bluuebunny/crossref_metadata_2025_split huggingface dataset:
Excitation power dependent Coulomb induced recombination dynamics in magnetically doped type-II quantum dots
Authors: Tarasek Steven , Chou Wu-Ching , Fan Wen-Chung , Thomay Tim 
Published: April 2020

Abstract
We observe that the wavefunction overlap of the carriers in type-II quantum dots (QDs) can be controlled by magnetic doping and strongly depends on the excitation power density. We study two different II-VI magnetic systems; ZnTe/(Zn, Mn)Se QDs with magnetic dopants in the matrix surrounding the dots, and (Zn, Mn)Te/ZnSe QDs doped in the dot core. Both magnetic systems, regardless of the location of the dopant magnetic ions, show a stark contrast in their emission with high excitation power densities (P
ex) when compared to nonmagnetic ZnTe/ZnSe QDs. Using time-resolved photoluminescence (TRPL), we observe a saturation in the blue shift for the magnetic systems at a lower P
ex, while additionally exhibiting a limited lifetime shortening over the entire range of P
ex, when compared to the nonmagnetic QDs. The results for the two magnetic systems are very similar, showing no dependence on the location of the magnetic impurities. This suggests that the behavior observed is an effect of the magnetic polaron on the band bending in the high P
ex regime. The ability to use magnetic ions to quickly saturate the charge concentration and control band bending in QDs could potentially aid in optimizing optoelectronic devices which are sensitive to high charge variations.
Multilevel Regression and Poststratification Versus Survey Sample Weighting for Estimating Population Quantities in Large Population Health Studies
Authors: Downes Marnie , Carlin John B 
Published: April 2020

Abstract
Multilevel regression and poststratification (MRP) is a model-based approach for estimating a population parameter of interest, generally from large-scale surveys. It has been shown to be effective in highly selected samples, which is particularly relevant to investigators of large-scale population health and epidemiologic surveys facing increasing difficulties in recruiting representative samples of participants. We aimed to further examine the accuracy and precision of MRP in a context where census data provided reasonable proxies for true population quantities of interest. We considered 2 outcomes from the baseline wave of the Ten to Men study (Australia, 2013–2014) and obtained relevant population data from the 2011 Australian Census. MRP was found to achieve generally superior performance relative to conventional survey weighting methods for the population as a whole and for population subsets of varying sizes. MRP resulted in less variability among estimates across population subsets relative to sample weighting, and there was some evidence of small gains in precision when using MRP, particularly for smaller population subsets. These findings offer further support for MRP as a promising analytical approach for addressing participation bias in the estimation of population descriptive quantities from large-scale health surveys and cohort studies.
MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks
Authors: de Weerd Hendrik A , Badam Tejaswi V S , Martínez-Enguita David , Åkesson Julia , Muthas Daniel , Gustafsson Mika , Lubovac-Pilav Zelmina 
Published: April 2020

Abstract

Motivation
Complex diseases are due to the dense interactions of many disease-associated factors that dysregulate genes that in turn form the so-called disease modules, which have shown to be a powerful concept for understanding pathological mechanisms. There exist many disease module inference methods that rely on somewhat different assumptions, but there is still no gold standard or best-performing method. Hence, there is a need for combining these methods to generate robust disease modules.

Results
We developed MODule IdentiFIER (MODifieR), an ensemble R package of nine disease module inference methods from transcriptomics networks. MODifieR uses standardized input and output allowing the possibility to combine individual modules generated from these methods into more robust disease-specific modules, contributing to a better understanding of complex diseases.

Availability and implementation
MODifieR is available under the GNU GPL license and can be freely downloaded from https://gitlab.com/Gustafsson-lab/MODifieR and as a Docker image from https://hub.docker.com/r/ddeweerd/modifier.

