bluuebunny/crossref_metadata_2025_split huggingface dataset:
Well-controlled area seepage law and disturbance degree between production wells prediction of tight gas reservoir: a case study of Sulige gas field, Ordos Basin, NW China
Authors: Xiao Feng , Xu Wen , Wang Jinkai 
Published: March 2020

AbstractBased on a sum of well test interpretation analysis, the flowage characteristics of the gas in reservoir were analyzed from physical parameters and double-logarithm curve characteristics of gas wells. The result showed that the permeability of gas well-fracturing area is greatly improved, which is the main area to provide productivity. The speed of pressure transmission was slow because of extremely low permeability of outside the fracturing area and fluid flow was dominated by a linear flow. And three common well test interpretation models were extracted. The characteristics of bi-zonal compound reservoir of gas wells were specified by combination with peripheral supply and pressure change characteristics of gas wells. Variations of reservoir pressure and flowing bottom-hole pressure with time were simulated and quantified under different physical parameters and daily production. And the rational proration scheme of gas production wells was established by integration with numerical simulation method. Numerical simulation results of 21 sets of well patterns showed that there were two recovery inflection points. And a new model was built to research well interference degree that was defined by a new and original mathematical expression about production. The result showed that the infill well pattern should be controlled at 500 m × (500–600) m.
EStradiol and PRogesterone in In vitro ferTilization (ESPRIT): a multicenter study evaluating third- versus second-generation estradiol and progesterone immunoassays
Authors: Polyzos N. P. , Anckaert E. , Drakopoulos P. , Tournaye H. , Schiettecatte J. , Donner H. , Bobba G. , Miles G. , Verhagen-Kamerbeek W. D. J. , Bosch E. 
Published: March 2020

Abstract
Purpose
To assess estradiol (E2) and progesterone levels during ovarian stimulation determined by third-generation (Gen III) and second-generation (Gen II) Elecsys® immunoassays.

Methods
E2 and progesterone concentrations were measured using Elecsys® Gen III and Gen II immunoassays, and progesterone concentrations on the day of ovulation triggering were determined by LC–MS/MS. This was a retrospective, non-interventional study conducted at European tertiary referral infertility clinics in women aged 18–45 years, with a body mass index 18–35 kg/m2, regular menses, and both ovaries.

Results
Serum samples were obtained from 230 women classified by oocyte retrieval as poor (33.0%; 0–3 oocytes), normal (40.9%; 4–15 oocytes), or high (26.1%; > 15 oocytes) responders. E2 and progesterone levels increased during ovarian stimulation, with greatest increases observed in high responders. Elecsys® Gen III and Gen II assay results were highly correlated for E2 (Pearson’s r = 0.99) and progesterone (r = 0.89); Gen III results were lower than Gen II for both E2 and progesterone. On the day of triggering, Gen III E2 and progesterone levels showed a difference of − 15.0% and − 27.9%, respectively. Progesterone levels (on day of triggering) measured by LC–MS/MS correlated better with Gen III (0.98) than Gen II (0.90). Mean relative differences for Gen III and Gen II assays versus LC–MS/MS were 14.6% and 62.8%, respectively.

Conclusion
E2 and progesterone levels determined with Elecsys® Gen II and III assays were highly correlated; results were lower for Gen III versus Gen II. Differences observed for progesterone on the day of triggering may be clinically relevant.
A modified particle swarm optimization based on decomposition with different ideal points for many-objective optimization problems
Authors: Qin Shufen , Sun Chaoli , Zhang Guochen , He Xiaojuan , Tan Ying 
Published: March 2020

