Monitoring and diagnostics

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EMPLOYING OPTICAL MEASUREMENTS FOR MONITORING AND DIAGNOSTICS OF COMBUSTION PROCESS IN INDUSTRIAL CONDITIONS

EMPLOYING OPTICAL MEASUREMENTS FOR MONITORING AND DIAGNOSTICS OF COMBUSTION PROCESS IN INDUSTRIAL CONDITIONS

The use of biomass in industrial plants usu- ally comes down to supplying it in solid form into a powdered-fuel burner, with prior pulverization in a mill or in the course of gasification and com- bustion of raw biogas in special burners installed in a boiler. It should be noted that the energy pa- rameters are variable, which in turn impacts the combustion process. In order to increase the effi- ciency of coal combustion and its co-combustion with biomass, especially in conjunction with low- carbon combustion technologies, it is necessary to employ monitoring and diagnostics systems. This is especially vital with high variability of boiler operation and its regulation when the ef- ficiency drops below 50%.

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A flexible and low power telemetric sensing and monitoring system for chronic wound diagnostics

A flexible and low power telemetric sensing and monitoring system for chronic wound diagnostics

The most effective and economical treatment of wounds is covering them with a suit- able dressing or bandage in order to protect damaged skin from external effects such as microorganism attacks [9]. For certain chronic wounds such as venous leg ulcers, appropriate compression bandages are applied to increase the healing rate [10,11]. These bandages may be retention (low pressure), light support (medium pressure) or compression (high pressure) bandages. The method of applying compression bandages on the affected limb is very important as the efficacy and maintenance of sub-bandage pressure depends on it [12]. Compression bandages can produce a pressure up to 60 mmHg at the ankle (extra high pressure), while the recommended high pressure value is 40 mmHg at the ankle [10,12]. Depending on the applied pressure range and the type of bandage used, the sub-bandage pressure may vary significantly during the physical movement of the patient, thus affecting the healing rate [13]. In addition to compression bandages, healing rates may also be increased by managing moisture pro- duced by the wound (exudate) through moisture-retentive dressings such as Anasept ® (hydrogel) and Hydrocolloids [14,15] for wounds with low exudate and dressings such as Allevyn ® (foam) or Melgisorb ® (calcium alginate) for wounds with moderate to high exudate. In addition to moisture levels, the temperature and pH under the dressing may change as a result of an infection [16,17]. Unfortunately, these parameters associ- ated with the dressings are not currently monitored in clinical practice. There is an op- portunity for advanced sensor technologies to contribute to improved wound monitoring and diagnostics.

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Social network diagnostics: a tool for monitoring group interventions

Social network diagnostics: a tool for monitoring group interventions

In this study we calculate several individual and net- work level metrics, which are widely used to describe networks [3,5], and show how the information contained in this analysis can be used by intervention staff during program implementation to better integrate members into the group. Table 1 summarizes the diagnostics we propose to be most informative for program monitoring, along with suggested thresholds. We use both individual- and network-level metrics. The individual metrics are: iso- lates, degree, and reciprocity; and the network metrics are sub-groups, density, centralization, transitivity, and cohe- sion. There are many other metrics available in SNA soft- ware (e.g., UCINET, Pajek, Statnet), and this proposed list is not meant to be exhaustive or exclusive, merely a rec- ommendation of the ones most likely to have immediate effects on individual and group processes as well as those for which intervention recommendations could be made, guided by basic research on network properties.

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Integration of On Board Diagnostics For Vehicular Pollution Monitoring Using Internet of Things (IoT)

Integration of On Board Diagnostics For Vehicular Pollution Monitoring Using Internet of Things (IoT)

Abstract— This paper presents a method for monitoring and control of vehicular emission exhaust using Internet of Things and On-Board Diagnostics. Pollution is the major threat faced today which causes Global warming and Environmental degradation and Quality of the Air is affected in huge. Major capital cities experience such problem due to the huge traffic at each node and roadside. Hence implementation of OBD (On-Board Diagnostics) and Internet of Things (IoT) enables effective monitoring and control of pollution on periodic basis. OBD involves vehicle information being displayed in the monitor screen of the vehicle owner so that engine health condition is known to the customer and the condition is kept under check. IoT is a system of interrelated computing devices, objects and people which are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-machine interaction. The main aim of this project is to protect the environment from the risk of harmful gases release, through pollution prevention by constant monitoring through Networking.

