Browsing by Author "Wang, Yan"

Now showing 1 - 11 of 11
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    Aggregated responses of human mobility to severe winter storms: An empirical study
    Wang, Yan; Wang, Qi; Taylor, John E. (PLOS, 2017-12-07)
    Increasing frequency of extreme winter storms has resulted in costly damages and a disruptive impact on the northeastern United States. It is important to understand human mobility patterns during such storms for disaster preparation and relief operations. We investigated the effects of severe winter storms on human mobility during a 2015 blizzard using 2.69 million Twitter geolocations. We found that displacements of different trip distances and radii of gyration of individuals' mobility were perturbed significantly. We further explored the characteristics of perturbed mobility during the storm, and demonstrated that individuals' recurrent mobility does not have a higher degree of similarity with their perturbed mobility, when comparing with its similarity to non-perturbed mobility. These empirical findings on human mobility impacted by severe winter storms have potential long-term implications on emergency response planning and the development of strategies to improve resilience in severe winter storms.
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    Effect of Monochromatic Light on Expression of Estrogen Receptor (ER) and Progesterone Receptor (PR) in Ovarian Follicles of Chicken
    Liu, Lingbin; Li, Diyan; Gilbert, Elizabeth R.; Xiao, Qihai; Zhao, Xiaoling; Wang, Yan; Yin, Huadong; Zhu, Qing (PLOS, 2015-12-01)
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    A Hybrid Experimental and Theoretical Approach to Optimize Recovery of Rare Earth Elements from Acid Mine Drainage Precipitates by Oxalic Acid Precipitation
    Wang, Yan; Ziemkiewicz, Paul; Noble, Aaron (MDPI, 2022-02-12)
    The development of processing techniques for the extraction of rare earth elements and critical minerals (REE/CM) from acid mine drainage precipitates (AMDp) has attracted increased interest in recent years. Processes under development often utilize a standard hydrometallurgical approach that includes leaching and solvent extraction followed by oxalic acid precipitation and calcination to produce a final rare earth oxide product. Impurities such as Ca, Al, Mn, Fe and Mg can be detrimental in the oxalate precipitation step and a survey of the literature showed limited data pertaining to the REE precipitation efficiency in solutions with high impurity concentrations. As such, a systematic laboratory-scale precipitation study was performed on a strip solution generated by the acid leaching and solvent extraction of an AMDp feedstock to identify the optimal processing conditions that maximize REE precipitation efficiency and product purity while minimizing the oxalic acid dosage. Given the unique chemical characteristics of AMDp, the feed solution utilized in this study contained a moderate concentration of REEs (440 mg/L) as well a significant concentration (>7000 mg/L total) of non-REE contaminants such as Ca, Al, Mn, Fe and Mg. Initially, a theoretical basis for the required oxalic acid dose, optimal pH and predicted precipitation efficiency was established by solution equilibrium calculations. Following the solution chemistry calculations, bench-scale precipitation experiments were conducted and these test results indicate that a pH of 1.5 to 2, a reaction time of more than 2 h and an oxalic acid dosage of 30 to 40 g/L optimized the REEs recovery of at ~95% to nearly 100% for individual REE species. The test results validated the optimal pH predicted by the solution chemistry calculations (1.5 to 5); however, the predicted dosage needed for complete REE recovery (10 g/L) was significantly lower than the experimentally-determined dosage of 30 to 40 g/L. The reason for this discrepancy was determined to be due to the large concentration of impurities and large number of potential metal complexes that cause inaccuracies in the solution equilibrium calculations. Based on these findings, a hybrid experimental and theoretical approach is proposed for future oxalic acid precipitation optimization studies.
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    Lateral Motion Prediction of On-Road Preceding Vehicles: A Data-Driven Approach
    Wang, Chen; Delport, Jacques; Wang, Yan (MDPI, 2019-05-07)
    Drivers’ behaviors and decision making on the road directly affect the safety of themselves, other drivers, and pedestrians. However, as distinct entities, people cannot predict the motions of surrounding vehicles and they have difficulty in performing safe reactionary driving maneuvers in a short time period. To overcome the limitations of making an immediate prediction, in this work, we propose a two-stage data-driven approach: classifying driving patterns of on-road surrounding vehicles using the Gaussian mixture models (GMM); and predicting vehicles’ short-term lateral motions (i.e., left/right turn and left/right lane change) based on real-world vehicle mobility data, provided by the U.S. Department of Transportation, with different ensemble decision trees. We considered several important kinetic features and higher order kinematic variables. The research results of our proposed approach demonstrate the effectiveness of pattern classification and on-road lateral motion prediction. This methodology framework has the potential to be incorporated into current data-driven collision warning systems, to enable more practical on-road preprocessing in intelligent vehicles, and to be applied in autopilot-driving scenarios.
