gebhart/patrepeval huggingface dataset:
Multivariate and Multiscale Dependence in the Global Climate System Revealed Through Complex Networks (2011)

A systematic characterization of multivariate dependence at multiple spatio-temporal scales is critical to understanding climate system dynamics and improving predictive ability from models and data. However, dependence structures in climate are complex due to nonlinear dynamical generating processes, long-range spatial and long-memory temporal relationships, as well as low-frequency variability. Here we utilize complex networks to explore dependence in climate data. Specifically, networks constructed from reanalysis-based atmospheric variables over oceans and partitioned with community detection methods demonstrate the potential to capture regional and global dependence structures within and among climate variables. Proximity-based dependence as well as long-range spatial relationships are examined along with their evolution over time, yielding new insights on ocean meteorology. The tools are implicitly validated by confirming conceptual understanding about aggregate correlations and teleconnections. Our results also suggest a close similarity of observed dependence patterns in relative humidity and horizontal wind speed over oceans. In addition, updraft velocity, which relates to convective activity over the oceans, exhibits short spatiotemporal decorrelation scales but long-range dependence over time. The multivariate and multi-scale dependence patterns broadly persist over multiple time windows. Our findings motivate further investigations of dependence structures among observations, reanalysis and model-simulated data to enhance process understanding, assess modelmore » reliability and improve regional climate predictions.« less
Dependent classes (2007)

Virtual classes allow nested classes to be refined in subclasses. In this way nested classes can be seen as dependent abstractions of the objects of the enclosing classes. Expressing dependency via nesting, however, has two limitations: Abstractions that depend on more than one object cannot be modeled and a class must know all classes that depend on its objects. This paper presents dependent classes , a generalization of virtual classes that expresses similar semantics by parameterization rather than by nesting. This increases expressivity of class variations as well as the flexibility of their modularization. Besides, dependent classes complement multimethods in scenarios where multi-dispatched abstractions rather than multi-dispatched methods are needed. They can also be used to express more precise signatures of multimethods and even extend their dispatch semantics. We present a formal semantics of dependent classes and a machine-checked type soundness proof in Isabelle/HOL [29], the first of this kind for a language with virtual classes and path-dependent types.
Performance of adaptive beamforming arrays for spatial interference rejection (2005)

This paper analyzes the performance of LMS and RLS adaptive beamforming algorithms used in smart antenna systems for spatial interference rejection. Multiple criteria are used to evaluate these beamforing algorithms including number of incident signals and their angular separation, number of array sensors and their spacing. Results of numerical simulations are useful for the design smart antenna systems with optimal performance.
Porous PEOT/PBT scaffolds for bone tissue engineering: Preparation, characterization, and in vitro bone marrow cell culturing (2002)

The preparation, characterization, and in vitro bone marrow cell culturing on porous PEOT/PBT copolymer scaffolds are described. These scaffolds are meant for use in bone tissue engineering. Previous research has shown that PEOT/PBT copolymers showed in vivo degradation, calcification, and bone bonding. Despite this, several of these copolymers do not support bone marrow cell growth in vitro. Surface modification, such as gas-plasma treatment, is needed to improve the in vitro cell attachment. Porous structures were prepared using a freeze-drying and a salt-leaching technique, the latter one resulting in highly porous interconnected structures of large pore size. Gas-plasma treatment with CO(2) generated a surface throughout the entire structure that enabled bone marrow cells to attach. The amount of DNA was determined as a measure for the amount of cells present on the scaffolds. No significant effect of pore size on the amount of DNA present was seen for scaffolds with pore sizes between 250-1000 microm. Light microscopy data showed cells in the center of the scaffolds, more cells were observed in the scaffolds of 425-500 microm and 500-710 microm pore size compared to the ones with 250-425 microm and 710-1000 microm pores.
Reactive ion etching: Optimized diamond membrane fabrication for transmission electron microscopy (2013)

