2,361 research outputs found
Editorial: Toxic effects and ecological risk assessment of typical pollutants in aquatic environments
Aquatic pollution caused by anthropogenic activities has been one of the major
environmental problems worldwide for decades. Rapid industrialization and urbanization
is releasing âtraditionalâ and emerging pollutants into waters in unprecedented quantities
and diversity, ultimately endangering biodiversity and human health. Meanwhile, the
management and control of risks from chemical pollutants, with varying scientific
composition, stringency, and efficacy, are being practiced in different countries and
regions.info:eu-repo/semantics/publishedVersio
Design of Seismic Intensity Rapid Report Platform
Abstract. Seismic intensity rapid report is one of the essential parts of the earthquake disaster relief and plays a baton role. In terms of serving the needs for earthquake early warning, emergency response, and seismic mobile observation, seismic network observation, a new seismic intensity rapid report platform is developed for the seismic intensity sensor network. The platform has a complete seismic intensity monitor system, and can achieve accurate and efficient intensity data recovery and analysis, built rapid and efficient intensity report system. Some key functions were utilized to integrate the platform, such as data collection, real-time data analysis, graphic display and intensity rapid reporting. A serial of experiments were carried out and the results showed that the platform could fulfill the purpose of seismic emergency response and deserve to be widely popularized
Reservoir Permeability Prediction Based on Analogy and Machine Learning Methods: Field Cases in DLG Block of Jingâan Oilfield, China
AbstractReservoir permeability, generally determined by experimental or well testing methods, is an essential parameter in the oil and gas field development. In this paper, we present a novel analogy and machine learning method to predict reservoir permeability. Firstly, the core test and production data of other 24 blocks (analog blocks) are counted according to the DLG block (target block) of Jingâan Oilfield, and the permeability analogy parameters including porosity, shale content, reservoir thickness, oil saturation, liquid production, and production pressure difference are optimized by Pearson and principal component analysis. Then, the fuzzy matter element method is used to calculate the similarity between the target block and analog blocks. According to the similarity calculation results, reservoir permeability of DLG block is predicted by reservoir engineering method (the relationship between core permeability and porosity of QK-D7 in similar blocks) and machine learning method (random forest, gradient boosting decision tree, light gradient boosting machine, and categorical boosting). By comparing the prediction accuracy of the two methods through the evaluation index determination coefficient (R2) and root mean square error (RMSE), the CatBoost model has higher accuracy in predicting reservoir permeability, with R2 of 0.951 and RMSE of 0.139. Finally, the CatBoost model is selected to predict reservoir permeability of 121 oil wells in the DLG block. This work uses simple logging and production data to quickly and accurately predict reservoir permeability without coring and testing. At the same time, the prediction results are well applied to the formulation of DLG block development technology strategy, which provides a new idea for the application of machine learning to predict oilfield parameters
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Genetically Determined Plasma Lipid Levels and Risk of Diabetic Retinopathy: A Mendelian Randomization Study.
Results from observational studies examining dyslipidemia as a risk factor for diabetic retinopathy (DR) have been inconsistent. We evaluated the causal relationship between plasma lipids and DR using a Mendelian randomization approach. We pooled genome-wide association studies summary statistics from 18 studies for two DR phenotypes: any DR (N = 2,969 case and 4,096 control subjects) and severe DR (N = 1,277 case and 3,980 control subjects). Previously identified lipid-associated single nucleotide polymorphisms served as instrumental variables. Meta-analysis to combine the Mendelian randomization estimates from different cohorts was conducted. There was no statistically significant change in odds ratios of having any DR or severe DR for any of the lipid fractions in the primary analysis that used single nucleotide polymorphisms that did not have a pleiotropic effect on another lipid fraction. Similarly, there was no significant association in the Caucasian and Chinese subgroup analyses. This study did not show evidence of a causal role of the four lipid fractions on DR. However, the study had limited power to detect odds ratios less than 1.23 per SD in genetically induced increase in plasma lipid levels, thus we cannot exclude that causal relationships with more modest effect sizes exist
Detecting PKD1 variants in polycystic kidney disease patients by single-molecule long-read sequencing
A genetic diagnosis of autosomal-dominant polycystic kidney disease (ADPKD) is challenging due to allelic heterogeneity, high GC content, and homology of the PKD1 gene with six pseudogenes. Short-read next-generation sequencing approaches, such as whole-genome sequencing and whole-exome sequencing, often fail at reliably characterizing complex regions such as PKD1. However, long-read single-molecule sequencing has been shown to be an alternative strategy that could overcome PKD1 complexities and discriminate between homologous regions of PKD1 and its pseudogenes. In this study, we present the increased power of resolution for complex regions using long-read sequencing to characterize a cohort of 19 patients with ADPKD. Our approach provided high sensitivity in identifying PKD1 pathogenic variants, diagnosing 94.7% of the patients. We show that reliable screening of ADPKD patients in a single test without interference of PKD1 homologous sequences, commonly introduced by residual amplification of PKD1 pseudogenes, by direct long-read sequencing is now possible. This strategy can be implemented in diagnostics and is highly suitable to sequence and resolve complex genomic regions that are of clinical relevance
Ground calibration of Gamma-Ray Detectors of GECAM-C
As a new member of GECAM mission, GECAM-C (also named High Energy Burst
Searcher, HEBS) was launched onboard the SATech-01 satellite on July 27th,
2022, which is capable to monitor gamma-ray transients from 6 keV to 6
MeV. As the main detector, there are 12 gamma-ray detectors (GRDs) equipped for
GECAM-C. In order to verify the GECAM-C GRD detector performance and to
validate the Monte Carlo simulations of detector response, comprehensive
on-ground calibration experiments have been performed using X-ray beam and
radioactive sources, including Energy-Channel relation, energy resolution,
detection efficiency, SiPM voltage-gain relation and the non-uniformity of
positional response. In this paper, the detailed calibration campaigns and data
analysis results for GECAM-C GRDs are presented, demonstrating the excellent
performance of GECAM-C GRD detectors.Comment: third versio
Rational synthesis of epoxy-functional spheres, worms and vesicles by RAFT aqueous emulsion polymerisation of glycidyl methacrylate
The rational synthesis of epoxy-functional diblock copolymer nano-objects has been achieved via RAFT aqueous emulsion polymerisation of glycidyl methacrylate (GlyMA; aqueous solubility âŒ22 g dm-3 at 50 °C) by utilising relatively mild conditions (pH 7, 50 °C) to preserve the epoxy groups. High monomer conversions were achieved within 1 h when using a poly(glycerol monomethacrylate) chain transfer agent with a mean degree of polymerisation (DP) of 28, with GPC analysis indicating relatively narrow molecular weight distributions (Mw/Mn < 1.40) when targeting PGlyMA DPs up to 80. A phase diagram was constructed to identify the synthesis conditions required to access pure spheres, worms or vesicles. Transmission electron microscopy, dynamic light scattering and small-angle X-ray scattering (SAXS) studies indicated the formation of well-defined worms and vesicles when targeting relatively long PGlyMA blocks. These epoxy-functional nano-objects were derivatised via epoxy-thiol chemistry by reaction with l-cysteine in aqueous solution. Finally, an in situ SAXS study was conducted during the RAFT aqueous emulsion polymerisation of GlyMA at 50 °C to examine the nucleation and size evolution of PGMA48-PGlyMA100 diblock copolymer spheres using a bespoke stirrable reaction cell
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