Synchronous Detection Research Articles

Synchronous detection of bolts looseness position and degree based on fusing electro-mechanical impedance

Looseness is the most common form of failure in bolt connections, which can cause safety accidents by reducing the rigidity of the structural connection, and the detection of bolt looseness is vital to maintain the health of the structure. However, due to the limitations of existing methods, it is difficult to detect the position of loose bolt and degree of looseness synchronously. In this study, an Electro-mechanical impedance (EMI) detection method based on fusing multi-frequency ranges was proposed. Firstly, the feasibility of bolt looseness detection based on EMI technology was analyzed through theoretical deduction; secondly, the qualitative relationship between excitation frequency and detection range was explored through finite element simulation, which provides a basis for the proposed fusing multi-frequency ranges method, and the conclusion was verified in four-bolted flange structure; finally, a detection method for bolt looseness was proposed, which uses the impedance shift as the damage index, and detect the position of loose bolt and degree of looseness synchronously by fusing EMI in multiple frequency ranges. The verification results show that the proposed method can identify the loosening status of bolts in the flange structure with high accuracy.

Deep Learning-Based Spectral Extraction for Improving the Performance of Surface-Enhanced Raman Spectroscopy Analysis on Multiplexed Identification and Quantitation.

Surface-enhanced Raman spectroscopy (SERS) has been recognized as a promising analytical technique for its capability of providing molecular fingerprint information and avoiding interference of water. Nevertheless, direct SERS detection of complicated samples without pretreatment to achieve the high-efficiency identification and quantitation in a multiplexed way is still a challenge. In this study, a novel spectral extraction neural network (SENN) model was proposed for synchronous SERS detection of each component in mixed solutions using a demonstration sample containing diquat dibromide (DDM), methyl viologen dichloride (MVD), and tetramethylthiuram disulfide (TMTD). A SERS spectra dataset including 3600 spectra of DDM, MVD, TMTD, and their mixtures was first constructed to train the SENN model. After the training step, the cosine similarity of the SENN model can achieve 0.999, 0.997, and 0.994 for DDM, MVD, and TMTD, respectively, which means that the spectra extracted from the mixture are highly consistent with those collected by the SERS experiment of the corresponding pure samples. Furthermore, a convolutional neural network model for quantitative analysis is combined with the SENN, which can simultaneously and rapidly realize the qualitative and quantitative SERS analysis of mixture solutions with lower than 8.8% relative standard deviation. The result demonstrates that the proposed strategy has great potential in improving SERS analysis in environmental monitoring, food safety, and so on.

IDF21-0409 Hypoglycemia and heart rate variability: synchronous detection by Holter and continuous glucose monitors

Background: Hypoglycemia is a notorious diabetic side effect leading to unwanted major vascular events and sudden cardiac death due to change in autonomic cardiac function. Previous studies have reported electrocardiographic (ECG) abnormalities such as QT interval prolongation in patients with hypoglycemia, so did heart rate variability (HRV). Aim: To document ECG and HRV changes during hypoglycemia and expect to establish a portable device to early detect hypoglycemia in the future. Method: Seventeen participants including ten poor controlled type 2 diabetes, six type 1 diabetes and one Latent autoimmune diabetes in adults (LADA) were enrolled in this study. There were six males and eleven females, aged from 37 to 77 (mean 50.3 ± 12.0) years old, with self-reported duration of diabetes from 6 to 33 (mean 20.8 ± 8.7) years. The mean HbA1c was 8.3 ± 1.4 % on the time of the examination. We used Holter- electrocardiogram (VitalSigns) and continuous glucose monitor (Medtronic) to record ECG waveform, heart rate variability and glucose level with synchronization of time for a duration of seven days. Results: Two of the seventeen participants did not experience hypoglycemia (≦70 mg/dL). The other participants who experienced hypoglycemia revealed, as a whole, a trend of correlation between blood glucose, corrected QT Interval (QTc), and HRV. When the participants experienced hypoglycemia were sub-divided into response and non-response groups according to the appearance of QTc prolongation, significant difference of age was found between two groups, most of them were type 1 diabetic patients. Among 90 events of hypoglycemia, 56 events (62%) presented with increased heart rate and/or Low Frequency/ High Frequency (LF/HF) ratio and /or decreased Root Mean Square of the Successive Differences (RMSSD). Besides, there were a trend of difference of glucose nadir, HRV include heart rate, RMSSD and LF/HF ratio between two groups. Discussion: In this study, Type 1 DM patient and younger age were easier to have QT interval prolongation during hypoglycemia. Besides, increased LF/HF ratio may represent that these group of patients have better regulation of autonomic nervous system. Heart rate variability can be seen during hypoglycemic events in both type 1 and type 2 diabetic patients especially in the response group.