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IoT System for Monitoring and Diagnostics of Engine

IoT System for Monitoring and Diagnostics of Engine

The data required for generating the health report consists of parameter values (outputs of in-built sensor) of different systems inside the vehicle. This data can be obtained using the OBD-II protocol which is followed by the vehicle manufactured after 1996. It uses Lab VIEW as platform that has automotive diagnostic command set tool kit which helps in building up the software required to communicate with the vehicle’s ECU through OBD-II system. OBD-II technology has been created to diagnose Vehicle’s condition. OBD-II scanner plugg to OBD-II port or usually called Data Link Connector (DLC), and after that it sends the diagnostics to Raspberry Pi. Compared from another Microcontrollers, Arduino, Raspberry Pi are chosen because it sustains the application to receive Real-time diagnostics, process the diagnostics and send command to automobiles at the same Time, rather than Arduino that must hold for another process finished to run another process.

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The vector population monitoring tool (VPMT): high-throughput DNA-based diagnostics for the monitoring of mosquito vector populations

The vector population monitoring tool (VPMT): high-throughput DNA-based diagnostics for the monitoring of mosquito vector populations

A key component of most malaria control strategies is e ff ective control of the mosquito vector. Indeed the World Health Organization supports vector control as the most generally effective measure to prevent malaria transmission and promotes a strategic approach to vector control known as Integrated Vector Management (IVM) [1]. IVM is defined as “a rational decision-making process for the optimal use of resources in the management of vector populations, so as to reduce or interrupt transmission of vector-borne diseases” [1]. An essential part of IVM is the gathering of contem- porary information on vector populations. Data, such as which mosquito species occur in the local population, their infection status, and whether they are resistant to insecticides are essential for effective intervention strategies. This type of monitoring requires high-throughput sensitive diagnostic assays, and a large number of di ff erent methods have been

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On-line transformer condition monitoring through diagnostics and anomaly detection

On-line transformer condition monitoring through diagnostics and anomaly detection

As transformers reach the end of their design lives, utili- ties wishing to minimize replacement costs must handle the conflicting requirements of retaining plant items in service for as long as possible, whilst avoiding failures in service. The application of various on-line monitoring and diagnostic techniques can aid in the identification of faults within the transformer [1], highlighting the need for maintenance or removal from service. Increasing this level of monitoring, by augmenting various monitoring techniques, can provide a fuller picture of plant health, increasing the certainty when a fault is identified and thus helping to anticipate imminent failure.

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The Vector Population Monitoring Tool (VPMT): High-Throughput DNA-Based Diagnostics for the Monitoring of Mosquito Vector Populations

The Vector Population Monitoring Tool (VPMT): High-Throughput DNA-Based Diagnostics for the Monitoring of Mosquito Vector Populations

Copyright © 2010 Chris Bass et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Regular monitoring of mosquito vector populations is an integral component of most vector control programmes. Contemporary data on mosquito species composition, infection status, and resistance to insecticides are a prerequisite for effective intervention. For this purpose we, with funding from the Innovative Vector Control Consortium (IVCC), have developed a suite of high- throughput assays based on a single “closed-tube” platform that collectively comprise the “Vector Population Monitoring Tool” (VPMT). The VPMT can be used to screen mosquito disease vector populations for a number of traits including Anopheles gambiae s.l. and Anopheles funestus species identification, detection of infection with Plasmodium parasites, and identification of insecticide resistance mechanisms. In this paper we focus on the Anopheles-specific assays that comprise the VPMT and include details of a new assay for resistance to dieldrin Rdl detection. The application of these tools, general and specific guidelines on their use based on field testing in Africa, and plans for further development are discussed.

