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Designing power transmission systems is a complex and often time-consuming problem. In this task, various computational tools make it possible to speed up the process and verify a great many different solutions before the final one is developed. It is widely possible today to conduct computer simulations of the operation of various devices before the first physical prototype is built. The article presents an example of a dynamic model of power transmission systems, which has been developed to support work aimed at designing new and optimizing existing systems of that type, as well as to help diagnose them by designing diagnostic algorithms sensitive to early stages of damage development. The paper also presents sample results of tests conducted with the model, used at the gear design stage. In the presented model, the main goal is to reproduce the phenomena occurring in gears as well as possible, using numerous experiments in this direction featured in the literature. Many already historical models present different ways of modeling, but they often made significant simplifications, required by the limitations of the nature of computational capabilities. Differences also result from the purpose of the models being developed, and the analysis of these different ways of doing things makes it possible to choose the most appropriate approach. [ABSTRACT FROM AUTHOR]

Maintenance is crucial for aircraft engines because of the demanding conditions to which they are exposed during operation. A proper maintenance plan is essential for ensuring safe flights and prolonging the life of the engines. It also plays a major role in managing costs for aeronautical companies. Various forms of degradation can affect different engine components. To optimize cost management, modern maintenance plans utilize diagnostic and prognostic techniques, such as Engine Health Monitoring (EHM), which assesses the health of the engine based on monitored parameters. In recent years, various EHM systems have been developed utilizing computational techniques. These algorithms are often enhanced by utilizing data reduction and noise filtering tools, which help to minimize computational time and efforts, and to improve performance by reducing noise from sensor data. This paper discusses the various mechanisms that lead to the degradation of aircraft engine components and the impact on engine performance. Additionally, it provides an overview of the most commonly used data reduction and diagnostic and prognostic techniques. [ABSTRACT FROM AUTHOR]

Industrial components and systems undergo degradation in process operations. Prognostics and health management (PHM) is a process to assess and predict health conditions of components and can be applied to condition-based monitoring and maintenance. PHM is commonly utilized to analyze the health condition of a single lifecycle until failure. When maintenance occurs, degradation can be removed, and the PHM model can be restarted with new parameters related to the expected postmaintenance conditions. Maintenance actions, mostly imperfect repairs, may not entirely reset the condition to as good as new, and further degradation may occur at a higher rate. Maintenance repairs should be considered in prognostic models to predict component health more accurately. Furthermore, processes typically have more than one component that degrade and influence process measurements. The dependence of process measurements to multiple fault modes and related degradation can make individual component health monitoring complex. Commonly, faults and their related effects on process parameters must be isolated. In these cases, the diagnostics and prognostics framework should handle unsynchronized failure and maintenance reinitialization of different components for multiple fault processes. This research paper presents the Maintenance-Dependent Monitoring and Prognostics Model (MDMPM) to detect anomalies, decouple faults for different components, and predict future health conditions to calculate remaining useful life (RUL). The model is demonstrated with semisimulated nuclear power plant (NPP) data, with simultaneous condenser pump degradation and condenser tube fouling. The MDMPM shows a reliable prediction of RULs of NPP maintenance-dependent processes with interacting component degradation modes. [ABSTRACT FROM AUTHOR]

Simple Summary: Lung cancer is the cause of many deaths that could have been avoided if the disease had been detected at an early stage. This is possible thanks to the lung cancer screening (LCS) program with the low-dose computed tomography (LDCT) of the chest. Due to the heavy workload on the healthcare system, shortages of specialists, and expensive equipment, new solutions are needed to support the work of the hospitals. One of the most promising is the use of artificial intelligence (AI). In this paper, we present promising results and discuss whether/why AI application in medicine, with an emphasis on lung cancer, is needed. It is speculated that thanks to an innovative AI solution many lives could be saved. A lot has happened in the field of lung cancer screening in recent months. The ongoing discussion and documentation published by the scientific community and policymakers are of great importance to the entire European community and perhaps beyond. Lung cancer is the main worldwide killer. Low-dose computed tomography-based screening, together with smoking cessation, is the only tool to fight lung cancer, as it has already been proven in the United States of America but also European randomized controlled trials. Screening requires a lot of well-organized specialized work, but it can be supported by artificial intelligence (AI). Here we discuss whether and how to use AI for patients, radiologists, pulmonologists, thoracic surgeons, and all hospital staff supporting screening process benefits. [ABSTRACT FROM AUTHOR]

Cervical cancer ranks third among all new cancer cases and causes of cancer deaths in females. The paper provides an overview of cervical cancer prevention strategies employed in different regions, with incidence and mortality rates ranging from high to low. It assesses the effectiveness of approaches proposed by national healthcare systems by analysing data published in the National Library of Medicine (Pubmed) since 2018 featuring the following keywords: "cervical cancer prevention", "cervical cancer screening", "barriers to cervical cancer prevention", "premalignant cervical lesions" and "current strategies". WHO's 90-70-90 global strategy for cervical cancer prevention and early screening has proven effective in different countries in both mathematical models and clinical practice. The data analysis carried out within this study identified promising approaches to cervical cancer screening and prevention, which can further enhance the effectiveness of the existing WHO strategy and national healthcare systems. One such approach is the application of AI technologies for detecting precancerous cervical lesions and choosing treatment strategies. As such studies show, the use of AI can not only increase detection accuracy but also ease the burden on primary care. [ABSTRACT FROM AUTHOR]

