Concept Of Monitoring Research Articles

Towards substitution of invasive telemetry: An integrated home cage concept for unobtrusive monitoring of objective physiological parameters in rodents.

This study presents a novel concept for a smart home cage design, tools, and software used to monitor the physiological parameters of mice and rats in animal-based experiments. The proposed system focuses on monitoring key clinical parameters, including heart rate, respiratory rate, and body temperature, and can also assess activity and circadian rhythm. As the basis of the smart home cage system, an in-depth analysis of the requirements was performed, including camera positioning, imaging system types, resolution, frame rates, external illumination, video acquisition, data storage, and synchronization. Two different camera perspectives were considered, and specific camera models, including two near-infrared and two thermal cameras, were selected to meet the requirements. The developed specifications, hardware models, and software are freely available via GitHub. During the first testing phase, the system demonstrated the potential of extracting vital parameters such as respiratory and heart rate. This technology has the potential to reduce the need for implantable sensors while providing reliable and accurate physiological data, leading to refinement and improvement in laboratory animal care.

Transdisciplinary research with respect to trust/confidence building by longer-term, near-field monitoring of a geological repository – part II

Abstract. In the disposal of radioactive waste in Germany, a question arises with regards to how confidence in the safety and thus also in the acceptability of a deep geological repository can be increased. One way to achieve this is to involve the interested public in the monitoring process of the repository, even after the emplacement phase and even in already backfilled areas of the repository. The transdisciplinary research project TRANSENS, specifically its work package TRUST, is investigating how the longer-term monitoring of a deep geological repository can lead to greater trust and confidence among the public. This scientific research is done in cooperation with a group of non-scientific actors chosen from the interested public, the so-called ArbeitsGruppeBevölkerung (AGBe). Results of a first workshop held together with the scientific research members and 12 non-scientific actors were already presented in Othmer et al. (2021). Building on this first workshop, a second workshop was held on the topic of repository monitoring. The results of this second workshop are presented in this article, focussing on the workshop process, the used methodology, and the insights gained. The second workshop consisted of three blocks, namely joint transdisciplinary research, concerns and reservations, and conflicting goals in the technical design of longer-term repository monitoring. After the workshop, an online questionnaire was sent out to AGBe members to gather their basic attitudes towards repository monitoring and the weighting of individual aspects of the monitoring concept. The results provided insights into the requirements of the AGBe for the design of socio-technical monitoring concepts that are considered trustworthy. The findings also revealed existing concerns and reservations, requirements for the technical design, and the relevance of individual aspects of the monitoring concept. Moreover, a change in attitude towards repository monitoring was observed, compared to the first workshop. In addition, the second workshop improved the experience in the application of various methods for transdisciplinary formats. It made progress in the transdisciplinary treatment of near-field monitoring topic as well because relevant information for the design of a socio-technical-based monitoring concept was developed. Further topics, such as decision-making based on technical monitoring data, were identified and will be dealt with using transdisciplinary formats during a third workshop.

Concept of Condition Monitoring for AC-DC Converter Output Capacitors via Discriminative Features

This paper discusses recent research on the condition mon- itoring (CM) approach for aluminium electrolytic capacitors (AEC) used in power electronics equipment such as switched- mode power supplies (SMPS). Capacitors are identified as the most critical component with the highest percentage of failure in AEC. CM offers a better paradigm for AEC due to its long- lasting ability (endurance). This study proposes accelerated life testing through electrical stress and long-term frequency testing for the AEC component. An experiment test bench was set up to monitor the critical electrical parameters such as dissipation factor (D), equivalent series resistance (ESR), capacitance (Cp), and impedance (Z), which serve as health indicators (HI) for the evaluation of the AECs. Time-domain features were extracted from the measured data, and the best features were selected using the correlation-based technique. This research contributes to developing a cost-effective CM approach for AECs used in power electronics equipment, which can reduce downtime and maintenance costs.

