bluuebunny/crossref_metadata_2025_split huggingface dataset:
Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models
Authors: Parsons L.A. , Hakim G.J. 
Published: August 2019

AbstractDespite the importance of interdecadal climate variability, we have a limited understanding of which geographic regions are associated with global temperature variability at these timescales. The instrumental record tends to be too short to develop sample statistics to study interdecadal climate variability, and Coupled Model Intercomparison Project, Phase 5 (CMIP5) climate models tend to disagree about which locations most strongly influence global mean interdecadal temperature variability. Here we use a new paleoclimate data assimilation product, the Last Millennium Reanalysis (LMR), to examine where local variability is associated with global mean temperature variability at interdecadal timescales. The LMR framework uses an ensemble Kalman filter data assimilation approach to combine the latest paleoclimate data and state‐of‐the‐art model data to generate annually resolved field reconstructions of surface temperature, which allow us to explore the timing and dynamics of preinstrumental climate variability in new ways. The LMR consistently shows that the middle‐ to high‐latitude north Pacific and the high‐latitude North Atlantic tend to lead global temperature variability on interdecadal timescales. These findings have important implications for understanding the dynamics of low‐frequency climate variability in the preindustrial era.
Simple and Applicable Method for Estimating Evapotranspiration and Its Components in Arid Regions
Authors: Xiong Yu Jiu , Zhao Wen Li , Wang Pei , Paw U Kyaw Tha , Qiu Guo Yu 
Published: August 2019

AbstractLand evapotranspiration (ET), which involves the exchange of energy and water between the atmosphere and land, is dynamic and affects the spatiotemporal distribution of water resources, a key limiting factor in arid regions. The accurate quantification of ET and its two components, that is, soil evaporation (Es) and vegetation transpiration (Ev), is crucial for managing water resources to ensure sustainable development. However, estimating ET and its components is challenging due to limitations associated with the structure and parameterization of models. The three‐temperature (3T) model, which includes limited inputs that are key to the ET process (e.g., net radiation and temperature), is hypothesized to be robust. In conjunction with the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project, this study was performed in a heterogeneous oasis in northwestern China using relatively high‐density eddy covariance observations. The mean absolute percent error values of the ET and its components estimated with the 3T model from the field scale (flux observations as model inputs) to large scales (Fluke, Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER] and Moderate Resolution Imaging Spectroradiometer [MODIS] data as model inputs) range from 9 to 25% over different landscapes. The ET estimates from the simple 3T model contained less bias than those from the Penman‐Monteith equation, which requires more model inputs and parameterization. When the components were separated in the 3T model based on high‐resolution images, such as Fluke and ASTER, the Ev/ET values were comparable to the isotope‐based observations, and the mean absolute percent error values were <10%. With its limited inputs, the 3T model is able to simply and easily estimate ET and its components.
Organic Aerosol Processing During Winter Severe Haze Episodes in Beijing
Authors: Zhao Jian , Qiu Yanmei , Zhou Wei , Xu Weiqi , Wang Junfeng , Zhang Yingjie , Li Linjie , Xie Conghui , Wang Qingqing , Du Wei , Worsnop Douglas R. , Canagaratna Manjula R. , Zhou Libo , Ge Xinlei , Fu Pingqing , Li Jie , Wang Zifa , Donahue Neil M. , Sun Yele 
Published: August 2019

AbstractOrganic aerosol (OA) constituted a large fraction of aerosol particles during severe haze episodes in winter in northern China, yet our understanding of its physical and chemical processing was limited. Here we investigate the sources and processes of OA during four haze episodes in winter in 2016 using high‐resolution aerosol mass spectrometer. The PM2.5 reached 400 μg/m3 during the severest episode (Ep1) when Beijing issued a red alert and implemented strict emission controls. Our results showed that secondary OA (SOA) dominated OA during haze episodes on average accounting for 46–66% of OA and was comparable to secondary inorganic aerosol (SIA) with the SOA/SIA ratios being 0.51–0.72. Primary OA from fossil‐fuel combustion, biomass burning, and cooking presented very strong diurnal variations during haze episodes and contributed up to 60% in OA at night. Comparatively, the changes in semivolatile and low‐volatility SOA were relatively small except a substantial increase in aqueous phase‐related oxidized OA (aq‐OOA) during Ep1 with high relative humidity and aerosol water content. aq‐OOA fell well into a small region in the middle of the triangle plot of f44 versus f43 (fraction of m/z 44 and 43 in OA, respectively), which can be used as a diagnostic for the presence of aqueous phase processing of SOA. In addition, the increases of SO2+/SO3+ as a function of relative humidity, the triangle plot of
versus
, and high nitrogen‐to‐carbon ratio in aq‐OOA suggest the potential formation of sulfur‐ and nitrogen‐containing organic compounds through aqueous phase processing.
Reventilation Episodes During the Sapropel S1 Deposition in the Eastern Mediterranean Based on Holococcolith Preservation
Authors: Incarbona Alessandro , Abu‐Zied Ramadan H. , Rohling Eelco J. , Ziveri Patrizia 
Published: September 2019

