Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting

Despite the prominent use of complex survey data and the growing popularity of machine learning methods in epidemiologic research, few machine learning software implementations offer options for handling complex samples. A major challenge impeding the broader incorporation of machine learning into epidemiologic research is incomplete guidance for analyzing complex survey data, including the importance of sampling weights for valid prediction in target populations. Using data from 15, 820 participants in the 1988-1994 National Health and Nutrition Examination Survey cohort, we determined whether ignoring weights in gradient boosting models of all-cause mortality affected prediction, as measured by the F1 score and corresponding 95% confidence intervals. In simulations, we additionally assessed the impact of sample size, weight variability, predictor strength, and model dimensionality. In the National Health and Nutrition Examination Survey data, unweighted model performance was inflated compared to the weighted model (F1 score 81.9% [95% confidence interval: 81.2%, 82.7%] vs 77.4% [95% confidence interval: 76.1%, 78.6%]). However, the error was mitigated if the F1 score was subsequently recalculated with observed outcomes from the weighted dataset (F1: 77.0%; 95% confidence interval: 75.7%, 78.4%). In simulations, this finding held in the largest sample size (N = 10,000) under all analytic conditions assessed. For sample sizes <5,000, sampling weights had little impact in simulations that more closely resembled a simple random sample (low weight variability) or in models with strong predictors, but findings were inconsistent under other analytic scenarios. Failing to account for sampling weights in gradient boosting models may limit generalizability for data from complex surveys, dependent on sample size and other analytic properties. In the absence of software for configuring weighted algorithms, post-hoc re-calculations of unweighted model performance using weighted observed outcomes may more accurately reflect model prediction in target populations than ignoring weights entirely

Born-Infeld Type Phantom Model in the ω−ω′\omega-\omega' Plane

In this paper, we investigate the dynamics of Born-Infeld(B-I) phantom model in the $\omega-\omega'$ plane, which is defined by the equation of state parameter for the dark energy and its derivative with respect to $N$(the logarithm of the scale factor $a$). We find the scalar field equation of motion in $\omega-\omega'$ plane, and show mathematically the property of attractor solutions which correspond to $\omega_\phi\sim-1$, $\Omega_\phi=1$, which avoid the "Big rip" problem and meets the current observations well.Comment: 6 pages, 3 figures, some references adde

Uncommon genetic syndromes and narrative production - Case Studies with Williams, Smith-Magenis and Prader- Willi Syndromes

This study compares narrative production among three syndromes with genetic microdeletions: Williams syndrome (WS), Smith-Magenis syndrome (SMS), and Prader-Willi syndrome (PWS), characterized by intellectual disabilities and relatively spared language abilities. Our objective is to study the quality of narrative production in the context of a common intellectual disability. To elicit a narrative production, the task Frog! Where Are You was used. Then, structure, process, and content of the narrative process were analysed in the three genetic disorders:WS (n52), SMS (n52), and PWS (n52). Data show evidence of an overall low narrative quality in these syndromes, despite a high variability within different measures of narrative production. Results support the hypothesis that narrative is a highly complex cognitive process and that, in a context of intellectual disability, there is no evidence of particular ‘hypernarrativity’ in these syndromes.This research was supported by the grants FEDER –

Revisiting the HD 21749 planetary system with stellar activity modelling

HD 21749 is a bright (V = 8.1 mag) K dwarf at 16 pc known to host an inner terrestrial planet HD 21749c as well as an outer sub-Neptune HD 21749b, both delivered by Transiting Exoplanet Survey Satellite (TESS). Follow-up spectroscopic observations measured the mass of HD 21749b to be 22.7 ± 2.2 M with a density of 7.0^{+1.6}_{-1.3} g cm-3, making it one of the densest sub-Neptunes. However, the mass measurement was suspected to be influenced by stellar rotation. Here, we present new high-cadence PFS RV data to disentangle the stellar activity signal from the planetary signal. We find that HD 21749 has a similar rotational time-scale as the planet's orbital period, and the amplitude of the planetary orbital RV signal is estimated to be similar to that of the stellar activity signal. We perform Gaussian process regression on the photometry and RVs from HARPS and PFS to model the stellar activity signal. Our new models reveal that HD 21749b has a radius of 2.86 ± 0.20 R, an orbital period of 35.6133 ± 0.0005 d with a mass of Mb = 20.0 ± 2.7 M and a density of 4.8^{+2.0}_{-1.4} g cm-3 on an eccentric orbit with e = 0.16 ± 0.06, which is consistent with the most recent values published for this system. HD 21749c has an orbital period of 7.7902 ± 0.0006 d, a radius of 1.13 ± 0.10 R, and a 3σ mass upper limit of 3.5 M. Our Monte Carlo simulations confirm that without properly taking stellar activity signals into account, the mass measurement of HD 21749b is likely to arrive at a significantly underestimated error bar

