bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial correlations of extended cosmological structures
Authors: Santucho V , Luparello H E , Lares M , Lambas D G , Ruiz A N , Sgró M A 
Published: March 2020

ABSTRACT
Studies of large-scale structures in the Universe, such as superstructures or cosmic voids, have been widely used to characterize the properties of the cosmic web through statistical analyses. On the other hand, the two-point correlation function of large-scale tracers such as galaxies or haloes provides a reliable statistical measure. However, this function applies to the spatial distribution of point-like objects, and therefore it is not appropriate for extended large structures that strongly depart from spherical symmetry. Here we present an analysis based on the standard correlation function formalism that can be applied to extended objects exhibiting arbitrary shapes. Following this approach, we compute the probability excess Ξ of having spheres sharing parts of cosmic structures with respect to a realization corresponding to a distribution of the same structures in random positions. For this aim, we identify superstructures defined as future virialized structures (FVSs) in semi-analytic galaxies in the MPDL2 MultiDark simulation. We have also identified cosmic voids to provide a joint study of their relative distribution with respect to the superstructures. Our analysis suggests that Ξ provides useful characterizations of the large-scale distribution, as suggested from an analysis of subsets of the simulation. Even when superstructure properties may exhibit negligible variations across the subsets, Ξ has the sensitivity to statistically distinguish sub-boxes that depart from the mean at larger scales. Thus, our methods can be applied in analysis of future surveys to provide characterizations of large-scale structure suitable to distinguish different theoretical scenarios.
On the nature of the soft γ-ray emission in the hard state of the black hole transient GRS 1716−249
Authors: Bassi T , Malzac J , Del Santo M , Jourdain E , Roques J-P , D’Aì A , Miller-Jones J C A , Belmont R , Motta S E , Segreto A , Testa V , Casella P 
Published: March 2020

ABSTRACT
The black hole transient GRS 1716−249 was monitored from the radio to the γ-ray band during its 2016–2017 outburst. This paper focuses on the spectral energy distribution (SED) obtained in 2017 February–March, when GRS 1716−249 was in a bright hard spectral state. The soft γ-ray data collected with the INTEGRAL/SPI telescope show the presence of a spectral component that is in excess of the thermal Comptonization emission. This component is usually interpreted as inverse Compton emission from a tiny fraction of non-thermal electrons in the X-ray corona. We find that hybrid thermal/non-thermal Comptonization models provide a good fit to the X-/γ-ray spectrum of GRS 1716−249. The best-fitting parameters are typical of the bright hard state spectra observed in other black hole X-ray binaries. Moreover, the magnetized hybrid Comptonization model belm provides an upper limit on the intensity of the coronal magnetic field of about 106 G. Alternatively, this soft γ-ray emission could originate from synchrotron emission in the radio jet. In order to test this hypothesis, we fit the SED with the irradiated disc plus Comptonization model combined with the jet internal shock emission model ishem. We found that a jet with an electron distribution of p ≃ 2.1 can reproduce the soft γ-ray emission of GRS 1716−249. However, if we introduce the expected cooling break around 10 keV, the jet model can no longer explain the observed soft γ-ray emission, unless the index of the electron energy distribution is significantly harder (p &lt; 2).
Proton and carbon ion radiotherapy in skull base chordomas: a prospective study based on a dual particle and a patient-customized treatment strategy
Authors: Iannalfi Alberto , D’Ippolito Emma , Riva Giulia , Molinelli Silvia , Gandini Sara , Viselner Gisela , Fiore Maria Rosaria , Vischioni Barbara , Vitolo Viviana , Bonora Maria , Ronchi Sara , Petrucci Rachele , Barcellini Amelia , Mirandola Alfredo , Russo Stefania , Vai Alessandro , Mastella Edoardo , Magro Giuseppe , Maestri Davide , Ciocca Mario , Preda Lorenzo , Valvo Francesca , Orecchia Roberto 
Published: March 2020

Abstract

Background
The aim of this study is to evaluate results in terms of local control (LC), overall survival (OS), and toxicity profile and to better identify factors influencing clinical outcome of skull base chordoma treated with proton therapy (PT) and carbon ion radiotherapy (CIRT).

