bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors Affecting Resiliency Among Volunteers in Disasters: A Systematic Literature Review
Authors: Ghodsi Hasan , Sohrabizadeh Sanaz , Khani Jazani Reaza , Kavousi Amir 
Published: November 2020

ABSTRACTObjective:Volunteers need considerable resiliency to cope with formidable challenges during their operations in disaster scenes. The present study was conducted to identify factors affecting the different aspects of resiliency among volunteers in disasters.Material and Methods:The databases of Web of Science, Scopus, PubMed, ProQuest, Google Scholar, World Health Organization Library, International Committee of the Red Cross (ICRC) Library, PsycArticles, and SafetyLit were searched until September 29, 2018. The main search terms were resiliency, disaster, humanitarian aid worker, and volunteer.Results:A total of 548 documents were obtained and screened based on the inclusion and exclusion criteria. A number of 8 documents was selected for the final analysis. The main factors contributing to the resilience of volunteers at the 3 stages of pre-, during, and post-disasters were classified into 3 groups of individual, environmental, and organizational. Important factors affecting resilience of volunteers in disasters included previous disaster response experience and disaster-related training.Conclusion:Resiliency should be deemed integral to relief operations. Considering the main factors affecting volunteers’ resiliency, it is highly suggested that organizations active in humanitarian endeavors explore the factors impacting on resilience among their volunteers via various research methods and seek to select those with higher degrees of resilience in order to avert untoward consequences in their missions.
An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model
Authors: Tulshyan Vatsal , Sharma Dolly , Mittal Mamta 
Published: November 2020

AbstractObjective:The coronavirus disease (COVID-19) pandemic was initiated in Wuhan Province of mainland China in December 2019 and has spread over the world. This study analyzes the effects of COVID-19 based on likely positive cases and fatality in India during and after the lockdown period from March 24, 2020, to May 24, 2020.Methods:Python has been used as the main programming language for data analysis and forecasting using the Prophet model, a time series analysis model. The data set has been preprocessed by grouping together the days for total numbers of cases and deaths on few selected dates and removing missing values present in some states.Results:The Prophet model performs better in terms of precision on the real data. Prediction depicts that, during the lockdown, the total cases were rising but in a controlled manner with an accuracy of 87%. After the relaxation of lockdown rules, the predictions have shown an obstreperous situation with an accuracy of 60%.Conclusion:The resilience could have been better if the lockdown with strict norms was continued without much relaxation. The situation after lockdown has been found to be uncertain as observed by the experimental study conducted in this work.
Solving the 4NLS with white noise initial data
Authors: Oh Tadahiro , Tzvetkov Nikolay , Wang Yuzhao 
Published: November 2020

AbstractWe construct global-in-time singular dynamics for the (renormalized) cubic fourth-order nonlinear Schrödinger equation on the circle, having the white noise measure as an invariant measure. For this purpose, we introduce the ‘random-resonant / nonlinear decomposition’, which allows us to single out the singular component of the solution. Unlike the classical McKean, Bourgain, Da Prato-Debussche type argument, this singular component is nonlinear, consisting of arbitrarily high powers of the random initial data. We also employ a random gauge transform, leading to random Fourier restriction norm spaces. For this problem, a contraction argument does not work, and we instead establish the convergence of smooth approximating solutions by studying the partially iterated Duhamel formulation under the random gauge transform. We reduce the crucial nonlinear estimates to boundedness properties of certain random multilinear functionals of the white noise.
Sensitivity of midturbinate versus nasopharyngeal swabs for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Authors: Jamal Alainna J. , Mozafarihashjin Mohammad , Coomes Eric , Anceva-Sami Sofia , Barati Shiva , Crowl Gloria , Faheem Amna , Farooqi Lubna , Kandel Christopher E. , Khan Saman , Li Angel X. , Mistry Henna , Paterson Aimee , Plenderleith Simon , Prost Karren , Poutanen Susan , Powis Jeff , Schryer Renée , Taylor Maureen , Yip Lily , Zhong Xi Zoe , McGeer Allison J. , Mubareka Samira ,   for the Toronto Invasive Bacterial Diseases Network COVID-19 Investigators
Published: November 2020

