The impacts of water level fluctuations from paddy fields and aquaculture ponds on wetland habitats for wintering waterbirds: Implications for wetland management

The distribution and composition of wetland habitats for wintering waterbirds are heavily influenced by water level fluctuations. Through polder construction and aquaculture activities, paddy fields and aquaculture ponds have decreased the lateral connectivity of water level fluctuations in the lake. However, the impacts of water level fluctuations on habitat suitability, which can be seen using high-resolution images analysis, often cannot separate disturbances caused by the paddy fields and aquaculture ponds, and it is difficult to capture the actual impact of water level fluctuations on wetland habitats. Based on remote sensing image data and hydrological data, we selected Caizi Lake as a study site and comparatively analyzed the changes in wintering waterbird habitats in a water level sequence under the two scenarios. Our work showed that paddy fields and aquaculture ponds should be considered as potential options for creating more suitable habitats for migratory waterbirds if combined with reasonable and effective management of the water level within the paddy fields and aquaculture ponds. The present study results could facilitate the management and sustainable utilization of Caizi Lake wetlands and provide support for creating small habitats by managing the water levels of paddy fields and aquaculture ponds.This research was funded by the National Natural Science Foundation of China (Grant No. U2040210), the Scientific and Technology Project of the Anhui Provincial Group Limited for Yangtze-to-Huaihe Water Diversion (Grant No. YJJH-ZT-ZX-20180404062)

Risk factors associated with abandonment of care in retinoblastoma: analysis of 692 patients from 10 countries.

BACKGROUND: Rates of care abandonment for retinoblastoma (RB) demonstrate significant geographical variation; however, other variables that place a patient at risk of abandoning care remain unclear. This study aims to identify the risk factors for care abandonment across a multinational set of patients. METHODS: A prospective, observational study of 692 patients from 11 RB centres in 10 countries was conducted from 1 January 2019 to 31 December 2019. Multivariate logistic regression was used to identify risk factors associated with higher rates of care abandonment. RESULTS: Logistic regression showed a higher risk of abandoning care based on country (high-risk countries include Bangladesh (OR=18.1), Pakistan (OR=45.5) and Peru (OR=9.23), p<0.001), female sex (OR=2.39, p=0.013) and advanced clinical stage (OR=4.22, p<0.001). Enucleation as primary treatment was not associated with a higher risk of care abandonment (OR=0.59, p=0.206). CONCLUSION: Country, advanced disease and female sex were all associated with higher rates of abandonment. In this analysis, enucleation as the primary treatment was not associated with abandonment. Further research investigating cultural barriers can enable the building of targeted retention strategies unique to each country

Statistical Methods for Problems in Heterogeneous Populations, from Clinical Trials to Latent-Variable Models

Thesis (Ph.D.)--University of Washington, 2022This dissertation provides methods for analyzing data from heterogeneous populations and addresses the problems of relative efficiency estimation, estimation in Markov-switching vector autoregressive models, and statistical inference in semiparametric finite mixtures. In Chapter 2, we propose a general framework for using external data available at the planning stage of a clinical trial to identify and make statistical inference about the efficiency gain from covariate adjustment to be expected in this future trial. We propose efficient estimators that allow for the incorporation of flexible statistical learning tools and develop statistical inference procedures to accompany the proposed estimators. In Chapter 3, we develop an approximate regularized Expectation-Maximization algorithm for parameter estimation in Markov-switching vector autoregressive models in high-dimensional settings. We rigorously analyze the estimation error of the estimate resulting from the proposed algorithm. In Chapter 4, we study a semiparametric extension of finite mixtures and introduce a framework for statistical inference that is well-suited to mixture model settings. We propose an efficient one-step estimator for estimating a general finite-dimensional summary of a component distribution and corresponding confidence intervals

Spatial Differentiation of Multi-Airport Logistics in Four Urban Agglomerations in China

A Multi-airport Logistics System (MLS) involves the logistics development of multiple airports in an urban agglomeration. Calculating spatial differentiation in MLS and examining its characteristics have theoretical and practical value. Based on MLS, we established an index system and applied the entropy-criteria importance through the intercriteria correlation weighting method to data from 2019 to evaluate the development and spatial differentiation of multi-airport logistics in four Chinese urban agglomerations in three dimensions: logistics resources, service chains, and market demand. The results showed the following: (1) The Guangdong–Hong Kong–Macao Greater Bay Area showed logistics resource-type development. (2) Given its considerable market demand and service support, the Yangtze River Delta ranked first in the service-chain aspect. (3) The market-demand performance of the Chengdu–Chongqing Double Cities Economic Circle was poor. (4) Beijing–Tianjin–Hebei showed mediocre performance in all three aspects. Based on the findings, we make suggestions for MLS development in urban agglomerations for the purpose of achieving high-quality development and supporting China’s overall national transportation network

FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

BACKGROUND: The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. METHODS: A total of 693 laboratory-confirmed FluA-p patients diagnosed between Jan 2013 and Dec 2018 and recruited from five teaching hospitals in China were included in the study. The sample included 494 patients in the derivation cohort and 199 patients in the validation cohort. The prediction rule was established based on independent risk factors for 30-day mortality in FluA-p patients from the derivation cohort. RESULTS: The 30-day mortality of FluA-p patients was 19.6% (136/693). The FluA-p score was based on a multivariate logistic regression model designed to predict mortality. Results indicated the following significant predictors (regression statistics and point contributions toward total score in parentheses): blood urea nitrogen &gt; 7 mmol/L (OR 1.604, 95% CI 1.150–4.492, p = 0.040; 1 points), pO2/FiO2 ≤ 250 mmHg (OR 2.649, 95% CI 1.103–5.142, p = 0.022; 2 points), cardiovascular disease (OR 3.967, 95% CI 1.269–7.322, p &lt; 0.001; 3 points), arterial PH &lt; 7.35 (OR 3.959, 95% CI 1.393–7.332, p &lt; 0.001; 3 points), smoking history (OR 5.176, 95% CI 2.604–11.838, p = 0.001; 4 points), lymphocytes &lt; 0.8 × 109/L (OR 8.391, 95% CI 3.271–16.212, p &lt; 0.001; 5 points), and early neurominidase inhibitor therapy (OR 0.567, 95% CI 0.202–0.833, p = 0.005; − 2 points). Seven points was used as the cut-off value for mortality risk stratification. The model showed a sensitivity of 0.941, a specificity of 0.762, and overall better predictive performance than the PSI risk class (AUROC = 0.908 vs 0.560, p &lt; 0.001) and the CURB-65 score (AUROC = 0.908 vs 0.777, p &lt; 0.001). CONCLUSIONS: Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions

Seismic design of multiple anti-slide piles by strength reduction dynamics analysis method

Landslide thrust is too large and the bearing capacity of a single anti-slide pile is difficult to meet this requirement, multiple anti-slide piles are chosen to solve this problem. However, due to the complexity of multiple anti-slide piles, the related studies of the dynamic response of this structure are few, which is difficult to meet the requirements of the current seismic stability analysis. In this paper a new method of dynamic stability analysis is presented. The strength reduction dynamics analysis method was introduced into the slope dynamic stability analysis. Through the analysis of a practical engineering, this method was demonstrated feasibility. The method provides a new train of thought. © 2015 ejge

TiO2 Nanorod-Derived Synthesis of Upstanding Hexagonal Kassite Nanosheet Arrays: An Intermediate Route to Novel Nanoporous TiO2 Nanosheet Arrays

In this report, upstanding and nanoporous hexagonal TiO2 nanosheet arrays were achieved via using kassite [CaTi2O4(OH)(2)] as an intermediate. The process developed involved a TiO2 nanorod-derived synthesis of upstanding hexagonal kassite nanosheet arrays and a transformation of the kassite to TiO2. To the best of our knowledge, this is the first successful attempt to grow ordered hexagonal kassite nanosheet arrays. The as-obtained kassite nanosheets showed a single-crystalline nature with their c-axis parallel to the substrate. A stepwise study of the growth of the interesting hexagonal kassite nanosheet arrays was demonstrated. Upon hydrothermal treatment with diluted HNO3 aqueous solution, the single-crystalline hexagonal kassite got converted to nanoporous ruble TiO2, with shape preservation. The approach described in this study provides a novel method for the synthesis of kassite and TiO2 nanosheet arrays and are ready for a variety of applications such as in catalytic or optoelectronic fields.</p

Genetic polymorphism and forensic efficiency of 21 autosomal STR loci from Shandong Han population in Northern China

Background Highly polymorphic autosomal STR loci are useful for understanding population structure better and for forensic application, however the non-CODIS STR loci in the Han population of Shandong, located in Northern China, are not well-characterised. Aim To investigate population genetic polymorphism and forensic efficiency of 21 autosomal STR loci from the Shandong Han population in Northern China and reveal the genetic relationships with other populations both at home and abroad. Subjects and methods In this study, population genetic data of 21 autosomal STR loci included in the Goldeneye DNA ID 22NC Kit that includes four CODIS loci and 17 non-CODIS loci were determined for 523 unrelated Han individuals in Shandong. Results Significant deviations from Hardy–Weinberg equilibrium were not observed. A total of 233 alleles were detected with allele frequencies ranging from 0.0010 to 0.3728. The combined power of discrimination was 0.99999999999999999999999990011134, and the combined power of exclusion was 0.99999999788131. Furthermore, in an analysis of population differentiation Nei’s standard genetic distance and multidimensional scaling analysis, which were conducted based on the overlapping 15 STR loci, revealed that the Shandong Han population was most closely related to populations in close geographic proximity. Conclusions This study demonstrated that the 21 autosomal STR loci included in the GoldeneyeTM DNA ID 22NC system are highly polymorphic and suitable for forensic identification and paternity testing in the Shandong Han population. Additionally, the present results enrich the population genetic database