Commonly used preparation method for thin diamond membranes by focused ion beam (FIB) techniques results in surface damage. Here, the authors introduce an alternative method based on reactive ion etching (RIE). To compare these methods, cross-sectional samples are produced in single crystal diamond, a material that has generated growing interest for a variety of applications. The samples are examined by Raman spectroscopy and high-resolution transmission electron microscopy (TEM). Raman spectra indicate that the crystalline structure of the RIE-processed diamond is preserved, while the FIB-processed diamond membrane has a broad-background sp2 feature. Atomic-resolution TEM imaging demonstrates that the RIE-based process produces no detectable damage, while the FIB-processed sample has an amorphous carbon layer of about 11 nm thick. These findings show that the RIE-based process allows the production of diamond TEM samples with reduced near-surface damage and can thus enable direct examination of growth defects and crystallographic damage induced by processes such as ion implantation and bombardment.
Comparing rapid rule-learning strategies in humans and monkeys (2023)

Inter-species comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of macaque monkey and human strategies on an analogue of the Wisconsin Card Sort Test, a widely studied and applied multi-attribute measure of cognitive function, wherein performance requires the inference of a changing rule given ambiguous feedback. We found that well-trained monkeys rapidly infer rules but are three times slower than humans. Model fits to their choices revealed hidden states akin to feature-based attention in both species, and decision processes that resembled a Win-stay lose-shift strategy with key differences. Monkeys and humans test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidates. An attention-set based learning stage categorization revealed that perseveration, random exploration and poor sensitivity to negative feedback explain the under-performance in monkeys.
Domain Knowledge Driven Pseudo Labels for Interpretable Goal-Conditioned Interactive Trajectory Prediction (2022)

Motion forecasting in highly interactive scenarios is a challenging problem in autonomous driving. In such scenarios, we need to accurately predict the joint behavior of interacting agents to ensure the safe and efficient navigation of autonomous vehicles. Recently, goal-conditioned methods have gained increasing attention due to their advantage in performance and their ability to capture the multimodality in trajec-tory distribution. In this work, we study the joint trajectory prediction problem with the goal-conditioned framework. In particular, we introduce a conditional-variational-autoencoder-based (CVAE) model to explicitly encode different interaction modes into the latent space. However, we discover that the vanilla model suffers from posterior collapse and cannot induce an informative latent space as desired. To address these issues, we propose a novel approach to avoid KL vanishing and induce an interpretable interactive latent space with pseudo labels. The proposed pseudo labels allow us to incorporate domain knowledge on interaction in a flexible manner. We motivate the proposed method using an illustrative toy example. In addition, we validate our framework on the Waymo Open Motion Dataset with both quantitative and qualitative evaluations.
2420Effects of a selective small-molecule formyl peptide receptor 2 agonist on post myocardial inflammation and left ventricular structure-function relationships (2019)