AbstractTo compare sensitivity of specimens for COVID-19 diagnosis, we tested 151 nasopharyngeal/midturbinate swab pairs from 117 COVID-19 inpatients using reverse-transcriptase polymerase chain reaction (RT-PCR). Sensitivity was 94% for nasopharyngeal and 75% for midturbinate swabs (P = .0001). In 88 nasopharyngeal/midturbinate pairs with matched saliva, sensitivity was 86% for nasopharyngeal swabs and 88% for combined midturbinate swabs/saliva.
Comparison of rule-based and neural network models for negation detection in radiology reports
Authors: Sykes D. , Grivas A. , Grover C. , Tobin R. , Sudlow C. , Whiteley W. , Mcintosh A. , Whalley H. , Alex B. 
Published: November 2020

AbstractUsing natural language processing, it is possible to extract structured information from raw text in the electronic health record (EHR) at reasonably high accuracy. However, the accurate distinction between negated and non-negated mentions of clinical terms remains a challenge. EHR text includes cases where diseases are stated not to be present or only hypothesised, meaning a disease can be mentioned in a report when it is not being reported as present. This makes tasks such as document classification and summarisation more difficult. We have developed the rule-based EdIE-R-Neg, part of an existing text mining pipeline called EdIE-R (Edinburgh Information Extraction for Radiology reports), developed to process brain imaging reports, (https://www.ltg.ed.ac.uk/software/edie-r/) and two machine learning approaches; one using a bidirectional long short-term memory network and another using a feedforward neural network. These were developed on data from the Edinburgh Stroke Study (ESS) and tested on data from routine reports from NHS Tayside (Tayside). Both datasets consist of written reports from medical scans. These models are compared with two existing rule-based models: pyConText (Harkema et al. 2009. Journal of Biomedical Informatics42(5), 839–851), a python implementation of a generalisation of NegEx, and NegBio (Peng et al. 2017. NegBio: A high-performance tool for negation and uncertainty detection in radiology reports. arXiv e-prints, p. arXiv:1712.05898), which identifies negation scopes through patterns applied to a syntactic representation of the sentence. On both the test set of the dataset from which our models were developed, as well as the largely similar Tayside test set, the neural network models and our custom-built rule-based system outperformed the existing methods. EdIE-R-Neg scored highest on F1 score, particularly on the test set of the Tayside dataset, from which no development data were used in these experiments, showing the power of custom-built rule-based systems for negation detection on datasets of this size. The performance gap of the machine learning models to EdIE-R-Neg on the Tayside test set was reduced through adding development Tayside data into the ESS training set, demonstrating the adaptability of the neural network models.
Food advertising during children’s television programmes in Italy
Authors: Gallus Silvano , Borroni Elisa , Stival Chiara , Kaur Sharanpreet , Davoli Sofia , Lugo Alessandra , Effertz Tobias , Garattini Silvio , Scaglioni Silvia 
Published: November 2020

AbstractObjective:Previous studies from European countries noted that food products promoted on TV for children did not comply with international guidelines, including the World Health Organization European Nutrient Profile Model (WHO-ENPM) and the EU Pledge Nutrition Criteria (EU-PNC, an initiative developed by leading food companies). We aim to provide new data from Italy.Design:Evaluation of Italian TV advertisements. Data on nutritional values for food product advertised were compared with nutritional standards issued by the WHO-ENPM and the EU-PNC.Setting:In total, 180 h of TV programmes from six Italian channels, 2016–2017.Participants:Eight hundred and ten consecutive advertisements during children’s programmes.Results:Out of 810 advertisements, 90 (11·1 %) referred to food products. Among these, 84·5 % of the foods promoted did not meet the WHO-ENPM and 55·6 % the EU-PNC guidelines. Advertisements promoting sweet and salty snacks (i.e. ≥ 70 % of all foods) v. other food products showed higher non-compliance with both the WHO-ENPM (OR: 73·8; 95 % CI: 4·09, 1330) and the EU-PNC (OR: 9·21; 95 % CI: 2·82, 30·1).Conclusions:In Italy, most food advertisements during children’s programmes are not compliant with European nutritional standards. Almost all the advertisements for snacks do not meet international guidelines. As the WHO-ENPM guidelines do not propose standards for all the food products, including meals, there is an urgent need to define independent and easy-to-read guidelines for food advertisements targeting children. As a first step towards the complete ban of food advertisements targeting children recommended by other researchers, these guidelines should be enforced by all the TV broadcasts.
Estimation of the IC to CG Ratio Using JEM‐GLIMS and Ground‐Based Lightning Network Data
Authors: Bandholnopparat K. , Sato M. , Adachi T. , Ushio T. , Takahashi Y. 
Published: November 2020

