Experimental Investigation on Interfacial Defect Criticality of FRP-Confined Concrete Columns.

Defects between fiber reinforced polymer (FRP) and repaired concrete components may easily come out due to misoperation during manufacturing, environmental deterioration, or impact from external load during service life. The defects may cause a degraded structure performance and even the unexpected structural failure. Different non-destructive techniques (NDTs) and sensors have been developed to assess the defects in FRP bonded system. The information of linking up the detected defects by NDTs and repair schemes is needed by assessing the criticality of detected defects. In this study, FRP confined concrete columns with interfacial defects were experimentally tested to determine the interfacial defect criticality on structural performance. It is found that interfacial defect can reduce the FRP confinement effectiveness, and ultimate strength and its corresponding strain of column deteriorate significantly if the interfacial defect area is larger than 50% of total confinement area. Meanwhile, proposed analytical model considering the defect ratio is validated for the prediction of stress⁻strain behavior of FRP confined columns. The evaluation of defect criticality could be made by comparing predicted stress⁻strain behavior with the original design to determine corresponding maintenance strategies.

Investigation of the Shear Behavior of Concrete Beams Reinforced with FRP Rebars and Stirrups Using ANN Hybridized with Genetic Algorithm.

The shear strength prediction of concrete beams reinforced with FRP rebars and stirrups is one of the most complicated issues in structural engineering applications. Numerous experimental and theoretical studies have been conducted to establish a relationship between the shear capacity and the design variables. However, existing semi-empirical models fail to deliver precise predictions due to the intricate nature of shear mechanisms. To provide a more accurate and reliable model, machine learning (ML) techniques are adopted to study the shear behavior of concrete beams reinforced with FRP rebars and stirrups. A database consisting of 120 tested specimens is compiled from the reported literature. An artificial neural network (ANN) and a combination of ANN with a genetic optimization algorithm (GA-ANN) are implemented for the development of an ML model. Through neural interpretation diagrams (NID), the critical design factors, i.e., beam width and effective depth, shear span-to-depth ratio, compressive strength of concrete, FRP longitudinal reinforcement ratio, FRP shear reinforcement ratio, and elastic modulus of FRP longitudinal reinforcement rebars and FRP stirrups, are identified and determined as input parameters of the models. The accuracy of the proposed models has been verified by comparing the model predictions with the available test results. The application of the GA-ANN model provides better statistical results (mean value Vexp/Vpre equal to 0.99, R2 of 0.91, and RMSE of 22.6 kN) and outperforms CSA S806-12 predictions by improving the R2 value by 18.2% and the RMSE value by 52.5%. Furthermore, special attention is paid to the coupling effects of design parameters on shear capacity, which has not been reasonably considered in the models in the literature and available design guidelines. Finally, an ML-regression equation considering the coupling effects is developed based on the data-driven regression analysis method. The analytical results revealed that the prediction agrees with the test results with reasonable accuracy, and the model can be effectively applied in the prediction of shear capacity of concrete beams reinforced with FRP bars and stirrups.

Aerosolization and Fluid Spillage During Phacoemulsification in Human Subjects.

BACKGROUND: Concerns had been raised for the potential hazard of SARS-CoV-2 transmissions via aerosols and fluid droplets during cataract surgeries amid the COVID-19 pandemic. This study aims to evaluate the rate of visible aerosol generation and fluid spillage from surgical wounds during phacoemulsification in human subjects. METHODS: This is a prospective consecutive interventional case series. High-resolution video captures of 30 consecutive uncomplicated phacoemulsification surgeries, performed by 3 board-certified specialists in ophthalmology, were assessed by 2 independent and masked investigators for intraoperative aerosolization and fluid spillage. Water-contact indicator tape was mounted on the base of the operating microscope, around the objective lens, to detect any fluid contact. RESULTS: No visible intraoperative aerosolization was detected in any of the cases, irrespective of different surgical practices among the surgeons with regard to wound size and position, lens fragmentation technique, power settings and means of ocular lubrication, or the different densities of cataract encountered. Large droplets spillage was noted from the paracentesis wounds in 70% of the cases. For all cases where fluid spill was detected on video, there was no fluid contact detected on the water-contact indicator tape. CONCLUSION: Visible aerosolization was not detected during phacoemulsification in our case series. Although the rate of fluid spillage was high, the lack of detectable contact with the indicator tape suggested that these large droplets posed no significant infectious risks to members of the surgical team.

Identification of Ethylene Responsive miRNAs and Their Targets from Newly Harvested Banana Fruits Using High-Throughput Sequencing.

The roles of microRNAs (miRNAs) related to ethylene response in banana fruits remain unknown because many miRNAs are differentially expressed as the fruit ripens, making the identification of ethylene-responsive miRNAs difficult. Using newly harvested banana fruits (within 5 h after harvest) as material, we found that these fruit did not ripen when treated with 5 µL/L of ethylene for 12 h at 22 °C. Two miRNA libraries were generated from newly harvested banana fruits with and without ethylene treatment and sequenced. In total, 128 known miRNAs belonging to 42 miRNA families were obtained, and 12 novel miRNAs were identified. Among them, 22 were differentially expressed in response to ethylene treatment, among which 6 known miRNAs and their putative targets were validated using qRT-PCR. These putative targets encoded proteins including GATA, ARF, DLC, and AGO, etc. KEGG and GO analyses showed that miRNAs differentially expressed in response to ethylene mainly function in the molecular and biological processes.