Interpretation Of Data Research Articles

Neutralizing Antibody Sample Testing and Report Harmonization

Immunogenicity testing and characterization is an important part of understanding the immune response to administration of a protein therapeutic. Neutralizing antibody (NAb) assays are used to characterize a positive anti-drug antibody (ADA) response. Harmonization of reporting of NAb assay performance and results enables efficient communication and expedient review by industry and health authorities. Herein, a cross-industry group of NAb assay experts have harmonized NAb assay reporting recommendations and provided a bioanalytical report (BAR) submission editable template developed to facilitate agency filings. This document addresses key bioanalytical reporting gaps and provides a report structure for documenting clinical NAb assay performance and results. This publication focuses on the content and presentation of the NAb sample analysis report including essential elements such as the method, critical reagents and equipment, data analysis, study samples, and results. The interpretation of immunogenicity data, including the evaluation of the impact of NAb on safety, exposure, and efficacy, is out of scope of this publication.Graphical

Integrated interpretation of geophysical data in the area of local gravity anomalies in the North of the Volga-Ural anteclise

Integrated interpretation of geophysical data in the area of local gravity anomalies in the North of the Volga-Ural anteclise

Effect of spin-lock frequency on quantitative myocardial T1ρ mapping

ObjectivesTo use T1ρ mapping to assess myocardial fibrosis and to provide a reference for future clinical application, it is necessary to understand the factors influencing T1ρ values. This study explored the influence of different spin-locking frequencies on T1ρ values under a 3.0-T MR system.MethodsFifty-seven healthy subjects were prospectively and consecutively included in this study, and T1ρ mapping was performed on them in 3 short-axis slices with three spin-lock frequencies at the amplitude of 300 Hz, 400 Hz, and 500 Hz, then nine T1ρ images were acquired per subject. Four T1ρ-weighted images were acquired using a spin-lock preparation pulse with varying durations (0 msec, 13.3 msec, 26.6 msec, 40 msec). T1ρ relaxation times were quantified for each slice and each myocardial segment. The results were analyzed using Student’s t-test and one-way analysis of variance (ANOVA) methods.ResultsMean T1ρ relaxation times were 43.5 ± 2.8 msec at 300 Hz, 44.9 ± 3.6 msec at 400 Hz, and 46.2 ± 3.1 msec at 500 Hz, showing a significant progressive increase from low to high spin-lock frequency (300 Hz vs. 400 Hz, p = 0.046; 300 Hz vs. 500 Hz, p < 0.001; 400 Hz vs. 500 Hz, p = 0.043). In addition, The T1ρ values of females were significantly higher than those of males (300 Hz, p = 0.049; 400 Hz, p = 0.01; 500 Hz, p = 0.002).ConclusionIn this prospective study, myocardial T1ρ values for the specific CMR setting are provided, and we found that gender and spin-lock frequency can affect the T1ρ values.Critical relevance statementT1ρ mapping could supersede late gadolinium enhancement for detection of myocardial fibrosis. Establishing reference mean values that take key technical elements into account will facilitate interpretation of data in disease states.Key PointsThis study established myocardial T1ρ reference values for different spin-lock frequencies.T1ρ values increased with spin-lock frequency, but numerical differences were minimal.Females had higher T1ρ values than males at all frequencies.Graphical

Semiotics Performance in The Poem “Tentang Mata” and “Tentang Mata Pula” By W.S. Rendra

Literary works are created to be enjoyed and appreciated by society. The formulation of the research argues about the language style, vocabulary, and intended meaning of the poem “Tentang Mata” and “Tentang Mata Pula” by W.S. Rendra. This research is to obtain a clear picture of the poem “Tentang Mata” and “Tentang Mata Pula” through a stylistic approach. The benefits of this research contribute to the development of linguistics applied and linguistic analysis from literary works, provide insight to scholars on how to conduct linguistic analysis of literary works, and become alternative teaching materials for language and literature teachers. The research approach uses a descriptive qualitative method in literature in line with stylistics. The research data were analyzed using data collection techniques involving the steps of data identification, data classification, and deductive data interpretation. The results of the research describe the conditions and situations that occurred in 1998, with the emergence of many connotative words in raising the issue of fate and living conditions, from poverty. In addition, it is presented that society itself is only chasing dreams by creating conditions and situations that are already disproportionate

Multilevel Factors Impacting Substance Use Treatment Access, Engagement, and Racial Equity Among Opioid Overdose Survivors in Boston, MA.