AbstractOrganic‐rich layers (sapropels), preserved in eastern Mediterranean marine sediment records, represent pronounced perturbations to thermohaline circulation and environmental conditions in the basin, in response to enhanced African monsoon activity and subsequent massive freshwater discharge. During the most recent event, Sapropel S1 formed between 10.8 and 6.1 ka, when freshwater‐driven stratification caused seafloor anoxia below ~1,800‐m depth, as a result of both failure of deep water formation and enhanced productivity. Here we analyze coccolith assemblages from the open eastern Mediterranean that form a west‐east transect across the basin and provide insights on past environmental changes. We focus on holococcoliths, which are specifically produced by coccolithophores as part of their life cycle during the haploid phase. Since holococcolith calcification is characterized by nanocrystals highly susceptible to dissolution, we are testing their potential preservation under different bottom environmental conditions, including the effect of postdepositional oxidation. A comparison with benthic foraminifera assemblages in a core recovered close to Lybia reveals that holococcolith preservation is enhanced during seafloor reventilation and benthic foraminiferal repopulation in the middle to upper part of the record, before the actual sapropel termination. There are two such events of improved deep‐water oxygenation in the Aegean and Adriatic Seas at 8.2 and 7.4 ka. The latter episode marks the onset of the transition to restored circulation in the eastern Mediterranean Sea, due to resumption of deep‐water formation in the southern Aegean Sea and the conclusion of enhanced biogenic productivity.
Cumulative and Coseismic (During the 2016 Mw6.6 Aketao Earthquake) Deformation of the Dextral‐Slip Muji Fault, Northeastern Pamir Orogen
Authors: Li Tao , Schoenbohm Lindsay M. , Chen Jie , Yuan Zhaode , Feng Wanpeng , Li Wenqiao , Xu Jianhong , Owen Lewis A. , Sobel Edward R. , Zhang Boxuan , Zheng Wenjun , Zhang Peizhen 
Published: August 2019

AbstractLocated at the northwestern syntaxis of the India‐Asia convergence zone, the Pamir orogen is characterized by complicated and strong active deformation. Constraining the detailed geometry and kinematics of major active structures is important both for understanding modern tectonic processes and for evaluating potential seismic hazards of the region. Our work focuses on the Muji Fault in the northeastern Pamir. Based on cumulative deformation recorded by landforms and coseismic deformation during the 2016 Mw6.6 Aketao earthquake, we determine the spatial extent, slip motion, fault‐plane geometry, and slip rate of the fault, on the basis of which we clarify its role in the modern tectonics of the Pamir and investigate its seismic behavior and associated seismic hazards. Our study indicates that (i) the Muji Fault, along with the Kongur Extensional System to its south, acts as a boundary fault that accommodates a relative divergence rate of 1.4–2.0°/Ma between the central‐western and eastern Pamir; (ii) geometric discontinuities along the fault exerted an important control on seismic rupture termination and slip gap formation during the Aketao earthquake; and (iii) the cumulative surface‐faulting deformation cannot be formed coseismically by repetitions of the Aketao earthquake, implying significant aseismic (postseismic and/or interseismic) creeping or possibly larger (approximately Mw7.2), surface‐faulting earthquakes. Our study highlights the usefulness of correlating cumulative and coseismic deformation patterns in active tectonic investigations and regional seismic hazard evaluations.
Predicting superhard materials via a machine learning informed evolutionary structure search
Authors: Avery Patrick , Wang Xiaoyu , Oses Corey , Gossett Eric , Proserpio Davide M. , Toher Cormac , Curtarolo Stefano , Zurek Eva 
Published: September 2019