Hydraulic power systems are commonly used in heavy industry (usually highly energy-intensive) and are often associated with high power losses. Designing a suitable system to allow an early assessment of the wear conditions of components in a hydraulic system (e.g., an axial piston pump) can effectively contribute to reducing energy losses during use. This paper presents the application of a deep machine learning system to determine the efficiency state of a multi-piston positive displacement pump. Such pumps are significant in high-power hydraulic systems. The correct operation of the entire hydraulic system often depends on its proper functioning. The wear and tear of individual pump components usually leads to a decrease in the pump's operating pressure and volumetric losses, subsequently resulting in a decrease in overall pump efficiency and increases in vibration and pump noise. This in turn leads to an increase in energy losses throughout the hydraulic system, which releases excess heat. Typical failures of the discussed pumps and their causes are described after reviewing current research work using deep machine learning. Next, the test bench on which the diagnostic experiment was conducted and the selected operating signals that were recorded are described. The measured signals were subjected to a time–frequency analysis, and their features, calculated in terms of the time and frequency domains, underwent a significance ranking using the minimum redundancy maximum relevance (MRMR) algorithm. The next step was to design a neural network structure to classify the wear state of the pump and to test and evaluate the effectiveness of the network's recognition of the pump's condition. The whole study was summarized with conclusions. [ABSTRACT FROM AUTHOR]

Copyright of Wiener Medizinische Wochenschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Paper presents diagnostic analysis of automotive ignition system for various working and adverse conditions in laboratory. Description and importance of basic diagnostics of automotive ignition system are examined in the first part of the paper. In the second the focus is placed on the basic principles and solution of the spark plug model. The test laboratory device is proposed in the following and the specialized measurements were executed by the proposed measurement system. The faults were simulated by application of oil and gasoline between the electrodes and failing by the driver to make the ignition contact on the spark plug. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To know the health status of hydrogen fuel cell, some diagnostics methods are proposed based on the historical status data of the hydrogen fuel cell. As multiple factors would cause the fuel cell problem, feature selection would be necessary during the diagnostics. In this paper, the author tried to apply an enhanced PCA algorithm to generate the proper features. Based on these features, a random forest algorithm is constructed for predicting the health status based on the history data. In this paper, we explore all aspects of hydrogen fuel cell sensor data, and extract several features by performing statistical analysis. We propose an efficient and accurate model for hydrogen fuel cell diagnostics. This model supports pipeline operations from feature selection to final result prediction. Besides, the model can also show which factor is essential for the health status of hydrogen fuel cell. • Pipeline operations from feature selection to result prediction are proposed. • An enhanced PCA algorithm is used for selecting the features. • Results showed that our method could improve the accuracy for diagnostics. • The proposed method could also be easily applied and reused. [ABSTRACT FROM AUTHOR]

Small naval vessels are equipped with high- and medium-speed engines with low diagnostic compliance. Faults in fuel installations are the most common cause of failure or inability to perform operational scenarios adequately. Identification of injector damage is severe as small engines are not equipped with indicators and thermocouples to measure the overall exhaust gas temperature in the exhaust manifold. The paper presents a vibration method for assessing the technical condition of a fuel installation. The proposed method is non-invasive and allows the indication of a damaged injector within a relatively short time. The paper presents simulation results verified with stand-bed tests. The research aimed to show the sensitivity and uniqueness of vibration symptoms to changes in the technical condition of fuel injection pumps. The conducted experiment confirmed the possibility of using vibration tests in the professional diagnostics of the fuel installation. These results are essential for the use of marine engines that do not have indicator valves. [ABSTRACT FROM AUTHOR]

High-speed loaded rotor systems are widely distributed in machines and equipment of various branches of technology, including transport. Maintaining rotor systems at the appropriate high technical level is an important task, the solution of which is necessary to reduce current costs, to decrease the number of emergency situations. In this paper, the process of appearance of fatigue cracks in rotor systems is considered and the degree of their development is determined. Based on the carried out studies, the method for predicting the development of the fatigue cracks has been developed. The destruction of structural elements under variable loads usually occurs gradually, as a result of the accumulation of microdamages that pass into the developing fatigue microcracks. The appearance of cracks does not mean that the structural elements are completely out of order and that immediate repairs are necessary. In practice, structural elements with cracks can continue to function reliably for a considerable time, and a slight decrease in operating loads can increase their durability and even completely halt the growth of cracks. Therefore, when vibrating the rotor machines, it is necessary to determine not only the presence and depth of the crack, but also its location, since the rate of crack growth depends on the level of stresses arising and on the length of the present crack. Early diagnosis of the appearance of defects in these systems solves many problems. The most important element of the analysis of the state of the structure is the determination of the degree of development of the crack, the determination of the time to reach the critical size. This allows us to remove the costly risks of disturbing critical technological processes. As shown in this paper, if detection of defects is possible with the help of modal and Fourier analysis, wavelet analysis makes it possible to determine the degree of crack development over time. Using the sample of 10 experiments and calculations involving modal, Fourier and wavelet analysis of one of the rotor systems, we obtained in the paper the results allowing extending them to rotor systems of different designs. [ABSTRACT FROM AUTHOR]

Doughnuts (aka market system diagrams) are central to market systems analysis, and to the way of thinking that seeks to investigate and address root causes of market system underperformance. But we rarely see them being used, and still less see them used well. Why is the defining framework of the Making Markets Work for the Poor (M4P) approach not used more, and why is it not used more consistently? This paper starts by getting under the hood of the doughnut to see what's really going on in there and describes how it needs to sit alongside other M4P tools. It then details three common examples of doughnut-related malpractice and the real implications this has for our ability to deliver sustainable change at scale in market systems. Finally, the paper analyses the incentive and capacity constraints that prevent programmes making better use of doughnuts, and suggests how these may be addressed. [ABSTRACT FROM AUTHOR]

