Investigation of Energy Efficient Power Coupling Steering System for Dual Motors Drive High Speed Tracked Vehicle

This paper presents an energy efficient power coupling steering system for dual motors drive high speed tracked vehicle. The system consists of a new type of center steering motor, two electromagnetic (EM) clutches, two planetary gear couplers, and two propulsion motors. The motor torque and power required by dynamic steering with different steering radiuses for dual motors drive high speed tracked vehicle were investigated. A motor-speed-based control strategy of dynamic steering is designed to achieve vehicle lateral stability enhancement. The model of the proposed control strategy in RecuDyn and Matlab/Simulink is given. The simulation results of dynamic steering with 0.5B and 2B radius show that understeer in small radius steering can be significantly improved

Happiness

Everyone wants to be happy. Happiness is obviously a good thing and if we can get it without sacrificing other important things, we would. Most people wish not just for their own happiness but also the happiness of people they love; some compassionate souls may even wish for the happiness of all sentient creatures. What exactly is it that we all want? Is it to be pleased or satisfied? To feel tranquil or joyous? To attain certain objective goods? And what role does happiness play in morality? Is the production of happiness the goal of morally right action? Is it the organizing principle of moral theory? Or is it just one contingent value among many? This entry reviews answers to these questions from the perspectives of ancient, modern, and contemporary philosophy

Cloaking and imaging at the same time

In this letter, we propose a conceptual device to perform subwavelength imaging with positive refraction. The key to this proposal is that a drain is no longer a must for some cases. What's more, this device is an isotropic omnidirectional cloak with a perfect electric conductor hiding region and shows versatile illusion optical effects. Numerical simulations are performed to verify the functionalities.Comment: 15 pages, 4 figure

Mechanism and Prevention Technologies of Reservoir Gas Disaster in Abandoned Oil Well of Coal Mine

AbstractThe reservoir gas disaster has distinct characteristics and is a key factor that threatens the safe and green mining of coal mines in the costorage area of coal and petroleum resources. In order to solve the problem of prevention and control of reservoir gas disasters in coal mines, the characteristics of oil-bed gas disasters in abandoned oil wells in coal mines were analyzed, and the oil-bed gas disaster mechanism of abandoned oil wells without isolation coal pillars was revealed to study the scope of gas disasters around oil wells under the influence of production. The research shows that: (1) abandoned oil well reservoir gas disasters have the characteristics of high gas pressure, high concentration, large lateral influence area, wide vertical sweep range, and frequent disasters, which seriously threaten the safety and green mining of coal mines; (2) divide the reservoir gas disaster of abandoned oil wells into the high-pressure gas disaster in the well and the disaster in the surrounding oil-bed gas enrichment area; (3) according to the numerical simulation results that the maximum damage depth of the coal seam mining floor is 38.6 m and the seepage height of high-pressure oil-bed gas is 40 m, the safety factor k is introduced, and the reservoir gas sweeping range of the abandoned oil well is determined to be 95.4 m below the coal seam to the surface; (4) the comprehensive prevention and control technical scheme of oil-bed gas for controlling high-pressure oil-bed gas in wells by ground plugging and downhole injection and injection of diluent to control enriched areas was proposed, which successfully solved the problem of safe and efficient exploitation of Shuangma coal mine in Ningdong coalfield by abandoned oil wells. The research results provide effective solutions for the realization of green mining in many coal mines in the costorage area of coal and oil resources in China and have important application value for the prevention and control of dynamic disasters in the costorage area of resources

A β-cyclodextrin modified graphitic carbon nitride with Au co-catalyst for efficient photocatalytic hydrogen peroxide production

Photocatalytic hydrogen peroxide (H2O2) production has attracted considerable attention as a renewable and environment-friendly method to replace other traditional production techniques. The performance of H2O2 production remains limited by the inertness of graphitic carbon nitride (CN) towards the adsorption and activation of O2. In this work, a photocatalyst comprising of β-cyclodextrin (β-CD)-modified CN with supporting Au co-catalyst (Au/β-CD-CN) has been utilized for effective H2O2 production under visible light irradiation. The static contact angle measurement suggested that β-CD modification increased the hydrophobicity of the CN photocatalyst as well as its affinity to oxygen gas, leading to an increase in H2O2 production. The rate of H2O2 production reached more than 0.1 mM/h under visible-light irradiation. The electron spin resonance spectra indicated that H2O2 was directly formed via a 2-electron oxygen reduction reaction (ORR) over the Au/β-CD-CN photocatalyst

Shrub type dominates the vertical distribution of leaf C : N : P stoichiometry across an extensive altitudinal gradient

