Development of Bayesian temporal models for global health estimation in data-limited settings

Estimation of health indicators globally is complicated because of data sparsity and data quality issues, especially in low and middle income countries without well-functioning registration systems. This dissertation introduces Bayesian methods for the estimation of stillbirth rates and adult mortality in data-limited settings. Motivated by statistical challenges in the estimation of stillbirth rates globally, we develop a Bayesian hierarchical temporal sparse regression model (BHTSRM). Bayesian hierarchical temporal regression models combine a hierarchical regression model with a temporal smoothing process. This type of model has been used for estimating health indicators for multiple populations in data-sparse settings to track high-quality data while producing covariate-driven estimates for populations with limited or no data. To extend its usage to settings where the number of candidate covariates is large relative to data availability, we propose the use of BHTSRMs that impose sparsity by using horseshoe priors on regression coefficients. We also develop a method to adjust observations with alternative stillbirth definitions and account for varying levels of uncertainty associated with different data sources in fitting the BHTSRM to stillbirth data. The proposed model has been used by the United Nations to estimate stillbirth rates globally. To facilitate prediction based on BHTSRMs, we propose an associated variable selection method: horseshoe shrinkage parameter reference distribution variable selection (HSS-VS). We check the performance of the new method through simulation exercises and use it for variable selection in the estimation of stillbirth rates. In low and middle income countries without well-functioning registration systems, sibling survival history (SSH) data can be used to estimate adult mortality but it may be subject to substantial reporting errors. We propose a new Bayesian survival model to estimate age-cohort specific survival probabilities from SSH data while accounting for bias and uncertainty introduced by SSH reporting errors. In the model, the cumulative hazard function is captured with a two-dimensional spline function. We apply it to estimate adult survival in Senegal

Estimating the stillbirth rate for 195 countries using a Bayesian sparse regression model with temporal smoothing

Estimation of stillbirth rates globally is complicated because of the paucity of reliable data from countries where most stillbirths occur. We com-piled data and developed a Bayesian hierarchical temporal sparse regression model for estimating stillbirth rates for 195 countries from 2000 to 2019. The model combines covariates with a temporal smoothing process so that estimates are data-driven in country-periods with high-quality data and deter-mined by covariates for country-periods with limited or no data. Horseshoe priors are used to encourage sparseness. The model adjusts observations with alternative stillbirth definitions and accounts for various sources of uncer-tainty. In-sample goodness of fit and out-of-sample validation results suggest that the model is reasonably well calibrated. The model is used by the UN In-teragency Group for Child Mortality Estimation to monitor the stillbirth rate for 195 countries

Modeling learning behaviors and predicting performance in an intelligent tutoring system: a two-layer hidden Markov modeling approach

To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with different learning outcomes demonstrated distinct learning patterns. Students who failed a problem set exhibited more passive learning behaviors and could hardly learn from practice, while students who mastered a problem set could effectively regulate their learning. Furthermore, we extended the use of TL-HMM to predicting learning outcome from behavior sequences and checked through cross-validation. TL-HMM is demonstrated helpful to gain insight into learners’ interactions with online learning environments. In practice, TL-HMM could be embedded in intelligent tutoring systems to monitor learning behaviors and learner status, so as to detect the difficulties of learners and facilitate learning

Study on controlling factors and developing a quantitative assessment model for spontaneous combustion hazard of coal gangue

Developing a quantitative hazard assessment model for spontaneous coal gangue combustion is imperative to ensuring the safety of coal mining operations. In this study, eight types of coal gangue from different coalfields were used to determine the controlling factors for spontaneous combustion. A variety of physical and chemical characterization methods were employed to investigate the physical and chemical characteristics of the samples. Based on the experimental results, six key parameters were identified, namely the aliphatic C–H components, pyrite sulfur content, physical oxygen absorption capacity, ash content, ignition point temperature, and activation energy for thermal decomposition. The results show that the spontaneous combustion hazard of coal gangue is positively correlated with the first three of these and is negatively correlated with the rest. Using the entropy-weight method combined with the analytic hierarchy process, appropriate weighting factors for each parameter were obtained and used to establish a quantitative assessment model for the spontaneous combustion hazard of coal gangue. This model is expected to enhance the current industrial best practices for the prevention and control of spontaneous coal gangue combustion