Existing high-priority target product profiles (TPPs) of the World Health Organization (WHO) establish important needs for tuberculosis (TB) diagnostic development. Building on this earlier work, this guidance series aims to provide study guidance for performing accuracy studies of novel diagnostic products that may meet the 4 high-priority WHO TPPs and thus enable adequate evidence generation to inform a WHO evidence review process. Diagnostic accuracy studies represent a fundamental step in the validation of all tests. Unfortunately, such studies often have limitations in design, execution, and reporting, leading to low certainty of the evidence about true test performance, which can delay or impede policy and scale-up decisions. This introductory paper outlines the following: (1) the purpose of this series of papers on study guidance; (2) WHO evidence needs and process for the development of policy guidelines for new TB diagnostic tests; and (3) study design considerations, ie, general diagnostic study considerations, intended use of test and role in the clinical pathway, choice of population and setting, index-test specific issues, suitable reference standard and comparators, study flow and specimen issues, and finally key issues beyond accuracy that should be considered. The other 4 papers in this series will provide more detailed guidance for each of the 4 WHO high-priority TPPs. By increasing the clarity around the clinical evaluation needs for tests that have the potential to meet the TPP specifications, we hope to support harmonized evidence generation and enable the WHO review process towards meeting the WHO End TB Strategy targets for reducing the incidence and mortality associated with TB. [ABSTRACT FROM AUTHOR]

Despite considerable advances over the last two decades in sensing instrumentation and information technology infrastructure, monitoring and diagnostics technology has not yet found its place in health management of mainstream machinery and equipment. This is in spite of numerous studies reporting that the expected savings from widespread deployment of condition-based maintenance (CBM) technology would be in the tens of billions of dollars in many industrial sectors as well as in governmental agencies. It turns out that a prerequisite to widespread deployment of CBM technology and practice in industry is cost efficient and effective diagnostics and prognostics. This paper presents a novel method for employing hidden Markov models (HMMs) for carrying out both diagnostic as well as prognostic activities for metal cutting tools. The methods employ HMMs for modelling sensor signals emanating from the machine (or features thereof), and in turn, identify the health state of the cutting tool as well as facilitate estimation of remaining useful life. This paper also investigates some of the underlying issues of proper HMM design and training for the express purpose of effective diagnostics and prognostics. The proposed methods were validated on a physical test-bed, a vertical drilling machine. Experimental results are very promising. [ABSTRACT FROM AUTHOR]

Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial applications. The following paper presents a method of motor failure detection in the multirotor UAV using piezo bars. The results of a real flight, in which the failure of the propulsion system caused the crash of a hybrid VTOL UAV, were presented and analyzed. The conclusions drawn from this flight led to the development of a lightweight, simple and reliable sensor that can detect a failure of the UAV propulsion system. The article presents the outcomes of laboratory tests concerning measurements made with a piezo sensor. An extensive analysis of the obtained results of vibrations recorded on a flying platform arm with a propulsion system is presented, and a methodology for using this type of data to detect failures is proposed. The article presents the possibility of using a piezoelectric sensor to record vibrations on the basis of which it is possible to detect a failure of the UAV propulsion system. [ABSTRACT FROM AUTHOR]

Infectious diseases account for millions of deaths each year. To reduce the number of infectious disease related deaths, diagnostic testing needs to be more accessible to patients in low-income countries as well as developed countries. Current diagnostic methods involve centralized laboratories, trained personnel, and are time-intensive, limiting translation to the point-of-care (POC). Microfluidic devices are a popular alternative for diagnostics due to reduced assay times, reduced sample volume, and lower cost. Microfluidic devices are small (<10 cm) and can perform complex assays. Microfluidic paper-based analytical devices (µPADs) are a popular approach to help translate diagnostics to the POC but historically suffer from poor sensitivity when compared to established laboratory methods. Magnetically labeling analytes allows samples to be sorted resulting in improved sensitivity and specificity. Microfluidic magnetophoresis is the process of manipulating magnetic particles in a magnetic field and offers the ability to wash and concentrate a sample during flow. However, until recently, magnetophoresis has not been used in conjunction with µPADs because magnetophoresis requires complex and expensive instrumentation to control flow. Coupling magnetophoresis with µPADs enables pump-free flow control, simple operation, and low cost. Early magnetophoresis µPADs showed detection limits similar to traditional methods but higher than targets for clinical use. In this work, we demonstrate a novel, simple MagnEtophoretic Slider Assay (MeSA) that is free of any external instrumentation and offers a new platform for POC diagnostics. We demonstrate the assay's capability through biotin competitive assays and a sandwich immunoassay for E. coli detection. The calculated limit of detection for E. coli was 1.62 × 103 Colony Forming Units per mL (CFU/ml). The work described is a novel and simple microfluidic platform that has potential for a wide range of future applications. [ABSTRACT FROM AUTHOR]

