gebhart/patrepeval huggingface dataset:
Efficient and Accurate Quantification of Uncertainty for Multiphase Flow With the Probabilistic Collocation Method (2009)

Summary In this study, we explore an efficient and accurate method for uncertainty analysis of petroleum reservoir simulations. The essence of the approach is the combination of Karhunen-Loeve (KL) expansion and probabilistic collocation method. Monte Carlo (MC) simulation is the most common and straightforward approach for uncertainty quantification. It generates a large number of realizations of the underlying reservoir. Solving the multiple realizations leads to a large computational effort, especially for large-scale problems. We present an accurate and efficient alternative. In this approach, the underlying random fields, such as permeability and porosity are represented by the KL expansion and the resulting random fields (e.g., fluid saturations and pressures) or variables (e.g., hydrocarbon production) are expressed by the polynomial chaos expansions. The probabilistic collocation method (PCM) is used to determine the coefficients of the polynomial chaos expansions by solving for the fluid saturation and pressure fields via the original partial differential equations for selected sets of collocation points. This approach is nonintrusive because it results in independent deterministic differential equations, which, similar to the MC method, can be implemented with existing codes or simulators. However, the required number of simulations in the PCM is much less than that in the MC method. The approach is demonstrated with black-oil problems in heterogeneous reservoirs with the commercial Eclipse simulator. The accuracy, efficiency, and compatibility of this approach are compared against MC simulations. This study reveals that, while its computational efforts are greatly reduced compared to the MC method, the PCM is able to estimate accurately the statistical moments and probability density functions of the fluid saturations (and pressures) and the hydrocarbon production.
Strontium-Delivering Glasses with Enhanced Bioactivity: A New Biomaterial for Antiosteoporotic Applications? (2008)

Bioactive glasses exhibit great performances for bone tissue regeneration. In biological conditions, they spontaneously bond to bone tissues while actively stimulating bone growth. Crucial parameters for the material’s bioactivity are the kinetics of formation of the interfacial calcium phosphate layer at the glass surface, as well as the release of critical concentrations of ionic dissolution products capable of stimulating cellular responses. In this paper we report the remarkable bioactivity properties of strontium-delivering sol−gel-derived glasses in the SiO2−CaO−SrO system. The glasses were tested in vitro and the interface between the glass and the biological medium was chemically mapped using highly sensitive nuclear microprobes. We prove the ability of our materials to form a phosphocalcic layer at their periphery with increased kinetics of reaction. Our key result is the demonstration that Sr-doped glasses can deliver controlled doses of strontium toward the biological medium. That is the determinant for bone tissue regeneration, as far as strontium is known to positively act on bone remodeling. Sr-delivering glasses could further represent an alternative to the constraining oral administration of strontium in treatment of osteoporosis.
Protective and Arthritis‐Resolving Activity in Sera of Mice Infected with Borrelia burgdorferi (1997)

Transfer of immune serum from immunocompetent mice infected with B. burgdorferi protects mice against syringe challenge, and transfer of immune serum after infection is established induces arthritis resolution but does not clear infection or spirochetemia or resolve carditis. Immune serum had very-high-titer passive protective activity against syringe challenge but failed to protect mice against host-adapted spirochetes when they were challenged with infected tissue transplants. Mice were passively immunized at selected intervals relative to challenge inoculation with antisera to recombinant forms of an immunodominant region of flagellin, P39, and OspC (which are recognized by immune serum), but none provided protection or modified existing infection or disease. Results suggest that spirochetes within joints, but not in other tissues, are selectively vulnerable to immune serum and that immune serum appears to contain antibody against yet-to-be-identified antigens that may be selectively expressed in the context of joint tissue.
Rationalization of hydrogen production by bulk g-C<sub>3</sub>N<sub>4</sub>: an in-depth correlation between physico-chemical parameters and solar light photocatalysis (2018)