Methods
We prospectively collected and analyzed data of 135 patients treated between November 2011 and December 2018. Total prescription dose in the PT group (70 patients) and CIRT group (65 patients) was 74 Gy relative biological effectiveness (RBE) delivered in 37 fractions and 70.4 Gy(RBE) delivered in 16 fractions, respectively (CIRT in unfavorable patients). LC and OS were evaluated using the Kaplan–Meier method. Univariate and multivariate analyses were performed, to identify prognostic factors on clinical outcomes.

Results
After a median follow-up of 49 (range, 6–87) months, 14 (21%) and 8 (11%) local failures were observed in CIRT and PT group, respectively. Five-year LC rate was 71% in CIRT cohort and 84% in PT cohort. The estimated 5-year OS rate in the CIRT and PT group was 82% and 83%, respectively. On multivariate analysis, gross tumor volume (GTV), optic pathways, and/or brainstem compression and dose coverage are independent prognostic factors of local failure risk. High rate toxicity grade ≥3 was reported in 11% of patients.

Conclusions
Particle radiotherapy is an effective treatment for skull base chordoma with acceptable late toxicity. GTV, optic pathways, and/or brainstem compression and target coverage were independent prognostic factors for LC.

Key Points
• Proton and carbon ion therapy are effective and safe in skull base chordoma.
• Prognostic factors are GTV, organs at risk compression, and dose coverage.
• Dual particle therapy and customized strategy was adopted.
Statistical double Λ hypernuclear formation from Ξ− absorption at rest in light nuclei
Authors: Ohnishi Akira , Ishizuka Chikako , Tsubakihara Kohsuke , Hirata Yuichi 
Published: March 2020

Abstract
We investigate double $\Lambda$ hyperfragment formation from the statistical decay of double $\Lambda$ compound nuclei produced in the $\Xi^-$ absorption at rest in the light nuclei $^{12}\mathrm{C}$, $^{14}\mathrm{N}$, and $^{16}\mathrm{O}$. We examine the target and the $\Lambda\Lambda$ bond energy dependence of the double $\Lambda$ hyperfragment formation probabilities, especially of those double hypernuclei observed in experiments. For the $^{12}\mathrm{C}$ ($^{14}\mathrm{N}$) target, the formation probabilities of $^{\,\;\;6}_{\Lambda\Lambda}\mathrm{He}$ and $^{\;10}_{\Lambda\Lambda}\mathrm{Be}$ ($^{\;13}_{\Lambda\Lambda}\mathrm{B}$) are found to be reasonably large as they are observed in the KEK-E373 (KEK-E176) experiment. By comparison, for the $^{16}\mathrm{O}$ target, the formation probability of $^{\;11}_{\Lambda\Lambda}\mathrm{Be}$ is calculated to be small with $\Delta B_{\Lambda\Lambda}$ consistent with the Nagara event. We also evaluate the formation probability of ${}^{\,\;\;5}_{\Lambda\Lambda}\mathrm{H}$ from a $\Xi^-$–${}^{6}\mathrm{He}$ bound state, ${}^{7}_{\Xi}\mathrm{H}$.
Association of fine-particulate and acidic-gas air pollution with premenstrual syndrome risk
Authors: Lin S-Y , Yang Y-C , Chang C Y-Y , Hsu W-H , Lin C-C , Jiang C-C , Wang I-K , Lin C-D , Hsu C-Y , Kao C-H 
Published: March 2020

Abstract

Objective
Air pollution had been reported to be associated with the reproductive health of women. However, the association of particulate matter (PM) and acid gases air pollution with premenstrual syndrome (PMS) warrants investigation. This study investigated the effects of air pollution on PMS risk.

Population
We combined data from the Taiwan Air Quality-Monitoring Database and the Longitudinal Health Insurance Database. In total, an observational cohort of 85 078 Taiwanese women not diagnosed as having PMS.

Methods
Air pollutant concentrations were grouped into four levels based on the concentration quartiles of several types of air pollutants.

Main outcome measures
We then applied univariable and multivariable Cox proportional hazard regression models to assess PMS risk in association with each pollutant type.

Results
Women exposed to Q4-level SO2 exhibited a 7.77 times higher PMS risk compared with those to Q1-level SO2 (95% confidence interval [CI] = 6.22–9.71). Women exposed to Q4-level NOx exhibited a 2.86 times higher PMS risk compared with those exposed to Q1-level NOx (95% CI = 2.39–3.43). Women exposed to Q4-level NO exhibited a 3.17 times higher PMS risk compared with women exposed to Q1-level NO (95% CI = 2.68–3.75). Finally, women exposed to Q4-level PM with a ≤2.5-µm diameter (PM2.5) exhibited a 3.41 times higher PMS risk compared with those exposed to Q1-level PM2.5 (95% CI = 2.88–4.04).

