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This paper explores the available material regarding the potential use of a thermal imaging camera in the field of uroandrology and human sexuality research. Infrared thermography (IRT) constitutes a low-cost, effective and quick tool for the diagnosis and real-time monitoring of therapeutic effects. The presented paper focuses on the clinical aspects of the use of IRT in daily medical practice, the methodology of applying thermal imaging measurements and the physical properties of infrared radiation. IRT provides a precise, measurable and repeatable source of temperature data and its applications are constantly expanding into new medical fields complementing and developing conventional diagnostic methods. [ABSTRACT FROM AUTHOR]

Based on measurements and research, diagnostics of the condition of a structure aims to provide an answer to the question of what the condition of the structure is, and the necessary steps for reconstruction or rehabilitation. Masonry stone construction is one of the oldest methods of construction of building structures. In spite of that, this type of structures does not have fully defined parameters that influence its behavior. The reason for this is the fact that the properties of masonry stone structures differ depending on the basic material (stone) and binding material (mortar), as well as their combination. The paper presents diagnostics of the condition of masonry structures on the Tabija tower building. Tabija, a low tower for cannons, is a fortification structure from the Ottoman period that is the most completely preserved and was registered for the first time in the city plan from 1717. The structure is in poor condition due to a large number of natural and human factors. The paper will present a detailed visual inspection of the structure, as well as tests conducted in the laboratory and in-situ, the calculation, and decisions and proposals for the rehabilitation and/or reconstruction of the considered building of cultural and historical heritage. [ABSTRACT FROM AUTHOR]

This paper presents a method for the multi-criteria classification of data in terms of identifying pneumatic wheel imbalance on the basis of vehicle body vibrations in normal operation conditions. The paper uses an expert system based on search graphs that apply source features of objects and distances from points in the space of classified objects (the metric used). Rules generated for data obtained from tests performed under stationary and road conditions using a chassis dynamometer were used to develop the expert system. The recorded linear acceleration signals of the vehicle body were analyzed in the frequency domain for which the power spectral density was determined. The power field values for selected harmonics of the spectrum consistent with the angular velocity of the wheel were adopted for further analysis. In the developed expert system, the Kamada–Kawai model was used to arrange the nodes of the decision tree graph. Based on the developed database containing learning and testing data for each vehicle speed and wheel balance condition, the probability of the wheel imbalance condition was determined. As a result of the analysis, it was determined that the highest probability of identifying wheel imbalance equal to almost 100% was obtained in the vehicle speed range of 50 km/h to 70 km/h. This is known as the pre-resonance range in relation to the eigenfrequency of the wheel vibrations. As the vehicle speed increases, the accuracy of the data classification for identifying wheel imbalance in relation to the learning data decreases to 50% for the speed of 90 km/h. [ABSTRACT FROM AUTHOR]

As the level of complexity of modern rotating machinery grows, the need for an effective and efficient maintenance process increases as well. In the last decade, researchers all over the world have shown strong aspiration to optimize the diagnostics phase in rotating machinery. This paper highlights some of the latest research on the detection of typical faults in rotating machinery such as mass rotor imbalance, misalignment, rub and looseness, bearing and gear faults. Various techniques for condition monitoring have been researched, and in this paper, they have been classified into three groups: physics-based, data-driven, and physics-based data-driven methods. Although most of the research falls into the first two prior mentioned groups, an intent to introduce a novel method, their symbiosis, has emerged in the last few years. The great potential for future work on physics-based data-driven methods in the field of rotating machinery has been briefly discussed. [ABSTRACT FROM AUTHOR]

Introduction: Gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NENs) are malignancies originating from cells of the diffuse endocrine system. They are rare and localize in the upper and lower parts of the gastrointestinal tract and in the pancreas. Despite such a varied location, GEP-NENs are considered a common group of neoplasms due to the fact of their similar morphology and ability to secrete peptide hormones and biologically active amines. They are associated with clinical manifestations specific to the substances produced by a particular neoplasm. The classification of GEP-NENs is constantly systematized and updated based on their differentiation and grading. The development of available diagnostic and treatment methods for these tumors has made significant progress over the past 10 years and is still ongoing. Aim: In the following paper, we review the diagnostics and treatment of GEP-NENs, taking into account the latest molecular, immunological, or gene-based methods. Imaging methods using markers for receptors allow for high diagnostic sensitivity. Methods: Medical databases were searched for the latest information. The authors also sought confirmation of the content of a particular publication in another publications, so as to present the most reliable information possible. Results: Research results revealed that the diagnostics and treatment of GEP-NENs have significantly advanced in recent years. Surgical interventions, especially minimally invasive techniques, have shown efficacy in treating GEP-NENs, with specific therapies such as somatostatin analogs, chemotherapy, and peptide receptor radionuclide therapy demonstrating promising outcomes. The evolution of diagnostic methods, including imaging techniques and biomarker testing, has contributed to improved patient care and prognosis. Conclusions: The increasing incidence of GEP-NENs is attributed to enhanced diagnostic capabilities rather than a rise in population prevalence. The study emphasizes the importance of ongoing research to identify specific markers for early detection and targeted therapies to further enhance the effectiveness of treating these rare and heterogeneous malignancies. The findings suggest a positive trajectory in the management of GEP-NENs, with future prospects focused on personalized and targeted treatment approaches. [ABSTRACT FROM AUTHOR]

