Electric-field induced droplet vertical vibration and horizontal motion: Experiments and simulations

In this work, Electrowetting on Dielectric (EWOD) and electrostatic induction (ESI) are employed to manipulate droplet on the PDMS-ITO substrate. Firstly, we report large vertical vibrations of the droplet, induced by EWOD, within a voltage range of 40 to 260 V. The droplet's transition from a vibrating state to a static equilibrium state are investigated in detail. It is indicated that the contact angle changes synchronously with voltage during the vibration. The electric signal in the circuit is measured to analyze the vibration state that varies with time. By studying the influence of driving voltage on the contact angle and the amplitude in the vibration, it is shown that the saturation voltage of both contact angle and amplitude is about 120 V. The intrinsic connection between contact angle saturation and amplitude saturation is clarified by studying the surface energy of the droplet. A theoretical model is constructed to numerically simulate the vibration morphology and amplitude of the droplet. Secondly, we realize the horizontal motion of droplets by ESI at the voltage less than 1000 V. The charge and electric force on the droplet are numerically calculated. The frictional resistance coefficients of the droplet are determined by the deceleration of the droplet. Under consideration of frictional resistance of the substrate and viscous resistance of the liquid, the motion of the droplet is calculated at 400 V and 1000 V, respectively. This work introduces a new method for manipulating various forms of droplet motion using the single apparatus

A Highly Specific Probe for Sensing Hydrogen Sulfide in Live Cells Based on Copper-Initiated Fluorogen with Aggregation-Induced Emission Characteristics

Here we reported the first fluorescent probe with aggregation-induced emission characteristics, namely AIE-S, for the detection of hydrogen sulfide (H2S) in live cells. The detection system is selective for complicated biological application and the response is fast enough to complete within seconds. Moreover, the probe exhibits the unique advantage of being immune to aggregation-caused quenching which is a detrimental phenomenon limiting the application of most current available H2S fluorescent probes. The detection mechanism was investigated and postulated to be S2- initiated de-coordination and thereafter aggregation of the AIE-S complex

Resource Support or Emotional Trust: Effects of Perceived Organizational Support on Entrepreneurial Performance of Global Talents in China

Global talents are introduced for entrepreneurship and development in China, which is not only a significant way to gather heterogeneous human capital and realize industrial transformation and upgrading in a short period of time, but also a strategic measure to drive innovative development and build an innovative country relying on talents. The regional innovation network gathers innovation elements such as upstream and downstream enterprises, universities and scientific research institutes in the industrial chain, which provides great information and resource support for global talents to gather innovation and entrepreneurship in China. Taking global talents in China as the research object, this paper constructs the relationship model among perceived organizational support, innovation network embeddedness and entrepreneurship performance in innovation network and conducts empirical research. The survey data of Global Talents in China was analyzed by SPSS 24.0 and MPLUS 7.4. The results show that the two dimensions of perceived organizational support instrumentality and emotionality have significant positive impact on entrepreneurial performance and innovation network embeddedness; while innovation network embeddedness has significant positive effects on entrepreneurial performance, but the influence of structural embeddedness is more significant than that of relational embeddedness; relational embeddedness and structural embeddedness play a partial mediating role in the influence of instrumental support and emotional support on technological innovation performance, while structural embeddedness plays a complete mediating role in the influence of instrumental support and emotional support on growth potential performance. Based on the results of empirical research, the paper proposes to further optimize the allocation of network resources, strengthen emotional support, expand the scale of innovative network, and strive to create an international talent development environment that is similar to overseas

Learning Balance Feature for Object Detection

In the field of studying scale variation, the Feature Pyramid Network (FPN) replaces the image pyramid and has become one of the most popular object detection methods for detecting multi-scale objects. State-of-the-art methods have FPN inserted into a pipeline between the backbone and the detection head to enable shallow features with more semantic information. However, FPN is insufficient for object detection on various scales, especially for small-scale object detection. One of the reasons is that the features are extracted at different network depths, which introduces gaps between features. That is, as the network becomes deeper and deeper, the high-level features have more semantics but less content description. This paper proposes a new method that includes a multi-scale receptive fields extraction module, a feature constructor module, and an attention module to improve the detection efficiency of FPN for objects of various scales and to bridge the gap in content description and semantics between different layers. Together, these three modules make the detector capable of selecting the most suitable feature for objects. Especially for the attention module, this paper chooses to use a parallel structure to simultaneously extract channel and spatial attention from the same features. When we use Adopting Adaptive Training Sample Selection (ATSS) and FreeAnchor as the baseline and ResNet50 as the backbone, the experimental results on the MS COCO dataset show that our algorithm can enhance the mean average precision (mAP) by 3.7% and 2.4% compared to FPN, respectively

