Complex Environmental Conditions Research Articles

Robust Damage Detection and Localization Under Complex Environmental Conditions Using Singular Value Decomposition-based Feature Extraction and One-dimensional Convolutional Neural Network

Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions (EOC), which are inevitable in the normal inspection of civil and mechanical structures. This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network (1D-CNN). After singular value decomposition-based feature extraction processing, a temporal robust damage index (TRDI) is extracted, and the effect of EOCs is well removed. Hence, even for the signals with a very large temperature-varying range and low signal-to-noise ratios (SNRs), the final damage detection and localization accuracy retain perfect 100%. Verifications are conducted on two different experimental datasets. The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises, and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20°C to 60°C. It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly, showing great potential for application in complex and unknown EOC.

Humidity sensitivity reducing of moisture swing adsorbents by hydrophobic carrier doping for CO2 direct air capture

The application of quaternary ammonium-based moisture-swing adsorbent provides an effective strategy for direct air capture (DAC) with low energy consumption of regeneration. This study optimized a fabrication method of shaped adsorbents and a hydrophobicity regulation method by doping polyvinylidene difluoride (PVDF). Characterization of the shaped adsorbents showed a desirable surface area and pore structure. Experiments of CO2 adsorption revealed that the adsorbents exhibited excellent CO2 adsorption capacity (∼0.90 mmol/g) in relative humidity (RH) range of 20 ∼ 85% was enhanced by 160% of that before doping. Meanwhile, a high CO2 adsorption rate (with a half-time of 3.6 ∼ 3.82 min) at 84.7% RH was displayed. The optimal doping ratio of PVDF was found to be 25% (QAR-25% PVDF). It can effectively release CO2 with 100% RH, and heat assistance (<60 °C) can be considered for optimal results. QAR-25% PVDF exhibited a cyclic capacity of 0.90 mmol/g after ten cycles, demonstrating its stability and reusability. DFT and microscopic characterization revealed the key role of C-F bond in promoting the hydrophobicity of adsorbents. Meanwhile, the isotherm of H2O/CO2 adsorption illustrated that doping PVDF could effectively reduce the humidity sensitivity of shaped adsorbents and improve CO2 adsorption rate significantly. Among DAC adsorbents reported previously, the adsorbents developed in this study showed higher functional group efficiency (ηQA = 0.89) at high humidity conditions. The fabrication method of shaped adsorbent provides a viable strategy for its large-scale deployment. Doping hydrophobic carriers into the adsorbent material is a simple yet effective way to reduce its humidity sensitivity, enabling it to better adapt to complex environmental conditions.

The Design and Simulation of Associated Protection for Low Voltage Shore-to-ship Power Supply System in Inland Port

Due to the complex environmental conditions of inland ports, it is of great significance to adopt associated protection to ensure the safe and reliable operation of the shore-to-ship power supply system. To accurately simulate the operating conditions of the shore-to-ship power supply system, the simulation model of the ship power system is established completely. According to the characteristics of the inland port, the simulation model of the shore-based power supply system is designed and established. Based on the established simulation model of a low voltage shore-to-ship power supply system, to meet its protection requirements of it, an associated protection method including safety interlock, under-voltage protection, and short-circuit protection is proposed. To verify the effectiveness of the associated protection, power faults are set in the shore-to-ship power supply system, and the action of the associated protection during the fault is analyzed by comparing the voltage and current waveforms of the shore-to-ship power supply system with associated protection and unprotected ones. The results show that the associated protection can effectively detect the power failures of the shore-to-ship power supply systems and take timely protection measures to ensure equipment safety.

AQUADA PLUS: Automated damage inspection of cyclic-loaded large-scale composite structures using thermal imagery and computer vision

This study develops and demonstrates a new method to locate and track multiple fatigue damages in large-scale composite structures subject to cyclic loads using thermography and computer vision. Progressive damages generate thermal features due to material friction, allowing efficient detection using passive thermography. Automated damage localization and evaluation are done by thermal image processing incorporated with thermodynamics principles. The proposed new method, AQUADA PLUS, is demonstrated on two composite wind turbine blades in which artificial defects are introduced to trigger damage growth when subject to cyclic loading. Multiple damage sites are located, tracked, and evaluated automatically despite the complex thermal background that changes considerably when the thermal videos are taken. A pioneering drone-based field test has been conducted to demonstrate the possibility of field application where complex environmental conditions and varying thermal backgrounds are present. The associated challenges are identified and the possible solutions are discussed for the further development of the proposed method toward real-world application. All original thermal videos presented in this study are shared with the public for future study.

