Real-time Dynamic Monitoring Research Articles

Real-time monitoring of biomolecular dynamics on cell membranes by quantum dot-based multicolor electrochemiluminescence

Electrochemiluminescence (ECL) offers numerous unique advantages for microscopic imaging. However, achieving real-time dynamic observation of biomolecules on cell membranes through ECL imaging remains a challenge. Herein, we present a new ECL nanoemitter for real-time multicolor imaging of biomolecules on cell membranes. The nanoemitter consists of quantum dots (QDs) with surface-immobilized glucose oxidase capable of catalyzing glucose oxidation to produce co-reactant hydrogen peroxide (H2O2). This nanoemitter enables sequential real-time imaging with a relatively high signal-to-noise ratio owing to the continuous availability of co-reactants. Therefore, by using the functionalized multicolor QDs for ECL-based single-particle tracking, the dynamic behaviors of individual biomolecules on cell membranes, including inter-molecular interactions, can be visualized in real time. This new nanoemitter is expected to facilitate investigations of the dynamics of biomolecules on cell membranes.

Development of a Versatile Protein Labeling Tool for Live-Cell Imaging Using Fluorescent β-Lactamase Inhibitors.

To understand the function of protein in live cells, real-time monitoring of protein dynamics and sensing of their surrounding environment are important methods. Fluorescent labeling tools are thus needed that possess fast labeling kinetics, high efficiency, and long-term stability. We developed a versatile chemical protein-labeling tool based on fluorophore-conjugated diazabicyclooctane β-lactamase inhibitors (BLIs) and wild-type TEM-1 β-lactamase protein tag. The fluorescent probes efficiently formed a stable carbamoylated complex with β-lactamase, and the labeled proteins were visualized over a long period of time in live cells. Moreover, use of an α-fluorinated carboxylate ester-based BLI prodrug enabled the probe to permeate cell membranes and stably label intracellular proteins after unexpected spontaneous ester hydrolysis. Lastly, combining the labeling tool with a pH-activatable fluorescent probe allowed visual monitoring of lysosomal protein translocation during autophagy.

Цветометрическая система мониторинга роста микроводоросли Dunaliella salina в лабораторных условиях

The brackish microalgae Dunaliella salina, being an extremophilic halophyte, is a promising object for biotechnological production. The aim of this work is to develop a methodology for non-destructive control of the development of a microalgae culture under conditions of balanced growth during periodic cultivation on plates. Before the start of the experiment, the microalgae culture was synchronized. The quantitative content of chlorophylls a and b, as well as carotenoids, was determined spectrophotometrically in alcohol extracts. During cultivation, time-lapse images were recorded on a smartphone camera. The basis of the colorimetric evaluation is the analysis of the time series of images in the RGB color model. It is shown that the ratio of colors correlates to a high degree with the content of the determined main plant pigments – chlorophylls and carotenoids, and with the data of spectrophotometric measurements of live suspensions. The changes in the blue channel are the most pronounced, the least being in the green channel. The logarithm of color intensity is linearly dependent on the degree of dilution of the culture. The developed method for real-time monitoring of the development dynamics of the D. salina microalgae culture makes it possible to build growth curves and solve multiparametric problems to optimize the cultivation of microalgae, including when working with large arrays of samples.

A Framework for Service-Oriented Digital Twin Systems for Discrete Workshops and Its Practical Case Study

