Browsing by Author "Chen, Chen"

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    Electron Temperature Enhancement Effects on Plasma Irregularities Associated with Charged Dust in the Earth's Mesosphere
    Chen, Chen (Virginia Tech, 2007-11-26)
    Recently, experimental observations have shown that Polar Mesospheric Summer Echoes PMSE may be modulated by radio wave heating the irregularity source region with a ground-based ionospheric heating facilities. It is clear from these past investigations that the temporal behavior of PMSE during ionospheric heating shows promise as a diagnostic for the associated dust layer. To investigate the temporal behavior of plasma irregularities thought to produce PMSE, this work describes a new model that incorporates both finite diffusion time effects as well as dust charging. The hybrid model utilizes fluid ions described by continuity and momentum equations, electrons whose behavior is determined from quasi-neutrality, and charged dust described by the standard Particle-In-Cell PIC method. The model has been used to investigate the temporal behavior of charged dust associated electron irregularities during electron temperature enhancement associated with radio wave heating. The model predicts that the temporal behavior of the irregularities depends on the ratio of the electron-ion ambipolar diffusion time to the dust particle charging time Td/Tc. The results indicate that typically for Td/Tc << 1, an enhancement in electron irregularity amplitude occurs for a period after turn-off of the radio wave heating. The work also predicts that for Td/Tc >> 1, an enhancement in electron irregularity amplitude occurs for a time period after the turn-on of the radio wave heating. Due to the dependence of Td on irregularity scale-size, these results have important implications for observations of PMSE modification at different radar frequencies. Both continuous and discrete charging model were embedded into this computational model, the results were compared and analyzed. It is evident that significant diagnostic information may be available about the dust layer from the temporal behavior of the electron irregularities during the heating process which modifies the background electron temperature. Particularly interesting and important periods of the temporal behavior are during the turn-on and turn-off of the radio wave heating. Although a number of past theoretical and experimental investigations have considered both these on and off period, this dissertation considers further possibilities for diagnostic information available as well as the underlying physical processes. Approximate analytical models are developed and compared to a more accurate full computational model as a reference. Then from the temporal behavior of the electron irregularities during the turn-on and turn-off of the radio wave heating, the analytical models are used to obtain possible diagnostic information for various charged dust and background plasma quantities. Finally, two experiment campaigns have been performed at HAARP, Gakona, Alaska. Preliminary observation results look promising for the existence of PMSE turn-on overshoot. However, more careful experiments need to be done before firm conclusions can be drawn. The new designed Echotek digital receiver is ready for use now. It will be much superior to the experimental setup used for measurements in the previous campaign.Therefore, future experimental campaigns are planning next year to support the theoretical research.
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    Evaluating the Influence of Crashes on Driving Behavior using Naturalistic Driving Study Data
    Guo, Feng; Chen, Chen (National Surface Transportation Safety Center for Excellence, 2015-07-16)
    It is hypothesized that intense events such as crashes could influence driver behavior and driving risk. This study evaluated the influences of crash events on driver behavior and driving risk using data from the 100-Car Naturalistic Driving Study, which included 51 crashes from primary drivers. Two metrics were used to measure driver behavior and risk: the proportion of baselines where the drivers were engaged in complex and moderate secondary tasks and the intensity of the near-crashes (NCs) and safety-critical incidents (SCIs). For the distraction analysis, we sampled 882 6-second baseline epochs within 15-hour windows before and after crashes. Results from a mixed binomial regression model indicated that the percentage of baselines where drivers engaged in complex secondary tasks dropped after crashes (odds ratio = 0.54; 95% CI [0.32, 0.93]). The driving risk analysis used the intensity of SCIs and NCs to measure the driving risk. Since there are typically more than one SCI and NC events before and after a crash, we developed four alternative recurrent event models to evaluate the influence of crashes based on actual driving time. The driving period was divided into several phases based on the relationship to crashes, and the intensities of these periods were compared. Results show a reduction in SCI intensity after the first crash (intensity rate ratio = 0.82; 95% CI [0.693, 0.971]) and the second crash (intensity rate ratio = 0.47; 95% CI [0.377, 0.59]) for male drivers. Females were observed to have a nonsignificant response to the first crash, but SCI intensity decreased after the second crash (intensity rate ratio = 0.43; 95% CI [0.342, 0.547]). This study indicated that crashes do have a positive effect on drivers’ behavior in terms of distraction and driving risk.
