scholarly journals Bayesian calibration of the mixing length parameter αML and of the helium-to-metal enrichment ratio ΔY/ΔZ with open clusters: the Hyades test-bed

2020 ◽  
Vol 501 (1) ◽  
pp. 383-397
Author(s):  
E Tognelli ◽  
M Dell’Omodarme ◽  
G Valle ◽  
P G Prada Moroni ◽  
S Degl’Innocenti

ABSTRACT We tested the capability of a Bayesian procedure to calibrate both the helium abundance and the mixing length parameter (αML), using precise photometric data for main-sequence (MS) stars in a cluster with negligible reddening and well-determined distance. The method has been applied first to a mock data set generated to mimic Hyades MS stars and then to the real Hyades cluster. We tested the impact on the results of varying the number of stars in the sample, the photometric errors, and the estimated [Fe/H]. The analysis of the synthetic data set shows that αML is recovered with a very good precision in all the analysed cases (with an error of few percent), while [Fe/H] and the helium-to-metal enrichment ratio ΔY/ΔZ are more problematic. If spectroscopic determinations of [Fe/H] are not available and thus [Fe/H] has to be recovered alongside with ΔY/ΔZ and αML, the well-known degeneracy between [Fe/H]–ΔY/ΔZ-αML could result in a large uncertainty on the recovered parameters, depending on the portion of the MS used for the analysis. On the other hand, the prior knowledge of an accurate [Fe/H] value puts a strong constraint on the models, leading to a more precise parameters recovery. Using the current set of pisa models, the most recent [Fe/H] value and the Gaia photometry and parallaxes for the Hyades cluster, we obtained the average values <αML> = 2.01 ± 0.05 and <ΔY/ΔZ> = 2.03 ± 0.33, sensitively reducing the uncertainty in these important parameters.

2017 ◽  
Vol 61 (5) ◽  
Author(s):  
Joseph J. Carreno ◽  
Ben Lomaestro ◽  
John Tietjan ◽  
Thomas P. Lodise

ABSTRACT This study evaluated the predictive performance of a Bayesian PK estimation method (ADAPT V) to estimate the 24-h vancomycin area under the curve (AUC) with limited pharmacokinetic (PK) sampling in adult obese patients receiving vancomycin for suspected or confirmed Gram-positive infections. This was an Albany Medical Center Institutional Review Board-approved prospective evaluation of 12 patients. Patients had a median (95% confidence interval) age of 61 years (39 to 71 years), a median creatinine clearance of 86 ml/min (75 to 120 ml/min), and a median body mass index of 45 kg/m2 (40 to 52 kg/m2). For each patient, five PK concentrations were measured, and four different vancomycin population PK models were used as Bayesian priors to estimate the vancomycin AUC (AUCFULL). Using each PK model as a prior, data-depleted PK subsets were used to estimate the 24-h AUC (i.e., peak and trough data [AUCPT], midpoint and trough data [AUCMT], and trough-only data [AUCT]). The 24-h AUC derived from the full data set (AUCFULL) was compared to the AUC derived from data-depleted subsets (AUCPT, AUCMT, and AUCT) for each model. For the four sets of analyses, AUCFULL estimates ranged from 437 to 489 mg·h/liter. The AUCPT provided the best approximation of the AUCFULL; AUCMT and AUCT tended to overestimate AUCFULL. Further prospective studies are needed to evaluate the impact of AUC monitoring in clinical practice, but the findings from this study suggest that the vancomycin AUC can be estimated with good precision and accuracy with limited PK sampling using Bayesian PK estimation software.


2019 ◽  
Vol 623 ◽  
pp. A59 ◽  
Author(s):  
G. Valle ◽  
M. Dell’Omodarme ◽  
P. G. Prada Moroni ◽  
S. Degl’Innocenti

