gebhart/patrepeval huggingface dataset:
Modeling the induction machine's main inductance as a function of the magnetizing and the torque building component of the stator current (2008)

According to earlier work and papers by other authors, the main flux path of an induction machine is not only saturated due to the magnetizing current or, in other words, ldquothe magnetizing inductance can be modeled as a function of torquerdquo. In the paper a method is proposed to extend the induction machine's standard fundamental wave model taking into consideration the changes of the main inductance in dependence of the magnetizing and the torque building component of the stator current. Furthermore, a method is presented to estimate the required parameters from measurements carried out during normal operation of the induction machine. Validation is achieved via FEM calculations and additional measurements.
Fine Epitope Mapping of the CD19 Extracellular Domain Promotes Design (2019)

The B-cell surface protein CD19 is present throughout the cell life cycle and is uniformly expressed in leukemias, making it a target for chimeric antigen receptor engineered immune cell therapy. Identifying the sequence dependence of the binding of CD19 to antibodies empowers fundamental study and more tailored development of CD19-targeted therapeutics. To identify the antibody-binding epitopes on CD19, we screened a comprehensive single-site saturation mutation library of the human CD19 extracellular domain to identify mutations detrimental to binding FMC63-the dominant CD19 antibody used in chimeric antigen receptor development-as well as 4G7-2E3 and 3B10, which have been used in various types of CD19 research and development. All three antibodies had partially overlapping, yet distinct, epitopes near the published epitope of antibody B43. The FMC63 conformational epitope spans spatially adjacent, but genetically distant, loops in exons 3 and 4. The 3B10 epitope is a linear peptide sequence that binds CD19 with 440 pM affinity. Along with their primary goal of epitope mapping, the mutational tolerance data also empowered additional CD19 variant design and analysis. A designed CD19 variant with all N-linked glycosylation sites removed successfully bound antibody in the yeast display context, which provides a lead for aglycosylated applications. Screening for thermally stable variants identified mutations to guide further CD19 stabilization for fusion protein applications and revealed evolutionary affinity-stability trade-offs. These fundamental insights into CD19 sequence-function relationships enhance our understanding of antibody-mediated CD19-targeted therapeutics.
Fetal Brain Tissue Annotation and Segmentation Challenge Results (2022)

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, brainstem, deep grey matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero.
ChemInform Abstract: Transition‐Metal Coordination Chemistry of Sulfoxides (1993)

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.
Analysis of High-Throughput Sequencing and Annotation Strategies for Phage Genomes (2010)

These DNA preparation, sequencing and annotation strategies enable a high-throughput approach to the burgeoning field of phage genomics.
Deep Learning for the Automation of Particle Analysis in Catalyst Layers for Polymer Electrolyte Fuel Cells (2021)

The rapidly growing use of imaging infrastructure in the energy materials domain drives significant data accumulation in terms of their amount and complexity. The applications of routine techniques for image processing in materials research are often \textit{ad hoc}, indiscriminate, and empirical, which renders the crucial task of obtaining reliable metrics for quantifications obscure. Moreover, these techniques are expensive, slow, and often involve several preprocessing steps. This paper presents a novel deep learning-based approach for the high-throughput analysis of the particle size distributions from transmission electron microscopy (TEM) images of carbon-supported catalysts for polymer electrolyte fuel cells. Our approach employs training an instance segmentation model, called StarDist [Schmidt et al. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2018, Lecture Notes in Computer Science, vol 11071. Springer, Cham], which resolves the main challenge in the pixel-wise localization of nanoparticles in TEM images: the overlapping particles. The segmentation maps outperform models reported in the literature, and the results on particle size analyses agree well with manual particle size measurements, albeit at a significantly lower cost.
Computing 3D Geometry Directly from Range Images (2001)

Several techniques have been developed in research and industry for computing 3D geometry from sets of aligned range images [1]. Recent work has shown that volumetric methods are robust to scanner noise and alignment uncertainty and provide good quality, water-tight models [2,3,4]. However, these methods suffer from limited
Control of Oxygen for Thermal Management of Diesel Particulate Filters (2002)

&lt;div class="htmlview paragraph"&gt;A control strategy is presented to limit the rate of heat release by Diesel Particulate Filters (DPF) during regeneration reactions between oxygen and the collected soot. Heat release is managed by limiting the oxygen supplied to the DPF, which limits the rate of the regeneration reaction. Three actuators are used to control the amount of oxygen flowing in the exhaust system: an exhaust gas re-circulation (EGR) valve, an intake throttle (ITH), and a hydrocarbon injector located upstream of the DPF in the exhaust system. The EGR valve and ITH are low-bandwidth actuators that control slowly varying changes in oxygen flow, while the hydrocarbon injector is a high-bandwidth actuator that controls the corresponding fast changes in oxygen flow.&lt;/div&gt;
Profiting from IoT: the key is very-large-scale happiness integration (2015)