Understanding leaf stoichiometric patterns is crucial for improving predictions of plant responses to environmental changes. Leaf stoichiometry of terrestrial ecosystems has been widely investigated along latitudinal and longitudinal gradients. However, very little is known about the vertical distribution of leaf C :N: P and the relative effects of environmental parameters, especially for shrubs. Here, we analyzed the shrub leaf C, N and P patterns in 125 mountainous sites over an extensive altitudinal gradient (523-4685 m) on the Tibetan Plateau. Results showed that the shrub leaf C and C :N were 7.3-47.5% higher than those of other regional and global flora, whereas the leaf N and N: P were 10.2-75.8% lower. Leaf C increased with rising altitude and decreasing temperature, supporting the physiological acclimation mechanism that high leaf C (e.g., alpine or evergreen shrub) could balance the cell osmotic pressure and resist freezing. The largest leaf N and high leaf P occurred in valley region (altitude 1500 m), likely due to the large nutrient leaching from higher elevations, faster litter decomposition and nutrient resorption ability of deciduous broadleaf shrub. Leaf N: P ratio further indicated increasing N limitation at higher altitudes. Interestingly, drought severity was the only climatic factor positively correlated with leaf N and P, which was more appropriate for evaluating the impact of water status than precipitation. Among the shrub ecosystem and functional types (alpine, subalpine, montane, valley, evergreen, deciduous, broadleaf, and conifer), their leaf element contents and responses to environments were remarkably different. Shrub type was the largest contributor to the total variations in leaf stoichiometry, while climate indirectly affected the leaf C :N: P via its interactive effects on shrub type or soil. Collectively, the large heterogeneity in shrub type was the most important factor explaining the overall leaf C :N: P variations, despite the broad climate gradient on the plateau. Temperature and drought induced shifts in shrub type distribution will influence the nutrient accumulation in mountainous shrubs. © Author(s) 2018

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

As microfluidics has been applied extensively in many cell and biochemical applications, monitoring the related processes is an important requirement. In this work, we design and fabricate a high-throughput microfluidic device which contains 32 microchambers to perform automated parallel microfluidic operations and monitoring on an automated stage of a microscope. Images are captured at multiple spots on the device during the operations for monitoring samples in microchambers in parallel; yet the device positions may vary at different time points throughout operations as the device moves back and forth on a motorized microscopic stage. Here, we report an image-based positioning strategy to realign the chamber position before every recording of microscopic image. We fabricate alignment marks at defined locations next to the chambers in the microfluidic device as reference positions. We also develop image processing algorithms to recognize the chamber positions in real-time, followed by realigning the chambers to their preset positions in the captured images. We perform experiments to validate and characterize the device functionality and the automated realignment operation. Together, this microfluidic realignment strategy can be a platform technology to achieve precise positioning of multiple chambers for general microfluidic applications requiring long-term parallel monitoring of cell and biochemical activities

PI3K/AKT/mTOR pathway-derived risk score exhibits correlation with immune infiltration in uveal melanoma patients

Uveal melanoma (UVM) is a rare but highly aggressive intraocular tumor with a poor prognosis and limited therapeutic options. Recent studies have implicated the PI3K/AKT/mTOR pathway in the pathogenesis and progression of UVM. Here, we aimed to explore the potential mechanism of PI3K/AKT/mTOR pathway-related genes (PRGs) in UVM and develop a novel prognostic-related risk model. Using unsupervised clustering on 14 PRGs profiles, we identified three distinct subtypes with varying immune characteristics. Subtype A demonstrated the worst overall survival and showed higher expression of human leukocyte antigen, immune checkpoints, and immune cell infiltration. Further enrichment analysis revealed that subtype A mainly functioned in inflammatory response, apoptosis, angiogenesis, and the PI3K/AKT/mTOR signaling pathway. Differential analysis between different subtypes identified 56 differentially expressed genes (DEGs), with the major enrichment pathway of these DEGs associated with PI3K/AKT/mTOR. Based on these DEGs, we developed a consensus machine learning-derived signature (RSF model) that exhibited the best power for predicting prognosis among 76 algorithm combinations. The novel signature demonstrated excellent robustness and predictive ability for the overall survival of patients. Moreover, we observed that patients classified by risk scores had distinguishable immune status and mutation. In conclusion, our study identified a consensus machine learning-derived signature as a potential biomarker for prognostic prediction in UVM patients. Our findings suggest that this signature is correlated with tumor immune infiltration and may serve as a valuable tool for personalized therapy in the clinical setting