The molybdate-binding protein ModA is required for Proteus mirabilis-induced UTI.

Proteus mirabilis is one of the pathogens commonly causing urinary tract infections (UTIs). The molybdate-binding protein ModA encoded by modA binds molybdate with high affinity and transports it. Increasing evidence shows that ModA promotes the survival of bacteria in anaerobic environments and participates in bacterial virulence by obtaining molybdenum. However, the role of ModA in the pathogenesis of P. mirabilis remains unknown. In this study, a series of phenotypic assays and transcriptomic analyses were used to study the role of ModA in the UTIs induced by P. mirabilis. Our data showed that ModA absorbed molybdate with high affinity and incorporated it into molybdopterin, thus affecting the anaerobic growth of P. mirabilis. Loss of ModA enhanced bacterial swarming and swimming and up-regulated the expression of multiple genes in flagellar assembly pathway. The loss of ModA also resulted in decreased biofilm formation under anaerobic growth conditions. The modA mutant significantly inhibited bacterial adhesion and invasion to urinary tract epithelial cells and down-regulated the expression of multiple genes associated with pilus assembly. Those alterations were not due to anaerobic growth defects. In addition, the decreased bacteria in the bladder tissue, the weakened inflammatory damage, the low level of IL-6, and minor weight change was observed in the UTI mouse model infected with modA mutant. Here, we reported that in P. mirabilis, ModA mediated the transport of molybdate, thereby affecting the activity of nitrate reductase and thus affecting the growth of bacteria under anaerobic conditions. Overall, this study clarified the indirect role of ModA in the anaerobic growth, motility, biofilm formation, and pathogenicity of P. mirabilis and its possible pathway, and emphasized the importance of the molybdate-binding protein ModA to P. mirabilis in mediating molybdate uptake, allowing the bacterium to adapt to complex environmental conditions and cause UTIs. Our results provided valuable information on the pathogenesis of ModA-induced P. mirabilis UTIs and may facilitate the development of new treatment strategies.

Reactive behaviors and mechanisms of cellulose in chemical looping combustions with iron-based oxygen carriers: An experimental combined with ReaxFF MD study

Biomass energy is one of the important and feasible renewable energy resources. Chemical looping combustion (CLC) can meet the requirements of efficient CO2 capture with low energy consumption. The combination of the two factors is intuitive and important for realizing carbon neutral energy processing and conversion. Cellulose is the component with the highest content in biomass. However, there is still a lack of clear understanding of the thermal conversion behavior and microscopic reaction mechanism of cellulose in CLC. In this work, the behaviors and mechanisms of cellulose in CLC with iron-based OCs were studied systematically based on the comprehensive technics of thermo-gravimetric analysis (TGA) experiments, kinetic models and molecular dynamic simulations. The reaction behaviors, kinetic mechanism, and complex reactive networks of cellulose under complex environmental interface conditions of CLC were revealed. Three different stages were revealed for thermal weight loss and reaction behavior of cellulose in CLC via TGA. The effects of different conversion rates and reaction stages on activation energy during CLC were described based on two model-free integration methods. The dynamic evolution of the CLC process was discussed by ReaxFF MD (reactive force field molecular dynamics) simulations. A complex reaction network of cellulose depolymerization and CO2 release in CLC was obtained.

Application and Automatic Monitoring and Analysis of Hybrid Support Structure in Ultra-DEEP Foundation Pit Engineering in the Lanzhou Area under Complex Environmental Conditions

This paper takes the deep foundation pit project of Lanzhou Hospital of Traditional Chinese Medicine as the background. The design and construction of the foundation pit is relatively difficult due to the complex environment around the pit, the dense surrounding buildings, the complex underground soil layer and the influence of groundwater on the pit. In order to detect problems in the construction process, the pit was monitored in real time through an automated monitoring system for the whole process of excavation and backfilling of the pit. The analysis of the actual monitoring data shows that: (i) the support scheme of bored pile + prestressed anchor cable support combined with concrete corner bracing can meet the design of this type of foundation pit without causing disturbance to the surrounding buildings; (ii) combined with the actual case of the influence of groundwater on the excavation process of the foundation pit, it proves that the real-time measurement by the robot can timely detect the safety hazards caused by external factors during the construction process of the foundation pit. The project is a very important one for deep pits and complex pits. This project provides a good reference case for deep foundation pits and foundation pit projects in complex environments.