The aim of this work is the systematic study of the photocatalytic activity of bulk graphitic carbon nitride (g-C<sub>3</sub>N<sub>4</sub>) in relation with the physical-chemical, structural and optical properties of the semiconductor. Fourteen g-C<sub>3</sub>N<sub>4</sub> samples have been prepared by thermal condensation starting from three different precursor (melamine, dicyandiamide and urea) and exploring various temperatures (in the range 500-700 °C). The materials obtained have been deeply characterized by high resolution scanning electron microscopy, thermogravimetric analysis, X-ray diffraction, nitrogen adsorption measurements (BET method), X-ray photoelectron spectroscopy and diffuse reflectance spectroscopy. Each semiconductor, coupled with Pt co-catalyst, was tested for hydrogen gas production from aqueous triethanolamine as model sacrificial agent, under simulated solar light. The hydrogen evolution profiles turned out to be strictly dependent on precursor type and synthesis temperature, with the highest evolution rate observed for the samples series produced from urea (up to <i>ca.</i> 4400 μmol g<sup>-1</sup> h<sup>-1</sup>). The results, corroborated by the excellent inter-day precision of irradiation tests (RSD < 5%, <i>n</i> = 3) together with the good batch-to-batch reproducibility (RSD < 11%, <i>n</i> = 3), were critically discussed. Apart from the appealing production values obtained using the as-prepared materials, it was importantly pointed out that, besides crystallinity and visible light absorption, the photocatalytic behavior is definitely correlated to the surface area, which is dependent on the synthesis conditions, that is polymerization temperature and nature of g-C<sub>3</sub>N<sub>4</sub> precursor. Overall, this systematic investigation demonstrated that, contrary to the polymerization degree (sp<sup>2</sup>/sp<sup>3</sup> carbon ratio), surface area is the real determinant parameter for g-C<sub>3</sub>N<sub>4</sub> hydrogen evolution activity.
Probabilistic forecasting from ensemble prediction systems: Improving upon the best‐member method by using a different weight and dressing kernel for each member (2006)

Abstract Ensembles of meteorological forecasts can both provide more accurate long‐term forecasts and help assess the uncertainty of these forecasts. No single method has however emerged to obtain large numbers of equiprobable scenarios from such ensembles. A simple resampling scheme, the ‘best member’ method, has recently been proposed to this effect: individual members of an ensemble are ‘dressed’ with error patterns drawn from a database of past errors made by the ‘best’ member of the ensemble at each time step. It has been shown that the best‐member method can lead to both underdispersive and overdispersive ensembles. The error patterns can be rescaled so as to obtain ensembles which display the desired variance. However, this approach fails in cases where the undressed ensemble members are already overdispersive. Furthermore, we show in this paper that it can also lead to an overestimation of the probability of extreme events. We propose to overcome both difficulties by dressing and weighting each member differently, using a different error distribution for each order statistic of the ensemble. We show on a synthetic example and using an operational ensemble prediction system that this new method leads to improved probabilistic forecasts, when the undressed ensemble members are both underdispersive and overdispersive. Copyright © 2006 Royal Meteorological Society.
Minimizing Remote Accesses in MapReduce Clusters (2013)

MapReduce, in particular Hadoop, is a popular framework for the distributed processing of large datasets on clusters of relatively inexpensive servers. Although Hadoop clusters are highly scalable and ensure data availability in the face of server failures, their efficiency is poor. We study data placement as a potential source of inefficiency. Despite networking improvements that have narrowed the performance gap between map tasks that access local or remote data, we find that nodes servicing remote HDFS requests see significant slowdowns of collocated map tasks due to interference effects, whereas nodes making these requests do not experience proportionate slowdowns. To reduce remote accesses, and thus avoid their destructive performance interference, we investigate an intelligent data placement policy we call 'partitioned data placement'. We find that, in an unconstrained cluster where a job's map tasks may be scheduled dynamically on any node over time, Hadoop's default random data placement is effective in avoiding remote accesses. However, when task placement is restricted by long-running jobs or other reservations, partitioned data placement substantially reduces remote access rates (e.g., by as much as 86% over random placement for a job allocated only one-third of a cluster).
Poly(2,6-dimethyl-1,4-phenylene oxide)-<i>b</i>-poly(vinylbenzyltrimethylammonium) Diblock Copolymers for Highly Conductive Anion Exchange Membranes (2015)