Abstract Background/Introduction Dysregulated inflammation following myocardial infarction (MI) can lead to maladaptive infarct healing, myocardial damage and heart failure. Formyl peptide receptor 2 (FPR2) plays an important role in the ligand-dependent regulation of inflammation resolution. Stimulation of resolution via FPR2 activation is hypothesized to preserve left ventricular (LV) structure-function relationships thereby preventing pathological cardiac remodeling, and heart failure. Purpose We evaluated a selective 4-phenylpyrrolidinone FPR2 agonist in rodent MI models by assessing the impact on LV and infarct scar remodeling and cardiac function. Methods The FPR2 agonist was evaluated in phagocytosis, chemotaxis and cytokine response assays. In vivo, following permanent occlusion of the left anterior descending (LAD) artery, C57BL/6 mice or Sprague-Dawley rats were treated with the FPR2 agonist or vehicle; PO gavage, QD. Treatment began 24 hours after occlusion (0.3 and 3 mg/kg) and continued for three days to assess early inflammation or four weeks to evaluate LV and infarct structure and function. Rats subjected to permanent MI were treated 48 hours after occlusion (0.01, 0.1. 1, 10 mg/kg) for six weeks to assess structure-function relationships. A parallel study in rats evaluated compound treatment (0.01, 0.1. 1, 10 mg/kg) following 60 minutes occlusion and reperfusion of the LAD artery. Results The FPR2 agonist enhanced cellular phagocytosis and chemotaxis, and stimulated IL-10 and MCP-1 gene expression in isolated human whole blood. In mice, FPR2 agonist treatment improved survival post MI, reduced LV chamber area and infarct size (26% and 55% vs. vehicle, respectively, P&lt;0.05) and preserved infarct wall thickness (59% vs. vehicle, P&lt;0.05). Treatment increased macrophage arginase 1 levels three days post-MI in the infarct border zone and CD206 levels in the whole heart, indicating a shift towards a pro-resolution phenotype. In rats, FPR2 agonist treatment preserved infarct wall thickness (maximal at 10 mg/kg, 96% vs. vehicle, P&lt;0.05) and increased LV ejection fraction at all doses (+9% vs. vehicle, P&lt;0.05). Following occlusion and reperfusion of the LAD artery, treatment preserved viable myocardium across the infarct wall at multiple doses (25–41%, P&lt;0.05) resulting in increased ejection fraction (14% and 19% vs vehicle at 0.01 and 1 mg/kg, respectively, P&lt;0.05). Conclusion(s) Improvements in cardiac structure-function versus vehicle treated animals support the concept that agonism of FPR2 improves post-MI wound healing, limiting adverse post-MI LV remodeling, thereby preserving cardiac function. These preclinical results suggest targeting FPR2 may present an innovative approach towards development of effective drug therapies to prevent heart failure post-MI. Acknowledgement/Funding Bristol-Myers Squibb Company
First-in-Class Inhibitors of the Ribosomal Oxygenase MINA53 (2021)

MINA53 is a JmjC domain 2-oxoglutarate-dependent oxygenase that catalyzes ribosomal hydroxylation and is a target of the oncogenic transcription factor <i>c</i>-MYC. Despite its anticancer target potential, no small-molecule MINA53 inhibitors are reported. Using ribosomal substrate fragments, we developed mass spectrometry assays for MINA53 and the related oxygenase NO66. These assays enabled the identification of 2-(aryl)alkylthio-3,4-dihydro-4-oxoypyrimidine-5-carboxylic acids as potent MINA53 inhibitors, with selectivity over NO66 and other JmjC oxygenases. Crystallographic studies with the JmjC demethylase KDM5B revealed active site binding but without direct metal chelation; however, molecular modeling investigations indicated that the inhibitors bind to MINA53 by directly interacting with the iron cofactor. The MINA53 inhibitors manifest evidence for target engagement and selectivity for MINA53 over KDM4-6. The MINA53 inhibitors show antiproliferative activity with solid cancer lines and sensitize cancer cells to conventional chemotherapy, suggesting that further work investigating their potential in combination therapies is warranted.
Изучение противовирусной активности Ингавирина® in vitro в отношении метапневмовируса человека (2012)

The antiviral activity of Ingavirin® against human metapneumovirus (HMPV) infection was investigated in vitro. The investigation used the human cell line ChangConjunctiva, permissive for HMPV, clone 1-5C4, and the HMPV strain isolated at the D. I. Ivanovsky Research Institute of Virology. The experimental studies suggest that when added at a concentration of 50 to 500 μg/ml to a nutrient medium 24 hours after HMPV infection, Ingavirin® suppressed effectively virus replication by 2.2-3.3 logs, respectively. When used at a concentration of 500 μg/ml 24 hours before cell infection, Ingavirin® protected cells from HMPV infection.
Ferroelectric thin films grown on tensile substrates: Renormalization of the Curie–Weiss law and apparent absence of ferroelectricity (1999)