There are well-documented racial/ethnic inequities in drug-related overdoses and access to evidence-based opioid use services nationally and in Boston, MA. To qualitatively explore the drivers of racial/ethnic inequities in access to opioid use disorder treatment and services in Boston. Semi-structured qualitative interviews. Using purposive sampling, researchers recruited 59 opioid overdose survivors in Boston who self-identified as Black, Hispanic or Latino/a/x, and/or White. Interviewers administered a socio-demographic and drug use survey, and used a semi-structured interview guide to explore experiences with and perspectives on substance use treatment and services. Participants' racial/ethnic identities were distributed across three subgroups: non-Hispanic Black (n = 18; 31%), non-Hispanic White (n = 18; 31%), and Latino/a/x (n = 23; 39%). Qualitative analysis identified multiple themes that were organized into four social-ecological levels after analysis. At the individual level, some participants emphasized the importance of personal responsibility and individual motivation in determining access to services. Participants expressed a range of perspectives about using medication for opioid use disorder treatment; Black and Latino/a/x participants were more likely than White participants to have critical perspectives. At the interpersonal level, experiences of bias, stigma, and racism from staff in healthcare and treatment settings were common. At the program/process level, participants described challenges connecting to services following overdose and barriers within specific programs, with Black and Latino/a/x participants experiencing particular gaps. At the systems level, the limited availability of housing, employment, and mental health care negatively impacted treatment access and engagement. A racism lens was used during data interpretation to apply the themes at a broader population level. Through this lens, the identified barriers can be understood to have a disproportionate impact on people of color. Findings call for programmatic and policy solutions that address racism, break down stigma, and ensure equitable access to evidence-based services and social supports.

Radiation Chemistry and Radiation Research: A History from the Beginning to the Platinum Edition.

At the dawn of the 20th Century, the underlying chemistry that produced the observed effects of ionizing radiation, e.g., X rays and Radium salts, on aqueous solutions was either unknown or restricted to products found postirradiation. For example, the Curies noted that sealed aqueous solutions of Radium inexplicably decomposed over time, even when kept in the dark. By 1928 there were numerous papers describing the phenomenological effects of ionizing radiation on a wide variety of materials, including the irradiated hands of early radiologists. One scientist who became intensely interested in these radiation effects was Hugo Fricke (Fricke Dosimetry) who established a laboratory in 1928 dedicated to studies on chemical effects of radiation, the results of which he believed were necessary to understand observed radiobiological effects. In this Platinum Issue of Radiation Research (70 years of continuous publication), we present the early history of the development of radiation chemistry and its contributions to all levels of mechanistic radiobiology. We summarize its development as one of the four disciplinary pillars of the Radiation Research Society and its Journal, Radiation Research, founded during the period 1952-1954. In addition, the work of scientists who contributed substantially to the discipline of Radiation Chemistry and to the birth, life and culture of the Society and its journal is presented. In the years following 1954, the increasing knowledge about the underlying temporal and spatial properties of the species produced by various types of radiation is summarized and related to its radiobiology and to modern technologies (e.g., pulsed radiolysis, electron paramagnetic resonance) which became available as the discipline of radiation chemistry developed. A summary of important results from these studies on Radiation Chemistry/Biochemistry in the 20th and 21st Century up to the present time is presented. Finally, we look into the future to see what possible directions radiation chemistry studies might take, based upon promising current research. We find at least two possible directions that will need radiation chemistry expertise to ensure proper experimental design and interpretation of data. These are FLASH radiotherapy, and mechanisms underlying the effects of low doses of radiation delivered at low dose rates. Examples of how radiation chemists could provide beneficial input to these studies are provided.