A New Approach to Estimate Age-Specific Mortality From Sibling Survival History Data in the Presence of Recall Errors

Sibling survival history (SSH) data can be used to estimate adult mortality rates. However, SSH data may be subject to substantial reporting errors in the form of omissions of siblings, or misreported years of birth and age at death. We present a new Bayesian survival modeling approach (B-Surv) to estimate agecohort-specific survival probabilities from SSH data while accounting for bias and uncertainty introduced by the age reporting errors. In the model, true survival by cohort and age is captured with a twodimensional splines function. SSH reported date of birth (DoB) and age at death (AaD) are the sum of the latent true outcome and a reporting error. A bivariate distribution of reporting errors in (DoB, AaD) is obtained from an analysis of such errors and its predictors, obtained from a comparison of SSH data with gold-standard data obtained in recent validation study conducted in a health demographic surveillance system in Senegal. We illustrate the approach using simulations and apply it to estimate adult survival in Senegal from DHS data

Three New Cycloartenol Triterpenoid Saponins from the Roots of Cimicifuga simplex Wormsk

Three new cycloartenol triterpene saponins, named shengmaxinsides A-C, have been isolated from the ethyl acetate soluble fraction of an ethanol extract of Cimicifuga simplex Wormsk roots. Their structures were established by chemical tests and detailed spectroscopic analysis as 25-O-acetyl-7,8-didehydrocimigenol-3-O-β-D-galactopyranoside (1), 7,8-didehydrocimigenol-3-O-β-D-galactopyranoside (2) and 7,8-didehydro-24S-O-acetylhydroshengmanol-3-O-β-D-galactopyranoside (3), respectively

Triassic depleted lithospheric mantle underneath the Paleozoic Chinese Altai orogen: Evidence from MORB-like basalts

Whole-rock geochemical and Sr-Nd-Pb-Hf isotopic analyses were conducted on the Triassic Ashele post-orogenie basalts from the Chinese Altai. The tholeiitic Ashele basalts possess moderate Na2O (2.46-4.52 wt%) but extremely low K2O (<= 0.06 wt%) contents, and are depleted in light rare earth elements (LREE). Their (La/Sm)(N) and (La/Yb)(N) ratios range from 0.78 to 0.88 and from 0.72 to 0.84, respectively, which, together with their low initial Sr-87/Sr-86 (0.7048-0.7052), high epsilon Nd(t) ( + 4.9 to + 5.6) and epsilon Hf(t) ( + 14.3 to + 16.3) values, indicate that the magmas were derived from a depleted mantle source. Their (206)pb/(204)pb and Pb-207/Pb-204 ratios (17.919-18.125 and 15.507-15.522, respectively) also support this interpretation. On the other hand, the Ashele basalts are enriched in Cs, Th and U, but depleted in Rb, Ba, Nb and Ta, possibly due to slight mantle metasomatism by subduction-related fluids. Because there was no record for large-scale thermal activity in the deep mantle during the Triassic, and geological evidence demonstrates reactivation of the Emil's fault, we propose that such a tectonic reactivation affected-the lithospherit mantle and resulted in its partial melting and subsequent generation of the Ashele basalts. This study shows that a depleted lithospheric mantle, not an ancient continental lithosphere, was underneath the Chinese Altai in the Triassic, which was possibly accreted during the Paleozoic orogeny. Therefore, the lithospheric mantle in this area today was possibly evolved from such a depleted mantle modified by consecutive partial melting after the Paleozoic orogeny

