On the determination of low degree harmonics by combining SLR with GRACE / GRACE-FO

2020 ◽  
Author(s):  
Rolf Koenig ◽  
Patrick Schreiner ◽  
Christoph Dahle
Keyword(s):  
State Of The Art ◽  
Normal Equation ◽  
Laser Ranging ◽  
Gravitational Fields ◽  
Low Degree ◽  
German Research ◽  
Temporal And Spatial ◽  
Earth’S Oblateness ◽  
Insight Into

<p>Today's state-of-the-art gravity missions GRACE and GRACE-FO monitor the Earth's gravitational field in high temporal and spatial resolution. The resulting time series of gravitational fields serves various geophysical applications. It is however recommended to replace the C(2,0) coefficients, which describe the change of the Earth's oblateness, by those determined by Satellite Laser Ranging (SLR) to geodetic satellites. There are also discussions ongoing on the C(2,1), S(2,1) and C(3,0) coefficients. Current research shows that a combination of GRACE and GRACE-FO with SLR can lead to an improvement of the determination of the low degree coefficients in view of certain geophysical applications. This contribution gives an insight into the recent research at the Helmholtz Center Potsdam - German Research Center for Geosciences (GFZ) on various methods for the multi-technique combination on normal equation level and discusses the effects on the low degree spherical harmonics.</p>

scholarly journals Combination of data from different space geodetic systems for the determination of Earth rotation parameters

1988 ◽  
Vol 128 ◽  
pp. 233-239
Author(s):  
Brent A. Archinal
Keyword(s):  
Earth Rotation ◽  
Normal Equation ◽  
Laser Ranging ◽  
Weighted Mean ◽  
Lunar Laser Ranging ◽  
Long Baseline ◽  
Lunar Laser ◽  
Earth Rotation Parameters ◽  
Vlbi Data

Simulation experiments have been performed in order to compare the Earth Rotation Parameter (ERP) results obtained from a) individual observational systems, b) the weighted mean of the results from a), and c) all of the observational data, via the combination of the normal equations obtained in a). These experiments included the use of 15 days of simulated Lunar Laser Ranging (LLR), Satellite Laser Ranging (SLR) to Lageos, and Very Long Baseline Interferometry (VLBI) data using realistic station positions and accuracies. Under the assumptions chosen, the normal equation combination solutions usually provide the best ERP over recovery periods of 6 and 12 hours, and 1, 2, and 5 days. However, solutions by the weighted mean (and even by VLBI alone) provide results that are nearly as good, i.e., within a factor of one to two in accuracy. Complete details are presented in [Archinal, 1987].

Determination of Mn, Fe, Ni, Cu, Zn, Cd and Pb in seawater using offline extraction and triple quadrupole ICP-MS/MS

2018 ◽  
Vol 33 (2) ◽  
pp. 304-313 ◽  
Author(s):  
S. L. Jackson ◽  
J. Spence ◽  
D. J. Janssen ◽  
A. R. S. Ross ◽  
J. T. Cullen
Keyword(s):  
Trace Elements ◽  
Spatial Distributions ◽  
Triple Quadrupole ◽  
Ocean Water ◽  
Sample Throughput ◽  
Accuracy And Precision ◽  
Icp Ms ◽  
Temporal And Spatial ◽  
Insight Into

Highly resolved temporal and spatial distributions of trace elements in ocean water can provide insight into ocean processes but carry a significant analytical demand which requires methods that combine accuracy and precision with high sample throughput.

scholarly journals In vivo interactome profiling by enzyme‐catalyzed proximity labeling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yangfan Xu ◽  
Xianqun Fan ◽  
Yang Hu
Keyword(s):  
State Of The Art ◽  
Catalytic Efficiency ◽  
Biological Processes ◽  
Protein Protein Interaction ◽  
Current State ◽  
Protein Interactome ◽  
Potential Applications ◽  
Protein Protein Interaction Networks ◽  
Temporal And Spatial

AbstractEnzyme-catalyzed proximity labeling (PL) combined with mass spectrometry (MS) has emerged as a revolutionary approach to reveal the protein-protein interaction networks, dissect complex biological processes, and characterize the subcellular proteome in a more physiological setting than before. The enzymatic tags are being upgraded to improve temporal and spatial resolution and obtain faster catalytic dynamics and higher catalytic efficiency. In vivo application of PL integrated with other state of the art techniques has recently been adapted in live animals and plants, allowing questions to be addressed that were previously inaccessible. It is timely to summarize the current state of PL-dependent interactome studies and their potential applications. We will focus on in vivo uses of newer versions of PL and highlight critical considerations for successful in vivo PL experiments that will provide novel insights into the protein interactome in the context of human diseases.