Macroalgae monitoring from satellite optical images using Context-sensitive level set (CSLS) model

Automatically detecting macroalgae from optical remote sensing images has been a long-standing problem in ocean monitoring. Existing operational spectral-based techniques tend to assign a threshold to an indicator such as Normalized Difference Vegetation Index (NDVI) to determine whether or not macroalgae exists in a pixel. This thresholding scheme relies on individual pixel features and cannot address the environment variability among different images or even across one single image. To address these limitations, we develop the unsupervised classification method taking the ecological indicator of NDVI as input by exploiting a region-based level set driven by context-sensitive energy function for macroalgae detection from optical remote sensing images. Quantitative and qualitative evaluations based on satellite optical images with various imaging time and spatial resolutions (16–250 m) from GF-1, GF-4, Landsat-8, and Aqua demonstrate the effectiveness and robustness for Ulva prolifera detection. The model is proved to be superior to the traditional NDVI thresholding method and state-of-the-art level set methods in terms of higher accuracy (Kappa coefficients 0.87–0.92) and automation (without artificial threshold/parameter adjustment). Moreover, the model has the advantage of accommodating complex environmental conditions (such as different water turbidity, thin clouds and sun glint), and can be utilized for detection of Sargassum bloom. The model could facilitate the accurate extraction of macroalgae information and thus serve disaster prevention and control. It may also be used to assist high-accuracy training data preparation for supervised classification and detect the objects with obvious texture and spectral characteristics (such as oil spills) based on customized bands combination.

Study on structural damage evolution of excavated slope subjected to earthquake and rainfall using electrical resistivity measurement

Earthquake and rainfall are two major factors contributing to the slope failures. To examine the evolution of slope structural damage and the failure mechanism during the shaking and rainfall process, a model test of excavated slope subjected to earthquake and rainfall has been performed. The evolution of structural damage within the slope is considered as the changing process of porosity and crack development. The unique relation between of porosity and resistivity of unsaturated soil is utilized to reveal the spatial-temporal variation of slope structural damage by electrical resistivity measurement method. The testing results show that the shaking induced cracks appear on the surface of upper soil layer at the mid-height of slope model, and the structural damage could be both accumulated on the surface and inside the slope under seismic motion. The damaged area provides preference infiltration path for rainwater flow in the following raining process, resulting in the rapid increase of water content of slope interior. The sliding body extends and develops upwards to the slope crest under rainfall condition. The failure patten suggested by the structural damage parameter is verified by the dynamic response of slope model. The structural damage parameter using resistivity is able to show the spatial-temporal evolution of structural damage inside the slope quantitatively, and reflect the porosity change of soil under continuous earthquake and rainfall conditions. The evolution of structural damage reveals that the dynamic failure mode of excavated slope under earthquake and rainfall is the upwards-developed retrogressive sliding of upper soil layer. The evaluating method using resistivity measurement is particularly promising for field test of slope where it can be used to monitor the structural damage change of soil mass subjected to complex environment conditions.

Resistance-driven innovations in the discovery of bactericides: novel triclosan derivatives decorating isopropanolamine moiety as promising anti-biofilm agents against destructive plant bacterial diseases.

Controlling bacterial infections in plants is a major challenge owing to the appearance of resistant strains. As a physical barrier, the bacterial biofilm helps bacterial infections acquire drug resistance by enabling bacteria to accommodate complex and volatile environmental conditions and avoid bactericidal effects. Thus, developing new antibacterial agents with antibiofilm potency is imperative. A series of simple triclosan derivatives containing isopropanolamine moiety were elaborately designed and assessed for their antibacterial behavior. Bioassay results showed that some title compounds had excellent bioactivity against three destructive bacteria Xanthomonas oryzae pv. oryzae (Xoo), Xanthomonas axonopodis pv. citri (Xac) and Pseudomonas syringae pv. actinidiae (Psa). Notably, compound C8 displayed high bioactivities toward Xoo and Xac, with EC50 values were 0.34 and 2.11 μg mL-1 , respectively. In vivo trials revealed that compound C8 exhibited excellent protective activities against rice bacterial blight and citrus bacterial canker at 200 μg mL-1 , with control effectivenesses of 49.57% and 85.60%, respectively. Compound A4 had remarkably inhibitory activity toward Psa, with an EC50 value of 2.63 μg mL-1 , and demonstrated outstanding protective activity with a value of 77.23% against Psa in vivo. Antibacterial mechanisms indicated that compound C8 dose-dependently prevented biofilm formation and extracellular polysaccharide production. C8 also significantly weakened the motility and pathogenicity of Xoo. This study contributes to the development and excavation of novel bactericidal candidates with broad-spectrum antibacterial activity by targeting bacterial biofilm to control refractory plant bacterial diseases. © 2023 Society of Chemical Industry.