Synchronous detection of IgG subtypes based on SERS combined with immunoassay

In this study, a rapid, simple, highly sensitive and anti-interference method for the joint detection of four IgG subtypes is established by using Raman microspheres with four characteristic Raman spectra. The results show that the concentrations of IgG1 in the range of 0–1500 ng ml−1, IgG2 in the range of 0–1100 ng ml−1, IgG3 in the range of 0–88.7 ng ml−1, IgG4 in the range of 0–77.2 ng ml−1, it shows a good correlation with the response value of The Raman signal. The lowest detection limits are 25.4 ng ml−1, 21.7 ng ml−1, 1.6 ng ml−1, 1.7 ng ml−1, respectively. Reproducibility is good, the coefficient of variation of low, medium and high concentration standard solution are within 10%. The recoveries of four IgG subtypes are in the range of 90%–110%, and the accuracy of the method is good. The coefficients of variation between and within the three batches of reagents are all less than 11%, showing good precision. There is no cross reaction with Procalcitonin (20 ng ml−1), Interleukin-6 (1 ng ml−1) and bovine serum albumin (10 mg ml−1), and the specificity is good. Common interfering substances such as bilirubin, triglyceride and trisodium citrate do not affect the determination results, and heparin sodium only affects the determination results of IgG1. This method has good anti-interference ability. The method has high sensitivity, simple operation and strong anti-interference ability, and has good correlation with the IgG detection methods commonly used in clinic. This simple and quantitative method can be used for the rapid detection of IgG subtypes in the future, which can improve the efficiency of clinical diagnosis.

Temperature, stress, refractive index and humidity multi parameter highly integrated optical fiber sensor

Multi parameter measurement based on optical fiber sensor has been a research hotspot in recent years. In this work, four kinds of optical fiber sensors, LPFG, FBG, PMF and SMS are used. The transmission characteristics and sensing characteristics of each sensor are analyzed in detail. Based on the modulation of resonance wavelength by environmental variables, the accurate and synchronous real-time detection of temperature, stress, refractive index and humidity is realized. We use all-optical coupling cascade and wavelength division multiplexing (WDM) technology to prepare a highly integrated sensing device. The problem of signal crosstalk of each sensor is solved, and the cost of signal transmission and reception is greatly reduced. It is of great significance for monitoring a variety of environmental variables under extreme conditions.

Synchronous electrochemical detection of dopamine and uric acid by a PMo12@MIL-100(Fe)@PVP nanocomposite

In this work, a noble-metal-free composite electrode was prepared based on PMo12O403− (PMo12), C9H5FeO7 (MIL-100(Fe), a Fe-based metal organic framework) and polyvinylpyrrolidone (PVP), and served as a high performance electrochemical sensor for synchronous detection of dopamine (DA) and uric acid (UA). The PMo12@MIL-100(Fe)@PVP composite electrode was fabricated by a in-situ hydrothermal method. Thanks to the synergistic effect of three active components (PMo12, MIL-100 and PVP), the electrode possesses large specific surface area and high electrical conductivity and therefore it shows high electrocatalytic oxidation performance of DA and UA with a spacing of 0.146 V between the two peak positions. These benefits of the electrode enable its electrochemical sensor to synchronously detect of DA and UA. Namely, the linear ranges can achieve 1–247 μM for DA and 5–406 μM for UA. Meanwhile, the detection limits are 0.586 μM for DA and 0.372 μM for UA. Moreover, the sensor can be applied to simultaneous determination of UA and DA in human serums with satisfactory recovery values.

