gebhart/patrepeval huggingface dataset:
Single-Step Purification of Sputum Extracellular vesicles from Cystic Fibrosis patients using aF4-MALS (2019)

Abstract Rationale Patients with cystic fibrosis (CF) present a large amount of respiratory damage caused in large part by chronic neutrophil influx into the lung. Neutrophils recruited to the lumen of the CF lung actively exocytose neutrophil elastase (NE) and other damaging molecules. Airway NE levels correlate strongly with disease severity in patients with CF. We previously showed that extracellular vesicles (EVs) from patients with other lung diseases carry NE and promote emphysema in a mouse model (Genschmer et al. 2019). Here, we hypothesized that airway NE also compartmentalizes within EVs in CF patients. Methods To avoid potential aggregation and purification biases, we gently sorted EVs from CF sputum samples using asymmetrical flow field flow fractionation (aF4). Sputum EV fractions were then subjected to analysis by multi-angle light scattering, nanoparticle tracking analysis and flow cytometry. Results Multi-angle light scattering and nanoparticle tracking analyses demonstrate the presence of EVs of different sizes ranging from 40–500 nm, with a concentration of ~5 × 107 EVs/mL. EVs were separated by size with aF4 and downstream flow cytometry analysis showed that discrete subfractions concentrate NE on their surface, but that NE burden was not proportional to size. Conclusions Our data show that there are discrete subtypes of EVs released by neutrophils carrying various amounts of NE on their surface. These findings provide evidence for a role of EVs in promoting inflammation in the lungs of patients with CF.
Impact of Strain Rate Dependent Viscosity on Damping Capacity of Electro- and Magnetorheological Dampers (2003)

Quasisteady modeling of linear stroke flow mode magnetorheological (MR) and electrorheological (ER) dampers has focused primarily on the utilization of the Bingham-plastic constitutive model to assess performance metrics such as damping capacity. In such Bingham-plastic MR (or ER) flows, the yield stress of the fluid, τy ,i sa ctivated by applying magnetic (or electric) field. The Bingham-plastic model assumes that the material is in either (1) a preyield condition where the local shear stress is less than the yield stress, τ τy ,s o that the material flows with a constant postyield viscosity. The objective of this paper is to analyze the damping capacity of such a controllable MR or ER damper in the situation when the field dependent fluid exhibits postyield shear thinning or thickening behavior, that is, the postyield viscosity is a function of shear rate. A Herschel-Bulkley model with a field dependent yield stress is proposed, and the impact of shear rate dependent viscosity on damping capacity is assessed. Key analysis results - velocity profile, shear stress profile, and damping coefficient - are presented in a nondimensional formulation that is consistent with prior results for the Bingham-plastic analysis. The nondimensional analysis formulated here clearly establishes the Bingham number as the independent variable for assessing flow mode damper performance.
Optical characterization of multi-component Au-colloid-DNA complexes (2006)

In this communication, we report on the results of experimental studies on the linking of Au colloids with different sizes (20, 50 and 80 nm in diameter) coupled by double-stranded DNA. Samples were characterized by optical transmission spectroscopy in the visible and near-infrared range and compared to transmission electron microscopy of the dried sample. The surface plasmon resonance of the Au particles coupled by DNA chains are recorded and compared with the spectra of isolated particles. In the cases of DNA chains functionalized with two thiol groups the spectra shows a broadening and a red shift of the surface plasmons which is a result of coupling the particles by this chains
Cow Milk Feeding Induces Antibodies to Insulin in Children – A Link Between Cow Milk and Insulin‐Dependent Diabetes Mellitus? (1998)

