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BACKGROUND: Circulating individual SFAs in pregnant females are critical for maternal and fetal health. However, research on identifying their modifiable factors is limited. OBJECTIVES: We aimed to examine the associations of total physical activity (PA) and types of PA with circulating individual SFAs during pregnancy in a multiracial/multiethnic cohort of pregnant females in the United States. METHODS: The study included participants in a nested case-control study (n = 321) from the Eunice Kennedy Shriver NICHD Fetal Growth Studies-Singleton Cohort. Sampling weights were applied, so the results represented the entire Fetal Growth Cohort. Plasma phospholipid SFAs were measured at 4 visits [10-14 (visit 1), 15-26 (visit 2), 23-31 (visit 3), and 33-39 (visit 4) weeks of gestation] throughout pregnancy. PA of the previous year at visit 1 and since the previous visit at the subsequent visits was assessed using the validated Pregnancy PA Questionnaire. Time-specific and longitudinal associations were examined using multivariable linear and generalized estimating equation models. RESULTS: Total PA (metabolic equivalent of task-h/wk) was positively associated with circulating heptadecanoic acid (17:0) at visit 1 (β × 103: 0.07; 95% CI: 0.02, 0.11) and pentadecanoic acid (15:0) at visit 3 (β × 103: 0.09; 95% CI: 0.03, 0.14) independent of sociodemographic, reproductive, pregnancy, and dietary factors. Across the 4 visits, the positive associations with total PA were consistent for pentadecanoic acid (β × 103: 0.06; 95% CI: 0.02, 0.10) and heptadecanoic acid (β × 103: 0.10; 95% CI: 0.06, 0.14). Out of the 4 PA types (i.e., sports/exercise, household/caregiving, transportation, and occupational PA) considered, the magnitude of positive associations was the largest for sports/exercise PA. CONCLUSIONS: Our findings suggest that maternal PA is positively associated with circulating pentadecanoic and heptadecanoic acids. The findings warrant confirmation by future studies.This trial was registered at clinicaltrials.gov as NCT00912132.

Interturn short circuit (ITSC) fault diagnosis at its early stage is very essential to improve the security of permanent magnet synchronous motors. In this article, a Bayesian optimization (BO) based residual convolutional neural network (CNN) algorithm for ITSC fault diagnosis was proposed. There are mainly two aspects of the contributions. First, it is a challenge to apply a conventional CNN on time-series signal tasks as they can only look back on history with a liner size, which will limit the network depth. Moreover, to obtain enough characteristics from acquired signals, the proposed algorithm requires adequate network depth, which may result in degradation difficulties. To solve these problems, a residual connection is embedded into the dilated CNN. Second, with the increase of network depth, the possible combination of hyperparameters will grow geometrically, thus the hyperparameters tuning will cost considerable time. To overcome this, the BO algorithm is adopted to select the optimal hyperparameter combination automatically. To demonstrate the effectiveness of the proposed algorithm, a motor fault experiment with various operating conditions was conducted on the motor that can be set for 17 fault severity levels. The test results and comparisons with other five algorithms show the advantage of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Background Collecting social determinants of health in electronic health records is time-consuming. Meanwhile, an Area Deprivation Index (ADI) aggregates sociodemographic information from census data. The objective of this study was to ascertain whether ADI is associated with stage of human papillomavirus (HPV)-related cancer at diagnosis. Methods We tested for the association between the stage of HPV-related cancer presentation and ADI as well as the association between stage and the value of each census-based measure using ordered logistic regression, adjusting for age, race and sex. Results Among 3247 cases of HPV-related cancers presenting to an urban academic medical center, the average age at diagnosis was 57. The average stage at diagnosis was Surveillance, Epidemiology and End Results Stage 3. In the study population, 43% of patients were female and 87% were white. In this study population, there was no association between stage of HPV-related cancer presentation and either aggregate or individual census variables. Conclusions These results may reflect insufficient sample size, a lack of socio-demographic diversity in our population, or suggest that simplifying social determinants of health into a single geocoded index is not a reliable surrogate for assessing a patient's risk for HPV-related cancer. [ABSTRACT FROM AUTHOR]

A methodology to assess the relative merits of using evaporation-pan networks and semiempirical functions to estimate reference-crop evapotranspiration (ET) is presented. Estimation-error variance is proposed as a basis for comparison. In the case of pan networks, ordinary kriging and universal kriging are viable options for determining estimation-error variance. In the case of semiempirical ET functions, a formulation is developed that expresses the estimation-error variance in terms of the uncertainties in extrapolating meteorological data from measurement locations. The proposed methodology is demonstrated within a 44,000 [km.sup.2] area of southern Florida. The results show that universal kriging is the preferred method for estimating reference-crop ET from pan measurements, and the Penman-Monteith method is the preferred estimation method from meteorological data. The pan-based universal kriging approach yields a lower estimation-error variance than the Penman-Monteith function, indicating that pan-based estimates of reference-crop evapo-transpiration are preferable to semiempirical evapotranspiration functions in south Florida.