Optimal Design of Ski Tracks in Construction Projects: Taking the Warm-Up and Training Ski Track of the South Area in the Yanqing Competition Zone of the Beijing 2022 Winter Olympic Games as an Example

Mature civil engineering software and platforms can provide a dynamic correlated situation of the road design, generate a quick and accurate grading design in terrain model making, and, most importantly, improve the design efficiency and calculation accuracy and reduce the workload of designers in the construction project. However, the application of existing platforms in complex site engineering for the design of ski tracks has not been well developed. The design process of ski tracks requires consideration of elaborate requirements in complex environmental conditions. In this study, we aim to simplify digital elevation model (DEM) data, optimize ski track contour lines, and localize the design expression of the ski track designs based on the experience of the construction of the National Alpine Ski Center in the Yanqing Competition Zone for the Beijing 2022 Winter Olympic Games. This study examines the feasibility of the optimal digital approach combining mathematics and computer science based on the case study of the warm-up and training ski track of the south area in the Yanqing Competition Zone. This study will contribute to the optimal design of skiing tracks in construction projects and help to improve designers’ workload efficiency for the design and construction of ski tracks in the future.

A combined inverse prediction and experimental analysis for the frozen ground heat transfer in a structure foundation

This paper takes the representative buried structure in permafrost regions, a transmission line tower foundation, as the research object. An inverse prediction is conducted in a scaled-down experimental system mimicking actual heat conduction of the frozen ground in a tower foundation. In permafrost regions, global warming and the heat transfer through the buried structures bring significantly adverse thermal effects on the stability of the infrastructures. In modeling the thermal effects, it has been a challenge to determine the ground surface boundary condition and heat source strength from the buried structures due to the complex climate and environmental conditions. In this work, based on the improved model predictive inverse method with an adaptive strategy, an inverse scheme is successfully implemented to simultaneously identify the time-varying surface temperature and the time-space-dependent heat source representing the buried structures. In this scheme, an adaptive time-varying predictive model is established by the rolling update of the sensitivity response coefficients according to the predicted temperature field to overcome the influence of nonlinear characteristics in the heat transfer process. The inverse method is verified by simulation and experimental data. According to the experimental inversion results, the reconstructed temperature distribution efficiently predicts the thermal state evolution of the permafrost foundation under seasonal freezing and thawing. It is found that, under the experimental conditions, the intensified thawing and freezing are significantly severe, e.g., the increased area ratio of active layer thickness is as high as 28% after building a tower, and the depth of permafrost table ranges from about 14 mm to about 38 mm, which could be detrimental to the stability and safety of the tower foundation. This study will provide valuable guidance for risk assessments or optimizing the design and maintenance of the real tower foundation and similar buried structures.

Combining Historical, Remote-Sensing, and Photogrammetric Data to Estimate the Wreck Site of the USS Kearsarge

Colombia has hundreds of historical shipwrecks, but systematic research on this topic is scarce, which makes locating wreck sites problematic. Colombia is home to the Caribbean archipelago of San Andres, Old Providence, and Santa Catalina. Its complex environmental conditions make it a “ship trap”. On 2 February 1894, the USS Kearsarge ran aground on Roncador Cay, one of the Archipelago’s islets, and the location of the wreck site remains uncertain. Due to its role in the American Civil War, the Kearsarge is important naval heritage. Based on historical and cartographic records, orthophotographs, Landsat images, and light-detection-and-ranging (LiDAR) data, this study aimed to estimate the location of the wreck site in a Geographic Information System (GIS). Court-martial records, particularly nautical data and astronomical coordinates, were reviewed, including a study from 1894 indicating the wreck’s location on a map without coordinates. Nautical charts were also analyzed to find the Kearsarge wreck symbol. To identify the wreck site’s ordnance, logbooks and information on previous salvage efforts were examined. The analysis of nautical charts revealed a few shipwrecks, but not the Kearsarge. Historical and remote-sensing data were processed in a GIS, along with the most recent nautical chart of Roncador Cay from 2017, to obtain a possible geographical location. This resulted in coordinates, which were used to detect features associated with the USS Kearsarge in the processed data. Although the wreck was not detected, the data helped to estimate the approximate coordinates for where the wreck could be located, quantifying our degree of uncertainty.