Gynecological ultrasonography plays a central role in the management of endometriosis. The rapid technical development as well as the currently increasing evidence for non-invasive diagnostic methods require an updated compilation of recommendations for the use of ultrasound in the management of endometriosis. The present work aims to highlight the accuracy of sonography for diagnosing and classifying endometriosis and will formulate the present list of key messages and recommendations. This paper aims to demonstrate the accuracy of TVS in the diagnosis and classification of endometriosis and to discuss the clinical applications and consequences of TVS findings for indication, surgical planning and assessment of associated risk factors. (1) Sophisticated ultrasound is the primary imaging modality recommended for suspected endometriosis. The examination procedure should be performed according to the IDEA Consensus. (2) Surgical intervention to confirm the diagnosis alone is not recommended. A preoperative imaging procedure with TVS and/or MRI is strongly recommended. (3) Ultrasound examination does not allow the definitive exclusion of endometriosis. (4) The examination is primarily transvaginal and should always be combined with a speculum and a bimanual examination. (5) Additional transabdominal ultrasonography may enhance the accuracy of the examination in case of extra pelvic disease, extensive findings or limited transvaginal access. (6) Sonographic assessment of both kidneys is mandatory when deep endometriosis (DE) and endometrioma are suspected. (7) Endometriomas are well defined by sonographic criteria. When evaluating the ovaries, the use of IOTA criteria is recommended. (8) The description of sonographic findings of deep endometriosis should be systematically recorded and performed using IDEA terminology. (9) Adenomyosis uteri has sonographically well-defined criteria (MUSA) that allow for detection with high sensitivity and specificity. MRI is not superior to differentiated skilled ultrasonography. (10) Classification of the extent of findings should be done according to the #Enzian classification. The current data situation proves the best possible prediction of the intraoperative situs of endometriosis (exclusive peritoneum) for the non-invasive application of the #Enzian classification. (11) Transvaginal sonographic examination by an experienced examiner is not inferior to MRI diagnostics regarding sensitivity and specificity in the prediction of the extent of deep endometriosis. (12) The major advantage of non-invasive imaging and classification of endometriosis is the differentiated planning or possible avoidance of surgical interventions. The recommendations represent the opinion of experts in the field of non-invasive and invasive diagnostics as well as therapy of endometriosis. They were developed with the participation of the following national and international societies: DEGUM, ÖGUM, SGUM, SEF, AGEM/DGGG, and EEL. [ABSTRACT FROM AUTHOR]

This paper reports on the design and synthesis of new multifunctional porphyrin-based therapeutic agents for potential therapeutic and diagnostic applications. Zinc complexes of A3B-type meso-arylporphyrins containing OH- and COOH- groups were modified with chelating ligands based on 4′-(4-methylphenyl)-2,2′:6′,2″-terpyridine derivatives in high yields. Novel complexes with Gd(III), Fe(III) were obtained for these conjugates. Aggregation behaviour in solutions of different solubilisers was studied to inform the selection of the optimal solubilising platform for the porphyrins obtained; their photophysical and photochemical properties were also characterised. Micellar Pluronic F127 formulation was found to be the most effective solubiliser for stabilising the fluorescence-active monomolecular form of the photosensitisers (PS). In vitro cytotoxicity of the compounds was studied on the HEP-2 cell line with and without irradiation for 1.5 and 24 h. As a result, the IC50 of compounds 12 and 14 at an irradiation dose of 8.073 J/cm2 was shown to be 1.87 ± 0.333 and 1.4 ± 0.152 μM, respectively; without irradiation, the compound had no toxic effect within the studied concentration range (1.5 h). A test for the inhibition of metabolic cooperation or promoter activity was also performed for the abovementioned compounds, showing the efficacy and safety of the conjugates obtained. Preliminary data have indicated the high potential of the new type of PS to be promising molecular theranostic agents. [ABSTRACT FROM AUTHOR]

The Southern Hemisphere temperature has experienced obvious changes with great spatial differences over the past several decades. Most regions show extreme warming, especially those located at 35°–55°S. In contrast, subsurface cooling exists between 15° and 35°S in the Indian and Pacific basins. The subsurface temperature and salinity change can be divided into spiciness change and heave components. The results show the warming due to isopycnal movement being largely offset by significant spiciness cooling at middepth. Surface warming and subduction into the interior ocean account for subsurface spiciness cooling near 45°S, while surface freshening and penetration along isopycnals are more important to the subsurface spiciness cooling farther north. The isobaric temperature change is associated with pure warming and pure heaving, and the subsurface cooling observed in the Indian and Pacific subtropics is predominantly attributed to pure heaving. This study provides a quantitative estimate of the relative contribution of surface temperature, salinity change, and circulation adjustment in subsurface temperature change, highlighting the importance of circulation change in producing subsurface cooling. Further research is needed to understand why different processes dominate in different ocean sections. Significance Statement: While the global ocean is warming, the subsurface temperature change exhibits a significant regional disparity. This paper attempts to explain the deep-reaching warming at 35°–55°S and cooling at 15°–35°S based on three historical observation datasets. We find that the cooling mostly occurs between 400 and 1000 m in the south Indian and Pacific subtropics (15°–35°S), which is attributed to pure heaving, indicating the importance of circulation change in these regions. The midlatitude warming (35°–55°S) is mainly caused by the pure warming process, which is related to heat uptake at the subpolar surface and northward and downward heat transport. The spiciness cooling near 45°S is mainly driven by the subduction of the surface warming signal while the freshening process has a stronger impact on spiciness cooling farther north. [ABSTRACT FROM AUTHOR]

This paper is an update of the diagnostic and therapeutic recommendations of the National Consultant for Gastroenterology and the Polish Society of Gastroenterology from 2013. It contains 49 recommendations for the diagnosis and treatment, both pharmacological and surgical, of ulcerative colitis in adults. The guidelines were developed by a group of experts appointed by the Polish Society of Gastroenterology and the National Consultant in the field of Gastroenterology. The methodology related to the GRADE methodology was used to assess the quality of available evidence and the strength of therapeutic recommendations. The degree of expert support for the proposed statements was assessed on a 6-point Likert scale. Voting results, together with comments, are included with each statement. [ABSTRACT FROM AUTHOR]