AbstractThe occurrence ratio of intracloud (IC) to cloud‐to‐ground (CG) discharges, which is denoted by Z‐ratio, is the crucial parameter for the studies on the global electric circuit. However, the latitudinal and regional dependences of Z‐ratio are not fully clarified. Therefore, using optical data obtained by the Global Lightning and Sprite Measurements on Japanese Experiment Module (JEM‐GLIMS), we distinguished the lightning discharge type, that is, IC, positive CG (+CG), and negative CG (−CG) discharges, and statistically estimated the Z‐ratio. We analyzed 8,354 lightning events that obtained by JEM‐GLIMS observation and succeeded in identifying 4,431 IC discharges, 597 +CG discharges, and 3,326 −CG discharges. From this result, we calculated the Z‐ratio over many regions around the world and estimated its latitudinal and regional dependences. It is found that the Z‐ratio over the continental area is larger than the oceanic area. We also found that the Z‐ratio significantly decreases with the latitude, which is generally comparable to the results shown in the previous studies. The estimated Z‐ratio varies from 2.9–0.29 from the equator to 50° latitude, and the global mean value is 1.6. The regional dependence of Z‐ratio derived from this study can be combined with the CG lightning data provided by the ground‐based lightning detection networks to estimate the occurrence number of IC discharges. Then, the occurrence number of both IC and CG discharges can be used for calculating a more accurate estimation of the total lightning currents in the global electric circuit.
Stream Dissolved Organic Matter in Permafrost Regions Shows Surprising Compositional Similarities but Negative Priming and Nutrient Effects
Authors: Wologo Ethan , Shakil Sarah , Zolkos Scott , Textor Sadie , Ewing Stephanie , Klassen Jane , Spencer Robert G. M. , Podgorski David C. , Tank Suzanne E. , Baker Michelle A. , O'Donnell Jonathan A. , Wickland Kimberly P. , Foks Sydney S. W. , Zarnetske Jay P. , Lee‐Cullin Joseph , Liu Futing , Yang Yuanhe , Kortelainen Pirkko , Kolehmainen Jaana , Dean Joshua F. , Vonk Jorien E. , Holmes Robert M. , Pinay Gilles , Powell Michaela M. , Howe Jansen , Frei Rebecca J. , Bratsman Samuel P. , Abbott Benjamin W. 
Published: November 2020

AbstractPermafrost degradation is delivering bioavailable dissolved organic matter (DOM) and inorganic nutrients to surface water networks. While these permafrost subsidies represent a small portion of total fluvial DOM and nutrient fluxes, they could influence food webs and net ecosystem carbon balance via priming or nutrient effects that destabilize background DOM. We investigated how addition of biolabile carbon (acetate) and inorganic nutrients (nitrogen and phosphorus) affected DOM decomposition with 28‐day incubations. We incubated late‐summer stream water from 23 locations nested in seven northern or high‐altitude regions in Asia, Europe, and North America. DOM loss ranged from 3% to 52%, showing a variety of longitudinal patterns within stream networks. DOM optical properties varied widely, but DOM showed compositional similarity based on Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR MS) analysis. Addition of acetate and nutrients decreased bulk DOM mineralization (i.e., negative priming), with more negative effects on biodegradable DOM but neutral or positive effects on stable DOM. Unexpectedly, acetate and nutrients triggered breakdown of colored DOM (CDOM), with median decreases of 1.6% in the control and 22% in the amended treatment. Additionally, the uptake of added acetate was strongly limited by nutrient availability across sites. These findings suggest that biolabile DOM and nutrients released from degrading permafrost may decrease background DOM mineralization but alter stoichiometry and light conditions in receiving waterbodies. We conclude that priming and nutrient effects are coupled in northern aquatic ecosystems and that quantifying two‐way interactions between DOM properties and environmental conditions could resolve conflicting observations about the drivers of DOM in permafrost zone waterways.
Simultaneously Formed Wedge‐Like Structures of Different Ion Species Deep in the Inner Magnetosphere
Authors: Ren Jie , Zong Q. G. , Yue C. , Zhou X. Z. , Fu S. Y. , Spence H. E. , Funsten H. O. 
Published: November 2020

