gebhart/patrepeval huggingface dataset:
Data from An Integrative Genomic and Proteomic Analysis of PIK3CA, PTEN, and AKT Mutations in Breast Cancer (2023)

&lt;div&gt;Abstract&lt;p&gt;Phosphatidylinositol 3-kinase (PI3K)/AKT pathway aberrations are common in cancer. By applying mass spectroscopy–based sequencing and reverse-phase protein arrays to 547 human breast cancers and 41 cell lines, we determined the subtype specificity and signaling effects of &lt;i&gt;PIK3CA, AKT&lt;/i&gt;, and &lt;i&gt;PTEN&lt;/i&gt; mutations and the effects of &lt;i&gt;PIK3CA&lt;/i&gt; mutations on responsiveness to PI3K inhibition &lt;i&gt;in vitro&lt;/i&gt; and on outcome after adjuvant tamoxifen. &lt;i&gt;PIK3CA&lt;/i&gt; mutations were more common in hormone receptor–positive (34.5%) and HER2-positive (22.7%) than in basal-like tumors (8.3%). &lt;i&gt;AKT1&lt;/i&gt; (1.4%) and &lt;i&gt;PTEN&lt;/i&gt; (2.3%) mutations were restricted to hormone receptor–positive cancers. Unlike &lt;i&gt;AKT1&lt;/i&gt; mutations that were absent from cell lines, &lt;i&gt;PIK3CA&lt;/i&gt; (39%) and &lt;i&gt;PTEN&lt;/i&gt; (20%) mutations were more common in cell lines than tumors, suggesting a selection for these but not &lt;i&gt;AKT1&lt;/i&gt; mutations during adaptation to culture. &lt;i&gt;PIK3CA&lt;/i&gt; mutations did not have a significant effect on outcome after adjuvant tamoxifen therapy in 157 hormone receptor–positive breast cancer patients. &lt;i&gt;PIK3CA&lt;/i&gt; mutations, in comparison with PTEN loss and &lt;i&gt;AKT1&lt;/i&gt; mutations, were associated with significantly less and inconsistent activation of AKT and of downstream PI3K/AKT signaling in tumors and cell lines. PTEN loss and &lt;i&gt;PIK3CA&lt;/i&gt; mutation were frequently concordant, suggesting different contributions to pathophysiology. PTEN loss rendered cells significantly more sensitive to growth inhibition by the PI3K inhibitor LY294002 than did &lt;i&gt;PIK3CA&lt;/i&gt; mutations. Thus, PI3K pathway aberrations likely play a distinct role in the pathogenesis of different breast cancer subtypes. The specific aberration present may have implications for the selection of PI3K-targeted therapies in hormone receptor–positive breast cancer. [Cancer Res 2008;68(15):6084–91]&lt;/p&gt;&lt;/div&gt;
Analysis of CDMA cellular radio systems employing adaptive antennas in multipath environments (2002)

This paper presents an analysis of code division multiple access (CDMA) cellular radio systems employing adaptive antennas in multipath environments. The results of simulations are described which illustrate the capacity improvements that can be achieved on the reverse link of a biphase asynchronous CDMA system using adaptive antenna arrays and switched beam systems at the base station. The effects of varying channel parameters are investigated for both correlated and uncorrelated multipath environments and the impact of imperfect power control is considered. Results are presented using both a geometrically based channel model and channels generated using ray tracing with a three dimensional building data base. These results indicate that the multipath structure significantly impacts the performance improvements that can be achieved by spatial filter systems.
Correlation of Signal‐Averaged P Wave with Electrophysiological Testing for Atrial Vulnerability in Strokes of Unexplained Etiology (1994)

SAPW may be useful to identify patients at risk of PAF who may be candidates for EPS.
Word-parallel associative memory for k-nearest-neighbor with configurable storage space of reference vectors (2015)