A Visible and Near‐Infrared Light‐Fueled Omnidirectional Twist‐Bend Crawling Robot

AbstractIn recent years, although light‐driven soft actuators have attracted intense scientific attention and achieved remarkable progress, the design and construction of an intelligent robotic system with maneuverability, self‐adaptability, untethered control, and greater freedom of action, in particular the omnidirectional motion capability on a plane, remains challenging. Herein, four types of photo‐thermal fillers and an unprecedented twist‐bend actuation mode is introduced into a liquid crystal elastomer‐based soft robot. The obtained twist‐bend crawling robot not only exhibits in situ rotation, four‐way turning, and four‐way linear motion under light irradiation with four wavelength bands (520, 655, 808, and 980 nm), but also demonstrates the ability to avoid obstacles in complex geographical environments. This work may bring a new perspective for fabrication and development of soft robots that can adapt to dynamic and complex environmental conditions.

Design and Application of an Airborne Radioactivity Survey System Based on Unmanned Aerial Vehicle

In this study, an airborne radioactivity survey (ARS) system based on an unmanned helicopter platform was designed to satisfy the requirements of geological exploration and environmental radiation monitoring under complex environmental conditions. The system is composed of an unmanned aerial vehicle platform, airborne equipment, and a ground control station, with both NaI(Tl) and CeBr3 crystals as detectors to meet the energy resolution and detection efficiency requirements of airborne radioactivity measurement. The designed ARS system is stable and reliable through the field flight test, and the measurement results are consistent with the existing data and can be widely used in fields such as large-scale uranium resource exploration, nuclear accident emergency monitoring, and environmental radiation investigation.

Causal interpretation for groundwater exploitation strategy in a coastal aquifer

Machine learning models (ML), as a collection of nonparametric or semiparametric estimation methods, can successfully encode the distribution of the problems into its trainable parameters based on observation data. However, the distributions of hydrological variables may change suddenly under complex environmental conditions, leading to biased estimates when using ML models. This work is the first attempt to solve this issue using structural causal models (SCM). Specifically, two SCM were constructed based on hydrological conditions and monitoring data. Then the Propensity Score estimator and the Double Machine Learning estimator were employed to estimate the causal effects of four treatments on the mean Cl− concentration (MCL) in the coastal aquifer. The results showed that pumping groundwater from area A1 or increasing the river level directly leads to a decrease in MCL, while pumping area A3 directly leads to an increase in MCL. Moreover, MCL can be effectively controlled by cooperative-treatment strategies. Finally, two practical exploitation strategies are derived. In the planting month, it should increase groundwater pumping from area A1, limit groundwater pumping from A2, and prohibit groundwater pumping from A3. For the normal month, it is proposed to increase the height of the rubber dam to raise the river level and reduce groundwater pumping from A1 and A2.

Intelligent Urban Sensing for Gas Leakage Risk Assessment

In order to mitigate gas leakage damage, it is important to assess systematic risk of gas leakage in utility networks. In practice, leakage detection systems heavily rely on tedious and expensive human efforts, such as manually checking and assessing the risk, and thus only a very limited portion of the gas pipeline network can usually be assessed during a period of time. Therefore, it is critical to develop tools for automatically and systematically evaluating the whole gas pipeline network and revealing high-risk sites for checking in a timely fashion. To this end, in this paper, we develop an intelligent gas leakage risk assessment system based on the analysis of large-scale multi-source data, such as gas pipeline data, Point of Interests (POIs) data, and human mobility data. However, it is a non-trivial endeavor to design such a risk assessment system due to the unclear leakage mechanism, complex environmental conditions, and large size of the pipeline network. To address these challenges, both internal features of gas pipelines and external environmental features should be exploited. Specifically, we design a novel urban sensing technique to extract environmental features by analyzing human mobility data. Then, a joint learning neural network is developed to assess the leakage risk by integrating both internal and external features. Moreover, an intelligent risk assessment system is implemented and deployed for experiments in real-world scenarios. The results demonstrate the effectiveness of our system for citywide gas leakage risk assessment. Indeed, the proposed system could help to locate the potential leakage sites in a timely way.