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REAL-TIME MONITORING AND ASSESSMENT OF CIRCUIT BREAKER OPERATIONS FOR DIAGNOSTICS AND CONTROL APPLICATIONS

REAL-TIME MONITORING AND ASSESSMENT OF CIRCUIT BREAKER OPERATIONS FOR DIAGNOSTICS AND CONTROL APPLICATIONS

CBMA provides better understanding of the condition and operating performance of each individual breaker by monitoring and analyzing expanded set of analog and digital signals from circuit breaker control circuitry. The advanced signal processing algorithms and knowledge base of the expert system implemented in the analysis software, significantly improve the reliability and consistency of the analysis results. Thanks to the fast and low cost CBM devices, new monitoring and control system described in this paper, enables permanent, real time monitoring of status and performance of circuit breakers for the entire network. In the first section of the paper, architecture of the whole system and basic processing algorithm are described. Second section explains the structure and basic functions of the hardware part of the system. Focus of the following section is on the organization of analysis software of the CBMA system. Basic building blocks, such as signal processing and expert system are elaborated and brief overview of knowledge base rules is given. At the end, an example of the stuck breaker case is illustrated with waveforms of relevant signals and expert system rules involved in problem detection process. A B S T R A C T

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Monitoring Viral Genetic Variation as a Tool To Improve Molecular Diagnostics for Mumps Virus

Monitoring Viral Genetic Variation as a Tool To Improve Molecular Diagnostics for Mumps Virus

Whole-genome sequencing. Two MuV samples from the 2017 New Zealand outbreak were col- lected as follows: sample MuVi/NewPlymouth.NZL/30.17[G] from New Plymouth, North Island, was an oropharynx swab collected on 24 July 2017 from an unvaccinated 19-year-old case; and sample MuVi/Dunedin.NZL/32.17[G] from Dunedin, South Island, was collected from a site not stated on 11 August 2017 from a 21-year-old case mentioned to have received the MMR vaccine at ages 15 months and 11 years. These samples were isolated in Vero E6/hSLAM cells (passage 1). Cultured virus was first treated with 75 units of Benzonase (Sigma-Aldrich/Merck, St. Louis, MO, USA) for 2 h at 37°C to remove human and African green monkey nucleic acids, and capsid-protected viral nucleic acids were extracted from cell culture supernatants using the NucliSENS easyMag instrument (bioMérieux, France). Whole- genome sequence data of the two New Zealand mumps virus isolates (strain MuVi/NewPlymouth.NZL/ 30.17[G], GenBank accession no. MG765426; and strain MuVi/Dunedin.NZL/32.17[G], GenBank accession no. MG765427) were generated using Nextera XT library preparation and Illumina sequencing (San Diego, CA, USA). In brief, first-strand cDNA was synthesized with Transcriptor reverse transcriptase (Roche Diagnostics, Basel, Switzerland) for 1 h at 60°C using random-hexamer primers. Second-strand cDNA was generated using the NEBNext Ultra II nondirectional RNA second-strand synthesis module (NEB, Ipswich, MA, USA). The resulting double-stranded cDNA was purified using AMPure XP beads (Beckman Coulter, Brea, CA, USA) and converted into Illumina sequencing libraries using the Nextera XT library preparation kit. Sequencing was done on a MiSeq instrument (Illumina, San Diego, CA, USA) using v2 chemistry (2 ⫻ 150 bp). CLC Genomics Workbench version 9.5 (Qiagen, Hilden, Germany) was used for assembly, reference mapping, and sequence analysis.

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IOT System for Monitoring and Diagnostics of Engine

IOT System for Monitoring and Diagnostics of Engine

The OBD-II system allows for monitoring of most electrical system on the vehicle. The OBD-II standard specifies the type of diagnostic connector and its pinout, the electrical signaling communication protocols available, and the messaging format. It also provides a prospect list of vehicle parameters to monitor along with how to encode the data for each. Monitored items include speed, revolutions per minute, ignition voltage, and coolant temperature. This system also informs a technologist when an individual cylinder has a misfire. The OBD-II standard also gives an extensible list of Data TCs. As a resolution of this standardization, a single device can enquiry the on-board computer(s) in any vehicle.