Apart from the speed performance, a common IC-implementation problem for nearest neighbor search, one of the most basic algorithms in pattern recognition, is low flexibility to different task applications. We report a digital word-parallel as sociative memory architecture with reconfigurable storage-space of reference vectors and clock-counting-based nearest-Euclidean-distance search, enabling single-chip implementation of k-nearest-neighbor (kNN) classification and configuration for m any different applications. The main time-consuming part of kNN, the clock-based minimal-distance searching, is carried out by weighted frequency dividers that drastically reduce the in principle exponential increase of the worst-case search-clock number with the bit width of vector components to only a linear in crease. This clock-based search concept achieves thus high classification speed, good area-efficiency and low power dissipation. In general, an IC implementation has limited flexibility after manufacturing. The proposed programmable switching circuits, which are located between groups of vector components, enable flexibility of reference feature-vector dimension and number at the same time. After k minimal distance searching, a dedicated circuit for majority vote is used to assign the unknown input to the class with the highest vote value. A test chip in 180 nm CMOS technology, which has 32 rows, 4 elements in each row and 2 8-bit components in each element, achieves low power dissipation of 61.4 mW (at 45.58 MHz and 1.8 V). In particular, the reconfigurable distance search circuit consumes only 11.9 mW.
A key-based coordination algorithm for dynamic readiness and repair service coordination (2003)

This paper describes an agent application for the coordination of air-craft repair, refit, refuel, and rearm teams in a dynamic setting. The paper also presents a new algorithm for dynamic distributed service team coordination and compares its performance to an optimal cen-tralized service team scheduler.
Evaluation of the potassium channel tracer [ 18 F]3F4AP in rhesus macaques (2020)

Demyelination causes slowed or failed neuronal conduction and is a driver of disability in multiple sclerosis and other neurological diseases. Currently, the gold standard for imaging demyelination is MRI, but despite its high spatial resolution and sensitivity to demyelinated lesions, it remains challenging to obtain specific and quantitative measures of molecular changes involved in demyelination. To understand the contribution of demyelination in different diseases and to assess the efficacy of myelin-repair therapies, it is critical to develop new in vivo imaging tools sensitive to changes induced by demyelination. Upon demyelination, axonal K<sup>+</sup> channels, normally located underneath the myelin sheath, become exposed and increase in expression, causing impaired conduction. Here, we investigate the properties of the K<sup>+</sup> channel PET tracer [<sup>18</sup>F]3F4AP in primates and its sensitivity to a focal brain injury that occurred three years prior to imaging. [<sup>18</sup>F]3F4AP exhibited favorable properties for brain imaging including high brain penetration, high metabolic stability, high plasma availability, high reproducibility, high specificity, and fast kinetics. [<sup>18</sup>F]3F4AP showed preferential binding in areas of low myelin content as well as in the previously injured area. Sensitivity of [<sup>18</sup>F]3F4AP for the focal brain injury was higher than [<sup>18</sup>F]FDG, [<sup>11</sup>C]PiB, and [<sup>11</sup>C]PBR28, and compared favorably to currently used MRI methods.
Generalizable Multi-Camera 3D Pedestrian Detection (2021)

We present a multi-camera 3D pedestrian detection method that does not need to train using data from the target scene. We estimate pedestrian location on the ground plane using a novel heuristic based on human body poses and person’s bounding boxes from an off-the-shelf monocular detector. We then project these locations onto the world ground plane and fuse them with a new formulation of a clique cover problem. We also propose an optional step for exploiting pedestrian appearance during fusion by using a domain-generalizable person re-identification model. We evaluated the proposed approach on the challenging WILDTRACK dataset. It obtained a MODA of 0.569 and an F-score of 0.78, superior to state-of-the-art generalizable detection techniques.
Gap Junction Communication between Autologous Endothelial and Tumor Cells Induce Cross-Recognition and Elimination by Specific CTL (2009)

Cellular interactions in the tumor stroma play a major role in cancer progression but can also induce tumor rejection. To explore the role of endothelial cells in these interactions, we used an in vitro three-dimensional collagen matrix model containing a cytotoxic T lymphocyte CTL clone (M4.48), autologous tumor cells (M4T), and an endothelial cell (M4E) line that are all derived from the same tumor. We demonstrate in this study that specific killing of the endothelial cells by the CTL clone required the autologous tumor cells and involved Ag cross-presentation. The formation of gap junctions between endothelial and tumor cells is required for antigenic peptide transfer to endothelial cells that are then recognized and eliminated by CTL. Our results indicate that gap junctions facilitate an effective CTL-mediated destruction of endothelial cells from the tumor microenvironment that may contribute to the control of tumor progression.
Robust object detection using marginal space learning and ranking-based multi-detector aggregation: Application to left ventricle detection in 2D MRI images (2009)

