The Effect of Algorithmic Recommendations on Female University Students’ Willingness to Engage in Romantic Behaviour

With algorithmic recommendations becoming an important way and means of information distribution, social media platforms are developing rapidly, and students in colleges and universities today have become the main audience for their information access. In this paper, through the application of TPB model in the intention to fall in love of young female groups in colleges and universities, four variables, namely attention, attitude, subjective norm and perceived behavioural control, were studied in depth, and a research model of factors influencing the relationship behaviour of young female groups was constructed based on the theoretical model of planned behaviour. According to the results, the factor of attention did not have a significant positive effect on relationship behaviour intentions, and behavioural attitudes, subjective norms and perceived behavioural control (PBC) had a significant positive effect on relationship behaviour intentions

The Effect of Algorithmic Recommendations on Female University Students’ Willingness to Engage in Romantic Behaviour

With algorithmic recommendations becoming an important way and means of information distribution, social media platforms are developing rapidly, and students in colleges and universities today have become the main audience for their information access. In this paper, through the application of TPB model in the intention to fall in love of young female groups in colleges and universities, four variables, namely attention, attitude, subjective norm and perceived behavioural control, were studied in depth, and a research model of factors influencing the relationship behaviour of young female groups was constructed based on the theoretical model of planned behaviour. According to the results, the factor of attention did not have a significant positive effect on relationship behaviour intentions, and behavioural attitudes, subjective norms and perceived behavioural control (PBC) had a significant positive effect on relationship behaviour intentions

Composites, Fabrication and Application of Polyvinylidene Fluoride for Flexible Electromechanical Devices: A Review

The technological development of piezoelectric materials is crucial for developing wearable and flexible electromechanical devices. There are many inorganic materials with piezoelectric effects, such as piezoelectric ceramics, aluminum nitride and zinc oxide. They all have very high piezoelectric coefficients and large piezoelectric response ranges. The characteristics of high hardness and low tenacity make inorganic piezoelectric materials unsuitable for flexible devices that require frequent bending. Polyvinylidene fluoride (PVDF) and its derivatives are the most popular materials used in flexible electromechanical devices in recent years and have high flexibility, high sensitivity, high ductility and a certain piezoelectric coefficient. Owing to increasing the piezoelectric coefficient of PVDF, researchers are committed to optimizing PVDF materials and enhancing their polarity by a series of means to further improve their mechanical–electrical conversion efficiency. This paper reviews the latest PVDF-related optimization-based materials, related processing and polarization methods and the applications of these materials in, e.g., wearable functional devices, chemical sensors, biosensors and flexible actuator devices for flexible micro-electromechanical devices. We also discuss the challenges of wearable devices based on flexible piezoelectric polymer, considering where further practical applications could be

Fintech and Financing Constraints of Enterprises: Evidence from China

Using a sample of China\u27s A-share listed companies from 2011 to 2018, this research examines the impact of financial technology (FinTech) on financing constraints experienced by enterprises. Results show that the development of FinTech can significantly reduce firms\u27 financing constraints, and this effect is partially mediated by facilitating firms\u27 direct and indirect financing, and by promoting inter-bank competition. The mitigating effect of FinTech is more pronounced in non-state-owned enterprises, in small- and medium-sized enterprises, and enterprises in the more highly developed eastern region of China. The direct mitigating effect of FinTech on reducing financing constraints is stronger for companies with a higher level of innovation or a lower level of social responsibility performance. Theoretical and practical implications of our findings are discussed

Fintech and Financing Constraints of Enterprises: Evidence from China

Using a sample of China\u27s A-share listed companies from 2011 to 2018, this research examines the impact of financial technology (FinTech) on financing constraints experienced by enterprises. Results show that the development of FinTech can significantly reduce firms\u27 financing constraints, and this effect is partially mediated by facilitating firms\u27 direct and indirect financing, and by promoting inter-bank competition. The mitigating effect of FinTech is more pronounced in non-state-owned enterprises, in small- and medium-sized enterprises, and enterprises in the more highly developed eastern region of China. The direct mitigating effect of FinTech on reducing financing constraints is stronger for companies with a higher level of innovation or a lower level of social responsibility performance. Theoretical and practical implications of our findings are discussed

Mechanical Vibration Measurement of Solidly Mounted Resonator in Fluid by Atomic Force Microscopy

The very small vibration of a solidly-mounted resonator (SMR) in fluid may trigger a relatively large motion of the covering fluid, which was implied by our protein-related experimental results. Therefore, a series of experimental methods for characterizing the mechanical longitudinal vibration of the SMR and the corresponding out-of-plane dynamic response of the fluid above the SMR surface is described in this paper. A SMR device with theoretical resonance frequency of 2.5 GHz was driven by an amplitude-modulated (AM) signal, in which the amplitude is modulated by a signal of the second resonance frequency of the atomic force microscope (AFM) cantilever. A lock-in amplifier is used to demodulate the vibration response of the AFM cantilever, which is proportional to the amplitude of the sample vibration in contact mode and tapping mode. The amplitude-frequency curve of the SMR surface is obtained in contact mode with a relatively stronger interaction force between the AFM tip and the SMR surface. The amplitude-frequency curve of the motion of the liquid above the SMR device and the peak amplitude of the fluid at different distances above the SMR surface are measured in tapping mode with a relatively weak interaction force between the AFM tip and the fluid sample

Flow-induced noise simulation using detached eddy simulation and the finite element acoustic analogy method

Signals in long-distance pipes are complex due to flow-induced noise generated in special structure, and the computation of these noise sources is difficult and time-consuming. To address this problem, a hybrid method based on computational fluid dynamics and Lighthill’s acoustic analogy theory is proposed to simulate flow-induced noise, with the results showing that the method is sufficient for noise predictions. The proposed method computes the turbulent flow field using detached eddy simulation and then calculates turbulence-generated sound using the finite element acoustic analogy method, which solves acoustic sources as volume sources. The velocity field obtained in the detached eddy simulation computation provides the sound source through interpolation between the computational fluid dynamics and acoustic meshes. The hybrid method is validated and assessed by comparing data from the cavity in pipe and large eddy simulation results. The peak value of flow-induced noise calculated at the monitor point is in good agreement with experimental data available in the literature

Multimodal Fusion for Indoor Sound Source Localization

To identify the localization of indoor sound source, especially when attempted using only a single microphone, it is a challenging problem to machine learning. To address these issues, this paper presents a distinct novel solution based on fusing visual and acoustic models. Therefore, we propose two novel approaches. First, to estimate orientation of vocal object in a stable manner, we employ the visual approach as estimation model, where we develop a robust image feature representation method that adopts Fourier analysis to efficiently extract polar descriptors. Second the distance information is estimated by calculating the signal difference between transmit receive ends. To implement these, we use phoneme-level hidden Markov models (HMMs) extracted from clean speech sound, to estimate the acoustic transfer function (ATF), which can capture the speech signal as a network of phoneme HMMs. And using the separated frame sequences of the ATF, we can indicate the signal difference between two positions, which can be used to estimate the distance of sound source. Experimental results show that the proposed method can simultaneously extract the sound source parameters of direction and distance, and thus improves the verification task of sound source localization