Damage index analysis of prefabricated segmental bridge columns under cyclic loading

Abstract The damage index is usually applied to evaluate the damage states of bridge structures, which is the basis of structural fragility study. The present study investigates the seismic damage index of the prefabricated segmental bridge columns (PSBC) under cyclic loading by theoretical and numerical analysis. Based on the previous pseudo-static experiments, different damage states characteristics of the monolithic cast-in-place bridge columns (MCBC) and the PSBC are discussed and analyzed to propose the limit-state capacities for each damage state of the PSBC. The limit-state capacities include four parameters: compressive strain of concrete, the tensile strain of steel, the prestress level and the residual displacement. Two finite element models of the PSBC are developed by OpenSees to carry on numerical analysis. Using the numerical results, the damage indexes for the PSBCs are obtained based on the limit-state capacities obtained above. The results indicate that the numerical results show good agreement with the experimental results of the bridge columns. The damage index formula of the PSBC, derived in this study, is reasonable and can be further applied. The maximum error between the proposed damage index and that obtained in the verified case is 20.3%. The proposed method in this paper for developing the damage index of the PSBC can be used in the seismic vulnerability analysis assessment of the bridge structures with prefabricated segmental columns.</div

Crack and mechanical behavior of CFRP plate-reinforced bridge roofs under high temperature with different anchoring measures

Abstract This paper investigates the crack and mechanical behavior of CFRP plate-reinforced bridge roof under high temperature with different anchoring measures. Six CFRP-reinforced test beams with different anchoring schemes were designed and constructed. The beam specimens, after the high temperature effects, were tested under four-point bending loads. The crack propagation, beam deflection, mid-span strain and the damage modes were observed and recorded until failure. The stiffness variation and the debonding failure mechanism of the test beams were comparatively investigated. The results indicate that the debonding bearing capacity of the specimens can be improved by the additional anchoring measures. The concrete shrinkage at the crack and the average crack spacing are more effectively reduced, when the additional anchoring measures are placed at the mid-span and the support position. In addition, a theoretical model is proposed for calculating the intermediate crack debonding bearing capacity. Based on the comparative analysis of various models and test results, it is shown that the proposed model could accurately calculate the intermediate crack debonding bearing capacity of the test specimens.</div

Interfacial bond-slip relationship between Carbon Fiber Reinforced Polymer Plate and Concrete after High Temperature of Asphalt Paving Construction

Abstract The bond-slip relationship of Carbon Fiber Reinforced Polymer (CFRP) plate-concrete after the influence of high temperature action of Stone Mastic Asphalt (SMA) paving was investigated in this article. Two groups of double shear specimens with different bonding length were designed and tested. Based on the test results, the failure modes of specimens, the strain distribution and the shear stress of CFRP-concrete interface were analyzed. Considering the influence of high temperature, the interfacial bond-slip constitutive model of CFRP plate and concrete after high temperature action of SMA paving construction was proposed. The proposed model can reflect the nonlinearity and interface softening behaviour of the CFRP plate-concrete interface constitutive relationship under special environment. Through the comparative study of exixting constitutive models, the interface bond-slip constitutive model proposed in this paper considers the effect of high temperature and has good agreement with the test results.</div

A study of feature importance for king salmon health classification with feature selection

AbstractKing salmon is important for aquaculture in New Zealand, contributing significant economic value. Fish health is a priority for the industry, and the change in the health status of king salmon needs to be accurately detected at the earliest possible stage. Many factors affect the health of king salmon, such as temperature. Identifying the key features that influence health prediction is a crucial step toward achieving this goal. This study utilizes trial data collected by the Cawthron Institute, which includes diverse information on king salmon, such as blood biochemistry and hematology. We explore the data by employing statistical methods and feature selection techniques in machine learning to identify the most relevant features for king salmon health prediction, aiming to classify individuals as healthy or unhealthy with a small number of features. The results show that although the most efficient feature selection techniques on different datasets vary, overall, feature selection approaches can successfully identify relevant and informative features for king salmon health classification. Through the incorporation of a few selected features, the learned classifiers could still achieve statistically equal or better classification performance. This study not only contributes to the understanding of the health indicators of king salmon but also provides crucial insights into health prediction, which will be beneficial to the improvement of the health of king salmon, leading to the development of more effective management strategies for aquaculture