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IoT System for Monitoring and Diagnostics of Engine

IoT System for Monitoring and Diagnostics of Engine

The data required for generating the health report consists of parameter values (outputs of in-built sensor) of different systems inside the vehicle. This data can be obtained using the OBD-II protocol which is followed by the vehicle manufactured after 1996. It uses Lab VIEW as platform that has automotive diagnostic command set tool kit which helps in building up the software required to communicate with the vehicle’s ECU through OBD-II system. OBD-II technology has been created to diagnose Vehicle’s condition. OBD-II scanner plugg to OBD-II port or usually called Data Link Connector (DLC), and after that it sends the diagnostics to Raspberry Pi. Compared from another Microcontrollers, Arduino, Raspberry Pi are chosen because it sustains the application to receive Real-time diagnostics, process the diagnostics and send command to automobiles at the same Time, rather than Arduino that must hold for another process finished to run another process.

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Diagnostics and Monitoring of COVID-19 Infection – Current Understanding

Diagnostics and Monitoring of COVID-19 Infection – Current Understanding

Sputum samples appear more reliable for RT-PCR and, since viral RNA concentration declines more slowly than in swabs, it can be detected till three weeks after symptoms appearance. Saliva samples are promising non-invasive specimens with high sensitivity for viral RNA detection as well as for the recovery of viable viral particles (29,33). Together with nasal samples, self-collected saliva samples are the most promising target in the development of point-to-care (POC) devices for the fast diagnosis and surveys aimed at monitoring SARS-CoV2 infection spread (34). For patients with pneumonia, lower respiratory tract specimens, such as sputum and bronchoalveolar lavage fluid, are tested in addition to upper respiratory samples. Viral RNA-based detection in the respiratory samples is the most suitable test also for the identification of asymptomatic carriers, which appear to have a prolonged viral shedding in respiratory tract compared to COVID-19 patients (35). Summarizing, respiratory samples are usually very reliable for confirming the infection in the early stage of disease. However, with its advancement, shedding of viral RNA in pharyngeal area declines the fastest, particularly in patients with mild symptoms, and disease can remain undetected in the majority of the cases if tested by RT-PCR one week after symptom onset (24,35,36).

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Internet of Things and Blockchain-Based Framework for Coronavirus (COVID-19) Disease

Internet of Things and Blockchain-Based Framework for Coronavirus (COVID-19) Disease

The WHO brings closely researchers from around the globe including government officials to promote the cycle of research and innovation and create international policies to control the transmission of the coronavirus epidemic and increase support for everyone infected. Testing COVID-19 might be possible through mobile in the future. Testing HIV, malaria and Tuberculosis are already being done through mobile. People would be used to identify and check substances, antibodies produced against viruses. This could appear far-fetched however the mobile can be used to diagnose patient conditions. Smartphones could be converted into instruments to easily detect a range of disease-causing agents like viruses, contaminants, and diseases. This framework provides a range of flexibility goods and services. The presence in remote diagnostics and monitoring, patient data, medical informatics, sensitive data health, public health information gathering, healthcare professionals, and information technology. The number of influences of health technology differs significantly depending on the sector. Its performance of mobile healthcare services is dependent on the level of development and the functionality of each service industry.

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Possibility of Use of Noise Analysis for Identification of Reactor Conditions during Accidents

Possibility of Use of Noise Analysis for Identification of Reactor Conditions during Accidents

motivated by the need of early identification of devia- tions form the normal operating conditions. With this respect, the reactor noise diagnostics is part of the de- fense-in-depth level-one technical features. The noise diagnostic tools and techniques are implemented at the nuclear power plants in different extents; some plants use the noise diagnostics rather limited, e.g. the loose part monitoring [8] or sensor-diagnostics [9], some other plants, e.g. the Paks NPP, operate complex reactor noise diagnostic systems [10]. The noise diagnostic methods can also be applied for specific reactor-physics purposes [11]. There were some attempts to apply the noise diag- nostic methods for controlling the reactor conditions ra- ther far from normal operation [12]. Essential progress has been made in the area of identification of thermo- hydraulic anomalies via noise diagnostics. Most impor- tant achievements of these researches, applicable for the accident process diagnostics will be referred below.

