gebhart/patrepeval huggingface dataset:
Cryptococcus flips its lid - membrane phospholipid asymmetry modulates antifungal drug resistance and virulence (2016)

Human fungal infections are increasing in prevalence and acquisition of antifungal drug resistance, while our antifungal drug armamentarium remains very limited, constituting a significant public health problem. Despite the fact that prominent antifungal drugs target the fungal cell membrane, very little is known about how fungal membrane biology regulates drug-target interactions. Asymmetrical phospholipid distribution is an essential property of biological membranes, which is maintained by a group of transporters that dynamically translocate specific phospholipid groups across the membrane bilayer. Lipid flippase is the enzyme responsible for translocation of certain phospholipids, including phosphatidylserine (PS), across the plasma membrane from the exocytoplasmic to the cytoplasmic leaflet. Loss of lipid flippase leads to abnormal phospholipid distribution and impaired intracellular vesicular trafficking. The recent research article by Huang <i>et al.</i> reported that in pathogenic fungus <i>Cryptococcus neoformans</i> loss of lipid flippase activity sensitized cryptococcal cells to multiple classes of antifungal drugs, including the cell wall active echinocandins, and abolished fungal virulence in murine models. This finding demonstrates that lipid flippase may promote fungal drug resistance and virulence and indicates that this enzyme may represent a novel antifungal drug target.
Artificial oxygen carriers for trauma: myth or reality? (2004)

Two-unit blood transfusion accounts for one third of blood use in trauma patients. Artificial oxygen carriers have no need for cross-match, allow volume expansion, prolonged storage at 1-38 degrees C, and improve rheology to reverse ischaemia. Haemoglobin-based oxygen carriers can provide a vital alternative given the predicted future shortfall in blood donations.
ChemInform Abstract: PBr3‐Mediated Unexpected Reductive Deoxygenation of α‐Aryl‐pyridinemethanols: Synthesis of Arylmethylpyridines. (2016)

Abstract In an attempt to substitute the hydroxy group in the title compounds by a bromine, a direct reductive deoxygenation takes place to produce the desired final target compounds.
Genomic copy number alterations as predictive markers of systemic recurrence in breast cancer (2008)

We tried to establish models that predict systemic recurrence in breast cancer by selecting marker clones with DNA copy number alterations (CNAs) using an array comparative genomic hybridization (CGH). Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess CNAs in 62 primary breast cancer tissues from 31 patients with systemic recurrence within 5 years after surgery and clinicopathologically well matched 31 patients who had no evidence of disease for at least 5years. Fourteen significant clones (11 clones showing gain and 3 showing loss) were identified by systemic recurrence-free survival (SRFS) analysis and 23 significant clones (17 clones showing gain and 6 showing loss) identified by chi(2) test and FDR test were selected as predictive markers of systemic breast cancer recurrence. The significant CNAs were found in the chromosomal regions of 5p15.33, 11q13.3, 15q26.3, 17q25.3, 18q23 and 21q22.3 with gain and 9p12, 11q24.1 and 14q32.33 with loss. We devised 2 prediction models for the systemic recurrence of breast cancer based on the 14 clones and the 23 clones, respectively. The survivals of the patients were significantly separated according to the scores from each model at the optimal cut off values in SRFS and overall survival analysis. We found candidate clones and genes of which CNAs were significantly associated with systemic recurrence of breast cancer. The devised prediction models with these clones were effective at differentiating the recurrence and nonrecurrence.
Texture of AZ31B Magnesium alloy sheets (2004)

The textures of AZ31B magnesium alloy sheets in the conditions of hot rolling, cold rolling and heat treatment were investigated, and its feature and influence to the mechanical property anisotropy were studied. The conclusions show that the texture of rolled magnesium alloy sheet prefer to basal texture with basal plane parallel to sheet surface, while other compositions of texture are relatively weaker; the density center of basal pole rotates away by about 18° from the transverse direction of sheet to rolling direction; to cold-rolling of sheet, there is no significant change of texture distributing after heat treatment at 300℃. After cold-rolling of sheet, the basal plane slopes to rolling direction, improving the ductility in this direction.
One touch multi-banking transaction ATM system using biometric and GSM authentication (2017)