Earlier access to patients' biomarker status could transform disease management. However, gold-standard techniques such as enzyme-linked immunosorbent assays (ELISAs) are typically not deployed at the point-of-care due to their cumbersome instrumentation and complexity. Electrochemical immunosensors can be disruptive in this sector with their small size and lower cost but, without further modifications, the performance of these sensors in complex media (e.g., blood) has been limited. This paper presents a low-cost fluidic accessory fabricated using widely accessible materials and processes for boosting sensor sensitivity through confinement of the detection media next to the electrode surface. Liquid confinement first highlighted a spontaneous reaction between the pseudoreference electrode and ELISA detection substrate 3,3',5,5'-tetramethylbenzidine (TMB) that decreases the amount of oxTMB available for detection. Different strategies are investigated to limit this and maximize reliability. Next, flow cell integration during the signal amplification step of sensor preparation was shown to substantially enhance the detection of cytokine interleukin-6 (IL-6) with the best sensitivity boost recorded for fresh human plasma (x7 increase compared to x5.8 in purified serum and x5.5 in PBS). The flow cell requires no specialized equipment and can be seamlessly integrated with commercial sensors, making an ideal companion for electrochemical signal enhancement. [ABSTRACT FROM AUTHOR]

As an integral part of the European strategy for advancing fusion-generated electricity, IFMIF-DONES represents a high-intensity neutron irradiation plant with the main purpose of assessing the suitability of materials for fusion reactor applications. Its primary mission is to examine how materials respond to irradiation within a neutron flux that mimics the conditions expected in the first wall of the proposed DEMO reactor, which is intended to succeed ITER. Consequently, IFMIF-DONES, whose construction is slated to commence shortly, plays a pivotal role in aiding the development, approval, and safe operation of DEMO, as well as future fusion power plants. This paper provides a quick overview of the current development of the IFMIF-DONES neutron source with a particular snapshot of the present engineering design status for what concerns the instrumentation and control systems together with its complex diagnostics, that guarantees the safe monitoring, supervision and regulation of all operations. The current status of design, after the completion of the preliminary design phase is presented, as well as the existing and future plans for their integration also using some of the new capabilities offered by Artificial Intelligence tools. [ABSTRACT FROM AUTHOR]

Thyroglobulin (Tg) is an iodinated glycoprotein, which is normally stored in the follicular colloid of the thyroid, being a substrate for thyroid hormone production. Since it is produced by well-differentiated thyroid cells, it is considered a reliable tumor marker for patients with differentiated thyroid carcinoma (DTC) during their follow-up after total thyroidectomy and radioiodine ablation. It is used to monitor residual disease and to detect recurrent disease. After total thyroid ablation, unstimulated highly sensitive Tg measurements are sufficiently accurate to avoid exogenous or endogenous thyrotropin (TSH) stimulation and provide accurate diagnostic and prognostic information in the great majority of DTC patients. Adopting sophisticated statistical analysis, i.e., decision tree models, the use of Tg before radioiodine theranostic administration was demonstrated to be useful in refining conventional, pathology-based risk stratification and providing personalized adjuvant or therapeutic radioiodine administrations. The follow-up of DTC patients aims to promptly identify patients with residual or recurrent disease following primary treatment. Our review paper covers the diagnostic, theranostic and prognostic value of thyroglobulin in DTC patients. [ABSTRACT FROM AUTHOR]

In today's health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors. [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]

Motivated by the analysis of rating data concerning perceived health status, a crucial variable in biomedical, economic and life insurance models, the paper deals with diagnostic procedures for identifying anomalous and/or influential observations in ordinal response models with challenging data structures. Deviations due to some respondents' atypical behavior, outlying covariates and gross errors may affect the reliability of likelihood based inference, especially when non robust link functions are adopted. The present paper investigates and exploits the properties of the generalized residuals. They appear in the estimating equations of the regression coefficients and hold the remarkable characteristic of interacting with the covariates in the same fashion as the linear regression residuals. Identification of statistical units incoherent with the model can be achieved by the analysis of the residuals produced by maximum likelihood or robust M-estimation, while the inspection of the weights generated by M-estimation allows to identify influential data. Simple guidelines are proposed to this end, which disclose information on the data structure. The purpose is twofold: recognizing statistical units that deserve specific attention for their peculiar features, and being aware of the sensitivity of the fitted model to small changes in the sample. In the analysis of the self-perceived health status, extreme design points associated with incoherent responses produce highly influential observations. The diagnostic procedures identify the outliers and assess their influence. [ABSTRACT FROM AUTHOR]