A thermodynamic theory is used to calculate the dielectric properties of epitaxial thin films grown on cubic substrates imposing biaxial tension on the film prototypic cubic state. For such “tensile” substrates, the theory shows that, in a conventional plate–capacitor setup, the films should display only a monotonic variation or a broad maximum in the temperature dependence of the permittivity and an apparent absence of the hysteretic polarization behavior. Changes of the Curie–Weiss temperature and constant caused by the mechanical film/substrate interaction are also predicted. Theoretical results agree with the observed properties of columnar-structured BaTiO3 and SrTiO3 thin films grown on Si.
Cardiopulmonary Long-Term Sequelae in Patients after Severe COVID-19 Disease (2023)

We aimed to identify cardiopulmonary long-term effects after severe COVID-19 disease as well as predictors of Long-COVID in a prospective registry. A total of 150 consecutive, hospitalized patients (February 2020 and April 2021) were included six months post hospital discharge for a clinical follow-up. Among them, 49% experienced fatigue, 38% exertional dyspnea and 75% fulfilled criteria for Long-COVID. Echocardiography detected reduced global longitudinal strain (GLS) in 11% and diastolic dysfunction in 4%. Magnetic resonance imaging revealed traces of pericardial effusion in 18% and signs of former pericarditis or myocarditis in 4%. Pulmonary function was impaired in 11%. Chest computed tomography identified post-infectious residues in 22%. Whereas fatigue did not correlate with cardiopulmonary abnormalities, exertional dyspnea was associated with impaired pulmonary function (OR 3.6 [95% CI: 1.2-11], <i>p</i> = 0.026), reduced GLS (OR 5.2 [95% CI: 1.6-16.7], <i>p</i> = 0.003) and/or left ventricular diastolic dysfunction (OR 4.2 [95% CI: 1.03-17], <i>p</i> = 0.04). Predictors of Long-COVID included length of in-hospital stay (OR: 1.15 [95% CI: 1.05-1.26], <i>p</i> = 0.004), admission to intensive care unit (OR cannot be computed, <i>p</i> = 0.001) and higher NT-proBNP (OR: 1.5 [95% CI: 1.05-2.14], <i>p</i> = 0.026). Even 6 months after discharge, a majority fulfilled criteria for Long-COVID. While no associations between fatigue and cardiopulmonary abnormalities were found, exertional dyspnea correlated with impaired pulmonary function, reduced GLS and/or diastolic dysfunction.
Plasmon induced transparency in three dimensional magnetic meta-molecules (2012)

We report the first three-dimensional photonic metamaterial, an array of erected U-shape plasmonic gold meta-molecules, that exhibits plasmon induced transparency due to the magnetic field coupling between metamolecules. Using electron beam lithography with alignment technique , three erected U-shape gold nano rings are integrated in a unit cell with 6 00 nm periodicity both in x and y direction s, covering the total area of 75 ´ 75 µm 2 on a fused silica substrate. T he height of each gold nano ring is 110 nm. By introducing structural asymmetry, the magnetic field of the bright split ring resonator (SRR) couple to the other two dark SRRs result in an energy level splitting, which is similar with EIT-like spectra . A classical RLC circuit model was proposed to explain the coupling mechanism of EIT-like spectra .
Quantification of low-affinity kinetics between cancer immunity relevant ligands and natural killer cell receptors with a self-induced back-action actuated nanopore electrophoresis (SANE) sensor (2020)

A plasmonic nanopore sensor enabling detection of bimodal optical and electrical molecular signatures was fabricated and tested for its ability to characterize low affinity ligand-receptor interactions. This plasmonic nanosensor uses a Self- Induced Back-Action (SIBA) mechanism for optical trapping to enable SIBA-Actuated Nanopore Electrophoresis (SANE) sensing through a nanopore located immediately below the optical trap volume. The ligand-receptor model consisted of a Natural Killer (NK) cell inhibitory receptor heterodimer molecule CD94/NKG2A that was synthesized to target a specific peptide-presenting Qa-1<sup>b</sup> Qdm ligand. The latter interaction pair was used as a simplified model of lowaffinity interactions between immune cells and peptide-presenting cancer cells that occur during cancer immunotherapy. A cancer-irrelevant GroEL ligand was also targeted by the same receptor in control experiments to test for non-specific interactions. Although the analysis of different pairs of bimodal SANE sensor signatures enabled some level of discrimination between specific and non-specific interactions the separation was not complete, which suggested the need for multi-dimensional data analyses in future work. Nevertheless, the SANE sensor showed ability to quantify the fast dissociation rate (<i>k</i><sub>off</sub>) in this low-affinity model system that was previously shown to be challenging to quantify with commercial technologies. The <i>k</i><sub>off</sub> value of targeted peptide-presenting ligands is known to correlate with the subsequent activation of immune cells in vivo, suggesting the potential utility of the SANE sensor as a screening tool in cancer immunotherapy.
An efficient approach suitable for the analysis and design of nonuniform transmission lines (1995)

