bluuebunny/crossref_metadata_2025 huggingface dataset:
Candidate Brown-dwarf Microlensing Events with Very Short Timescales and Small Angular Einstein Radii
Authors: Han Cheongho , Lee Chung-Uk , Udalski Andrzej , Gould Andrew , Bond Ian A. , Bozza Valerio ,   (LEADING AUTHORS), Albrow Michael D. , Chung Sun-Ju , Hwang Kyu-Ha , Jung Youn Kil , Ryu Yoon-Hyun , Shin In-Gu , Shvartzvald Yossi , Yee Jennifer C. , Zang Weicheng , Cha Sang-Mok , Kim Dong-Jin , Kim Hyoun-Woo , Kim Seung-Lee , Lee Dong-Joo , Lee Yongseok , Park Byeong-Gon , Pogge Richard W. , Jee M. James , Kim Doeon ,   (The KMTNet Collaboration), Mróz Przemek , Szymański Michał K. , Skowron Jan , Poleski Radek , Soszyński Igor , Pietrukowicz Paweł , Kozłowski Szymon , Ulaczyk Krzysztof , Rybicki Krzysztof A. , Iwanek Patryk , Wrona Marcin ,   (The OGLE Collaboration), Abe Fumio , Barry Richard , Bennett David P. , Bhattacharya Aparna , Donachie Martin , Fujii Hirosane , Fukui Akihiko , Itow Yoshitaka , Hirao Yuki , Kamei Yuhei , Kondo Iona , Koshimoto Naoki , Li Man Cheung Alex , Matsubara Yutaka , Muraki Yasushi , Miyazaki Shota , Nagakane Masayuki , Ranc Clément , Rattenbury Nicholas J. , Satoh Yuki , Shoji Hikaru , Suematsu Haruno , Sullivan Denis J. , Sumi Takahiro , Suzuki Daisuke , Tristram Paul J. , Yamakawa Takeharu , Yamawaki Tsubasa , Yonehara Atsunori ,   (The MOA Collaboration)
Published: February 2020

Short-timescale microlensing events are likely to be produced by substellar brown dwarfs (BDs), but it is difficult to securely identify BD lenses based on only event timescales

because short-timescale events can also be produced by stellar lenses with high relative lens-source proper motions. In this paper, we report three strong candidate BD-lens events found from the search for lensing events not only with short timescales (

) but also with very small angular Einstein radii (

) among the events that have been found in the 2016–2019 observing seasons. These events include MOA-2017-BLG-147, MOA-2017-BLG-241, and MOA-2019-BLG-256, in which the first two events are produced by single lenses and the last event is produced by a binary lens. From the Monte Carlo simulations of Galactic events conducted with the combined

and

constraint, it is estimated that the lens masses of the individual events are

,

, and

and the probability of the lens mass smaller than the lower limit of stars is ∼80% for all events. We point out that routine lens mass measurements of short-timescale lensing events require survey-mode space-based observations.
SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey
Authors: Wang Rui , Luo A-Li , Chen Jian-Jun , Hou Wen , Zhang Shuo , Zhao Yong-Heng , Li Xiang-Ru , Hou Yong-Hui ,   LAMOST MRS Collaboration
Published: February 2020

The fundamental stellar atmospheric parameters (T
eff and log g) and 13 chemical abundances are derived for medium-resolution spectroscopy from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Medium Resolution Survey (MRS) data sets with a deep-learning method. The neural networks we designed, named SPCANet, precisely map LAMOST MRS spectra to stellar parameters and chemical abundances. The stellar labels derived by SPCANet have precisions of 119 K for T
eff and 0.17 dex for log g. The abundance precision of 11 elements including [C/H], [N/H], [O/H], [Mg/H], [Al/H], [Si/H], [S/H], [Ca/H], [Ti/H], [Cr/H], [Fe/H], and [Ni/H] are 0.06 ∼ 0.12 dex, while that of [Cu/H] is 0.19 dex. These precisions can be reached even for spectra with signal-to-noise ratios as low as 10. The results of SPCANet are consistent with those from other surveys such as APOGEE, GALAH, and RAVE, and are also validated with the previous literature values including clusters and field stars. The catalog of the estimated parameters is available at doi:10.12149/101012.
KMTNet Nearby Galaxy Survey II. Searching for Dwarf Galaxies in Deep and Wide-field Images of the NGC 1291 System
Authors: Byun Woowon , Sheen Yun-Kyeong , Park Hong Soo , Ho Luis C. , Lee Joon Hyeop , Kim Sang Chul , Jeong Hyunjin , Park Byeong-Gon , Seon Kwang-Il , Lee Youngdae , Lee Yongseok , Cha Sang-Mok , Ko Jongwan , Kim Minjin
Published: February 2020

We present newly discovered dwarf galaxy candidates in deep and wide-field images of NGC 1291 obtained with the Korea Microlensing Telescope Network. We identify 15 dwarf galaxy candidates by visual inspection. Using imaging simulations, we demonstrate that the completeness rate of our detection is greater than 70% for the central surface-brightness value of μ
0,R
 ≲ 26 mag arcsec−2 and for magnitudes M