Aims. We critically analysed the theoretical foundation and statistical reliability of the mixing-length calibration by means of standard (Teff, [Fe/H]) and global asteroseismic observables (Δν, νmax) of field stars. We also discussed the soundness of inferring a possible metallicity dependence of the mixing-length parameter from field stars. Methods. We followed a theoretical approach based on mock datasets of artificial stars sampled from a grid of stellar models with a fixed mixing-length parameter αml. We then recovered the mixing-length parameter of the mock stars by means of SCEPtER maximum-likelihood algorithm. We finally analysed the differences between the true and recovered mixing-length values quantifying the random errors due to the observational uncertainties and the biases due to possible discrepancies in the chemical composition and input physics between artificial stars and the models adopted in the recovery. Results. We verified that the αml estimates are affected by a huge spread, even in the ideal configuration of perfect agreement between the mock data and the recovery grid of models. While the artificial stars were computed at fixed solar-calibrated αml = 2.10, the recovered values had a mean of 2.20 and a standard deviation of 0.52. Then we explored the case in which the solar heavy-element mixture used to compute the models is different from that adopted in the artificial stars. We found an estimated mixing-length mean of 2.24 ± 0.48 and, more interestingly, a metallicity relationship in which αml increases by 0.4 for an increase of 1 dex in [Fe/H]. Thus, a simple heavy-element mixture mismatch induced a spurious, but statistically robust, dependence of the estimated mixing-length on metallicity. The origin of this trend was further investigated considering the differences in the initial helium abundance Y – [Fe/H] – initial metallicity Z relation assumed in the models and data. We found that a discrepancy between the adopted helium-to-metal enrichment ratio ΔY/ΔZ caused the appearance of spurious trends in the estimated mixing-length values. An underestimation of its value from ΔY/ΔZ = 2.0 in the mock data to ΔY/ΔZ = 1.0 in the recovery grid resulted in an increasing trend, while the opposite behaviour occurred for an equivalent overestimation. A similar effect was caused by an offset in the [Fe/H] to global metallicity Z conversion. A systematic overestimation of [Fe/H] by 0.1 dex in the recovery grid of models forced an increasing trend of αml versus [Fe/H] of about 0.2 per dex. We also explored the impact of some possible discrepancies between the adopted input physics in the recovery grid of models and mock data. We observed an induced trend with metallicity of about Δαml = 0.3 per dex when the effect of the microscopic diffusion is neglected in the recovery grid, while no trends originated from a wrong assumption on the effective temperature scale by ±100 K. Finally, we proved that the impact of different assumptions on the outer boundary conditions was apparent only in the RGB phase. Conclusions. We showed that the mixing-length estimates of field stars are affected by a huge spread even in an ideal case in which the stellar models used to estimate αml are exactly the same models as used to build the mock dataset. Moreover, we proved that there are many assumptions adopted in the stellar models used in the calibration that can induce spurious trend of the estimated αml with [Fe/H]. Therefore, any attempt to calibrate the mixing-length parameter by means of Teff, [Fe/H], Δν, and νmax of field stars seems to be statistically poorly reliable. As such, any claim about the possible dependence of the mixing-length on the metallicity for field stars should be considered cautiously and critically.


Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.


2013 ◽  
Vol 99 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Aaron Young ◽  
Philip Davignon ◽  
Margaret B. Hansen ◽  
Mark A. Eggen

ABSTRACT Recent media coverage has focused on the supply of physicians in the United States, especially with the impact of a growing physician shortage and the Affordable Care Act. State medical boards and other entities maintain data on physician licensure and discipline, as well as some biographical data describing their physician populations. However, there are gaps of workforce information in these sources. The Federation of State Medical Boards' (FSMB) Census of Licensed Physicians and the AMA Masterfile, for example, offer valuable information, but they provide a limited picture of the physician workforce. Furthermore, they are unable to shed light on some of the nuances in physician availability, such as how much time physicians spend providing direct patient care. In response to these gaps, policymakers and regulators have in recent years discussed the creation of a physician minimum data set (MDS), which would be gathered periodically and would provide key physician workforce information. While proponents of an MDS believe it would provide benefits to a variety of stakeholders, an effort has not been attempted to determine whether state medical boards think it is important to collect physician workforce data and if they currently collect workforce information from licensed physicians. To learn more, the FSMB sent surveys to the executive directors at state medical boards to determine their perceptions of collecting workforce data and current practices regarding their collection of such data. The purpose of this article is to convey results from this effort. Survey findings indicate that the vast majority of boards view physician workforce information as valuable in the determination of health care needs within their state, and that various boards are already collecting some data elements. Analysis of the data confirms the potential benefits of a physician minimum data set (MDS) and why state medical boards are in a unique position to collect MDS information from physicians.


2019 ◽  
Vol 11 (1) ◽  
pp. 156-173
Author(s):  
Spenser Robinson ◽  
A.J. Singh

This paper shows Leadership in Energy and Environmental Design (LEED) certified hospitality properties exhibit increased expenses and earn lower net operating income (NOI) than non-certified buildings. ENERGY STAR certified properties demonstrate lower overall expenses than non-certified buildings with statistically neutral NOI effects. Using a custom sample of all green buildings and their competitive data set as of 2013 provided by Smith Travel Research (STR), the paper documents potential reasons for this result including increased operational expenses, potential confusion with certified and registered LEED projects in the data, and qualitative input. The qualitative input comes from a small sample survey of five industry professionals. The paper provides one of the only analyses on operating efficiencies with LEED and ENERGY STAR hospitality properties.