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    Evaluating Time-varying Effect in Single-type and Multi-type Semi-parametric Recurrent Event Models
    Chen, Chen (Virginia Tech, 2015-12-11)
    This dissertation aims to develop statistical methodologies for estimating the effects of time-fixed and time-varying factors in recurrent events modeling context. The research is motivated by the traffic safety research question of evaluating the influence of crash on driving risk and driver behavior. The methodologies developed, however, are general and can be applied to other fields. Four alternative approaches based on various data settings are elaborated and applied to 100-Car Naturalistic Driving Study in the following Chapters. Chapter 1 provides a general introduction and background of each method, with a sketch of 100-Car Naturalistic Driving Study. In Chapter 2, I assessed the impact of crash on driving behavior by comparing the frequency of distraction events in per-defined windows. A count-based approach based on mixed-effect binomial regression models was used. In Chapter 3, I introduced intensity-based recurrent event models by treating number of Safety Critical Incidents and Near Crash over time as a counting process. Recurrent event models fit the natural generation scheme of the data in this study. Four semi-parametric models are explored: Andersen-Gill model, Andersen-Gill model with stratified baseline functions, frailty model, and frailty model with stratified baseline functions. I derived model estimation procedure and and conducted model comparison via simulation and application. The recurrent event models in Chapter 3 are all based on proportional assumption, where effects are constant. However, the change of effects over time is often of primary interest. In Chapter 4, I developed time-varying coefficient model using penalized B-spline function to approximate varying coefficients. Shared frailty terms was used to incorporate correlation within subjects. Inference and statistical test are also provided. Frailty representation was proposed to link time-varying coefficient model with regular frailty model. In Chapter 5, I further extended framework to accommodate multi-type recurrent events with time-varying coefficient. Two types of recurrent-event models were developed. These models incorporate correlation among intensity functions from different type of events by correlated frailty terms. Chapter 6 gives a general review on the contributions of this dissertation and discussion of future research directions.
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    Genome sequences of wild and domestic bactrian camels
    Jirimutu; Wang, Zhen; Ding, Guohui; Chen, Gangliang; Sun, Yamin; Sun, Zhihong; Zhang, Heping; Wang, Lei; Hasi, Surong; Zhang, Yan; Li, Jianmei; Shi, Yixiang; Xu, Ze; He, Chuan; Yu, Siriguleng; Li, Shengdi; Zhang, Wenbin; Batmunkh, Mijiddorj; Ts, Batsukh; Narenbatu; Unierhu; Bat-Ireedui, Shirzana; Gao, Hongwei; Baysgalan, Banzragch; Li, Qing; Jia, Zhiling; Turigenbayila; Subudenggerile; Narenmanduhu; Wang, Zhaoxia; Wang, Juan; Pan, Lei; Chen, Yongcan; Ganerdene, Yaichil; Dabxilt; Erdemt; Altansha; Altansukh; Liu, Tuya; Cao, Minhui; Aruuntsever; Bayart; Hosblig; He, Fei; Zha-ti, A.; Zheng, Guangyong; Qiu, Feng; Sun, Zikui; Zhao, Lele; Zhao, Wenjing; Liu, Baohong; Li, Chao; Chen, Yunqin; Tang, Xiaoyan; Guo, Chunyan; Liu, Wei; Ming, Liang; Temuulen; Cui, Aiying; Li, Yi; Gao, Junhui; Li, Jing; Wurentaodi; Niu, Shen; Sun, Tao; Zhai, Zhengxiao; Zhang, Min; Chen, Chen; Baldan, Tunteg; Bayaer, Tuman; Li, Yixue; Meng, He (Springer Nature, 2012-11)
    Bactrian camels serve as an important means of transportation in the cold desert regions of China and Mongolia. Here we present a 2.01 Gb draft genome sequence from both a wild and a domestic bactrian camel. We estimate the camel genome to be 2.38 Gb, containing 20,821 protein-coding genes. Our phylogenomics analysis reveals that camels shared common ancestors with other even-toed ungulates about 55-60 million years ago. Rapidly evolving genes in the camel lineage are significantly enriched in metabolic pathways, and these changes may underlie the insulin resistance typically observed in these animals. We estimate the genome-wide heterozygosity rates in both wild and domestic camels to be 1.0 x 10(-3). However, genomic regions with significantly lower heterozygosity are found in the domestic camel, and olfactory receptors are enriched in these regions. Our comparative genomics analyses may also shed light on the genetic basis of the camel's remarkable salt tolerance and unusual immune system.