Raising nurse educators’ awareness regarding caring pedagogical relationships’ barriers to foster inclusive simulation settings: Insights from a phenomenological study

AimThe purpose of this paper was to shed light on the main barriers to caring pedagogical relationships within simulation centers from the perspective of nursing students and offer targeted strategies to reduce these barriers. BackgroundA caring pedagogical relationship is a powerful strategy to foster students’ learning within simulation settings. However, the development of this relationship could be hindered if nurse educators are not aware of its barriers. Hence, this could affect students’ learning and well-being within this academic context. According to our knowledge, no previous research has addressed the question of the barriers to caring pedagogical relationships within the context of simulation. DesignThis study employed a descriptive phenomenological method, entitled Relational Caring Inquiry, to collect and analyze data gathered from 19 students enrolled in an undergraduate nursing program. ResultsThis paper focuses on one eidos-theme that emerged from our data analysis and interpretation entitled “Educator’s conscientization regarding barriers to the development of a caring pedagogical relationship”. According to data analysis and interpretation, this eidos-theme was the most emphasized by research participants. It emerged from the following themes: (a) educators’ dehumanizing practices, (b) disruptive and stressful academic context, (c) lack of educators’ experiences and (d) educators’ disinterest in students’ learning. ConclusionsLeaving caring pedagogical relationships’ barriers unaddressed has shown adverse impacts on students’ learning process and their mental and physical well-being. This paper brings to light the main barriers to caring pedagogical relationships and invites educators, managers and nurse leaders to be aware of these obstacles and collectively engage in humanizing nursing education. In other words, we emphasize the impact of these barriers on students’ apprenticeship and suggest political actions to build caring and inclusive simulation environments. Study Registration NumberCERSES-19–050-D.

Twenty Years in EUCAST Anti-Fungal Susceptibility Testing: Progress & Remaining Challenges.

Since its inception in 2002, the EUCAST Antifungal Susceptibility Testing Subcommittee (AFST) has developed and refined susceptibility testing methods for yeast, moulds and dermatophytes, and established epidemiological cut-off values and breakpoints for antifungals. For yeast, three challenges have been addressed. Interpretation of trailing growth in fluconazole susceptibility testing, which has been proven without impact on efficacy if below the 50% endpoint. Variability in rezafungin MIC testing due to laboratory conditions, which has been solved by the addition of Tween 20 to the growth medium in E.Def 7.4. And third, interpretation of MICs for rare yeast with no breakpoints, where recommendations have been established for MIC-based clinical advice. For moulds, refinements include the validation of spectrophotometer reading for A. fumigatus to facilitate objective MIC determination, and for dermatophytes the establishment of a microdilution method with automated reading and a selective medium to minimise the risk of contaminations. Recent initiatives involve development and validation of agar-based screening assays for detection of potential azole and echinocandin resistance in A. fumigatus and Aspergillus species, respectively, and of terbinafine resistance in Trichophyton species. Moreover, the development of a EUCAST guidance document for molecular resistance testing represents an advancement, particularly for identifying target gene alterations associated with resistance. In summary, EUCAST AFST continues to play a pivotal role in standardizing AFST and facilitating accurate interpretation of susceptibility data for clinical decision-making. Adoption of EUCAST breakpoints for commercial test methods, however, requires thorough validation to ensure concordance with EUCAST reference testing species-specific MIC distributions.

Thermal compensation of monolithic distributed fibre optic sensors: From the lab to the field

Distributed fibre optic sensing (DFOS) is gaining popularity as a diagnostic solution for short-term non-destructive testing (NDT) and long-term structural health monitoring (SHM). However, there are still challenges to be overcome, particularly with regard to long-term measurements under real field conditions, taking into account, among other things, temperature changes. These changes affect strain measurements through both thermal expansion and optical effects, and appropriate correction depends on the internal design of the sensor and the installation methods. Therefore, despite the fact that thermal compensation is one of the key prerequisites for correct data interpretation, there are no universal and clear procedures for DFOS. The lack of sufficient guidelines and proven applications is the main motivation for undertaking studies. The scope and novelty of the presented research lies in 1) the theoretical explanation of the thermal performance of monolithic DFOS sensors compared to the layered sensing cables; 2) the analysis and correction of strain data measured with monolithic sensors placed in a thermal chamber; 3) the verification of the laboratory results and the proposed approach in real field conditions: in a concrete footbridge deck and in a steel underground gas pipeline. All presented measurements were performed with high spatial resolution (mm order) Rayleigh-based interrogators under the control of conventional reference spot thermistors. The research demonstrated the linear thermal response of the monolithic sensors and confirmed their usefulness for distinguishing between length- and stress-dependent strains. Finally, the thermal compensation approach was proposed and verified in real operating conditions.