Every individuals has multiple bank accounts in different banks, people's need to carry multiple ATM cards for transaction, there may be different PINs for every account. In traditional system, ATM terminal customer recognition systems only rely on bank cards, security pin number, and such identity verification methods which measures are not perfect and functions are too single and at times there are incidents where we forget ours security PIN number, lose our cards, cards get stolen, stolen PIN numbers. To overcome the bugs in traditional ATM system, introducing a new ATM terminal customer recognition system, “One touch Multi-banking Transaction system using Biometric and GSM Authentication”. Biometric based fingerprint authentication technique is one of the most secure systems, unauthorized accesses are restricted, as this makes fingerprint a unique identification for everyone. This system also assures a secure GSM (OTP-One time Password) based transaction. Here the proposed system has no risk overhead in managing multiple account transactions and achieves high security as compare to the traditional ATM system.
Full Waveform Inversion and the Truncated Newton Method (2017)

International audience
Online daily adaptive proton therapy (2019)

It is recognized that the use of a single plan calculated on an image acquired some time before the treatment is generally insufficient to accurately represent the daily dose to the target and to the organs at risk. This is particularly true for protons, due to the physical finite range. Although this characteristic enables the generation of steep dose gradients, which is essential for highly conformal radiotherapy, it also tightens the dependency of the delivered dose to the range accuracy. In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution. A plan should be ideally adapted as soon as anatomical variations occur, ideally online. In this review, we describe in detail the different steps of the adaptive workflow and discuss the challenges and corresponding state-of-the art developments in particular for an <i>online</i> adaptive strategy.
MetaSV: an accurate and integrative structural-variant caller for next generation sequencing (2015)

Supplementary data are available at Bioinformatics online.
Convolutional Neural Network for Sentence Classification (2015)

The goal of a Knowledge Base–supported Question Answering (KB-supported QA) system is to answer a query natural language by obtaining the answer from a knowledge database, which stores knowledge in the form of (entity, relation, value) triples. QA systems understand questions by extracting entity and relation pairs. This thesis aims at recognizing the relation candidates inside a question. We define a multi-label classification problem for this challenging task. Based on the word2vec representation of words, we propose two convolutional neural networks (CNNs) to solve the multi-label classification problem, namely Parallel CNN and Deep CNN. The Parallel CNN contains four parallel convolutional layers while Deep CNN contains two serial convolutional layers. The convolutional layers of both the models capture local semantic features. A max over time pooling layer is placed on the top of the last convolutional layer to select global semantic features. Fully connected layers with dropout are used to summarize the features. Our experiments show that these two models outperform the traditional Support Vector Classification (SVC)–based method by a large margin. Furthermore, we observe that Deep CNN has better performance than Parallel CNN, indicating that the deep structure enables much stronger semantic learning capacity than the wide but shallow network.
Integrated development of distributed real-time applications with asynchronous communication (2007)

This paper illustrates added values of an integrated development methodology for distributed real-time applications. Strategic focuses of the proposed methodology and middle-ware framework are real-time and embedded applications. The framework builds on top of real-time Java with an asynchronous communication model for broadcast networks and fieldbusses. Results of the EC research projects HIDOORS (IST 2001-32329) and HIJA (IST 2003-511718) are used to establish a methodology which supports design, implementation, and analysis of distributed real-time applications.
The inhibited autoxidation of styrene. Part VI. The relative efficiencies and the kinetics for inhibition by N-aryl anilines and N-alkyl anilines (1967)

