bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toward High Precision XCO2Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements
Authors: Yang D. , Boesch H. , Liu Y. , Somkuti P. , Cai Z. , Chen X. , Di Noia A. , Lin C. , Lu N. , Lyu D. , Parker R. J. , Tian L. , Wang M. , Webb A. , Yao L. , Yin Z. , Zheng Y. , Deutscher N. M. , Griffith D. W. T. , Hase F. , Kivi R. , Morino I. , Notholt J. , Ohyama H. , Pollard D. F. , Shiomi K. , Sussmann R. , Té Y. , Velazco V. A. , Warneke T. , Wunch D. 
Published: October 2020

AbstractTanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL‐FP) algorithm is implemented for TanSat nadir mode XCO2retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8thorder Fourier series. The spectrum‐correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O2A band retrieval. Accordingly, we extend the previous TanSat single CO2weak band retrieval to a combined O2A and CO2weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post‐screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2retrieval. We show that our new approach produces a significant improvement on the XCO2retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of −0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2retrieval from TanSat and subsequently the Level‐2 data production, and hence will be applied in the TanSat operational XCO2processing.
Burma Terrane Collision and Northward Indentation in the Eastern Himalayas Recorded in the Eocene‐Miocene Chindwin Basin (Myanmar)
Authors: Westerweel Jan , Licht Alexis , Cogné Nathan , Roperch Pierrick , Dupont‐Nivet Guillaume , Kay Thi Myat , Swe Hnin Hnin , Huang Huasheng , Win Zaw , Wa Aung Day 
Published: October 2020

AbstractThe Burma Terrane (Myanmar) played an important role in the India‐Asia collision and moved over 2,000 km northward on the Indian Plate during the Cenozoic, before colliding with the Asian margin. However, the timing of this collision and its correlation to regional uplift phases, sedimentary provenance, and basin development remain poorly constrained. We report sedimentological, paleomagnetic, and geochronological data from the late Eocene to early Miocene strata of the Chindwin Basin in the Burmese forearc, constraining the paleogeographic evolution of the Burma Terrane and the Eastern Himalayan orogen. Our results highlight two unconformities of late Eocene‐middle Oligocene and latest Oligocene‐early Miocene age, revealing a two‐stage interaction of the Burma Terrane with the Asian margin during its northward translation. The first unconformity follows rapid ~0.6 m/ky subsidence in the Burmese forearc, as shown by magnetostratigraphy. The transition to a fluvial depositional environment and the occurrence of reworked sediments at this first unconformity likely records the commencing collision of India and the northern extent of the Burma Terrane with the Asian margin. The second unconformity shows drastic changes in magnetic properties, mineralogy, and provenance, with high‐grade metamorphic grains and early Miocene apatite U‐Pb and fission‐track ages indicating that it is coeval to a major deformation phase in Myanmar and the Eastern Himalayan orogen. It likely records the indentation of the Burma Terrane into the Eastern Himalayan collision zone, forming the modern Eastern Himalayan Syntaxis.
Pore‐Scale Study of Water Adsorption and Subsequent Methane Transport in Clay in the Presence of Wettability Heterogeneity
Authors: Xu Rui , Prodanović Maša , Landry Christopher 
Published: October 2020

AbstractClay minerals are abundant in shale, characterized by a lamellar structure and dimensions smaller than a micron, giving rise to nanometer‐scale pore sizes and large specific surface area. They are commonly associated with water. However, the spatial distribution of the unsaturated water in clay is not very well understood, which significantly affects the subsequent shale gas flow capacity. Wettability heterogeneity in the presence of hydrocarbons further complicates the water distribution in clay. In this study, we use a 3‐D lattice Boltzmann model to study water adsorption and condensation in a reconstructed clay microstructure based on broad‐ion‐beam scanning electron microscopy images. Three wettability conditions are considered including a water‐wet case, a water‐repellent case, and a mixed‐wet case. The spatial distribution of the condensed liquid water phase is visualized, and the connectivity of the remaining open pore spaces is characterized. For the water‐wet case, water preferentially condenses in the small and narrow pore spaces, while the water‐repellent case reports the opposite trend. The mixed‐wet case results in mixed behavior, and connectivity of the pore space is bound by the former two cases. We then study the subsequent methane flow capacity with the presence of water for these three cases, and the calculated methane relative permeability curves show a percolation threshold for the water‐wet case, which is in good agreement with available experimental data in the literature measured on geosynthetic clay liners.
Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage
Authors: Espah Borujeni Amin , Zhang Jing , Doosthosseini Hamid , Nielsen Alec A. K. , Voigt Christopher A. 
Published: October 2020