Exposure to cow milk (CM)-based formulas in early infancy has been associated with an increased risk of insulin-dependent diabetes mellitus (IDDM), but studies on the possible pathogenic mechanism(s) linking CM and IDDM are contradicting. We hypothesized that if CM formulas contained bovine insulin (BI), exposure to them could lead to immunization against insulin, which is the only known beta-cell-specific autoantigen in IDDM. We measured immunoglobulin G (IgG) antibodies by enzyme immunoassay (EIA) to BI and human insulin (HI) in children who received, during the first 9 months of life, either a formula containing whole CM proteins or a formula containing hydrolyzed casein (HC) peptides. BI was detectable by radioimmunoassay (RIA) and immunoblotting in the CM-based formula. At 6 months of age the children who received CM formula had higher levels of IgG antibodies to BI than children who received either HC formula or children who were exclusively breast-fed (median levels 0.480 versus 0.185, P = 0.04; and 0.480 versus 0.160, P = 0.04; respectively). Also, at 9 months of age, children in the CM group differed from the HC group (0.403 versus 0.230; P = 0.02). Antibodies to BI and HI showed a positive correlation and cross-reacted in inhibition studies. The high incidence of insulin-binding antibodies in young children with IDDM may be explained by oral immunization to BI present in CM. Exposure to BI, which differs from HI only by three amino acids, may break the tolerance to insulin.
Supplementary Methods from CRR9/CLPTM1L Regulates Cell Survival Signaling and Is Required for Ras Transformation and Lung Tumorigenesis (2023)

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How We Make DNA Origami (2017)

DNA origami has attracted substantial attention since its invention ten years ago, due to the seemingly infinite possibilities that it affords for creating customized nanoscale objects. Although the basic concept of DNA origami is easy to understand, using custom DNA origami in practical applications requires detailed know-how for designing and producing the particles with sufficient quality and for preparing them at appropriate concentrations with the necessary degree of purity in custom environments. Such know-how is not readily available for newcomers to the field, thus slowing down the rate at which new applications outside the field of DNA nanotechnology may emerge. To foster faster progress, we share in this article the experience in making and preparing DNA origami that we have accumulated over recent years. We discuss design solutions for creating advanced structural motifs including corners and various types of hinges that expand the design space for the more rigid multilayer DNA origami and provide guidelines for preventing undesired aggregation and on how to induce specific oligomerization of multiple DNA origami building blocks. In addition, we provide detailed protocols and discuss the expected results for five key methods that allow efficient and damage-free preparation of DNA origami. These methods are agarose-gel purification, filtration through molecular cut-off membranes, PEG precipitation, size-exclusion chromatography, and ultracentrifugation-based sedimentation. The guide for creating advanced design motifs and the detailed protocols with their experimental characterization that we describe here should lower the barrier for researchers to accomplish the full DNA origami production workflow.
<title>Optimal piecewise linear image coding</title> (1998)

Piecewise linear (PL) image coding proceeds in three steps: 1) a digital image is converted into a 1D-signal using a scanning procedure, for example by scanning lines in a zig- zag or Hilbert order. 2) The signal is approximated by the graph of a piecewise linear function, which consists of a finite number connected line segments. 3) Entropy encoding of the sequence of the segment end points. In this step differential coding can be used for one or both coordinate sequences of the end points. In this step differential coding can be used for one or both coordinate sequences of the end points. To ensure a desired approximation quality a constraint is imposed, e.g., on the root-mean-square error of the PL signal. In this paper we consider uniform approximation. Two problems are addressed: first, an optimal PL approximation in the sense of a minimal number of segments is to be obtained. Second, when entropy coding of the segments is used, how can one jointly optimize the variable length code and the PL approximation yielding a better or even minimal rate without violating the uniform error bound. The first problem is solved by dynamic programing, the second is approached by using Huffman coding and an annealing procedure in which the design of the Huffman tables and the dynamic programming is alternately iterated using a cost function that reflects the codework lengths of the current variable length code. This algorithm is guaranteed to converge to a minimum length code. We describe the algorithms, implementation issues, compare two different scanning procedures, the zig-zag line scan and the Hilbert scan, and report results for encoding various test images.
Distortion tolerant pattern recognition based on self-organizing feature extraction (1995)