Large Language Models Diagnose Facial Deformity.

This study examines the application of Large Language Models (LLMs) in diagnosing jaw deformities, aiming to overcome the limitations of various diagnostic methods by harnessing the advanced capabilities of LLMs for enhanced data interpretation. The goal is to provide tools that simplify complex data analysis and make diagnostic processes more accessible and intuitive for clinical practitioners. An experiment involving patients with jaw deformities was conducted, where cephalometric measurements (SNB Angle, Facial Angle, Mandibular Unit Length) were converted into text for LLM analysis. Multiple LLMs, including LLAMA-2 variants, GPT models, and the Gemini-Pro model, were evaluated against various methods (Threshold-based, Machine Learning Models) using balanced accuracy and F1-score. Our research demonstrates that larger LLMs efficiently adapt to diagnostic tasks, showing rapid performance saturation with minimal training examples and reducing ambiguous classification, which highlights their robust in-context learning abilities. The conversion of complex cephalometric measurements into intuitive text formats not only broadens the accessibility of the information but also enhances the interpretability, providing clinicians with clear and actionable insights. Integrating LLMs into the diagnosis of jaw deformities marks a significant advancement in making diagnostic processes more accessible and reducing reliance on specialized training. These models serve as valuable auxiliary tools, offering clear, understandable outputs that facilitate easier decision-making for clinicians, particularly those with less experience or in settings with limited access to specialized expertise. Future refinements and adaptations to include more comprehensive and medically specific datasets are expected to enhance the precision and utility of LLMs, potentially transforming the landscape of medical diagnostics.

Advanced In Situ and Operando Characterization Techniques for Zinc‐Ion Batteries

Aqueous zinc‐ion batteries (AZIB) are increasingly recognized as a promising next‐generation energy storage technology, prized for their affordability and high safety profile. Yet, their widespread adoption is challenged by complex reaction mechanisms and the evolving nature of both the electrode material and interfaces, which remain critical barriers. This review underscores the utility of in situ and operando characterization techniques in AZIB systems, offering invaluable tools for tracking these intricate processes and deepening understanding of energy storage mechanisms. This review presents an extensive overview of cutting‐edge in situ and operando methods, emphasizing their crucial role in structural investigations of materials and interfaces during electrochemical processes. This review particularly focuses on the synergistic application of various in situ techniques, delving into the nuances of experimental setups and data interpretation. Finally, it addresses current challenges in the field and proposes potential strategies, aiming to enhance the impact and broaden the application of these techniques for future advancements and mechanistic insights in AZIB research.

Short Tandem Repeats in the era of next-generation sequencing: from historical loci to population databases.

In this study, we explore the landscape of short tandem repeats (STRs) within the human genome through the lens of evolving technologies to detect genomic variations. STRs, which encompass approximately 3% of our genomic DNA, are crucial for understanding human genetic diversity, disease mechanisms, and evolutionary biology. The advent of high-throughput sequencing methods has revolutionized our ability to accurately map and analyze STRs, highlighting their significance in genetic disorders, forensic science, and population genetics. We review the current available methodologies for STR analysis, the challenges in interpreting STR variations across different populations, and the implications of STRs in medical genetics. Our findings underscore the urgent need for comprehensive STR databases that reflect the genetic diversity of global populations, facilitating the interpretation of STR data in clinical diagnostics, genetic research, and forensic applications. This work sets the stage for future studies aimed at harnessing STR variations to elucidate complex genetic traits and diseases, reinforcing the importance of integrating STRs into genetic research and clinical practice.

Voluntary optimisation of antimicrobial consumption in swine and poultry production in Thailand: a policy analysis.