Faster CNN-based vehicle detection and counting strategy for fixed camera scenes

Automatic detection and counting of vehicles in a video is a challenging task and has become a key application area of traffic monitoring and management. In this paper, an efficient real-time approach for the detection and counting of moving vehicles is presented based on YOLOv2 and features point motion analysis. The work is based on synchronous vehicle features detection and tracking to achieve accurate counting results. The proposed strategy works in two phases; the first one is vehicle detection and the second is the counting of moving vehicles. Different convolutional neural networks including pixel by pixel classification networks and regression networks are investigated to improve the detection and counting decisions. For initial object detection, we have utilized state-of-the-art faster deep learning object detection algorithm YOLOv2 before refining them using K-means clustering and KLT tracker. Then an efficient approach is introduced using temporal information of the detection and tracking feature points between the framesets to assign each vehicle label with their corresponding trajectories and truly counted it. Experimental results on twelve challenging videos have shown that the proposed scheme generally outperforms state-of-the-art strategies. Moreover, the proposed approach using YOLOv2 increases the average time performance for the twelve tested sequences by 93.4% and 98.9% from 1.24 frames per second achieved using Faster Region-based Convolutional Neural Network (F R-CNN ) and 0.19 frames per second achieved using the background subtraction based CNN approach (BS-CNN ), respectively to 18.7 frames per second.

Optimum Design and Test of a Novel Bionic Electronic Stethoscope based on the Cruciform Microcantilever with Leaf Microelectromechanical Systems Structure

AbstractThis paper proposes a heart sound sensing structure and system by combining the traditional auscultation structure and human‐like ear eardrum gas–solid coupling sound conduction process. This system is based on the lever pickup mechanism of eardrum vibration and the traditional stethoscope pickup amplification, microelectromechanical system (MEMS) technology, and the detection principle of piezoresistive and Wheatstone bridge. The optimal size and process parameters of the biomimetic sensor structure are given through theoretical calculation and numerical simulation on Comsol and SRIM. Computer numerical control, 3D printing, MEMS technology, and 3D heterogeneous integration technology are used to complete the precise processing and encapsulation of the proposed structure. After the performance tests, results show that the optimal structure can collect directional signals, with a bandwidth from 10 Hz to 1 kHz, which can effectively cover the range of the heart frequency. The signal‐to‐noise ratio is improved by 2.3 dB compared with the 3M stethoscope. An electrocardiogram and phonocardiogram synchronization detection system is developed with this structure. The structure and system can be effectively applied to the high‐quality collection and intelligent recognition of heart sound data sets. The recognition accuracy can reach 98.5%. It is highly effective for early screening and intelligent diagnosis of cardiovascular diseases.

Shunt Active Power Filter Performances based on Seven-level NPC Inverter using Fuzzy and LS-PWM Control Scheme

This paper presents novel seven-level neutral point clamped (npc) shunt active power filter system based on LS-PWM and fuzzy control approaches which can eliminate current harmonics generated by nonlinear loads. Today, multi-level inverters are strongly used in the medium and high voltage applications; their advantages are low harmonic distortions, low switching losses, low electromagnetic interference, and low acoustic noise. Second, fuzzy logic techniques have been successfully employed in several power electronic applications. Fuzzy controller does not need an accurate mathematical model, can work with imprecise inputs, can handle non-linearity, and are more robust than conventional controllers. To benefit from these advantages a novel control scheme for seven-level (npc) inverter based on Fuzzy and LS-PWM technique is proposed. The reference current signals required to compensate harmonic currents use the synchronous current detection method, this technique is easy to implement and achieves good performances for harmonic compensation. The proposed shunt APF is evaluated using Matlab-Simulink software and SimPowerSystem Toolbox under transient and steady state for various operation conditions. The simulation results show the effectiveness of the proposed shunt active filter based on seven-level (NPC) inverter for improving the power quality and the superiority of combined fuzzy and LS-PWM control scheme to conventional controller in term of harmonics compensation and dynamic performances.

