and closeness for each cell. Working with a total of 285 tissue samples surgically removed from 12 different patients, we demonstrate that the self-organizing clusters of cancerous cells exhibit distinctive graph metrics that distinguish them from the healthy cells and the unhealthy inflamed cells at the cellular level with an accuracy of at least 85%. At the tissue level, we accomplish correct tissue classifications of cancerous, healthy and non-neoplastic inflamed tissue samples with an accuracy of 100% by requiring correct classification for the majority of the cells within the tissue sample.
Proliferative Alloresponse of T Cytotoxic Cells Identifies Rejection-Prone Children With Small Bowel Transplantation (2010)

Proliferative alloresponses of Tc cells can identify rejection-prone children receiving SBTx.
Recent advances in vascular inflammation: C-reactive protein and other inflammatory biomarkers (2003)

The pursuit of highly sensitive and specific markers of vascular inflammation has produced a wealth of information that has been instrumental in advancing our comprehension of this complex process. Further studies will establish the role of these new markers in the diagnosis, monitoring, and prognostication of inflammatory vascular disease.
Fiber optic phase stepping system for interferometry (1991)

A closed loop phase control system using an all-fiber optical configuration has been developed for use in phase stepping interferometry. This system drives the relative phase of two interfering beams through a sequence of pi/2 rad increments so that the initial relative phase of these beams can be determined. This phase stepping system uses optical fibers to provide spatially uniform phase steps from a flexible, easily aligned optical configuration. In addition, this system uses phase feed back to eliminate phase modulator errors and to compensate for phase drifts caused by environmental disturbances.
Editor’s Page (1962)

Get PDF Email Share Share with Facebook Tweet This Post on reddit Share with LinkedIn Add to CiteULike Add to Mendeley Add to BibSonomy Get Citation Copy Citation Text Deane B. Judd, "Editor's Page," J. Opt. Soc. Am. 52, 1332-1332 (1962) Export Citation BibTex Endnote (RIS) HTML Plain Text Citation alert Save article
Studies of factor Xa/phospholipid-induced intravascular coagulation in rabbits. Effects of immunodepletion of tissue factor pathway inhibitor. (1993)

In earlier studies from this laboratory evidence was obtained for a physiological function of tissue factor pathway inhibitor (TFPI) as a regulator of hemostasis capable of preventing thrombotic complications that might otherwise result from exposure of blood to trace amounts of tissue factor (TF). However, it was not possible to conclude that the protective effect of TFPI stemmed solely from inhibition of factor VIIa/TF catalytic activity, since TFPI neutralizes stoichiometric amounts of factor Xa in forming an inhibited factor Xa/TFPI/factor VIIa/TF complex. Therefore, we examined the effects of immunodepletion of TFPI on the extent of coagulation initiated in rabbits by exposure to factor Xa and phospholipid in the absence of TF. In one experimental approach, factor Xa was generated endogenously with the factor X-activating fraction of Russell's viper venom (0.33 microgram/kg) in rabbits receiving an infusion of phosphatidylcholine/phosphatidylserine (PCPS) vesicles, 1 mg/kg over 2 hours. In a second approach, rabbits were injected with a complex of factor Xa (0.75 microgram/kg) and PCPS (12.5 micrograms/kg). In contrast with the observed sensitization of TFPI-depleted rabbits to TF-induced coagulation, TFPI-depleted rabbits were not sensitized to coagulation initiated by factor Xa and phospholipid in the absence of TF. These data support the conclusion that the physiological function of TFPI in regulating TF-dependent coagulation stems primarily from its ability to inhibit factor VIIa/TF catalytic activity.
CRFR1 is expressed on pancreatic β cells, promotes β cell proliferation, and potentiates insulin secretion in a glucose-dependent manner (2009)

Corticotropin-releasing factor (CRF), originally characterized as the principal neuroregulator of the hypothalamus-pituitary-adrenal axis, has broad central and peripheral distribution and actions. We demonstrate the presence of CRF receptor type 1 (CRFR1) on primary beta cells and show that activation of pancreatic CRFR1 promotes insulin secretion, thus contributing to the restoration of normoglycemic equilibrium. Stimulation of pancreatic CRFR1 initiates a cAMP response that promotes insulin secretion in vitro and in vivo and leads to the phosphorylation of cAMP response element binding and the induction of the expression of several immediate-early genes. Thus, the insulinotropic actions of pancreatic CRFR1 oppose the activation of CRFR1 on anterior pituitary corticotropes, leading to the release of glucocorticoids that functionally antagonize the actions of insulin. Stimulation of the MIN6 insulinoma line and primary rat islets with CRF also activates the MAPK signaling cascade leading to rapid phosphorylation of Erk1/2 in response to CRFR1-selective ligands, which induce proliferation in primary rat neonatal beta cells. Importantly, CRFR1 stimulates insulin secretion only during conditions of intermediate to high ambient glucose, and the CRFR1-dependent phosphorylation of Erk1/2 is greater with elevated glucose concentrations. This response is reminiscent of the actions of the incretins, which potentiate insulin secretion only during elevated glucose conditions. The presence of CRFR1 on beta cells adds another layer of complexity to the intricate network of paracrine and autocrine factors and their cognate receptors whose coordinated efforts can dictate islet hormone output and regulate beta cell proliferation.
shapeDTW: shape Dynamic Time Warping (2016)