Antimicrobial resistance (AMR) is a global health concern with significant implications on economies and health security, affecting humans, animals, food, and the environment. To tackle this issue, promoting responsible antimicrobial use in livestock production has emerged as a crucial intervention. In 2018, Thailand introduced the Voluntary Optimization of Antimicrobial Consumption (VOAC) programme, with the objective to encourage responsible antimicrobial use practises. This study aimed to analyse the context, content, process and actors of the VOAC programme. A qualitative method including document reviews and key informant interviews were applied. In-depth interviews were conducted with 18 key informants who are key stakeholders from public and private sectors involved in the policy formulation, design of policy contents and implementation of VOAC: policy makers or officers responsible for animal health (n = 12), animal producers (n = 2), animal product traders or retailers (n = 2), and farm veterinarians (n = 2). Interview transcripts were validated by informants for accuracy, and triangulated with document review findings. Deductive approach was applied for data analysis and interpretation based on Walt and Gilson's policy analysis framework. The VOAC farm certification comprises of Raised Without Antibiotics (RWA) and Reducing Antibiotic Use (RAU), both aiming to combat AMR in food animals. Global and national factors, including increased public awareness, policy commitments, export requirements from the European Union, and international organisation advocacies, influenced the development of the programme led by the Department of Livestock Development (DLD), under the Ministry of Agriculture and Cooperatives. Collaboration with the private sector facilitated policy clarity, with implementation primarily executed through regional, provincial, and district livestock officers. Integration of the programme with the pre-existing Good Agriculture Practise certification system enabled cost-effective implementation without additional resources. In 2022, DLD official data reported 214 RWA farms (112 pig and 102 broiler), and 230 RAU farms (83 pig and 147 broiler). Incentives for farms to participate in the programme include improving corporate image and demonstrating corporate responsibility addressing AMR in food products. Recommendations include optimising certification strategies, increasing consumer awareness of RWA and RAU products and strengthening monitoring and evaluation systems.

Metabolomics highlights biochemical perturbations occurring in the kidney and liver of mice administered a human dose of colistin.

Introduction: Colistin (CMS) is used for the curation of infections caused by multidrug-resistant bacteria. CMS is constrained by toxicity, particularly in kidney and neuronal cells. The recommended human doses are 2.5-5mg/kg/day, and the toxicity is linked to higher doses. So far, the in vivo toxicity studies have used doses even 10-fold higher than human doses. It is essential to investigate the impact of metabolic response of doses, that are comparable to human doses, to identify biomarkers of latent toxicity. The innovation of the current study is the in vivo stimulation of CMS's impact using a range of CMS doses that have never been investigated before, i.e., 1 and 1.5mg/kg. The 1 and 1.5mg/kg, administered in mice, correspond to the therapeutic and toxic human doses, based on previous expertise of our team, regarding the human exposure. The study mainly focused on the biochemical impact of CMS on the metabolome, and on the alterations provoked by 50%-fold of dose increase. The main objectives were i) the comprehension of the biochemical changes resulting after CMS administration and ii) from its dose increase; and iii) the determination of dose-related metabolites that could be considered as toxicity monitoring biomarkers. Methods: The in vivo experiment employed two doses of CMS versus a control group treated with normal saline, and samples of plasma, kidney, and liver were analysed with a UPLC-MS-based metabolomics protocol. Both univariate and multivariate statistical approaches (PCA, OPLS-DA, PLS regression, ROC) and pathway analysis were combined for the data interpretation. Results: The results pointed out six dose-responding metabolites (PAA, DA4S, 2,8-DHA, etc.), dysregulation of renal dopamine, and extended perturbations in renal purine metabolism. Also, the study determined altered levels of liver suberylglycine, a metabolite linked to hepatic steatosis. One of the most intriguing findings was the detection of elevated levels of renal xanthine and uric acid, that act as AChE activators, leading to the rapid degradation of acetylcholine. This evidence provides a naïve hypothesis, for the potential association between the CMS induced nephrotoxicity and CMS induced 39 neurotoxicity, that should be further investigated.