Author(s):  
Thomas Christiansen

This chapter discusses whether the European Union has a distinctive take on, and may make a particular contribution to, global governance, as well as the reverse image of the impact that global governance has in the development of integration in Europe. This includes a focus on collective norms and interests as expressed through common institutions, policies, and activities. In doing so, the chapter compares and contrasts the evolution of a supranational order in Europe with the growth of global regimes and the emergence of a multipolar world, and explores the nature of the EU’s relationships with other global powers and regions. In a final section, the chapter asks whether the EU’s relationship with global developments is best seen as a test-bed for new ideas, procedures, and concepts; a construction for the defence of a privileged way of life; or an archaic remnant of a different era.


2019 ◽  
Vol 33 (3) ◽  
pp. 187-202
Author(s):  
Ahmed Rachid El-Khattabi ◽  
T. William Lester

The use of tax increment financing (TIF) remains a popular, yet highly controversial, tool among policy makers in their efforts to promote economic development. This study conducts a comprehensive assessment of the effectiveness of Missouri’s TIF program, specifically in Kansas City and St. Louis, in creating economic opportunities. We build a time-series data set starting 1990 through 2012 of detailed employment levels, establishment counts, and sales at the census block-group level to run a set of difference-in-differences with matching estimates for the impact of TIF at the local level. Although we analyze the impact of TIF on a wide set of indicators and across various industry sectors, we find no conclusive evidence that the TIF program in either city has a causal impact on key economic development indicators.


2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yahya Albalawi ◽  
Jim Buckley ◽  
Nikola S. Nikolov

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ian Glaspole ◽  
Francesco Bonella ◽  
Elena Bargagli ◽  
Marilyn K. Glassberg ◽  
Fabian Caro ◽  
...  

Abstract Background Idiopathic pulmonary fibrosis (IPF) predominantly affects individuals aged > 60 years who have several comorbidities. Nintedanib is an approved treatment for IPF, which reduces the rate of decline in forced vital capacity (FVC). We assessed the efficacy and safety of nintedanib in patients with IPF who were elderly and who had multiple comorbidities. Methods Data were pooled from five clinical trials in which patients were randomised to receive nintedanib 150 mg twice daily or placebo. We assessed outcomes in subgroups by age < 75 versus ≥ 75 years, by < 5 and ≥ 5 comorbidities, and by Charlson Comorbidity Index (CCI) ≤ 3 and > 3 at baseline. Results The data set comprised 1690 patients. Nintedanib reduced the rate of decline in FVC (mL/year) over 52 weeks versus placebo in patients aged ≥ 75 years (difference: 105.3 [95% CI 39.3, 171.2]) (n = 326) and < 75 years (difference 125.2 [90.1, 160.4]) (n = 1364) (p = 0.60 for treatment-by-time-by-subgroup interaction), in patients with < 5 comorbidities (difference: 107.9 [95% CI 65.0, 150.9]) (n = 843) and ≥ 5 comorbidities (difference 139.3 [93.8, 184.8]) (n = 847) (p = 0.41 for treatment-by-time-by-subgroup interaction) and in patients with CCI score ≤ 3 (difference: 106.4 [95% CI 70.4, 142.4]) (n = 1330) and CCI score > 3 (difference: 129.5 [57.6, 201.4]) (n = 360) (p = 0.57 for treatment-by-time-by-subgroup interaction). The adverse event profile of nintedanib was generally similar across subgroups. The proportion of patients with adverse events leading to treatment discontinuation was greater in patients aged ≥ 75 years than < 75 years in both the nintedanib (26.4% versus 16.0%) and placebo (12.2% versus 10.8%) groups. Similarly the proportion of patients with adverse events leading to treatment discontinuation was greater in patients with ≥ 5 than < 5 comorbidities (nintedanib: 20.5% versus 15.7%; placebo: 12.1% versus 10.0%). Conclusions Our findings suggest that the effect of nintedanib on reducing the rate of FVC decline is consistent across subgroups based on age and comorbidity burden. Proactive management of adverse events is important to reduce the impact of adverse events and help patients remain on therapy. Trial registration: ClinicalTrials.gov NCT00514683, NCT01335464, NCT01335477, NCT02788474, NCT01979952.


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