A shielded stripline structure made from textile materials is introduced as a wearable flexible transmission line for broadband operation. The stripline with a total height of 3.2 mm consists of a foam substrate and silver fabric conductors. For shielding purpose, the structure is truncated on its sides at a total width of 20 mm using embroidered via walls made from conductive thread. The impedance bandwidth and propagation characteristics are investigated through simulation and experiment, demonstrating that the textile stripline can work efficiently and reliably from dc to 8 GHz. Moreover, it is shown that the textile stripline is robust in terms of propagation characteristics, as even when bent up to 90° and 180° it can maintain consistent propagation properties in the whole operation band. A further advantage of the structure is the simple fabrication, arising from the low sensitivity of the structure to width and height tolerances, as well as to the accuracy of the feeding method. Finally, it is shown that the low-loss radio frequency foam substrate material can be replaced with low-cost clothing felt without significant detrimental impact on the efficiency.

Various types of scan blindness are analyzed in a single-polarized tapered-slot phased array with triangular lattice arrangement, and a scan blindness removal strategy is proposed. In the presented analysis, two types of scan blindness are observed which have not been previously reported. First, a special case of parallel plate cavity resonance is demonstrated to cause scan blindness at a fixed frequency for E-plane scanning. Second, another cause for E-plane scan blindness is extended from previous observations, by including the fundamental mode of a half-mode open waveguide. This type of leaky-wave-induced scan blindness is limited to triangular lattices and can occur at lower frequencies compared to other types of leaky-wave blindness. In the second part of this paper, parasitic notches are proposed as an effective measure to significantly improve the E-plane scanning characteristics of the considered array by reducing the magnitude of the leaky modes. As a beneficial side-effect, these parasitic notches are also proven to improve the H-plane scanning characteristics by suppressing resonances within the stripline substrate cavity of the individual tapered-slot elements. Numerical simulations and measurements performed on a 169-element array prototype validate the analysis and confirm the effectiveness of the proposed concept for scan blindness suppression.

Several different lying positions, such as lying on the left side, supine, lying on the right side and prone position, existed when healthy people fell asleep. This article explored the influence of lying positions on the shape of ECG (electrocardiograph) waveform during sleep, and then lying position classification based on ECG waveform features and random forest was achieved. By means of de-noising the overnight sleep ECG data from ISRUC website dataset, as well as extracting the waveform features, we calculated a total of 30 ECG waveform features, including 2 newly proposed features, S/R and ∠QSR. The means and significant difference level of these features within different lying positions were calculated, respectively. Then 12 features were selected for three kinds of classification schemes. The lying positions had comparatively less effect on time-limit features. QT interval and RR interval were significantly lower than that in supine ( $${\text{P}}\, \le \,0.01$$ P ≤ 0.01 ). Significant differences appeared in most of the amplitude and double-direction features. When lying on the left side, the height of P wave and T wave, QRS area and T area, the QR potential difference and ∠QSR were significantly lower than those in supine ( $${\text{P}}\, \le \,0.01$$ P ≤ 0.01 ). However, S/R was significantly greater on left than those in supine ( $${\text{P}}\, \le \,0.01$$ P ≤ 0.01 ) and on right ( $${\text{P}}\, \le \,0.05$$ P ≤ 0.05 ). The height of T wave and area under T wave were significantly higher in supine than those on right ( $${\text{P}}\, \le \,0.01$$ P ≤ 0.01 ). For the subject specific classifier, a mean accuracy of 97.17% with Cohen’s kappa statistic κ of 0.91, and AUC > 0.97 were achieved. While the accuracy and κ dropped to 63.87% and 0.32, AUC > 0.66, respectively when the subject independent classifier was considered. When subjects were lying on the left side during sleep, due to the effect of gravity on heart, the position of heart changed, for example, turned and rotated, causing changes in the vectorcardiogram of frontal plane and horizontal plane, which lead to a change in ECG. When lying on the right side, the heart was upheld by the mediastinum, so that the degree of freedom was poor, and the ECG waveform was almost unchanged. The proposed method could be used as a technique for convenient lying position classification.

In China’s heavy-haul railways, coal transportation accounts for nearly half of the total freight volume. Coal dust frequently spills from open-top wagons and accumulates on the ballast bed, which significantly undermines track stability and drainage performance. However, existing studies mainly focused on ballast fouling assessment, coal dust layers have not been systematically investigated as an independent detection target. This study proposes a rapid method for detecting coal dust thickness using high-frequency ground penetrating radar (GPR), integrating numerical modeling, advanced signal processing, and field validation to analyze the time- and frequency-domain response characteristics of coal dust layers. A finite-difference time-domain (FDTD) model was established to analyze how coal dust thicknesses and coverage lengths affect GPR time-frequency signatures. A dedicated signal processing protocol was developed to enhance coal dust feature localization. A Freight train mounted three-air-horn 2 GHz antenna was employed to conduct field experiments. Numerical results demonstrated that the proposed method achieves a thickness estimation accuracy within ±0.4 cm. Field experiments confirmed that coal dust contamination replaces the hyperbolic diffraction patterns of sleepers with continuous reflection layers, consistent with simulation findings. The proposed approach provides a novel, nondestructive, and data-driven solution for detecting coal dust contamination in freight railways, contributing to more precise and intelligent ballast maintenance strategies.

The flow behaviors under different filling pressures were observed using electrode contact method. The relationships of recorded time and related point location were analyzed and deduced in terms of the flow tendency. The flow behavior figures were plotted at different time according the relationship. It was found that the unstable flow pattern takes place because filling cross-sectional area changes abruptly from the flow behavior figures. According to energy conservation and mass conservation theory, the relationship of flow velocity and filling pressure was established. Combining this relationship and critical flow velocity, the judgment equation of critical filling pressure was achieved.

Background: The coronavirus disease 2019 (COVID-19) pandemic resulted in radical changes in many aspects of life. To deal with this, each country has implemented continuous health measures from the beginning of the outbreak. Discovering how governmental actions impacted public behaviour during the outbreak stage is the purpose of this study. Methods: This study uses a hybrid large-scale data visualisation method to analyse public behaviour (epidemic concerns, self-protection, and mobility trends), using the data provided by multiple authorities. Meanwhile, a content analysis method is used to qualitatively code the health measures of three countries with severe early epidemic outbreaks from different continents, namely China, Italy, and the United States. Eight dimensions are coded to rate the mobility restrictions implemented in the above countries. Results: (1) Governmental measures did not immediately persuade the public to change their behaviours during the COVID-19 epidemic. Instead, the public behaviour proceeded in a three-phase rule, which is typically witnessed in an epidemic outbreak, namely the wait-and-see phase, the surge phase and the slow-release phase. (2) The strictness of the mobility restrictions of the three countries can be ranked as follows: Hubei Province in China (with an average score of 8.5 out of 10), Lombardy in Italy (7.125), and New York State in the United States (5.375). Strict mobility restrictions are more likely to cause a surge of population outflow from the epidemic area in the short term, whereas the effect of mobility restrictions is positively related to the stringency of policies in the long term. Conclusion: The public showed generally lawful behaviour during regional epidemic outbreaks and blockades. Meanwhile public behaviour was deeply affected by the actions of local governments, rather than the global pandemic situation. The contextual differences between the various countries are important factors that influence the effects of the different governments’ health measures.