Abstract A new method of moment‐based formulation for the analysis of nonuniform transmission lines is presented. Subdomain complex basis functions are used to simulate different structures over a wide range of frequencies. The results obtained using the proposed formulation are validated by comparison to those obtained by CAD packages. Strip‐line and microstrip‐line transitions are investigated with an application to the design of a matched microstrip taper with width and dielectric height variations. © 1995 John Wiley &amp; Sons, Inc.
Deducing Ink Spreading Curves from Reflection Spectra Acquired Within Printed Color Images (2009)

The Yule&#x2013;Nielsen modified spectral Neugebauer model (YNSN) enhanced for accounting for ink spreading in the different ink superposition conditions provides accurate spectral predictions, but requires one to measure the reflectances of special halftone calibration patches in order to compute the ink spreading curves mapping nominal ink surface coverage to effective ink surface coverage. Printing special halftone calibration patches within the borders of the print pages is cumbersome, since these special patches need to be cut out before assembling the final printed product. In the present contribution, we calibrate the ink spreading curves directly from the printed images by fitting them so as to minimize a distance metric between predicted reflectances and measured reflectances at selected relatively uniform locations. We compare the prediction accuracy of the so-calibrated YNSN model with the prediction accuracy of the same model calibrated by the spectral reflectances of classical uniform calibration patches. Interestingly, when the model is calibrated from image tiles originating from the same or from a similar color image as the one comprising the test tiles, better prediction results are obtained than when performing a classical calibration on 50% halftone patches printed in all superposition conditions.
Passive sweat wearable: A new paradigm in the wearable landscape toward enabling “detect to treat” opportunities (2023)

Growing interest over recent years in personalized health monitoring coupled with the skyrocketing popularity of wearable smart devices has led to the increased relevance of wearable sweat-based sensors for biomarker detection. From optimizing workouts to risk management of cardiovascular diseases and monitoring prediabetes, the ability of sweat sensors to continuously and noninvasively measure biomarkers in real-time has a wide range of applications. Conventional sweat sensors utilize external stimulation of sweat glands to obtain samples, however; this stimulation influences the expression profile of the biomarkers and reduces the accuracy of the detection method. To address this limitation, our laboratory pioneered the development of the passive sweat sensor subfield, which allowed for our progress in developing a sweat chemistry panel. Passive sweat sensors utilize nanoporous structures to confine and detect biomarkers in ultra-low sweat volumes. The ability of passive sweat sensors to use smaller samples than conventional sensors enable users with sedentary lifestyles who perspire less to benefit from sweat sensor technology not previously afforded to them. Herein, the mechanisms and strategies of current sweat sensors are summarized with an emphasis on the emerging subfield of passive sweat-based diagnostics. Prospects for this technology include discovering new biomarkers expressed in sweat and expanding the list of relevant detectable biomarkers. Moreover, the accuracy of biomarker detection can be enhanced with machine learning using prediction algorithms trained on clinical data. Applying this machine learning in conjunction with multiplex biomarker detection will allow for a more holistic approach to trend predictions. This article is categorized under: Diagnostic Tools > Diagnostic Nanodevices Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > Biosensing.
Study on Sharpless Kinetic Resol Ution of Racemic Allyl Propargyl Alcohols (1988)

Abstract A kinetic resolution of racemic allyl propargyl alcohols by enantioselective epoxidation is described.