AbstractIn this study, ion data from the Helium, Oxygen, Proton, and Electron (HOPE) spectrometers onboard Van Allen Probes reveal the existence of wedge‐like structures of O+, He+, and H+ ions deep in the inner magnetosphere. The behaviors of the wedge‐like structures in terms of temporal evolution, spatial distribution, upper energy limit, as well as dependence on solar wind and different geomagnetic indices are investigated from both event studies of several consecutive orbits on 3 February 2013 and the subsequent statistical analyses using 4 years of data. Unlike the dominant distribution at
–8 in the dayside observed by the polar orbit satellites in previous studies, the wedge‐like structures deep in the equatorial plane of the inner magnetosphere are found mostly at the Mcllwain L shells of
–5 and have a preferential location in the duskside and nightside. The O+ and He+ structures can extend to smaller L shells with higher upper energy limits than the H+ structures, while the upper energy limits of all these particle species show a similar variation tendency with respect to magnetic local time (MLT) and L. Observations indicate that these wedge‐like structures are probably attributed to fresh substorm injections from the outer region.
In Situ Observations of Microphysics, Electric Fields, and Lightning in the Trailing Stratiform Region of a Mesoscale Convective System
Authors: Detwiler Andrew , Kennedy Patrick 
Published: November 2020

AbstractWe use in situ airborne observations to extend a previous analysis by Lang and Rutledge (2008; https://doi.org/10.1029/2006JD007709) of remotely sensed radar and lightning mapping array observations of the 11 June 2000 asymmetric mesoscale convective system (MCS) that moved through the primary observation region of the Severe Thunderstorm Electrification/Precipitation Study in northeastern Colorado and northwestern Kansas. We analyze in detail in situ aircraft observations, radar, and remotely mapped lightning discharges from a portion of the MCS that was starting to produce a bow echo during the time of the aircraft mission. The observations are interpreted to indicate the presence of a rearward and downward‐sloping positive charge layer detraining from a mature cell near the leading convective region. In the convective cell the positive charge region was at an altitude of ~10 km MSL. It then descended rearward, crossing the 6 km MSL altitude plane ~40 km to the rear of the leading convective region. During an 8‐min period, three major lightning discharges initiated in the convective region and propagated rearward into the trailing stratiform region in association with this positive charge layer. Airborne in situ microphysical and electrical observations suggest that the charge layer in the stratiform region of the storm during this period resulted from charge separation in the convective region and transport from there into the stratiform region. Microphysical and meteorological conditions in the stratiform region were not supportive of significant in situ charge separation in this portion of the stratiform region during this time period.
Plant Hydraulic Stress Strategy Improves Model Predictions of the Response of Gross Primary Productivity to Drought Across China
Authors: Wu Haohao , Fu Congsheng , Wu Huawu , Zhang Lingling 
Published: November 2020