Conclusions
High incidences of PMS were noted in women who lived in areas with higher concentrations of SO2, NOx, NO, NO2 and PM2.5.
Child-Related Transfers, Household Labour Supply, and Welfare
Authors: Guner Nezih , Kaygusuz Remzi , Ventura Gustavo 
Published: March 2020

AbstractWhat are the macroeconomic effects of transfers to households with children? How do alternative policies fare in welfare terms? We answer these questions in an equilibrium life-cycle model with household labour supply decisions, skill losses of females associated to non-participation, and heterogeneity in terms of fertility, childcare expenditures, and access to informal care. Calibrating our model to the U.S. economy, we first provide a roadmap for policy evaluation by contrasting transfers that are conditional on market work (childcare subsidies and childcare credits) with those that are not (child credits), when both types can be means tested or universal. We then evaluate expansions of current arrangements for the U.S. and find that expansions of conditional transfers have substantial positive effects on female labour supply, that are largest at the bottom of the skill distribution. Expanding childcare credits leads to long-run increases in the participation of married females of 10.6%, while an equivalent expansion of child credits leads to the opposite ($-$2.4%). Expanding existing programs generates substantial welfare gains for newborn households, which are largest for less-skilled households. Expanding childcare credits leads to the largest welfare gains for newborns and achieves majority support.
Exploring the influence of silver and lead on structure and function of xylanase: spectroscopic and calorimetric methods
Authors: Jing Mingyang , Tang Rui , Han Guangye , Zhang Shansheng , Liu Rutao 
Published: March 2020

Abstract
Soil contamination with heavy metal could induce the alteration of soil ecological environments, and soil enzyme activities are sensitive indicators for the soil toxicology. Xylanase is one of predominant soil enzymes related to carbon nitrogen cycle. In this work, we explored the underlying mechanisms for conformational and enzymatic activity alterations of xylanase after silver and lead exposure at molecular level with systematical measurements including multiple spectroscopic methods, isothermal titration calorimetry, and enzymatic activity. Both silver and lead could loosen and unfold the skeleton of xylanase with the quenching of endogenous fluorescence. Silver interacted with xylanase forming larger-size aggregations through Van der Waals forces and hydrogen bonding, while lead interacted with xylanase forming larger-size aggregations through hydrophobic force. Silver and lead induced an obvious loss (67.1 and 56.31%) of the xylanase enzymatic activity, but silver has a greater impact on xylanase than that of lead. The xylanase enzymatic activity significantly decreased due to the conformational alterations. The negative effect of silver exposure on xylanase structure and function was more prominent than that of lead.
Frequent unregulated use of antibiotics in rural Cambodian infants
Authors: Miyazaki Asuka , Tung Rathavy , Taing Bunsreng , Matsui Mitsuaki , Iwamoto Azusa , Cox Sharon E 
Published: March 2020

Abstract

Background
Despite a high prevalence of antibiotic resistance in Cambodia, few studies have assessed health-seeking behaviour and the use of antibiotics by caregivers of young children in Cambodia.

Methods
We conducted a cross-sectional survey of infants &lt;12 months of age and their caregivers, assessing the frequency of reported illness, common symptoms and associated health-seeking behaviour through structured questionnaires administered by trained fieldworkers at a home visit. In a subset of these participants, ages 4–8 months with no acute malnutrition, we conducted a 3-month surveillance with fortnightly home visits.

Results
Of 149 infants (ages 1–11 months, 54.4% male) enrolled in the cross-sectional study, 76 (51.4%) reported symptoms of diarrhoea, fever or cough in the previous 14 d, with associated use of antibiotics reported in 22 (14.8%) infants. In 47 infants enrolled in the longitudinal surveillance, there were 141 reported episodes of illness in 44 (94%) infants with 21 infants (45%) reported to have received antibiotics in 32/141 (22.7%) episodes. Amoxicillin was the most commonly reported antibiotic in both surveys (68% [40/59 episodes reporting the use of antibiotics]).