A generic, modular, neural network-based feature extraction and pattern classification system is proposed for finding essentially two-dimensional objects or object parts from digital images in a distortion tolerant manner, The distortion tolerance is built up gradually by successive blocks in a pipeline architecture. The system consists of only feedforward neural networks, allowing efficient parallel implementation. The most time and data-consuming stage, learning the relevant features, is wholly unsupervised and can be made off-line. The consequent supervised stage where the object classes are learned is simple and fast. The feature extraction is based on distortion tolerant Gabor transformations, followed by minimum distortion clustering by multilayer self-organizing maps. Due to the unsupervised learning strategy, there is no need for preclassified training samples or other explicit selection for training patterns during the training, which allows a large amount of training material to be used at the early stages, A supervised, one-layer subspace network classifier on top of the feature extractor is used for object labeling. The system has been trained with natural images giving the relevant features, and human faces and their parts have been used as the object classes for testing. The current experiments indicate that the feature space has sufficient resolution power for a moderate number of classes with rather strong distortions.
Value based Architecture of a Suite of Management Tools (2016)

Abstract In order to improve the effectiveness of managers, it is imperative that managers need to be supported by information systems. Accordingly, it becomes necessary to design and implement management systems reflecting increasing maturity in interoperability, integration and usage processes so that they can help managers work together. The objective is to create the foundations for responsibility management within an organization by providing information technology based platforms to integrate and coordinate management processes and sharing information across all functional levels and management hierarchies. In this paper, the architecture of a suite of management tools that can aid managers in responsibility management is discussed.
Supplementary Methods and Figures 1-4 from Chimeric NKG2D–Modified T Cells Inhibit Systemic T-Cell Lymphoma Growth in a Manner Involving Multiple Cytokines and Cytotoxic Pathways (2023)

Supplementary Methods and Figures 1-4 from Chimeric NKG2D–Modified T Cells Inhibit Systemic T-Cell Lymphoma Growth in a Manner Involving Multiple Cytokines and Cytotoxic Pathways
A Prospective Study on Modulation of Immunosuppression for Epstein-Barr Virus Reactivation in Pediatric Patients Who Underwent Unrelated Hematopoietic Stem-Cell Transplantation (2010)

We conclude that PCR-guided modulation of IS may play a role in early intervention for EBV-PTLD and a prospective, randomized study is needed.
Direct Oxidation of Hydrocarbons in a Solid Oxide Fuel Cell: I. Methane Oxidation (1999)

The performance of Cu cermets as anodes for the direct oxidation of in solid oxide fuel cells was examined. Mixtures of Cu and yttria‐stabilized zirconia (YSZ) were found to give similar performance to Ni‐YSZ cermets when was used as the fuel, but did not deactivate in dry . While Cu‐YSZ was essentially inert to methane, the addition of ceria to the anode gave rise to reasonable power densities and stable operation over a period of at least 3 days. Proof of direct oxidation of came from chemical analysis of the products leaving the cell. The major carbon‐containing product was , with only traces of CO observed, and there was excellent agreement between the actual cell current and that predicted by the methane conversion. These results demonstrate that direct, electrocatalytic oxidation of dry methane is possible, with reasonable performance. © 1999 The Electrochemical Society. All rights reserved.
Fast Simultaneous Characterization of all Analog Phased Array Elements (2022)

Characterization of individual elements of a phased array involves determining not only the radiation pattern of each element and the response of the gain/phase control circuitry behind the element, but the interaction of each element with all of the other elements within the array. The obvious approach is to just turn off all but one element in order to test each element one at a time, but this is extremely time consuming and often does not work due to differences in behavior between the on and off states of individual elements. It will be shown in this paper how individual element performance can be extracted from the combined pattern of the array with all elements active using orthogonal coding applied to each element of the array through the onboard gain/phase control circuitry.
Low bandwidth decoder framework for H.264/AVC scalable extension (2010)