Programmable Entropy-Driven Circuit-Cascaded Self-Feedback DNAzyme Network for Ultra-Sensitive Fluorescence and Photoelectrochemical Dual-Mode Biosensing

Inspired by natural DNA networks, programmable artificial DNA networks have become an attractive tool for developing high-performance biosensors. However, there is still a lot of room for expansion in terms of sensitivity, atom economy, and result self-validation for current microRNA sensors. In this protocol, miRNA-122 as a target model, an ultrasensitive fluorescence (FL) and photoelectrochemical (PEC) dual-mode biosensing platform is developed using a programmable entropy-driven circuit (EDC) cascaded self-feedback DNAzyme network. The well-designed EDC realizes full utilization of the DNA strands and improves the atomic economy of the signal amplification system. The unique and rational design of the double-CdSe quantum-dot-released EDC substrate and the cascaded self-feedback DNAzyme amplification network significantly avoids high background signals and enhances sensitivity and specificity. Also, the enzyme-free, programmable EDC cascaded DNAzyme network effectively avoids the risk of signal leakage and enhances the accuracy of the sensor. Moreover, the introduction of superparamagnetic Fe3O4@SiO2-cDNA accelerates the rapid extraction of E2-CdSe QDs and E3-CdSe QDs, which greatly improves the timeliness of sensor signal reading. In addition to the strengths of linear range (6 orders of magnitude) and stability, the biosensor design with dual signal reading makes the test results self-confirming

Potential-Modulated Electrochemiluminescence of Carbon Nitride Nanosheets for Dual-Signal Sensing of Metal Ions

As an emerging semiconductor, graphite-phase polymeric carbon nitride (GPPCN) has drawn much attention not only in photocatalysis but also in optical sensors such as electrochemiluminescence (ECL) sensing of metal ions. However, when the concentrations of interfering metal ions are several times higher than that of the target metal ion, it is almost impossible to distinguish which metal ion changes the ECL signals in real sample detection. Herein, we report that the dual-ECL signals could be actuated by different ECL reactions merely from GPPCN nanosheets at anodic and cathodic potentials, respectively. Interestingly, the different metal ions exhibited distinct quenching/enhancement of the ECL signal at different driven potentials, presumably ascribed to the diversity of energy-level matches between the metal ions and GPPCN nanosheets and catalytic interactions of the intermediate species in ECL reactions. On this basis, without any labeling and masking reagents, the accuracy and reliability of sensors based on the ECL of GPPCN nanosheets toward metal ions were largely improved; thus, the false-positive result caused by interferential metal ions could be effectively avoided. As an example, the proposed GPPCN ECL sensor with a detection limit of 1.13 nM was successfully applied for the detection of trace Ni²⁺ ion in tap and lake water

Reversible Assembly of Graphitic Carbon Nitride 3D Network for Highly Selective Dyes Absorption and Regeneration

Responsive assembly of 2D materials is of great interest for a range of applications. In this work, interfacial functionalized carbon nitride (CN) nanofibers were synthesized by hydrolyzing bulk CN in sodium hydroxide solution. The reversible assemble and disassemble behavior of the as-prepared CN nanofibers was investigated by using CO₂ as a trigger to form a hydrogel network at first. Compared to the most widespread absorbent materials such as active carbon, graphene and previously reported supramolecular gel, the proposed CN hydrogel not only exhibited a competitive absorbing capacity (maximum absorbing capacity of methylene blue up to 402 mg/g) but also overcame the typical deficiencies such as poor selectivity and high energy-consuming regeneration. This work would provide a strategy to construct a 3D CN network and open an avenue for developing smart assembly for potential applications ranging from environment to selective extraction