AbstractThe computational prediction of superhard materials would enable the in silico design of compounds that could be used in a wide variety of technological applications. Herein, good agreement was found between experimental Vickers hardnesses, Hv, of a wide range of materials and those calculated by three macroscopic hardness models that employ the shear and/or bulk moduli obtained from: (i) first principles via AFLOW-AEL (AFLOW Automatic Elastic Library), and (ii) a machine learning (ML) model trained on materials within the AFLOW repository. Because $$H_{\mathrm{v}}^{{\mathrm{ML}}}$$

H

v

ML

values can be quickly estimated, they can be used in conjunction with an evolutionary search to predict stable, superhard materials. This methodology is implemented in the XtalOpt evolutionary algorithm. Each crystal is minimized to the nearest local minimum, and its Vickers hardness is computed via a linear relationship with the shear modulus discovered by Teter. Both the energy/enthalpy and $$H_{{\mathrm{v,Teter}}}^{{\mathrm{ML}}}$$

H

v,Teter

ML

are employed to determine a structure’s fitness. This implementation is applied towards the carbon system, and 43 new superhard phases are found. A topological analysis reveals that phases estimated to be slightly harder than diamond contain a substantial fraction of diamond and/or lonsdaleite.
Health worker and patient views on implementation of smoking cessation in routine tuberculosis care
Authors: Boeckmann Melanie , Warsi Sahil , Noor Maryam , Dogar Omara , Mustagfira Esha Haowa , Firoze Fariza , Zahid Raana , Readshaw Anne , Siddiqi Kamran , Kotz Daniel ,   the TB & Tobacco Consortium, Keding Ada , Gabe Rhian , Marshall Anna , Parrott Steve , Swami Shilpi , Khan Amina , Raja Sonia , Sohail Salman , Huque Rumana , Barua Deepa , Huque Samina , Jahan Iashrat , Fatima Razia , Qadeer Ejaz , Sheikh Aziz , Elsey Helen , Karki Jiban , Králíková Eva , Nohavova Iveta , Zvolska Kamila , Pankova Alexandra , Baral Sushil , Regmi Shophika , Shrestha Prabin , Khanal Sudeepa , Joshi Basant 
Published: September 2019

AbstractSmoking worsens tuberculosis (TB) outcomes. Persons with TB who smoke can benefit from smoking cessation. We report findings of a multi-country qualitative process evaluation assessing barriers and facilitators to implementation of smoking cessation behaviour support in TB clinics in Bangladesh and Pakistan. We conducted semi-structured qualitative interviews at five case study clinics with 35 patients and 8 health workers over a period of 11 months (2017–2018) at different time points during the intervention implementation phase. Interviews were conducted by trained researchers in the native languages, audio-recorded, transcribed into English and analysed using a combined deductive–inductive approach guided by the Consolidated Framework for Implementation Research and Theoretical Domains Framework. All patients report willingness to quit smoking and recent quit attempts. Individuals’ main motivations to quit are their health and the need to financially provide for a family. Behavioural regulation such as avoiding exposure to cigarettes and social influences from friends, family and colleagues are main themes of the interviews. Most male patients do not feel shy admitting to smoking, for the sole female patient interviewee stigma was an issue. Health workers report structural characteristics such as high workload and limited time per patient as primary barriers to offering behavioural support. Self-efficacy to discuss tobacco use with women varies by health worker. Systemic barriers to implementation such as staff workload and socio-cultural barriers to cessation like gender relations, stigma or social influences should be dealt with creatively to optimize the behaviour support for sustainability and scale-up.
Data-driven unsupervised clustering of online learner behaviour
Authors: Peach Robert L. , Yaliraki Sophia N. , Lefevre David , Barahona Mauricio 
Published: September 2019