Precisely Detecting the Telomerase Activities by an AIEgen Probe with Dual Signal Outputs after Cell-Cycle Synchronization.

By maintaining the telomere lengths, telomerase can make the tumor cells avoid the apoptosis, thus, achieving the cell immortalization. In the past, a series of telomerase detection systems have been developed through utilizing the unique characteristic of telomerase extended primer. However, fluctuation of telomerase activity, along with the cell cycle progression, leads to ambiguous detection results. Here, we reported a dual signal output detection strategy based on cell-cycle synchronization for precisely detecting telomerase activities by using a new AIEgen probe SSNB. Experimental and simulating calculation results demonstrated that positively charged SSNB could interact with DNA through the electrostatic interaction and π-π interaction, as well as the hydrogen bonds. The aggregation of SSNB caused by the extended template strand primer (TP) could be observed in tumor cells, thus, indicating the telomerase activity in various cell lines. Furthermore, after cell cycle synchronization, it was found that the telomerase activity in the S phase was the highest, no matter from the fluorescence intensity or the ROS generation situation. Dual signal outputs of SSNB verified the significance and necessity of cell-cycle synchronization detection for telomerase activity. This strategy could open a new window for the biotargets of which activity is variational in time dimension.

A wearable piezoelectro-triboelectric sensor with nanocomposite electrodes for human physiological detection

The detection capability of many electronic sensors is easily interfered by the external turbulent environment. The sensor integrated with different power generation mechanisms can realize multi-states detection by coupling voltage signals. Herein, a flexible wearable bracelet-structure piezoelectro-triboelectric sensor with nanocomposite electrodes (NCEP-TS) is designed and fabricated by nanoparticle doping and thin-film technologies. To investigate its sensing properties, we conducted systematic wearability experiments with consideration of acceleration, temperature, ultraviolet (UV) rays, magnetism, and composite physical fields. The experimental results indicate that the sensitivities of the NCEP-TS reach 1.4 V/g and 0.73 V/mm, and the hystereses are only 2.6% and 2.5%, which is a significant enhancement compared with that of the piezoelectro-triboelectric sensor with single metal electrodes (SMEP-TS). In addition, the stability of the NCEP-TS exceeds that of the SMEP-TS by more than 41.25%. It can be concluded that the NCEP-TS has excellent characteristics, such as high sensitivity, high stability, and low hysteresis. It is worth noting that the flexible feature of the NCEP-TS can provide wearable comfort to realize synchronous detection of pulse and velocity signals. Meanwhile, the output power of the NCEP-TS reaches milliwatt (mW) level in the experiment, which demonstrates the self-powered capability of this sensor. This work provides a reference for improving the sensing properties of the wearable sensor from the electrode perspective. Therefore, the NCEP-TS is a potential alternative for the application of wearable sensors in the field of human physiological monitoring.

Advanced Computing Methods for Impedance Plethysmography Data Processing.

In this paper we are introducing innovative solutions applied in impedance plethysmography concerning improvement of the rheagraph characteristics and the efficiency increase of the developing rheograms using computer methods. The described methods have been developed in order to ensure the stability of parameters and to extend the functionality of the rheographic system based on digital signal processing, which applies to the compensation of the base resistance with a digital potentiometer, digital synthesis of quadrature excitation signals and the performance of digital synchronous detection. The emphasis was put on methods for determination of hemodynamic parameters by computer processing of the rheograms. As a result–three methods for respiratory artifacts elimination have been proposed: based on the discrete cosine transform, the discrete wavelet transform and the approximation of the zero line with spline functions. Additionally, computer methods for physiological indicators determination, including those based on wavelet decomposition, were also proposed and described in this paper. The efficiency of various rheogram compression algorithms was tested, evaluated and presented in this work.