The ever-increasing demand for electricity and the need for conventional sources to cooperate with renewable ones generates the need to increase the efficiency and safety of the generation sources. Therefore, it is necessary to find a way to operate existing facilities more efficiently with full detection of emerging faults. These are the requirements of Polish, European and International law, which demands that energy facilities operate with the highest efficiency and meet a number of restrictive requirements. In order to improve the operation of steam power plants of electric generating stations, thermal-fluid diagnostics have been traditionally used, and in this paper a three-hull steam turbine, having a high-pressure, a medium-pressure and a low-pressure part, has been selected for analysis. The turbine class is of the order of 200 MW electric. Genetic algorithms (GA) were used in the process of creating the diagnostic model. So far, they have been used for diagnostic purposes in gas turbines, and no work has been found in the literature using GA for the diagnostic process of such complex objects as steam turbines located in professional manufacturing facilities. The use of genetic algorithms allowed rapid acquisition of global extremes, that is efficiency and power of the unit. The result of the work undertaken is the possibility to carry out a full diagnostic process, meaning detection, localization and identification of single and double degradations. In this way 100 % of the main faults are found, but there are sometimes additional ones, and these are not perfectly identified especially for single time detection. Thus, the results showed that with a very high success rate the simulated damage to the geometrical elements of the steam turbine under study is found. [ABSTRACT FROM AUTHOR]

Copyright of Family Medicine Forum / Forum Medycyny Rodzinnej is the property of VM Medica-VM Group (Via Medica) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper deals with the main provisions of the new standard DSTU 9118:2022 «Technical diagnostics. Diagnosing the technical condition of structure materials. General requirements». The standard covers industrial facilities: pipelines, pipeline systems, and technological equipment (boilers, containers, tanks, etc.) of power, oil processing, petrochemical and chemical productions, lifting equipment and facilities and other high-risk welded structures. The standard defines the main provisions on technical diagnostics, its indices and characteristics, and requirements to diagnostic support of the facility. The standard is designed for personnel, specialists, and executives, involved in assessment of the technical conditions of the facilities. Application of AE method in the mode of continuous monitoring to ensure fulfillment of the Standard provisions is considered. 5 Ref., 2 Tabl., 3 Fig. [ABSTRACT FROM AUTHOR]

Definition: Magnetic nanoparticles (MNPs) have great potential in various areas such as medicine, cancer therapy and diagnostics, biosensing, and material science. In particular, magnetite (Fe3O4) nanoparticles are extensively used for numerous bioapplications due to their biocompatibility, high saturation magnetization, chemical stability, large surface area, and easy functionalization. This paper describes magnetic nanoparticle physical and biological properties, emphasizing synthesis approaches, toxicity, and various biomedical applications, focusing on the most recent advancements in the areas of therapy, diagnostics, theranostics, magnetic separation, and biosensing. [ABSTRACT FROM AUTHOR]

In this study, the authors explored the issues of the Soderbergh electrolysis cell's increase in economic efficiency. This result was achieved by analyzing the temperature fields of the electrolysis cell in order to determine the overheating points. As a result, it led to the determination of the points of the hearth bottom's subsequent breakdown, causing the failure of the electrolysis cell. In this paper, the mathematical modeling of the temperature fields using a spatially distributed mathematical model and conducted experimental studies were carried out. The mathematical model also provides the opportunity to measure the temperature field in the hearth bottom (at the bottom) of the OA-300M electrolysis cell. The results of the given research can be used to solve the experimental determination of the hearth bottom internal defect problem. [ABSTRACT FROM AUTHOR]

Due to the wide use of gearmotor systems in industry, many diagnostic techniques have been developed/employed to prevent their failures. An insufficient lubrication of gearboxes of these machines could shorten their life and lead to catastrophic failures and losses, making it important to ensure a required lubrication level. For the first time in worldwide terms, this paper proposed to diagnose a lack of gearbox oil lubrication using motor current signature analysis (MCSA). This study proposed, investigated, and experimentally validated two new technologies to diagnose a lack of lubrication of gear motor systems based on MCSA. Two new diagnostic features were extracted from the current signals of a three-phase induction motor. The effectiveness of the proposed technologies was evaluated for different gear lubrication levels and was compared for three phases of motor current signals and for a case of averaging the proposed diagnostic features over three phases. The results confirmed a high effectiveness of the proposed technologies for diagnosing a lack of oil lubrication in gearmotor systems. Other contributions were as follows: (i) it was shown for the first time in worldwide terms, that the motor current nonlinearity level increases with the reduction of the sgearbox oil level; (ii) novel experimental validations of the proposed two diagnostic technologies via comprehensive experimental trials (iii) novel experimental comparisons of the diagnosis effectiveness of the proposed two diagnostic technologies. [ABSTRACT FROM AUTHOR]

The paper examines the peculiarities of the adaptive and rehabilitation processes of children with special educational needs. It was found that one of the most significant issues of rehabilitation work with children with special educational needs is to create the conditions for their integration into society. This stipulates the determination of the state of their adaptive and rehabilitation potential formation suggesting identification of social characteristics and social relations of the children with special educational needs; definition of the levels of their learning opportunities, skills and abilities development; elucidation of the peculiarities of intra-family relations in families bringing up children with special educational needs; research of rehabilitation processes features being passed by children with special educational needs. For studying the state of adaptive and rehabilitation potential formation in working with children with special educational needs, we have conducted a diagnostic study among children with special educational needs who receive rehabilitation services at the Shepetivka City Center for Social Rehabilitation of Disabled Children of Khmelnytskyi region. The parents of the children took part in the study as well. The results of the diagnosis revealed that the children with special educational needs are dominated by medium and low levels of formation of self-concept and comprehention of their relations with the social environment; they are characterized by medium and low levels of general mental development; children with special educational needs suffer hostility and conflict in their families, while their parents experience feelings of guilt, anxiety, and mental stress; the difficulties being faced by the children with special educational needs during the rehabilitation process are mainly related to their focusing on their own illness. In this regard, we have developed and substantiated the forms and methods for regulating the adaptive and rehabilitation processes in working with children with special educational needs, which, in our opinion, should be applied by specialists at the centers for the social rehabilitation of children with disabilities. [ABSTRACT FROM AUTHOR]