Petrogenesis and geodynamic implications of two episodes of Permian and Triassic high-silica granitoids in the Chinese Altai, Central Asian Orogenic Belt

Tectonic transition from post-collision to intraplate settings is a crucial process in orogenic belts. To characterize such a transition in the Chinese Altai, we conduct an integrated study on Permian to Triassic granitoids. Zircon U-Pb dating reveals that the granitoids can be subdivided into two stages: early Permian (291-286 Ma) and late Triassic (216-209 Ma). Granitoids of both two stages exhibit high SiO2, low Mg#, low Cr and Ni contents, and variable Sr-Nd-Hf isotopes, all of which indicate a multiple crustal origin. Generally, the Triassic granitoids have similar epsilon Nd(t) but relatively higher epsilon Hf(t) values than those of the Permian granitoids. Moreover, the Triassic granitoids possess relatively higher ASI and more variable Al2O3/TiO2, CaO/Na2O, Rb/Sr and Rb/Ba values than those of the Permian granitoids, suggesting that the Triassic magmatic sources were much variable and complicated with higher proportions of sediments. By integrating regional data, two magmatic peaks at Permian and Triassic can also be recognized. From early Permian to Triassic, the SiO2, Na2O + K2O and Th contents, ASI and Sr-87/ Sr-86, Al2O3/TiO2, Rb/Sr and Rb/Ba values for the felsic rocks gradually increase, implying more and more strongly reworking of continental crust. Also, the Rb, Y + Nb and Yb + Ta concentrations for felsic rocks progressively increase from early Permian to Triassic, demonstrating a geodynamic evolution from syn/post-collision to intraplate settings. Furthermore, we propose that the post-collision and intraplate tectonism, especially the latter, could facilitate the generation of high-silica granites, which drive maturation of continental crust in accretionary orogenic belts

Effects of dietary supplementation with epidermal growth factor-expressing Saccharomyces cerevisiae on duodenal development in weaned piglets

The aim of the present study was to assess the effects of dietary supplementation with epidermal growth factor (EGF)-expressing Saccharomyces cerevisiae on duodenal development in weaned piglets. In total, forty piglets weaned at 21–26 d of age were assigned to one of the five groups that were provided basic diet (control group) or diet supplemented with S. cerevisiae expressing either empty-vector (INVSc1(EV) group), tagged EGF (T-EGF) (INVSc1-TE(−) group), extracellular EGF (EE-EGF) (INVSc1-EE(+) group) or intracellular EGF (IE-EGF) (INVSc1-IE(+) group). All treatments were delivered as 60·00 μg/kg body weight EGF/d. On 0, 7, 14 and 21 d, eight piglets per treatment were sacrificed to analyse the morphology, activities and mRNA expressions of digestive enzymes, as well as Ig levels (IgA, IgM, IgG) in duodenal mucosa. The results showed significant improvement on 7, 14 and 21 d, with respect to average daily gain (P&lt;0·05), mucosa morphology (villus height and crypt depth) (P&lt;0·05), Ig levels (P&lt;0·01), activities and mRNA expressions of digestive enzymes (creatine kinase, alkaline phosphatase, lactate dehydrogenase and sucrase) (P&lt;0·05) and the mRNA expression of EGF-receptor (P&lt;0·01) in NVSc1-TE(−), INVSc1-EE(+) and INVSc1-IE(+) groups compared with control and INVSc1(EV) groups. In addition, a trend was observed in which the INVSc1-IE(+) group showed an improvement in Ig levels (0·05&lt;P&lt;0·10), mRNA expressions of digestive enzymes and EGF-receptor (P&lt;0·05) compared with NVSc1-TE(−) and INVSc1-EE(+) groups. These results indicate that supplementing recombinant EGF-expressing S. cerevisiae to the diet of weaned piglets enhanced duodenal development. Moreover, biological activity (Ig levels, mRNA expressions of digestive enzymes and EGF-receptor) of IE-EGF was better than either EE-EGF or T-EGF