Diblock copolymer membranes of poly(2,6-dimethyl-1,4-phenylene oxide)-b-poly(vinylbenzyltrimethylammonium) (PPO-b-PVBTMA) were prepared as anion exchange membranes. The membranes were produced by growing poly(vinylbenzyl chloride) (PVBC) blocks from a PPO macroinitiator using nitroxide-mediated polymerization to make PPO-b-PVBC copolymers with varying PVBC content, then melt pressing into films, and subsequently reacting with trimethylamine. Phase separation was indicated for the PPO-b-PVBC polymers based on the evidence of two Tgs from differential scanning calorimetry measurements. The melt-processing conditions to form films produced lightly cross-linked materials. The conversion to PPO-b-PVBTMA membranes by reaction with trimethylamine led to materials with varying ion exchange capacities based on the amount of PVBC in the precursor. The water uptake, the dimensional changes with hydration, and the ionic conductivities in the hydroxide and bicarbonate forms were determined. The water uptake was suppressed by the light cross-linking in the hydrophilic PVBTMA component, allowing the films to remain insoluble in aqueous solutions at high IEC values. Membranes with IECs up to 2.9 mequiv/g were flexible under dry and hydrated conditions and showed hydroxide conductivity of 132 ± 3.8 mS/cm at 60 °C.
The Differential Clinical Impact of Human Coronavirus Species in Children With Cystic Fibrosis (2012)

We investigated the clinical impact of human coronaviruses (HCoV) OC43, 229E, HKU1 and NL63 in pediatric patients with cystic fibrosis (CF) during routine and exacerbation visits. A total of 408 nasopharyngeal aspirate samples were obtained from 103 patients over a 1-year period. Samples positive for HCoV were submitted for nucleotide sequencing to determine the species. Nineteen samples (4.65%) were positive for HCoV, of which 8 were positive for NL63, 6 for OC43, 4 for HKU1, and 1 for 229E. Identification of HCoV was not associated with an increased rate of respiratory exacerbations, but NL63-positive patients had higher exacerbation rates than patients who were positive for other HCoV species.
Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features (2017)

<b>Purpose:</b> The purpose of this study is classifying multiple sclerosis (MS) patients in the four clinical forms as defined by the McDonald criteria using machine learning algorithms trained on clinical data combined with lesion loads and magnetic resonance metabolic features. <b>Materials and Methods:</b> Eighty-seven MS patients [12 Clinically Isolated Syndrome (CIS), 30 Relapse Remitting (RR), 17 Primary Progressive (PP), and 28 Secondary Progressive (SP)] and 18 healthy controls were included in this study. Longitudinal data available for each MS patient included clinical (e.g., age, disease duration, Expanded Disability Status Scale), conventional magnetic resonance imaging and spectroscopic imaging. We extract <i>N</i>-acetyl-aspartate (NAA), Choline (Cho), and Creatine (Cre) concentrations, and we compute three features for each spectroscopic grid by averaging metabolite ratios (NAA/Cho, NAA/Cre, Cho/Cre) over good quality voxels. We built linear mixed-effects models to test for statistically significant differences between MS forms. We test nine binary classification tasks on clinical data, lesion loads, and metabolic features, using a leave-one-patient-out cross-validation method based on 100 random patient-based bootstrap selections. We compute F1-scores and BAR values after tuning Linear Discriminant Analysis (LDA), Support Vector Machines with gaussian kernel (SVM-rbf), and Random Forests. <b>Results:</b> Statistically significant differences were found between the disease starting points of each MS form using four different response variables: Lesion Load, NAA/Cre, NAA/Cho, and Cho/Cre ratios. Training SVM-rbf on clinical and lesion loads yields F1-scores of 71-72% for CIS vs. RR and CIS vs. RR+SP, respectively. For RR vs. PP we obtained good classification results (maximum F1-score of 85%) after training LDA on clinical and metabolic features, while for RR vs. SP we obtained slightly higher classification results (maximum F1-score of 87%) after training LDA and SVM-rbf on clinical, lesion loads and metabolic features. <b>Conclusions:</b> Our results suggest that metabolic features are better at differentiating between relapsing-remitting and primary progressive forms, while lesion loads are better at differentiating between relapsing-remitting and secondary progressive forms. Therefore, combining clinical data with magnetic resonance lesion loads and metabolic features can improve the discrimination between relapsing-remitting and progressive forms.
Effect of compounds released during pretreatment of wheat straw on microbial growth and enzymatic hydrolysis rates (2006)