To address issues in discrete manufacturing workshops, such as the difficulty for management personnel to coordinate workshop production and the challenge of visualizing and supervising a massive amount of temporary data, this paper proposes a service-oriented digital-twin-system framework for discrete workshops using the industrial IoT platform as the system-service platform to solve the problems of the opaque monitoring of operators in discrete workshops, the low interactivity of 2D monitoring systems, and the difficulty of the visual monitoring of workshop data. Firstly, the current situation of intelligent manufacturing workshop-monitoring demand in the context of new-generation information technology is analyzed, and a six-dimensional digital-twin-workshop-monitoring architecture is proposed, whereby a discrete workshop monitoring system based on the digital twin is constructed with IoT as the service platform. We will conduct research on the construction of virtual workshops for the system development process, twin data collection based on edge computing gateways, and dynamic monitoring of the production process. Finally, through the application of this system framework in a movable-arm-production workshop, the more intelligent human–machine interaction process of browsing and controlling workshop information, such as the equipment layout and production processes in the virtual workshop, has been realized. This includes data acquisition based on edge-computing gateways, dynamic real-time monitoring of the production process, etc., which provides a reference for realizing the visual monitoring of the discrete workshop.

Study on acoustic emission properties and crack growth rate identification of rail steels under different fatigue loading conditions

The acoustic emission (AE) technique is a non-destructive real-time dynamic monitoring technique for structural health. Nonetheless, there has been a lack of research on the initiation and propagation mechanisms of fatigue cracks in rails. In this paper, the AE signal properties of fatigue crack initiation and growth are studied in three types of rail materials under different fatigue loading conditions, and a method is proposed to identify the fatigue crack growth rate. The results show that this method has good applicability for different rail materials, and the crack growth rate can be quantitatively identified based on the AE energy growth rate.

A novel acoustic emission sensor design and modeling method for monitoring the status of high-speed train bearings

Acoustic emission (AE) technology is suitable for monitoring the status of high-speed train bearings owing to its high sensitivity and real-time dynamic monitoring capabilities. However, a complete theoretical model of the AE sensor, which is the core component of AE signal sensing equipment, has not yet been reported. The existing matching layer models do not account for wave attenuation in the matching layer. To address these shortcomings, we established a novel piezoelectric AE sensor design and modeling method. First, a rough contact model is established for piezoelectric ceramics, and the influence of roughness on size selection of piezoelectric ceramics is analyzed. Second, the sound intensity transmission coefficient (SITC) model of the matching layer is established considering the attenuation of AE waves, and the corresponding relationship between the attenuation coefficient and the optimum thickness of the matching layer is derived. Then a complete finite element (FE) model of an AE sensor is established, and the electroacoustic properties of the AE sensor are numerically simulated based on acoustic and piezoelectric coupling. Furthermore, AE sensors with different thicknesses of matching layers are constructed, and the validity of the mathematical model of the matching layer is verified through a lead-breaking experiment. Thereafter, a novel comprehensive performance evaluation index (CPEI) is designed through principal component analysis (PCA) based on hit parameters of AE sensors. Finally, the effectiveness and environmental adaptability of the AE sensor is verified by performance testing under complex conditions near an actual high-speed train line. The proposed method can provide a valuable theoretical framework for AE sensor design and status monitoring of high-speed train bearings.

Intelligent renovation of existing Olympic venues: digital design and construction strategy of a DfD-based prefabricated structure system

This article introduces introduces a new prefabricated and assembled steel structure system and its key construction technologies for repeated switching scenes in existing stadiums. This steel structure system follows the DfD design method, minimizing the volume of each group of structural member units and separating the connection interfaces between members. In order to improve the construction and assembly efficiency of all the structural components, this study establishes an assembly-oriented BIM model data system by adding customized attributes in the family library in Autodesk REVIT. By associating model attributes with on-site monitoring data of the construction process, this research realizes real-time acquisition and display of construction data of all components during the whole life cycle. At the same time, aiming at the requirements of high-precision positioning and digital dynamic monitoring in future on-site construction, this research proposes an innovative construction positioning monitoring method which combines motion capture system with traditional construction monitoring technology. By correcting the positioning data of motion capture system with traditional construction monitoring data, real-time dynamic monitoring of several monitoring points in a 12*15 m large site is realized and the measurement error is controlled within ±1 mm. This study takes the construction project of “ice-water conversion” from the main swimming pool of the National Swimming Center in the Summer Olympic Games to the curling venue of the Winter Olympic Games as an example to show the important role of relevant technology to improve the construction efficiency in the construction application for the renovation of existing Olympic venues.