Conclusions
Antibiotic usage is high in this population and appears to be occurring largely outside of the formal healthcare system.
How unique is unique? Quantifying geometric differences in stripe patterns of Cape mountain zebra,Equus zebra zebra(Perissodactyla: Equidae)
Authors: Prinsloo Nicolas D , Postma Martin , de Bruyn P J Nico 
Published: March 2020

AbstractQuantified coat pattern dissimilarity provides a visible surface for individual animal traceability to populations. We determined the feasibility in quantifying uniqueness of stripe patterns of Cape mountain zebra (CMZ; Equus zebra zebra) using geometric morphometrics. We photogrammetrically created dense surface models of CMZ (N = 56). Stripe edges were landmarked, superimposed and compared for shape variation across replicates and the population. Significant allometry in stripe patterns prompted allometric correction to remove increased curvature of stripes at the rump, belly and back with larger adult individuals, to facilitate equilibrated comparison between individuals. Re-landmarked replicates showed lower dissimilarity (Di) than non-replicates (Dp), representing minimal landmarking error. Individuals were 78.07 ± 1.79% unique (U=1−DiDp×100%) relative to the study population. Size, the number of torso stripes and degree of branching in four rear torso stripes described the most shape variation (36.79%) but a significant portion could only be distinguished with geometric morphometrics (41.82%). This is the first known use of geometric morphometrics to quantify coat pattern uniqueness, using a model species to provide baseline individual morphological variation. Measures of coat pattern similarity have a place in phenotypic monitoring and identification.
Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label
Authors: Zheng Chuansheng , Deng Xianbo , Fu Qiang , Zhou Qiang , Feng Jiapei , Ma Hui , Liu Wenyu , Wang Xinggang 
Published: March 2020

AbstractAccurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 detection on chest CT is helpful to counter the outbreak of SARS-CoV-2. A weakly-supervised deep learning-based software system was developed using 3D CT volumes to detect COVID-19. For each patient, the lung region was segmented using a pre-trained UNet; then the segmented 3D lung region was fed into a 3D deep neural network to predict the probability of COVID-19 infectious. 499 CT volumes collected from Dec. 13, 2019, to Jan. 23, 2020, were used for training and 131 CT volumes collected from Jan 24, 2020, to Feb 6, 2020, were used for testing. The deep learning algorithm obtained 0.959 ROC AUC and 0.976 PR AUC. There was an operating point with 0.907 sensitivity and 0.911 specificity in the ROC curve. When using a probability threshold of 0.5 to classify COVID-positive and COVID-negative, the algorithm obtained an accuracy of 0.901, a positive predictive value of 0.840 and a very high negative predictive value of 0.982. The algorithm took only 1.93 seconds to process a single patient’s CT volume using a dedicated GPU. Our weakly-supervised deep learning model can accurately predict the COVID-19 infectious probability in chest CT volumes without the need for annotating the lesions for training. The easily-trained and highperformance deep learning algorithm provides a fast way to identify COVID-19 patients, which is beneficial to control the outbreak of SARS-CoV-2. The developed deep learning software is available athttps://github.com/sydney0zq/covid-19-detection.
Purging of deleterious mutations during domestication in the predominant selfing crop soybean
Authors: Kim Myung-Shin , Lozano Roberto , Kim Ji Hong , Bae Dong Nyuk , Kim Sang-Tae , Park Jung-Ho , Choi Man Soo , Kim Jaehyun , Ok Hyun Choong , Park Soo-Kwon , Gore Michael A. , Moon Jung-Kyung , Jeong Soon-Chun 
Published: March 2020

AbstractAs a predominant plant protein and oil source for both food and feed, soybean is unique in that both domesticated and wild types are predominantly selfing. Here we present a genome-wide variation map of 781 soybean accessions that include 418 domesticated (Glycine max) and 345 wild (Glycine soja) accessions and 18 of their natural hybrids. We identified 10.5 million single nucleotide polymorphisms and 5.7 million small indels that contribute to within- and between-population variations. We describe improved detection of domestication-selective sweeps and drastic reduction of overall deleterious alleles in domesticated soybean relative to wild soybean in contrast to the cost of domestication hypothesis. This resource enables the marker density of existing data sets to be increased to improve the resolution of association studies.
Mental health status among family members of health care workers in Ningbo, China during the Coronavirus Disease 2019 (COVID-19) outbreak: a Cross-sectional Study
Authors: Ying Yuchen , Kong Fanqian , Zhu Binbin , Ji Yunxin , Lou Zhongze , Ruan Liemin 
Published: March 2020

