Optimal Time Frequency Fusion Symmetric Dot Pattern Bearing Fault Feature Enhancement and Diagnosis.

Regarding the difficulty of extracting the acquired fault signal features of bearings from a strong background noise vibration signal, coupled with the fact that one-dimensional (1D) signals provide limited fault information, an optimal time frequency fusion symmetric dot pattern (SDP) bearing fault feature enhancement and diagnosis method is proposed. Firstly, the vibration signals are transformed into two-dimensional (2D) features by the time frequency fusion algorithm SDP, which can multi-scale analyze the fluctuations of signals at minor scales, as well as enhance bearing fault features. Secondly, the bat algorithm is employed to optimize the SDP parameters adaptively. It can effectively improve the distinctions between various types of faults. Finally, the fault diagnosis model can be constructed by a deep convolutional neural network (DCNN). To validate the effectiveness of the proposed method, Case Western Reserve University's (CWRU) bearing fault dataset and bearing fault dataset laboratory experimental platform were used. The experimental results illustrate that the fault diagnosis accuracy of the proposed method is 100%, which proves the feasibility and effectiveness of the proposed method. By comparing with other 2D transformer methods, the experimental results illustrate that the proposed method achieves the highest accuracy in bearing fault diagnosis. It validated the superiority of the proposed methodology.

Bearing-Fault-Feature Enhancement and Diagnosis Based on Coarse-Grained Lattice Features.

In view of the frequent failures occurring in rolling bearings, the strong background noise present in signals, weak features, and difficulties associated with extracting fault characteristics, a method of enhancing and diagnosing rolling bearing faults based on coarse-grained lattice features (CGLFs) is proposed. First, the vibrational signals of bearings are subjected to adaptive filtering to eliminate background noise. Second, frequency-domain transformation is performed, and a coarse-grained approach is used to continuously segment the spectrum. Within each segment, amplitude-enhancement operations are executed, transforming the data into a CGLF graph that enhances fault characteristics. This graph is then fed into a Swin Transformer-based pattern-recognition network. Third and finally, a high-precision fault diagnosis model is constructed using fully connected layers and Softmax, enabling the diagnosis of bearing faults. The fault recognition accuracy reaches 98.30% and 98.50% with public datasets and laboratory data, respectively, thereby validating the feasibility and effectiveness of the proposed method. This research offers an efficient and feasible fault diagnosis approach for rolling bearings.

Gold nanocluster-based ratiometric fluorescence immunoassay for broad-spectrum screening of five eugenols.

BACKGROUND: Eugenol compounds (EUGs), which share chemical similarities with eugenol, belong to a group of phenolic compounds primarily found in clove oil. They are highly valued by fish dealers due to their exceptional anesthetic properties, playing a crucial role in reducing disease incidence and mortality during the transportation of live fish. Despite their widespread use, the safety of EUGs remains a contentious topic, raising concerns about the safety of aquatic products. This underscores the need for efficient and sensitive analytical methods for detecting EUGs. RESULTS: Nanomaterial-based ratiometric fluorescence immunoassay has gained increasing attention due to its integration of the immunoassay's excellent specificity and compatibility for high-throughput analysis, coupled with the exceptional sensitivity and anti-interference capabilities of ratiometric fluorescence assays. In this study, we developed a sensitive ratiometric fluorescence immunoassay for screening five EUGs. This method employs a broad-specificity monoclonal antibody (mAb) as a recognition reagent, selective for five EUGs. It leverages the horseradish peroxidase (HRP)-triggered formation of fluorescent 2,3-diaminophenazine (DAP) and the quenching of fluorescent gold clusters (Au NCs) for detection. The assay's detection limits for eugenol, isoeugenol, eugenol methyl eugenol, methyl isoeugenol, and acetyl isoeugenol in tilapia fish and shrimp were found to be 9.8/19.5 µg/kg, 0.11/0.22 µg/kg, 19/36 Tilapia ng/kg, 8/16 ng/kg, and 3.0/6.1 µg/kg, respectively. Furthermore, when testing spiked Tilapia fish and shrimp samples, recoveries ranging from 84.1 to 111.9 %, with the coefficients of variation staying below 7.1 % was achieved. SIGNIFICANCE: This work introduces an easy-to-use, broad-specificity, and highly sensitive method for the screening of five EUGs at a pg/mL level, which not only provides a high-throughput strategy for screening eugenol-type fish anesthetics in aquatic products, but also can serve as a benchmark for developing immunoassays for other small molecular pollutants, rendering potent technological support for guarding food safety and human health.