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    HPLC-DAD Fingerprints Combined With Multivariate Analysis of Epimedii Folium From Major Producing Areas in Eastern Asia: Effect of Geographical Origin and Species
    Li, Ben; Lima, Marta R. M.; Nie, Yuhao; Xu, Long; Liu, Xiang; Yuan, Hongchao; Chen, Chen; Dias, Alberto C. P.; Zhang, Xiaoying (Frontiers, 2021-11-26)
    The growth location and plant variety may influence the active components and biological activities of plants used in phytomedicine. In this study, nine sets of different Epimedii Folium, from different representative cultivation locations and Epimedium species, were collected for comparison, using HPLC-DAD combined with multivariate analysis. The objective was to investigate the influence of geographical origin and Epimedium species on the quality of Epimedii Folium, and provide applicable guidance for cultivation and quality control of Epimedii Folium. Several Epimedium spp. sets were used to establish the HPLC-DAD fingerprints and 91 peaks (compounds) were selected for the multivariate analysis. Major compounds were analyzed by HPLC-DAD combined with principal component analysis (PCA). HPLC quantitative analysis of known bioactive compounds was performed. Application of PCA to HPLC data showed that Epimedium samples sharing the same geographical origin or species clustered together, indicating that both species and geographical origin have impacts on the quality of Epimedii Folium. The major bioactive flavonoid compounds, epimedin C, icariin and baohuoside I, were identified and quantified. The concentration of bioactive compounds was significantly influenced both by species and geographical origin. E. sagittatum from Sichuan showed the highest content of bioactive compounds. The results showed that both Epimedium species and geographical origin have strong impact into quality of Epimedii Folium. HPLC data combined with multivariate analysis is a suitable approach to inform the selection of cultivation areas and choose Epimedium spp. most suitable for different geographical areas, resulting in improved quality of Epimedii Folium.
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    The Manufacture of Polymer Nanocomposite Materials Using Supercritical Carbon Dioxide
    Chen, Chen (Virginia Tech, 2011-11-30)
    The use of supercritical carbon dioxide (scCO₂) as a processing aid to help exfoliate nano-clays and improve their dispersion during melt blending in polymer matrices has been reported in the literature. One of the best processes in terms of improving the degree of nano-clay dispersion and composite mechanical properties was developed in our laboratory. This process allows the clay to be in direct contact with scCO₂ and expanding the clay-CO₂ mixture via rapid depressurization into a two-stage screw extruder to mix with the polymer pellets. However, composites with clay loading higher than 6.6 wt % were not reported. In addition, the scCO₂ aided processing method has not been applied to carbon nanotube (CNT) based composites. This dissertation initially focused on applying the scCO₂ aided processing technique to the field of CNT expansion and CNT/polymer composite preparation. The relationship with the expanded CNT morphology and the experimental conditions of the expansion procedure (including pressures, temperatures, exposure time, and depressurization rates) was studied. Microscopy results showed improved CNT dispersion in the polymer matrix and more uniform networks formed with the use of scCO₂, which indicated that CO₂ expanded CNTs are easier to disperse into the polymer matrix during the blending procedure. The CNT/ poly(phenylsulfone) (PPSF) composites prepared with scCO₂ aided method provided continuous improvements in Young's modulus up to the addition of 7 wt % CNTs. However, the Young's modulus of the composite prepared by means of conventional direct melt blending failed to increase beyond the addition of 1 wt % CNT. The second part of this work is concerned with the development of a semi-continuous process using scCO₂ to process polymer-clay composites with clay loading higher than 6.6 wt % (i.e. 10 wt %). Two major modifications are involved in the new procedure: exfoliating the nano-clay directly into the hopper filled with pellets followed by processing the composite immediately and sequentially mixing the clay into the melt. Transmission electron microscopy (TEM) and wide angle X-ray diffraction (WAXD) results show that this modified procedure help to reduce the clay collapse when processing the composites with high clay loadings. Surface modified montmorillonite (MMT) nano-clay/polypropylene (PP) composite at 10 wt % nano-clay with improved clay dispersion was obtained with increased modulus and tensile strength of 63 % and 16%, respectively, compared to the pure PP matrix. Additional mechanical property improvements for nano-clay based composites are then obtained with the use of high crystallinity polypropylene (HCPP) and polypropylene grafted with maleic anhydride (PP-g-MA). HCPP has higher crystallinity and stiffness than conventional PP and, therefore, composites made from HCPP have better mechanical properties to start with. PP-g-MA has polar groups grafted on the PP chains that promote the intercalation of PP with clay. By using the newly developed procedure, the HCPP nanocomposite at 10 wt % of nano-clay has a Young's modulus as high as 3.236 GPa, and the modulus of the 10% MMT/PP-g-MA sample is found to be 2.595 GPa, both higher than that of the composite prepared by the direct blending method and that of a composite based on a conventional PP matrix.