Spatio-temporal visual learning for home-based monitoring

This paper introduces a novel concept for Home-based Monitoring (HM) that enables robust analysis and understanding of activities towards improved caring and safety. Spatio-Temporal Visual Learning for HM (STVL-HM) is a novel method that learns from sensor data that is jointly represented in space and time in order to robustify the HM process. We propose a hybrid model based on a Convolution Neural Network (CNN) and Transformers. The CNN first learns the visual spatial features from various sensor data. The learned visual features are then fed into the transformer, which captures temporal information by observing the sensor status at various timestamps. STVL-HM has been tested using Kinetics-400, the real use case of human activity recognition scenario for HM data. The results reveal the clear superiority of the STVL-HM compared to the recent baseline HM solutions.

New concept of permafrost degradation monitoring based on photonics technologies: Case study from Calypsostranda (Bellsund, Svalbard)

AbstractGround temperature measurements are crucial for a better understanding of changes in the natural environment, especially in the Arctic. Previous measurement systems provided accurate measurements; however, their most significant disadvantage was the relatively low spatial resolution, including in the vertical profile. The aim of this work was to develop and initially validate a new, original temperature measurement system based on the photonic sensing technique of optical frequency‐domain reflectometry (OFDR). The system consists of a fibre‐optic sensor, an interrogator, and an automatic data acquisition system. Such fibre‐optic sensors allow a significant increase in spatial resolution. Data on precise temperature distribution in the ground profile will allow for a detailed determination of the changes in the thickness of the permafrost active layer (PAL) and, as a consequence, a better description of the current state of the permafrost and the layers above it in relation to their progressive degradation. In the longer term, it will make a better prediction of the pace of possible changes in the polar environment and will open up previously unavailable opportunities in the field of climate change monitoring and forecasting.

ParkinsonGoesDTx – a novel gait monitor concept triggers treatment decisions in Parkinson’s disease

ParkinsonGoesDTx – a novel gait monitor concept triggers treatment decisions in Parkinson’s disease

Fluid migration pathways to groundwater in mature oil fields: Exploring the roles of water injection/production and oil-well integrity in California, USA

Mature oil fields potentially contain multiple fluid migration pathways toward protected groundwater (total dissolved solids, TDS, in nonexempted aquifer <10,000 mg/L) because of their extensive development histories. Time-series data for water use, fluid pressures, oil-well construction, and geochemistry from the South Belridge and Lost Hills mature oil fields in California are used to explore the roles of injection/production of oil-field water and well-integrity issues in fluid migration. Injection/production of oil-field water modified hydraulic gradients in both oil fields, resulting in chemical transport from deeper groundwater and hydrocarbon-reservoir systems to aquifers in the oil fields. Those aquifers are used for water supply outside the oil-field boundaries. Oil wells drilled before 1976 can be fluid migration pathways because a relatively large percentage of them have >10 m of uncemented annulus that straddles oil-well casing damage and/or the base of groundwater with TDS <10,000 mg/L. The risk of groundwater-quality degradation is higher when wells with those risk factors occur in areas with upward hydraulic gradients created by positive net injection, groundwater withdrawals, or combinations of these variables. The complex changes in hydrologic conditions and groundwater chemistry likely would not have been discovered in the absence of years to decades of monitoring data for groundwater elevations and chemistry, and installation of monitoring wells in areas with overlapping risk factors. Important monitoring concepts based on results from this and other studies include monitoring hydrocarbon-reservoir and groundwater systems at multiple spatiotemporal scales and maintaining transparency and accessibility of data and analyses. This analysis focuses on two California oil fields, but the methods used and processes affecting fluid migration could be relevant in other oil fields where substantial injection/production of oil-field water occurs and oil-well integrity is of concern.

Guided wave ultrasonic feature determination in Type IV composite overwrapped pressure vessels towards the digital twin

The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.