Single-crystal chemical vapour deposition (CVD) diamond detectors are an established transmissive synchrotron beamline diagnostic instrument used for beam position and beam intensity monitoring. A recently commercialized alternative is silicon carbide (4H-SiC) devices. These have the potential to provide the same diagnostic information as commercially available single-crystal CVD diamond X-ray beam position monitors, but with a much larger transmissive aperture. At Diamond Light Source an experimental comparison of the performance of single-crystal CVD diamond and 4H-SiC X-ray beam position monitors has been carried out. A quantitative comparison of their performance is presented in this paper. The single-crystal diamond and 4H-SiC beam position monitors were installed in-line along the synchrotron X-ray beam path enabling synchronous measurements at kilohertz rates of the beam motion from both devices. The results of several tests of the two position monitors' performance are presented: comparing signal uniformity across the surface of the detectors, comparing kHz intensity measurements, and comparing kHz beam position measurements from the detectors. Each test is performed with a range of applied external bias voltages. A discussion of the benefits and limitations of 4H-SiC and single-crystal CVD diamond detectors is included. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has revolutionized various fields, including healthcare, drug delivery, and material science. Liposomes, as versatile nanocarriers, have emerged as promising tools in AI applications. This paper explores the intersection of liposomes and AI, highlighting their synergistic potential in drug delivery, medical imaging, diagnostics, and beyond. We delve into the mechanisms of liposomal drug delivery and discuss how AI algorithms enhance targeting, efficiency, and therapeutic outcomes. Furthermore, we examine recent advancements in liposomebased imaging agents and biosensors facilitated by AI-driven analysis techniques. Additionally, challenges and future directions in integrating liposomes with AI are discussed, paving the way for innovative solutions in personalized medicine and the diagnostics. [ABSTRACT FROM AUTHOR]

The paper considers the optimal allocation issues of the allocated limited investment costs of a power company for the worn-out and damaged equipment replacement, taking into account the objectively existing limiting technical and economic factors. In particular, the main existing strategies for electrical equipment maintenance and repair used in the world practice are analysed. A fuzzy mathematical model for a comprehensive assessment of the electrical equipment units and groups importance degree in the allocating costs task for the worn and damaged equipment replacement has been developed. A mathematical model of options optimal selection for replacing the power company equipment based on integer programming in limited financial resources conditions is proposed. A technical condition comprehensive modelling of the power system subsystem electrical equipment and modes was carried out to determine the system risk index in case of emergency failures, planned and unplanned electrical equipment decommissioning, and the estimated distribution of power company investment costs for equipment replacement was performed. [ABSTRACT FROM AUTHOR]

Monitoring dynamic load transfer from train traffic to sub-ballast layers is crucial for verifying the reliability and safety of railway lines, assessing the design cost-effectiveness and achieving minimum environmental impact. For this purpose, measurements in labs, in situ or modeling the influence of dynamic loads on the immediate and long-term roadway quality are often performed using suitable software. The available test sections enabled monitoring of the dynamic loads and optimizing the critical spots where increased dynamic effects from railway traffic may occur. The subject of this paper is the calibration of the sensors installed in the different test sections of the trans-European corridor number V. As a result, the necessary input parameters for the subsequent numerical modeling of the dynamic effects on the track substructure and vibration propagation on the available sections of the upgraded railway line were obtained. The sensor calibration was carried out on the experimental field, part of the Experimental Basis of the Department of Railway Engineering and Track Management. As part of the calibration, the sensitivity of the sensors embedded in the track bed to the applied dynamic loads resulting from the impact effects of the lightweight deflectometer was assessed. The result of the calibration was the demonstration of sufficient sensitivity of the sensors and their suitability for implementation in an actual railway track structure, with the aim of obtaining relevant values of the response of the sub-ballast layers to dynamic loads and assessing the operational impacts on the sustainable environment. Also, the main result of the research was the possibility of using the theoretical–experimental route to optimize the layers of the railway body. [ABSTRACT FROM AUTHOR]

In the realm of space exploration, solid rocket motors (SRMs) play a pivotal role due to their reliability and high thrust-to-weight ratio. Serving as boosters in space launch vehicles and employed in military systems, and other critical & emerging applications, SRMs' structural integrity monitoring, is of paramount importance. Traditional maintenance approaches often prove inefficient, leading to either unnecessary interventions or unexpected failures. Condition-based maintenance (CBM) emerges as a transformative strategy, incorporating advanced sensing technologies and predictive analytics. By continuously monitoring crucial parameters such as temperature, pressure, and strain, CBM enables real-time analysis, ensuring timely intervention upon detecting anomalies, thereby optimizing SRM lifecycle management. This paper critically evaluates conventional SRM health diagnosis methods and explores emerging sensing technologies. Photonic sensors and fiber-optic sensors, in particular, demonstrate exceptional promise. Their enhanced sensitivity and broad measurement range allow precise monitoring of temperature, strain, pressure, and vibration, capturing subtle changes indicative of degradation or potential failures. These sensors enable comprehensive, non-intrusive monitoring of multiple SRM locations simultaneously. Integrated with data analytics, these sensors empower predictive analysis, facilitating SRM behavior prediction and optimal maintenance planning. Ultimately, CBM, bolstered by advanced photonic sensors, promises enhanced operational availability, reduced costs, improved safety, and efficient resource allocation in SRM applications. [ABSTRACT FROM AUTHOR]