AbstractMany evolutionary algorithms have been proposed for multi-/many-objective optimization problems; however, the tradeoff of convergence and diversity is still the challenge for optimization algorithms. In this paper, we propose a modified particle swarm optimization based on decomposition framework with different ideal points on each reference vector, called MPSO/DD, for many-objective optimization problems. In the MPSO/DD algorithm, the decomposition strategy is used to ensure the diversity of the population, and the ideal point on each reference vector can draw the population converge faster to the optimal front. The position of each individual will be updated by learning the demonstrators in its neighborhood that have less distance to the ideal point along the reference vector. Eight state-of-the-art evolutionary multi-/many-objective optimization algorithms are adopted to compare the performance with MPSO/DD for solving many-objective optimization problems. The experimental results on seven DTLZ test problems with 3, 5, 8, 10, 15 and 20 objectives, respectively, show the efficiency of our proposed method on solving problems with high-dimensional objective space.
Photoacoustic viscoelasticity imaging for the detection of acute hepatitis: a feasibility study
Authors: Wang Qian , Shi Yujiao 
Published: March 2020

AbstractBiomechanical assessments are essential for the understanding of physiological states and the characterization of certain tissue pathologies such as liver cirrhosis. In this work, we showed by the photoacoustic viscoelasticity (PAVE) imaging that obvious mechanical change was also observed in the development of the acute hepatitis owing to the hepatocyte enlargement and intracellular fluid increment, indicating that the PAVE technique can be developed as a supplementary method for detecting acute hepatitis in future. The feasibility of the PAVE imaging is validated by a group of agar phantoms. Furthermore, acute hepatitis pathological animal models were established and imaged ex vivo and in situ by the PAVE technique to demonstrate its capability for the mechanical characterization of acute hepatitis, and the imaging results were consistent with pathological results. The feasibility study of detecting acute hepatitis by the PAVE technique proved that this method has potential to be developed as a clinical biomechanical imaging method to supplement current clinical strategy for liver disease detection.
Guidelines for Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD)
Authors: Ercole Ari , Brinck Vibeke , George Pradeep , Hicks Ramona , Huijben Jilske , Jarrett Michael , Vassar Mary , Wilson Lindsay ,   the DAQCORD collaborators
Published: March 2020

AbstractBackground:High-quality data are critical to the entire scientific enterprise, yet the complexity and effort involved in data curation are vastly under-appreciated. This is especially true for large observational, clinical studies because of the amount of multimodal data that is captured and the opportunity for addressing numerous research questions through analysis, either alone or in combination with other data sets. However, a lack of details concerning data curation methods can result in unresolved questions about the robustness of the data, its utility for addressing specific research questions or hypotheses and how to interpret the results. We aimed to develop a framework for the design, documentation and reporting of data curation methods in order to advance the scientific rigour, reproducibility and analysis of the data.Methods:Forty-six experts participated in a modified Delphi process to reach consensus on indicators of data curation that could be used in the design and reporting of studies.Results:We identified 46 indicators that are applicable to the design, training/testing, run time and post-collection phases of studies.Conclusion:The Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD) Guidelines are the first comprehensive set of data quality indicators for large observational studies. They were developed around the needs of neuroscience projects, but we believe they are relevant and generalisable, in whole or in part, to other fields of health research, and also to smaller observational studies and preclinical research. The DAQCORD Guidelines provide a framework for achieving high-quality data; a cornerstone of health research.
SLAVERY AND ITS AFTERMATH IN THE MANDARA MOUNTAINS
Authors: CHÉTIMA MELCHISEDEK 
Published: March 2020

AbstractBased on long-term oral historical research in the Mandara Mountains, this article traces the ways in which memories of slavery have been preserved in songs which are usually not part of the more formal oral historical narratives. It historicizes this process by focusing on the selective memories of different generations as well as on the influence of colonial and post-colonial politics, particularly post-1990 democratic politics in Cameroon. The major change over time is the shift from the shameful memory of slavery to be repressed – or treated only obliquely – to its public claim as a political resource after the democratic transition of the 1990s. In retelling the history of being sold as slaves, the residents of the Mandara Mountains reversed the negative meaning of slavery to use it to celebrate their resistance to Islam and to voice political claims. This new narrative congeals around beingkirdi, a new regional and trans-religious identity claimed by Christians and pagans in the mountains.
INSTRUMENTAL VARIABLE QUANTILE REGRESSION WITH MISCLASSIFICATION
Authors: Ura Takuya 
Published: March 2020