The kinetics and deuterium isotope effects for the N-aryl aniline and N-alkyl aniline inhibited autoxidation of styrene indicate that the rate-controlling step for inhibition involves abstraction of the amino hydrogen by a peroxy radical. The rate constants for this reaction have been correlated by means of the Hammett equation with the σ + constants of the substituents for diphenylamines (ρ = −0.89) and N-methylanilines (ρ = −1.6). A numerical difference involving a factor of two between the simple kinetic expression applicable to most aromatic amine inhibitors and the expression applicable to most phenols and p-phenylenediamines is suggested. The important role played by the substrate in studies of inhibitor action is emphasized.
Pulmonary aspects of anaesthesia (1993)

University of Pennsylvania, and The Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
Small-molecule p21-activated kinase inhibitor PF-3758309 is a potent inhibitor of oncogenic signaling and tumor growth (2010)

Despite abundant evidence that aberrant Rho-family GTPase activation contributes to most steps of cancer initiation and progression, there is a dearth of inhibitors of their effectors (e.g., p21-activated kinases). Through high-throughput screening and structure-based design, we identify PF-3758309, a potent (K(d) = 2.7 nM), ATP-competitive, pyrrolopyrazole inhibitor of PAK4. In cells, PF-3758309 inhibits phosphorylation of the PAK4 substrate GEF-H1 (IC(50) = 1.3 nM) and anchorage-independent growth of a panel of tumor cell lines (IC(50) = 4.7 +/- 3 nM). The molecular underpinnings of PF-3758309 biological effects were characterized using an integration of traditional and emerging technologies. Crystallographic characterization of the PF-3758309/PAK4 complex defined determinants of potency and kinase selectivity. Global high-content cellular analysis confirms that PF-3758309 modulates known PAK4-dependent signaling nodes and identifies unexpected links to additional pathways (e.g., p53). In tumor models, PF-3758309 inhibits PAK4-dependent pathways in proteomic studies and regulates functional activities related to cell proliferation and survival. PF-3758309 blocks the growth of multiple human tumor xenografts, with a plasma EC(50) value of 0.4 nM in the most sensitive model. This study defines PAK4-related pathways, provides additional support for PAK4 as a therapeutic target with a unique combination of functions (apoptotic, cytoskeletal, cell-cycle), and identifies a potent, orally available small-molecule PAK inhibitor with significant promise for the treatment of human cancers.
Early type stars as calibrators for ground-based interferometry (2006)

Visibility measurements with Michelson interferometers, particularly the measurement of fringe contrast, are affected by various atmospheric and instrumental effects, all of which reduce the measured contrast. To compensate for this, stars with known or predictable diameters (calibrators) are observed so that the overall reduction in the visibility can be measured. Objects with the smallest possible diameters are preferred as calibrators, since the predicted visibilities become less sensitive to any uncertainties. Therefore, unreddened, early type stars are usually chosen if they are available because they are relatively bright for a given angular diameter. However, early type stars bring additional complications. Rapid rotation, common with these stars can cause variations in the visibility amplitudes due to oblateness and surface brightness asymmetries that are larger than implied by the usual error estimates. In addition, rotation can introduce significant phase offsets. Using Roche models, von Zeipel theory, and the observed constraints of V, B-V, and <i>v</i> sin <i>i</i>, it is possible to put limits on the size of these effects and even estimate the distribution of possible visibilities. To make this easily available to the community, we are in the process of creating a catalog of possible calibrators, including histograms of the visibilities, calculated for configurations used at a number of observatories. We show the examples of several early type stars which are potential calibrators using parameters appropriate for the Navy Prototype Optical Interferometer.
Long-term impact of nitrogen addition on the carbon balance of a boreal pine forest in Northern Sweden (2020)