AbstractTo perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.
Movie viewing elicits rich and reliable brain state dynamics
Authors: Meer Johan N. van der , Breakspear Michael , Chang Luke J. , Sonkusare Saurabh , Cocchi Luca 
Published: October 2020

AbstractAdaptive brain function requires that sensory impressions of the social and natural milieu are dynamically incorporated into intrinsic brain activity. While dynamic switches between brain states have been well characterised in resting state acquisitions, the remodelling of these state transitions by engagement in naturalistic stimuli remains poorly understood. Here, we show that the temporal dynamics of brain states, as measured in fMRI, are reshaped from predominantly bistable transitions between two relatively indistinct states at rest, toward a sequence of well-defined functional states during movie viewing whose transitions are temporally aligned to specific features of the movie. The expression of these brain states covaries with different physiological states and reflects subjectively rated engagement in the movie. In sum, a data-driven decoding of brain states reveals the distinct reshaping of functional network expression and reliable state transitions that accompany the switch from resting state to perceptual immersion in an ecologically valid sensory experience.
Generation and trapping of a mesoderm biased state of human pluripotency
Authors: Stavish Dylan , Böiers Charlotta , Price Christopher , Frith Thomas J. R. , Halliwell Jason , Saldaña-Guerrero Ingrid , Wray Jason , Brown John , Carr Jonathon , James Chela , Barbaric Ivana , Andrews Peter W. , Enver Tariq 
Published: October 2020

AbstractWe postulate that exit from pluripotency involves intermediates that retain pluripotency while simultaneously exhibiting lineage-bias. Using a MIXL1 reporter, we explore mesoderm lineage-bias within the human pluripotent stem cell compartment. We identify a substate, which at the single cell level coexpresses pluripotent and mesodermal gene expression programmes. Functionally these cells initiate stem cell cultures and exhibit mesodermal bias in differentiation assays. By promoting mesodermal identity through manipulation of WNT signalling while preventing exit from pluripotency using lysophosphatidic acid, we ‘trap’ and maintain cells in a lineage-biased stem cell state through multiple passages. These cells correspond to a normal state on the differentiation trajectory, the plasticity of which is evidenced by their reacquisition of an unbiased state upon removal of differentiation cues. The use of ‘cross-antagonistic’ signalling to trap pluripotent stem cell intermediates with different lineage-bias may have general applicability in the efficient production of cells for regenerative medicine.
Hysteresis of tropical forests in the 21st century
Authors: Staal Arie , Fetzer Ingo , Wang-Erlandsson Lan , Bosmans Joyce H. C. , Dekker Stefan C. , van Nes Egbert H. , Rockström Johan , Tuinenburg Obbe A. 
Published: October 2020

AbstractTropical forests modify the conditions they depend on through feedbacks at different spatial scales. These feedbacks shape the hysteresis (history-dependence) of tropical forests, thus controlling their resilience to deforestation and response to climate change. Here, we determine the emergent hysteresis from local-scale tipping points and regional-scale forest-rainfall feedbacks across the tropics under the recent climate and a severe climate-change scenario. By integrating remote sensing, a global hydrological model, and detailed atmospheric moisture tracking simulations, we find that forest-rainfall feedback expands the geographic range of possible forest distributions, especially in the Amazon. The Amazon forest could partially recover from complete deforestation, but may lose that resilience later this century. The Congo forest currently lacks resilience, but is predicted to gain it under climate change, whereas forests in Australasia are resilient under both current and future climates. Our results show how tropical forests shape their own distributions and create the climatic conditions that enable them.
Episodes of fast crystal growth in pegmatites
Authors: Phelps Patrick R. , Lee Cin-Ty A. , Morton Douglas M. 
Published: October 2020

AbstractPegmatites are shallow, coarse-grained magmatic intrusions with crystals occasionally approaching meters in length. Compared to their plutonic hosts, pegmatites are thought to have cooled rapidly, suggesting that these large crystals must have grown fast. Growth rates and conditions, however, remain poorly constrained. Here we investigate quartz crystals and their trace element compositions from miarolitic cavities in the Stewart pegmatite in southern California, USA, to quantify crystal growth rates. Trace element concentrations deviate considerably from equilibrium and are best explained by kinetic effects associated with rapid crystal growth. Kinetic crystal growth theory is used to show that crystals accelerated from an initial growth rate of 10−6–10−7 m s−1 to 10−5–10−4 m s−1 (10-100 mm day−1 to 1–10 m day−1), indicating meter sized crystals could have formed within days, if these rates are sustained throughout pegmatite formation. The rapid growth rates require that quartz crystals grew from thin (micron scale) chemical boundary layers at the fluid-crystal interfaces. A strong advective component is required to sustain such thin boundary layers. Turbulent conditions (high Reynolds number) in these miarolitic cavities are shown to exist during crystallization, suggesting that volatile exsolution, crystallization, and cavity generation occur together.
Progression from being at-risk to psychosis: next steps
Authors: Addington Jean , Farris Megan , Devoe Daniel , Metzak Paul 
Published: October 2020