In the field of aircraft engine diagnostics, many advanced algorithms have been proposed over the last few years. However, there is still wide room for improvement, especially in the development of more integrated and complete engine health management systems to detect, identify, and forecast complex faults in a short time. Furthermore, it is necessary to ensure that these systems preserve their capabilities over time despite engine deterioration. This paper addresses these necessities by proposing an integrated system that considers the joint operation of feature extraction, anomaly detection, fault identification, and prognostic algorithms for engines with long operation times. To effectively reveal the actual engine condition, light adaptive degraded engine models are computed along with different health indicators that are used as inputs to train and test recognition and prediction models. The system is developed and evaluated using a specialized NASA platform which provides data from a turbofan engine fleet simultaneously experiencing long-term performance deterioration and faults. Contrary to other compared solutions, our results show that the proposed system is robust against the effects of engine deterioration, maintaining its level of detection, recognition, and prediction accuracy over a total engine service life. The low computational cost algorithms has generally fast performance in all stages, making the system suitable for online applications. [ABSTRACT FROM AUTHOR]

Background: Preterm birth (PTB) is a leading cause of childhood disability, and it has become a key public health priority recognized by the World Health Organization and the United Nations. Objectives: This review will: (1) summarize current practice in the diagnosis and management of PTB, (2) outline developments in precision-based medicine for diagnostics to improve the care provided to pregnant women at risk of PTB, and (3) discuss the implications of current research in personalized medicine and the potential of future advances to influence the clinical care of women at risk of PTB. Methodology: This is a narrative literature review. Relevant journal articles were identified following searches of computerized databases. Key Results: Current and emerging technologies for the utility of personalized medicine in the context of PTB have the potential for applications in: (1) direct diagnostics to identify and target infection as one of the main known causes of PTB, (2) identifying novel maternal and fetal biomarkers, (3) the use of artificial intelligence and computational modeling, and (4) combining methods to enhance diagnosis and treatment. Conclusions: In this paper, we show how current research has moved in the direction of the targeted use of biomarkers in the context of PTB, with many novel approaches. [ABSTRACT FROM AUTHOR]

Ganoderma boninense (G. boninense) is a soil-borne fungus threatening oil palm at the present. It causes basal stem rot disease on oil palm. Within six months, this fungus can cause an oil palm plantation to suffer a significant 43% economic loss. The high persistence and nature of spread of G. boninense in soil make control of the disease challenging. Therefore, controlling the pathogen requires a thorough understanding of the mechanisms that underlie pathogenicity as well as its interactions with host plants. In this paper, we present the general characteristics, the pathogenic mechanisms, and the host's defensive system of G. boninense. We also review upcoming and most promising techniques for disease management that will have the least negative effects on the environment and natural resources. [ABSTRACT FROM AUTHOR]

Featured Application: This approach is suitable for diagnostics of other systems in terms of real-time fault identification and mitigation. It will also be useful in the field of digital twin applications. Many different types of aircraft designs have flight control systems (FCS) powered by hydraulic systems. With respect to the torques, moments, surface areas, and opposing forces to be acted upon, components introduce faults into the hydraulic system when these components are aging or degrading. The diagnostics of a hydraulically powered flight control actuation system (HPFCAS) rely on the faults produced within the subsystem components as well as the entire system's mechanism itself. In this paper, a model for an HPFCAS is developed to analyze faults where the HPFCAS was approached as a system of systems (SOS). The identified faults were injected into the system. It is established that some of the faults from the different subsystems had similar characteristic effects and were propagated with attendant consequences. For instance, a measured decrease in the pressure value is observed because of the decrease in the pump speed. A similar characteristic is observed if there is leakage on the line or if there is a clogging valve. These form complex integrated responses in determining where the fault is coming from if only one component is analyzed since it involves components serving different subsystems. Results show that only models that can describe the real characteristics or attributes of the specific systems, due to their defined components, are sufficient for effective diagnostics. This is because the data obtained are more accurate at predicting the behavior of components. [ABSTRACT FROM AUTHOR]

This paper presents a methodology that is designed for rapid exploratory analysis of the outputs from ensembles of climate models, especially when these outputs consist of maps. The approach formalizes and extends the technique of "intermodel empirical orthogonal function" analysis, combining multivariate analysis of variance techniques with singular value decompositions (SVDs) of structured components of the ensemble data matrix. The SVDs yield spatial patterns associated with these components, which we call ensemble principal patterns (EPPs). A unique hierarchical partitioning of variation is obtained for balanced ensembles in which all combinations of factors, such as GCM and RCM pairs in a regional ensemble, appear with equal frequency: suggestions are also proposed to handle unbalanced ensembles without imputing missing values or discarding runs. Applications include the selection of ensemble members to propagate uncertainty into subsequent analyses, and the diagnosis of modes of variation associated with specific model variants or parameter perturbations. The approach is illustrated using outputs from the EuroCORDEX regional ensemble over the United Kingdom. [ABSTRACT FROM AUTHOR]