There has been a rapidly growing interest in the use of composite and polymer materials for the construction of marine propellers for over 20 years. The main advantages of these materials are a reduction in the weight of the propeller, increased efficiency due to the hydroelasticity effect, a reduction of the hydroacoustic signature, and a cost reduction for serial production. This paper presents an overview of diagnostic methods that can be applied at the design level and during the operation of marine propellers made of polymeric materials. Non-invasive contact and non-contact-based diagnostic techniques for evaluating the technical state of the propeller are reviewed, and the advantages and disadvantages of qualitative and quantitative methods are identified. Operational diagnostic procedures for propellers are areessential for the safety of vessels at sea. Finally, the structure of a diagnostic system is proposed. It combined diagnosis process with the genesis of damage and the prognosis of the technical condition, i.e. production and in-service diagnostics. [ABSTRACT FROM AUTHOR]

Salivary gland malignancies (SGMs) account for less than 5% of new diagnoses in head and neck tumors. If feasible, surgery is the preferred treatment modality. Nevertheless, some malignancies have a tendency of recurrence, with possible distant metastasis. Alternative treatment strategies, such as primary radiation or chemotherapeutics, often present low response rates. As a result, there is an unmet need for novel therapeutic approaches. Nowadays, target-based therapies (e.g., small inhibitors and immunotherapy) are used by the medical oncologist for possible treatment of advanced SGMs. Based on recent published trials, some novel treatments may provide additional disease control for some patients. However, sample sizes are small, the general findings are unsatisfactory, and a lot of uncertainties remain to be elucidated. Nevertheless, research shows that patients do not benefit from blind administration of systemic treatments and therefore a more personalized approach is highly needed. The aim of this review paper is to summarize the most recent advances in the biological understanding and molecular pathways of salivary gland cancers, the association of these pathways with the current treatments used and their implications for more personalized targeted-based therapies. [ABSTRACT FROM AUTHOR]

Successful water management is critical to achieving high performance in proton exchange membrane fuel cells (PEMFCs). The relatively high sensitivity of terahertz radiation to liquid water is promising as a complementary alternative for flooding detection in PEMFCs. Using a novel, commercially available terahertz source and camera, this paper investigates the feasibility of a compact and low‐cost terahertz imaging system for visualizing water build‐up inside an operating PEMFC, supported by simultaneous high‐resolution optical imaging. Several phenomena of water accumulation and transport, such as membrane hydration, main droplet appearance, water pool formation, growth, and eventual flush out by gases are imaged by terahertz imaging. These results agree with optical imaging and cell voltage readings. The proposed setup is also able to distinguish the effect of different air flow rates. [ABSTRACT FROM AUTHOR]

Introduction The composition of saliva changes depending on the current physiological state of the body, which gives many diagnostic possibilities. Oral fluid diagnostics has become more commercially available in recent years, and the interest in it is related to the relative ease of use, low cost of testing and a non-invasive form of obtaining clinical material. Aim This paper deals with the importance of saliva as a diagnostic material. Material and methods The study examined the presence of genetic material of two viruses (HHV-6 and HHV-7) belonging to the Herpesvidae family in the saliva of healthy persons. The research group consisted of 24 families with at least one child. The saliva samples (85) had a known status for the presence of CMV and EBV DNA. Results and conclusion In total, the presence of HHV-6 DNA was detected in 68 saliva samples (80%), and HHV-7 DNA in 62 saliva samples (72.9%) of the tested persons. The presence of DNA of the studied viruses in children and adults was compared, and the presence of DNA of viruses was analyzed in terms of entire families, as well as the results for HHV-6 and 7 were correlated with the presence of other herpesviruses in saliva, comparing with reports of other authors [ABSTRACT FROM AUTHOR]

Strain wave gears, also known as harmonic drives, are employed in a wide range of fields such as robotics and aerospace, where light weights, precision, and reliability are essential to the correct execution of the tasks. For this reason, their understanding and optimization are of high interest for both academia and industry. Previous studies have been mainly focused on investigating and modeling the working principle of strain wave gears in nominal operating conditions. On the contrary, the present paper describes the results of an experimental campaign aimed to introduce wear in gears of two different suppliers and its impact on the gear torsional stiffness. Results show how the change in the gear performance strongly depends both on the gear manufacturer and the location of wear. For the analyzed components, a damaged wave generator–flexspline interface reduces the gear stiffness up to one-fourth of its nominal value, while the non-nominal shape of the teeth jeopardizes the gearbox performance, leading up to just 4% of the nominal stiffness values, and resulting in backlash. Such data can be used to properly model the presence of wear in strain wave gears and to train data-driven diagnostics and prognostics routines to effectively detect such a fault. [ABSTRACT FROM AUTHOR]

The paper describes the concept of improving the efficiency of the process of monitoring the technical condition and evaluating the service life of an asynchronous electric drive of promising trains based on the analysis of diagnostic information of various physical nature, taking into ac-count different types of diagnostic signals generated by individual drive elements and measured using vibration and current sensors. The implementation of the project provides an increase in the effectiveness of monitoring the technical condition of the electromechanical equipment of trains, allows to move from scheduled maintenance of high-speed rail transport to service according to the actual condition, to increase safety, as well as to the introduction automatic monitoring systems. Functional purpose of the system: monitoring the technical condition of electromechanical equipment and predicting the residual life of its nodes through the use of an intelligent decision-making unit based on a neural network. A scheme of hardware for data collection and analysis, an algorithm for collecting and processing data based on a registrar, and a predictive diagnostics algorithm have been developed. [ABSTRACT FROM AUTHOR]

