Significance: Low-frequency oscillations (LFOs) ranging from 0.01 to 0.15 Hz are common in functional imaging studies. Some of these LFOs are non-neuronal and are correlated with autonomic physiological processes. Aim:We investigate the relationships between systemic low-frequency oscillations (sLFOs) measured at different peripheral sites during resting states in ischemic stroke patients.Approach: Twenty-seven ischemic stroke patients (ages 44 to 90; 20 male and 7 female) were recruited for the study. During the experiments, fluctuations in oxyhemoglobin concentration were measured in the left and right toes, fingertips, and earlobes using a multichannel nearinfrared spectroscopy instrument. We applied cross-correlation and frequency component analyses on the sLFO data. Results:The results showed that embolization broke the symmetry of the sLFO transmission and that the damage was not limited to the local area but spread throughout the body. Among six peripheral sites, the power spectrum width of the earlobes was significantly larger than that of the fingers and toes. This indicates that the earlobes may contain more physiological information. Finally, the results of fuzzy clustering verified that sLFOs can serve as perfusion biomarkers to differentiate stroke from healthy subjects. Conclusions:The high correlation values and corresponding delays in sLFOs support the hypothesis that (1) the correlation characteristics of sLFOs in stroke patients are different from those of healthy subjects. These characteristics can reflect patient condition, to an extent. Embolization in ischemic stroke patients breaks the symmetry of the body's sLFO transmission, disrupting the balance of blood circulation. (2) sLFOs can be used as perfusion biomarkers to differentiate ischemic stroke patients from healthy subjects. Studying these signals can explicate the overall feedback/influence of pericentral interactions. Finally, peripheral sLFOs have been shown to be an effective and accurate tool for assessing peripheral blood circulation and vascular integrity in ischemic stroke patients.
With the rapid development of the Internet of Things (IoTs), big data analytics has been widely used in the sport field. In this paper, a light-weight, self-powered sensor based on a triboelectric nanogenerator for big data analytics in sports has been demonstrated. The weight of each sensing unit is ~0.4 g. The friction material consists of polyaniline (PANI) and polytetrafluoroethylene (PTFE). Based on the triboelectric nanogenerator (TENG), the device can convert small amounts of mechanical energy into the electrical signal, which contains information about the hitting position and hitting velocity of table tennis balls. By collecting data from daily table tennis training in real time, the personalized training program can be adjusted. A practical application has been exhibited for collecting table tennis information in real time and, according to these data, coaches can develop personalized training for an amateur to enhance the ability of hand control, which can improve their table tennis skills. This work opens up a new direction in intelligent athletic facilities and big data analytics.
In order to get rid of the impact of the global financial crisis and actively respond to global climate change, it has become a common choice for global economic development to develop clean energy such as wind energy, improve energy efficiency and reduce greenhouse gas emissions. With the advantages of simple structure, unnecessary facing the wind direction, and unique appearance, the vertical axis wind turbine (VAWT) attracts extensive attention in the field of small and medium wind turbines. The lift-type VAWT exhibits outstanding aerodynamic characteristics at a high tip speed ratio, while the starting characteristics are generally undesirable at a low wind speed; thus, how to improve the starting characteristics of the lift-type VAWT has always been an important issue. In this paper, a lift-drag combined starter (LDCS) suitable for lift-type VAWT was proposed to optimize the starting characteristics of lift-type VAWT. With semi-elliptical drag blades and lift blades equipped on the middle and rear part outside the starter, the structure is characterized by lift-drag combination, weakening the adverse effect of the starter with semi-elliptical drag blades alone on the output performance of the original lift-type VAWT and improving the characteristics of the lift-drag combined VAWT. The static characteristic is one of the important starting characteristics of the wind turbine. The rapid development of computational fluid dynamics has laid a solid material foundation for VAWT. Thus the static characteristics of the LDCS with different numbers of blades were investigated by conducting numerical simulation and wind tunnel tests. The results demonstrated that the static torque coefficient of LDCS increased significantly with the increased incoming wind speed. The average value of the static torque coefficient also increased significantly. This study can provide guidelines for the research of lift-drag combined wind turbines.
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