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Elevated plasma levels of homocysteine have been implicated in neurodevelopmental and neurodegenerative disorders in human studies. Although the molecular mechanisms underlying the effects of homocysteine (Hcy) cytotoxicity on the nervous system are not yet fully unknown, induction of DNA interstrand cross-links and inhibition of neural stem cells (NSCs) survival may be involved. The objective of our study was to investigate the effects of Hcy on DNA interstrand cross-links in NSCs, and to explore its possible mechanisms. We also found that Hcy induced cell DNA damage on a dose-dependent manner and evoked reactive oxidative species (ROS) production, leading to elevated apoptosis in NSCs. Moreover, Hcy exposure activated the Fanconi anemia (FA) pathway, which was characterized by increases in monoubiquitination of Fanci and Fancd2 and enhancement of the interaction between above two proteins. On contrary, N-Acety-l-Cysteine (NAC) decreased Hcy-evoked ROS production and significantly ameliorated DNA damage and improved cell survival. These data suggest that Hcy may play a role in the pathogenesis of neurological diseases via a molecular mechanism that induces DNA interstrand cross-links via oxidative stress and involves in negative regulation of NSCs survival.

To investigate the protective effects and potential mechanisms of tea polyphenols intervention on excess alcohol intake induced liver injury in rats. This study established the animal model of chronic liver injury rats induced by alcohol. Our results will provide experimental evidence for the effects of tea polyphenol on chronic alcoholic liver injury.Alcohol-induced liver injury rat models were established, and the tea polyphenols intervention was performed in the meantime. After 8 weeks, rats were anesthetized, and visceral fat and liver samples were separated, weighted and stored. Visceral fat content was evaluated in fat/body weight ratio. Liver lipid accumulation was assessed by liver index and the result of Oil Red O staining. Hepatic superoxide dismutase (SOD) activity, malondialdehyde (MDA) content, total antioxidant capacity assay (T-AOC) and glutathione peroxidase (GSH-Px) activity were detected. And fatty acid translocase (FAT/CD36) protein level in liver was detected.Compared with the control group rats, the fat/body weight ratio, SOD/MDA, T-AOC and GSH-Px activity of chronic liver injury rats were decreased significantly (Tea polyphenols intervention can improve lipid deposition and oxidative stress in chronic alcoholic liver, which is concurrent with decreased FAT/CD36 protein expression on the hepatocyte membrane.

Research on guanxi, and in particular its influence on workplace outcomes, has greatly increased in the past 2 decades. Despite this proliferation, scholars have paid little attention to conceptual development of the construct. My review of the existing literature on guanxi highlighted the great variety of ways that guanxi has been conceptualized and operationalized, and the fact that existing theoretical models of guanxi operation remain largely untested. To address the lack of specificity in defining the construct of guanxi, I conducted 5 interrelated studies to define and test the construct. I focused on external guanxi between boundary spanners--people from different organizations who interact on behalf of their organizations for work purposes--in the context of the Taiwan workplace. The project entails two parts. In the initial qualitative part, I adopted an indigenous psychology perspective to delineate the contents, processes, and defining characteristics of guanxi. The results were useful in assessing the adequacy of existing theoretical conceptualizations for addressing actual workplace guanxi dynamics (Study 1, Part 1). They also supported the theoretical postulations, which I categorized as cultural-based workplace guanxi. A second objective of the qualitative study was to identify the best way to operationalize workplace guanxi, and to generate a set of items to measure it. My analysis indicated that a measure of guanxi should capture its dynamic and changeable quality and highlighted 3 dimensions of guanxi quality, namely, ganqing, renqing, and xinren (Study 1, Part 2). Based on these results, I generated items to represent each dimension. The second part of the research focused on scale development. I used the items generated in the initial qualitative study to propose a measure of guanxi quality, the Guanxi Quality Scale (GQS), which I refined and tested in subsequent studies: pretesting the initial pool of scale items (Studies 2A and 2B), testing the factor structure (Studies 3 and 4), and assessing the construct validity of the new measure (Studies 4 and 5). Results of the factor analyses conducted in Studies 3 and 4 supported a higher-order factor structure of guanxi quality that was measured by the 3 latent factors of ganqing, renqing, and xinren. The final 15-item GQS showed high reliability and validity and can be used to measure workplace guanxi in future research. The 5 studies of this project represent a concerted effort to provide a comprehensive understanding of guanxi. The results of this study provide a common starting point and language for researchers who are investigating guanxi. By maintaining an emphasis on obtaining an insider perspective, this research also provides outsiders with valuable insights on the cultural emphasis on relationships in the context of the Taiwan workplace. DOCTOR OF PHILOSOPHY (HSS)