Tackling cancer is a major challenge right on the global level. Europe is only the tip of an iceberg of cancer around the world. Prosperous developed countries share the same problems besetting Europe–and the countries and regions with fewer resources and less propitious conditions are in many cases struggling often heroically against a growing tide of disease. This paper offers a view on these geographically wider, but essentially similar, challenges, and on the prospects for and barriers to better results in this ceaseless battle. A series of panels have been organized by the European Alliance for Personalised Medicine (EAPM) to identify different aspects of cancer care around the globe. There is significant diversity in key issues such as NGS, RWE, molecular diagnostics, and reimbursement in different regions. In all, it leads to disparities in access and diagnostics, patients' engagement, and efforts for a better understanding of cancer. [ABSTRACT FROM AUTHOR]

Contemporary operation-related requirements for combustion engines force the necessity of ongoing assessment of their in operation technical condition (e.g. marine engines). The engine efficiency and durability depend on a variety of parameters. One of them is valve clearance. As has been proven in the paper, the assessment of the valve clearance can be based on vibration signals, which is not a problem in terms of signal measurement and processing and is not invasive into the engine structure. The authors described the experimental research aiming at providing information necessary to develop and validate the proposed method. Active experiments were used with the task of valve clearance and registration of vibrations using a three-axis transducer placed on the engine cylinder head. The tests were carried out during various operating conditions of the engine set by 5 rotational speeds and 5 load conditions. In order to extract the training examples, fragments of the signal related to the closing of individual valves were divided into 11 shorter portions. From each of them, an effective value of the signal was determined. Obtained total 32054 training vectors for each valve related to 4 classes of valve clearance including very sensitive clearance above 0.8 mm associat-ed with high dynamic interactions in cylinder head. In the paper, the authors propose to use a convolutional network CNN to assess the correct engine valve clearance. The obtained results were compared with other methods of machine learning (pattern recognition network, random forest). Finally, using CNN the valve clearance class identification error was less than 1% for the intake valve and less than 3.5% for the exhaust valve. Developed method replaces the existing standard methods based on FFT and STFT combined with regression calculation where approximation error is up to 10%. Such results are more useful for further studies related not only to classification, but also to the prediction of the valve clearance condition in real engine operations.

A novel approach for cost-effective and temporally resolved in-line combustion gas diagnostics based on spontaneous Stokes Raman spectroscopy is presented in this paper. The proposed instrument uses a multipass configuration designed to increase the scattering generation, giving information about gas species concentrations, including H2 and N2 that are not commonly available from analysis with absorption spectroscopy techniques. The system performs calibrated analysis providing both qualitative and quantitative information about the gas composition. Depending on the application, the device can work with spectra integration time from 0.15 s up to 10 s, with a Raman spectrum ranging from the H2 rotational peak at Raman shift of 587 cm−1 up to the H2 vibrational peak at 4156 cm−1, covering all the Raman emissions of major combustion species. The device response was characterized by a working pressure from 0.7 to 7.5 bar. The instrument prototype has been made completely transportable, designed to operate using a gas sampling system, and ready to be operated in relevant industrial in-line environments. [ABSTRACT FROM AUTHOR]

The integration of biochips with AI opened up new possibilities and is expected to revolutionize smart healthcare tools within the next five years. The combination of miniaturized, multi-functional, rapid, high-throughput sample processing and sensing capabilities of biochips, with the computational data processing and predictive power of AI, allows medical professionals to collect and analyze vast amounts of data quickly and efficiently, leading to more accurate and timely diagnoses and prognostic evaluations. Biochips, as smart healthcare devices, offer continuous monitoring of patient symptoms. Integrated virtual assistants have the potential to send predictive feedback to users and healthcare practitioners, paving the way for personalized and predictive medicine. This review explores the current state-of-the-art biochip technologies including gene-chips, organ-on-a-chips, and neural implants, and the diagnostic and therapeutic utility of AI-assisted biochips in medical practices such as cancer, diabetes, infectious diseases, and neurological disorders. Choosing the appropriate AI model for a specific biomedical application, and possible solutions to the current challenges are explored. Surveying advances in machine learning models for biochip functionality, this paper offers a review of biochips for the future of biomedicine, an essential guide for keeping up with trends in healthcare, while inspiring cross-disciplinary collaboration among biomedical engineering, medicine, and machine learning fields. [Display omitted] • Biochips are key for diagnosis, drug delivery, disease modeling, and neurostimulation. • AI-assisted biochip technology offers advances in novel diagnostics and therapeutics. • Useful in cancer, diabetes, infectious diseases, and neurological disorders. • Predictive analytics in AI-biochips shed light on predictive and precision medicine. [ABSTRACT FROM AUTHOR]