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    MUSTN1 mRNA Abundance and Protein Localization is Greatest in Muscle Tissues of Chinese Meat-Quality Chickens
    Li, Juan; Chen, Yang; Wang, Ya-Gang; Zhao, Xiaoling; Gilbert, Elizabeth R.; Liu, Yi-Ping; Wang, Yan; Hu, Yao-Dong; Zhu, Qing (MDPI, 2013-03-08)
    The Mustang, Musculoskeletal Temporally Activated Novel-1 Gene (MUSTN1) plays an important role in regulating musculoskeletal development in mammals. We evaluated the developmental and tissue-specific regulation of MUSTN1 mRNA and protein abundance in Erlang Mountainous (EM) chickens. Results indicated that MUSTN1 mRNA/protein was expressed in most tissues with especially high expression in heart and skeletal muscle. The MUSTN1 protein localized to the nucleus in myocardium and skeletal muscle fibers. There were significant differences in mRNA and protein abundance among tissues, ages and between males and females. In conclusion, MUSTN1 was expressed the greatest in skeletal muscle where it localized to the nucleus. Thus, in chickens MUSTN1 may play a vital role in muscle development.
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    Nested Bayesian Optimization for Computer Experiments
    Wang, Yan; Wang, Meng; AlBahar, Areej; Yue, Xiaowei (IEEE, 2022-09)
    Computer experiments can emulate the physical systems, help computational investigations, and yield analytic solutions. They have been widely employed with many engineering applications (e.g., aerospace, automotive, energy systems). Conventional Bayesian optimization did not incorporate the nested structures in computer experiments. This article proposes a novel nested Bayesian optimization method for complex computer experiments with multistep or hierarchical characteristics. We prove the theoretical properties of nested outputs given that the distribution of nested outputs is Gaussian or non-Gaussian. The closed forms of nested expected improvement are derived. We also propose the computational algorithms for nested Bayesian optimization. Three numerical studies show that the proposed nested Bayesian optimization method outperforms the five benchmark Bayesian optimization methods that ignore the intermediate outputs of the inner computer code. The case study shows that the nested Bayesian optimization can efficiently minimize the residual stress during composite structures assembly and avoid convergence to local optima.
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    Polymorphisms in the Chicken Growth Differentiation Factor 9 Gene Associated with Reproductive Traits
    Liu, Lingbin; Cui, Zhifu; Xiao, Qihai; Zhang, Haihan; Zhao, Xiaoling; Wang, Yan; Yin, Huadong; Li, Diyan; Zhu, Qing (Hindawi, 2018-09-19)
    The aim of the study was to investigate GDF9 gene polymorphisms and their association with reproductive traits in chicken using DNA sequencing. A total of 279 Dongxiang blue-shelled (DX) chickens and 232 Luhua (LH) chickens were used for validation. We detected 15 single nucleotide polymorphisms (SNPs): nine SNPs were previously unreported in chicken, two were missense mutations, and only three exhibited significant associations with reproductive traits. G.17156387C>T was significantly associated with age at first egg (AFE) and weight of first egg (WFE) in both breeds. Birds carrying the CC genotype exhibited higher AFE and WFE values than those with the TT genotype. The SNP g.17156427A>G exhibited an association with egg weight at 300 days of age (EWTA) in DX but not in LH chickens. The SNP g.17156703A>C affected the AFE and EN (total number of eggs at 300 days of age) in DX chickens. In addition, certain diplotypes significantly affected AFE, BWTA (body weight at 300 days of age), and EN in both breeds. RT-PCR results showed that the GDF9 gene was highly expressed in stroma with cortical follicles (STR) and prehierarchal follicles. These results provided further evidence that the GDF9 gene is involved in determining reproductive traits in chicken.