The current research probed into the effects of green tea polyphenols (GTPs) on ethanol-induced spatial learning and memory impairments and inquired the potential molecular mechanism in rats. Thirty 8-week-old male Sprague-Dawley rats were randomly divided into three groups. The control group (control, n=10), ethanol group (ethanol, n=10), and GTPs intervention group (GTP, n=10) received gavage administration of saline, ethanol, and ethanol-GTP solution, respectively, for 8 weeks. Morris water maze was applied to assess the spatial learning and memory function of rats in each group at the last week of treatment. There was no dramatic change in body weight of rats in the different groups. Compared with rats in the control group, 8-week ethanol gavaged rats showed increased escape latency period and decreased time in the target quadrant. Moreover, 8-week ethanol gavage decreased the density of pyramidal layer neurons, expression of NMDAR1, and CREB phosphorylation in the hippocampus region. In contrast, GTP intervention decreased escape latency period and increased the time in the target quadrant, the density of pyramidal layer neurons, expression of NMDAR1, and CREB phosphorylation in the hippocampus region. The current findings indicated that GTP intervention can improve ethanol-induced spatial learning and memory impairments in rats after ethanol withdrawal, which is related to the upregulated density of pyramidal layer neurons, expression of NMDAR1, and CREB phosphorylation in the hippocampus region.

Near-field electrospinning (NFES) is a site addressable microfabrication process and is utilized to deposit the micro/nano polyvinylidene fluoride (PVDF) fibers arrays on printed circuit board nanofiber-based based piezoelectric sensor architectures. In addition, a biomimetic and flexible hybrid self-powered sensors (BHSS) was created by hybridizing both Cu - biomimetic Polydimethylsiloxane triboelectric sensors to enhance the energy-harvesting characteristic. The optimized BHSS had open-circuit voltage (VOC) of 15 V and 115 nA of short-circuit current (ISC) and a maximum average power density is 675 μW m−2 with a load of 10 MΩ. Furthermore, an intelligent glove and the force sensor with are successively confirmed that the developed BHSS has promising applications in wearable self-power sensor technology. The machine learning algorithm of Long Short-Term Memory (LSTM) in the context of gesture recognition was used and effectively distinguish five human actions satisfactorily. LSTM based real-time electrical signals of five gestures dataset with varying duration and complexity can achieve an overall classification rate of 82.3%.

Endogenous phytohormones gibberellins (GAs) and brassinosteroids (BRs) are associated with the development and growth of higher plants, but the crosstalk between them in leaves of tea plant is unclear. We determined whether or not a crosstalk exists between GAs and BRs at three developmental stages of tea leaves. We performed phytohormone measurement, phenotypic analysis, cytological–anatomical structural analysis, RT-qPCR analysis, and protein–protein interaction (PPI) prediction to obtain physiological, biochemical, and bioinformatic evidences. Leaf area, spongy tissue cell expansion, and GAs- and BRs-related gene expressions were regulated by the crosstalk between GAs and BRs. GAs levels positively correlated with BRs levels at three developmental stages of tea leaves. GAs levels positively correlated with the expression levels of CsCPD (Cytochrome P450 90A1) and CsDWF4 (Dwarf4), which are involved in BRs biosynthesis pathway at three developmental stages of tea leaves. The expression of CsGA20ox1 (Gibberellin 20 oxidase 1), a gene involved in the GAs biosynthesis pathway, positively correlated with GAs and BRs levels at three developmental stages of tea leaves. These results suggested that CsGA20ox1, CsCPD, and CsDWF4 might play regulative roles in the crosstalk between GAs and BRs at the developmental stages of tea leaves. Our findings provided a new and feasible strategy to understand the crosstalk between the GAs and BRs metabolism pathways.