AbstractBackgroundSo far, the psychological impact of COVID-19 epidemic among family members of Health care workers (HCWs) in China has been neglected. The present cross-sectional study aimed to investigate the mental health status and related factors of families of HCWs in Designated Hospitals in Ningbo, China.MethodFamily members of HCWs working in five designated hospitals in Ningbo, China were recruited between February 10th and 20th, 2020. Information on demographic variables, the COVID-19-related events in the lives, knowledge of COVID-19 and the working status of family members (that is, HCWs) was collected using online self-administered questionnaires. The mental health status were assessed using the Chinese version of Patient Health Questionnare-9 (PHQ-9) and Chinese version of Generalized Anxiety Disorder-7 (GAD-7). Multivariable logistic regression analyses were conducted to identify the main factors associated with the mental health conditions.ResultsA total of 822 participants completed questionnaires correctly. (response rate of 95.80%). The overall prevalence of GAD and depressive symptoms were 33.73%, and 29.35%, respectively. More times (hours) to focus on the COVID-19 (Odd ratio (OR)=1.215, 95% confidence interval (CI):1.061-1.391), family members (that is, HCWs) directly contact with confirmed or suspected COVID-19 patients (OR=1.477, 95%CI:1.069-2.040) were risk factors for GAD, while higher participants self-reported safety score for protective equipment of HCWs (OR=0.807, 95%CI:0.700-0.930) was a protective factor. More times (hours) to focus on the COVID-19 (OR=1.215, 95%CI:1.061-1.391), longer average working times per week for family members (that is, HCWs) (OR=1.017, 95%CI:1.005-1.029), being parents and other next of kin of HCWs were risk factors for depressive symptoms (OR=3.526, 95%CI:1.609-7.728 and OR=1.639, 95%CI:1.096-2.451, respectively). In addition, compared with participants who were HCWs, participants who were enterprise workers and were more likely to develop depressive symptoms(OR=1.750, 95%CI:1.104-2.776), while who were government employees or institutions employees were less likely to suffer depressive symptoms (OR=0.529, 95%CI:0.286-0.977).ConclusionsPsychological responses to COVID-19 have been dramatic among family members of HCWs during the rising phase of the outbreak. Our findings provide strong evidence to pay more attention on the mental health status of this vulnerable but often unseen populations during COVID-19 epidemic.
A Cybernetics-based Dynamic Infection Model for Analyzing SARS-COV-2 Infection Stability and Predicting Uncontrollable Risks
Authors: Xiao Wenlei , Liu Qiang , Huan Ji , Sun Pengpeng , Wang Liuquan , Zang Chenxin , Zhu Sanying , Gao Liansheng 
Published: March 2020

AbstractSince December 2019, COVID-19 has raged in Wuhan and subsequently all over China and the world. We propose a Cybernetics-based Dynamic Infection Model (CDIM) to the dynamic infection process with a probability distributed incubation delay and feedback principle. Reproductive trends and the stability of the SARS-COV-2 infection in a city can then be analyzed, and the uncontrollable risks can be forecasted before they really happen. The infection mechanism of a city is depicted using the philosophy of cybernetics and approaches of the control engineering. Distinguished with other epidemiological models, such as SIR, SEIR, etc., that compute the theoretical number of infected people in a closed population, CDIM considers the immigration and emigration population as system inputs, and administrative and medical resources as dynamic control variables. The epidemic regulation can be simulated in the model to support the decision-making for containing the outbreak. City case studies are demonstrated for verification and validation.
Wuhan and Hubei COVID-19 mortality analysis reveals the critical role of timely supply of medical resources
Authors: Zhang Zuqin , Yao Wei , Wang Yan , Long Cheng , Fu Xinmiao 
Published: March 2020

AbstractWe report that COVID-19 mortality and recovery rates in Hubei Province, China exponentially decays (R2>0.93) and grows (R2>0.95), respectively. A great number of newly supplied medical resources, including more than 42000 aided health workers, over 26000 makeshift beds and 23000 acute care beds, enabled overwhelming patients to be treated effectively in hospitals. This may inform other countries to deal with the coming COVID-19 pandemic when patients are overwhelming the local health care system.