Fully Superhydrophilic, Self-Floatable, and Multi-Contamination-Resistant Solar Steam Generator Inspired by Seaweed

• Independent floatability guarantees stable interfacial steam generation. • Complete hydration ensures superhydrophilicity and continuous water pumping. • High water affinity endows the floater with long-term multi-contamination resistance against oil spill, microbial corrosion, salt crystallization, protein adsorption, etc. • These merits allow the floater to perform stable solar evaporation from seawater or even wastewater. Highly hydrophilic materials enable rapid water delivery and salt redissolution in solar-driven seawater desalination. However, the lack of independent floatability inhibits heat localization at the air/water interface. In nature, seaweeds with internal gas microvesicles can float near the sea surface to ensure photosynthesis. Here, we have developed a seaweed-inspired, independently floatable, but superhydrophilic (SIFS) solar evaporator. It needs no extra floatation support and can simultaneously achieve continuous water pumping and heat concentration. The evaporator resists salt accumulation, oil pollution, microbial corrosion, and protein adsorption. Densely packed hollow glass microbeads promote intrinsic floatability and heat insulation. Superhydrophilic zwitterionic sulfobetaine hydrogel provides a continuous water supply, redissolves the deposited salt, and endows the SIFS evaporator with excellent anti-fouling properties. With its unprecedented anti-contamination ability, this SIFS evaporator is expected to open a new avenue for designing floatable superhydrophilic materials and solving real-world issues of solar steam generation in complex environmental conditions.

A resorufin-based fluorescent probe for hydrazine detection and its application in environmental analysis and bioimaging.

Hydrazine (N2H4) is an important industrial raw material that has been widely used in industrial production and agricultural interventions, but its widespread application also inevitably causes environmental pollution. In this study, based on resorufin, we constructed a novel "turn-on" fluorescent probe RFT for the selective detection of hydrazine under complex environmental conditions and in vivo. The probe RFT exhibited excellent stability and selectivity towards the detection of hydrazine with a low detection limit of 260 nM. In addition, RFT was successfully applied to the detection of hydrazine in environmental water samples and living cells. Most importantly, RFT could not only detect the exogenous hydrazine in zebrafish and mice, but also image and visualize the up-regulation of endogenous hydrazine induced by isoniazid in zebrafish.

Label-free dual-mode sensing platform based on target-regulated CRISPR-Cas12a activity for ochratoxin A in Morinda officinalis.

Many traditional Chinese herbs are susceptible to ochratoxin A (OTA), a potent mycotoxin, which causes serious effects on the quality of the herb and on people's health. The development of methods to detect OTA is extremely important. Most methods for detecting OTA are based on a single-signal output mode, which might be easily influenced by complex environmental conditions. In this research, by taking advantage of the cleavage of DNA by target-induced CRISPR-Cas12a activity and the difference in electrostatic force of DNA to different charge electrochemiluminescent (ECL) and electrochemical (EC) probes, a biosensor is developed for the detection of OTA. First, the CRISPR-Cas12a system consists of a well-designed crRNA, its complementary strand (also as an aptamer for OTA), and Cas12a. Without the target, this CRISPR-Cas12a system is in the "activated stage", which digests hairpin DNA on the electrode, resulting in a weak ECL signal and strong current response. With the introduction of OTA bound with the aptamer, CRISPR-Cas12a activity is inhibited ("locked stage"). Thus, hairpin DNA remained intact on the electrode, resulting in recovery of the ECL signal and attenuation of the current intensity. As a result, this label-free dual-mode sensing platform realizes an assay for OTA in Morinda officinalis. This target-regulated CRISPR-Cas12a activity-sensing platform with dual-mode output not only provides high sensitivity (due to the CRISPR-Cas12a system), but also has good anti-interference ability against complex substrates (due to dual-mode output), and exhibits a broad range of prospects for application.