De novo synthesis of a novel hapten and development of a monoclonal antibody-based immunoassay for the detection of dichlorvos and trichlorfon.

The absence of high-affinity antibodies has hindered the development of satisfactory immunoassays for dichlorvos (DDVP) and trichlorfon (TCP), two highly toxic organophosphorus pesticides. Herein, the de novo synthesis of a novel anti-DDVP hapten was introduced. Subsequently, a specific anti-DDVP monoclonal antibody (Mab) was produced with satisfying affinity to DDVP (IC50: 12.4 ng mL-1). This Mab was highly specific to DDVP, and TCP could readily convert into DDVP under mild alkaline conditions. Leveraging this insight, an indirect competitive ELISA was successfully developed for simultaneous detection of DDVP and TCP. The limit of detection in rice, cabbage and apple for DDVP /TCP was found to be 12.1/14.6 µg kg-1, 7.3/8.8 µg kg-1 and 6.9/8.3 µg kg-1, respectively. This study not only provides an effective strategy for producing a high-quality anti-DDVP Mab but also affords a reliable and cost-effective tool suitable for high-throughput detection of DDVP and TCP in food samples.

Development of broad-spectrum immunoassay with monoclonal antibody to detect five eugenols and study of their molecular recognition mechanism.

In this study, three eugenol fragment-containing haptens were synthesized, and a monoclonal antibody (mAb) selective for five commonly-found eugenol compounds (EUGs, i.e., eugenol, isoeugenol, methyl eugenol, methyl isoeugenol, and acetyl isoeugenol) was obtained. Based on this mAb, a broad-spectrum indirect competitive ELISA for high-throughput detection of five EUGs was developed. The detection limits for eugenol, isoeugenol, methyl eugenol, methyl isoeugenol and acetyl isoeugenol in both tilapia and shrimp samples were 25.3/ 50.6 µg/kg, 0.075/0.15 µg/kg, 0.48/0.96 µg/kg, 0.16/0.32 µg/kg, and 18.16/36.32 µg/kg, respectively. The recoveries for five EUGs ranged from 80.4 to 114.0 % with a coefficient of variation less than 11.5 %. Moreover, homology modelling and molecular docking were conducted to elucidate the interactions mechanism of mAb-EUGs. The work provides a promising tool for high-throughput screening of EUGs in aquatic products, which can serve as a benchmark for designing haptens and developing immunoassays for other small molecules.

Controllable formation of polydopamine on carbon dots for ultrasensitive detection of alkaline phosphatase and ratiometric fluorescence immunoassay of benzocaine.

Sensing alkaline phosphatase (ALP) activity with high sensitivity and accuracy is critical for both ALP-related health and food safety supervision and the development of ALP-triggered immunoassay platforms. Herein, an ultrasensitive ratiometric fluorescence (RF) sensing system based on the controllable formation of luminescent polydopamine and efficient quenching of carbon dots was proposed for the ALP activity assay, achieving quantitative detection in the range of 0.01-100 mU/L. Furthermore, this RF sensing system was integrated with an ALP-based ELISA platform to construct an RF-ELISA for benzocaine, a potentially abused anesthetic in edible fish, and ultrasensitive assay at the level of fg/mL was realized. This ratiometric strategy-based platform effectively shields various interferences through the self-calibration effect, thus providing more accurate and reliable quantification results. This study not only offers an efficient method for ultratrace detection of ALP and benzocaine but also proposes a universal platform for ultrasensitive detection of diverse targets in food analysis by replacing the recognition unit.

Ratiometric Fluorescence Immunoassay Based on MnO2 Nanoflakes for Sensitive and Accurate Detection of Tricaine.