МОНІТОРИНГ ТА ЕКСПЕРТНО-АНАЛІТИЧНА ОЦІНКА НАДІЙНОСТІ ТЕПЛОІЗОЛЯЦІЙНОЇ ОБОЛОНКИ БУДІВЕЛЬ

The current state of research on monitoring and expert-analytical assessment of the reliability of the thermal insulation envelope of buildings is analyzed. It was established that the reliability of the thermal insulation shell is determined by organizational and technological factors that affect the probability of thermal failure of the enclosing structures. A structural diagram of the concept of monitoring is proposed for the purpose of developing mechanisms for ensuring the reliability of the thermal insulation envelope of buildings. The structural scheme of the concept of monitoring the reliability of the thermal insulation shell of buildings assumes that the components of the target monitoring program are technical diagnostics based on the results of experimental thermal imaging survey, analysis of the risks of thermal failure of enclosing structures and the development of an expert analytical assessment of the reliability of the thermal insulation shell of buildings.

A free-floating structure triboelectric nanogenerator based on natural wool ball for offshore wind turbine environmental monitoring

The marine distributed wireless sensor network system can promote the development of offshore wind turbine environmental monitoring. However, traditional ocean sensors and large power generation equipment are hard to meet the requirements of distributed sensor networks. Hence, we proposed a free-floating structure triboelectric nanogenerator (FF-TENG) based on the all-in-one ocean energy harvesting and sensing device concept for offshore wind turbine environmental monitoring. The FF-TENG device follows the integrated structure design of the sphere and floating body, which brings high wave energy capture efficiency and high wave sensing sensitivity. In this design, the wool ball plays the role of the triboelectric material owning to excellent positive triboelectricity. And the lightweight characteristic of the wool ball endows the FF-TENG device with fine wave-following properties in the ocean environment. In rolling working mode, when the motion amplitude and frequency are 5 cm and 4.5 Hz, the instantaneous open-circuit voltage (Voc) and short-circuit current (Isc) of a single FF-TENG can arrive at 462 V and 15.5 μA, respectively. The transferred charge (Qsc) of a single FF-TENG can reach 107 nC. According to the results, the FF-TENG device can achieve a 4.26 times energy harvesting effect compared with nine-independent spherical TENG. Moreover, the Isc of FF-TENG represents a nicely linear relationship with the swing angle (minimum frequency: 0.2 Hz), which indicates that the FF-TENG can monitor the change of wave frequency and amplitude. This research provides a new path for all-in-one ocean energy harvesting and sensing device in offshore wind turbine environmental monitoring.

Uninterrupted real-time cerebral stress level monitoring using wearable biosensors: A review.

Stress is the major unseen bug for the health of humans with the increasing workaholic era. Long periods of avoidance are the main precursor for chronic disorders that are quite tough to treat. As precaution is better than cure, stress detection and monitoring are vital. Although there are ways to measure stress clinically, there is still a constant need and demand for methods that measure stress personally and in an ex vitro manner for the convenience of the user. The concept of continuous stress monitoring has been introduced to tackle the issue of unseen stress accumulating in the body simultaneously with being user-friendly and reliable. Stress biosensors nowadays provide real-time, noninvasive, and continuous monitoring of stress. These biosensors are innovative anthropogenic creations that are a combination of biomarkers and indicators like heart rate variation, electrodermal activity, skin temperature, galvanic skin response, and electroencephalograph of stress in the body along with machine learning algorithms and techniques. The collaboration of biological markers, artificial intelligence techniques, and data science tools makes stress biosensors a hot topic for research. These attributes have made continuous stress detection a possibility with ease. The advancement in stress biosensing technologies has made a great impact on the lives of human beings so far. This article focuses on the comprehensive study of stress-indicating biomarkers and the techniques along with principles of the biosensors used for continuous stress detection. The precise overview of wearable stress monitoring systems is also sectioned to pave a pathway for possible future research studies.