&amp;lt;p&amp;gt;Nitrogen (N) added through atmospheric deposition or as fertilizer in boreal forests may alter their carbon (C) sequestration potential and sensitivity to climatic changes. While previous studies have primarily explored the responses of individual ecosystem components such as stem biomass production and soil carbon changes following N addition, the long-term impacts of N addition on the ecosystem-scale C balance of boreal forests still remain unclear. Here, we use data from eddy-covariance measurements in a fertilized Scots pine (Pinus sylvestris L.) forest (i.e. 16 ha receiving 100 and 50 kg N ha&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; since 2006 and 2012, respectively) and an adjacent unfertilized control stand in boreal Sweden to investigate how one decade of N addition affected the net ecosystem productivity (NEP), gross primary production (GPP) and ecosystem respiration (ER) over five fertilization years (2015-2019). Results showed that N fertilization increased GPP in all five years with by 18% at average to 1183&amp;amp;#177;41 g C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; in the N-fertilized stand compared to 1003&amp;amp;#177;56 g C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; in the control stand. ER was also increased from 744&amp;amp;#177;29 g C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; in the control stand to 875&amp;amp;#177;37 g C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; in the fertilized stand. As a result, fertilization increased NEP from 259&amp;amp;#177;28 g C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; in the control stand to 308&amp;amp;#177;20 g C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-1&amp;lt;/sup&amp;gt; in the N-fertilized stand. Our results further suggested that the annual NEP was similar between stands during years with normal weather conditions (2015-2016) while NEP diverged due to a larger reduction in the control stand in years with environmental constraints (i.e. a cool summer in 2017 and droughts in 2018 and 2019). These findings indicate that enhanced N input to boreal forests increases and stabilizes their C sequestration potential under future climate conditions.&amp;lt;/p&amp;gt;
Nitric Oxide Generation on Demand for Biomedical Applications via Electrocatalytic Nitrite Reduction by Copper BMPA- and BEPA-Carboxylate Complexes (2019)

Intravascular (IV) catheters are essential devices in the hospital that are used to monitor a patient's blood and for administering drugs or nutrients. However, IV catheters are also prone to blood clotting at the point of insertion and infection by formation of robust bacterial biofilms on their surface. Nitric oxide (NO) is ideally suited to counteract both of these problems, due to its antimicrobial properties and its ability to inhibit platelet activation/aggregation. One way to equip catheters with NO releasing properties is by electrocatalytic nitrite reduction to NO by copper complexes in a multi-lumen configuration. In this work, we systematically investigate six closely related Cu(II) BMPA- and BEPA-carboxylate complexes (BMPA = bis-(2-methylpyridyl)amine); BEPA = bis-(2-ethylpyridyl)amine), using carboxylate groups of different chain lengths. The corresponding Cu(II) complexes were characterized using UV-Vis, EPR spectroscopy, and X-ray crystallography. Using detailed cyclic voltammetry (CV) and bulk electrocatalyic studies (with real-time NO quantification), in aqueous buffer, pH 7.4, we are able to derive clear reactivity relations between the ligand structures of the complexes, their Faradaic efficiencies for NO generation, their turnover frequencies (TOFs), and their redox potentials. Our results show that the complex [Cu(BEPA-Bu)](OAc) is the best catalyst with a high Faradaic efficiency over large nitrite concentration ranges and the expected best tolerance to oxygen levels. For this species, the more positive redox potential suppresses NO disproportionation, which is a major Achilles heel of the (faster) catalysts with the more negative reduction potentials.
Analyzing the Sensitivity of WRF’s Single-Layer Urban Canopy Model to Parameter Uncertainty Using Advanced Monte Carlo Simulation (2011)

Abstract Single-layer physically based urban canopy models (UCM) have gained popularity for modeling urban–atmosphere interactions, especially the energy transport component. For a UCM to capture the physics of conductive, radiative, and turbulent advective transport of energy, it is important to provide it with an accurate parameter space, including both mesoscale meteorological forcing and microscale surface inputs. While field measurement of all input parameters to a UCM is rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty for model performance. In this paper, an advanced Monte Carlo approach—namely, subset simulation—is used to quantify the impact of the uncertainty of surface input parameters on the output of an offline modified version of the Weather Research and Forecasting (WRF)-UCM. On the basis of the conditional sampling technique, the importance of surface parameters is determined in terms of their impact on critical model responses. It is found that model outputs (both critical energy fluxes and surface temperatures) are highly sensitive to uncertainties in urban geometry, whereas variations in emissivities and building interior temperatures are relatively insignificant. In addition, the sensitivity of the model to input surface parameters is also shown to be very weakly dependent on meteorological parameters. The statistical quantification of the model’s sensitivity to input parameters has practical implications, such as surface parameter calibrations in UCM and guidance for urban heat island mitigation strategies.
Evidence of Maintenance Tagging in the Hippocampus for the Persistence of Long-Lasting Memory Storage (2015)