R
 ≲ −10 mag. The structural and photometric properties of the dwarf galaxy candidates appear to be broadly consistent with those of ordinary dwarf galaxies in nearby groups and clusters, with μ
0,R
 ∼ 22.5 to 26.5 mag arcsec−2 and effective radii of 200 pc to 1 kpc. The dwarf galaxy candidates show a concentration toward NGC 1291 and tend to be redder the closer they are to the center, possibly indicating that they are associated with NGC 1291. The dwarf candidates presented in this paper appear to be bluer than those in denser environments, revealing that the quenching of star formation in dwarf galaxies is susceptible to the environment, while the morphology shaping is not.
Real-time Flare Prediction Based on Distinctions between Flaring and Non-flaring Active Region Spectra
Authors: Panos Brandon , Kleint Lucia
Published: February 2020

With machine learning entering into the awareness of the heliophysics community, solar flare prediction has become a topic of increased interest. Although machine-learning models have advanced with each successive publication, the input data has remained largely fixed on magnetic features. Despite this increased model complexity, results seem to indicate that photospheric magnetic field data alone may not be a wholly sufficient source of data for flare prediction. For the first time, we have extended the study of flare prediction to spectral data. In this work, we use Deep Neural Networks to monitor the changes of several features derived from the strong resonant Mg II h and k lines observed by the Interface Region Imaging Spectrograph. The features in descending order of predictive capability are: the triplet emission at 2798.77 Å, line core intensity, total continuum emission between the h and k line cores, the k/h ratio, line width, followed by several other line features such as asymmetry and line center. Regions that are about to flare generate spectra that are distinguishable from non-flaring active region spectra. Our algorithm can correctly identify pre-flare spectra approximately 35 minutes before the start of the flare, with an AUC of 86% and an accuracy, precision, and recall of 80%. The accuracy and AUC monotonically increase to 90% and 97%, respectively, as we move closer in time to the start of the flare. Our study indicates that spectral data alone can lead to good predictive models and should be considered an additional source of information alongside photospheric magnetograms.
The Mysterious Location of Maryland on 2014 MU69 and the Reconfiguration of Its Bilobate Shape
Authors: Hirabayashi Masatoshi , Trowbridge Alexander J. , Bodewits Dennis
Published: February 2020

2014 MU69 (named Arrokoth), targeted by New Horizons, has a unique bilobate shape. Research suggested that there is a large circular depression feature with a diameter of ∼7 km on the smaller lobe of this object. This feature, called Maryland, is surrounded by topographically high regions and faces perpendicular to the shortest axis of this object. Here, following the interpretation by earlier work that Maryland is formed by an impact, we investigate how the Maryland impact affects the structure of a neck of this object. We find that to avoid a structural breakup driven by this impact, MU69 needs high cohesive strength, at least tens of kilopascals depending on the bulk density. The cohesive strength at this level is much higher than that of other small bodies observed at high resolution, which is usually reported to be a few hundred pascals. It may be possible that MU69 actually has such a high cohesive strength, which may challenge the current knowledge about the cohesive strength of small bodies. Alternatively, we hypothesize a scenario that the Maryland impact actually broke the neck structure and made the shape settle into the current configuration. Considering this scenario, we obtain that the bulk density of MU69 should be between 300 and 500 kg m−3.
Implementation and Analysis of a Smart Team Management System Using iOS Devices As iBeacon
Authors: S Sindhumol
Published: February 2020

A cost-effective smart team management system using iOS devices as iBeacon for better task monitoring and presence detection is proposed in this work. It is designed to maximum utilize the proximity information offered by iOS devices through iBeacon integration. In addition to this positioning service, iOS core location framework, geofencing and push notifications features are also included in this work, to create a productive environment in an organization. Along with the employee tracking and task monitoring features, the proposed application provides the typical project management services like task allocation and notification, instant chat, status report, and employee log. On entering the iBeacon range, daily task details and announcements from all associated teams will be available in team member devices. The system is connected to a server for productive team management, and peer to peer communication is utilized for instant exchange of information. An experimental evaluation to study the effect of interference, obstacles, and measured power on received signal strength and accuracy of the proposed iBeacon is also conducted. The observed results positively recommend the proposed app as an efficient iBeacon application for project management.
Smartphone Crowdsourcing and Data Sharing Towards Advancing User Experience and Mobile Services
Authors: Alepis Efthymios , Kontogianni Aristea
Published: February 2020

Recent advances in IT have offered people the opportunity to have powerful ultramobile devices in their pockets incorporating a plethora of capabilities which, in most cases, require Internet connectivity. This constant need for Internet access though, especially when a wireless hotspot is unavailable requires connection via network data. The fixed cellular data packages offered by carriers usually do not come for free and to a large extend cannot be adapted to the dynamic needs of users who sometimes need more than they own, while in other cases under-use their network data.  This issue, in combination with the fact that signal quality in many areas is not even fair for one or more carriers has led to the development of a novel android application that aims at allowing users in general and tourists to “foresee” bad signal coverage at places of their interest, as well as to share their cellular data via mobile tethering.
Enhanced Bootstrapping Algorithm for Automatic Annotation of Tweets
Authors: Mohd Mudasir , Jan Rafiya , Hakak Nida
Published: February 2020