Review of Remote Sensing Approaches and Soft Computing for Infrastructure Monitoring

During the past few decades, remote sensing has been established as an innovative, effective and cost-efficient option for the provision of high-quality information concerning infrastructure to governments or decision makers in order to update their plans and/or take actions towards the mitigation of the infrastructure risk. Meanwhile, climate change has emerged as a serious global challenge and hence there is an urgent need to develop reliable and cost-efficient infrastructure monitoring solutions. In this framework, the current study conducts a comprehensive review concerning the use of different remote-sensing sensors for the monitoring of multiple types of infrastructure including roads and railways, dams, bridges, archaeological sites and buildings. The aim of this contribution is to identify the best practices and processing methodologies for the comprehensive monitoring of critical national infrastructure falling under the research project named “PROION”. In light of this, the review summarizes the wide variety of approaches that have been utilized for the monitoring of infrastructure and are based on the collection of remote-sensing data, acquired using the global navigation satellite system (GNSS), synthetic aperture radar (SAR), light detection and ranging (LiDAR) and unmanned aerial vehicles (UAV) sensors. Moreover, great emphasis is given to the contribution of the state-of-the-art soft computing methods throughout infrastructure monitoring aiming to increase the automation of the procedure. The statistical analysis of the reviewing publications revealed that SARs and LiDARs are the prevalent remote-sensing sensors used in infrastructure monitoring concepts, while regarding the type of infrastructure, research is orientated onto transportation networks (road and railway) and bridges. Added to this, deep learning-, fuzzy logic- and expert-based approaches have gained ground in the field of infrastructure monitoring over the past few years.

Monitoring concept for powder flow monitoring in Laser-Directed Energy Deposition (L-DED) process based on flexible piezoelectric sensors

Background: The quality of powder-blown Laser-Directed Energy Deposition (L-DED) is mainly governed by the energy density per unit of mass employed to melt the material. In most of the previous works, the focus in process monitoring and control was on the control of energy input, by controlling the properties of the melt pool. However, the powder mass input is as important to monitor as the energy input, in order to preserve the equilibrium of the process. Methods: In this paper, the authors present the first test results of the Pyzoflex® sensor for powder flow monitoring in L-DED using real powder feeding system in the robot-based laser-processing cell. The sensor was tested against the powder projected from the powder feeder under typical flow regimes and the real-time measurements were taken using a specifically designed software tool. Results: The graphical representation of the registered sensor signals are clearly correlated with the powder flow values set at the powder feeder, which demonstrates that the piezoelectric sensors can detect the powder flow with elevated precision in real time. Conclusions: The first laboratory tests of flexible printed piezoelectric sensors demonstrate that they are fast and precise in the powder flow measurement, but that more effort must be invested in the robustness of the measurement setup as well as in clearing and stabilization of the registered signal.

Concept for the Real-Time Monitoring of Molecular Configurations during Manipulation with a Scanning Probe Microscope.

A bold vision in nanofabrication is the assembly of functional molecular structures using a scanning probe microscope (SPM). This approach requires continuous monitoring of the molecular configuration during manipulation. Until now, this has been impossible because the SPM tip cannot simultaneously act as an actuator and an imaging probe. Here, we implement configuration monitoring using experimental data other than images collected during the manipulation process. We model the manipulation as a partially observable Markov decision process (POMDP) and approximate the actual configuration in real time using a particle filter. To achieve this, the models underlying the POMDP are precomputed and organized in the form of a finite-state automaton, allowing the use of complex atomistic simulations. We exemplify the configuration monitoring process and reveal structural motifs behind measured force gradients. The proposed methodology marks an important step toward the piece-by-piece creation of supramolecular structures in a robotic and possibly automated manner.