First-order formalism for dark energy and dust

This work deals with first-order formalism for dark energy and dust in standard cosmology, for models described by real scalar field in the presence of dust in spatially flat space. The field dynamics may be standard or tachyonic, and we show how the equations of motion can be solved by first-order differential equations. We investigate a model to illustrate how the dustlike matter may affect the cosmic evolution using this framework.Comment: 5 pages, 1 figure; title changed, new author included, discussions extended, references added, version to appear in EPJ

Associations between alcohol and cigarette use and type 1 and 2 myocardial infarction among people with HIV

Objectives: People with HIV have a higher risk of myocardial infarction (MI) than the general population, with a greater proportion of type 2 MI (T2MI) due to oxygen demand–supply mismatch compared with type 1 (T1MI) resulting from atherothrombotic plaque disruption. People living with HIV report a greater prevalence of cigarette and alcohol use than do the general population. Alcohol use and smoking as risk factors for MI by type are not well studied among people living with HIV. We examined longitudinal associations between smoking and alcohol use patterns and MI by type among people living with HIV. Design and Methods: Using longitudinal data from the Centers for AIDS Research Network of Integrated Clinical Systems cohort, we conducted time-updated Cox proportional hazards models to determine the impact of smoking and alcohol consumption on adjudicated T1MI and T2MI. Results: Among 13 506 people living with HIV, with a median 4 years of follow-up, we observed 177 T1MI and 141 T2MI. Current smoking was associated with a 60% increase in risk of both T1MI and T2MI. In addition, every cigarette smoked per day was associated with a 4% increase in risk of T1MI, with a suggestive, but not significant, 2% increase for T2MI. Cigarette use had a greater impact on T1MI for men than for women and on T2MI for women than for men. Increasing alcohol use was associated with a lower risk of T1MI but not T2MI. Frequency of heavy episodic alcohol use was not associated with MI. Conclusions: Our findings reinforce the prioritization of smoking reduction, even without cessation, and cessation among people living with HIV for MI prevention and highlight the different impacts on MI type by gender

TOI 122b and TOI 237b: Two Small Warm Planets Orbiting Inactive M Dwarfs Found by TESS

We report the discovery and validation of TOI 122b and TOI 237b, two warm planets transiting inactive M dwarfs observed by the Transiting Exoplanet Survey Satellite (TESS). Our analysis shows that TOI 122b has a radius of 2.72 ± 0.18 R ⊕ and receives 8.8 ± 1.0 times Earth's bolometric insolation, and TOI 237b has a radius of 1.44±0.12 R ⊕ and receives 3.7 ± 0.5 times Earth's insolation, straddling the 6.7 Earth insolation that Mercury receives from the Sun. This makes these two of the cooler planets yet discovered by TESS, even on their 5.08 and 5.43 day orbits. Together, they span the small-planet radius valley, providing useful laboratories for exploring volatile evolution around M dwarfs. Their relatively nearby distances (62.23 ± 0.21 pc and 38.11 ± 0.23 pc, respectively) make them potentially feasible targets for future radial velocity follow-up and atmospheric characterization, although such observations may require substantial investments of time on large telescopes

Track E Implementation Science, Health Systems and Economics

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138412/1/jia218443.pd

Canadian Normative Data for Minimal Assessment of Cognitive Function in Multiple Sclerosis

Objective: The Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) is a consensus-based collection of neuropsychological tests that evaluate cognitive functioning in individuals with multiple sclerosis (MS). The tests are typically scored using each respective published test manual, leaving the examiner to make interpretations from norms derived from different American populations. Given demographic differences, this may lead to misinterpretation of findings in Canadians. Our goal was to establish both discrete and regression-based normative data for the MACFIMS based on a largely co-normed Canadian population to allow for improved psychometric interpretation. Methods: MACFIMS data sets were aggregated from across three different Canadian cities (Ottawa, Toronto, and London), yielding a total of 330 healthy control participants from four different studies evaluating cognition in individuals with MS. Given the variety of contributing studies, there was variability in terms of the number of participants completing each measure. Results: Both age-based discrete normative data and demographically adjusted (sex, age, and educa