AbstractThis article investigates the instrumental variable quantile regression model (Chernozhukov and Hansen, 2005,Econometrica73, 245–261; 2013,Annual Review of Economics, 5, 57–81) with a binary endogenous treatment. It offers two identification results when the treatment status is not directly observed. The first result is that, remarkably, the reduced-form quantile regression of the outcome variable on the instrumental variable provides a lower bound on the structural quantile treatment effect under the stochastic monotonicity condition. This result is relevant, not only when the treatment variable is subject to misclassification, but also when any measurement of the treatment variable is not available. The second result is for the structural quantile function when the treatment status is measured with error; the sharp identified set is characterized by a set of moment conditions under widely used assumptions on the measurement error. Furthermore, an inference method is provided in the presence of other covariates.
Alternative observational designs to estimate the effectiveness of one dose of oral cholera vaccine in Lusaka, Zambia
Authors: Ferreras E. , Blake A. , Chewe O. , Mwaba J. , Zulu G. , Poncin M. , Rakesh A. , Page A. L. , Quilici M. L. , Azman A. S. , Cohuet S. , Ciglenecki I. , Malama K. , Chizema-Kawesha E. , Luquero F. J. 
Published: March 2020

Abstract
We conducted a matched case-control (MCC), test-negative case-control (TNCC) and case-cohort study in 2016 in Lusaka, Zambia, following a mass vaccination campaign. Confirmed cholera cases served as cases in all three study designs. In the TNCC, control-subjects were cases with negative cholera culture and polymerase chain reaction results. Matched controls by age and sex were selected among neighbours of the confirmed cases in the MCC study. For the case-cohort study, we recruited a cohort of randomly selected individuals living in areas considered at-risk of cholera. We recruited 211 suspected cases (66 confirmed cholera cases and 145 non-cholera diarrhoea cases), 1055 matched controls and a cohort of 921. Adjusted vaccine effectiveness of one dose of oral cholera vaccine (OCV) was 88.9% (95% confidence interval (CI) 42.7–97.8) in the MCC study, 80.2% (95% CI: 16.9–95.3) in the TNCC design and 89.4% (95% CI: 64.6–96.9) in the case-cohort study. Three study designs confirmed the short-term effectiveness of single dose OCV. Major healthcare-seeking behaviour bias did not appear to affect our estimates. Most of the protection among vaccinated individuals could be attributed to the direct effect of the vaccine.
Creating a Novel Disaster Medicine Virtual Reality Training Environment
Authors: Gout Laurent , Hart Alexander , Houze-Cerfon Charles-Henri , Sarin Ritu , Ciottone Gregory R. , Bounes Vincent 
Published: March 2020

AbstractIntroduction:Disasters are high-acuity, low-frequency events which require medical providers to respond in often chaotic settings. Due to this infrequency, skills can atrophy, so providers must train and drill to maintain them. Historically, drilling for disaster response has been costly, and thus infrequent. Virtual Reality Environments (VREs) have been demonstrated to be acceptable to trainees, and useful for training Disaster Medicine skills. The improved cost of virtual reality training can allow for increased frequency of simulation and training.Problem:The problem addressed was to create a novel Disaster Medicine VRE for training and drilling.Methods:A VRE was created using SecondLife (Linden Lab; San Francisco, California USA) and adapted for use in Disaster Medicine training and drilling. It is easily accessible for the end-users (trainees), and is adaptable for multiple scenario types due to the presence of varying architecture and objects. Victim models were created which can be role played by educators, or can be virtual dummies, and can be adapted for wide ranging scenarios. Finally, a unique physiologic simulator was created which allows for dummies to mimic disease processes, wounds, and treatment outcomes.Results:The VRE was created and has been used extensively in an academic setting to train medical students, as well as to train and drill disaster responders.Conclusions:This manuscript presents a new VRE for the training and drilling of Disaster Medicine scenarios in an immersive, interactive experience for trainees.
A 20‐Year Climatology of Madden‐Julian Oscillation Convection: Large‐Scale Precipitation Tracking From TRMM‐GPM Rainfall
Authors: Kerns Brandon W. , Chen Shuyi S. 
Published: March 2020