Annotations are critical in various text mining tasks such as opinion mining, sentiment analysis, word sense disambiguation. Supervised learning algorithms start with the training of the classifier and require manually annotated datasets. However, manual annotations are often subjective, biased, onerous, and burdensome to develop; therefore, there is a need for automatic annotation. Automatic annotators automatically annotate the data for creating the training set for the supervised classifier, but lack subjectivity and ignore semantics of underlying textual structures. The objective of this research is to develop scalable and semantically rich automatic annotation system while incorporating domain dependent characteristics of the annotation process. The authors devised an enhanced bootstrapping algorithm for the automatic annotation of Tweets and employed distributional semantic models (LSA and Word2Vec) to augment the novel Bootstrapping algorithm and tested the proposed algorithm on the 12,000 crowd-sourced annotated Tweets and achieved a 68.56% accuracy which is higher than the baseline accuracy.
Exploiting Visual Features in Financial Time Series Prediction
Authors: Karaçor Adil Gürsel , Erkan Turan Erman
Published: February 2020

The possibility to enhance prediction accuracy for foreign exchange rates was investigated in two ways: first applying an outside the box approach to modeling price graphs by exploiting their visual properties, and secondly employing the most efficient methods to detect patterns to classify the direction of movement. The approach that exploits the visual properties of price graphs which make use of density regions along with high and low values describing the shape; hence, the authors propose the name ‘Finance Vision.' The data used in the predictive model consists of 1-hour past price values of 4 different currency pairs, between 2003 and 2016. Prediction performances of state-of-the-art methods; Extreme Gradient Boosting, Artificial Neural Network and Support Vector Machines are compared over the same data with the same sets of features. Results show that density based visual features contribute considerably to prediction performance.
Data Analytic Techniques for Developing Decision Support System on Agrometeorological Parameters for Farmers
Authors: Sowmya B.J.  , Krishna Chaitanya S.  , Seema S. , Srinivasa K.G.
Published: February 2020

The day-to-day lives of humans are changing remarkably due to the evolution in tools, techniques and technology across the planet. This evolution is not only impacting the growth of humans but also contributing to the growth and well-being of society and country. The domain of data analytics (DA) and internet of things (IoT) is very much facilitating this growth. But there have been only a handful of innovations and explorations in the field of agriculture, although it being the backbone and largely contributing to the gross domestic product (GDP) of a country like India. The reason for it may be profuse, such as the erratic weather conditions, improper irrigation, farmers being skeptical using modern tools and many more. But being in a developing country that has its primary focus on invention and innovation, a consensus has to be reached so that the modern tools and technologies, abet agriculture throughout the country. In our work, an attempt is made to analyze the different aspects that influences the variable outcomes in agriculture with the aid of various data analytic algorithms. Rainfall, humidity and temperature are some of the variables that determine the type of crop. Therefore, the task of prediction of crop type given these factors using decision trees and support vector machines (SVM) is implemented, and the accuracy of the models are computed. Here, more focus is given to the state of Karnataka and to its major crops. With rice, ragi and maize being some of the predominant crops, an analysis is portrayed considering the yield across the state.
Can We Enable Digital Transition in Healthcare Delivery?
Authors: Occelli Sylvie , Scelfo Bibiana
Published: February 2020

Implementing digital health transition is challenging. Whilst technology progresses rapidly, the appropriation of innovation in healthcare is slower and has to deal with the local context. This is the case with Piedmont, an Italian region where in the last decade a number of telemedicine projects have been launched. In order to assess their implementation a survey has been recently conducted by the regional Health Department. This work builds upon the results of this investigation. The conceptual approach underlying the survey is illustrated and the main findings of the investigation discussed. To examine the regional situation, a notion of telemedicine maturity model is used. By making it explicit the main dimensions entailed in developing an ehealth service, its application can facilitate the digital health transition in the region. A core argument is that to handle the complexity of ehealth projects a collaborative environment for exchanging health knowledge should be implemented.
Interactivity of Digital Media
Authors: Pius Nedumkallel Jose
Published: February 2020

This study reviews the literature on interactivity, a concept which is widely discussed in the context of media, communication, and information systems research. Extant research in these areas suggests that the concept needs timely explication with changes in mediated technologies. In this context, this study reviews the theoretical definitions of interactivity and discusses their relevance and shortcomings in the current scenario. The study also reviews past research works in interactivity based on the type of digital media. The study has categorized the interactivity literature into news, politics, health, e-commerce, mobile communication, and social media. Finally, the study has given directions for future research in each of these areas.
Digital Forensics
Authors: Montasari Reza , Hill Richard , Parkinson Simon , Peltola Pekka , Hosseinian-Far Amin , Daneshkhah Alireza
Published: February 2020

Considering the ever-growing ubiquity of technology, there is an associated growth in the possibility of digital devices related to a criminal investigation or civil litigation. As the variety of digital devices is increasing, the storage capacity of each is also rising exponentially. Due to the varied and large volumes of data produced, law enforcement agencies (LEAs) worldwide are facing a significant backlog of cases. This has culminated in significant delays in dealing with cases that urgently require digital forensic investigations (DFIs). It is of paramount importance that new research approaches be adopted to address such challenges. This article evaluates the existing set of circumstances surrounding the field of digital forensics (DF). The article provides two important contributions to the field of DF; it identifies and analyses the most important mid- and long-term challenges that need to be considered by LEAs. It also proposes important specific future research directions, the undertaking of which can assist LEAs in adopting a new approach to addressing these challenges.
Management Models for Business Incubators
Authors: Machado Andreia de Bem , Catapan Araci Hack , Sousa Maria José
Published: February 2020