AbstractThe widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal behaviour directly from the raw data without prescribing a priori subjective reference behaviours. The method uses a dynamic time warping kernel to create a pair-wise similarity between time-series of learner actions, and combines it with an unsupervised multiscale graph clustering algorithm to identify groups of learners with similar temporal behaviour. To showcase our approach, we analyse task completion data from a cohort of learners taking an online post-graduate degree at Imperial Business School. Our analysis reveals clusters of learners with statistically distinct patterns of engagement, from distributed to massed learning, with different levels of regularity, adherence to pre-planned course structure and task completion. The approach also reveals outlier learners with highly sporadic behaviour. A posteriori comparison against student performance shows that, whereas high-performing learners are spread across clusters with diverse temporal engagement, low performers are located significantly in the massed learning cluster, and our unsupervised clustering identifies low performers more accurately than common machine learning classification methods trained on temporal statistics of the data. Finally, we test the applicability of the method by analysing two additional data sets: a different cohort of the same course, and time-series of different format from another university.
Fast Groupwise Registration Using Multi-Level and Multi-Resolution Graph Shrinkage
Authors: Dong Pei , Cao Xiaohuan , Yap Pew-Thian , Shen Dinggang 
Published: September 2019

AbstractGroupwise registration aligns a set of images to a common space. It can however be inefficient and ineffective when dealing with datasets with significant anatomical variations. To mitigate these problems, we propose a groupwise registration framework based on hierarchical multi-level and multi-resolution shrinkage of a graph set. First, to deal with datasets with complex inhomogeneous image distributions, we divide the images hierarchically into multiple clusters. Since the images in each cluster have similar appearances, they can be registered effectively. Second, we employ a multi-resolution strategy to reduce computational cost. Experimental results on two public datasets show that our proposed method yields state-of-the-art registration accuracy with significantly reduced computational time.
Success of Montreal Protocol Demonstrated by Comparing High-Quality UV Measurements with “World Avoided” Calculations from Two Chemistry-Climate Models
Authors: McKenzie Richard , Bernhard Germar , Liley Ben , Disterhoft Patrick , Rhodes Steve , Bais Alkiviadis , Morgenstern Olaf , Newman Paul , Oman Luke , Brogniez Colette , Simic Stana 
Published: September 2019

AbstractThe Montreal Protocol on Substances that Deplete the Ozone Layer has been hailed as the most successful environmental treaty ever (https://www.unenvironment.org/news-and-stories/story/montreal-protocol-triumph-treaty). Yet, although our main concern about ozone depletion is the subsequent increase in harmful solar UV radiation at the Earth’s surface, no studies to date have demonstrated its effectiveness in that regard. Here we use long-term UV Index (UVI) data derived from high-quality UV spectroradiometer measurements to demonstrate its success in curbing increases in UV radiation. Without this landmark agreement, UVI values would have increased at mid-latitude locations by approximately 20% between the early 1990s and today and would approximately quadruple at mid-latitudes by 2100. In contrast, an analysis of UVI data from multiple clean-air sites shows that maximum daily UVI values have remained essentially constant over the last ~20 years in all seasons, and may even have decreased slightly in the southern hemisphere, especially in Antarctica, where effects of ozone depletion were larger. Reconstructions of the UVI from total ozone data show evidence of increasing UVI levels in the 1980s, but unfortunately, there are no high-quality UV measurements available prior to the early 1990s to confirm these increases with direct observations.
Model of Anisotropic Reverse Cardiac Growth in Mechanical Dyssynchrony
Authors: Arumugam Jayavel , Mojumder Joy , Kassab Ghassan , Lee Lik Chuan 
Published: September 2019

AbstractBased on recent single-cell experiments showing that longitudinal myocyte stretch produces both parallel and serial addition of sarcomeres, we developed an anisotropic growth constitutive model with elastic myofiber stretch as the growth stimuli to simulate long-term changes in biventricular geometry associated with alterations in cardiac electromechanics. The constitutive model is developed based on the volumetric growth framework. In the model, local growth evolutions of the myocyte’s longitudinal and transverse directions are driven by the deviations of maximum elastic myofiber stretch over a cardiac cycle from its corresponding local homeostatic set point, but with different sensitivities. Local homeostatic set point is determined from a simulation with normal activation pattern. The growth constitutive model is coupled to an electromechanics model and calibrated based on both global and local ventricular geometrical changes associated with chronic left ventricular free wall pacing found in previous animal experiments. We show that the coupled electromechanics-growth model can quantitatively reproduce the following: (1) Thinning and thickening of the ventricular wall respectively at early and late activated regions and (2) Global left ventricular dilation as measured in experiments. These findings reinforce the role of elastic myofiber stretch as a growth stimulant at both cellular level and tissue-level.
The influence of inter-particle forces on diffusion at the nanoscale
Authors: Giorgi Francesco , Coglitore Diego , Curran Judith M. , Gilliland Douglas , Macko Peter , Whelan Maurice , Worth Andrew , Patterson Eann A. 
Published: September 2019