AbstractThis study presents a 20‐year climatology of the Madden‐Julian Oscillation (MJO) convection based on Large‐scale Precipitation Tracking (LPT) using TRMM‐GPM Multisatellite Precipitation Analysis (TMPA) data from 1998–2018 over the global tropics‐midlatitudes (50°S–50°N). A total of 215 convective events are identified as MJO LPT systems over the 20 years, extending the results of Kerns and Chen (2016, https://doi.org/10.1002/2015JD024661). MJO LPT systems provide quantitative information regarding size, intensity, and location of the MJO convection in both the longitudinal and meridional directions. The MJO contributes up to 40–50% of the annual precipitation over the tropical Indo‐Pacific warm pool. MJO LPT systems have distinct seasonal and interannual variability. While MJO LPT systems are generally confined over the equatorial tropics during Boreal winter, some MJO LPT systems propagate northeast in the Bay of Bengal or from the South China Sea to the western North Pacific during Boreal summer. MJO LPT systems are more than doubled over the Indian Ocean (IO) and Maritime Continent (MC) during La Nina compared to El Nino. The 63% of MJO LPT systems initiate over the tropical IO, 26% over the MC and western Pacific, and 11% from the central Pacific to South America. About 40% of the MJO LPT systems that initialized over the IO were unable to propagate through the MC, namely, the barrier effect. The MC barrier effect is most pronounced during the spring and autumn transitions. This 20‐year MJO LPT climatology product will be provided as a supplement to this publication.
A Microbial Functional Group‐Based CH4 Model Integrated Into a Terrestrial Ecosystem Model: Model Structure, Site‐Level Evaluation, and Sensitivity Analysis
Authors: Song Chaoqing , Luan Junwei , Xu Xiaofeng , Ma Minna , Aurela Mika , Lohila Annalea , Mammarella Ivan , Alekseychik Pavel , Tuittila Eeva‐Stiina , Gong Wei , Chen Xiuzhi , Meng Xianhong , Yuan Wenping 
Published: March 2020

AbstractWetlands are one of the most important terrestrial ecosystems for land‐atmosphere CH4 exchange. A new process‐based, biophysical model to quantify CH4 emissions from natural wetlands was developed and integrated into a terrestrial ecosystem model (Integrated Biosphere Simulator). The new model represents a multisubstance system (CH4, O2, CO2, and H2) and describes CH4 production, oxidation, and three transport processes (diffusion, plant‐mediated transport, and ebullition). The new model uses several critical microbial mechanisms to represent the interaction of anaerobic fermenters and homoacetogens, hydrogenotrophic, and acetoclastic methanogens, and methanotrophs in CH4 production and oxidation. We applied the model to 24 different wetlands globally to compare the simulated CH4 emissions to observations and conducted a sensitivity analysis. The results indicated that (1) for most sites, the model was able to capture the magnitude and variation of observed CH4 emissions under varying environmental conditions; (2) the parameters that regulate dissolved organic carbon and acetate production, and acetoclastic methanogenesis had the significant impact on simulated CH4 emissions; (3) the representation of the process components of CH4 cycling showed that CH4 oxidation was about half or more of CH4 production, and plant‐mediated transport was the dominant pathway at most sites; and (4) the seasonality of simulated CH4 emissions can be controlled by soil temperature, water table position, or combinations thereof.
Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates
Authors: Quetin Gregory R. , Bloom A. Anthony , Bowman Kevin W. , Konings Alexandra G. 
Published: March 2020