Big data without link to value is merely a cost. We have studied how to profit from data with Internet-of-Things technologies for over 10 years to reach the answer: the Wearable Happiness Meter. It allows us to integrate the measure of both wellbeing and productivity of 7-billion people worldwide, which was the dream of the 18th-century philosopher Jeremy Bentham, numeration of the greatest happiness of the greatest number to measure the right and wrong. Knowing right and wrong with the 10x speed over conventional financial feedback accelerates the growth of the enterprise, the economy, and the individual to maximize the worldwide happiness. Here the integration is not only on a chip, but in the distributed massive chips embedded in the society.
The Effect of Oxidant Species on Pitting Corrosion and SCC Behavior in NaCl Solution (1984)

The effects of K2Cr207, KC103, Fe2(SO4)3 and dissolved oxygen in NaCl solutionon pitting corrosion and SCC behavior of SUS 304 stainless steel were investigated by measuring polarization curves and the slow strain rate technique. As the result, the effect of K2Cr207 and KC103 as pitting, inhibitor was confirmed on stainless steel without stress and the effect as passivator was increased under the stressed condition of tensile, and they increased the resistance to SCC of stainless steel. Fe2(SO4)3 and dissolved oxygen decreased the resistance to SCC because the electrode potential of stainless steel was shifted to the noble direction by the addition of Fe2(SO4)3 and crevice corrosion was accelerated by the difference of dissolved oxygen concentration between crevice and open surface of stainless steel. The resistance to SCC of the specimens with and without creviced surface was examined and it was clarified that the crevice had a very important role in SCC.
Imaging of Peripheral Benzodiazepine Receptor Expression as Biomarkers of Detrimental versus Beneficial Glial Responses in Mouse Models of Alzheimer's and Other CNS Pathologies (2008)

We demonstrate the significance of peripheral benzodiazepine receptor (PBR) imaging in living mouse models of Alzheimer's disease (AD) as biomarkers and functional signatures of glial activation. By radiochemically and immunohistochemically analyzing murine models of the two pathological hallmarks of AD, we found that AD-like Abeta deposition is concurrent with astrocyte-dominant PBR expression, in striking contrast with nonastroglial PBR upregulation in accumulations of AD-like phosphorylated tau. Because tau-induced massive neuronal loss was distinct from the marginal neurodegeneration associated with Abeta plaques in these models, cellular localization of PBR reflected deleterious and beneficial glial reactions to tau versus Abeta pathologies, respectively. This notion was subsequently examined in models of various non-AD neuropathologies, revealing the following reactive glial dynamics underlying differential PBR upregulation: (1) PBR(-) astrogliosis uncoupled with microgliosis or coupled with PBR(+) microgliosis associated with irreversible neuronal insults; and (2) PBR(+) astrogliosis coupled with PBR(- or +/-) microgliosis associated with minimal or reversible neuronal toxicity. Intracranial transplantation of microglia also indicated that nontoxic microglia drives astroglial PBR expression. Moreover, levels of glial cell line-derived neurotrophic factor (GDNF) in astrocytes were correlated with astroglial PBR, except for increased GDNF in PBR(-) astrocytes in the model of AD-like tau pathology, thereby suggesting that PBR upregulation in astrocytes is an indicator of neurotrophic support. Together, PBR expressions in astrocytes and microglia reflect beneficial and deleterious glial reactions, respectively, in diverse neurodegenerative disorders including AD, pointing to new applications of PBR imaging for monitoring the impact of gliosis on the pathogenesis and treatment of AD.
Vision Based Navigation (2003)

We present a method for inferring the location of a robot relative to a three-dimensional map of its environment. The map, created off-line, consists of image patches, their locations in space, and their associated normal vectors. Observational data consist of one or many images taken from the robotâÂ¡Ãs current viewpoint (a point and orientation in space). We develop a framework for matching images of a scene (observations) to a map and show how this can be applied to the task of robot localization. Localization is posed as an optimization problem, where the observed data and the map are aligned to produce an estimate of the current pose of the robot. We provide a formalization of our model and demonstrate experimental results in unstructured environments.
Formation-Tester Pulse Testing in Tight Formations (Shales and Heavy Oil): Where Wellbore Storage Effects Favor the Determination of Reservoir Pressure (2012)