Magnetic resonance imaging (MRI) is currently the gold standard for left ventricle (LV) quantification. Detection of the LV in an MRI image is a prerequisite for functional measurement. However, due to the large variations in the orientation, size, shape, and image intensity of the LV, automatic LV detection is challenging. In this paper, we propose to use marginal space learning (MSL) to exploit the recent advances in learning discriminative classifiers. Unlike full space learning (FSL) where a monolithic classifier is trained directly in the five dimensional object pose space (two for position, one for rotation, and two for anisotropic scaling), we train three detectors, namely, the position detector, the position-orientation detector, and the position-orientation-scale detector. As a contribution of this paper, we perform thorough comparison between MSL and FSL. Experiments show MSL significantly outperforms FSL on both the training and test sets. Additionally, we also detect several LV landmarks, such as the LV apex and two annulus points. If we combine the detected candidates from both the whole-object detector and landmark detectors, we can further improve the system robustness even when one detector fails. A novel ranking-based strategy is proposed to combine the detected candidates from all detectors. Experiments show our ranking-based aggregation approach can significantly reduce the detection outliers.
INTERACTION OF SILVER IONS WITH SULPHIDE MINERALS WITH SPECIAL EMPHASIS ON THE CHALCOPYRITE/PYRITE GALVANIC COUPLE (2008)

Short and long term immersion tests were performed using different massive mineral sulphide specimens of museum grade and quartz of analytical grade in an acid medium containing silver ions. After attack, the sample surfaces were observed by SEM and products characterized by EDS. Parallel, massive specimens of pyrite (FeS2) and chalcopyrite (CuFeS2) were embedded in an epoxy resin, either electrically isolated or in electrical contact and treated with solution containing silver ions in the presence of bacteria. Finally, massive chalcopyrite and pyrite electrodes were subjected to electrochemical measurements in an acid medium under different experimental conditions (addition of silver ions and inoculation). Silver deposition took place preferentially on specific mineral surfaces: chalcopyrite, galena, covellite and chalcocite. Conversely, the chemical reaction of silver ions with pyrite and sphalerite was negligible. In a mixture of chalcopyrite and pyrite, silver was deposited on the former surface creating new cathodic sites which accelerated the electrochemical reactions of chalcopyrite dissolution.On a effectué des essais d’immersion à court et à long terme en utilisant différents spécimens de minéral de sulfure massif de qualité musée et du quartz de qualité analytique en milieu acide contenant des ions d’argent. Après l’attaque, on a observé la surface des échantillons au SEM et l’on a caractérisé les produits par EDS. On a incorporé en parallèle dans une résine époxy les spécimens massifs de pyrite (FeS2) et de chalcopyrite (CuFeS2), soit électriquement isolés ou en contact électrique et on les a traités avec une solution contenant des ions d’argent en présence de bactéries. Finalement, on a soumis les électrodes massives de chalcopyrite et de pyrite à des mesures électrochimiques dans un milieu acide sous différentes conditions expérimentales (addition d’ions d’argent et inoculation). Le dépôt d’argent a pris place préférentiellement sur des surfaces minérales spécifiques: chalcopyrite, galène, covelline et chalcosine. Inversement, la réaction chimique des ions d’argent avec la pyrite et la fausse galène était négligeable. Dans un mélange de chalcopyrite et de pyrite, l’argent était déposé sur la première surface, créant de nouveaux sites cathodiques qui accéléraient les réactions électrochimiques de dissolution de la chalcopyrite.
Highly unidirectional InAs∕InGaAs∕GaAs quantum-dot ring lasers (2005)

