The tactical role of return height in tennis rallies has been largely overlooked in existing research, which tends to focus on placement or overall outcomes. This study addresses this gap by developing a machine learning based decision model to optimize return height in prolonged rallies. Using data from seven matches of the 2024 Australian Open Men’s Singles Champion, 7,200 shot-level records were extracted and analyzed. Three algorithms—support vector machine (SVM), artificial neural network (ANN), and random forest (RF)—were applied to predict optimal return heights, with RF achieving the highest accuracy (84.5%) and F1-score (94.0%). Furthermore, a personalized model incorporating K-means clustering improved accuracy to 81.2% for specific player styles. Feature importance and sensitivity analysis confirmed that return height is a key tactical determinant. This study contributes a data-driven framework for analyzing return strategy in tennis and provides practical implications for coaching, player training, and real-time tactical support.
A molecularly imprinted membrane was prepared in aqueous media using CS as functional monomer, EGCG as template molecules. The morphologies of molecularly imprinted membrane before and after modification with porogen (PEG) were observed by SEM. The imprinted membrane showed an excellent performance after several times adsorption and desorption. According to Scatchard analysis, the result showed that the imprinted membrane had a binding site for EGCG, the max adsorption capacity of imprinted membrane and equilibrium binding constant arrived at 49.52 mg/g, 4.046, respectively
The development of adsorbents that combine high efficiency, selectivity, and scalability for the removal of radioactive cesium (Cs+) from contaminated water remains a critical challenge. Although powdered Prussian blue (PB) is an excellent Cs+ scavenger, its practical application is limited by difficulties in recovery and the risk of secondary pollution. To address this, we report the mass-producible fabrication of Prussian blue/polyacrylonitrile (PB/PAN) composite fibers via a facile and scalable wet-spinning technique. Batch adsorption experiments demonstrated that the process follows the Langmuir model and pseudo-second-order kinetics, indicating monolayer chemisorption with a maximum capacity of 24.11 mg/g at 298 K. The fibers exhibited exceptional selectivity for Cs+ in a multicomponent system containing 13 competing ions. Furthermore, the adsorbent showed excellent reusability, retaining over 75% of its initial capacity after three adsorption-desorption cycles. Mechanistic studies, combining spectroscopic analyses (XPS, XRD, Mössbauer) and theoretical calculations (DFT), revealed that the high performance originates from a "lattice insertion-coordination" mechanism, where Cs+ is selectively embedded into the PB lattice vacancies and coordinates with cyanide nitrogen atoms. This work provides not only a practical and scalable adsorbent for environmental remediation but also offers profound insights into the molecular-level interaction between Cs+ and PB-based materials.
Students in international classroom settings face difficulties comprehending and writing down data shared with them, which causes unnecessary frustration and misunderstanding. However, utilizing digital aids to record and store data can alleviate these issues and ensure comprehension by providing other means of studying/reinforcement. This paper presents an application to actively listen and write down notes for students as teachers instruct class. We applied our application to multiple class settings and company meetings, and conducted a qualitative evaluation of the approach.
Explaining the causes of infeasibility of Boolean formulas has practical applications in various fields. A small unsatisfiable subset can provide a succinct explanation of infeasibility and is valuable for applications, such as FPGA routing. The Boolean-based FPGA detailed routing formulation expresses the routing constraints as a Boolean function which is satisfiable if and only if the layout is routable. The unsatisfiable subformulas can help the FPGA routing tool to diagnose and eliminate the causes of unroutable. For this typical application, a resolutionbased local search algorithm to extract unsatisfiable subformulas is integrated into Booleanbased FPGA routing method. The fastest algorithm of deriving minimum unsatisfiable subformulas, called the branch-and-bound algorithm, is adopted to compare with the local search algorithm. On the standard FPGA routing benchmark, the results show that the local search algorithm outperforms the branch-and-bound algorithm on runtime. It is also concluded that the unsatisfiable subformulas play a very important role in FPGA routing real applications.