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Soft tissue is an important operation object in robot-assisted surgery and its mechanical response is of great significance to the precision of surgical operation. Accurate prediction of soft tissue mechanical properties can effectively avoid the potential damage of biological tissue caused by excessive operating force. In this paper, three typical mechanical responses of soft tissue were obtained by no-slip compression experiments of liver tissue. Second, the prediction model of soft tissue mechanical response based on gray prediction was established, and the influence of key parameters of the model on the precision of mechanical response prediction was analyzed. The results show that the gray prediction model can accurately predict the mechanical response of soft tissue, and the prediction accuracy is the highest when the number of historical data is 7. The prediction method of soft tissue mechanical response proposed in this paper will provide important data reference for accurate operation of surgery. [ABSTRACT FROM AUTHOR]

Chemical graph theory plays an essential role in modeling and designing any chemical structure or chemical network. For a (molecular) graph, the Zagreb indices and the Zagreb eccentricity indices are well-known topological indices to describe the structure of a molecule or graph and can be used to predict properties such as the size and number of rings in a molecule, as well as the thermodynamic stability and reactivity of compounds. In this paper, we introduce a class of molecular models, namely, the Vicsek polygon graphs, which extend the traditional Vicsek networks. We compute the Zagreb indices and the Zagreb eccentricity indices of Vicsek polygon graphs by self-similarity and the recurrence relation based on the construction of graphs. [ABSTRACT FROM AUTHOR]

In this paper, the finite element method is used to investigate the sound absorption performance of the micro perforated plates (MPPs) with acoustic black hole (ABH) back cavities. First, the finite element models of MPPs with sealed back cavities and ABH back cavities are developed. The simulation results show that the absorption bandwidth of ABH back cavities increases by 63.8% compared to the sealed back cavity of the same size, but the frequency of the highest absorption coefficient is increased. Second, the mechanism for expanding the band width is illustrated by the pressure distribution inside two cavities. Finally, the effect of different cavity numbers of stages and lengths on the sound absorption performance is analyzed. This study broadens the application scenario of MPPs by incorporating ABH back cavities and can provide a reference value for acoustic modulation. [ABSTRACT FROM AUTHOR]

This paper proposes a ventilation barrier for low-frequency sound insulation with a double-opening Helmholtz's periodic structure. The energy band characteristics of the unit structure and the sound transmission loss of the ventilation barrier are calculated using the finite element method. The research results show that the ventilation barrier exhibits excellent sound insulation in the range of 323–803 Hz, and the sound insulation band is consistent with the bandgap of the unit structure. In order to reveal the sound insulation mechanism, we have performed a modal analysis of the unit structure. Further, the effects of different dimensional parameters on the structural bandgap are analyzed by changing the structure. The results show that extending the length of the structure inlet or outlet can effectively reduce the start frequency of the low-frequency bandgap, thus achieving the regulation of the sound insulation band. The proposed low-frequency sound insulation ventilation barrier has a simple structure with great application prospects. In addition, the proposed ventilation barrier provides a new idea for noise control in low-frequency ventilation environments. [ABSTRACT FROM AUTHOR]

According to the traditional law of mass, the insulation of low-frequency sound usually requires thick, high-density materials. However, lightweight metamaterials containing acoustic structures can also achieve high acoustic transmission losses. In this study, we present a sonic black hole (SBH) device coupled with micro-perforated plates (MPPs) and intraluminal column structure to achieve high sound insulation performance with light weight. The finite element model (FEM) is developed to analyze the acoustic energy distribution and dissipation inside the SBH device to evaluate its sound transmission loss (STL), and the accuracy of the analytical model is verified by impedance tube testing. The analysis results show that the SBH device has excellent sound insulation performance in the broadband and low frequency mainly due to the energy dissipation caused by the MPPs and column structure, and wavelength compression, energy focusing caused by the SBH effect. Finally, the sound insulation capacity of SBH can be further improved by improving the structure, such as increasing the complexity of acoustic medium flow and adding the number of layers of MPPs. The numerical model and the calculation results of this paper provide a new way of thinking for the design and optimization of SBH sound insulation structures. [ABSTRACT FROM AUTHOR]

In this paper, we study Vicsek polygons and extended Vicsek networks, which are an extension of Vicsek fractal. Our research indices are some Fermat-type indices, including the Fermat eccentricity and the Fermat eccentric distance sum. Fermat-type indices are novel graph invariants with vast potential in research on structure–activity and quantitative structure–property. By the approach of finite pattern, we solve some integrals to gain their asymptotic formulas on Fermat eccentricity and Fermat eccentric distance sum. [ABSTRACT FROM AUTHOR]