The primary goal of this research is to do a systematic review about management models for business incubators. Management models are grounded in three basic pillars: people, processes, and technologies. In this scenario, the business incubator management model is fundamental because it is important for business incubators to meet the demands of new entrepreneurs and entrepreneurship. Therefore, the objective of this research is to map the light of the systematic review of business incubator management models on the world stage. To do so, the methodology used was the integrative review of the literature using the Scopus database and regulations, international and national documents. As a result, one of the problems found in these models was that most business incubator management models describe a business incubator as a transformation mechanism, but do not spell out details about the incubation process or models and best practices for business incubators. management for the continuous improvement of incubated enterprises.
Unparalleled Rapid Evolution of KIR Genes in Rhesus and Cynomolgus Macaque Populations
Authors: Bruijnesteijn Jesse , de Groot Nanine , van der Wiel Marit K. H. , Otting Nel , de Vos-Rouweler Annemiek J. M. , de Groot Natasja G. , Bontrop Ronald E.
Published: February 2020

The killer cell Ig-like receptors (KIR) modulate immune responses through interactions with MHC class I molecules. The KIR region in large cohorts of rhesus and cynomolgus macaque populations were characterized, and the experimental design enabled the definition of a considerable number of alleles (n = 576) and haplotypes, which are highly variable with regard to architecture. Although high levels of polymorphism were recorded, only a few alleles are shared between species and populations. The rapid evolution of allelic polymorphism, accumulated by point mutations, was further confirmed by the emergence of a novel KIR allele in a rhesus macaque family. In addition to allelic variation, abundant orthologous and species-specific KIR genes were identified, the latter of which are frequently generated by fusion events. The concerted action of both genetic mechanisms, in combination with differential selective pressures at the population level, resulted in the unparalleled rapid evolution of the KIR gene region in two closely related macaque species. The variation of the KIR gene repertoire at the species and population level might have an impact on the outcome of preclinical studies with macaque models.
IL-37 Represses the Autoimmunity in Myasthenia Gravis via Directly Targeting Follicular Th and B Cells
Authors: Liu Zhuo , Zhu Liwen , Lu Zhengjuan , Chen Huiping , Fan Lizhen , Xue Qun , Shi Jianquan , Li Meiying , Li Hui , Gong Jie , Shi Jingping , Wang Tao , Jiang Mei-Ling , Cao Runjing , Meng Hailan , Wang Chenhui , Xu Yun , Zhang Cun-Jin
Published: February 2020

IL-37 is a newly identified immune-suppressive factor; however, the function, cellular sources, and mechanism of IL-37 in humoral immunity and Myasthenia gravis (MG) are still unclear. In this study, we found IL-37 were substantially downregulated in the serum and PBMCs of MG patients compared with healthy controls. The lower IL-37 was associated with severer disease (quantitative MG score) and higher follicular Th (Tfh)/Tfh17 and B cell numbers. Flow cytometry analysis revealed that IL-37 was mainly produced by CD4+ T cells without overlapping with Th1, Th17, and Tfh subsets in MG patients. Regulatory IL-37+ T cell rarely expressed Foxp3 and CD25 but produced numerous IL-4. Tfh and B cell expressed high levels of SIGIRR, the receptor of IL-37, in MG patients. Mechanically, IL-37 directly bond to SIGIRR, repressed the proliferation, cytokine production of Tfh and B cells, and the secretion of autoantibody via inhibition of STAT3 signaling in Tfh and B cells.
Opinions of healthcare providers on the design of a smartphone application for asthma treatment in the Kingdom of Saudi Arabia
Authors: Al-Otaibi Hajed M. , Ansari Khalid A. , Hamad Osama , Alanzi Turki M.
Published: February 2020

Introduction: In several countries of the world, smartphone applications have been designed to contribute to the treatment of asthma. However, none of these applications has been developed in Saudi Arabia. Therefore, the objective of this article is to design a smartphone application for the treatment of asthma based on the opinions of healthcare providers from the Kingdom of Saudi Arabia. Methods: In order to know the opinion of the healthcare providers from Saudi Arabia about the design of an asthmaApp, we used a purposive sampling method and conducted a cross sectional survey employing a questionnaire which was distributed through the QuestionPro.com website to all healthcare providers working in this country. The questionnaire was sent to 376 healthcare providers and the response rate was 25%. Results: The data indicated that the majority of the respondents opined that the following features were important or very important in the design of a smartphone application for asthma treatment in Saudi Arabia: information about. patient diagnosis (98%), primary physician access information(83%), patient satisfaction with the therapeutic process (91%), push notifications about reminder for drugs (95%), push notification for treatment of inhaler and other drugs (92%), push notifications about reminders of clinic visits and therapy sections (81%), push notifications to ask for help sending SMS to primary physician about patients’ attacks (89%), pathophysiology of asthma (82%), asthma triggers (98%), drug guidelines (94%), drug side effects (93%), number of asthma attacks (98%), medication statistics (88%), visual inputs such as peak flow (91%), data to link patients to healthcare providers and to healthcare centers (82%), and Global Initiative for Asthma (GINA) references (72%). Conclusions: According to the opinion of the majority of healthcare providers (92%), the proposed smartphone application designed based on medical guidelines will contribute to improve the treatment of patients with asthma in the Kingdom of Saudi Arabia, and will help to reduce the number of asthma cases that need hospitalization, and the number of asthma cases in the emergency departments of the hospitals of the Kingdom.
Nebulized heparin and salbutamol versus salbutamol alone in acute exacerbations of chronic obstructive pulmonary disease requiring mechanical ventilation: a double-blind randomized controlled trial
Authors: Ashoor Tarek Mohamed , Hasseb Ahmad Mahmoud , Esmat Ibrahim Mamdouh
Published: February 2020