Tricaine is a common anesthetic used in the long-distance transport of live fish. Recently, its negative impact on human health has aroused extensive concern. Thus, rapid and reliable techniques for tricaine residue analysis are essential to ensuring the quality of aquatic products. Herein, a specific anti-tricaine monoclonal antibody (Mab) was prepared. Then, a sensitive and robust ratiometric fluorescence ELISA (RF-ELISA) was constructed for detecting tricaine based on two MnO2 nanoflake-mediated (MnO2 NFs) fluorogenic reactions. In the RF-ELISA protocol, MnO2 NFs with oxidase-like activity can trigger the formation of fluorescent 2,3-diaminophenazine (oxOPD) with an emissive peak at 570 nm from non-fluorescent o-phenylenediamine (OPD), while ascorbic acid (AA) can decompose MnO2 NFs to lose their oxidase-mimicking activity, which is accompanied by the oxidation of AA into dehydroascorbic acid (DHAA). The subsequent reaction between the generated DHAA and OPD will result in the production of 3-(1,2-dihydroxy ethyl)furo[3,4-b]quinoxalin-1(3H)-on (DFQ), which has a potent emission peak at 445 nm. By virtue of the alkaline phosphatase (ALP) labeled on the antibody, which can catalyze the production of AA from ascorbic acid 2-phosphate (AAP), the concentration of tricaine can be linked to the variation of the RF signal (F445/F570) via a competitive immunoreaction. After optimization, RF-ELISA displayed a detection limit (LOD) of 0.28 ng/mL toward tricaine (in buffer solution), which was 376-fold lower than that of the traditional colorimetric ELISA. For practical application, the LODs of RF-ELISA for tricaine detection in shrimp and tilapia samples were determined to be 2.8 and 5.6 ng/g, respectively. Recoveries for spiked shrimp and tilapia samples, as well as the validation data from LC-MS/MS, showed that RF-ELISA exhibited good accuracy, precision, and reliability. This RF-ELISA protocol opened up new ways for tricaine and other-target analyses in food safety detection.

Oil spill identification in X-band marine radar image using K-means and texture feature.

Marine oil pollution poses a serious threat to the marine ecological balance. It is of great significance to develop rapid and efficient oil spill detection methods for the mitigation of marine oil spill pollution and the restoration of the marine ecological environment. X-band marine radar is one of the important monitoring devices, in this article, we perform the digital X-band radar image by "Sperry Marine" radar system for an oil film extraction experiment. First, the de-noised image was obtained by preprocessing the original image in the Cartesian coordinate system. Second, it was cut into slices. Third, the texture features of the slices were calculated based on the gray-level co-occurrence matrix (GLCM) and K-means method to extract the rough oil spill regions. Finally, the oil spill regions were segmented using the Sauvola threshold algorithm. The experimental results indicate that this study provides a scientific method for the research of oil film extraction. Compared with other methods of oil spill extraction in X-band single-polarization marine radar images, the proposed technology is more intelligent, and it can provide technical support for marine oil spill emergency response in the future.

An Underwater Positioning System for UUVs Based on LiDAR Camera and Inertial Measurement Unit.

Underwater positioning presents a challenging issue, because of the rapid attenuation of electronic magnetic waves, the disturbances and uncertainties in the environment. Conventional methods usually employed acoustic devices to localize Unmanned Underwater Vehicles (UUVs), which suffer from a slow refresh rate, low resolution, and are susceptible to the environmental noise. In addition, the complex terrain can also degrade the accuracy of the acoustic navigation systems. The applications of underwater positioning methods based on visual sensors are prevented by difficulties of acquiring the depth maps due to the sparse features, the changing illumination condition, and the scattering phenomenon. In the paper, a novel visual-based underwater positioning system is proposed based on a Light Detection and Ranging (LiDAR) camera and an inertial measurement unit. The LiDAR camera, benefiting from the laser scanning techniques, could simultaneously generate the associated depth maps. The inertial sensor would offer information about its altitudes. Through the fusion of the data from multiple sensors, the positions of the UUVs can be predicted. After that, the Bundle Adjustment (BA) method is used to recalculate the rotation matrix and the translation vector to improve the accuracy. The experiments are carried out in a tank to illustrate the effects and accuracy of the investigated method, in which the ultra-wideband (UWB) positioning system is used to provide reference trajectories. It is concluded that the developed positioning system is able to estimate the trajectory of UUVs accurately, whilst being stable and robust.

A high-resolution colorimetric immunoassay for tyramine detection based on enzyme-enabled growth of gold nanostar coupled with smartphone readout.

In this work, a specific monoclonal antibody against tyramine was produced based on a new hapten design. Then, we developed a high-resolution multicolor colorimetric immunoassay for tyramine based on this antibody by integrating enzyme-induced multicolor generation with smartphone-assistant signal readout. The multicolor generation is due to the shift of the local surface plasmon resonance band of gold nanostructure controlled by alkaline phosphatase-induced the growth of gold nanostars. Quantitative detection of tyramine was achieved via analyzing the red/blue channel values of assay solution's image taken by a smartphone with the support of a color recognizer application. The limit of detection of this immunoassay for tyramine detection in beef, pork and yoghurt was 19.7 mg/kg or L. The average recoveries were between 83 % and 103 %., and the results were validated by high performance liquid chromatography to be reliable. Overall, this developed immunoassay provides a promising platform for on-site detection of tyramine.