Supplementary information
Supplementary data are available at Bioinformatics online.
New Measures for the Coronavirus Disease 2019 Response: A Lesson From the Wenzhou Experience
Authors: Ruan Linhui , Wen Min , Zeng Qingrun , Chen Chengshui , Huang Shengwei , Yang Su , Yang Jianjing , Wang Jingqiang , Hu Yuhuan , Ding Saidan , Zhang Ying , Zhang Hongxia , Feng Yuanjing , Jin Kunlin , Zhuge Qichuan 
Published: April 2020

Abstract
As the outbreak of coronavirus disease 2019 (COVID-19) has spread globally, determining how to prevent the spread is of paramount importance. We reported the effectiveness of different responses of 4 affected cities in preventing the COVID-19 spread. We expect the Wenzhou anti–COVID-19 measures may provide information for cities around the world that are experiencing this epidemic.
Laniakea: an open solution to provide Galaxy “on-demand” instances over heterogeneous cloud infrastructures
Authors: Tangaro Marco Antonio , Donvito Giacinto , Antonacci Marica , Chiara Matteo , Mandreoli Pietro , Pesole Graziano , Zambelli Federico 
Published: April 2020

Abstract

Background
While the popular workflow manager Galaxy is currently made available through several publicly accessible servers, there are scenarios where users can be better served by full administrative control over a private Galaxy instance, including, but not limited to, concerns about data privacy, customisation needs, prioritisation of particular job types, tools development, and training activities. In such cases, a cloud-based Galaxy virtual instance represents an alternative that equips the user with complete control over the Galaxy instance itself without the burden of the hardware and software infrastructure involved in running and maintaining a Galaxy server.

Results
We present Laniakea, a complete software solution to set up a “Galaxy on-demand” platform as a service. Building on the INDIGO-DataCloud software stack, Laniakea can be deployed over common cloud architectures usually supported both by public and private e-infrastructures. The user interacts with a Laniakea-based service through a simple front-end that allows a general setup of a Galaxy instance, and then Laniakea takes care of the automatic deployment of the virtual hardware and the software components. At the end of the process, the user gains access with full administrative privileges to a private, production-grade, fully customisable, Galaxy virtual instance and to the underlying virtual machine (VM). Laniakea features deployment of single-server or cluster-backed Galaxy instances, sharing of reference data across multiple instances, data volume encryption, and support for VM image-based, Docker-based, and Ansible recipe-based Galaxy deployments. A Laniakea-based Galaxy on-demand service, named Laniakea@ReCaS, is currently hosted at the ELIXIR-IT ReCaS cloud facility.

Conclusions
Laniakea offers to scientific e-infrastructures a complete and easy-to-use software solution to provide a Galaxy on-demand service to their users. Laniakea-based cloud services will help in making Galaxy more accessible to a broader user base by removing most of the burdens involved in deploying and running a Galaxy service. In turn, this will facilitate the adoption of Galaxy in scenarios where classic public instances do not represent an optimal solution. Finally, the implementation of Laniakea can be easily adapted and expanded to support different services and platforms beyond Galaxy.
Variational full-waveform inversion
Authors: Zhang Xin , Curtis Andrew 
Published: April 2020

SUMMARY
Seismic full-waveform inversion (FWI) can produce high-resolution images of the Earth’s subsurface. Since full-waveform modelling is significantly nonlinear with respect to velocities, Monte Carlo methods have been used to assess image uncertainties. However, because of the high computational cost of Monte Carlo sampling methods, uncertainty assessment remains intractable for larger data sets and 3-D applications. In this study, we propose a new method called variational FWI, which uses Stein variational gradient descent to solve FWI problems. We apply the method to a 2-D synthetic example and demonstrate that the method produces accurate approximations to those obtained by Hamiltonian Monte Carlo. Since variational inference solves the problem using optimization, the method can be applied to larger data sets and 3-D applications by using stochastic optimization and distributed optimization.
Full wave sensitivity of SK(K)S phases to arbitrary anisotropy in the upper and lower mantle
Authors: Tesoniero Andrea , Leng Kuangdai , D. Long Maureen , Nissen-Meyer Tarje 
Published: April 2020