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    Polymorphisms in the Perilipin Gene May Affect Carcass Traits of Chinese Meat-type Chickens
    Zhang, Lu; Zhu, Qing; Liu, Yi-Ping; Gilbert, Elizabeth R.; Li, Diyan; Yin, Huadong; Wang, Yan; Yang, Zhiqin; Wang, Zhen; Yuan, Yuncong; Zhao, Xiaoling (Asian-Australasian Assoc Animal Production Soc, 2015-06-01)
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    Tracking Disaster Dynamics for Urban Resilience: Human-Mobility and Semantic Perspectives
    Wang, Yan (Virginia Tech, 2018-06-11)
    Fostering urban resilience and creating agility to disaster response is an urgent task faced by cities worldwide in the context of climate change and increasing frequencies of natural disasters. Understanding and tracking the dynamic process of resilience to disasters is the first step to operationalize the concept of urban resilience. In this dissertation, I present four related but evolutionary perspectives to investigate the impact of natural disasters on interactive human-environment systems as well as the dynamic process of resilience, including human mobility, spatial networks, and coupled mobility and sentiment perspectives. In the first, human-mobility perspective, I examine the nuanced impact of a severe winter storm on human mobility patterns and the relationship between perturbed mobility during the storm and recurrent mobility under normal circumstances. In the second, where I adopt a spatial network perspective, I investigate the dynamic process of resilience over time by analyzing networked human-spatial systems using an ecology-inspired approach. The third perspective involves sentiment as an additional factor to human mobility to understand urban dynamics during an earthquake. In this perspective, I explore the relation between disaster magnitude and a population's collective sentiment, as well as temporal correlations between sentiment and mobility. Each of the three empirical studies employs a quantitative, empirical research methodology and uses voluntarily reported geo-referenced data collected through a Twitter Streaming API. After multiple investigations on diverse types of natural disaster (e.g. severe winter storm, flooding, hurricane, and earthquake), I develop a Detecting Urban Emergencies Technique (DUET), as the fourth part of my dissertation, for identifying and tracking general types of emergencies in a short period without prior definitions of emergent topics. Research findings from the three empirical studies and the proposed DUET detection technique introduce a new lens and approach for understanding population dynamics and achieving urban resilience. This dissertation contributes to a more complete understanding of urban resilience to disasters with crowdsourced data, and enables more effective urban informatics in the face of extreme events.
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    Transcriptome Response of Liver and Muscle in Heat-Stressed Laying Hens
    Wang, Yan; Jia, Xinzheng; Hsieh, John C. F.; Monson, Melissa S.; Zhang, Jibin; Shu, Dingming; Nie, Qinghua; Persia, Michael E.; Rothschild, Max F.; Lamont, Susan J. (MDPI, 2021-02-10)
    Exposure to high ambient temperature has detrimental effects on poultry welfare and production. Although changes in gene expression due to heat exposure have been well described for broiler chickens, knowledge of the effects of heat on laying hens is still relatively limited. In this study, we profiled the transcriptome for pectoralis major muscle (n = 24) and liver (n = 24), during a 4-week cyclic heating experiment performed on layers in the early phase of egg production. Both heat-control and time-based contrasts were analyzed to determine differentially expressed genes (DEGs). Heat exposure induced different changes in gene expression for the two tissues, and we also observed changes in gene expression over time in the control animals suggesting that metabolic changes occurred during the transition from onset of lay to peak egg production. A total of 73 DEGs in liver were shared between the 3 h heat-control contrast, and the 4-week versus 3 h time contrast in the control group, suggesting a core set of genes that is responsible for maintenance of metabolic homeostasis regardless of the physiologic stressor (heat or commencing egg production). The identified DEGs improve our understanding of the layer’s response to stressors and may serve as targets for genetic selection in the future to improve resilience.
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    Whole-transcriptome analysis of atrophic ovaries in broody chickens reveals regulatory pathways associated with proliferation and apoptosis
    Liu, Lingbin; Xiao, Qihai; Gilbert, Elizabeth R.; Cui, Zhifu; Zhao, Xiaoling; Wang, Yan; Yin, Huadong; Li, Diyan; Zhang, Haihan; Zhu, Qing (Springer Nature, 2018-05-08)
    Broodiness in laying hens results in atrophy of the ovary and consequently decreases productivity. However, the regulatory mechanisms that drive ovary development remain elusive. Thus, we collected atrophic ovaries (AO) from 380-day-old broody chickens (BC) and normal ovaries (NO) from evenaged egg-laying hens (EH) for RNA sequencing. We identified 3,480 protein-coding transcripts that were differentially expressed (DE), including 1,719 that were down-regulated and 1,761 that were up-regulated in AO. There were 959 lncRNA transcripts that were DE, including 56 that were downregulated and 903 that were up-regulated. Among the116 miRNAs that were DE, 79 were downregulated and 37 were up-regulated in AO. Numerous DE protein-coding transcripts and target genes for miRNAs/lncRNAs were significantly enriched in reproductive processes, cell proliferation, and apoptosis pathways. A miRNA-intersection gene-pathway network was constructed by considering target relationships and correlation of the expression levels between ovary development-related genes and miRNAs. We also constructed a competing endogenous RNA (ceRNA) network by integrating competing relationships between protein-coding genes and lncRNA transcripts, and identified several lncRNA transcripts predicted to regulate the CASP6, CYP1B1, GADD45, MMP2, and SMAS2 genes. In conclusion, we discovered protein-coding genes, miRNAs, and lncRNA transcripts that are candidate regulators of ovary development in broody chickens.