Construction and Application of On-Line Roof Separation Monitoring System Based on High-Precision FBG Indicator

Aiming at the existing problems of low efficiency, lagging monitoring results, and poor reliability and accuracy in the present roadway roof separation monitoring system, a high-precision Fiber Bragg Grating (FBG) separation indicator is designed through theoretical analysis, numerical simulation, and laboratory tests—according to the fiber grating sensing principle. Based on the Microsoft. Net platform, C# programming language, and VS2010 integrated development tools, the corresponding on-line monitoring software is developed. On this basis, a real-time on-line roof separation monitoring system is proposed. The high-precision FBG separator was calibrated and tested in the laboratory and results suggested that both the left and right arm demonstrate good sensitivity and linearity with linear fitting coefficient values of 0.9981 and 0.9979, respectively. The monitoring system was successfully applied to roof separation monitoring of the #14301 rail roadway in the Shaqu coal mine. The monitoring results showed that the on-line roof separation monitoring system based on the high-precision FBG separation indicator has the advantages of high precision, good stability, and long-distance signal transmission, which can achieve real-time dynamic monitoring and provides an effective method for long-term on-line monitoring of roadway roof separation.

Flexible and Wearable Photonic-Crystal Fiber Interferometer for Physiological Monitoring and Healthcare

Utilization of flexible optical systems for real-time comprehensive physiological monitoring has been restricted by their low mechanical robustness and reconfigurability. Here we report a mechanically robust, reconfigurable, flexible, and wearable photonic interferometer system for real-time precision tracking of limb activities, facial motions, respiration, and pulse rate with significant temporal stability and repeatability. Vital health diagnostic parameters have been measured by virtue of a highly sensitive response of the system. The proposed system features curvature sensitivity of 3.1 nm/m–1 over the range of 0–1.71 m–1, temperature sensitivity of 284 pm/°C between 30 and 60 °C, and physical strain sensitivity of 540 pm/1% tensile strain. Such a robust, reconfigurable, and sensitive system would have a wide practical and sustainable utility for real-time dynamic activity monitoring in health, industrial, and various other sectors.

Analysis on the Steps of Physical Education Teaching Based on Deep Learning

The rapid progress of the internet of things and artificial intelligence has brought new opportunities for the construction and development of intelligent sports. This paper designs an analysis and evaluation system of physical education teaching steps based on deep learning technology. The intelligent wearable devices are used to conduct real-time dynamic monitoring of students' exercise steps and heart rate in class so as to build a sports teaching activity data set. The authors analyze the time step sequence based on transformer deep model to realize the estimation of motion effect. In addition, they propose a hierarchical fusion model based on transformer, which makes full use of the steps and heart rate information to predict the abnormal situation in physical education. The experimental results show the effectiveness of the system.

Serum circular RNA hsa_circ_0000702 as a novel biomarker for diagnosis of gastric cancer.

There is mounting evidence that Circular RNAs (circRNAs) are essential for the initiation and development of gastric cancer (GC). In this study, we further investigated the clinical importance and applicability of serum hsa_circ_0000702 in the diagnosis and treatment of GC. Sanger sequencing, agarose gel electrophoresis, and RNase R assay were used to confirm the origin, alterations, and stability of hsa_circ_0000702 in GC patients. Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect the expression level of hsa_circ_0000702 in GC cell lines, serum, and tissues. Additionally, receiver operating characteristic (ROC) curves were built to evaluate their prognostic value and how well they would work in conjunction with popular biochemical markers for GC. Finally, real-time dynamic monitoring was used to assess its prognostic usefulness. Hsa_circ_0000702 exhibited the fundamental traits of circRNA. Hsa_circ_0000702 had good sensitivity, specificity, and stability. It was discovered that hsa_circ_0000702 was down-regulated in GC cell lines, serum, and tissues, and that the level of tumor differentiation and tumor node metastasis (TNM) staging were connected with serum hsa_circ_0000702. The area under the ROC curve of serum hsa_circ_0000702 was calculated to be 0.745 (95% CI: 0.669-0.821), indicating high diagnostic efficacy. The diagnostic value was greatly increased by combining serum CEA and CA19-9. Finally, preoperative and postoperative dynamic monitoring revealed serum hsa_circ_0000702 to be of clinical application. Serum hsa_circ_0000702 was variably expressed in GC patients, indicating that serum hsa_circ_0000702 may be a novel biomarker for GC diagnosis and dynamic monitoring.