Metal-Free All-Carbon Nanohybrid for Ultrasensitive Photoelectrochemical Immunosensing of alpha-Fetoprotein

C₆₀ can accept up to six electrons reversibly and show exceptional light absorption over the entire UV–vis spectrum, making it a potential photoactive probe for photoelectrochemical (PEC) bioassay. However, few successful works have been reported to apply fullerenes in PEC biosensing, partially because of the low electronic conductivity and poor interfacial interactions with targeted biomolecules. Herein, we report the addressing of these two obstacles by coupling high conductive graphite flake (Gr), graphene oxide (GO) with sufficient oxygen-containing functional groups, and an alkylated C₆₀ (AC₆₀) into a metal-free all-carbon nanohybrid (AC₆₀-Gr-GO) via harnessing delicate noncovalent interactions among them through a facile mechanical grinding. It was revealed that the as-obtained AC₆₀-Gr-GO nanohybrid not only showed conspicuous enhancement of photocurrent up to 35 times but also offered rich anchors for bioconjugation. With detection of alpha-fetoprotein as an example, the AC₆₀-Gr-GO based PEC immunosensor demonstrated a broad linear detection range (1 pg·mL^–1 to 100 ng·mL^–1) and a detection limit as low as 0.54 pg·mL^–1, superior/competitive to PEC immunosensors for AFP in previous reports. By a proper reinforcement in conductivity and biointerface engineering, this work may provide a new way to use fullerenes as photoactive materials in more general PEC biosensing

Chemically Modulated Carbon Nitride Nanosheets for Highly Selective Electrochemiluminescent Detection of Multiple Metal-ions

Chemical structures of two-dimensional (2D) nanosheet can effectively control the properties thus guiding their applications. Herein, we demonstrate that carbon nitride nanosheets (CNNS) with tunable chemical structures can be obtained by exfoliating facile accessible bulk carbon nitride (CN) of different polymerization degree. Interestingly, the electrochemiluminescence (ECL) properties of as-prepared CNNS were significantly modulated. As a result, unusual changes for different CNNS in quenching of ECL because of inner filter effect/electron transfer and enhancement of ECL owing to catalytic effect were observed by adding different metal ions. On the basis of this, by using various CNNS, highly selective ECL sensors for rapid detecting multiple metal-ions such as Cu²⁺, Ni²⁺, and Cd²⁺ were successfully developed without any labeling and masking reagents. Multiple competitive mechanisms were further revealed to account for such enhanced selectivity in the proposed ECL sensors. The strategy of preparing CNNS with tunable chemical structures that facilely modulated the optical properties would open a vista to explore 2D carbon-rich materials for developing a wide range of applications such as sensors with enhanced performances

Simultaneous Unlocking Optoelectronic and Interfacial Properties of C₆₀ for Ultrasensitive Immunosensing by Coupling to Metal–Organic Framework

Due to exceptional electron-accepting ability, light-absorption, and a delocalized conjugated structure, buckminsterfullerene (C60) has attracted fascinating interest in the field of organic solar cells. However, poor delocalization and accumulation of electrons for pristine C60 in physiological aqueous solution and difficulties in conjugation with biomolecules limit its extended photovoltaic applications in bioassay. Herein, we reported the noncovalent coupling of C60 to an electronically complementary porphyrin-derived metal–organic framework (PCN-224) with carboxyl-group terminals. Such assembly not only offered a friendly interface for bioconjugation but also resulted in a long-range ordering C60@PCN-224 donor–acceptor system that demonstrated an unprecedented photocurrent enhancement up to 10 times with respect to each component. As an example, by further cooperating with Nanobodies, the as-prepared C60@PCN-224 was applied to a photoelectrochemical (PEC) immunosensor for S100 calcium-binding protein B with by far the most promising detection activities. This work may open a new venue to unlock the great potential of C60 in PEC biosensing with excellent performances