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Application of the Seebeck   effect for the Monitoring of the Neutron Embrittlement and Low-cycle fatigue   in Nuclear Reactor Technology (D585)

Application of the Seebeck effect for the Monitoring of the Neutron Embrittlement and Low-cycle fatigue in Nuclear Reactor Technology (D585)

Extensive finite element calculations have shown, that the change of SC measured is related to the small part of the specimens where the temperature gradient is applied. The calculations also have shown the influence of the ambient temperature on both, the amount of the measured TEP and the location of its generation. For inhomogeneous materials this might lead to misinterpretations of the results. However, the method has a potential to be improved by using a thermoelectric scanning microscope as proposed in this report. Such a microscope would be able to produce 3- dimensional plots in which the distribution of inhomogeneities and localized damage could be visualized. As far as we know, this method is new and might open a promising possibility for monitoring of material degradation.

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Ultrasound and Clinical Preoperative Characteristics for Discrimination Between Ovarian Metastatic Colorectal Cancer and Primary Ovarian Cancer: A Case-Control Study

Ultrasound and Clinical Preoperative Characteristics for Discrimination Between Ovarian Metastatic Colorectal Cancer and Primary Ovarian Cancer: A Case-Control Study

In this study, previous treatment for CRC was the strongest clinical variable; if this is present, and there is an ovarian tumor, metastasis should be suspected, regardless of ultrasound parameters. All but one patient who had previously had CRC underwent chemotherapy, and hence had high-risk disease at diagnosis. On the ultrasounds, ovarian mCRC was mostly solid or multilocular-solid. Compared with primary OC, mCRC tumors more often had signs of necrosis in the solid components; less often, they had irregular internal walls, if locular, and were more mobile. Those with ovarian mCRC who had not previously undergone treatment for CRC had larger tumors with fewer papillations and more locules compared with primary OC tumors. Upon abdominal scanning for cancer dissemination, patients with OC had ascites, peritoneal carcinomatosis, and omental involvement more often, and liver metastases less often than those with mCRC. In addition to the previously described layered structure of a multilocular metastatic tumor [7], an ultrasound image resembling a tree was noted. Primary OC and mCRC are graphically compared in Figure 9. The most accurate methods for discriminating ovarian mCRC from primary OC were the proposed decision tree model and SA, which both generated fair AUC values. Application of the ADNEX model in this patient population resulted in a poor AUC value when CA-125 was included, and failed without CA-125. Moreover, the absolute percentage and RR values for risk of metastases were higher than those at risk of primary OC; however, it is not clear whether these differences are clinically significant. Diagnostics 2019, 9, 210 15 of 18

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Consolato M. Sergi 1,2

Consolato M. Sergi 1,2

Pediatrics is rapidly evolving, and the diagnostic tools are expanding the spectrum of diagnoses that can be identified at the bedside. The recent progress identified in pediatrics of the last 20 years is astonishing and has consolidated the concept that children are not “smaller adults” and indeed, perinatal and pediatric pathology has become an independent subspecialty in pathology with impressive intersections with fetal medicine, neonatology, and pediatrics. The neonatal intensive care unit (NICU) as well as the pediatric intensive care unit (PICU) play a major role in modern hospitals. These sections of the hospital provide sick newborns and children with the highest level of medical care. Differently from the general medical floors, both units allow intensive nursing care and continuous monitoring of vital parameters, including heart rate, breathing, and blood pressure. The survival of premature babies and small for date newborns has increased exponentially in the last few decades. On the other hand, the immune system, as well as the pulmonary and gastrointestinal organs, remain difficult to manage. At this age an increased rate of infection has been identified, and gastrointestinal dysfunction is common [1–6]. Cardiovascular function and sepsis are intimately related and may trigger early death without NICU or PICU intervention [7]. Although the diagnostic procedures in newborns are often overlapping with diagnostic algorithms used at older age, they continue to be a complex and dynamic process which requires a proper investigation of the obstetrical and medical history, skillful physical examination, appropriate laboratory tests, and imaging studies with or without pathological examination of tissue biopsies. On the other hand, even with these steps, diagnosis may remain elusive. The journey from the first appearance of symptom or sign to the final diagnosis may seem sometimes interminable. Today, new techniques seem to shorten this journey swiftly

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