AbstractModeling the net carbon balance is challenging due to the knowledge gaps in the variability and processes controlling gross carbon fluxes. Terrestrial carbon cycle modeling is susceptible to several sources of bias, including meteorological uncertainty, model structural uncertainty, and model parametric uncertainty. To determine the impact of these uncertainties, we compare three model‐derived representations of the global terrestrial carbon balance across 1997–2009: (1) observation‐constrained model‐data fusion (CARBon Data Model FraMEwork, CARDAMOM), (2) the reanalysis‐driven Trends in Net Land‐Atmosphere Carbon Exchange (TRENDY) land biosphere model ensemble, and (3) the Coupled Model Intercomparison Project 5 (CMIP5) Earth System Model ensemble. We consider the spread in carbon cycle simulations attributable primarily to parametric uncertainty (CARDAMOM), structural uncertainty (TRENDY), and combined structural and simulated meteorological uncertainty (CMIP5). We find that the spread across the CARDAMOM ensemble long‐term mean—produced by parameter uncertainty—is larger than the spread of TRENDY and CMIP5 for net biosphere exchange (NBE) but similar for gross primary productivity (GPP). The carbon flux dynamics of CARDAMOM compares to models in TRENDY as well as models in TRENDY compare to each other in many regions for NBE seasonal (nine of 12), NBE interannual (11 of 12), and GPP seasonal variability (7 of 12), although not for GPP interannual variability (2 of 12). The simple model structure of CARDAMOM and systematic assimilation of observations is sufficient to produce carbon dynamics within the range of more complex models. These results are encouraging for the use of model‐data fusion products with empirically estimated uncertainty for global carbon cycle studies.
Full Domestic Supply Chains of Blue Virtual Water Flows Estimated for Major U.S. Cities
Authors: Garcia Susana , Rushforth Richard , Ruddell Benjamin L. , Mejia Alfonso 
Published: March 2020

AbstractThrough the trade of products and services, cities indirectly depend on distant water sources to function, prosper, and grow. To fully account for indirect (virtual) water dependencies, virtual water flows need to be known along complex supply chains. To this purpose, we build a new environmental multiregional input–output model for U.S. regions. The model is used to quantify the domestic, blue virtual water flows and analyze the water footprints of 69 major U.S. cities. Our results show a large inequality in the urban water consumed for economic production: just 7 out of the 69 cities included in this study account for 35% of the U.S. national water footprint of production. This is due to the production of water‐intensive agricultural products in the metropolitan areas of western cities. The inequality reduces for the urban water footprint of consumption because, through the supply chains of industrialized food sectors, western virtual water is partially transferred to eastern cities as final demand. The water embodied in industrial products and services tends to be higher in western cities than in eastern cities; that is, the water embodied in food services could be several times higher in Los Angeles than in New York City. Trade hub cities attract large inflows of products which are mostly transformed for consumption elsewhere. Thus, the omission of product interdependencies within trade hub cities can increase by several times their water footprints of consumption. Overall, the proposed model is able to enhance subnational estimates of U.S. virtual water flows.
Symbiolite formation: a powerful in vitro model to untangle the role of bacterial communities in the photosynthesis-induced formation of microbialites
Authors: Nitschke Matthew R , Fidalgo Cátia , Simões João , Brandão Cláudio , Alves Artur , Serôdio João , Frommlet Jörg C 
Published: March 2020

Abstract
Microbially induced calcification is an ancient, community-driven mineralisation process that produces different types of microbialites. Symbiolites are photosynthesis-induced microbialites, formed by calcifying co-cultures of dinoflagellates from the family Symbiodiniaceae and bacteria. Symbiolites encase the calcifying community as endolithic cells, pointing at an autoendolithic niche of symbiotic dinoflagellates, and provide a rare opportunity to study the role of bacteria in bacterial–algal calcification, as symbiodiniacean cultures display either distinct symbiolite-producing (SP) or non-symbiolite-producing (NP) phenotypes. Using Illumina sequencing, we found that the bacterial communities of SP and NP cultures differed significantly in the relative abundance of 23 genera, 14 families, and 2 phyla. SP cultures were rich in biofilm digesters from the phylum Planctomycetes and their predicted metagenomes were enriched in orthologs related to biofilm formation. In contrast, NP cultures were dominated by biofilm digesters from the Bacteroidetes, and were inferred as enriched in proteases and nucleases. Functional assays confirmed the potential of co-cultures and bacterial isolates to produce biofilms and point at acidic polysaccharides as key stimulators for mineral precipitation. Hence, bacteria appear to influence symbiolite formation primarily through their biofilm-producing and modifying activity and we anticipate that symbiolite formation, as a low-complexity in vitro model, will significantly advance our understanding of photosynthesis-induced microbial calcification processes.