MAF-DCGI Based Single-Phase Uninterrupted PV-Battery System Under Unintentional Islanding

The unintentional islanding is a critical issue in grid-connected solar battery systems in case of grid loss. This interrupts the power supply to the loads. Therefore, in this paper, an uninterrupted photovoltaic (PV)-battery energy storage (BES) system is presented to improve the reliability of the power supply. Besides, this system also furnishes the mitigation of load harmonics current and nonactive power compensation along with peak energy optimization for the PV array. The PV-battery system comprises a battery control by converter and an inverter regulated by an adaptive algorithm. The bidirectional controller regulates the voltage of the DC link capacitor. The moving average filter (MAF) - dual cascaded generalized integrator (DCGI) based adaptive control algorithm is used for utility-interactive operation and a voltage-based control algorithm is used for a standalone mode of operation. MAF-DCGI based phase-locked loop (PLL) is used for synchronization and islanding detection mechanism. An energy management system is used to manage the power flow between the devices in different modes of operation and smooth connection to the grid satisfying the IEEE 1547-2018 standard.

Increased serum cystatin C levels and responses of pancreatic α- and β-cells in type 2 diabetes.

BackgroundIncreased serum cystatin C (CysC) can predict the onset of type 2 diabetes (T2D). Meanwhile, impaired pancreatic α- and β-cell functions get involved in the pathophysiological processes of T2D. So this study was to explore the relationships between serum CysC levels and pancreatic α- and β-cell functions in T2D.MethodsIn this cross-sectional observational study, a total of 2634 patients with T2D were consecutively recruited. Each recruited patient received a serum CysC test and oral glucose tolerance test for synchronous detection of serum C-peptide and plasma glucagon. As components of pancreatic β-cell function, insulin secretion and sensitivity indices were evaluated by C-peptide area under the curve (AUC-CP) and C-peptide-substituted Matsuda’s index (Matsuda-CP), respectively. Fasting glucagon (F-GLA) and post-challenge glucagon calculated by glucagon area under the curve (AUC-GLA) were used to assess pancreatic α-cell function. These skewed indices and were further natural log-transformed (ln).ResultsWith quartiles of serum CysC levels ascending, AUC-CP, F-GLA and AUC-GLA were increased, while Matsuda-CP was decreased (P for trend <0.001). Moreover, serum CysC levels were positively related to lnAUC-CP, lnF-GLA and lnAUC-GLA (r= 0.241, 0.131 and 0.208, respectively, P < 0.001), and inversely related to lnMatsuda-CP (r= –0.195, P < 0.001). Furthermore, after controlling for other relevant variables via multivariable linear regression analysis, serum CysC levels were identified to account for lnAUC-CP (β= 0.178, t= 10.518, P < 0.001), lnMatsuda-CP (β= –0.137, t= –7.118, P < 0.001), lnF-GLA (β= 0.049, t= 2.263, P = 0.024) and lnAUC-GLA (β= 0.121, t= 5.730, P < 0.001).ConclusionsIncreased serum CysC levels may be partly responsible for increased insulin secretion from β-cells, decreased systemic insulin sensitivity, and elevated fasting and postprandial glucagon secretion from α-cells in T2D.

Low-cost electronic circuitry for photoacoustic gas sensing

The circuitry comprises a sine wave generator based on direct digital synthesis, a laser diode driver module, a band-pass frequency filter, a synchronous detector with phase adjustment circuitry and a low pass filter to form an analog lock-in amplifier, and an analog-to-digital converter. A 32-bit ARM microcontroller programmed with the open source Mecrisp dialect of the Forth interpreter language is used to set the frequency, and read the data from the analog-to-digital converter. The circuitry is tethered via a serial interface to a personal computer. A graphical user interface written in Phython allows easy interaction with the microcontroller by sending the appropriate Forth commands. The data acquired is visualized and stored on the personal computer for further processing. The circuitry is easy to build as it is based on through-hole devices, except for two necessary surface mount items, which, however, still can be soldered with a fine tipped soldering iron. The performance of the circuitry was demonstrated by the photoacoustic detection of NO2 using a laser diode with a wavelength of 450 nm.