Research on a real-time dynamic monitoring method for silent aspiration after stroke based on semisupervised deep learning: A protocol study.

This study aims to establish a real-time dynamic monitoring system for silent aspiration (SA) to provide evidence for the early diagnosis of and precise intervention for SA after stroke. Multisource signals, including sound, nasal airflow, electromyographic, pressure and acceleration signals, will be obtained by multisource sensors during swallowing events. The extracted signals will be labeled according to videofluoroscopic swallowing studies (VFSSs) and input into a special dataset. Then, a real-time dynamic monitoring model for SA will be built and trained based on semisupervised deep learning. Model optimization will be performed based on the mapping relationship between multisource signals and insula-centered cerebral cortex-brainstem functional connectivity through resting-state functional magnetic resonance imaging. Finally, a real-time dynamic monitoring system for SA will be established, of which the sensitivity and specificity will be improved by clinical application. Multisource signals will be stably extracted by multisource sensors. Data from a total of 3200 swallows will be obtained from patients with SA, including 1200 labeled swallows from the nonaspiration category from VFSSs and 2000 unlabeled swallows. A significant difference in the multisource signals is expected to be found between the SA and nonaspiration groups. The features of labeled and pseudolabeled multisource signals will be extracted through semisupervised deep learning to establish a dynamic monitoring model for SA. Moreover, strong correlations are expected to be found between the Granger causality analysis (GCA) value (from the left middle frontal gyrus to the right anterior insula) and the laryngeal rise time (LRT). Finally, a dynamic monitoring system will be established based on the former model, by which SA can be identified precisely. The study will establish a real-time dynamic monitoring system for SA with high sensitivity, specificity, accuracy and F1 score.

Real-time monitoring norepinephrine exocytosis by high K+via an endoplasmic reticulum-targeting fluorescent probe.

Norepinephrine (NE), a neurotransmitter, has multiple functions in the neural system and peripheral organs. Abnormal levels of NE may lead to numerous neuro-degenerative and psychiatric disorders, such as Parkinson's disease, depression and Alzheimer's disease. Moreover, studies have indicated that an increase in NE may induce endoplasmic reticulum (ER) stress and cell apoptosis via oxidative stress. Therefore, developing a measure to monitor NE levels in the ER appears to be particularly important. The fluorescence imaging technique has become an ideal tool for detecting various biological molecules in situ, with the advantages of high selectivity, nondestructive testing, and real-time dynamic monitoring. However, there are currently no activatable ER fluorescent probes that can be used to monitor NE levels in the ER. Herein, a robust ER-targetable fluorescence probe (ER-NE) for detecting NE in the ER was constructed for the first time. With the excellent properties of high selectivity, low cytotoxicity and good biocompatibility for NE detection, ER-NE successfully achieved the detection of endogenous and exogenous NE under physiological conditions. More importantly, a probe was further applied to monitor NE exocytosis stimulated by continuous incubation with high K+. We expect that the probe may serve as a powerful tool for detecting NE and provide a potential new diagnostic method for related neurodegenerative diseases.

Automated instant labeling chemistry workflow for real-time monitoring of monoclonal antibody N-glycosylation

Integration of Instant Procainamide (Instant-PC) flow chemistry into the N-GLYcanyzer PAT sequential injection system enables automated real-time monitoring of mAb N-glycosylation dynamics to facilitate advanced biologics manufacturing processes.