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    Representing Diversity in Digital Research: Digital Feminist Ethics and Resisting Dominant Normatives
    Baniya, Sweta; Hutchinson, Les; Kumari, Ashanka; Larson, Kyle; Lindgren, Chris A. (The WAC Clearinghouse, 2019)
    In this paper, the authors consider how their engaged practices of feminist ethics have come up against specific dominant normatives. Privileging the experiences of women of color, they question the embodied relationship they have with their research participants, and offer their methodological approaches for addressing ethical challenges that have surfaced through conducting their research in both digital and non-digital spaces and places. Collectively, they collaborate to develop newfound strategies and methodologies for negotiating the often mundane, micro-level moments of friction that prevents intersectional phronesis. Overall, they pitch ethical research practices for digital and non-digital research with diverse subjects of different races, backgrounds, and cultures such that voice(s) are not compromised during research.
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    Soft Computing-based Life-Cycle Cost Analysis Tools for Transportation Infrastructure Management
    Chen, Chen (Virginia Tech, 2007-06-07)
    Increasing demands, shrinking financial and human resources, and increased infrastructure deterioration have made the task of maintaining the infrastructure systems more challenging than ever before. Life-cycle cost analysis (LCCA) is an important tool for transportation infrastructure management, which is used extensively to support project level decisions, and is increasingly being applied to enhance network level analysis. However, traditional LCCA tools cannot practically and effectively utilize expert knowledge and handle ambiguous uncertainties. The main objective of this dissertation was to develop enhanced LCCA models using soft computing (mainly fuzzy logic) techniques. The proposed models use available "real-world" information to forecast life-cycle costs of competing maintenance and rehabilitation strategies and support infrastructure management decisions. A critical review of available soft computing techniques and their applications in infrastructure management suggested that these techniques provide appealing alternatives for supporting many of the infrastructure management functions. In particular, LCCA often utilizes information that is uncertain, ambiguous and incomplete, which is obtained from both existing databases and expert opinion. Consequently, fuzzy logic techniques were selected to enhance life-cycle cost analysis of transportation infrastructure investments because they provide a formal approach for the effective treatment of these types of information. The dissertation first proposes a fuzzy-logic-based decision-support model, whose inference rules can be customized according to agency's management policies and expert opinion. The feasibility and practicality of the proposed model is illustrated by its implementation in a life-cycle cost analysis algorithm for comparing and selecting pavement maintenance, rehabilitation and reconstruction (MR&R) policies. To enhance the traditional probabilistic LCCA model, the fuzzy-logic-based model is then incorporated into the risk analysis process. A fuzzy logic approach for determining the timing of pavement MR&R treatments in a probabilistic LCCA model for selecting pavement MR&R strategies is proposed. The proposed approach uses performance curves and fuzzy-logic triggering models to determine the most effective timing of pavement MR&R activities. The application of the approach in a case study demonstrates that the fuzzy-logic-based risk analysis model for LCCA can effectively produce results that are at least comparable to those of the benchmark methods while effectively considering some of the ambiguous uncertainty inherent to the process. Finally, the research establishes a systematic method to calibrate the fuzzy-logic based rehabilitation decision model using real cases extracted from the Long Term Pavement Performance (LTPP) database. By reinterpreting the model in the form of a neuro-fuzzy system, the calibration algorithm takes advantage of the learning capabilities of artificial neural networks for tuning the fuzzy membership functions and rules. The practicality of the method is demonstrated by successfully tuning the treatment selection model to distinguish between rehabilitation (light overlay) and do-nothing cases.
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    Stuck in Time: Negative Income Shock Constricts the Temporal Window of Valuation Spanning the Future and the Past
    Bickel, Warren K.; Wilson, A. George; Chen, Chen; Koffarnus, Mikhail N.; Franck, Christopher T. (PLOS, 2016-09-15)
    Insufficient resources are associated with negative consequences including decreased valuation of future reinforcers. To determine if these effects result from scarcity, we examined the consequences of acute, abrupt changes in resource availability on delay discounting—the subjective devaluation of rewards as delay to receipt increases. In the current study, 599 individuals recruited from Amazon Mechanical Turk read a narrative of a sudden change (positive, neutral, or negative) to one’s hypothetical future income and completed a delay discounting task examining future and past monetary gains and losses. The effects of the explicit zero procedure, a framing manipulation, was also examined. Negative income shock significantly increased discounting rates for gains and loses occurring both in the future and the past. Positive income windfalls significantly decreased discounting to a lesser extent. The framing procedure significantly reduced discounting under all conditions. Negative income shocks may result in short-term choices.