scholarly journals The Degree of Oxidation of Graphene Oxide

Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 560
Author(s):  
Alexandra Carvalho ◽  
Mariana C. F. Costa ◽  
Valeria S. Marangoni ◽  
Pei Rou Ng ◽  
Thi Le Hang Nguyen ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Ab Initio ◽  
State Of The Art ◽  
High Accuracy ◽  
Precise Determination ◽  
Photoemission Spectroscopy ◽  
Pristine Graphene ◽  
X Ray ◽  
Degree Of Oxidation

We show that the degree of oxidation of graphene oxide (GO) can be obtained by using a combination of state-of-the-art ab initio computational modeling and X-ray photoemission spectroscopy (XPS). We show that the shift of the XPS C1s peak relative to pristine graphene, ΔEC1s, can be described with high accuracy by ΔEC1s=A(cO−cl)2+E0, where c0 is the oxygen concentration, A=52.3 eV, cl=0.122, and E0=1.22 eV. Our results demonstrate a precise determination of the oxygen content of GO samples.

scholarly journals Significance of Mast Cell Formed Extracellular Traps in Microbial Defense

2021 ◽  
Author(s):  
Daniel Elieh Ali Komi ◽  
Wolfgang M. Kuebler
Keyword(s):  
State Of The Art ◽  
Extracellular Dna ◽  
Cellular Mechanisms ◽  
Extracellular Traps ◽  
Synthetic Chemicals ◽  
Dna Strands ◽  
Associated Proteins ◽  
Microbial Defense ◽  
And Function ◽  
Insight Into

AbstractMast cells (MCs) are critically involved in microbial defense by releasing antimicrobial peptides (such as cathelicidin LL-37 and defensins) and phagocytosis of microbes. In past years, it has become evident that in addition MCs may eliminate invading pathogens by ejection of web-like structures of DNA strands embedded with proteins known together as extracellular traps (ETs). Upon stimulation of resting MCs with various microorganisms, their products (including superantigens and toxins), or synthetic chemicals, MCs become activated and enter into a multistage process that includes disintegration of the nuclear membrane, release of chromatin into the cytoplasm, adhesion of cytoplasmic granules on the emerging DNA web, and ejection of the complex into the extracellular space. This so-called ETosis is often associated with cell death of the producing MC, and the type of stimulus potentially determines the ratio of surviving vs. killed MCs. Comparison of different microorganisms with specific elimination characteristics such as S pyogenes (eliminated by MCs only through extracellular mechanisms), S aureus (removed by phagocytosis), fungi, and parasites has revealed important aspects of MC extracellular trap (MCET) biology. Molecular studies identified that the formation of MCET depends on NADPH oxidase-generated reactive oxygen species (ROS). In this review, we summarize the present state-of-the-art on the biological relevance of MCETosis, and its underlying molecular and cellular mechanisms. We also provide an overview over the techniques used to study the structure and function of MCETs, including electron microscopy and fluorescence microscopy using specific monoclonal antibodies (mAbs) to detect MCET-associated proteins such as tryptase and histones, and cell-impermeant DNA dyes for labeling of extracellular DNA. Comparing the type and biofunction of further MCET decorating proteins with ETs produced by other immune cells may help provide a better insight into MCET biology in the pathogenesis of autoimmune and inflammatory disorders as well as microbial defense.

scholarly journals Characterization and Quantification of Selenoprotein P: Challenges to Mass Spectrometry

2021 ◽  
Vol 22 (12) ◽  
pp. 6283
Author(s):  
Jérémy Lamarche ◽  
Luisa Ronga ◽  
Joanna Szpunar ◽  
Ryszard Lobinski
Keyword(s):  
Mass Spectrometry ◽  
State Of The Art ◽  
Animal Health ◽  
Primary Standard ◽  
Selenoprotein P ◽  
Primary Standards ◽  
Analytical Approaches ◽  
Careful Investigation ◽  
Accurate Quantification

Selenoprotein P (SELENOP) is an emerging marker of the nutritional status of selenium and of various diseases, however, its chemical characteristics still need to be investigated and methods for its accurate quantitation improved. SELENOP is unique among selenoproteins, as it contains multiple genetically encoded SeCys residues, whereas all the other characterized selenoproteins contain just one. SELENOP occurs in the form of multiple isoforms, truncated species and post-translationally modified variants which are relatively poorly characterized. The accurate quantification of SELENOP is contingent on the availability of specific primary standards and reference methods. Before recombinant SELENOP becomes available to be used as a primary standard, careful investigation of the characteristics of the SELENOP measured by electrospray MS and strict control of the recoveries at the various steps of the analytical procedures are strongly recommended. This review critically discusses the state-of-the-art of analytical approaches to the characterization and quantification of SELENOP. While immunoassays remain the standard for the determination of human and animal health status, because of their speed and simplicity, mass spectrometry techniques offer many attractive and complementary features that are highlighted and critically evaluated.