Study on Denoising Microseismic Signal Based on Autoencoder Convolutional Neural Networks

As a kind of dynamic real-time monitoring technology, microseismic monitoring technology has been widely used for rockburst warning. Due to the complexity of the actual monitoring environment, the monitoring signals often contain different types of noise, affecting the earning warning of rockburst. In this study, an Autoencoder Convolutional Neural Network denoising model based on deep learning has been proposed to denoising of the complex signals. The unsupervised adaptive training method is used to train the model, which only needs to set its initial parameters. The importance of an enhanced training dataset is illustrated by the comparison experiment. The results indicate that the training and verification shows well performance during training. The denoising efficiency of the proposed model is studied by the denoising of the synthetic noise-containing signals. Furthermore, the dataset from the water conveyance tunnel in the Hanjiang-to-Weihe River water diversion project (HJ-Project) in Shaanxi Province is taken as an engineering example to evolute the performance of the proposed model for practical project. The denoising performance of the model is analysed through the visual denoising results and evaluation index. The model can effectively denoise the complex noised signal which separate it into pure microseismic signal and noise signal, and improve the signal-to-noise ratio, which is benefit for arrive-time picking and source locating then improve the performance of early warning of rockburst.

A novel multifunctional carrier with magnetic-NIR luminescent-microwave heating characteristics for drug delivery

We constructed a novel core–shell structured Fe3O4@WO3-x(x = 0∼1)@GdF3: Yb/Er nanoparticles with magnetic-NIR luminescent-microwave heating characteristics used as drug carrier to investigate the loading and controllable release properties of the chemotherapeutic drug doxorubicin (DOX). The porous surface of Fe3O4@WO3-x(x = 0∼1)@GdF3:Yb/Er nanoparticles can store DOX molecules by means of physical adsorption. The Fe3O4 core and GdF3: Yb/Er shell functioned successfully for magnetic targeting (1.40 emu•g−1) and NIR fluorescence imaging (NIR 650–850 nm), respectively. The introduction of WO3-x(x = 0∼1) with LSPR effect enhanced the luminescence of near-infrared region of Fe3O4@WO3-x(x = 0∼1)@GdF3:Yb/Er nanoparticles successfully. In addition, the WO3-x(x = 0∼1) acts as a good microwave absorber with excellent microwave thermal response property for microwave triggered drug release (the DOX release of 12% under microwave irradiation for 10 s outclass the 2% within 1 h without microwave irradiation release). The release profile could be controlled by the duration and number of cycles of microwave application. Moreover, it can monitor the drug release process in real time under the guidance of near infrared imaging, which is convenient to evaluate the therapeutic effect. This work provides a new idea for realizing the visual real-time dynamic monitoring of the chemotherapy process and realizing “positioning-timing-quantitative” administration, thus improving the chemotherapy effect.

Flexible pressure sensor based on graphene/PS microsphere/PDMS composite dielectric layer and activated carbon non-woven fabrics

• Fabrication of ultra-thin dielectric layers with surface microstructures and filler doping. • Offering new ideas for improving the sensitivity of flexible capacitive sensors. • Activated carbon non-woven fabrics are used to make flexible electrodes. • New dielectric layer fabrication process developed. • A number of dynamic tests have been completed using this sensor. With the widespread application of wearable devices, the demand for high-performance sensors has increased dramatically. This study proposes a novel capacitive sensor. By using polystyrene (PS) microspheres and the sacrificial layer method, the ultrathin dielectric layer with surface micro-dome structure and uniform graphene doping are fabricated. In addition, the activated carbon non-woven fabrics (ACNWF) electrode was prepared, and the device characteristics of the sensor were investigated. The sensor has a good capacitive response in a wide pressure range (0–150 kPa) and a sensitivity of 0.209 kPa −1 in the low-pressure range. The short response time (<25 ms) is suitable for real-time dynamic monitoring. Meanwhile, the sensor has good stability (3500 cycles) and performs well in mouse double-click, muscle contraction and arm swing. This sensor has great potential in wearable electronics and human-computer interaction.