We evaluate the performance of the penalized vector autoregression (VAR), diffusion index (DI), and regression tree-based ensemble learning models to forecast Singapore's macroeconomy using high-dimensional data. Our dataset consists of 220 monthly time series that capture the economy of Singapore and 20 monthly times series that capture the global economic environment. We find that the penalized VAR model and the ensemble learning model give an outstanding performance in both short and long horizons. On the other hand, the performance of the DI model depends crucially on the methods to select the number of factors. In particular, a conventional selection method may overestimate the true number of factors and thus deteriorate the forecasting performance of the DI model. Additionally, the VAR and DI models may utilize different information in forecasting. [ABSTRACT FROM AUTHOR]

Using wearable devices to realize the mining and application of human behavior patterns has become a hotspot in the field of intelligent positioning. Wearable devices provide an analyzable data foundation for indoor spatial distribution and human behavior pattern prediction. The development of the intelligent positioning system based on RSSI has encountered a bottleneck that it is difficult to improve the positioning accuracy. Therefore, some research works started emphasizing location technology based on channel state information (CSI). In this paper, the principle used by Wi-Fi channel state information to realize intelligent positioning is described, the characteristics of CSI are analyzed, and an intelligent positioning algorithm based on CSI is proposed. Specifically, the algorithm first estimates the angle of arrival (AoA) based on the MUSIC algorithm, separates the reflected paths in the multipath components, and accurately estimates the AoA of each path. Second, phase estimation with channel state information is achieved by forming different antenna subarray measurements under the consideration of a subset of antennas and subcarriers. Then, the phase response linear fitting of the data packet CSI is eliminated using the ToF purification algorithm to obtain the corrected phase response and realize the elimination of the STO noise of the channel state information. Finally, the target position is calculated by effectively filtering the reflection path through the likelihood value, and the accurate target positioning function is achieved. The experimental results demonstrate that the intelligent positioning algorithm proposed in this paper can achieve decimeter-level positioning accuracy under the condition of a fixed number of APs, and the average error is better than that of deep learning-based and SVM-based positioning algorithms. In other words, the accuracy of intelligent positioning is improved. [ABSTRACT FROM AUTHOR]

This study presents the tensile properties of glass fiber-reinforced polymer (GFRP) composites under dynamic loadings. The dynamic tensile tests were performed via a high-speed servo-hydraulic testing machine with a velocity ranging from 1 m/s to 15 m/s, corresponding to a strain rate range between 4.9 s−1 and 93.7 s−1. The effects of the strain rate on the tensile strength and dynamic increase factor (DIF) were considered. The results showed that the tensile strength and DIF of GFRP increased with the strain rate. The failure pattern of GFRP was discussed via a group of high-speed camera images. The results of this research can provide useful information for future construction, e.g., protective structures under extreme impacts. [ABSTRACT FROM AUTHOR]

Let M be an almost cosymplectic manifold such that the Reeb vector field is Killing. In this paper, it is proved that if the metric of M satisfying the η -Einstein condition is an η -Ricci soliton, then either M is Ricci flat or the potential vector field is an infinitesimal contact transformation. Also, a concrete example of cosymplectic 3 -manifold admitting non-trivial Ricci and η -Ricci solitons is constructed. [ABSTRACT FROM AUTHOR]

Humans obtain characteristic information such as texture and weight of external objects, relying on the brain's integration and classification of tactile information; however, the decoding mechanism of multi-level tactile information is relatively elusive from the temporal sequence. In this paper, nonvariant frequency, along with the variant pulse width of electrotactile stimulus, was performed to generate multi-level pressure sensation. Event-related potentials (ERPs) were measured to investigate the mechanism of whole temporal tactile processing. Five ERP components, containing P100–N140–P200–N200–P300, were observed. By establishing the relationship between stimulation parameters and ERP component amplitudes, we found the following: (1) P200 is the most significant component for distinguishing multi-level tactile sensations; (2) P300 is correlated well with the subjective judgment of tactile sensation. The temporal sequence of brain topographies was implemented to clarify the spatiotemporal characteristics of the tactile process, which conformed to the serial processing model in neurophysiology and cortical network response area described by fMRI. Our results can help further clarify the mechanism of tactile sequential processing, which can be applied to improve the tactile BCI performance, sensory enhancement, and clinical diagnosis for doctors to evaluate the tactile process disorders by examining the temporal ERP components. [ABSTRACT FROM AUTHOR]