Better diagnostics are always essential for the treatment and prevention of a disease. Existing technologies for detecting infectious and non-infectious diseases are mostly tedious, expensive, and do not meet the World Health Organization's (WHO) ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end user) criteria. Hence, more accurate, sensitive, and faster diagnostic technologies that meet the ASSURED criteria are highly required for timely and evidenced-based treatment. Presently, the diagnostics industry is finding interest in microfluidics-based biosensors, as this integration comprises all qualities, such as reduction in the size of the equipment, rapid turnaround time, possibility of parallel multiple analysis or multiplexing, etc. Microfluidics deal with the manipulation/analysis of fluid within micrometer-sized channels. Biosensors comprise biomolecules immobilized on a physicochemical transducer for the detection of a specific analyte. In this review article, we provide an outline of the history of microfluidics, current practices in the selection of materials in microfluidics, and how and where microfluidics-based biosensors have been used for the diagnosis of infectious and non-infectious diseases. Our inclination in this review article is toward the employment of microfluidics-based biosensors for the improvement of already existing/traditional methods in order to reduce efforts without compromising the accuracy of the diagnostic test. This article also suggests the possible improvements required in microfluidic chip-based biosensors in order to meet the ASSURED criteria. [ABSTRACT FROM AUTHOR]

Currently, applications of the algorithms based on artificial intelligence (AI) principles can be observed in various fields. This can be also noticed in the wide area of electrical drives. Consideration has been limited to neural networks; however, the tasks for the models can be defined as follows: control, state variable estimation, and diagnostics. In the subsequent sections of this paper, electrical machines, as well as power electronic devices, are assumed as the main objects. This paper describes the basics, issues, and possibilities related to the used tools and explains the growing popularity of neural network applications in automatic systems with electrical drives. The paper begins with the overall considerations; following that, the content proceeds with the details, and two specific examples are shown. The first example deals with a neural network-based speed controller tested in a structure with a synchronous reluctance motor. Then, the implementation of recurrent neural networks as state variable estimators is analyzed. The achieved results present a precise estimation of the load speed and the shaft torque signals from a two-mass system. All descriptions in the article are considered in the context of the trends and perspectives in modern algorithm applications for electrical drives. [ABSTRACT FROM AUTHOR]

The paper presents probabilistic aspects of diagnostics of grinding processes with consideration of metrological aspects of evaluation of topography of machined surfaces and selected problems of assessment of machining accuracy. The processes of creating the geometric structure of the ground surface are described. It was pointed out that the distribution of features important for process diagnostics depends on the mechanism of cumulative effects of random disturbances. Usually, there is a multiplicative mechanism or an additive mechanism of the component vectors of relative displacements of the tool and workpiece. The paper describes a method for determining the classification ability of specific parameters used to evaluate stereometric features of ground surfaces. It is shown that the ability to differentiate the geometric structure of a certain set of surfaces using a selected parameter depends on the geometric mean of the differences in normalized and sorted, consecutive values of this parameter. A methodology is presented for evaluating the ability of various parameters to distinguish different geometric structures of surfaces. Further, on the basis of analyses of a number of grinding processes, a methodology was formulated for proceeding leading to a comprehensive evaluation of machining accuracy and forecasting its results. It was taken into account that in forecasting the accuracy of grinding, it is necessary to determine the deviations, arising under the conditions of multiplicative interaction of the effects of various causes of inaccuracy. Examples are given of processes in which, due to the deformation of the technological system, dependent on the position of the zone and machining force, varying temperature fields and tool wear, the distributions of dimensional deviations are not the realization of stationary processes. It was emphasized that on the basis of the characteristics of the dispersion of the deviation value in the sum set of elements, it is not possible to infer its causes. Only the determination of the "instantaneous" values of the deviation dispersion parameters allows a more complete diagnosis of the process. [ABSTRACT FROM AUTHOR]

Aircraft systems are designed to perform functions that will aid the various missions of the aircraft. Their performance, when subjected to an unfamiliar condition of operation, imposes stress on them. The system components experience degradation due to fault which ultimately results in failure. Maintenance and monitoring mechanisms are put in place to ensure these systems are readily available when required. Thus, the sensing of parameters assists in providing conditions under which healthy and faulty scenarios can be indicated. To obtain parameter values, sensor data is processed, and the results are displayed so that the presence of faults may be known. Some faults are intermittent and incipient in nature. These are not discovered easily and can only be known through a display of unusual system performance by error code indication. Therefore, the assessed faults are transmitted to a maintenance crew by error codes. The results may be fault found (FF), no fault found (NFF), or cannot display (CND). However, the main classification of the faults and their origins may not be known in the system. This continues throughout the life cycle of the system or equipment. This paper reviews the diagnostic methods used for the hydraulically powered flight control actuation system (HPFCAS) of an aircraft and its interaction with other aircraft systems. The complexities of the subsystem's integration are discussed, and different subsystems are identified. Approaches used for the diagnostics of faults, such as model-based, statistical mapping and classification, the use of algorithms, as well as parity checks are reviewed. These are integrated vehicle health management (IVHM) tools for systems diagnostics. The review shows that when a system is made up of several subsystems on the aircraft with dissimilar functions, the probability of fault existing in the system increases, as the subsystems are interconnected for resource sharing, space, and weight savings. Additionally, this review demonstrates that data-driven approaches for the fault diagnostics of components are good. However, they require large amounts of data for feature extraction. For a system such as the HPFCAS, flight-management data or aircraft maintenance records hold information on performance, health monitoring, diagnostics, and time scales during operation. These are needed for analysis. Here, a knowledge of training algorithms is used to interpret different fault scenarios from the record. Thus, such specific data are not readily available for use in a data-driven approach, since manufacturers, producers, and the end users of the system components or equipment do not readily distribute these verifiable data. This makes it difficult to perform diagnostics using a data-driven approach. In conclusion, this paper exposes the areas of interest, which constitute opportunities and challenges in the diagnostics and health monitoring of flight-control actuation systems on aircraft. [ABSTRACT FROM AUTHOR]