Statistical Significance is Desirable but not Absolute : In Search of the True Study

In the field of scientific research, the pursuit of robust and reliable results is paramount. Traditionally, the p-value has been the cornerstone of statistical analysis, used to determine the significance of study findings. However, there is a growing consensus that the calculation of effect size and statistical power analysis offer a more comprehensive and superior approach to data interpretation. While the p-value has its place in statistical analysis, the calculation of effect size and statistical power analysis provides a more nuanced and informative perspective on research findings. Embracing these methods will enhance the quality and impact of scientific research, leading to more robust and meaningful conclusions.

An end-to-end approach for single-cell infrared absorption spectroscopy of bacterial inclusion bodies: from AFM-IR measurement to data interpretation of large sample sets

BackgroundInclusion bodies (IBs) are well-known subcellular structures in bacteria where protein aggregates are collected. Various methods have probed their structure, but single-cell spectroscopy remains challenging. Atomic Force Microscopy-based Infrared Spectroscopy (AFM-IR) is a novel technology with high potential for the characterisation of biomaterials such as IBs.ResultsWe present a detailed investigation using AFM-IR, revealing the substructure of IBs and their variation at the single-cell level, including a rigorous optimisation of data collection parameters and addressing issues such as laser power, pulse frequency, and sample drift. An analysis pipeline was developed tailored to AFM-IR image data, allowing high-throughput, label-free imaging of more than 3500 IBs in 12,000 bacterial cells. We examined IBs generated in Escherichia coli under different stress conditions. Dimensionality reduction analysis of the resulting spectra suggested distinct clustering of stress conditions, aligning with the nature and severity of the applied stresses. Correlation analyses revealed intricate relationships between the physical and morphological properties of IBs.ConclusionsOur study highlights the power and limitations of AFM-IR, revealing structural heterogeneity within and between IBs. We show that it is possible to perform quantitative analyses of AFM-IR maps over a large collection of different samples and determine how to control for various technical artefacts.

A novel cuffless blood pressure monitoring device in hypertension care

Background: Hypertension management is challenged by the dynamic nature of blood pressure (BP) fluctuations. These fluctuations are influenced by factors such as physical activity, emotional changes, and sleep patterns. Traditional guidelines focus on static measurements taken in clinical settings. However, these readings may not accurately represent an individual’s typical BP levels. This approach can lead to misdiagnoses, such as white coat or masked hypertension, resulting in either unnecessary treatment or missed diagnoses.Current Concepts: Recent global hypertension guidelines emphasize the importance of home BP monitoring and 24-hour ambulatory BP measurements for more accurate diagnoses and treatment plans. However, several barriers exist, such as the high cost of ambulatory BP devices and practical challenges associated with home BP monitoring, which limit their widespread utilization. Despite these challenges, integrating BP measurements into mobile devices offers a promising approach to monitoring BP outside the clinical setting. Various innovative approaches have been developed, including smartwatches utilizing photoplethysmography sensors and machine learning algorithms. However, their accuracy and the need for periodic calibration are areas of concern.Discussion and Conclusion: Mobile device BP monitoring represents a significant advancement in hypertension management, offering the potential for continuous, convenient, and less intrusive monitoring. Despite these potential benefits, challenges such as device accuracy verification, large-scale data interpretation, and calibration must be addressed. The future of hypertension management will likely rely on these technologies, along with traditional methods, to provide better insight into individual BP profiles. This integration promises to improve hypertension diagnosis, management, and ultimately patient outcomes, although further research and development are necessary to overcome the current limitations.

Transcending Lifshitz Theory: Reliable Prediction of Adhesion Forces between Hydrocarbon Surfaces in Condensed Phases Using Molecular Contact Thermodynamics.