In the process of producing ethanol from lignocellulosic materials such as wheat straw, compounds that can act inhibitory to enzymatic hydrolysis and to cellular growth may be generated during the pretreatment. Ethanol production was evaluated on pretreated wheat straw hydrolysate using four different recombinant Saccharomyces cerevisiae strains, CPB.CR4, CPB.CB4, F12, and FLX. The fermentation performance of the four S. cerevisiae strains was tested in hydrolysate of wheat straw that has been pretreated at high dry matter content (220 g/L dry matter). The results clearly showed that F12 was the most robust strain, whereas the other three strains were strongly inhibited when the fraction of hydrolysate in the fermentation medium was higher than 60% (v/v). Furthermore, the impact of different lignin derivatives commonly found in the hydrolysate of pretreated wheat straw, was tested on two different enzyme mixtures, a mixture of Celluclast 1.5 L FG and Novozym 188 (3:1) and one crude enzyme preparation produced from Penicillium brasilianum IBT 20888. From all the potential inhibiting compounds that were tested, formic acid had the most severe influence on the hydrolysis rate resulting in a complete inactivation of the two enzyme mixtures.
Decanoyl-Arg-Val-Lys-Arg-Chloromethylketone: An Antiviral Compound That Acts against Flaviviruses through the Inhibition of Furin-Mediated prM Cleavage (2019)

Flaviviruses, such as Zika virus (ZIKV), Japanese encephalitis virus (JEV), Dengue virus (DENV), and West Nile virus (WNV), are important arthropod-borne pathogens that present an immense global health problem. Their unpredictable disease severity, unusual clinical features, and severe neurological manifestations underscore an urgent need for antiviral interventions. Furin, a host proprotein convertase, is a key contender in processing flavivirus prM protein to M protein, turning the inert virus to an infectious particle. For this reason, the current study was planned to evaluate the antiviral activity of decanoyl-Arg-Val-Lys-Arg-chloromethylketone, a specific furin inhibitor, against flaviviruses, including ZIKV and JEV. Analysis of viral proteins revealed a significant increase in the prM/E index of ZIKV or JEV in dec-RVKR-cmk-treated Vero cells compared to DMSO-treated control cells, indicating dec-RVKR-cmk inhibits prM cleavage. Plaque assay, qRT-PCR, and immunofluorescence assay revealed a strong antiviral activity of dec-RVKR-cmk against ZIKV and JEV in terms of the reduction in virus progeny titer and in viral RNA and protein production in both mammalian cells and mosquito cells. Time-of-drug addition assay revealed that the maximum reduction of virus titer was observed in post-infection treatment. Furthermore, our results showed that dec-RVKR-cmk exerts its inhibitory action on the virus release and next round infectivity but not on viral RNA replication. Taken together, our study highlights an interesting antiviral activity of dec-RVKR-cmk against flaviviruses.
Clustered Pathway Genes in Aflatoxin Biosynthesis (2004)

Aflatoxins, a group of polyketide-derived furanocoumarins (Fig. [1][1]), are the most toxic and carcinogenic compounds among the known mycotoxins. Among the at least 16 structurally related aflatoxins characterized, however, there are only four major aflatoxins, B1, B2, G1, and G2 (AFB1, AFG1, AFB2
A new high speed cmos camera for real-time tracking applications (2004)