SUMMARY
Core-refracted phases such as SKS and SKKS are commonly used to probe seismic anisotropy in the upper and lowermost portions of the Earth’s mantle. Measurements of SK(K)S splitting are often interpreted in the context of ray theory, and their frequency dependent sensitivity to anisotropy remains imperfectly understood, particularly for anisotropy in the lowermost mantle. The goal of this work is to obtain constraints on the frequency dependent sensitivity of SK(K)S phases to mantle anisotropy, particularly at the base of the mantle, through global wavefield simulations. We present results from a new numerical approach to modelling the effects of seismic anisotropy of arbitrary geometry on seismic wave propagation in global 3-D earth models using the spectral element solver AxiSEM3D. While previous versions of AxiSEM3D were capable of handling radially anisotropic input models, here we take advantage of the ability of the solver to handle the full fourth-order elasticity tensor, with 21 independent coefficients. We take advantage of the computational efficiency of the method to compute wavefields at the relatively short periods (5 s) that are needed to simulate SK(K)S phases. We benchmark the code for simple, single-layer anisotropic models by measuring the splitting (via both the splitting intensity and the traditional splitting parameters ϕ and δt) of synthetic waveforms and comparing them to well-understood analytical solutions. We then carry out a series of numerical experiments for laterally homogeneous upper mantle anisotropic models with different symmetry classes, and compare the splitting of synthetic waveforms to predictions from ray theory. We next investigate the full wave sensitivity of SK(K)S phases to lowermost mantle anisotropy, using elasticity models based on crystallographic preferred orientation of bridgmanite and post-perovskite. We find that SK(K)S phases have significant sensitivity to anisotropy at the base of the mantle, and while ray theoretical approximations capture the first-order aspects of the splitting behaviour, full wavefield simulations will allow for more accurate modelling of SK(K)S splitting data, particularly in the presence of lateral heterogeneity. Lastly, we present a cross-verification test of AxiSEM3D against the SPECFEM3D_GLOBE spectral element solver for global seismic waves in an anisotropic earth model that includes both radial and azimuthal anisotropy. A nearly perfect agreement is achieved, with a significantly lower computational cost for AxiSEM3D. Our results highlight the capability of AxiSEM3D to handle arbitrary anisotropy geometries and its potential for future studies aimed at unraveling the details of anisotropy at the base of the mantle.
Risk of Severe Bacterial Infection in People Living Human Immunodeficiency Virus Infection in the Combined Antiretroviral Therapy Era
Authors: Melliez Hugues , Mary-Krause Murielle , Guiguet Marguerite , Carrieri Patrizia , Abgrall Sophie , Enel Patricia , Gallien Sébastien , Duval Xavier , Duvivier Claudine , Pavie Juliette , Siguier Martin , Freire-Maresca Anaenza , Tattevin Pierre , Costagliola Dominique 
Published: April 2020

AbstractBackgroundSevere bacterial infections are the first cause of morbidity in people with human immunodeficiency virus (PWH). We aimed to assess their incidence and to analyze their determinants.MethodsWe studied human immunodeficiency virus (HIV)-1-infected individuals aged at least 15 years and prospectively followed between 2006 and 2015 in the French Hospital Database on HIV. The Andersen and Gill model was used to calculate the adjusted hazard ratios (HRs), focusing on heavy alcohol use and neutrophil function-altering comorbidities.ResultsOf 25 795 participants, 1414 developed 1883 severe bacterial infections. Between 2006 and 2009 and 2013 and 2015, the incidence fell from 13.2 (95% confidence interval [CI], 12.3–14.1) to 7.1 (95% CI, 6.3–7.8) per 1000 person-years. Heavy alcohol use was associated with an increased risk of severe bacterial infection (HR = 1.3, 95% CI = 1.1–1.7 for 40–80 g/day and HR = 1.6, 95% CI = 1.2–2.1 for &gt;80 g/day), as were diabetes, chronic kidney disease, and end-stage liver disease (HR = 1.2, 95% CI = 1.0–1.4 when 1 comorbidity; HR = 2.3, 95% CI = 1.6–3.4 when more than 1 comorbidity), and nonacquired immune deficiency syndrome-defining malignancy (HR = 2.0; 95% CI, 1.6–2.4).ConclusionsHeavy alcohol use was associated with an increased risk of severe bacterial infection, as were neutrophil function-altering comorbidities. Controlled-drinking approaches should be promoted and comorbidity management should be strengthened in PWH.
In vitro activity of ceftolozane/tazobactam alone and in combination with amikacin against MDR/XDR Pseudomonas aeruginosa isolates from Greece
Authors: Galani Irene , Papoutsaki Vassiliki , Karantani Irene , Karaiskos Ilias , Galani Lamprini , Adamou Panagiota , Deliolanis Ioannis , Kodonaki Antigoni , Papadogeorgaki Eleni , Markopoulou Margarita , Maraki Sofia , Damala Maria , Prifti Eleni , Vagiakou Eleni , Petinaki Efthimia , Fountoulis Kimon , Tsiplakou Sophia , Kirikou Helen , Souli Maria , Antoniadou Anastasia , Giamarellou Helen 
Published: April 2020