Printed circuit board assembly (PCBA) is a cost-effective hardware device used in mechanical, process, electrical, electronic, military, and medical equipment providing automated and digital functionalities for users. Keeping high quality standards in the PCBA production process is a major challenge for the electronics production industry. Defective PCBAs are submitted to analysis, debug, and repair processes. This paper presents an augmented reality (AR) fault diagnosis support system for assembled electronic systems—the Cadence inspectAR Augmented Reality Electronics Platform. The system's functional concept and components are described. The steps of the diagnostic process are presented and discussed. The diagnostic capabilities of the system are illustrated with an example of the system's use in industrial practice. The planned steps in the development of the elaborated system are indicated. [ABSTRACT FROM AUTHOR]

Analysis of the method of using sonography during surgery in animals with polycystic kidney disease is an urgent task since firstly, sonography is a safe and non-invasive method of examination, which allows determining the structural features of the kidneys before, during, and after surgery. Secondly, from the standpoint of improving the results of surgery, sonography helps to clarify the localisation of cysts and determine their size. Thirdly, an important factor in the use of sonography is the reduction of pain and the risk of postoperative complications. In addition, due to this method of kidney examination, it is possible to more accurately determine the optimal route of access to cysts, which helps to reduce tissue injury and ensures rapid recovery of the animal after surgery. The purpose of the study is to analyse in detail and describe the method of using sonography during surgery in animals with polycystic kidney disease. The study focuses on the need to determine how sonography affects reducing the duration of surgery, improving the quality of cyst removal, and reducing the risk of complications during abdominal surgery. The approach in this study is based on the analysis of scientific papers on this subject, in particular on the experience of veterinarians who have already used sonography during abdominal operations in animals with polycystic kidney disease. Thus, special techniques of sonography and surgical treatment of kidney cysts include dopplerography, colour dopplerography, 3D and 4D sonography, elastography, introperative sonography, intraperitoneal sonography, and duplex scanning of renal arteries and veins. Surgical methods of treatment include extraction of individual cysts, drainage of cysts, resection, and nephrectomy. The use of sonography at different stages of surgical intervention helps to optimise the operation process, reduce the risk of complications, and contribute to the introduction of new approaches in the treatment of animals with polycystic kidney disease, which will substantially improve their quality of life [ABSTRACT FROM AUTHOR]

The article diagnoses the prospects for the development of enterprises for the processing of solid household waste (SHW). It is specified that improving the quality of services provided by enterprises and the transition to European standards in the field of removal, utilization and processing of solid waste is a top priority, as Ukraine seeks to become a member of the EU in the future. It is noted that recycling is an important component of sustainable development and contributes to the creation of a more efficient and environmentally conscious economy for enterprises and the country. The most common types of solid waste recycling are presented, each of which is aimed at transforming a specific type of waste. The paper analyzes successful business cases that have already been implemented as a result of recycled solid waste and introduced into practice in other countries of the world. It is noted that some Ukrainian enterprises in collaboration with foreign partners have actively begun to implement similar cases. It is noted that a promising direction is the energy sector, which is currently also related to the processing of solid waste. It is noted that, even taking into account the active hostilities taking place on the territory of Ukraine, there are enterprises, organizations and institutions that are already actively working or just starting their business activities in the field of SHW processing. It is concluded that it is an important aspect, in particular, firstly, how the growing awareness of society about the problems of environmental pollution and the need to protect it creates a demand for environmentally friendly technologies and services, including waste recycling. Secondly, legislative and regulatory initiatives aimed at reducing waste and improving waste management create a favorable framework for the development of this sector. Thirdly, technological progress in the field of recycling makes it possible to create new products from waste and reduce the negative impact on the environment. Also, the development of this sector can stimulate investment and contribute to the creation of new jobs in the field of ecological economy. All this testifies to the potentially high investment attractiveness and prospects for the development of solid waste processing enterprises. [ABSTRACT FROM AUTHOR]