Weld quality characterization by vibration analysis for ultrasonic metal welding processes

Ultrasonic metal welding is an efficient, solid-state welding process that is well established in the production of electrical equipment. However, isolated and untraceable failures occasionally occur in industrial production processes. According to the state of the art, these failures are due to a multitude of influencing variables, such as material and surface condition of the joining partners, as well as tool and fixture wear. This study presents quality prediction models based on measurements of mechanical vibrations of the welding machine using laser triangulation sensors, sonotrode penetration depth measurements, and machine internal welding power signals. The acquired data are processed and transformed into a random forest model to estimate the shear strength of the welds. The robustness of the prediction model has been successfully validated by welding experiments with significant external disturbances, such as surface roughness, contamination and material hardness. Within the framework of this study, the development of a stable and industrially applicable concept for process monitoring is demonstrated with a regression model that achieves a mean relative estimation error of 4.30% and a R2 value of 0.964. Furthermore, a classification model that determines the external disturbances for the individual welds was successfully validated, achieving a micro F1 value of 94% and a macro F1 value of 95%.

The information system concept for thermal monitoring of a spent nuclear fuel storage container

The paper notes that the most common way of handling spent nuclear fuel (SNF) of power reactors is its temporary long-term dry storage. At the same time, the operation of the dry spent fuel storage facilities almost never use the modern capabilities of information systems in safety control and collecting information for the next studies under implementation of aging management programs. The author proposes a structure of an information system that can be implemented in a dry spent fuel storage facility with ventilated storage containers. To control the thermal component of spent fuel storage safety, a database structure has been developed, which contains 5 tables. An algorithm for monitoring the thermal state of spent fuel was created for the proposed information system, which is based on the comparison of measured and forecast values of the safety criterion, in which the level of heating the ventilation air temperature was chosen. Predictive values of the safety criterion are obtained on the basis of previously published studies. The proposed algorithm is an implementation of the information function of the system. The proposed information system can be used for effective thermal monitoring and collecting information for the next studies under the implementation of aging management programs for spent fuel storage equipment, permanent control of spent fuel storage safety, staff training, etc.

Anti-Spike Antibody Responses in Allogeneic Stem Cell Transplant Recipients to Two Doses of COVID-19 mRNA Vaccination: A Retrospective, Single-Center Analysis.

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients were excluded from the initial SARS-CoV-2 mRNA vaccination efficacy trials. Suboptimal vaccine responses have been reported in immunocompromised cohorts such as patients with solid tumors or hematologic malignancies, suggesting the need for additional research. Widespread data on the antibody responses and vaccine efficacy in allo-HSCT recipients is limited. In our single-center, retrospective study, we analyzed the anti-spike IgG antibody responses in 75 allo-HSCT recipients who received a series of two doses of mRNA vaccination. We collected data on previous COVID-19 infection, B and T lymphocyte recovery, donor types, graft-vs.-host disease (GVHD), and immunosuppressive medications at the time of vaccination. With the original variant, a cutoff of 4,160 arbitrary units (AU)/mL has been correlated with a 0.95 probability of a viral neutralization. We also examined the number of allo-HSCT recipients who achieved this conservative threshold. To our knowledge, no correlate exists for the currently prevalent Omicron variant and viral neutralization. Despite 29.3% (22/75) of patients being on systemic immunosuppressive medications due to chronic GVHD, positive antibody responses > 50 AU/mL were seen in 96% of patients. However, only 48% (36/75) of patients were above the neutralizing antibody threshold. Those with previous COVID-19 infection had significantly higher antibody responses. Although encouraging, the variability of the responses underscores the concept of ongoing antibody monitoring as well as consideration of additional doses of the COVID-19 vaccine in this cohort.