AbstractObjectivesWe evaluated the in vitro activity of ceftolozane/tazobactam and comparator agents against MDR non-MBL Pseudomonas aeruginosa isolates collected from nine Greek hospitals and we assessed the potential synergistic interaction between ceftolozane/tazobactam and amikacin.MethodsA total of 160 non-MBL P. aeruginosa isolates collected in 2016 were tested for susceptibility to ceftolozane/tazobactam and seven comparator agents including ceftazidime/avibactam. Time–kill assays were performed for synergy testing using ceftolozane/tazobactam 60 or 7.5 mg/L, corresponding to the peak and trough concentrations of a 1.5 g q8h dose, respectively, in combination with 69 mg/L amikacin, corresponding to the free peak plasma concentration. Synergy was defined as a ≥2 log10 cfu/mL reduction compared with the most active agent.ResultsOverall, ceftolozane/tazobactam inhibited 64.4% of the P. aeruginosa strains at ≤4 mg/L. Colistin was the most active agent (MIC50/90, 0.5/2 mg/L; 96.3% susceptible) followed by ceftazidime/avibactam (MIC50/90, 4/16 mg/L; 80.6% susceptible). GES-type enzymes were predominantly responsible for ceftolozane/tazobactam resistance; 81.6% of the non-producers were susceptible. MICs for the P. aeruginosa isolates selected for synergy testing were 2–32 mg/L ceftolozane/tazobactam and 2–128 mg/L amikacin. The combination of ceftolozane/tazobactam with amikacin was synergistic against 85.0% of all the isolates tested and against 75.0% of the GES producers. No antagonistic interactions were observed.ConclusionsCeftolozane/tazobactam demonstrated good in vitro activity against MDR/XDR P. aeruginosa clinical isolates, including strains with co-resistance to other antipseudomonal drugs. In combination with amikacin, a synergistic interaction at 24 h was observed against 85.0% of P. aeruginosa strains tested, including isolates with ceftolozane/tazobactam MICs of 32 mg/L or GES producers.
Development and Validation of a Liquid Chromatography High-Resolution Mass Spectrometry (LC-HRMS) Bioanalytical Method for Quantifying Cannabinoids in Whole Blood: Application for Determining Recent Cannabis Use
Authors: DeGregorio Michael W , Audino Susan A , Montoya Edward , Phong Aron , Kao Chiao-Jung , Wurz Gregory T 
Published: April 2020

Abstract

Background
Cannabis legalization is expanding rapidly throughout the United States, but there is no reliable means of establishing recent use.

Objective
To develop and validate a bioanalytical method for determination of Δ9-tetrahydrocannabinol (Δ9-THC), cannabinol, 11-hydroxy-Δ9-THC, 11-nor-9-carboxy-Δ9-THC, and 8β,11-dihydroxy-Δ9-THC in whole blood microsamples by liquid chromatography high-resolution mass spectrometry (LC-HRMS).

Methods
Cannabinoid extraction from whole blood was performed using a mixture of n-hexane/ethyl acetate (90:10, v/v). Chromatographic separation was performed with a C18 column using a binary mobile phase gradient of water and acetonitrile, each with 0.1% formic acid. Detection was performed by positive ion mode heated electrospray ionization with full scan MS on an Orbitrap mass spectrometer. A clinical study was performed in 30 subjects to identify recent cannabis use based on analysis of cannabinoids in blood samples up to 200 min post-smoking.

Results
Acceptable linearity of all calibration curves was observed (r2&gt;0.99) for all analytes over a 1–100 ng/mL concentration range, with acceptable accuracy. Limit of detection (LOD) was 0.5 ng/mL. Accuracy and precision met acceptance criteria for all analytes. Repeatability (CV) was &lt;5% at low (3 ng/mL) and high (90 ng/mL) concentrations. In the clinical study, the ratios between 11-nor-9-carboxy-Δ9-THC and Δ9-THC fell immediately after smoking and returned to near baseline levels by 200 min post-smoking, which is consistent with recent use.