We report fabrication and characterization of semiconductor ring lasers with quantum-dot active region. The InAs∕InGaAs∕GaAs “dots-in-a-well” ridge-waveguide ring lasers are monolithically integrated with coupling waveguides and monitoring quantum-dot photodetectors. The lowest threshold current density for semiconductor ring lasers is demonstrated. When enhanced by a forward biased S-section waveguide, stable unidirectional operation with record suppression ratio of counterpropagating waves exceeding 30dB is achieved.
Supplementary Data from Diffusion-Weighted Magnetic Resonance Imaging for Predicting and Detecting Early Response to Chemoradiation Therapy of Squamous Cell Carcinomas of the Head and Neck (2023)

Supplementary Data from Diffusion-Weighted Magnetic Resonance Imaging for Predicting and Detecting Early Response to Chemoradiation Therapy of Squamous Cell Carcinomas of the Head and Neck
ChemInform Abstract: Mechanistic Aspects of the Photooxidation of Water at the n‐TiO2/Aqueous Interface: Optically Induced Transients as a Kinetic Probe. (1989)

Abstract It is demonstrated that the method of optically induced photocurrent transients is a powerful tool for the study of the mechanisms of photoinduced charge transfer at the semiconductor/electrolyte interface.
CCDC 201211: Experimental Crystal Structure Determination (2004)

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Critical Undercooling in DNA-Mediated Nanoparticle Crystallization* (2020)

The nucleation of DNA-functionalized nanoparticle superlattices is observed to exhibit a temperature hysteresis between melting and freezing transitions that allows for the study of nucleation thermodynamics. This chapter shows that the undercooling required to initiate nucleation increases as the nanoparticle coordination number increases. It elucidates the role of kinetic effects on the undercooling of programmable atom equivalent (PAE) with different size, shape, and DNA sequence and shows that heterogeneous nucleation can be turned on or off through introduction of DNA-modified surfaces. Valency-specific interactions are hypothesized in some accounts to impose a steric restriction that limits the frequency of protein collisions with the appropriate orientation for crystallization to occur, and thus a kinetically dominated undercooling would increase with decreased coordination number. The conceptual framework introduced to describe PAE nucleation positions systematic melting and freezing experiments as powerful tools to understand and therefore better control PAE crystallization behavior.
Molekulare Signaturen im Blut von Patienten mit Bronchialkarzinomen (2009)

Das Ziel der vorliegenden Arbeit war, die Etablierung komplexer Autoantikörper- und miRNA-Expressionsprofile in peripherem Blut.\nMit Hilfe der Analyse von über 1800 Autoantigenen wurde die Genauigkeit für verschiedene vergleichende Klassifikationen bestimmt. Lungentumorpatienten konnten von gesunden Probanden mit einer Genauigkeit von 98% getrennt werden. Patienten mit niedrig-gradigen Lungentumoren wurden mit einer Genauigkeit von 93,41% von Gesunden getrennt. Eine Trennung von Patienten mit NSCLC bzw. SCLC von Gesunden erzielte Genauigkeiten über 95%. Die Trennung der Lungentumorpatienten von Patienten mit COPD erreichte eine Genauigkeit von 76,75%. COPD-Patienten wurden von Gesunden mit 97,60% Genauigkeit getrennt. Entsprechende Unterscheidungen bei diesen Erkrankungen waren mit anderen Biomarkern bisher nicht mit vergleichbaren Ergebnissen möglich.\nDurch die Expressionsanalyse von über 800 miRNAs konnten Lungentumorpatienten mit einer Genauigkeit von 95,4% von Gesunden unterschieden werden. Insgesamt wurden in Blutzellen von Lungentumorpatienten 27 signifikant deregulierte miRNAs identifiziert. Mit vorliegender Studie konnten erstmals solide Tumoren anhand eines miRNA-Expressionsprofils in Blutzellen klassifiziert werden.\nIn vorliegender Arbeit konnten komplexe Autoantikörper- und miRNA-Expressionsprofile in peripherem Blut von Lungentumorpatienten etabliert werden. Mit diesen Profilen wurden vergleichende Klassifikationen mit hoher Genauigkeit erreicht.
ChemInform Abstract: Enantioselective Alkylation of Aldehydes with Diethylzinc Using a New Catalyst System, ((R)‐Thiolan‐2‐yl)diphenylmethanol and Metal Alkoxides. (2002)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatial-Temporal Graph Convolutional Network for Action Recognition (2019)

