69 research outputs found
The Effect of Normal Force on the Coupled Temperature Field of Metal Impregnation Carbon/Stainless Steel under the Friction and Wear with Electric Current
AbstractTemperature field model for aluminum-stainless steel composite conductor rail (stainless steel)/collector shoe (metal impregnation carbon) under the coupling of contact resistor-friction thermal was established by FE software ANSYS. The temperature field distribution model of the friction pair was simulated and the maximum coupled temperature changing with different normal force was researched. The results show that the maximum coupled temperatures decrease firstly and then rise with the increasing of normal force under the constant displacement, current and relative sliding speed. There is an optimal normal force making the maximum coupled temperature to be the lowest for the friction pair of the metal impregnation carbon and stainless steel. The normal force can be used as the working normal force in order to reduce the abrasion induced by temperature rising
Quantitative assessment of the associations between XRCC1 polymorphisms and bladder cancer risk
BACKGROUND: The XRCC1 polymorphisms have been implicated in bladder cancer risk, but individually published studies show inconsistent results. The aim of our study was to clarify the effects of XRCC1 variants on bladder cancer risk. METHODS: A systematic literature search up to September 13, 2012 was carried out in PubMed, EMBASE and Wanfang databases, and the references of retrieved articles were screened. Crude odds ratios with 95% confidence intervals were used to assess the associations between XRCC1 Arg194Trp and Arg399Gln polymorphisms and bladder cancer risk. Heterogeneity and publication bias were also evaluated. RESULTS: A total of 14 and 18 studies were eligible for meta-analyses of Arg194Trp and Arg399Gln, respectively. Regrouping was adopted in accordance with the most probable appropriate genetic models. No obvious heterogeneity between studies was found. For overall bladder cancer, the pooled odds ratios for Arg194Trp and Arg399Gln were 1.69 (95% confidence interval: 1.25 to 2.28; P = 0.001) and 1.10 (95% confidence interval: 1.03 to 1.19; P = 0.008), respectively. After excluding the studies that were not in Hardy–Weinberg equilibrium, the estimated pooled odds ratio still did not change at all. CONCLUSIONS: The meta-analysis results suggest that XRCC1 Arg194Trp and Arg399Gln polymorphisms may be associated with elevated bladder cancer risk
MicroRNA-124-3p inhibits cell migration and invasion in bladder cancer cells by targeting ROCK1
Surface modification of SiLK-R by graft copolymerization of 4-vinylpyridine for adhesion enhancement and reduction of copper diffusion
Master'sMASTER OF ENGINEERIN
How to Motivate Generation Y with Different CulturalBackgrounds - A Cross-Cultural Comparison between China and Sweden
Generation Y have become the newest group of the global workforce in Multinational Business and are about to become the largest. They are often referred to as a global group with global characteristics which leads them to be recruited and retained in the same way. Generation Y have their own general (global) characteristics, but are still affected by their national culture. The most up-to-date and comprehensive research made on national culture is the Global Leadership Organizational Behavior Effectiveness (GLOBE) research. This research has measured national culture in 62 countries and attributed them National Culture Values that can be measured in nine different cultural dimensions. These National Culture Values must be taken into account in order to properly motivate Generation Y with different cultural backgrounds. When you want to motivate someone, it is important to understand his/her wants and needs. The classical Content Motivation Theories focus on people’s needs and how these needs must be identified and met if you want to motivate people properly, but since they were constructed for generations with different characteristics than Generation Y, they have to be modified. This dissertation is based on the impact of National Culture Values on Generation Y in China and Sweden, and how these values may be in conflict with Generation Y’s general characteristics. To measure if the National Culture Values are stronger than the general characteristics of Generation Y in these conflicts, we have conducted a survey with two sample groups, one with Chinese students and one with Swedish students. The result of survey shows in some situations, the National Culture Values are stronger than the general characteristics of Generation Y, and vice versa. The main hypothesis of this dissertation is: National Culture Values affect Generation Y and must be taken into account in order to properly motivate them
Using Wearable Sensors to Estimate Vertical Ground Reaction Force Based on a Transformer
In this paper, we present a new method to estimate ground reaction forces (GRF) from wearable sensors for a variety of real-world situations. We address the drawbacks of using force plates with limited activity range and high cost in previous work. We use a transformer encoder as a feature extractor to extract temporal and spatial features from wearable sensors more efficiently. Using the Mean Absolute Percentage Error (MAPE) as the evaluation criterion, the experimental results show that the average error of the predicted values using the transformer as a feature extractor improved by 32% compared to the RNN architecture and by 25% compared to the LSTM architecture. Finally, we use Gate_MSE to solve the problem of a large peak error in GRF prediction. Meanwhile, this paper explores the effect of the number of wearable sensors or wearable modes on GRF prediction
Robust Adaptive Output Feedback Control for a Guided Spinning Rocket
An adaptive autopilot is presented for the pitch and yaw channels of a guided spinning rocket. Firstly, the uncertain dynamic model of a guided spinning rocket is established, which is used to evaluate the performance of the proposed adaptive autopilot. Secondly, a robust adaptive output feedback autopilot containing a baseline component and an adaptive component is designed. The main challenge that needs to be addressed is the determination of a corresponding square and strictly positive real transfer function. A simple design procedure based on linear matrix inequality is proposed that allows the realization of such a transfer function, thereby allowing a globally stable adaptive output feedback law to be generated. Finally, numerical simulations are performed to evaluate the robustness and tracking performance of the proposed robust adaptive autopilot. The simulation results showed that the robust adaptive output autopilot can achieve asymptotic command tracking with significant uncertainty in control effectiveness, moment coefficient, and measurement noise
Faster Deep Inertial Pose Estimation with Six Inertial Sensors
We propose a novel pose estimation method that can predict the full-body pose from six inertial sensors worn by the user. This method solves problems encountered in vision, such as occlusion or expensive deployment. We address several complex challenges. First, we use the SRU network structure instead of the bidirectional RNN structure used in previous work to reduce the computational effort of the model without losing its accuracy. Second, our model does not require joint position supervision to achieve the best results of the previous work. Finally, since sensor data tend to be noisy, we use SmoothLoss to reduce the impact of inertial sensors on pose estimation. The faster deep inertial poser model proposed in this paper can perform online inference at 90 FPS on the CPU. We reduce the impact of each error by more than 10% and increased the inference speed by 250% compared to the previous state of the art
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