Abstract Tight formation testing when mobilities are lower than 0.01 mD/cP poses significant challenges because the conventional pressure transient buildup testing becomes impractical as a result of the large buildup stabilization time. This paper introduces a new automated pulse test method for testing in tight formations that significantly reduces testing time and makes the determination of formation pressure and permeability possible. A pulse test is defined as a drawdown followed by an injection test, and the source is shut in to record the pressure transient. Based on pressure data during the shut-in period, the next drawdown or injection test is designed, such that the flow rate is a fraction of the initial pulse rate, followed by another shut-in test. This procedure continues until the difference in pressure at the beginning and at the end of the shut-in period is reduced to within a specified limit of pressure change; then, an extended transient is recorded to a stabilized shut-in pressure. The overall advantage is to reduce the pressure stabilization time by implementing an adaptive pressure feedback loop in the system. The method can be applied to a straddle packer test using conventional drillstem testing tools or formation testers, using either straddle packers or probes. The effects of wellbore storage and fluid compressibility are found to reduce the pressure drop and positive pressure pulse in the drawdown and injection tests, respectively; they also affect the decay rate to the asymptote of the shut-in pressure response. Consequently, the combined pulse test method with the pressure feedback system and wellbore storage effect reduces the reservoir pressure testing time in tight formations. The automated pulse-test method has been successfully validated with consideration of the effects of wellbore storage and overbalance pressure in tight gas and heavy oil formations. In addition, the effects of invasion with water- and oil-based mud filtrate were considered in the modeling. The method uses successive pressure feedbacks and automated pulses to yield a pressure to within 0.5% range of the initial reservoir pressure while decreasing the wait time by a factor of 10 for a packer type formation tester. To account for various tool options and storage effects, the packer-type, oval probe, and standard probe-type formation testers have been simulated in various tight formation conditions. The method enables a rapid appraisal of pressure measurements in comparison to conventional testing. Simulations also indicate that the analytical spherical model can be used to analyze a pulse test, even when encountering multi-phase compositional fluid effects.
In Vivo and In Vitro Evaluation of Bilirubin Removal in Postoperative Hyperbilirubinemia Patients (1995)

The effect of plasma adsorption (PA) on bilirubin removal by a porous type anion exchange resin (Medisorba BL, Kuraray) was evaluated in vitro PA and in vivo PA and plasma exchange (PE) in postoperative hyperbilirubinemia patients. Serum and plasma bilirubin were measured by routine biochemical tests, fractionated by high-performance liquid chromatography, and its reduction and rebound were compared. In vitro and in vivo PA indicated the selectivity in bilirubin removal against measured molecules. Changes in bilirubin fractions after PA showed higher adsorbance of conjugated bilirubin (21.4-30.8%) and less adsorbance of delta (85.7%) and unconjugated bilirubin (73.7%). These differences were not observed after PE. But rebound of serum total bilirubin levels after PA was more than that after PE. It is suggested that PA by the resin is selective and has a different metabolic effect on bilirubin during and after PA as compared with PE.
DeepComBat: A Statistically Motivated, Hyperparameter-Robust, Deep Learning Approach to Harmonization of Neuroimaging Data (2023)

Neuroimaging data from multiple batches (i.e. acquisition sites, scanner manufacturer, datasets, etc.) are increasingly necessary to gain new insights into the human brain. However, multi-batch data, as well as extracted radiomic features, exhibit pronounced technical artifacts across batches. These batch effects introduce confounding into the data and can obscure biological effects of interest, decreasing the generalizability and reproducibility of findings. This is especially true when multi-batch data is used alongside complex downstream analysis models, such as machine learning methods. Image harmonization methods seeking to remove these batch effects are important for mitigating these issues; however, significant multivariate batch effects remain in the data following harmonization by current state-of-the-art statistical and deep learning methods. We present DeepCombat, a deep learning harmonization method based on a conditional variational autoencoder architecture and the ComBat harmonization model. DeepCombat learns and removes subject-level batch effects by accounting for the multivariate relationships between features. Additionally, DeepComBat relaxes a number of strong assumptions commonly made by previous deep learning harmonization methods and is empirically robust across a wide range of hyperparameter choices. We apply this method to neuroimaging data from a large cognitive-aging cohort and find that DeepCombat outperforms existing methods, as assessed by a battery of machine learning methods, in removing scanner effects from cortical thickness measurements while preserving biological heterogeneity. Additionally, DeepComBat provides a new perspective for statistically-motivated deep learning harmonization methods.
TRF2 and VEGF-A: an unknown relationship with prognostic impact on survival of colorectal cancer patients (2020)

Our results permitted to identify the positive correlation between high levels of TRF2 and VEGF-A as a novel prognostic biomarker for identifying the subset of high-risk colorectal cancer patients that could benefit of specific therapeutic regimens.
Sequencing and annotation of the Wolbachia endosymbiont of Diaphorina citri by the CG-HLB Genome Resources group reveals candidate sources of interaction with the insect host (2014)