Sarcosporidia and sarcosporidiosis in Southeast Kazakhstan present formidable challenges to livestock health. This paper focuses on the outcomes of two key innovations: advancements in molecular diagnostics and the development of integrated control strategies. In the realm of diagnostics, the implementation of Polymerase Chain Reaction (PCR) techniques for species-specific identification and quantification yielded notable results. Our comprehensive survey of vertebrates in the region identified a diverse range of Sarcosporidia species, with an average prevalence reduction of 25% compared to conventional methods. This advancement not only enhances accuracy in parasite identification but also provides a more nuanced understanding of the local epidemiological landscape. The integration of Geographic Information System (GIS) and remote sensing technologies into our surveillance system revealed specific high-risk areas with an unprecedented precision of 90%. This targeted approach allowed for resource optimization, resulting in a 30% reduction in overall prevalence rates in the identified regions. The practical implications of this innovation are evident in its potential to guide effective intervention strategies and resource allocation. Genomic studies elucidated the genetic diversity within Sarcosporidia strains, laying the foundation for targeted interventions. Building on this knowledge, preliminary trials of our integrated control strategies showcased a promising 40% reduction in Sarcosporidia prevalence in the selected communities. This innovative approach combines traditional deworming practices with environmentally friendly treatments, providing a viable and sustainable solution. In conclusion, our research signifies a substantial leap forward in understanding and combating Sarcosporidia infections in Southeast Kazakhstan. The tangible results of improved diagnostics and the promising outcomes of integrated control strategies underscore the potential for transformative impacts on livestock health, agricultural productivity, and the well-being of the communities reliant on these animals. [ABSTRACT FROM AUTHOR]

Molecular sampling with vacuum-assisted tissue electroporation is a novel, minimally invasive method for molecular profiling of solid lesions. In this paper, we report on the design of the battery-powered pulsed electric field generator and electrode configuration for an electroporation-based molecular sampling device for skin cancer diagnostics. Using numerical models of skin electroporation corroborated by the potato tissue phantom model, we show that the electroporated tissue volume, which is the maximum volume for biomarker sampling, strongly depends on the electrode's geometry, needle electrode skin penetration depths, and the applied pulsed electric field protocol. In addition, using excised human basal cell carcinoma (BCC) tissues, we show that diffusion of proteins out of human BCC tissues into water strongly depends on the strength of the applied electric field and on the time after the field application. The developed numerical simulations, confirmed by experiments in potato tissue phantoms and excised human cancer lesions, provide essential tools for the development of electroporation-based molecular markers sampling devices for personalized skin cancer diagnostics. [ABSTRACT FROM AUTHOR]

This paper is concerned with possible model misspecification in moment inequality models. Two issues are addressed. First, standard tests and confidence sets for the true parameter in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a pseudo-true parameter in such scenarios, and hence, do not suffer from spurious precision. Second, specification tests have relatively low power against a range of misspecified models. Thus, failure to reject the null of correct specification does not necessarily provide evidence of correct specification. That is, model specification tests are subject to the problem that absence of evidence is not evidence of absence. This paper develops new diagnostics for model misspecification in moment inequality models that do not suffer from this problem. [ABSTRACT FROM AUTHOR]

Copyright of FME Transactions is the property of University of Belgrade, Faculty of Mechanical Engineering 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.)

This work is an introduction of acoustic emission (AE) signals used in order to detect the malfunction of selected semiconductor elements. The authors proposed the use of internally generated signals (elastic waves) of acoustic emission leading to the detection of the pre-fail state of switching IGBT transistors. The analysis of the AE signals allows the creation of a reference pattern of properly working transistors and at the same time the identification of abnormal signals, which are generated by a defective element. Unlike many papers, this article shows experimental results demonstrating a comparison of undamaged, properly working and defective IGBT transistors which can be used, for example, as a reference for diagnostic tools. Analysis of the signal in the frequency domain obtained from the faulty transistor (overheated or with damaged casing) shows the presence of additional frequencies which can indicate the imminent occurrence of critical damage. [ABSTRACT FROM AUTHOR]

An electrical device (attachment) for shaping voltage to test the insulation of 6 – 10 kV cable lines is considered. The attachment is capable of generating an ultralow-frequency (0.1 Hz) voltage of 40 kV and a rectified negative-polarity voltage of 60 kV, which allows testing the condition of the insulation of high-voltage cable lines with cross-linked polyethylene insulation and cables with impregnated paper insulation. The device is applicable to 6 – 10 kV distribution networks. It has low weight and dimensions (20 kg and 456 × 363 × 181 mm). Its maximum leakage current is 50 mA. The device can operate from 12 V power supplies, which makes it more mobile. The remote wireless control unit reduces the risk of electrical injuries during high-voltage testing. The attachment is aimed at improving the reliability of the integrated power grid by reducing the number of insulation failures during the transmission of electric power through cable lines of distribution networks. [ABSTRACT FROM AUTHOR]

Bridges, as public structures, are national infrastructure structures. The investment requirements and demands for safe operation should put them at the forefront of engineers' attention. The important SNP bridge in Bratislava (Slovakia), which is one of the first bridges in the world to be suspended entirely on cables, has been the subject of a diagnosis of its health after 50 years of operation. The article describes and documents the individual steps of this diagnostics ‐ identification of the rope material, the status of the rope material and its current strength properties, and the experimentally and computationally determination of the forces in the individual ropes and their cables. The uniqueness of all the diagnostic steps was that they were carried out directly in the outdoor conditions of full operation of the bridge. The achieved results are briefly documented in the paper. Conclusions and further necessary steps for the final comprehensive safety assessment of the bridge operation are formulated. [ABSTRACT FROM AUTHOR]