BackgroundNebulized heparin has been effectively used in the management of many pulmonary diseases. However, its effect on mechanically ventilated patients with acute exacerbation chronic obstructive pulmonary disease (AECOPD) has never been studied. This study aimed to assess the efficacy of nebulized heparin and salbutamol to increase ventilator-free days (VFD) in mechanically ventilated AECOPD patients and the effect of nebulized heparin on respiratory and coagulation functions.MethodsIn this double-blind controlled study, 60 mechanically ventilated adult patients with AECOPD were randomly allocated into two groups; heparin and salbutamol (HS) group and salbutamol only (S) group. In the HS group, patients received nebulized heparin (25,000 IU) and salbutamol (5 mg) every 6 hours. Patients in the S group received nebulized salbutamol only (5 mg). The treatment was continued while patients remained ventilated for a maximum of 14 days. The primary outcome was VFDs at day 14. PaCO2, PaO2/FiO2 ratio, number of nebulizations withheld, C-reactive protein (CRP) titer and activated partial thromboplastin time (APTT) were secondary outcomes.ResultsPatients in the HS group had significantly more VFDs (4.7 [3.3]) compared with those in the S group (2.4 [2.6]), P = 0.007. PaCO2 levels, PaO2/FiO2, the decrease in the CRP level and the increase in the APTT from the baseline were comparable in both groups.ConclusionsThe co-administration of nebulized heparin and salbutamol, compared with salbutamol alone, significantly increased (VFDs) among mechanically ventilated AECOPD patients without increasing bleeding risks.
Non–Articular Rheumatism
Authors: McDonald Scott W. A. , Blackwood S. H.M.
Published: February 2020

No abstract available.
Warmte-terapie by rumatoïede artritis
Authors: Goedhart Ben
Published: February 2020

No abstract available.
The Bloomsbury Handbook of Global Education and Learning
Authors: Bourn Douglas
Published: February 2020

Learning about global issues and themes has become an increasingly recognised element of education in many countries around the world. Terms such as global learning, global citizenship and global education can be seen within national education policies and international initiatives led by the UN, UNESCO, European Commission and OECD. The Bloomsbury Handbook of Global Education and Learning brings together the main elements of the debates, provides analysis of policies, and suggests new directions for research in these areas. Written by internationally renowned scholars from Brazil, Canada, Finland, Germany, Ireland, Italy, Japan, Pakistan, Poland, South Africa, Spain, Sweden, Taiwan, UK and the USA, the handbook offers a much needed resource for academics, researchers, policy-makers and practitioners who need a clear picture of global learning.
Evaluation of NU-WRF model performance on air quality simulation under various model resolutions – an investigation within the framework of MICS-Asia Phase III
Authors: Tao Zhining , Chin Mian , Gao Meng , Kucsera Tom , Kim Dongchul , Bian Huisheng , Kurokawa Jun-ichi , Wang Yuesi , Liu Zirui , Carmichael Gregory R. , Wang Zifa , Akimoto Hajime
Published: February 2020

Abstract. Horizontal grid resolution has a profound effect on model performances on
meteorology and air quality simulations. In contribution to MICS-Asia Phase III, one of whose goals was to identify and reduce model uncertainty in air quality prediction, this study examined the impact of grid resolution on meteorology and air quality simulation over East Asia, focusing on the North China Plain (NCP) region. The NASA Unified Weather Research and Forecasting (NU-WRF) model has been applied with the horizontal resolutions at 45, 15, and 5 km. The results revealed that, in comparison with ground observations, no single resolution can yield the best model performance for all variables across all stations. From a regional average perspective (i.e., across all monitoring sites), air temperature modeling was not sensitive to the grid resolution but wind and precipitation simulation showed the opposite. NU-WRF with the 5 km grid simulated the wind speed best, while the 45 km grid yielded the most realistic precipitation as compared to the site observations. For air quality simulations, finer resolution generally led to better comparisons with observations for O3, CO, NOx, and PM2.5. However, the improvement of model performance on air quality was not linear with the resolution increase. The accuracy of modeled surface O3 of the 15 km grid was greatly improved over the one from the 45 km grid. A further increase in grid resolution to 5 km, however, showed diminished impact on model performance improvement on O3 prediction. In addition, a 5 km resolution grid showed large advantage in better capturing the frequency of high-pollution occurrences. This was important for the assessment of noncompliance with ambient air quality standards, which was key to air quality planning and management. Balancing the modeling accuracy and resource limitation, a 15 km grid resolution was suggested for future MICS-Asia air quality modeling activity if the research region remained unchanged. This investigation also found a large overestimate of ground-level O3 and an underestimate of surface NOx and CO, likely due to missing emissions of NOx and CO.
A new classification of satellite-derived liquid water cloud regimes at cloud scale
Authors: Unglaub Claudia , Block Karoline , Mülmenstädt Johannes , Sourdeval Odran , Quaas Johannes
Published: February 2020