This paper extends the Spatial-Temporal Graph Convolutional Network (ST-GCN) for skeleton-based action recognition by introducing two novel modules, namely, the Graph Vertex Feature Encoder (GVFE) and the Dilated Hierarchical Temporal Convolutional Network (DH-TCN). On the one hand, the GVFE module learns appropriate vertex features for action recognition by encoding raw skeleton data into a new feature space. On the other hand, the DH-TCN module is capable of capturing both short-term and long-term temporal dependencies using a hierarchical dilated convolutional network. Experiments have been conducted on the challenging NTU RGB-D-60 and NTU RGB-D 120 datasets. The obtained results show that our method competes with state-of-the-art approaches while using a smaller number of layers and parameters; thus reducing the required training time and memory.
Non-Dimensional Finite Element Formulation for Thermal Problems (2012)

The use of dimensional analysis and dimensionless parameters is very common in the field of heat transfer; nevertheless the concept of non-dimensional finite element formulation has been applied to a limited type of thermo-fluid problems. The non-dimensional finite element method should provide the dimensionless solution for a given problem. The aim of present work is to develop a non-dimensional thermal finite element for getting dimensionless solution of the problems that do not have a closed form solution. An example is a fin (or extended surface) design. Fin efficiency is a performance characteristic that can be used as design criterion; thus closed form dimensionless solutions for fin efficiency are available in the literature. The results are for different geometry, single material fins. In case, if the fin problem has some geometric and/or material complexities then closed form solutions are not available and finite element approach can be used. However, the obtained finite element solution would not be in dimensionless form. For example, no closed form solutions are available for variable thickness composite fins (i.e. a fin having a base material with a coating over its surface), and the literature shows that finite element solution has been used to study thermal performance of the variable thickness composite fins. Therefore, non-dimensional finite element approach can be applied to directly obtain the dimensionless solution for the problem. The current work consists of presenting a non-dimensional finite element formulation for thermal problems. The element formulation is first validated by solving a test case study that has known closed form solution. The objective is to demonstrate the usefulness of the non-dimensional finite element approach by obtaining dimensionless finite element solutions for some applied problems that do not have a closed form solution.
Development of nanoelectrospray high resolution isotope dilution mass spectrometry for targeted quantitative analysis of urinary metabolites: application to population profiling and clinical studies (2015)

An automated nESI-HRMS method for targeted quantitative analysis and global metabolic profiling of urine samples.
Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso (2019)

We consider estimation of a functional parameter of a realistically modeled data distribution based on observing independent and identically distributed observations. We define an $m$-th order Spline Highly Adaptive Lasso Minimum Loss Estimator (Spline HAL-MLE) of a functional parameter that is defined by minimizing the empirical risk function over an $m$-th order smoothness class of functions. We show that this $m$-th order smoothness class consists of all functions that can be represented as an infinitesimal linear combination of tensor products of $\leq m$-th order spline-basis functions, and involves assuming $m$-derivatives in each coordinate. By selecting $m$ with cross-validation we obtain a Spline-HAL-MLE that is able to adapt to the underlying unknown smoothness of the true function, while guaranteeing a rate of convergence faster than $n^{-1/4}$, as long as the true function is cadlag (right-continuous with left-hand limits) and has finite sectional variation norm. The $m=0$-smoothness class consists of all cadlag functions with finite sectional variation norm and corresponds with the original HAL-MLE defined in van der Laan (2015). In this article we establish that this Spline-HAL-MLE yields an asymptotically efficient estimator of any smooth feature of the functional parameter under an easily verifiable global undersmoothing condition. A sufficient condition for the latter condition is that the minimum of the empirical mean of the selected basis functions is smaller than a constant times $n^{-1/2}$, which is not parameter specific and enforces the selection of the $L_1$-norm in the lasso to be large enough to include sparsely supported basis. We demonstrate our general result for the $m=0$-HAL-MLE of the average treatment effect and of the integral of the square of the data density. We also present simulations for these two examples confirming the theory.