Exercise is an effective therapy for insulin resistance. However, the underlying mechanism remains to be elucidated. Previous research demonstrated that TGFβ-activated kinase 1 (TAK1)-dependent signaling plays a crucial character in hepatic insulin resistance. Hepatic ubiquitin specific protease 4 (USP4), USP18, and dual-specificity phosphatases 14 (DUSP14) can suppress TAK1 phosphorylation, besides tumor necrosis factor receptor-associated factor 3 (TRAF3) and tripartite motif 8 (TRIM8) promote its phosphorylation. In this study, we tried to verify our hypothesis that exercise improves insulin resistance in high-fat diet (HFD)-induced obese (DIO) rats via regulating the TAK1 dependent signaling and TAK1 regulators in liver. Forty male Sprague-Dawley rats were randomized into four groups (n = 10): standard diet and sedentary as normal control; fed on HFD and DIO-sedentary; fed on HFD and DIO-chronic exercise; and fed on HFD and DIO-acute exercise. HFD feeding resulted in increased body weight, visceral fat mass, serum FFAs and hepatic lipid deposition, but decreased hepatic glycogen content and insulin sensitivity. Moreover, hepatic TRAF3 and TRIM8 protein levels increased, whereas USP4, USP18, and DUSP14 protein levels were decreased under obese status, which resulted in enhanced TAK1 phosphorylation and impaired insulin signaling. Exercise training, containing chronic and acute mode, both ameliorated insulin resistance. Meanwhile, decreased TAK1, c-Jun N-terminal kinase 1 (JNK1), and insulin receptor substrate 1 (IRS1) phosphorylation enhanced Akt phosphorylation in liver. Moreover, exercise enhanced USP4 and DUSP14 protein levels, whereas decreased TRIM8 protein levels in obese rats' liver. These results showed that exercise triggered a crucial modulation in TAK1-dependent signaling and its regulators in obese rats' liver, and distinct improvement in insulin sensitivity, which provide new insights into the mechanism by which physical exercise improves insulin resistance.

Aims Little is known regarding whether the NFE2/miR-423-5p and FAM3A-ATP-Akt pathway in liver mediates exercise allured alleviation of insulin resistance connected with diet-induced obesity. This research inquired the influence of exercise on liver insulin sensitivity and whole body insulin resistance in high-fat diet fed rats. Materials and methods Forty male Sprague-Dawley rats at seven-week-old were assigned to four groups at random: standard diet as normal control group (NC, n = 10), high-fat diet group (HFD, n = 10), high-fat diet with chronic exercise intervention group (HFD-CE, n = 10) and high-fat diet with acute exercise intervention group (HFD-AE, n = 10). Key findings Compared with rats fed with a standard diet, eight-week high-fat diet feeding lead to elevated body weight, visceral fat content and serum FFAs, and decreased insulin sensitivity index. Moreover, high-fat diet enhanced NFE2 protein expression and miR-423-5p level, decreased FAM3A mRNA and protein expression, ATP level and Akt phosphorylation in liver. In contrast, physical exercise, both chronic and acute exercise alleviated whole body insulin resistance, reduced hepatic NFE2 and miR-423-5p expression, and serum FFAs level, meanwhile enhanced FAM3A mRNA and protein expression, ATP level and Akt phosphorylation in liver. The current findings indicated that exercise in diet-induced obesity, both chronic and acute, induce a momentous regulation in NFE2/miR-423-5p and FAM3A-ATP-Akt pathway in liver, and improve hepatic insulin sensitivity and whole body insulin resistance. Significance All these results supply crucial evidence in our comprehending of the molecular mechanism that connected exercise to an alleviation of insulin resistance.