Lifshitz theory is widely used to calculate interfacial interaction energies and underpins established approaches to the interpretation of measurement data from experimental methods including the surface forces apparatus and the atomic force microscope. However, a significant limitation of Lifshitz theory is that it uses the bulk dielectric properties of the medium to predict the work of adhesion. Here, we demonstrate that a different approach, in which the interactions between molecules at surfaces and in the medium are described by a set of surface site interaction points (SSIPs), yields interaction free energies that are correlated better with experimentally determined values. The work of adhesion W(Lifshitz) between hydrocarbon surfaces was calculated in 260 liquids using Lifshitz theory and compared with interaction free energies ΔΔG calculated using the SSIP model. The predictions of these models diverge in significant ways. In particular, ΔΔG values for hydrocarbon surfaces are typically small and vary little, but in contrast, W(Lifshitz) values span 4 orders of magnitude. Moreover, the SSIP model yields significantly different ΔΔG values in some liquids for which Lifshitz theory predicts similar values of W(Lifshitz). These divergent predictions were tested using atomic force microscopy. Experimentally determined works of adhesion were closer to the values predicted using the SSIP model than Lifshitz theory. In mixtures of methanol and benzyl alcohol, even greater differences were found in the interaction energies calculated using the two models: the value of ΔΔG calculated using the SSIP model declines smoothly as the benzyl alcohol concentration increases, and values are well correlated with experimental data; however, W(Lifshitz) decreases to a minimum and then increases, reaching a larger value for benzyl alcohol than for methanol. We conclude that the SSIP model provides more reliable estimates of the work of adhesion than Lifshitz theory.

A survey of vision-based condition monitoring methods using deep learning: A synthetic fiber rope perspective

Computer vision technology has attracted significant interest in the condition monitoring (CM) community due to its potential to automate visual inspection and analysis of structures and components. By facilitating the processing and interpretation of visual information, including images and video data, computer vision holds promise for CM applications. However, it is essential to distinguish computer vision from non-contact CM techniques regarding their underlying principles and methods. While computer vision enables non-contact, remote monitoring, and condition assessment with minimal disruption to daily operations, it is distinct from non-contact CM techniques, which utilize various sensors to assess the condition of assets without physical contact or interference. Building upon the potential of computer vision technology, this survey paper presents a comprehensive overview of the current state-of-the-art CM methods based on computer vision and deep learning (DL) techniques, focusing on their application in monitoring synthetic fiber ropes (SFRs). SFRs are a viable alternative to steel wire ropes for underwater equipment and cranes that handle heavy loads. This is due to their high resistance to frictional wear, high tensile strength, lightweight, and flexibility. New materials, technologies, and processes for CM are being developed to meet the growing demand for SFRs. The paper explores ongoing research in applications that monitor the wear and aging of materials, as well as estimate their remaining useful life. The survey briefly discusses the traditional non-destructive testing and machine learning (ML) methods for CM applications. More importantly, DL-based methods, including supervised, unsupervised, semi-supervised, and self-supervised methods, are discussed in detail, together with the use of deep generative models and the recently developed diffusion models in the generation of synthetic datasets. Furthermore, the paper addresses the difficulties present in DL-based CM applications, including the scarcity of labeled data and the complexity and variety of the models used. The article ends by discussing the benefits of employing DL-based visual methods to understand SFR degradation processes, particularly in monitoring and maintenance.

Methodological principles of searching for disposal sites of radioactively contaminated materials by geophysical methods

This article is devoted to radiometric studies at one of the sites of the Chornobyl nuclear power plant (the “Sandy Plateau” site), which is located on the south-eastern outskirts of the city of Pripyat. Radioactive substances, both artificial and natural, resulting from incidents and disasters at nuclear facilities pose the greatest danger. The disposal sites for radioactively contaminated materials considered in this work are sources of groundwater pollution. Currently, there is a problem of searching for their location for reburial in specialized stationary burial grounds, to solve which detailed complex geophysical studies are used. Various geophysical methods are considered, including micro-sensing and radiometric studies, to determine the location of burials. Particular attention is paid to the analysis and interpretation of geophysical data, as well as the economic and practical aspects of the application of these methods. As a result of the study, it was established: that when searching and studying burial sites of radioactively contaminated materials, the use of surface gamma photography makes it possible to assess the level of radioactive contamination of the upper layers of the soil (to a depth of 0.8-1 m). However, if the thickness of buried radioactively contaminated materials exceeds a certain level, which leads to weak contamination of rocks at a depth of more than 1-1.5 m, then burial objects may go undetected when using only gamma-ray imaging. In such cases, microgamma probing becomes an effective method. Increased values of exposure dose rate and the nature of microgamma sounding curves serve as indicators of the presence (increase in exposure dose rate with depth) or absence (sharp decrease in exposure dose rate with depth) of radioactively contaminated materials in the studied area.