SEFPN: Scale-Equalizing Feature Pyramid Network for Object Detection

Feature Pyramid Network (FPN) is used as the neck of current popular object detection networks. Research has shown that the structure of FPN has some defects. In addition to the loss of information caused by the reduction of the channel number, the features scale of different levels are also different, and the corresponding information at different abstract levels are also different, resulting in a semantic gap between each level. We call the semantic gap level imbalance. Correlation convolution is a way to alleviate the imbalance between adjacent layers; however, how to alleviate imbalance between all levels is another problem. In this article, we propose a new simple but effective network structure called Scale-Equalizing Feature Pyramid Network (SEFPN), which generates multiple features of different scales by iteratively fusing the features of each level. SEFPN improves the overall performance of the network by balancing the semantic representation of each layer of features. The experimental results on the MS-COCO2017 dataset show that the integration of SEFPN as a standalone module into the one-stage network can further improve the performance of the detector, by ∼1AP, and improve the detection performance of Faster R-CNN, a typical two-stage network, especially for large object detection APL∼2AP

Flow Coefficient and Starting Performance Prediction of Variable Geometry Curved Axisymmetric Inlet

With the development of combined cycle engines, it is urgent to estimate more quickly and accurately the flow capture capacity and starting performance of variable geometry inlets over a wide Mach number range. Based on the flow field and parameter fitting, two prediction methods for the curved axisymmetric inlet with lip translation scheme have been proposed. The method based on the flow field of the reference inlet is more efficient than the parameters-based prediction method, as it can accurately predict the lip translation distance and the corresponding flow coefficient over the entire working range of the inlet without additional numerical calculations. Moreover, the starting Mach number is accurately predicted by the fitting method based on the throat Mach number of the reference inlet, with a relative error of only 0.95% compared to the numerical simulation. The flow coefficient-based method is simple and accurate for predicting lip translation distances with a known starting Mach number, with a relative error of only 1.65% compared to numerical simulations. The prediction approaches can overcome the drawbacks of the standard iterative algorithms and significantly enhance computational accuracy and efficiency

Experimental Study on Local Scour at the Monopile Foundation of an Offshore Wind Turbine under the Combined Action of Wave–Current–Vibration

Monopile foundations are the most widely used offshore wind turbine foundations. The experiments were conducted to investigate the influencing factors of local scour around the monopile under the action of wave–current–vibration. The study analyzed the characteristics of local scour, including the maximum scour depth, the development of scour hole shape, and the shape of the scour hole profile. The dimensionless influencing factors (vibration intensity, Froude number, Keulegan–Carpenter number, and combined wave–current parameter) are subsequently analyzed. An empirical formula is developed to predict the local scour depth of a monopile under the combined influence of wave–current–vibration. The formula provides a theoretical underpinning for engineering design

A Jpeg Image Coding Scheme For Wireless Multimedia Sensor Networks

With resource-constrained wireless multimedia sensor networks, image coding and transmission must respect the trade-off among energy consumption, compression ratio and image quality. Compression of videosurveillance image sequences collected by a wireless multimedia sensor network is studied. A low-complexity image compression scheme based on change detection and adapted JPEG is proposed. For adaptation to the limited capacity of store and forward, change detection algorithm is used to locate the region of interest and cut down the data for transmission by only transmitting the region of interest. For adaptation to the limited computational capability, DCT and quantization of JPEG is optimized to reduce the computation complexity. Computation complexity analysis and simulation results indicate that the proposed image compression scheme effectively reduces the data traffic and energy consumption of computation under the required image quality