Structure restoration plays an important role in image completion. Though much progress has been made, existing techniques are ineffective to restore plausible complex structures, due to the high complexity of structure registration between neighboring regions. We address this challenge by taking two measures. The first is to get the images whose structures are potential to be well merged with the structures around the hole. This can be achieved by effectively retrieving the mass images on the internet, which provide enough candidates. The second is to coherently blend the retrieved structures with the structures around the hole, which is by suppressing the connection differences between these structures. Experimental results show that we can easily complete images, especially with complex structures or for filling large holes.

Traffic data is highly skewed with rare traffic incidents in the real word while most of the existing automatic incident detection (AID) algorithms suffer from limitations due to their inability to detect incidents under imbalanced traffic data condition. This paper developed feasible AID algorithms based on resampling methods to process imbalanced traffic data. In order to obtain the optimal sampling method for incident detection, we compare the detection performance of different AID algorithms based on various resampling methods. The detection performance is evaluated by the common criteria including classification rate, detection rate, false alarm rate, mean time to detection and an integrated performance index. The I-880 dataset is finally used in experiments to verify the proposed algorithms. The experimental results indicate that the proposed AID algorithm based on resampling can achieve better performance through handling imbalanced traffic data problem. Moreover, the under-sampling is competitive than over-sampling for traffic incident detection.

In order to adapt to new modern car styling, the aerodynamic numerical simulations based on computational fluid dynamics (CFD) are applied to the process of car styling. We received the early modeling design automobile aerodynamic coefficients, pressure distribution, velocity contours and other body outflow field data after the CFD post, combined with these data some advice to improve the aerodynamic drag of the designed car are given. Proposed aerodynamic automobile design method is based on numerical simulations, according to experience in air vehicle dynamics studies.

Considering the fact that the amount of traffic incident data is rare compared to the large amount of normal traffic state data in the real word, we proposed an Automatic Incident Detection (AID) algorithm based on subsampling method. First, an improved subsampling method based on Edited Nearest Neighbor Rule (ENN) algorithm was used to reconstruct the training set to get a balanced dataset. Then, the Support Vector Machine (SVM) was adopted as a classifier to detect traffic incidents. The real traffic data collected from the I-880 freeway in American was used to build the model and test the performance of the proposed AID algorithm. In addition, we made a comparison of the detection performances between the AID algorithm obtained by the original training set and the one by the relatively balanced training set. The experimental results show that the proposed AID algorithm based on subsampling is suitable for imbalanced dataset and can obtain a better detection performance.

In order to develop the four in-wheel motors driven Electric Vehicle (EV), this paper designed a skidding detector depending on the motor torque, established a slip-ratio estimator. Then, the Model Following Control (MFC) and Optimal Slip-ratio Control algorithms were analysed, compared and optimized. All of the algorithms were simulated using the one-wheel vehicle model. The simultion results show that the algorithms can make full use of the road adhesion characteristics and do good work on the ASR and the vehicle dynamics.

It is very important to extract high quality texture features from images. This is, however, often laborious, because the randomness in the color distribution patterns for texture elements makes texture measurement very difficult, despite these elements having a very similar visual appearance. In this paper, we propose the use of multi-scale color histograms to measure the effect of color distribution patterns efficiently and without having to compute the actual patterns, which saves considerable effort. Meanwhile, the hue-saturation-intensity color model is mainly adopted to take the advantage of human visual experiences in texture recognition. We discuss and validate the effectiveness and efficiency of our method by applying to various benchmarks. The results show that we can extract quality dominant textures automatically in real time, and faster by several orders of magnitude than existing methods.

Accurate FEA model of torsion beam suspension and its strain histories are keys to precisely predicting its fatigue life. A strain analysis method is presented, integrating FEA and neural network analysis. The displacement and force histories of the wheel center and strain histories of multiple measurement points on the suspension are measured from road durability test. Apply transient response analysis to determine the FEA model and obtain strain histories of the measurement points. Use a neural network method to obtain accurate additional load. By comparing analysis results and test data, the accurate strain response of torsion beam suspension can be gained