A clinical case of using the concept of monitoring in the treatment of a gunshot defect of the soft tissues of the knee joint

Rapid rehabilitation and restoration of the function of damaged anatomical areas in the military is the main goal of military medicine. In the case of gunshot wounds of the knee joint with defects of soft tissues, one of the optional methods of reconstructive and plastic "closure" is the usage of a propeller flap. The clinical case represents a mine-explosive wound of the lower extremities with a defect of the soft tissues of the lateral aspect of the right knee joint in a serviceman of the Ukrainian Armed Forces as a result of artillery shelling in the east of Ukraine in November 2022. There was an isolated shrapnel tangential non-penetrating wound on the lateral aspect of the right knee joint with a soft tissue defect measuring 7.2x3.2-1.0 cm. The aim of the work was to study the thermographic and sonographic features of soft tissue perfusion after gunshot injuries of the lower extremities and on the basis of the temperature dynamics data from the wound surface in combination with the sonographic examination of the vessels to determine the rationality and relevance in the reconstruction of defects of the lower extremities by propeller tactics. Reconstruction with flap with a perforating vessel as the "key" of LSGA (lateral superior genicular artery) and a dynamic multimodal concept (DMT) with the use of audio doppler in the pre-, intra- and postoperative period) with closure of the defect due to a rotary perforating flap with supplying was carried out. During the entire period of treatment, of the injured the temperature background from the surface of the flap was followed up using FLIR C2, and sonographic changes in blood flow were monitored in the projection of the LSGA location. We came to the conclusion that applying the technique of flaps on perforating vessels, several goals are tactically achieved: restoration of the completeness and function of the damaged area, reduction of complications in the recipient and donor areas. Thus, the propeller flap can be classified as a primary option for "replacemen t" of tissues among the restorative tactics of the damaged area of the lower extremities caused by a gunshot origin.

In Situ IoT Development and Application for Continuous Water Monitoring in a Lentic Ecosystem in South Brazil

The monitoring of water resources through conventional methods, related to a manual process when performing the sample collection, followed by laboratory analysis, presents some difficulties concerning the logistics of the process, such as access to the interior of a lake, in addition to often being based on a small number of samples. The concept of the internet of things (IoT) is used here to collect data through five parametric probes contained in the floating station located inside a lake and inform them in real time continuously. The main objective of this research is to demonstrate the applicability of the IoT concept in the continuous monitoring of water in a lentic environment. Therefore, it is necessary to develop a tool for this. Upon reaching this objective, the advantages observed in this research confirmed that the IoT paradigm is an essential resource, justifying a natural tendency to establish itself when there is a need to collect data efficiently and continuously. Furthermore, the experimental result proves the IoT concept’s efficiency, agility, and reliability to environmental issues, especially regarding the most significant natural and indispensable resource for the planet, water.

Above management: Scale development and empirical testing for public opinion monitoring of marine pollution

The marine eco-environment is receiving increasing attention globally, and the rapid development of network technology has enabled individuals to express their dissatisfaction and appeals for marine pollution through public engagement measures, particularly on network platforms. As a result, chaotic public opinions and information dissemination on marine pollution are becoming more prevalent. Previous studies have mainly focused on practical measures of marine pollution management, with limited exploration of how to prioritize the monitoring of public opinions on marine pollution. This study aims to develop a comprehensive and scientific measurement scale for public opinion monitoring on marine pollution by defining its implications and dimensions, verifying its reliability, validity, and predictive validity. The research defines the implications of public opinion monitoring regarding marine pollution based on previous literature and experience, using empathy theory as an entry point. The study uses text analysis to explore the internal laws of topic data on social media sites (n = 12,653), forming a theoretical conception of public opinion monitoring composed of three Level 1 dimensions (empathy arousal, empathy experience, and empathy memory). Based on research conclusions and related measurement scales, the study compiles the measurement items to develop the initial scale. Finally, the study verifies the scale reliability and validity (n1 = 435, n2 = 465) and predictive validity (n = 257). Results show that the public opinion monitoring scale has good reliability and validity, and the three Level 1 dimensions have a high level of interpretation for public opinion monitoring and good predictive validity. This research expands the application scope of public opinion monitoring theory and emphasizes the significance of public opinion management on the basis of traditional management research, increasing marine pollution managers' attention to the public domain of the network. Furthermore, it provides public opinion monitoring instruments for marine pollution through scale development and empirical research, reducing the occurrence of public trust crises and creating a stable and harmonious network environment.