An insight into the determination of size and number concentration of silver nanoparticles in blood using single particle ICP-MS (spICP-MS): Feasibility of application to samples relevant to in vivo toxicology studies

2021 ◽  
Author(s):  
Isabel Abad-Álvaro ◽  
Diego Leite ◽  
Dorota Bartczak ◽  
Susana Cuello ◽  
Beatriz Gomez-Gomez ◽  
...  
Keyword(s):  
Silver Nanoparticles ◽  
Single Particle ◽  
Number Concentration ◽  
Biological Matrices ◽  
Icp Ms ◽  
Toxicological Studies ◽  
Insight Into

Toxicological studies concerning nanomaterials in complex biological matrices usually require a carefully designed workflow that involves handling, transportation and preparation of a large number of samples without affecting the nanoparticle...

Towards Interconnected Blockchains

2021 ◽  
Vol 54 (7) ◽  
pp. 1-39
Author(s):  
Ankur Lohachab ◽  
Saurabh Garg ◽  
Byeong Kang ◽  
Muhammad Bilal Amin ◽  
Junmin Lee ◽  
...  
Keyword(s):  
State Of The Art ◽  
The State ◽  
Future Research ◽  
Missing Link ◽  
Layered Architecture ◽  
Blockchain Technology ◽  
Wide Scale ◽  
Effective Development ◽  
Insight Into ◽  
Game Changer

Unprecedented attention towards blockchain technology is serving as a game-changer in fostering the development of blockchain-enabled distinctive frameworks. However, fragmentation unleashed by its underlying concepts hinders different stakeholders from effectively utilizing blockchain-supported services, resulting in the obstruction of its wide-scale adoption. To explore synergies among the isolated frameworks requires comprehensively studying inter-blockchain communication approaches. These approaches broadly come under the umbrella of Blockchain Interoperability (BI) notion, as it can facilitate a novel paradigm of an integrated blockchain ecosystem that connects state-of-the-art disparate blockchains. Currently, there is a lack of studies that comprehensively review BI, which works as a stumbling block in its development. Therefore, this article aims to articulate potential of BI by reviewing it from diverse perspectives. Beginning with a glance of blockchain architecture fundamentals, this article discusses its associated platforms, taxonomy, and consensus mechanisms. Subsequently, it argues about BI’s requirement by exemplifying its potential opportunities and application areas. Concerning BI, an architecture seems to be a missing link. Hence, this article introduces a layered architecture for the effective development of protocols and methods for interoperable blockchains. Furthermore, this article proposes an in-depth BI research taxonomy and provides an insight into the state-of-the-art projects. Finally, it determines possible open challenges and future research in the domain.

scholarly journals Insight into Glutamatergic Involvement in Rewarding Effects of Mephedrone in Rats: In Vivo and Ex Vivo Study

2021 ◽  
Author(s):  
Olga Wronikowska ◽  
Maria Zykubek ◽  
Agnieszka Michalak ◽  
Anna Pankowska ◽  
Paulina Kozioł ◽  
...  
Keyword(s):  
Ex Vivo ◽  
Interdisciplinary Approach ◽  
Nmda Antagonist ◽  
Exchange Chromatography ◽  
Resonance Spectroscopy ◽  
Monoamine Transporters ◽  
Ex Vivo Study ◽  
Insight Into

AbstractMephedrone is a widely used drug of abuse, exerting its effects by interacting with monoamine transporters. Although this mechanism has been widely studied heretofore, little is known about the involvement of glutamatergic transmission in mephedrone effects. In this study, we comprehensively evaluated glutamatergic involvement in rewarding effects of mephedrone using an interdisciplinary approach including (1) behavioural study on effects of memantine (non-selective NMDA antagonist) on expression of mephedrone-induced conditioned place preference (CPP) in rats; (2) evaluation of glutamate concentrations in the hippocampus of rats following 6 days of mephedrone administration, using in vivo magnetic resonance spectroscopy (MRS); and (3) determination of glutamate levels in the hippocampus of rats treated with mephedrone and subjected to MRS, using ion-exchange chromatography. In the presented research, we confirmed priorly reported mephedrone-induced rewarding effects in the CPP paradigm and showed that memantine (5 mg/kg) was able to reverse the expression of this effect. MRS study showed that subchronic mephedrone administration increased glutamate level in the hippocampus when measured in vivo 24 h (5 mg/kg, 10 mg/kg and 20 mg/kg) and 2 weeks (5 mg/kg and 20 mg/kg) after last injection. Ex vivo chromatographic analysis did not show significant changes in hippocampal glutamate concentrations; however, it showed similar results as obtained in the MRS study proving its validity. Taken together, the presented study provides new insight into glutamatergic involvement in rewarding properties of mephedrone.

scholarly journals Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 930
Author(s):  
Fahimeh Hadavimoghaddam ◽  
Mehdi Ostadhassan ◽  
Ehsan Heidaryan ◽  
Mohammad Ali Sadri ◽  
Inna Chapanova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Viscosity Data ◽  
Oil Viscosity ◽  
Pvt Data ◽  
Proposed Model ◽  
Wide Range ◽  
Engineering Problems ◽  
Functional Forms ◽  
Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

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