AbstractOver the past 20 years there has been a great deal of research into those considered to be at risk for developing psychosis. Much has been learned and studies have been encouraging. The aim of this paper is to offer an update of the current status of research on risk for psychosis, and what the next steps might be in examining the progression from CHR to psychosis. Advances have been made in accurate prediction, yet there are some methodological issues in ascertainment, diagnosis, the use of data-driven selection methods and lack of external validation. Although there have been several high-quality treatment trials the heterogeneity of this clinical high-risk population has to be addressed so that their treatment needs can be properly met. Recommendations for the future include more collaborative research programmes, and ensuring they are accessible and harmonized with respect to criteria and outcomes so that the field can continue to move forward with the development of large collaborative consortiums as well as increased funding for multisite projects.
The MARAS dataset, vegetation and soil characteristics of dryland rangelands across Patagonia
Authors: Oliva Gabriel , dos Santos Eder , Sofía Osiris , Umaña Fernando , Massara Virginia , García Martínez Guillermo , Caruso Cecilia , Cariac German , Echevarría Daniela , Fantozzi Anabella , Butti Lucas , Bran Donaldo , Gaitán Juan , Ferrante Daniela , Paredes Paula , Domínguez Erwin , Maestre Fernando T. 
Published: October 2020

AbstractWe present the MARAS (Environmental Monitoring of Arid and Semiarid Regions) dataset, which stores vegetation and soil data of 426 rangeland monitoring plots installed throughout Patagonia, a 624.500 km2 area of southern Argentina and Chile. Data for each monitoring plot includes basic climatic and landscape features, photographs, 500 point intercepts for vegetation cover, plant species list and biodiversity indexes, 50-m line-intercept transect for vegetation spatial pattern analysis, land function indexes drawn from 11 measures of soil surface characteristics and laboratory soil analysis (pH, conductivity, organic matter, N and texture). Monitoring plots were installed between 2007 and 2019, and are being reassessed at 5-year intervals (247 have been surveyed twice). The MARAS dataset provides a baseline from which to evaluate the impacts of climate change and changes in land use intensity in Patagonian ecosystems, which collectively constitute one of the world´s largest rangeland areas. This dataset will be of interest to scientists exploring key ecological questions such as biodiversity-ecosystem functioning relationships, plant-soil interactions and climatic controls on ecosystem structure and functioning.
Air pollution emissions from Chinese power plants based on the continuous emission monitoring systems network
Authors: Tang Ling , Xue Xiaoda , Qu Jiabao , Mi Zhifu , Bo Xin , Chang Xiangyu , Wang Shouyang , Li Shibei , Cui Weigeng , Dong Guangxia 
Published: October 2020

AbstractTo meet the growing electricity demand, China’s power generation sector has become an increasingly large source of air pollutants. Specific control policymaking needs an inventory reflecting the overall, heterogeneous, time-varying features of power plant emissions. Due to the lack of comprehensive real measurements, existing inventories rely on average emission factors that suffer from many assumptions and high uncertainty. This study is the first to develop an inventory of particulate matter (PM), SO2 and NOX emissions from power plants using systematic actual measurements monitored by China’s continuous emission monitoring systems (CEMS) network over 96–98% of the total thermal power capacity. With nationwide, source-level, real-time CEMS-monitored data, this study directly estimates emission factors and absolute emissions, avoiding the use of indirect average emission factors, thereby reducing the level of uncertainty. This dataset provides plant-level information on absolute emissions, fuel uses, generating capacities, geographic locations, etc. The dataset facilitates power emission characterization and clean air policy-making, and the CEMS-based estimation method can be employed by other countries seeking to regulate their power emissions.
RETRACTED ARTICLE: Genome assembly and annotation of Meloidogyne enterolobii, an emerging parthenogenetic root-knot nematode
Authors: Koutsovoulos Georgios D. , Poullet Marine , Elashry Abdelnaser , Kozlowski Djampa K. L. , Sallet Erika , Da Rocha Martine , Perfus-Barbeoch Laetitia , Martin-Jimenez Cristina , Frey Juerg Ernst , Ahrens Christian H. , Kiewnick Sebastian , Danchin Etienne G. J. 
Published: October 2020

