Nonlinear dynamics of a flapping rotary wing: Modeling and optimal wing kinematic analysis

The analysis of the passive rotation feature of a micro Flapping Rotary Wing (FRW) applicable for Micro Air Vehicle (MAV) design is presented in this paper. The dynamics of the wing and its influence on aerodynamic performance of FRW is studied at low Reynolds number (∼103). The FRW is modeled as a simplified system of three rigid bodies: a rotary base with two flapping wings. The multibody dynamic theory is employed to derive the motion equations for FRW. A quasi-steady aerodynamic model is utilized for the calculation of the aerodynamic forces and moments. The dynamic motion process and the effects of the kinematics of wings on the dynamic rotational equilibrium of FWR and the aerodynamic performances are studied. The results show that the passive rotation motion of the wings is a continuous dynamic process which converges into an equilibrium rotary velocity due to the interaction between aerodynamic thrust, drag force and wing inertia. This causes a unique dynamic time-lag phenomena of lift generation for FRW, unlike the normal flapping wing flight vehicle driven by its own motor to actively rotate its wings. The analysis also shows that in order to acquire a high positive lift generation with high power efficiency and small dynamic time-lag, a relative high mid-up stroke angle within 7–15° and low mid-down stroke angle within −40° to −35° are necessary. The results provide a quantified guidance for design option of FRW together with the optimal kinematics of motion according to flight performance requirement

Unconventional ferromagnetism and spin-triplet superconductivity in the imbalanced Kagome-lattice Hubbard model

Unconventional ferromagnetism and superconductivity in the imbalanced kagome-lattice Hubbard model are investigated by the mean-field theory and determinant quantum Monte Carlo method. Due to the asymmetric band structure of kagome lattice, the spin-$z$ ferromagnetic order intrinsically exists in the system, which is first enhanced by the interaction, and then continuously destructed after reaching a maximum at a moderate interaction strength. In contrast, the $xy$-plane ferromagnetism develops only above a critical interaction, which is estimated to be $U_c/t=3.65 \pm 0.05$ by finite-size scaling. We further verify the nature of the above transverse magnetic transition, and demonstrate it belongs to the three-dimensional $XY$ universality class. Finally, we study the superconducting property, and reveal the possible superconducting state has a triplet $f$-wave pairing symmetry. Our results uncover the exotic quantum states induced by the interactions on kagome lattice, and provide important insights regarding the interplay between electronic correlations and geometry frustrations

Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks

Voucher abuse detection is an important anomaly detection problem in E-commerce. While many GNN-based solutions have emerged, the supervised paradigm depends on a large quantity of labeled data. A popular alternative is to adopt self-supervised pre-training using label-free data, and further fine-tune on a downstream task with limited labels. Nevertheless, the "pre-train, fine-tune" paradigm is often plagued by the objective gap between pre-training and downstream tasks. Hence, we propose VPGNN, a prompt-based fine-tuning framework on GNNs for voucher abuse detection. We design a novel graph prompting function to reformulate the downstream task into a similar template as the pretext task in pre-training, thereby narrowing the objective gap. Extensive experiments on both proprietary and public datasets demonstrate the strength of VPGNN in both few-shot and semi-supervised scenarios. Moreover, an online deployment of VPGNN in a production environment shows a 23.4% improvement over two existing deployed models.Comment: 7 pages, Accepted by CIKM23 Applied Research Trac

Prognostic value of osteopontin splice variant-c expression in breast cancers: a meta-analysis

Objectives. Osteopontin (OPN) is overexpressed in breast cancers, while its clinical and prognostic significance remained unclear. This study aimed to assess the prognostic value of OPN, especially its splice variants, in breast cancers. Methods. Data were extracted from eligible studies concerning the OPN and OPN-c expression in breast cancer patients and were used to calculate the association between OPN/OPN-c and survival. Two reviewer teams independently screened the literatures according to the inclusion and exclusion criteria based on quality evaluation. Following the processes of data extraction, assessment, and transformation, meta-analysis was carried out via RevMan 5.3 software. Results. A total of ten studies involving 1,567 patients were included. The results demonstrated that high level OPN indicated a poor outcome in the OS (HR = 2.22, 95% CI: 1.23–4.00, and ; random-effects model) with heterogeneity (%) of breast cancer patients. High level OPN-c appeared to be more significantly associated with poor survival (HR = 2.14, 95% CI: 1.51–3.04, and ; fixed-effects model) with undetected heterogeneity (%). Conclusions. Our analyses indicated that both OPN and OPN-c could be considered as prognostic markers for breast cancers. The high level of OPN-c was suggested to be more reliably associated with poor survival in breast cancer patients