The behavior of fiber reinforced polymer (FRP) composites at high temperature is a critical issue that needs to be clearly understood for their structural uses in civil engineering. However, due to technical difficulties during testing at high temperature, limited experimental investigations have been conducted regarding the thermal behavior of basalt fiber reinforced polymer (BFRP) composites, especially for the in-plane shear modulus of BFRP laminates. To this end, both an analytical derivation and an experimental program were carried out in this work to study the in-plane shear modulus of BFRP laminates. After the analytical derivation, the in-plane shear modulus was investigated as a function of the elastic modulus in different directions (0°, 45° and 90° of the load-to-fiber angle) and Poisson’s ratio in the fiber direction. To obtain the in-plane shear modulus, the four parameters were tested at different temperatures from 20 to 250 °C. A novel non-contacting digital image correlation (DIC) sensing system was adopted in the high-temperature tests to measure the local strain field on the FRP samples. Based on the test results, it was found that the elastic moduli in different directions were reduced to a very low level (less than 20%) from 20 to 250 °C. Furthermore, the in-plane shear modulus of BFRP at 250 °C was only 3% of that at 20 °C.

An iron-based shape memory alloy (Fe-SMA) can be used to conveniently apply prestress strengthening via a heating and cooling procedure. Material-level tests demonstrated that prestress of Fe-SMAs is sensitive to mechanical and thermal loading. Durability of steel structures strengthened by Fe-SMAs when subjected to harsh service conditions, such as coupled thermomechanical cycles is not fully understood. In this study, high-cycle fatigue tests were conducted on damaged steel plates retrofitted with Fe-SMA strips. Four temperature scenarios were adopted: room temperature (RT), a low temperature (LT) of $-20°\mathrm{C}$ , a high temperature (HT) of 60°C, and a cyclic temperature (CT) from $-20°\mathrm{C}$ to 60°C. Results showed that regardless of temperature variation, the Fe-SMA presented reliable repairing effects on steel plates, of which, the fatigue life was 2.1–3.5 times larger than that of the unstrengthened samples. The difference in coefficients of thermal expansion (CTEs) between the Fe-SMA and steel, as well as loss of prestress of the Fe-SMA due to fatigue and thermal loading, both affected the fatigue performance of the retrofitted specimens.

Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network (CaSCN), winner-take-all and cortex–subcortex covariance network (WTA-CSSCN), and modulation analysis of structural covariance network (MOD-SCN) have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface (GUI) toolkit of brain structural covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily.