Monitoring Requirements Research Articles

Monitoring insect numbers and biodiversity with a vertical-beam entomological radar.

Concerns about perceived widespread declines in insect numbers have led to recognition of a requirement for long-term monitoring of insect biodiversity. Here we examine whether an existing, radar-based, insect monitoring system developed for research on insect migration could be adapted to this role. The radar detects individual larger (greater than 10 mg) insects flying at heights of 150-2550 m and estimates their size and mass. It operates automatically and almost continuously through both day and night. Accumulation of data over a 'half-month' (approx. 15 days) averages out weather effects and broadens the source area of the wind-borne observation sample. Insect counts are scaled or interpolated to compensate for missed observations; adjustment for variation of detectability with range and insect size is also possible. Size distributions for individual days and nights exhibit distinct peaks, representing different insect types, and Simpson and Shannon-Wiener indices of biodiversity are calculated from these. Half-month count, biomass and index statistics exhibit variations associated with the annual cycle and year to year changes that can be attributed to drought and periods of high rainfall. While species-based biodiversity measures cannot be provided, the radar's capacity to estimate insect biomass over a wide area indicates utility for tracking insect population sizes. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Competitivity Issues Related to Biobank Activity

The recent development of biomedical research and greater attention to the use of human bio-material has led to an increase in the number of studies devoted to biobanks. In considering the question of whether a biobank can be subject to insolvency, the present article discusses multiple points of view related to the legal status of biobanks according to which they are perceived either as an object or subject of law. From an analysis of the various organizational forms of biobank activity, the author argues that biobanks should be considered as subjects of law. Here considerations include accessing financial support from government, municipal, and other sources, the possibility of carrying out income-generating activities, mechanisms for the protection of obtained bio-material, the monitoring requirement related to entities carrying out such activities, and the possibility of recognizing such entities as insolvent. Based on the results of this research (including an analysis of the experience of foreign countries), the permissible organizational-legal forms that biobanks are instantiated, namely, public corporations, public-law companies, institutions, and public benefit funds. Because of the sensitivities involved, it is argued that such organizations should be of a non-profit character. In the light of the research question, special attention is paid to the form of a consortium. Due to the impossibility of liquidating the assets of biobank organizations in order to meet the claims of creditors, it is argued that such organizations cannot be declared insolvent.

Plasmon AgNPs/MoS2/ZnO nanorods array ternary heterojunctions enabling high-efficiency solar-light energy utilization for photocatalysis and recyclable SERS detection

BackgroundSurface-enhanced Raman scattering (SERS) has gained widespread use in molecule-level detection benefiting from its high sensitivity, nondestructive data acquisition, and capacity for providing molecular fingerprint information. However, the strong adhesion of target molecules to the substrate (known as the “memory effect”) inherently hinders the reusability of SERS substrates. Research has shown that self-cleaning SERS substrates based on versatile semiconductor materials with SERS enhancement capabilities and solar photocatalytic properties offer an effective platform for the sensitive detection and degradation of harmful molecules. ResultsIn this research, a resuable SERS-active substrate was facilely fabricated by anchoring silver nanoparticles (AgNPs) to the edges of MoS2 nanosheet decorated on ZnO nanorod arrays (NRAs). This innovative design exhibited a remarkable SERS enhancement factor (EF) of 4.6 × 107 and demonstrated significant solar photocatalytic efficiency. Such superior characteristics of ternary plasma heterojunction were ascribable to the synergistic effect of the “Schottky barrier” and “hot spots” between MoS2 and AgNPs, the inherent chemical enhancement proficiency of the MoS2/ZnO NRAs heterojunction, as well as the ultrafast electron transfer within the ternary heterojunction. SignificanceThe developed ternary heterojunction substrate enabled highly sensitive SERS detection of trace amounts of organic molecules. Moreover, this SERS substrate exhibited self-cleaning and recyclability via solar-light-driven photocatalysis. This bifunctional recyclable SERS substrate proved capable of meeting various requirements for routine monitoring of environmental organic pollutants and provided a robust avenue for advancing energy utilization materials that serve as high-performance SERS sensors and catalysts.

Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine

The widespread integration of renewable energy sources (RESs) into power systems using power electronics-based interface devices has led to a substantial rise in power quality (PQ) issues. There is an immediate requirement for effective monitoring, detection, and classification of power quality disturbances (PQDs) that is needed to take remedial measures and design planning of the system architecture. This study presents a hybrid approach with an objective for the feature extraction and classification of PQDs. The proposed hybrid approach is comprised of an optimized tunable-Q wavelet transform (OTQWT) for the feature extraction and incremental support vector machine (ISVM). A four-stage approach is suggested for the PQ detection and classification in this study. In the first stage, the various data are retrieved both in the form of synthetic data by mathematical formulations and real-time data with prototype design setup. In the second stage, regardless of the specified wavelet function, the PQD signals are decomposed into low-pass and high-pass sub-bands using the tunable-Q wavelet transform (TQWT). However, the utilization of default decomposition parameters to address nonstationary PQ signals may lead to information loss and reduced performance of the system. To avoid this limitation, an OTQWT as an enhanced technique to TQWT based on an Adaptive Particle Swarm Optimization (APSO) is suggested. A modified objective function based on the mean square error (MSE) is used to improve the decomposition process. In the third stage, an efficient classifier is suggested based on the ISVM. Lastly, to test and evaluate the performance of the proposed approach, twelve types of PQDs including noise and multiple occurrences are considered. The comparative analysis with other popular methods reflects the better performance of the proposed approach and justifies its use for PQ detection and classification purposes in real-time​ conditions.

Revolutionizing Glucose Monitoring: Enzyme-Free 2D-MoS2 Nanostructures for Ultra-Sensitive Glucose Sensors with Real-Time Health-Monitoring Capabilities.

The growing requirement for real-time monitoring of health factors such as heart rate, temperature, and blood glucose levels has resulted in an increase in demand for electrochemical sensors. This study focuses on enzyme-free glucose sensors based on 2D-MoS2 nanostructures explored by simple hydrothermal route. The 2D-MoS2 nanostructures were characterized by powder X-ray diffraction, energy-dispersive X-ray spectroscopy, scanning electron microscopy, transmission electron microscopy, Raman spectroscopy, and XPS techniques and were immobilized at GCE to obtain MoS2-GCE interface. The fabricated interface was characterized by electrochemical impedance spectroscopy which shows less charge transfer resistance and demonstrated superior electrocatalytic properties of the modified surface. The sensing interface was applied for the detection of glucose using amperometry. The MoS2-GCE-sensing interface responded effectively as a nonenzymatic glucose sensor (NEGS) over a linearity range of 0.01-0.20 μM with a very low detection limit of 22.08 ng mL-1. This study demonstrates an easy method for developing a MoS2-GCE interface, providing a potential option for the construction of flexible and disposable nonenzymatic glucose sensors (NEGS). Moreover, the fabricated MoS2-GCE electrode precisely detected glucose molecules in real blood serum and urine samples of diabetic and nondiabetic persons. These findings suggest that 2D-MoS2 nanostructured materials show considerable promise as a possible option for hyperglycemia detection and therapy. Furthermore, the development of NEGS might create new prospects in the glucometer industry.

Quantitative macroinvertebrate bioassessment in seasonally astatic aquatic habitats, Part II. Applying the method.

Seasonally astatic aquatic habitats are important ecologically, municipally, and agriculturally. Regulatory agencies and conservation organizations have developed various plans for protecting or constructing temporary wetlands, resulting in habitat monitoring requirements, particularly as relates to restoration and constructed habitats. Unfortunately, there has been no effort to develop a unified, consistent method for wetland biological monitoring. In Part I, we presented a quantifiable, replicable method for assessing seasonally astatic wetlands, which would allow for direct comparison between individual wetlands, wetland sites, and wetland types. Here in Part II, we apply the method and present the results from more than a decade of a data on two disparate sites that support California vernal pool habitats. These habitats include natural, restored, and constructed vernal pools. Our results demonstrate that the method we present yields reliable, statistically useful, and actionable data and provides a better method for assessing astatic wetland ecological health and the persistence of federally listed vernal pool crustaceans than other methods so far employed.

Direct injection ultra-performance liquid chromatography-tandem mass spectrometry for the high-throughput determination of etomidate and etomidate acid in wastewater.

Etomidate (ET), a hypnotic agent used for the induction of anesthesia, is rapidly metabolized to etomidate acid (ETA) in the liver. Recently, ET has become one of the most serious alternative drugs of abuse in China. Therefore, an urgent need exists to develop a fast and convenient analysis method for monitoring ET. The current work presents a simple, fast, and sensitive direct injection method for the determination of ET and ETA in wastewater. After the optimization of the ultra-performance liquid chromatography-tandem mass spectrometry and sample filtration conditions, the method exhibited satisfactory limits of detection (1 ng/L) and good filtration loss. The validated method was successfully applied to determine the concentrations of ET and ETA in wastewater samples (n = 245) from several wastewater treatment plants in China. The concentrations of the targets in positive samples ranged from less than the lower limits of quantitation to 47.71 ng/L. The method can meet ET monitoring and high-throughput analysis requirements.

Aircraft Objection Detection Method of Airport Surface based on Improved YOLOv5

An aircraft object detection method on the basis of improved YOLOv5 was proposed to address the issues of large model size, high number of parameters, and inability to meet real-time monitoring requirements of aircrafts in traditional object detection. Firstly, the basic unit of ShuffleNetv2 network was optimized through replacing 3x3 convolution with 5x5 convolution and removing subsequent 1x1 convolution. Simultaneously, the original ReLU activation function was replaced with PReLU. Secondly, CBAM (Convolutional Block Attention Module) attention mechanism was developed to enhance the detection accuracy of the improved network. Finally, improved ShuffleNetv2 network was applied as the backbone structure of YOLOv5. Experimental results revealed that the parameter number of the improved YOLOv5 method introduced in this paper was decreased by 18 times, with a model size of 1.03M. Therefore, a 20.8% increase was achieved in frames per second (FPS) in GPU environments and a 234.6% increase was observed in FPS in CPU environments, while a mean average precision (mAP@0.5) of 0.99 was maintained compared with traditional YOLOv5 network. Because of the advantages of fewer parameters, faster recognition speed, higher localization accuracy, and smaller memory requirement, the developed method was found to be suitable for real-time monitoring of aircrafts in airport surface.

GST A Robust Tax Regime: A Bibliometric Analysis on GST

A value-added tax placed on the delivery of goods and services is known as the goods and services tax (GST), and it is one of the most critical tax changes implemented in many countries worldwide. Indirect taxes, including sales tax, service tax, excise duty, and value-added tax, will be rolled into a single, all-encompassing tax system called the goods and services tax (GST). The introduction of the Goods and Services Tax (GST) has been the topic of substantial study and analysis. This literature review aims to summarise the most important results and insights from the existing literature on GST. This review will focus on the research that has been conducted. The goods and services tax, sometimes known as the GST, has been adopted by several countries worldwide, including Australia, Canada, New Zealand, Malaysia, Singapore, and India. The evolution of the Goods and Services Tax (GST) has been affected by several issues, including the necessity to simplify the tax system, expand the tax base, increase revenue collection, encourage economic development, and make it easier to do business across international borders. In addition, the research underlines that the design and execution of the Goods and Services Tax (GST) differ from country to country due to each nation's specific economic, social, and political conditions. Increasing the amount of money that the government takes in is one of the most important objectives of the GST. According to the research findings, the GST's effects on the income collected are complex. While some studies suggest that an increase in revenue collection has occurred as a result of the adoption of the Goods and Services Tax (GST), other studies highlight the challenges that have arisen as a result of the GST, including revenue leakage, compliance concerns, and the requirement for ongoing monitoring and enforcement. In addition, the research analyses elements that impact revenue collection, such as the tax rate, tax base, exemptions, and the efficiency of tax administration. These factors all have a role in determining how much money is brought in. This study focuses on scientific visualization based on the bibliometric analysis of 426 publications, of which 180 were completed after applying the filters on the keywords "Goods and services tax" in the Scopus database from 2017 to 2022. The articles were analyzed for a period ranging from 2017 to 2022. Bibliometric analysis, appraisal, and visualization are some of the uses that R has seen. The examination produced a scientific map that included co-occurrence analysis, network analysis, a co-citation network, and a collaboration network. These elements contributed to a better understanding of the research topic as conceptual, intellectual, and social structures. The outcome of the bibliometric analysis demonstrates that the evolution of the Goods and Services Tax (GST) has resulted in the introduction of a new tax regime in several nations. Furthermore, the outcome of the social collaboration analysis demonstrates that many nations, including India, the United Kingdom, Canada, and Australia, are collaborating to conduct more fruitful research.

Model of lnformation Support for a Regional Operator for the Management of Municipal Solid Waste

The purpose of the research is to compile a modern model of information support for a regional operator for the management of municipal solid waste and analyze the requirements for this system.Methods are based on various publications of reports by environmental operators, the public law company "Russian Еcological Operator" (РРK RЕO), on legislative documentation, research and software solutions (SТЕC Housing and Рublic Utilities, Sirena Housing and Рublic Utilities, Еlectronic Тrading Рlatform RЕO) in terms of automation of waste removal.Results. А modern information model for data exchange in the network of a regional operator for the management of solid waste has been built, which meets the needs of the industry. Based on the legislation, the study included recom- mendations for the work and functioning of departments. Ready-made solutions for automating the work of a regional operator for the removal of municipal solid waste are presented. Аn algorithm has been developed for the functioning of the system to send data on the amount of municipal solid waste (MSW) arriving at the landfill in accordance with the new requirements for automatic monitoring of waste accepted at the landfill.Conclusion. Тhe implementation of a modern level of information support for a regional operator for the management of municipal solid waste is relevant, not only from an environmental point of view, the formation of an integrated effective approach to waste management, but also from information security. Organizing the work of a regional operator for the management of municipal solid waste is a process that requires modern information support. Тo carry out the process of building competent logistics, infocommunication kits and data transmission systems are used to track vehicles trans- porting waste. Software is used to monitor the level of vehicle load, the total amount of waste removed, fuel consump- tion, analyze the load and condition of landfills with solid municipal waste, waste separation and recycling processes.

UV−Curable choline chloride and bromophenol red covalent functionalized chitosan antibacterial and pH−sensitive hydrogels

Food safety and food freshness issues have become important concerns for consumers and hydrogels with high antibacterial efficiency, low toxicity and pH−sensitive colorimetric intelligence are one of candidates to meet the requirement of food package and food spoilage monitoring. Nevertheless, hydrogels prepared only by assembling the ingredients with non−covalent interactions through time−consuming molding process usually encounter drawbacks such as relatively poor mechanical properties, stability and thermal stability, which always restrict their further applications. To overwhelm these shortcomings, UV−curable choline chloride (ChCl) and bromophenol red (BR) covalent functionalized antibacterial and pH−sensitive cross−linked hydrogels (UV−hydrogels) were developed in this paper. The UV−hydrogels possessed good thermal stability because the initiated thermal decomposition temperature (Td5) is in the range of 135.8–184.7 °C. The DMA analysis revealed that the UV−hydrogels are with good mechanical properties because the elongation at break is in the range of 117–525% and the tensile strength is in the range of 0.8–2.7 MPa. The UV−hydrogels with BR groups exhibited naked eye visible color variation from yellow to dark blue-green with the variation of the pH values from 2 to 14. The antibacterial efficiency of the UV−hydrogels against S. aureus, E. coli and M. albican increased with the increment of covalent−grafted ChCl amount. Cytotoxicity assay demonstrated that the UV−hydrogels are low toxicity against L929 cells. The experiment of monitoring freshness of beef denoted the UV−hydrogels have potential application in animal–derived high protein food packaging and freshness monitoring.

Developing and Testing High-Performance SHM Sensors Mounting Low-Noise MEMS Accelerometers.

Recently, there has been increased interest in adopting novel sensing technologies for continuously monitoring structural systems. In this respect, micro-electrical mechanical system (MEMS) sensors are widely used in several applications, including structural health monitoring (SHM), in which accelerometric samples are acquired to perform modal analysis. Thanks to their significantly lower cost, ease of installation in the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analyses show that MEMS can correctly detect modal frequencies, which are useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated, and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

3-D forward modeling of shale gas fracturing dynamic monitoring using the borehole-to-ground transient electromagnetic method

The borehole-ground transient electromagnetic method enhances the detection range and resolution by placing the transmitter electrode within the borehole, allowing for close-proximity excitation of subsurface targets and compensating for the shortcomings of traditional ground-based methods. Utilizing an unstructured vector finite element method combined with a second-order backward Euler variable time-stepping difference scheme and the MUMPS solver, we have achieved three-dimensional forward modeling simulation of the transient electromagnetic field for a borehole-ground electric source. Based on the validation of its accuracy, we analyzed the effectiveness of this method for dynamic monitoring of shale gas reservoir fracturing. Through forward modeling, we examined the characteristics of the radial electric field response during shale gas reservoir fracturing monitoring and evaluated the effectiveness of the borehole-ground TEM method in dynamic monitoring of shale gas reservoirs. The research results indicate that this method can meet the requirements for reservoir fracturing dynamic monitoring and has a promising application prospect.

Harbour porpoise (Phocoena phocoena) in the Wadden Sea World Heritage Site and requirements for trilateral monitoring

The harbour porpoise (Phocoena phocoena) is considered part of the ‘Outstanding Universal Value’ characterising the Wadden Sea World Heritage Site (WS WHS). The Trilateral Wadden Sea Plan aims to preserve the conservation status of the Trilateral Wadden Sea Cooperation Area, encompassing the WS WHS. The plan has specified two conservation targets for the harbour porpoise: (1) viable stocks and a natural reproduction capacity and (2) conservation of habitat quality for its conservation. To assess the current occurrence of the harbour porpoise in the Wadden Sea area, we collated and analysed data from regional and national research projects using telemetry, aerial surveys, strandings and passive acoustic monitoring, obtained over the years 1990–2020. The results illustrate that porpoises occur in both offshore and intertidal waters, showing seasonal movements and changes in local occurrence over time. Some porpoises displayed limited home ranges throughout the year, suggesting a possible residency for some of the animals using the Wadden Sea area. We also showed that methods, frequency and spatial coverage of monitoring activities vary among the countries Denmark, Germany and the Netherlands. We discuss the suitability of the different methods both regarding the challenges of monitoring in the complex Wadden Sea habitat as well as their ability to target the conservation aims of the WHS. We give several recommendations to assess the status of the species to meet the identified conservation aims.

Technologization of Legal Solutions in the field of International Trade Compliance

Modern technologies, and above all — information technologies, do play a significant role in navigating the complex regulatory and organizational landscape of compliance with international trade rules and management in the international trade system. The technologization of international trade compliance programs, internal compliance programs, the processes of systematization and automation of work with databases should be developed and implemented in all organizations engaged in international trade as an integral part of doing business and systematization of international trade operations. Taking into account the nature of international trade operations and their even minimal connection with specific States, in addition to clearly developing programs for compliance with international standards of trade and customs operations, the author substantiates a differentiated approach to international trade compliance, involving consideration of regulatory requirements of individual States and separate monitoring of compliance with the requirements of the State with which the relationship is associated. The author also dwells on a differentiated substantive approach to compliance procedures in trade using various software tools for monitoring and ensuring compliance in the absence, in most cases, of detailed international legal regulation (based on international treaties) of export-import operations.

In Situ Heterojunction-based PEC Sensor Coupled with LSPR for Sensitive Detection of Aflatoxin B1

To enhance the performance of photoelectrochemical (PEC) sensors, heterojunction construction is a workable technique. However, the interface defects inside the structure are often ignored. In this work, an innovative photoelectrochemical (PEC) sensor based on a “turn-off” PEC model was constructed using the synergistic effects of in situ growing heterojunction and local surface plasmon resonance (LSPR) to detect Aflatoxin B1 (AFB1) instantly. In situ heterojunctions were constructed based on bismuth-based perovskite, and the internal electric field spontaneously established during the growth process can effectively compensate for the interfacial defects and promote the separation and transfer of e−/h+ pairs. Moreover, the gold nanoparticles (Au NPs) LSPR effect can improve PEC performance by enhancing the light trapping ability of the material. The PEC sensor’s detecting area for AFB1 analysis is 10.0 fg/ml-100 ng ml−1, and the detection limit is 4.34 fg ml−1. Good stability, reproducibility, and selectivity underscore the sensor’s suitability for meeting the requirements of food quality monitoring.

EPri-MDAS: An efficient privacy-preserving multiple data aggregation scheme without trusted authority for fog-based smart grid

With the increasingly pervasive deployment of fog servers, fog computing extends data processing and analysis to network edges. At the same time, as the next-generation power grid, the smart grid should meet the requirements of security, efficiency, and real-time monitoring of user energy consumption. By utilizing the low-latency and distributed properties of fog computing, it can improve communication efficiency and user service satisfaction in smart grids. For the sake of providing adequate functionality for the power grid, various schemes have been proposed. Whereas, many methods are vulnerable to privacy leakage since the existence of trusted authority may increase the exposure to threats. In this paper, we propose the EPri-MDAS: an Efficient Privacy-preserving Multiple Data Aggregation Scheme without trusted authority based on the ElGamal homomorphic cryptosystem, which achieves both data integrity verification and data source authentication with the most efficient block cipher-based authenticated encryption algorithm. It performs well in energy efficiency with strong security. Especially, the proposed multidimensional aggregation statistics scheme can perform the fine-grained data analyses; it also allows for fault tolerance while protecting personal privacy. The security analysis and simulation experiments show that EPri-MDAS can satisfy the security requirements and work efficiently in the smart grid.

Muddy irrigation ditch understanding for agriculture environmental monitoring

Understanding an irrigation ditch plays an important role in intelligent agriculture environmental monitoring, especially in field environments where large chunks of ditches are particularly covered by various types of natural unstructured soil, vegetation and weeds. However, due to the diverse and unstructured muddy ditches, understanding them remains a challenge. Traditional approaches of understanding a scene from three-dimensional (3D) point clouds or multi-sensor fusion are energy intensive and computationally complex, making them quite laborious in application on a resource-constrained system. In this study, we propose a methodology to understand irrigation ditches and reconstruct them in a 3D scene, using only a resource-constrained monocular camera, without prior training. Spatial similar textures projections are extracted and clustered. Through geometric constraints of distribution and orientation, similar texture projections are refined and their corresponding surfaces are shaped. By contours and evidence lines, the ditch bottom surfaces are represented. Thus an irrigation ditch can be understood and reconstructed in a 3D environment, which can be used in agricultural automatic control system, agricultural robots, and precise agriculture. Unlike machine learning-based algorithms, the proposed method requires no prior training nor knowledge of the camera’s internal parameters such as focal length, field angle, and aperture. Additionally, pure geometric features make the presented method robust to varying illumination and colour. The percentage of incorrectly classified pixels was compared to the ground truth. Experimental results demonstrated that the approach can successfully elucidate irrigation ditches, meeting requirements in safety monitoring in an agriculture environment.

Cardiac Multi-Frequency Vibration Signal Sensor Module and Feature Extraction Method Based on Vibration Modeling.

Cardiovascular diseases pose a long-term risk to human health. This study focuses on the rich-spectrum mechanical vibrations generated during cardiac activity. By combining Fourier series theory, we propose a multi-frequency vibration model for the heart, decomposing cardiac vibration into frequency bands and establishing a systematic interpretation for detecting multi-frequency cardiac vibrations. Based on this, we develop a small multi-frequency vibration sensor module based on flexible polyvinylidene fluoride (PVDF) films, which is capable of synchronously collecting ultra-low-frequency seismocardiography (ULF-SCG), seismocardiography (SCG), and phonocardiography (PCG) signals with high sensitivity. Comparative experiments validate the sensor's performance and we further develop an algorithm framework for feature extraction based on 1D-CNN models, achieving continuous recognition of multiple vibration features. Testing shows that the recognition coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) of the 8 features are 0.95, 2.18 ms, and 4.89 ms, respectively, with an average prediction speed of 60.18 us/point, meeting the re-quirements for online monitoring while ensuring accuracy in extracting multiple feature points. Finally, integrating the vibration model, sensor, and feature extraction algorithm, we propose a dynamic monitoring system for multi-frequency cardiac vibration, which can be applied to portable monitoring devices for daily dynamic cardiac monitoring, providing a new approach for the early diagnosis and prevention of cardiovascular diseases.

Integrated monitoring method of flood free surface and surface velocity in a laboratory compound channel

River flooding can pose a significant threat to people's lives and properties on the floodplain. Due to the difficulty and potential danger of monitoring field river floods, laboratory experiments have become the main and key method for exploring flood propagation and evaluating potential flood risks. However, the complex three-dimensional flow state of floods in the compound channel makes current measurement techniques inadequate for meeting monitoring requirements. To this end, a new technique is developed in this study that can simultaneously monitor the flood free surface and the surface velocity in the laboratory compound channel. The developed measurement technique combines stereoscopy and the particle tracking velocimetry (PTV) method through the pixel coordinate fitting method, so that the coordinates of the tracer particles can be reconstructed in the three-dimensional state. This method can not only increase the basic data in the free surface construction but can also capture the complex three-dimensional flood flow behavior. The proposed technology was applied to measure the free surface of flood propagation in a laboratory compound channel. Water level, flow velocity, wave velocity, and wave height were simultaneously measured. The measurement accuracy was verified using wave probes, spatial planes, and fringe projection techniques. The results indicate that the water level measurement error is approximately 1.6 mm, and the flow velocity measurement error is around 3 %. The developed measurement system is simpler than previous methods based on light reflection or absorption. Most importantly, it can simultaneously measure both the flood free surface and surface velocity by only sowing tracer particles on the water surface. The current measurement technology offers a new tool for studying flood propagation in a laboratory compound channel.