Abstract. Clouds are highly variable in time and space, affecting climate sensitivity and
climate change. To study and distinguish the different influences of clouds on
the climate system, it is useful to separate clouds into individual cloud
regimes. In this work we present a new cloud classification for liquid water
clouds at cloud scale defined using cloud parameters retrieved from combined
satellite measurements from CloudSat and CALIPSO. The idea is that cloud
heterogeneity is a measure that allows us to distinguish cumuliform and
stratiform clouds, and cloud-base height is a measure to distinguish cloud
altitude. The approach makes use of a newly developed cloud-base height
retrieval. Using three cloud-base
height intervals and two intervals of cloud-top variability as an inhomogeneity parameter
provides six new liquid cloud classes. The results show a smooth transition
between marine and continental clouds as well as between stratiform and
cumuliform clouds in different latitudes at the high spatial resolution of
about 20 km. Analysing the micro- and macrophysical cloud
parameters from
collocated combined MODIS, CloudSat and CALIPSO retrievals shows distinct
characteristics for each cloud regime that are in agreement with expectation
and literature. This demonstrates the usefulness of the classification.
Increase of the particle hit rate in a laser single-particle mass spectrometer by pulse delayed extraction technology
Authors: Chen Ying , Kozlovskiy Viacheslav , Du Xubing , Lv Jinnuo , Nikiforov Sergei , Yu Jiajun , Kolosov Alexander , Gao Wei , Zhou Zhen , Huang Zhengxu , Li Lei
Published: February 2020

Abstract. A single-particle mass spectrometer (SPMS) can provide a
wealth of valuable information on chemical and physical parameters of
individual particles in real time. One of the main performance criteria of
the instrument is efficiency of particle detection (hit rate). Most SPMS
instruments use constant electrical field (DC) extraction, where stationary
high voltage is applied to the extraction electrodes. As the aerosol
particles initially carry a certain charge, those with a high amount to
charge can be deflected by this electric field and lost, thus decreasing the
hit rate. We realized that the delayed extraction technique can eliminate the
stochastic dispersion of the particle beam caused by their deflection in the
stationary electric field. As the result, the hit rate of the instrument can
be significantly improved. Also, as the effect of the deflection in the
electric field is mass dependent, it can cause distortion of the measured
size distribution of the particles. Hence, the delayed extraction technique
can bring the recorded distribution closer to the actual one. We found that
the delayed extraction technique provides a mass resolution improvement as well
as increases the hit rate. The gain in the hit rate depends on the type of
particles. It can be 2 orders of magnitude for model particles and up to
2–4 times for ambient particles. In the present work we report experiments
and results showing the effect of the delayed extraction on the beam
divergence caused by particle charge, the hit rate improvement, and the
effect of the delayed extraction on the measured particle size distribution.
Dissolved inorganic nitrogen and particulate organic nitrogen budget in the Yucatán shelf: driving mechanisms through a physical–biogeochemical coupled model
Authors: Estrada-Allis Sheila N. , Sheinbaum Pardo Julio , Azevedo Correia de Souza Joao M. , Enríquez Ortiz Cecilia Elizabeth , Mariño Tapia Ismael , Herrera-Silveira Jorge A.
Published: February 2020

Abstract. Continental shelves are the most productive areas in the seas with the strongest implications for global nitrogen cycling. The Yucatán shelf (YS) is the largest shelf in the Gulf of Mexico (GoM); however, its nitrogen budget has not been quantified. This is largely due to the lack of significant spatio-temporal in situ measurements and the complexity of the shelf dynamics, including coastal upwelling, coastal-trapped waves (CTWs), and influence of the Yucatán Current (YC) via bottom Ekman transport and dynamic uplift. In this paper, we investigate and quantify the nitrogen budget of dissolved inorganic nitrogen (DIN) and particulate organic nitrogen (PON) in the YS using a 9-year output from a coupled physical–biogeochemical model of the GoM. The sum of DIN and PON is here referred to as total nitrogen (TN). Results indicate that the main entrance of DIN is through its southern (continental) and eastern margins. The TN is then advected to the deep oligotrophic Bay of Campeche and central GoM. It is also shown that the inner shelf (bounded by the 50 m isobath) is “efficient” in terms of TN, since all DIN imported into this shelf is consumed by the phytoplankton. Submarine groundwater discharges (SGDs) contribute 20 % of the TN, while denitrification removes up to 53 % of TN that enters into the inner shelf. The high-frequency variability of the TN fluxes in the southern margin is modulated by fluxes from the YC due to enhanced bottom Ekman transport when the YC leans against the shelf break (250 m isobath) on the eastern margin. This current–topography interaction can help to maintain the upwelling of Cape Catoche, uplifting nutrient-rich water into the euphotic layer. The export of TN at both western and northwestern margins is modulated by CTWs with a mean period of about 10 d in agreement with recent observational and modelling studies.
Process studies at the air-sea interface after atmospheric deposition in the Mediterranean Sea: objectives and strategy of the PEACETIME oceanographic campaign (May–June 2017)
Authors: Guieu Cécile , D'Ortenzio Fabrizio , Dulac François , Taillandier Vincent , Doglioli Andrea , Petrenko Anne , Barrillon Stéphanie , Mallet Marc , Nabat Pierre , Desboeufs Karine
Published: February 2020