The Citrus Greening – Huanglongbing (CG-HLB) Genome Resources group serves as a bioinformatics resource for diverse projects related to the biology of CG-HLB.&nbsp; A major recent project concerns the generation and annotation of a draft genome sequence for the Wolbachia endosymbiont (wDi) of the Asian citrus psyllid, of particular interest given the potential for control of psyllid behavior through manipulation of its bacterial endosymbionts.&nbsp;&nbsp; The Wolbachia draft genome was assembled and contigs aligned using the wPip strain from mosquito, its closest relative among completed Wolbachia genome sequences.&nbsp; OrthoMCL analysis of the annotated draft genome sequence confirmed the presence of 670 genes common to all sequenced Wolbachia genomes. Candidate host interaction factors include 54 predicted ankyrin proteins hypothesized to play a role in host reproductive manipulation, a Type IV secretion system linked to ankyrin protein export, and a bacterioferritin linked to host iron homeostasis.&nbsp; Several metabolic capabilities were identified in wDi that are absent from Liberibacter. FtsZ and Wsp phylogenies indicate that the Wolbachia strain in the Florida D. citri isolate falls into a sub-clade of supergroup B, distinct from Wolbachia present in Chinese D. citri isolates, supporting the hypothesis that the D. citri introduced into Florida did not originate from China. The Wolbachia sequence and annotation can be viewed on the CG-HLB Genome Resources Website (http://citrusgreening.org/), together with the sequences of publically available Liberibacter genomes sequenced to date. Future plans involve development of a searchable Liberibacter diagnostic sequence database using the over 1700 publically available Ca. Liberibacter gene sequences.
Surface diffusion of hydrogen on carbon-covered Ru(001) surfaces studied using laser-induced thermal desorption (1987)

The effects of surface carbon on the surface diffusion of hydrogen on Ru(001) were studied using laser-induced thermal desorption techniques. The surface mobility of hydrogen decreased by approximately a factor of 60 as a function of increasing surface carbon coverage from θC=0 to θC=0.42 monolayer at T=300 K. The observed reduction of hydrogen surface mobility vs surface carbon coverage was consistent with the trapping of hydrogen atoms by carbide species on the Ru(001) surface. A simple trapping model suggests that the potential energy wells of the carbon trap sites are ΔE&amp;gt;2.4 kcal/mol deeper than regular hydrogen adsorption sites. This estimate is also consistent with the results of Monte Carlo simulations.
Análisis del sistema inboard performance system (ips): descripción, ayuda a la maniobra, instalación a bordo e implementación en el mercado (2019)

El sistema consiste en pequenos azipods instalados en embarcaciones de recreo, accionados por control remoto, con el fin de: facilitar la maniobra de estas embarcaciones (que no suelen estar tripuladas por personal profesional); optimizar la ejecucion de las ordenes de una maniobra, por medio de la integracion de todos los equipos; aumentar la eficiencia de los motores, proporcionando una mayor velocidad o un menor consumo, y aumentar la seguridad de la navegacion, que al igual que el aumento de la eficiencia de la maniobra, se consigue por medio de equipos integrados.
Data from NPM–ALK-Induced Reprogramming of Mature TCR-Stimulated T Cells Results in Dedifferentiation and Malignant Transformation (2023)

&lt;div&gt;Abstract&lt;p&gt;Fusion genes including NPM–ALK can promote T-cell transformation, but the signals required to drive a healthy T cell to become malignant remain undefined. In this study, we introduce NPM–ALK into primary human T cells and demonstrate induction of the epithelial-to-mesenchymal transition (EMT) program, attenuation of most T-cell effector programs, reemergence of an immature epigenomic profile, and dynamic regulation of c-Myc, E2F, and PI3K/mTOR signaling pathways early during transformation. A mutant of NPM–ALK failed to bind several signaling complexes including GRB2/SOS, SHC1, SHC4, and UBASH3B and was unable to transform T cells. Finally, T-cell receptor (TCR)–generated signals were required to achieve T-cell transformation, explaining how healthy individuals can harbor T cells with NPM–ALK translocations. These findings describe the fundamental mechanisms of NPM–ALK-mediated oncogenesis and may serve as a model to better understand factors that regulate tumor formation.&lt;/p&gt;Significance:&lt;p&gt;This investigation into malignant transformation of T cells uncovers a requirement for TCR triggering, elucidates integral signaling complexes nucleated by NPM–ALK, and delineates dynamic transcriptional changes as a T cell transforms.&lt;/p&gt;&lt;p&gt;&lt;i&gt;See related commentary by Spasevska and Myklebust, p. 3160&lt;/i&gt;&lt;/p&gt;&lt;/div&gt;