AbstractVan der Waals and electrostatic interactions are the dominant forces acting at the nanoscale and they have been reported to directly influence a range of phenomena including surface adhesion, friction, and colloid stability but their contribution on nanoparticle diffusion dynamics is still not clear. In this study we evaluated experimentally the changes in the diffusion coefficient of nanoparticles as a result of varying the magnitude of Van der Waals and electrostatic forces. We controlled the magnitude of these forces by varying the ionic strength of a salt solution, which has been shown to be a parameter that directly controls the forces, and found by tracking single nanoparticles dispersed in solutions with different salt molarity that the diffusion of nanoparticles increases with the magnitude of the electrostatic forces and Van der Waals forces. Our results demonstrate that these two concurrently dynamic forces play a pivotal role in driving the diffusion process and must be taken into account when considering nanoparticle behaviour.
Transcriptomic and functional analyses of 3D placental extravillous trophoblast spheroids
Authors: Wong Michael K. , Wahed Mishquatul , Shawky Sarah A. , Dvorkin-Gheva Anna , Raha Sandeep 
Published: August 2019

AbstractPlacental extravillous trophoblast (EVT) invasion is essential in establishing proper blood supply to the fetus during pregnancy. However, traditional 2D in vitro systems do not model the in vivo invasion process in an anatomically-relevant manner. Our objectives were to develop a 3D spheroid model that would allow better emulation of placental invasion in vitro and to characterize the transcriptomic and functional outcomes. HTR8/SVneo EVT cells were self-assembled into 3D spheroids using ultra-low attachment plates. Transcriptomic profiling followed by gene set enrichment and gene ontology analyses revealed major global transcriptomic differences, with significant up-regulations in EVTs cultured as 3D spheroids in canonical pathways and biological processes such as immune response, angiogenesis, response to stimulus, wound healing, and others. These findings were further validated by RT-qPCR, showing significant up-regulations in genes and/or proteins related to epithelial-mesenchymal transition, cell-cell contact, angiogenesis, and invasion/migration. A high-throughput, spheroid invasion assay was applied to reveal the dynamic invasion of EVTs away from the spheroid core into extracellular matrix. Lastly, lipopolysaccharide, dexamethasone, or Δ9-tetrahydrocannabinol exposure was found to impact the invasion of EVT spheroids. Altogether, we present a well-characterized, 3D spheroid model of EVT invasion and demonstrate its potential use in drug and toxin screening during pregnancy.
M1-like macrophage polarization prevails in young children with classic Hodgkin Lymphoma from Argentina
Authors: Jimenez O. , Barros M. H. , De Matteo E. , Garcia Lombardi M. , Preciado M. V. , Niedobitek G. , Chabay P. 
Published: September 2019

AbstractThe microenvironment in classical Hodgkin lymphoma (cHL) comprises a mixture of different types of cells, which are responsible for lymphoma pathogenesis and progression. Even though microenvironment composition in adult cHL has been largely studied, only few groups studied pediatric cHL, in which both Epstein Barr virus (EBV) infection and age may display a role in their pathogenesis. Furthermore, our group described that EBV is significantly associated with cHL in Argentina in patients under the age of 10 years old. For that reason, our aim was to describe the microenvironment composition in 46 pediatric cHL patients. M1-like polarization status prevailed in the whole series independently of EBV association. On the other hand, in children older than 10 years, a tolerogenic environment illustrated by higher FOXP3 expression was proved, accompanied by a macrophage polarization status towards M2. In contrast, in children younger than 10 years, M1-like was prevalent, along with an increase in cytotoxic GrB+ cells. This study supports the notion that pediatric cHL exhibits a particular tumor microenvironment composition.