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This paper studies the characteristics of internal waves induced by the motion of a submerged body through a combination of experimental and numerical methods. First, by deploying an array of conductivity probes in an experiment, the temporal evolution of the internal wave at the plane of the conductivity probe array is obtained and compared with numerical simulation results based on the Navier–Stokes equations, thereby validating the accuracy of the Computational Fluid Dynamics (CFD) model. Subsequently, utilizing CFD calculations, further exploration is conducted on the spatiotemporal distribution characteristics of the internal wave, encompassing its generation and evolution, velocity field distribution, wake angle, and wave profile features. Finally, the variation of the internal wave with the Froude number (Fr) is investigated, revealing that it varies apparently with Fr, including the wave component, wave mode, wake length, wake angle, wave amplitude, and so on. It is found that when Fr is large, the internal wave converges toward the centerline behind the body, until forming a line. The wave magnitude changes with Fr in four stages, i.e., increasing with Fr from zero in the first stage, reaching a peak and decreasing thereafter in the second stage, then changing little in the third stage, and finally increasing approximately linearly in the fourth stage. [ABSTRACT FROM AUTHOR]

Effective science communication is one of the key skills undergraduates must achieve and is one of the threshold learning outcomes for Science (TLO 4.1). In addition, presenting published research to their peers allows students to critically evaluate scientific research (TLO 3.1) and develop a deeper appreciation for the link between experimental methodologies and the contestable nature of scientific knowledge. Although it is recognised that feedback given to students has positive impacts on student learning, increasing workload pressures may restrict academics' capacity to provide effective feedback. An alternate approach is to facilitate the exchange of feedback between peers, where gaining experience in providing feedback can further develop students' skills in critique, which enhances their learning outcomes. In this study, 3rd year undergraduate biomedical science students were asked to provide anonymous, written feedback on the quality of an oral "journal club" presentation of a primary research article by a group of their peers. Students gave extensive, rich and detailed feedback to their peers. The quality of the feedback given was high, with most students receiving a grade of distinction or higher for the feedback they provided. In addition, the improvement in student learning outcomes was significantly greater with peer feedback than with academic feedback alone, suggesting that performing peer review provides students with additional benefits.

TCL CSOT utilized inkjet printing technology to produce impressive medium and large‐size OLED products in the previous. In this work, high‐resolution notebook equipped with IGZO backplane is shown. This inkjet printing notebook offers 240 PPI along with good optical performance. Also, breakthrough in high‐resolution printing has been achieved, 274 PPI panel has been successfully printed. It is demonstrated that inkjet printing technology would adapt the trend of display products with various sizes toward higher resolution. [ABSTRACT FROM AUTHOR]

With the development of the Internet of Things, a huge number of devices are connected to the network, network traffic is exhibiting massive and low latency characteristics. At the same time, it is becoming cheaper and cheaper to launch DDoS attacks, and the attack traffic is becoming larger and larger. Software-defined networking SDN is proposed as a new network architecture. However, the controller as the core of SDN is vulnerable to DDoS attacks and causes a single point of failure in the network. This paper combines the ideas of distributed and edge computing, firstly, a DDoS attack detection algorithm using heterogeneous integrated feature selection and random forest algorithm is proposed. Then, this DDoS attack detection algorithm is distributed and deployed on the edge equipment switches of SDN to perform distributed edge parallel computing using the residual computing power of the switches for fast and accurate detection of DDoS attacks. Finally, simulation experiments are conducted in the SDN environment using the CIC-DDoS2019 dataset to evaluate the effectiveness and feasibility of the proposed scheme. The experimental results show that the performance evaluation metrics of this solution: accuracy, precision, recall and F-value all reach 99.99%, while the prediction time is only 0.4 s, all metrics are better than other DDoS attack detection methods in the same category. Therefore, this solution is able to detect DDoS attacks in a timely and accurate manner. [ABSTRACT FROM AUTHOR]