Dynamic moist air monitor in a micro area with extremely high figure-of-merit.

In the rapidly changing moisture air, conventional relative humidity (RH) sensors are often difficult to respond in time and accurately due to the limitation of flow rate and non-uniform airflow distribution. In this study, we numerically demonstrate that humidity changes on micro-zones can be monitored in real time using a Bloch surface wave (BSW) ubiquitous in one-dimensional photonic crystals (1DPC). This phenomenon can be observed by leakage radiation microscope (LRM). After theoretically deriving the angular resolution limit of LRM, we obtained the minimum BSW angular change on a practical scheme that can be observed in the momentum space to complete the detection, and realized the dynamic real-time monitoring of small-scale humidity change in experiment for the first time. This monitoring method has extremely high figure of merit (FOM) without hysteresis, which can be used in humidity sensing and refractive index sensing as well as the research on turbulence.

Ultra-high-speed hybrid ceramic triboelectric bearing with real-time dynamic instability monitoring

The reliability and stability of bearing operation are crucial factors limiting the performance of high-speed rotating machinery. In this study, an ultra-high-speed hybrid ceramic rolling element triboelectric bearing (US-HCTEB) was developed to provide real-time dynamic behavior and stability monitoring. Herein, we adopted a floating rolling–sliding combination freestanding mode that ensures bearing structural integrity. Furthermore, a crown-shaped cage was employed with an opening, allowing the ceramic rolling element to be used as a dielectric material that was coupled with a sector-shaped interdigital electrode set on the bearing end cover to form a floating freestanding triboelectric nanogenerator (TENG). The rolling element self-rotated and revolved owing to the traction of the raceways, sweeping the electrodes to generate an alternating current. Additionally, the superiority and reliability of the US-HCTEB were demonstrated using a 30 million cycle durability test and an ultra-high rotating speed test at 16000 rpm, which far exceeds the capabilities of previously reported triboelectric bearings. The US-HCTEB output was then evaluated considering variable working conditions, structural optimization, and the surrounding environment. Dry contact lubrication and low humidity were found to be beneficial for the output performance. The spectra of the output current and the statistics describing the rolling element instantaneous speed suggest that the high-speed heavy radial load of the US-HCTEB could reduce overall skidding at the cost of increased instability. Subsequently, an extremely fast acceleration and deceleration test program was conducted on the US-HCTEB to evaluate its performance under the complex and nonstationary conditions in which high-speed bearings operate. The results revealed that the US-HCTEB not only achieved real-time and high-resolution dynamic behavior identification but also exhibited high reliability as it functioned appropriately until bearing failure. Thus, the proposed high-precision US-HCTEB can serve as an essential basis for the development of smart rolling bearings.

Real-time detection of response regulator phosphorylation dynamics in live bacteria

Bacteria utilize two-component system (TCS) signal transduction pathways to sense and adapt to changing environments. In a typical TCS, a stimulus induces a sensor histidine kinase (SHK) to phosphorylate a response regulator (RR), which then dimerizes and activates a transcriptional response. Here, we demonstrate that oligomerization-dependent depolarization of excitation light by fused mNeonGreen fluorescent protein probes enables real-time monitoring of RR dimerization dynamics in live bacteria. Using inducible promoters to independently express SHKs and RRs, we detect RR dimerization within seconds of stimulus addition in several model pathways. We go on to combine experiments with mathematical modeling to reveal that TCS phosphosignaling accelerates with SHK expression but decelerates with RR expression and SHK phosphatase activity. We further observe pulsatile activation of the SHK NarX in response to addition and depletion of the extracellular electron acceptor nitrate when the corresponding TCS is expressed from both inducible systems and the native chromosomal operon. Finally, we combine our method with polarized light microscopy to enable single-cell measurements of RR dimerization under changing stimulus conditions. Direct invivo characterization of RR oligomerization dynamics should enable insights into the regulation of bacterial physiology.