In the process of scalable video coding (SVC) decoding, large external memory bandwidth is required for SVC inter-layer prediction. In this paper, a low bandwidth decoder framework is proposed for SVC. Two main decoding schemes are developed to reduce the external memory bandwidth. Macroblock-level on-the-fly padding and on-line upsampling is proposed for SVC spatial scalability decoding. This scheme reduces 36% of decoding bandwidth and 34% of processing cycles. For SVC quality scalability, a layer-interleaving decoding scheme is proposed to eliminate all inter-layer prediction bandwidth which is 41-51% of decoding bandwidth. The corresponding hardware architectures of these two decoding schemes are also provided. This low bandwidth framework can save 33-52% of DRAM access power for SVC decoding.
Increased epithelial and serum expression of macrophage migration inhibitory factor (MIF) in gastric cancer: potential role of MIF in gastric carcinogenesis (2006)

Epithelial and serum MIF expression was progressively increased in H pylori induced gastritis, intestinal metaplasia, and gastric cancer, suggesting that MIF is involved in gastric carcinogenesis and may be a valuable biomarker for the early detection of gastric cancer.
Adding a reward increases the reinforcing value of fruit (2017)

Adolescents' snack choices could be altered by increasing the reinforcing value (RV) of healthy snacks compared with unhealthy snacks. This study assessed whether the RV of fruit increased by linking it to a reward and if this increased RV was comparable with the RV of unhealthy snacks alone. Moderation effects of sex, hunger, BMI z-scores and sensitivity to reward were also explored. The RV of snacks was assessed in a sample of 165 adolescents (15·1 (sd 1·5) years, 39·4 % boys and 17·4 % overweight) using a computerised food reinforcement task. Adolescents obtained points for snacks through mouse clicks (responses) following progressive ratio schedules of increasing response requirements. Participants were (computer) randomised to three experimental groups (1:1:1): fruit (n 53), fruit+reward (n 60) or unhealthy snacks (n 69). The RV was evaluated as total number of responses and breakpoint (schedule of terminating food reinforcement task). Multilevel regression analyses (total number of responses) and Cox's proportional hazard regression models (breakpoint) were used. The total number of responses made were not different between fruit+reward and fruit (b -473; 95 % CI -1152, 205, P=0·17) or unhealthy snacks (b410; 95 % CI -222, 1043, P=0·20). The breakpoint was slightly higher for fruit than fruit+reward (HR 1·34; 95 % CI 1·00, 1·79, P=0·050), whereas no difference between unhealthy snacks and fruit+reward (HR 0·86; 95 % CI 0·62, 1·18, P=0·34) was observed. No indication of moderation was found. Offering rewards slightly increases the RV of fruit and may be a promising strategy to increase healthy food choices. Future studies should however, explore if other rewards, could reach larger effect sizes.
Magneto-thermo-mechanical characterization of magnetostrictive composites (2001)

This paper describes magneto-thermo-mechanical characterization of magnetostrictive composites. The purpose of this study is to evaluate the behavior of magnetostrictive composites under combined magnetic, thermal and mechanical loading, and to determine fundamental properties used for design of actuator and sensor systems that incorporate these materials. Currently the composites are being used in sonar transducers. The magnetostrictive composite contains Terfenol-D (Tb<SUB>0.3</SUB>Dy<SUB>0.7</SUB>Fe<SUB>2</SUB>) particulate embedded into an epoxy binder. Composite form is used due to the relative brittleness and limited operational frequencies of monolithic Terfenol-D. Two different tests were performed both at room temperature and under thermal loading: 1) constant magnetic field with cyclically varying load around a bias load and 2) constant pre-load with varying magnetic field. Testing was performed on five different volume fraction composites, namely, 10%, 20%, 30%, 40% and 50%. Parameters that were evaluated include strain output, magnetic field, magnetization and elastic modulus. Results for the constant magnetic field tests indicate that modulus generally increases with increasing volume fraction and increasing magnetic field. However, for low fields, an initial dip is noticed in modulus (i.e. (Delta) E effect) attributed to domains becoming more mobile at lower magnetic field levels. Results also indicate an increase in modulus with decrease in temperature. Results for the constant load test indicate a strong dependence of strain output on applied pre-stress. Results indicate that max strain peaks at a certain value of the pre-stress and then decreases for increasing pre-stress. Results also indicate that strain output peaks between 0 degree(s)C and +10 degree(s)C and that strain generally increases with increasing volume fraction.
A rationale for the therapeutic action of aprotinin. (1979)