Group-Wise Sidelink Synchronization Signal and Carrier Frequency Offset Detection Method for D2D-Based NR-V2X Systems

This article proposes an effective joint sidelink secondary synchronization signal (S-SSS) and carrier frequency offset (CFO) detection method for device-to-device-based new radio vehicle-to-everything networks. In order to improve the S-SSS and CFO detection performance, the proposed method uses a group-by-group correlation between four consecutive sidelink synchronization signals. The benefits and drawbacks of the proposed detection scheme are presented, and a theoretical analysis is derived, which is further discussed by means of simulation results. Both analytical results and simulations show that the proposed solution attains an improved detection performance using a group-wise correlation with slightly increased complexity, compared to existing detection algorithms.

Abstract P3-03-21: Contralateral breast cancers detected by pre-operative MRI in patients diagnosed with DCIS: Whart do they mean?

Abstract Background: For patients with ductal carcinoma in situ (DCIS), data about contralateral breast cancers detected by MRI at primary diagnosis and the impact of MRI use on the incidence and stage of contralateral breast cancers during follow-up are scarce. Methods: We selected all women diagnosed with a primary DCIS in the Netherlands in 2011-2015 from the Netherlands Cancer Registry. The synchronous and metachronous detection of contralateral DCIS and contralateral invasive breast cancer was assessed for patients who did receive an MRI upon primary diagnosis (MRI group) and for an age-matched control group without MRI. Incidence of contralateral disease during follow-up was calculated using competing risk methods.Results: Of the 8486 patients diagnosed with primary DCIS, 1571 (19%) received an MRI. In the MRI group, 0.8% of patients were diagnosed with a synchronous contralateral DCIS and 1.3% with synchronous contralateral invasive breast cancer. Median follow-up time was 6.4 years (IQR: 5.1-7.6). The estimated five-year cumulative incidence of synchronous plus metachronous contralateral DCIS was 2.0% (95% CI: 1.4%-2.8%)) for the MRI group and 0.9% (95% CI: 0.5%-1.5%) for the age-matched control group. The five-year cumulative incidence of contralateral invasive breast cancer was 3.5% (95% CI: 2.7%-4.5%) for the MRI group and 2.3% (95% CI: 1.6%-3.1%) for the age-matched control group. In patients aged &amp;lt;50 years, the cumulative incidence of metachronous contralateral DCIS was statistically significantly higher in the MRI group than in the age-matched controls (sHR= 4.22 (95%CI: 1.19-14.99), P=0.03). This was not the case in patients aged 50-74 years (sHR=0.89 (95%CI: 0.41-1.93), P=0.77). Conclusions: MRI led to more frequent detection of synchronous contralateral invasive breast cancers without lowering the number of metachronous contralateral invasive breast cancers. In patients aged below 50 years, MRI added to conventional imaging led to a persisting higher rate of DCIS diagnosed in the opposite breast, also without influencing the occurrence of invasive breast cancers being detected during the first five years of follow-up. Footnotes Citation Format: Kristien Keymeulen, Sandra Geurts, Loes Kooreman, Lucien Duijm, Sanne Engelen, Sigrid Vanwetswinkel, Ernest Luiten, Sabine Siesling, Adri Voogd, Vivianne Tjan-Heijnen. Contralateral breast cancers detected by pre-operative MRI in patients diagnosed with DCIS: Whart do they mean? [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-21.

Time-modulated excitation for enhanced single-molecule localization microscopy.