Dynamic Time Warping (DTW) is an algorithm to align temporal sequences with possible local non-linear distortions, and has been widely applied to audio, video and graphics data alignments. DTW is essentially a point-to-point matching method under some boundary and temporal consistency constraints. Although DTW obtains a global optimal solution, it does not necessarily achieve locally sensible matchings. Concretely, two temporal points with entirely dissimilar local structures may be matched by DTW. To address this problem, we propose an improved alignment algorithm, named shape Dynamic Time Warping (shapeDTW), which enhances DTW by taking point-wise local structural information into consideration. shapeDTW is inherently a DTW algorithm, but additionally attempts to pair locally similar structures and to avoid matching points with distinct neighborhood structures. We apply shapeDTW to align audio signal pairs having ground-truth alignments, as well as artificially simulated pairs of aligned sequences, and obtain quantitatively much lower alignment errors than DTW and its two variants. When shapeDTW is used as a distance measure in a nearest neighbor classifier (NN-shapeDTW) to classify time series, it beats DTW on 64 out of 84 UCR time series datasets, with significantly improved classification accuracies. By using a properly designed local structure descriptor, shapeDTW improves accuracies by more than 10% on 18 datasets. To the best of our knowledge, shapeDTW is the first distance measure under the nearest neighbor classifier scheme to significantly outperform DTW, which had been widely recognized as the best distance measure to date. Our code is publicly accessible at: https://github.com/jiapingz/shapeDTW.
Learning Syntax as Notational Expertise when using DrawBridge (2014)

We report an experiment that explores the classroom application of DrawBridge, a system designed to support the acquisition of skill in using text-based programming language syntax. Graphical syntax is increasingly popular in educational programming languages such as Scratch, but anecdotal reports from classroom teachers suggest that students are now finding it difficult to make the transition to conventional text syntax. This research investigates text syntax use as a specific notational competence, and evaluates the use of DrawBridge to scaffold text syntax acquisition.
AI Driven Heterogeneous MEC System for Dynamic Environment -- Challenges and Solutions (2020)

By taking full advantage of Computing, Communication and Caching (3C) resources at the network edge, Mobile Edge Computing (MEC) is envisioned as one of the key enablers for the next generation networks. However, current fixed-location MEC architecture may not be able to make real-time decision in dynamic environment, especially in large-scale scenarios. To address this issue, in this paper, a Heterogeneous MEC (H-MEC) architecture is proposed, which is composed of fixed unit, i.e., Ground Stations (GSs) as well as moving nodes, i.e., Ground Vehicles (GVs) and Unmanned Aerial Vehicles (UAVs), all with 3C resource enabled. The key challenges in H-MEC, i.e., mobile edge node management, real-time decision making, user association and resource allocation along with the possible Artificial Intelligence (AI)-based solutions are discussed. In addition, the AI-based joint Resource schEduling (ARE) framework with two different AI-based mechanisms, i.e., Deep neural network (DNN)-based and deep reinforcement learning (DRL)-based architectures are proposed. DNN-based solution with online incremental learning applies the global optimizer and therefore has better performance than the DRL-based architecture with online policy updating, but requires longer training time. The simulation results are given to verify the efficiency of our proposed ARE framework.
TCP Congestion Avoidance Algorithm Identification (2013)

The Internet has recently been evolving from homogeneous congestion control to heterogeneous congestion control. Several years ago, Internet traffic was mainly controlled by the traditional RENO, whereas it is now controlled by multiple different TCP algorithms, such as RENO, CUBIC, and Compound TCP (CTCP). However, there is very little work on the performance and stability study of the Internet with heterogeneous congestion control. One fundamental reason is the lack of the deployment information of different TCP algorithms. In this paper, we first propose a tool called TCP Congestion Avoidance Algorithm Identification (CAAI) for actively identifying the TCP algorithm of a remote Web server. CAAI can identify all default TCP algorithms (e.g., RENO, CUBIC, and CTCP) and most non-default TCP algorithms of major operating system families. We then present the CAAI measurement result of about 30 000 Web servers. We found that only 3.31 % ~ 14.47 % of the Web servers still use RENO, 46.92% of the Web servers use BIC or CUBIC, and 14.5 % ~ 25.66 % of the Web servers use CTCP. Our measurement results show a strong sign that the majority of TCP flows are not controlled by RENO anymore, and a strong sign that the Internet congestion control has changed from homogeneous to heterogeneous.
An automatic gain controller for MIMO-OFDM WLAN systems (2008)