AbstractThe response of the terrestrial carbon cycle to droughts, which have recently increased in incidence and severity, is a hot topic in research, but the role played by vegetation water use strategies remains unclear. Both the soil moisture stress (SMS) and plant hydraulic stress (PHS) strategies are used in land surface models, but their performance in simulating the terrestrial carbon cycle and its response to droughts in various climatic zones remains uncertain. In this study, we used Community Land Model Version 5 to simulate gross primary productivity (GPP) across four different climatic subregions of China during 2000–2015 to investigate the roles played by PHS and SMS in the response of GPP to dry events and dry or rainy years in various climate zones. Simulated GPP with the two strategies were overestimated by 2.0–2.3% for the entire China compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data. GPP simulated using PHS configuration fit eddy covariance and MODIS data better than that obtained using SMS across China, except for the Qinghai‐Tibet Plateau. PHS increased simulated GPP by 0.10–0.63 g C m−2 day−1 during dry events across different climatic regions because of root hydraulic lift but decreased GPP by 0.37–0.45 g C m−2 day−1 during growing season in the humid southeastern region because of high atmospheric vapor pressure deficit and root hydraulic descent. Simulations forced by data collected locally in China performed better than those forced by CRUNCEP7 global data at the site but worse at the regional scale, in particular for the Qinghai‐Tibet Plateau.
Nonlinear ionization dynamics of hot dense plasma observed in a laser-plasma amplifier
Authors: Tuitje F. , Martínez Gil P. , Helk T. , Gautier J. , Tissandier F. , Goddet J.-P. , Guggenmos A. , Kleineberg U. , Sebban S. , Oliva E. , Spielmann C. , Zürch M. 
Published: November 2020

AbstractUnderstanding the behaviour of matter under conditions of extreme temperature, pressure, density and electromagnetic fields has profound effects on our understanding of cosmologic objects and the formation of the universe. Lacking direct access to such objects, our interpretation of observed data mainly relies on theoretical models. However, such models, which need to encompass nuclear physics, atomic physics and plasma physics over a huge dynamic range in the dimensions of energy and time, can only provide reliable information if we can benchmark them to experiments under well-defined laboratory conditions. Due to the plethora of effects occurring in this kind of highly excited matter, characterizing isolated dynamics or obtaining direct insight remains challenging. High-density plasmas are turbulent and opaque for radiation below the plasma frequency and allow only near-surface insight into ionization processes with visible wavelengths. Here, the output of a high-harmonic seeded laser-plasma amplifier using eight-fold ionized krypton as the gain medium operating at a 32.8 nm wavelength is ptychographically imaged. A complex-valued wavefront is observed in the extreme ultraviolet (XUV) beam with high resolution. Ab initio spatio-temporal Maxwell–Bloch simulations show excellent agreement with the experimental observations, revealing overionization of krypton in the plasma channel due to nonlinear laser-plasma interactions, successfully validating this four-dimensional multiscale model. This constitutes the first experimental observation of the laser ion abundance reshaping a laser-plasma amplifier. The presented approach shows the possibility of directly modelling light-plasma interactions in extreme conditions, such as those present during the early times of the universe, with direct experimental verification.
Anaerobic bacterial degradation of protein and lipid macromolecules in subarctic marine sediment
Authors: Pelikan Claus , Wasmund Kenneth , Glombitza Clemens , Hausmann Bela , Herbold Craig W , Flieder Mathias , Loy Alexander 
Published: November 2020

Abstract
Microorganisms in marine sediments play major roles in marine biogeochemical cycles by mineralizing substantial quantities of organic matter from decaying cells. Proteins and lipids are abundant components of necromass, yet the taxonomic identities of microorganisms that actively degrade them remain poorly resolved. Here, we revealed identities, trophic interactions, and genomic features of bacteria that degraded 13C-labeled proteins and lipids in cold anoxic microcosms containing sulfidic subarctic marine sediment. Supplemented proteins and lipids were rapidly fermented to various volatile fatty acids within 5 days. DNA-stable isotope probing (SIP) suggested Psychrilyobacter atlanticus was an important primary degrader of proteins, and Psychromonas members were important primary degraders of both proteins and lipids. Closely related Psychromonas populations, as represented by distinct 16S rRNA gene variants, differentially utilized either proteins or lipids. DNA-SIP also showed 13C-labeling of various Deltaproteobacteria within 10 days, indicating trophic transfer of carbon to putative sulfate-reducers. Metagenome-assembled genomes revealed the primary hydrolyzers encoded secreted peptidases or lipases, and enzymes for catabolism of protein or lipid degradation products. Psychromonas species are prevalent in diverse marine sediments, suggesting they are important players in organic carbon processing in situ. Together, this study provides new insights into the identities, functions, and genomes of bacteria that actively degrade abundant necromass macromolecules in the seafloor.