Conclusions and Highlights
The developed LC-HRMS bioanalytical method is suitable for quantification of five key cannabinoids in whole capillary blood microsamples and can be used in conjunction with a test for determining recent cannabis use.
The Cognitive Mechanisms in Music Listening Interventions for Pain: A Scoping Review
Authors: Howlin Claire , Rooney Brendan 
Published: April 2020

AbstractMusic interventions have been introduced in a range of pain management contexts, yet considerable inconsistencies have been identified across evaluation studies. These inconsistencies have been attributed to a lack of clarity around the prospective cognitive mechanisms of action underlying such interventions. The current systematic scoping review was conducted to examine the theoretical rationales provided in the literature for introducing music listening interventions (MLIs) in pain contexts. 3 search terms (music, listening, and pain) were used in four electronic databases, and 75 articles were included for analysis. Content analysis was used to identify that more intensive listening schedules were associated with chronic and cancer pain compared with procedural pain. The degree to which patients had a choice over the music selection could be categorized into 1 of 5 levels. Thematic synthesis was then applied to develop 5 themes that describe the cognitive mechanisms involved in MLIs for pain. These mechanisms were brought together to build the Cognitive Vitality Model, which emphasizes the role of individual agency in mediating the beneficial effects of music listening through the processes of Meaning-Making, Enjoyment, and Musical Integration. Finally, content analysis was used to demonstrate that only a small proportion of studies were explicitly designed to examine the cognitive mechanisms underlying MLIs and we have suggested ways to improve future practice and empirical research. We call on researchers to design and evaluate MLIs in line with the Cognitive Vitality Model of music listening interventions for pain.
Impact of high baseline Aspergillus-specific IgG levels on weight and quality-of-life outcomes of patients with chronic pulmonary aspergillosis
Authors: Bongomin Felix , Garcez Tomaz , Denning David W 
Published: April 2020

Abstract
This study aimed to evaluate the impact of quantitative baseline Aspergillus-specific immunoglobulin G (IgG) serum levels on weight changes of patients with chronic pulmonary aspergillosis (CPA) under antifungal treatment. We retrospectively reviewed data of patients diagnosed with CPA between April 2015 and March 2018 at the National Aspergillosis Centre (Manchester, UK). All patients were on continued antifungal treatment for 12 months. Data on Aspergillus-specific IgG levels, St George's quality of life (SGQoL) variables and weight at baseline, 6 months and 12 months were extracted. We defined a high serum Aspergillus-specific IgG as ≥ 200 mg/l (Group A) and low level &lt; 200 mg/l (Group B). Forty-nine patients (37 male; 12 female), median age 65 years (range: 29–86) were studied. Overall, 33% (n = 16) of the patients were in Group A. The baseline characteristics between the two groups were similar. The median Charlson comorbidity index was 4 (range: 0–5) and 3 (range: 0–9) for Group A and Group B, respectively (P = .543). There was a sustained decline in median Aspergillus IgG levels from baseline, through 6 month to 12 months of continues therapy from 170 (range: 20–1110) to 121 (range: 20–1126), and finally 107 (15–937) mg/l, respectively (P &lt; .001). Group A patients gained more weight at 6 months (9/15 [60%] vs. 7/33 [21%], P = .012) and at 12 months of treatment (9/15 [60%] vs. 7/33 [22%]), and more patients in Group B lost weight ((13/33 [41%] vs. 1/15 [7%]), P = .015). However, there was no difference in QoL outcomes across groups at 6 (P = .3) and 12 (P = .7) months. A very high Aspergillus IgG may confer a higher likelihood of weight gain as a key, objective marker of clinical response, if patients can tolerate 12 months of antifungal therapy.
Long-term statistics of pulsar glitches triggered by a Brownian stress accumulation process
Authors: Carlin J B , Melatos A 
Published: April 2020

ABSTRACT
A microphysics-agnostic meta-model of rotational glitches in rotation-powered pulsars is developed, wherein the globally averaged internal stress accumulates as a Brownian process between glitches, and a glitch is triggered once a critical threshold is surmounted. Precise, falsifiable predictions are made regarding long-term event statistics in individual pulsars. For example, the Spearman cross-correlation coefficient between the size of a glitch and the waiting time until the next glitch should exceed 0.25 in all pulsars. Among the six pulsars with the most recorded glitches, PSR J0537−6910 and PSR J0835−4510 are consistent with the predictions of the meta-model, while PSR J1740−3015 and PSR J0631+1036 are not. PSR J0534+2200 and PSR J1341−6220 are only consistent with the meta-model, if there exists an undetected population of small glitches with small waiting times, which we do not resolve. The results are compared with a state-dependent Poisson process, another microphysics-agnostic meta-model in the literature. The results are also applied briefly to recent pulse-to-pulse observations of PSRJ0835−4510, which appear to reveal evidence for a negative fluctuation in rotation frequency just prior to the 2016 glitch.