MIMO-OFDM based wireless LAN standards are currently being defined. These systems employ packed-based communication, which requires fast and accurate automatic gain control. The precise estimation of the expected receive signal power of data symbols, based on preamble symbols is required in order to optimally detect the data signals. In this paper, two different preamble OFDM-symbols are considered and analyzed with regards to their suitability for received signal power estimation in MIMO-OFDM systems. An AGC architecture for an IEEE 802.11a based MIMO system is proposed and FPGA implementation results are reported.
Gray's Elegy: A restored reading (1943)

Gray's Elegy: A restored reading Get access V. R. V. R. Search for other works by this author on: Oxford Academic Google Scholar Notes and Queries, Volume 184, Issue 4, 13 February 1943, Pages 102–103, https://doi.org/10.1093/nq/184.4.102a Published: 13 February 1943
Novel Approaches for Application of Principal Component Analysis on Dynamic PET Images for Improvement of Image Quality and Clinical Diagnosis (2005)

Positron Emission Tomography, PET, can be used for dynamic studies in humans. In such studies a selected part of the body, often the whole brain, is imaged repeatedly after administration of a radiolabelled tracer. Such studies are performed to provide sequences of images reflecting the tracer’s kinetic behaviour, which may be related to physiological, biochemical and functional properties of tissues. This information can be obtained by analyzing the distribution and kinetic behaviour of the administered tracers in different regions, tissues and organs. Each image in the sequence thus contains part of the kinetic information about the administered tracer. Several factors make analysis of PET images difficult, such as a high noise magnitude and correlation between image elements in conjunction with a high level of non-specific binding to the target and a sometimes small difference in target expression between pathological and healthy regions. It is therefore important to understand how these factors affect the derived quantitative measurements when using different methods such as kinetic modelling and multivariate image analysis. In this thesis, a new method to explore the properties of the noise in dynamic PET images was introduced and implemented. The method is based on an analysis of the autocorrelation function of the images. This was followed by proposing and implementing three novel approaches for application of Principal Component Analysis, PCA, on dynamic human PET studies. The common underlying idea of these approaches was that the images need to be normalized before application of PCA to ensure that the PCA is signal driven, not noise driven. Different ways to estimate and correct for the noise variance were investigated. Normalizations were carried out Slice-Wise (SW), for the whole volume at once, and in both image domain and sinogram domain respectively. We also investigated the value of masking out and removing the area outside the brain for the analysis. The results were very encouraging. We could demonstrate that for phantoms as well as for real image data, the applied normalizations allow PCA to reveal the signal much more clearly than what can be seen in the original image data sets. Using our normalizations, PCA can thus be used as a multivariate analysis technique that without any modelling assumptions can separate important kinetic information into different component images. Furthermore, these images contained optimized signal to noise ratio (SNR), low levels of noise and thus showed improved quality and contrast. This should allow more accurate visualization and better precision in the discrimination between pathological and healthy regions. Hopefully this can in turn lead to improved clinical diagnosis.
Auto Safety Regulation: An Analysis of Market Failure (1981)

Although a number of studies have shown seat belts to be highly effective in the prevention of death and injuries, they are used by less than 20% of automobile occupants. This low utilization has led to the present regulation that beginning in 1982 new cars must be equipped with a passive restraint system (i.e., either automatic seat belts or air cushions). This paper examines the potential sources of market failure in this situation (information imperfections and market externalities) and performs a cost-benefit analysis of the mandatory passive restraint regulation. A major finding is very high benefit-cost ratios from the substitution of passive for manual seat belts but much more mixed results in the case of air cushions.
Durability improvement for structural wood composites through chemical treatments: current state of the art (2005)

The use of latest chemical treatments for durability improvement of structural wood composites is discussed. Preservative treatment of wood have a major effect on product properties and often requires changes in the manufacturing process. A number of factors that need to be taken into account when developing such a system include the nature of the preservative, nature of the wood furnish, nature of the adhesive, influence on panel properties from interaction of preservative with adhesive and wood, and the methods of preservative incorporation. Some factors involved with pretreatment of wood furnish, post treatment of finished products and online treatment are discussed.