Fusion reactors are complex systems of interconnected parts, many of which rely on novel technologies. Understanding the patterns of connectivity is essential for many design aspects: assessing technical risks, leveraging modularity, preventing rework and enabling functional integration. The enabling design artefact is the system's architecture, its conceptual model of functions, components and interfaces. In this paper, we present two architecture modelling and analysis methods based on Dependency Structure Matrices (DSM). Firstly, the bottom-up method builds an architecture model from decentralized documentation of all ITER diagnostics and their interfaces. The DSM highlights a modular system topology, integration challenges and opportunities for managing complexity. The limitations of this method, however, motivate the development of a top-down alternative. The top-down method is suited for early-stage design definition, therefore generating valuable insights throughout the development lifecycle. The architecture model serves as a central storage of design information, from which viewpoints can be automatically generated: DSMs, functional flow diagrams, cabling diagrams, interface reports and requirements propagation tables. This model-based information paradigm drastically improves design quality, project planning, change management and stakeholder communication. The top-down method is demonstrated for the Visible Spectroscopy Reference System, one of ITER's first diagnostics, but promises a more widespread application. • A modelling method to define the multi-level components, functions and interfaces of fusion devices. • Automatically generated design documents that improve communication with multidisciplinary stakeholders. • Recommendations for the organization and management of sets of diagnostic systems. [ABSTRACT FROM AUTHOR]

• The nanophotonic field has advanced to be used as a method to detect infectious diseases. • Multiplex nanophotonic diagnostics enable rapid and simultaneous detection of viral pathogens. • High sensitivity and specificity of multiplex nanophotonic diagnostics enable real-time identification of viruses without the need for nucleic acid amplification. • Photonic diagnostics such as localized surface plasmon resonance (LSPR), magnetic resonance imaging (MRI), optical coherence tomography (OCT), and photoacoustic imaging (PAI), can be developed as point-of-care diagnostic tools and used as procedures for treating viral diseases. The field of nanophotonics has advanced and can be utilized as a method to detect different infectious diseases. The introduction of multiplex nanophotonic diagnostics has enabled the speedy and simultaneous detection of viral infections and specific biomarkers. The quick reaction times, high sensitivity, and specificity of multiplex nanophotonic diagnostics enable real-time identification of viruses without the need for nucleic acid amplification. This review presents an overview of nanophotonic tools used to identify diseases and particular biomarkers. The paper also examines possible research areas for the development of unique, cutting-edge multiplex nanophotonic diagnostics capable of concurrently detecting various diseases or biomarkers/biomolecules. Furthermore, it discusses barriers to further advancement and offers insight into anticipated trends. [Display omitted] [ABSTRACT FROM AUTHOR]

The pandemic of COVID-19 and its widespread transmission have made us realize the importance of early, quick diagnostic tests for facilitating effective cure and management. The primary obstacles encountered were accurately distinguishing COVID-19 from other illnesses including the flu, common cold, etc. While the polymerase chain reaction technique is a robust technique for the determination of SARS-CoV-2 in patients of COVID-19, there arises a high demand for affordable, quick, user-friendly, and precise point-of-care (POC) diagnostic in therapeutic settings. The necessity for available tests with rapid outcomes spurred the advancement of POC tests that are characterized by speed, automation, and high precision and accuracy. Paper-based POC devices have gained increasing interest in recent years because of rapid, low-cost detection without requiring external instruments. At present, microfluidic paper-based analysis devices have garnered public attention and accelerated the development of such POCT for efficient multistep assays. In the current review, our focus will be on the fabrication of detection modules for SARS-CoV-2. Here, we have included a discussion on various strategies for the detection of viral moieties. The compilation of these strategies would offer comprehensive insight into the detection of the causative agent preparedness for future pandemics. We also provide a descriptive outline for paper-based diagnostic platforms, involving the determination mechanisms, as well as a commercial kit for COVID-19 as well as their outlook.

This paper discusses a new method for measuring and calculating the angle of inclination of a railway support or a contact network support, using an unmanned aerial vehicle flying along a straight path, parallel to the railway track. A review of existing measurement methods is carried out, their advantages and disadvantages are indicated. In the method under consideration, it is proposed to measure angles and distances with six laser scanning rangefinders installed in threes on horizontal and inclined planes on an unmanned aerial vehicle. This allows you to increase the speed and accuracy of determining the angle of inclination of vertical supports. The calculations use the minimum distances from the laser scanning range finder to the top and bottom of the support surface. The formulas use geometric relationships and the cosine theorem to calculate the roll of supports taking into account their taper. Measuring distances and angles three times allows for averaging over them, which significantly increases the accuracy of calculations. A model experiment is carried out on a model of a reinforced concrete contact network support in four orientations. A comparison is made between theoretically calculated and experimentally measured distances and inclination angles. The accuracy of parameter determination complies with regulatory requirements.

Abstract Context Prostate‐specific antigen is non‐specific for prostate cancer. This is improved by multiparametric MRI but a significant amount of indolent prostate cancer is detected by the current MRI pathway and data is emerging that clinically significant cancers maybe missed using a standard PSA threshold. Volatile organic compound (VOC) analysis may offer novel biomarkers for prostate cancer and clinically significant disease. Objective To perform a systematic review of the literature to evaluate the current evidence for the use of VOCs as novel biomarkers for prostate cancer and clinically significant prostate cancer. Evidence Acquisition A systematic search of MEDLINE, Scopus, Web of Science and the Cochrane Library was undertaken by two independent reviewers and papers were assessed for inclusion in the review. Study characteristics, sensitivity and specificity of GC–MS or eNose were extracted. Risk of bias and applicability issues were determined using QUADAS 2 and the quality of reporting using the STARD checklist. Evidence Synthesis Nineteen studies were included, of which 6 utilised eNose and 13 GC–MS. eNose sensitivity and specificity were 0.71–0.95 and 0.79–0.96, respectively, and GC–MS found a sensitivity and specificity of 0.66–1.00 and 0.53–0.97, respectively. There were concerns about bias in patient recruitment due to differences in the timing of the index test relative to the reference standard. Conclusion This review has found promising early results for urinary metabolomics in the detection of prostate cancer. However, there is a need for larger, high‐quality studies to validate this. Future work should focus on the detection of clinically significant prostate cancer.