Abstract. In spring, the Mediterranean Sea, a well-stratified low nutrient low chlorophyll region, receives atmospheric deposition both desert dust from the Sahara and airborne particles from anthropogenic sources. Such deposition translates into a supply of new nutrients and trace metals for the surface waters that likely impact biogeochemical cycles. However, the quantification of the impacts and the processes involved are still far from being assessed in situ. In this paper, we provide a state of the art regarding dust deposition and its impact on the Mediterranean Sea biogeochemistry and we describe in this context the objectives and strategy of the PEACETIME project and cruise, entirely dedicated to filling this knowledge gap. Our strategy to go a step forward than in previous approaches in understanding these impacts by catching a real deposition event at sea is detailed. The PEACETIME oceanographic campaign took place in May–June 2017 and we describe how we were able to successfully adapt the planned transect in order to sample a Saharan dust deposition event, thanks to a dedicated strategy, so-called Fast Action. That was successful, providing, for the first time in our knowledge, a coupled atmospheric and oceanographic sampling before, during and after an atmospheric deposition event. Atmospheric and marine in situ observations and process studies have been conducted in contrasted area and we summarize the work performed at sea, the type of data acquired and their valorization in the papers published in the special issue.
Transferring principles of solid-state and Laplace NMR to the field of in vivo brain MRI
Authors: de Almeida Martins João P. , Tax Chantal M. W. , Szczepankiewicz Filip , Jones Derek K. , Westin Carl-Fredrik , Topgaard Daniel
Published: February 2020

Abstract. Magnetic resonance imaging (MRI) is the primary method
for noninvasive investigations of the human brain in health, disease, and
development but yields data that are difficult to interpret whenever the
millimeter-scale voxels contain multiple microscopic tissue environments
with different chemical and structural properties. We propose a novel MRI
framework to quantify the microscopic heterogeneity of the living human
brain as spatially resolved five-dimensional relaxation–diffusion
distributions by augmenting a conventional diffusion-weighted imaging
sequence with signal encoding principles from multidimensional solid-state
nuclear magnetic resonance (NMR) spectroscopy, relaxation–diffusion
correlation methods from Laplace NMR of porous media, and Monte Carlo data
inversion. The high dimensionality of the distribution space allows
resolution of multiple microscopic environments within each heterogeneous
voxel as well as their individual characterization with novel statistical
measures that combine the chemical sensitivity of the relaxation rates with
the link between microstructure and the anisotropic diffusivity of tissue
water. The proposed framework is demonstrated on a healthy volunteer using
both exhaustive and clinically viable acquisition protocols.
Landslide hazard probability and risk assessment at the community level: a case of western Hubei, China
Authors: Fu Sheng , Chen Lixia , Woldai Tsehaie , Yin Kunlong , Gui Lei , Li Deying , Du Juan , Zhou Chao , Xu Yong , Lian Zhipeng
Published: February 2020

Abstract. Small communities living in mountainous terrain in Hubei province are often affected by landslides. Previous studies by the China Geological Survey focused on the 1:100 000 scale. Therefore, a more detailed assessment, especially at the community level, is urgently required by local governments for risk management. In this study, we conducted a more detailed semiquantitative landslide and risk assessment at the community level using a scale of 1:10 000. We applied the probabilistic method to assess landslide spatial, temporal, and size probabilities, while the hazard and risk assessment were considered for four return periods (5, 10, 20, and 50 years) and two size scenarios (landslide volume). The spatial probability from susceptibility mapping with an accuracy of 84 % indicates that the major controlling factors are Quaternary deposits and weathered eluvium from Ordovician limestones. This study revealed that most building areas in hazard maps are at the foot of major slopes with very high hazard probabilities, and therefore we computed the potential loss of life and property for each slope. The results reveal that 1530 people and USD 18 million worth of property were at risk of landslides within a 50-year return period and a landslide volume of 50 000 m3. The longer the return period is, the higher the hazard probability is. Compared with the classic inverse gamma and power law distribution of landslide magnitude and frequency, the function by the ordinary least squares method is more suitable for landslide size probability analysis of the study area. According to these methods, the proposed procedure of landslide risk assessment proves more useful than the existing data from the 1:100 000 scale in western Hubei, China.
Improved accuracy and efficiency of flood inundation mapping of low-, medium-, and high-flow events using the AutoRoute model
Authors: Follum Michael L. , Vera Ricardo , Tavakoly Ahmad A. , Gutenson Joseph L.
Published: February 2020