The synaptic tagging and capture (STC) hypothesis provides a compelling explanation for synaptic specificity and facilitation of long-term potentiation. Its implication on long-term memory (LTM) formation led to postulate the behavioral tagging mechanism. Here we show that a maintenance tagging process may operate in the hippocampus late after acquisition for the persistence of long-lasting memory storage. The proposed maintenance tagging has several characteristics: (1) the tag is transient and time-dependent; (2) it sets in a late critical time window after an aversive training which induces a short-lasting LTM; (3) exposing rats to a novel environment specifically within this tag time window enables the consolidation to a long-lasting LTM; (4) a familiar environment exploration was not effective; (5) the effect of novelty on the promotion of memory persistence requires dopamine D1/D5 receptors and Arc expression in the dorsal hippocampus. The present results can be explained by a broader version of the behavioral tagging hypothesis and highlight the idea that the durability of a memory trace depends either on late tag mechanisms induced by a training session or on events experienced close in time to this tag.
An optical search for transients lasting a few seconds (2019)

Abstract Using a prototype of the Tomo-e Gozen wide-field CMOS mosaic camera, we acquire wide-field optical images at a cadence of $2\:$Hz and search them for transient sources of duration 1.5 to $11.5\:$s. Over the course of eight nights, our survey encompasses the equivalent of roughly two days on one square degree, to a fluence equivalent to a limiting magnitude of about $V = 15.6$ in a 1-s exposure. After examining by-eye the candidates identified by a software pipeline, we find no sources which meet all our criteria. We compute upper limits to the rate of optical transients consistent with our survey, and compare those to the rates expected and observed for representative sources of ephemeral optical light.
Crystallization Kinetics in Atomic Layer Deposited (ALD) Thin Films: Opportunities of Time and Chemical Environment (2022)

Atomic layer deposition (ALD) frequently produces amorphous films, however crystalline phases are often desired for various electrical, chemical, and optical applications. Thus, understanding the fundamental crystallization kinetics of films deposited by ALD is important in designing process pathways to achieve low-temperature crystallization, ultra-thin film (&lt;50 nm) crystallization, controlled microstructures, and epitaxial growth. This presentation will discuss our work to study the crystallization kinetics in ALD TiO 2 thin films and challenge some pre-conceived notions about thickness and temperature requirements for ALD film crystallization. We will focus on a prototypical TiO 2 ALD process using tetrakis(dimethylamino)titanium(IV) (TDMAT) and water at between 140 °C and 220 °C. Initially, we will discuss data collected on post-deposition, isothermal crystallization kinetics at temperatures ranging from 140 to 200 °C. These time-dependent transformation kinetics are fit to the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, revealing a continuous nucleation process and a two-dimensional growth mechanism, consistent with the observed grain sizes. We also use images collected over short annealing times to independently determine the crystal nucleation rate, which allows us to determine that the activation energies for nucleation (1.32–1.35 eV K -1 atom -1 ) are about one order of magnitude greater than the activation energies for grain growth (0.12–0.24 eV K -1 atom -1 ), sugggesting that nucleation is the more significant barrier to crystallization in this system. Finally, we will show how a modification to the process’s chemical environment can lower this barrier to nucleation leading to dramatic in situ crystallization (with no post-deposition annealing) at unusually low process temperatures and film thicknesses (&lt; 15 nm).