Background: Advancements in genomic technologies are rapidly evolving, with the potential to transform laboratory diagnostics by enabling high-throughput analysis of complex biological data, such as microbiome data. Large Language Models (LLMs) have shown significant promise in extracting actionable insights from vast datasets, but their application in generating microbiome findings reports with clinical interpretations and lifestyle recommendations has not been explored yet. Methods: This article introduces an innovative framework that utilizes LLMs to automate the generation of findings reports in the context of microbiome diagnostics. The proposed model integrates LLMs within an event-driven, workflow-based architecture, designed to enhance scalability and adaptability in clinical laboratory environments. Special focus is given to aligning the model with clinical standards and regulatory guidelines such as the In-Vitro Diagnostic Regulation (IVDR) and the guidelines published by the High-Level Expert Group on Artificial Intelligence (HLEG AI). The implementation of this model was demonstrated through a prototype called "MicroFlow". Results: The implementation of MicroFlow indicates the viability of automating findings report generation using LLMs. Initial evaluation by laboratory expert users indicated that the integration of LLMs is promising, with the generated reports being plausible and useful, although further testing on real-world data is necessary to assess the model's accuracy and reliability. Conclusions: This work presents a potential approach for using LLMs to support the generation of findings reports in microbiome diagnostics. While the initial results seem promising, further evaluation and refinement are needed to ensure the model's effectiveness and adherence to clinical standards. Future efforts will focus on improvements based on feedback from laboratory experts and comprehensive testing on real patient data. [ABSTRACT FROM AUTHOR]

This paper presents a systematic literature survey on diagnostic methods used for railway materials and systems. The authors analyze various railway accident reports, focusing on the types of failures described and their causes. Previous review papers have addressed various aspects of railway systems diagnostics; however, most of the existing research focuses on specific parts of the rail vehicle or subsystems. In contrast, this survey focuses on railway diagnostic systems rather than general diagnostic methods used in mechanical and electrical engineering. The authors classify the types of failures and diagnostic methods that are used in rail transport into two categories: infrastructure and rolling stock. The purpose of this paper is to systematize the types of failure that occur in railway transport systems; identify the state-of-the-art means and methods of diagnostics in railway materials and systems, with particular focus on new research findings; and identify trends and possible research gaps in need of further development.

Copyright of Journal of Laboratory Diagnostics / Diagnostyka Laboratoryjna is the property of Index Copernicus International 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.)

This paper presents the roadmap of the main materials to be used for ITER and DEMO class reactors as well as an overview of the most relevant innovations that have been made in recent years. The main idea in the EUROfusion development program for the FW (first wall) is the use of low-activation materials. Thus far, several candidates have been proposed: RAFM and ODS steels, SiC/SiC ceramic composites and vanadium alloys. In turn, the most relevant diagnostic systems and PFMs (plasma-facing materials) will be described, all accompanied by the corresponding justification for the selection of the materials as well as their main characteristics. Finally, an outlook will be provided on future material development activities to be carried out during the next phase of the conceptual design for DEMO, which is highly dependent on the success of the IFMIF-DONES facility, whose design, operation and objectives are also described in this paper. [ABSTRACT FROM AUTHOR]

The transition from internal combustion to electric propulsion in cars presents component designers with new challenges in terms of noise reduction. Until now, components such as the suspension, its knocks were masked by the combustion engine or exhaust system. The absence of such significant sources, means that hitherto inaudible components are starting to become a nuisance. In order to reduce their noise, a number of optimisation solutions, both active and passive, are used. In order to do so, relevant measurements and data analysis must be carried out. This paper aims to present the acoustic characteristics of the interiors of two cars excited structurally in the vicinity of the front shock absorber mounting and by the operation of another component, the windscreen wipers on dry and wet windscreens. Measurements were made using 3D intensity probes based on acoustic particle velocity sensors. The results, in the form of both acoustic particle velocity and sound pressure characteristics and spectrograms, are presented comparatively for two types of car. [ABSTRACT FROM AUTHOR]

Purpose of Review: The objective of this paper is to review the armamentarium of tests available for diagnosis of invasive fungal infections (IFI) in lung transplant recipients (LTs), focusing on developments over the last 5 years. Recent Findings: The use of fungal biomarkers is increasing, especially Aspergillus galactomannan, which now has an established role in diagnosis and prevention of invasive aspergillosis. Molecular diagnostics are increasingly being applied to tissue and other specimens to assist identification of fungi. Functional imaging has an evolving role, improving diagnostic precision and time to diagnosis. Summary: While demonstration of fungi in tissue obtained biopsy remains the gold standard for diagnosis of IFI in LTs, this is not always possible. There are now a host of biomarkers, molecular, and imaging techniques available that are less invasive and allow earlier diagnosis of IFIs. [ABSTRACT FROM AUTHOR]