Abstract
Root-knot nematodes (genus Meloidogyne) are plant parasites causing huge economic loss in the agricultural industry and affecting severely numerous developing countries. Control methods against these plant pests are sparse, the preferred one being the deployment of plant cultivars bearing resistance genes against Meloidogyne species. However, M. enterolobii is not controlled by the resistance genes deployed in the crop plants cultivated in Europe. The recent identification of this species in Europe is thus a major concern. Here, we sequenced the genome of M. enterolobii using short and long-read technologies. The genome assembly spans 240 Mbp with contig N50 size of 143 kbp, enabling high-quality annotations of 59,773 coding genes, 4,068 non-coding genes, and 10,944 transposable elements (spanning 8.7% of the genome). We validated the genome size by flow cytometry and the structure, quality and completeness by bioinformatics metrics. This ensemble of resources will fuel future projects aiming at pinpointing the genome singularities, the origin, diversity, and adaptive potential of this emerging plant pest.
Frequency-dependent circuits anchored in the dorsal and ventral left anterior insula
Authors: Wang Yifeng , Zou Qijun , Ao Yujia , Liu Yang , Ouyang Yujie , Wang Xinqi , Biswal Bharat , Cui Qian , Chen Huafu 
Published: October 2020

AbstractThe hub role of the right anterior insula (AI) has been emphasized in cognitive neurosciences and been demonstrated to be frequency-dependently organized. However, the functional organization of left AI (LAI) has not been systematically investigated. Here we used 100 unrelated datasets from the Human Connectome Project to study the frequency-dependent organization of LAI along slow 6 to slow 1 bands. The broadband functional connectivity of LAI was similar to previous findings. In slow 6-slow 3 bands, both dorsal and ventral seeds in LAI were correlated to the salience network (SN) and language network (LN) and anti-correlated to the default mode network (DMN). However, these seeds were only correlated to the LAI in slow 2-slow 1 bands. These findings indicate that broadband and narrow band functional connections reflect different functional organizations of the LAI. Furthermore, the dorsal seed had a stronger connection with the LN and anti-correlation with DMN while the ventral seed had a stronger connection within the SN in slow 6-slow 3 bands. In slow 2-slow 1 bands, both seeds had stronger connections with themselves. These observations indicate distinctive functional organizations for the two parts of LAI. Significant frequency effect and frequency by seed interaction were also found, suggesting different frequency characteristics of these two seeds. The functional integration and functional segregation of LDAI and LVAI were further supported by their cognitive associations. The frequency- and seed-dependent functional organizations of LAI may enlighten future clinical and cognitive investigations.
Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region
Authors: Aubreville Marc , Bertram Christof A. , Marzahl Christian , Gurtner Corinne , Dettwiler Martina , Schmidt Anja , Bartenschlager Florian , Merz Sophie , Fragoso Marco , Kershaw Olivia , Klopfleisch Robert , Maier Andreas 
Published: October 2020

AbstractManual count of mitotic figures, which is determined in the tumor region with the highest mitotic activity, is a key parameter of most tumor grading schemes. It can be, however, strongly dependent on the area selection due to uneven mitotic figure distribution in the tumor section. We aimed to assess the question, how significantly the area selection could impact the mitotic count, which has a known high inter-rater disagreement. On a data set of 32 whole slide images of H&E-stained canine cutaneous mast cell tumor, fully annotated for mitotic figures, we asked eight veterinary pathologists (five board-certified, three in training) to select a field of interest for the mitotic count. To assess the potential difference on the mitotic count, we compared the mitotic count of the selected regions to the overall distribution on the slide. Additionally, we evaluated three deep learning-based methods for the assessment of highest mitotic density: In one approach, the model would directly try to predict the mitotic count for the presented image patches as a regression task. The second method aims at deriving a segmentation mask for mitotic figures, which is then used to obtain a mitotic density. Finally, we evaluated a two-stage object-detection pipeline based on state-of-the-art architectures to identify individual mitotic figures. We found that the predictions by all models were, on average, better than those of the experts. The two-stage object detector performed best and outperformed most of the human pathologists on the majority of tumor cases. The correlation between the predicted and the ground truth mitotic count was also best for this approach (0.963–0.979). Further, we found considerable differences in position selection between pathologists, which could partially explain the high variance that has been reported for the manual mitotic count. To achieve better inter-rater agreement, we propose to use a computer-based area selection for support of the pathologist in the manual mitotic count.