Aprotinin, a protease inhibitor, has been used in a wide variety of pathophysiological states thought to be associated with an increase in protease activity. Opinion differ with respect to the success of the therapy. This paper proposes a rationale for the therapeutic action of aprotinin based on biochemical and physiological evidence. In the kallikrein-kinin system, in addition to kallikrein, other serine-esterases such as trypsin, plasmin, etc. can generate kinin production. In certain disease states such as pancreatitis there is not only an increase in serine-protease activity but frequently these enzymes reach parts of the organism where they are not found in health. Thus in such circumstances increased production of kinins can result. The consequences of increased kinin generation are discussed in light of work indicating their role in metabolic and circulatory homeostasis. Aprotinin is specifically a serine-esterase inhibitor. It is suggested that perhaps the most important action of this compound is as an inhibitor of the kallikrein-kinin system. On this basis a therapeutic regime in various disease states for the use of aprotinin, which allows for control of kinin generation, is suggested.
Biobehavioral Changes Following Transition to Automated Insulin Delivery: A Large Real-life Database Analysis (2022)

Observed in real life of >19,000 individuals with type 1 diabetes, transitions from PLGS to AID resulted in improvement of all glycemic parameters, equivalent to improvements observed in randomized clinical trials, and reduced user-initiated boluses. However, glycemic and behavioral changes with AID use may differ greatly across different demographic and clinical groups.
ChemInform Abstract: Charge‐Transfer Complex Formation by Grinding Crystals of Donor and Acceptor (1996)

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.
Mobilizing materials to enable a fast energy transition: a conceptual framework (2023)

Limiting climate heating while meeting basic needs of all necessitates eliminating fossil carbon emissions. This paper discusses the dynamics of mobilizing materials required for large-scale deployment of renewable energy, which entail: 1) availability of resources in the environment and technosphere; 2) accessibility, which depends on resource quality and available technologies; 3) processability, which depends on energy availability, processing capacity, and environmental impacts on planetary boundaries; and 4) operability, which depends on social acceptance and geopolitical agreements. Also, materials can be mobilized through four routes: 1) increasing primary production; 2) diverting existing primary production; 3) repurposing existing in-use stocks; and 4) re-mining previous wastes and emissions. The interplay of these enabling factors determines the maximum possible rate of material mobilization and thus of the energy transition itself. This paper presents and discusses a framework to explore joint energy-material transformations, enabling to consider material aspects in transition modelling and guide technological developments.
Adaptive Bayesian Linear Regression for Automated Machine Learning (2019)

To solve a machine learning problem, one typically needs to perform data preprocessing, modeling, and hyperparameter tuning, which is known as model selection and hyperparameter optimization.The goal of automated machine learning (AutoML) is to design methods that can automatically perform model selection and hyperparameter optimization without human interventions for a given dataset. In this paper, we propose a meta-learning method that can search for a high-performance machine learning pipeline from the predefined set of candidate pipelines for supervised classification datasets in an efficient way by leveraging meta-data collected from previous experiments. More specifically, our method combines an adaptive Bayesian regression model with a neural network basis function and the acquisition function from Bayesian optimization. The adaptive Bayesian regression model is able to capture knowledge from previous meta-data and thus make predictions of the performances of machine learning pipelines on a new dataset. The acquisition function is then used to guide the search of possible pipelines based on the predictions.The experiments demonstrate that our approach can quickly identify high-performance pipelines for a range of test datasets and outperforms the baseline methods.