Abstract. This article presents improvements and the development of a postprocessing module for the regional-scale flood mapping tool, AutoRoute. The accuracy of this model to simulate low-, medium-, and high-flow-rate scenarios is demonstrated at seven test sites within the US. AutoRoute is one of the tools used to create high-resolution flood inundation maps at regional to continental scales, but it has previously only been tested using extreme flood events. Modifications to the AutoRoute model and postprocessing scripts are shown to improve accuracy (e.g., average F value increase of 17.5 % for low-flow events) and computational efficiency (simulation time reduced by over 40 %) when compared to previous versions. Although flood inundation results for low-flow events are shown to be comparable with published values (average F value of 63.3 %), the model results tend to be overestimated, especially in flatter terrain. Higher-flow scenarios tend to be more accurately simulated (average F value of 77.5 %). With improved computational efficiency and the enhanced ability to simulate both low- and high-flow scenarios, the AutoRoute model may be well suited to provide first-order estimates of flooding within an operational, regional- to continental-scale hydrologic modeling framework.
Review article: Review of fragility analyses for major building types in China with new implications for intensity–PGA relation development
Authors: Xin Danhua , Daniell James Edward , Wenzel Friedemann
Published: February 2020

Abstract. The evaluation of the seismic fragility of buildings is
one key task of earthquake safety and loss assessment. Many research reports
and papers have been published over the past 4 decades that deal with the
vulnerability of buildings to ground motion caused by earthquakes in China.
We first scrutinized 69 papers and theses studying building damage for
earthquakes that occurred in densely populated areas. They represent observations
where macroseismic intensities have been determined according to the official
Chinese Seismic Intensity Scale. From these many studies we derived
the median fragility functions (dependent on intensity) for four damage
limit states of the two most widely distributed building types: masonry and
reinforced concrete. We also inspected 18 publications that provide
analytical fragility functions (dependent on PGA, peak ground acceleration) for the same damage
classes and building categories. Thus, a solid fragility database based on
both intensity and PGA is established for seismicity-prone areas in mainland
China. A comprehensive view of the problems posed by the evaluation of
fragility for different building types is given. Based on the newly
collected fragility database, we propose a new approach in deriving
intensity–PGA relations by using fragility as the bridge, and reasonable
intensity–PGA relations are developed. This novel approach may shed light on
new thought in decreasing the scatter in traditional intensity–PGA relation
development, i.e., by further classifying observed macroseismic intensities
and instrumental ground motions based on differences in building seismic
resistance capability.
Review Article: A comprehensive review of datasets and methodologies employed to produce thunderstorm climatologies
Authors: Hayward Leah , Whitworth Malcolm , Pepin Nick , Dorling Steve
Published: February 2020

Abstract. Thunderstorm and lightning climatological research is conducted with a view to increasing knowledge about the distribution of thunderstorm related hazards and to gain an understanding of environmental factors increasing or decreasing their frequency. There are three main methodologies used in the construction of thunderstorm climatologies; thunderstorm frequency, thunderstorm tracking or lightning flash density. These approaches utilise a wide variety of underpinning datasets and employ many different methods ranging from correlations with potential influencing factors and mapping the distribution of thunderstorm day frequencies, to tracking individual thunderstorm cell movements. Meanwhile, lightning flash density climatologies are produced using lightning data alone and these studies therefore follow a more standardised format. Whilst lightning flash density climatologies are primarily concerned with the occurrence of cloud to ground lightning, the occurrence of any form of lightning confirms the presence of a thunderstorm and can therefore be used in the compilation of a thunderstorm climatology. Regardless of approach, the choice of analysis method is heavily influenced by dataset coverage, quality and the controlling factors under investigation. The issues investigated must also reflect the needs of the end use application to ensure that the results can be used effectively to reduce exposure to hazard, improve forecasting or enhance climatological understanding.
Seasonal statistical–dynamical prediction of the North Atlantic Oscillation by probabilistic post-processing and its evaluation
Authors: Düsterhus André
Published: February 2020

Abstract. Dynamical models of various centres have shown in recent years seasonal prediction skill of the North Atlantic Oscillation (NAO). By filtering the ensemble members on the basis of statistical predictors, known as subsampling, it is possible to achieve even higher prediction skill. In this study the aim is to design a generalisation of the subsampling approach and establish it as a post-processing procedure. Instead of selecting discrete ensemble members for each year, as the subsampling approach does, the distributions of ensembles and statistical predictors are combined to create a probabilistic prediction of the winter NAO. By comparing the combined statistical–dynamical prediction with the predictions of its single components, it can be shown that it achieves similar results to the statistical prediction. At the same time it can be shown that, unlike the statistical prediction, the combined prediction has fewer years where it performs worse than the dynamical prediction. By applying the gained distributions to other meteorological variables, like geopotential height, precipitation and surface temperature, it can be shown that evaluating prediction skill depends highly on the chosen metric. Besides the common anomaly correlation (ACC) this study also presents scores based on the Earth mover's distance (EMD) and the integrated quadratic distance (IQD), which are designed to evaluate skills of probabilistic predictions. It shows that by evaluating the predictions for each year separately compared to applying a metric to all years at the same time, like correlation-based metrics, leads to different interpretations of the analysis.