Structured illumination in single-molecule localization microscopy provides new information on the position of molecules and thus improves the localization precision compared to standard localization methods. Here, we used a time-shifted sinusoidal excitation pattern to modulate the fluorescence signal of the molecules whose position information is carried by the phase and recovered by synchronous demodulation. We designed two flexible fast demodulation systems located upstream of the camera, allowing us to overcome the limiting camera acquisition frequency and thus to maximize the collection of photons in the demodulation process. The temporally modulated fluorescence signal was then sampled synchronously on the same image, repeatedly during acquisition. This microscopy, called ModLoc, allows us to experimentally improve the localization precision by a factor of 2.4 in one direction, compared to classical Gaussian fitting methods. A temporal study and an experimental demonstration both show that the short lifetimes of the molecules in blinking regimes impose a modulation frequency in the kilohertz range, which is beyond the reach of current cameras. A demodulation system operating at these frequencies would thus be necessary to take full advantage of this new localization approach. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Fast and simultaneous detection of dissolved BOD and nitrite in wastewater by using bioelectrode with bidirectional extracellular electron transport

Timely and simultaneously detecting BOD and nitrite concentrations is of great significance for curbing of water pollution and adjusting wastewater treatment strategies. However, existing BOD and nitrite biosensors cannot perform synchronous detection due to their single electroactivity and differences in detection time. This study reported a novel dual-function electrochemical biosensor (DFEB) that could perform fast, simultaneous detection of nitrite and dissolved BOD. DFEB conducted a potential-step chronoamperometry on the mixed-bacteria bioelectrode with bidirectional electron transfer ability to obtain response signals. DFEB accurately measured dissolved BOD in the range of 5 ∼ 100 mg BOD L−1 and nitrite in the range of 0.05 ∼ 16 mg NO2−-N L−1 within 20 min and maintain stable performance over 200 tests. DFEB performed well in artificial wastewater, aquatic wastewater, anaerobic tank effluent and anammox effluent, with relative errors < 15.7% and 16.8% in detecting nitrite and dissolved BOD, respectively. Our study provided a feasible way to develop multifunctional biosensors for detecting pollutants with different redox properties in wastewater.

Methods for synchronous detection of 14 mycotoxins in Pseudostellariae Radix and investigation on its contamination

This study aimed to establish a method for synchronous detection of 14 mycotoxins in Pseudostellariae Radix and investigate its contamination with mycotoxins, so as to provide technical guidance for monitoring the quality of Chinese medicinal materials and medication safety. The sample was extracted with 80% acetonitrile in an oscillator for 1 h, purified using the modified QuEChERS purifying agent(0.1 g PSA + 0.3 g C_(18) + 0.3 g MgSO_4), and separated on a Waters HSS T3 chromatographic column(2.1 mm×100 mm, 1.8 μm). The gradient elution was carried out with 0.1% formic acid in water and acetonitrile, followed by the scanning in the multi-reaction monitoring(MRM) mode and the analysis of mycotoxin contamination in 26 Pseudostellariae Radix samples. The recovery rates of the established method were within the range of 82.17%-113.6%, with the RSD values less than 7% and the limits of quantification(LOQ) being 0.019-0.976 μg·kg~(-1). The detection rate of 14 mycotoxins in 26 batches of medicinal materials was 53.85%. The detection rate of sterigmatocystin(ST) was the highest, followed by those of zearalenone(ZEN), aflatoxin G_2(AFG_2), fumonisin B_1(FB_1), HT-2 toxin, and nivalenol(NIV). Their respective detection rates were 38.46%, 26.92%, 23.08%, 11.54%, 11.54%, and 7.69%, with the pollution ranges being 1.48-69.65, 0.11-31.05, 0.11-0.66, 0.28-0.83, 20.86-42.56, and 0.46-1.84 μg·kg~(-1), respectively. The established method for the detection of 14 mycotoxins is accurate, fast and reliable. The research results have very important practical significance for guiding the monitoring and prevention and control of exogenous fungal contamination of Chinese medicinal materials.