There are many potential applications for very high-speed vision sensors in robotics. Maybe tracking is the most obvious one. The main idea of this paper is to combine existing standard technology (CMOS imaging sensors, FPGA "glue logic", and USB 2.0 interface) to use direct pixel access capabilities for real-time tracking. We designed and built such a prototype camera system, including FPGA programmed functionality for Fixed Pattern Noise (FPN) calibration, subsampling and direct subwindow access. The performance of this new camera is on one hand limited by the maximum pixel clock of the sensor, on the other hand by the USB 2.0 microframe timing and bandwith constraints. We achieve "frame rates" of up to 2.5 kHz for small subwindows which can be randomly and individually addressed for each update cycle. Besides all given technical details and specifications of the system, we show a demonstration application of a high-speed blob tracking system which verifies the usability of our new camera for highly demanding tracking applications.
Design considerations for the ALDC cores (1998)

The IBM adaptive lossless data compression (ALDC) family of products uses a derivative of Lempel-Ziv encoding to compress data. Several variables affect the compression performance of the ALDC algorithm: data content, history size, and data extent. As ALDC compression is integrated into different applications, restrictions are placed upon these variables that affect the overall compression performance of the system. More complex applications require further support for higher-order data structures such as variable-length segments, error recovery, and expansion. The IBM Blue Logic ALDC and embedded lossless data compression (ELDC) cores have been developed to work in these application environments. These cores and the issues associated with integrating data compression into a system are discussed.
The Proteolytic Stability of ‘Designed’β-Peptides Containingα-Peptide-Bond Mimics and of Mixedα,β-Peptides: Application to the Construction of MHC-Binding Peptides (2005)

Whereas α-peptides are rapidly degraded in vivo and in vitro by a multitude of peptidases, substrates constructed entirely of or incorporating homologated α-amino acid (i.e., β-amino acid) units exhibit a superior stability profile. Efforts made so far to proteolytically hydrolyze a ββ peptide bond have not proved fruitful; a study aimed at breaching this proteolytic stability is discussed here. A series of such bonds have been designed with side-chain groups similar in relative positions (constitution) and three-dimensional arrangements (configuration) as found about α-peptidic amide bonds. Increasing the prospect for degradation would permit the tuning of β-peptide stability; here, however, no cleavage was observed (1, 2, 4–6, Table 1). Peptides comprised of α- and β-amino acids (mixed α,β-peptides, 8–11) are expected to benefit from both recognition by a natural receptor and a high level of proteolytic stability, ideal characteristics of pharmacologically active compounds. β3-Peptides containing α-amino acid moieties at the N-terminus are degraded, albeit slowly, by several peptidases. Of particular interest is the ability of pronase to cleave an αβ peptide bond, namely that of αAlaβ3hAla. Significantly, successful hydrolysis is independent of the configuration of the β-amino acid. Some of the α,β-peptides discussed here are being investigated for their binding affinities to class I MHC proteins. The computer-programming steps required to prepare α,β-peptides on an automated peptide synthesizer are presented.
Use of Multivitamin/Mineral Prenatal Supplements: Influence on the Outcome of Pregnancy (1997)

The objective of this study was to examine the association of prenatal multivitamin/mineral supplement use during the first and second trimesters of pregnancy by low income, urban women in the Camden Study (1985-1995, n = 1,430) and preterm delivery (< 37 completed weeks) and infant low birth weight (< 2,500 g). Prenatal supplement use was corroborated by assay of circulating micronutrients at entry to care (no differences) and week 28 gestation (increased concentrations of folate and ferritin for supplement users). Compared with women who entered care during the first or second trimester but did not use prenatal supplements, supplement use starting in the first or second trimester was associated with approximately a twofold reduction in risk of preterm delivery. After controlling for potential confounding variables, risk of very preterm delivery (< 33 weeks' gestation) was reduced more than fourfold for first trimester users and approximately twofold when use dated from the second trimester. Infant low birth weight and very low birth weight (< 1,500 g) risks were also reduced. Risk of low birth weight was reduced approximately twofold with supplement use during the first and second trimester. Diminution in risk was greater for very low birth weight infants, amounting to a sevenfold reduction in risk of very low birth weight with first trimester supplementation and a greater than sixfold reduction when supplement use started in the second trimester. Thus, in low income, urban women, use of prenatal multivitamin/mineral supplements may have the potential to diminish infant morbidity and mortality.