Prussian blue nanoparticles-enabled sensitive and accurate ratiometric fluorescence immunoassay for histamine.

Herein, a nanozyme-mediated ratiometric fluorescence immunoassay for histamine (HA) has been developed. Prussian blue nanoparticles (PBNPs) with outstanding peroxidase-like activity were labelled with goat anti-mouse IgG via a facile electrostatic adsorption to yield the nanozyme-antibody conjugate which acted as a bridge to link the ratiometric fluorescence readout with HA concentration. As substrate, o-phenylenediamine (OPD) was oxidized into 2,3-diaminophenazine (oxOPD) by H2O2 under the catalysis of PBNPs, producing a novel emission at 570 nm and quenching the fluorescence of carbon dots (CDs) at 450 nm simultaneously. Under optimal conditions, the ratio of fluorescence intensity at 570 nm and 450 nm (I570/I450) linearly correlated with HA concentration ranging from 1.6 ng/mL to 125 µg/mL, with a detection limit (LOD) of 1.2 ng/mL. In addition, analytical performances including specificity, accuracy and applicability were evaluated, which revealed that this ratiometric fluorescence immunoassay affords an effective platform for sensitive and accurate detection of HA.

Hydrographic data inspection and disaster monitoring using shipborne radar small range images with electronic navigation chart.

Shipborne radars cannot only enable navigation and collision avoidance but also play an important role in the fields of hydrographic data inspection and disaster monitoring. In this paper, target extraction methods for oil films, ships and coastlines from original shipborne radar images are proposed. First, the shipborne radar video images are acquired by a signal acquisition card. Second, based on remote sensing image processing technology, the radar images are preprocessed, and the contours of the targets are extracted. Then, the targets identified in the radar images are integrated into an electronic navigation chart (ENC) by a geographic information system. The experiments show that the proposed target segmentation methods of shipborne radar images are effective. Using the geometric feature information of the targets identified in the shipborne radar images, information matching between radar images and ENC can be realized for hydrographic data inspection and disaster monitoring.

Modulating Linker Composition of Haptens Resulted in Improved Immunoassay for Histamine.

Histamine (HA) is an important food contaminant generated during food fermentation or spoilage. However, an immunoassay for direct (derivatization free) determination of HA has rarely been reported due to its small size to induce the desired antibodies by its current hapten-protein conjugates. In this work, despite violating the classical hapten design criteria which recommend introducing a linear aliphatic (phenyl free) linker into the immunizing hapten, a novel haptens, HA-245 designed and synthesized with a phenyl-contained linker, exhibited significantly enhanced immunological properties. Thus, a quality-improved monoclonal antibody (Mab) against HA was elicited by its hapten-carrier conjugates. Then, as the linear aliphatic linker contained haptens, Hapten B was used as linker-heterologous coating haptens to eliminate the recognition of linker antibodies. Indirect competitive ELISA (ic-ELISA) was developed with a 50% inhibition concentration (IC50) of 0.21 mg/L and a limit of detection (LOD) of 0.06 mg/L in buffer solution. The average recoveries of HA from spiked food samples for this ic-ELISA ranged from 84.1% and 108.5%, and the analysis results agreed well with those of referenced LC-MS/MS. This investigation not only realized derivatization-free immunoassay for HA, but also provided a valuable guidance for hapten design and development of immunoassay for small molecules.

Detecting community structures in networks by label propagation with prediction of percolation transition.

Though label propagation algorithm (LPA) is one of the fastest algorithms for community detection in complex networks, the problem of trivial solutions frequently occurring in the algorithm affects its performance. We propose a label propagation algorithm with prediction of percolation transition (LPAp). After analyzing the reason for multiple solutions of LPA, by transforming the process of community detection into network construction process, a trivial solution in label propagation is considered as a giant component in the percolation transition. We add a prediction process of percolation transition in label propagation to delay the occurrence of trivial solutions, which makes small communities easier to be found. We also give an incomplete update condition which considers both neighbor purity and the contribution of small degree vertices to community detection to reduce the computation time of LPAp. Numerical tests are conducted. Experimental results on synthetic networks and real-world networks show that the LPAp is more accurate, more sensitive to small community, and has the ability to identify a single community structure. Moreover, LPAp with the incomplete update process can use less computation time than LPA, nearly without modularity loss.