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Dosimetric evaluation of the influence of metallic hip prostheses on radiotherapy for prostate cancer

Radiation Physics and Chemistry 2025年 237卷

作者： Alessa Maschio Felipe Beraldo da Cruz Marcella Cogo Muniz Castro Lucio Pereira Neves William de Souza Santos Ana Paula Perini Postgraduate Program in Biomedical Engineering (PPGEB) Faculty of Electrical Engineering Federal University of Uberlândia Uberlândia MG Brazil Cancer Hospital (HC-UFU/Ebserh) Uberlândia MG Brazil Institute of Physics Federal University of Uberlândia Uberlândia MG Brazil Department of Physics Federal University of Sergipe São Cristóvão SE Brazil

Prostate cancer is the fourth most common type of cancer worldwide, mainly affecting individuals of advanced age. Projections indicate an increase in the number of hip arthroplasties, suggesting that numerous patients undergoing radiotherapy treatment may have hip prostheses, resulting in perturbations in dose distribution. The objective of this study is to evaluate the impact of hip prostheses during radiotherapy for prostate cancer. To achieve this, computational simulations were performed using the Monte Carlo N–Particle® Transport Code Version 6.3, modifying the location and composition of the prostheses, as well as the treatment plans, to obtain the conversion coefficients for equivalent dose ( CC[H T ] ). In the simulations, a hip prosthesis was modeled and implemented in the male reference phantom from ICRP Publication 145. For the unilateral prosthesis, reductions in CC[H prostate ] values were observed: 2.21 % (titanium alloy), 4.52 % (CoCrMo alloy), and 4.62 % (stainless steel). For bilateral prostheses, the reductions were 3.92 % (titanium alloy), 8.65 % (CoCrMo alloy), and 8.76 % (stainless steel). When fields that did not pass through the prostheses were used, the dose to the prostate remained at 100 %, with an average increase in CC[H urinary bladder ] values of 8.38 % (unilateral prosthesis) and 11.06 % (bilateral prostheses). It was also observed that the presence of the prosthesis led to a higher electron count, which can be explained by the electron backscattering occurring in the material. The results highlighted the importance of personalized radiotherapy treatments, as different materials and the number of prostheses can impact dose distribution.

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Phytotherapeutic potential of Campomanesia xanthocarpa (Mart.) O. Berg: antitumor effects in vitro and in silico, with emphasis on SK-MEL-28 melanoma cells-a study on leaf and fruit infusions

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In silico pharmacology 2024年第2期12卷 105页

作者： Vanessa Ruana Ferreira da Silva Gilnei Bruno da Silva Daiane Manica Carolina Turnes Pasini Deolindo Margarete Dulce Bagatini Aniela Pinto Kempka Multicentric Postgraduate Program in Biochemistry and Molecular Biology State University of Santa Catarina Lages SC Brazil. Postgraduate Program in Biochemistry Federal University of Santa Catarina Florianópolis SC Brazil. Ministry of AgricultureLivestock and Food Supply Federal Agricultural Defense Laboratory São José SC Brazil. Department of Food Science and Technology Federal University of Santa Catarina Florianópolis SC Brazil. Postgraduate Program in Biomedical Sciences Federal University of Fronteira Sul Chapecó SC Brazil. Department of Food Engineering and Chemical Engineering Santa Catarina State University Fernando de Noronha Street BR 282 Km 573.5 Pinhalzinho SC 89870-000 Brazil.

The study investigated the efficacy of Campomanesia xanthocarpa infusions on human melanoma cells (SK-MEL-28). The phytochemical profile revealed 18 phenolic compounds in the leaf infusion and 9 in the fruit infusion. After 24 h of treatment, the infusions demonstrated antineoplastic effects, reducing cell viability at all tested concentrations for the leaf infusion. For the fruit infusion, a significant reduction in cell viability was observed specifically at the 800 μg/mL concentration. Fluorescence microscopy and mitochondrial membrane potential results indicated that the leaf infusion was more effective in reducing cell viability and mitochondrial function in SK-MEL-28 cells, possibly due to its greater variety of phenolic compounds compared to the fruit infusion. The leaf infusion also induced higher production of intracellular reactive oxygen species compared to the fruit infusion. Protein sulfhydryl levels were reduced for the leaf infusion. Epigallocatechin gallate, Isoquercitrin, Rutin, Kaempferol-3-O-rutinoside, Chlorogenic acid, and Ellagic acid were identified as the main compounds with activity against SK-MEL-28 cells. Molecular docking analysis underscored factors such as affinity, cavity size, binding mode, and contact residues with specific compounds chosen for their favorable properties in targeting BRAF, CDK4, CDK6, MEK1, and MEK2. The variability in binding affinities may directly influence the compounds' ability to inhibit different signaling pathways related to cancer cell growth and proliferation. The results suggest that phenolic compounds from C. xanthocarpa extracts have therapeutic potential and could contribute to melanoma therapies.

关键词： Antineoplastic effect Bioactive compounds Cell viability Molecular docking SK-MEL-28 Simultaneous inhibitions

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The effects of UV light wavelength and distance differences in viral genetic material integrity

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AIP Conference Proceedings 2024年第1期3155卷

作者： Arya Adiningrat Ahmad Ghitha Fadhlurrahman Yuli Rismawanto Tony Khristanto Hariadi Maria Ulfa Rama Okta Wiyagi Muhammad Yusvin Mustar Molecular Medicine and Therapy Laboratory Faculty of Medicine and Health Science Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Oral Biology and Biomedical Sciences Faculty of Dentistry Universitas Muhammadiyah Yogyakarta Bantul Indonesia Department of Electrical Engineering Faculty of Electrical Engineering Universitas Muhammadiyah Yogyakarta Bantul Indonesia Master of Hospital Administration Postgraduate Program Universitas Muhammadiyah Yogyakarta Bantul Indonesia

The pandemic has shown viral capacity in massive spreading and environmental adaptability for years. It has infected millions of people with several symptoms leading to millions of mortality worldwide. Its fast-spreading capacity, unpredictability prognosis and variants appearance are leading big threats, particularly to the health facilities. Therefore, appropriate health protection equipment, including adequate and safe decontamination procedures, is required to support the facilities in overcoming potential future contaminating pathogens. Unfortunately, only a few studies evaluated the utilization of medical decontamination devices. Rapid and massive manufacturing of decontamination devices without further and adequate post-monitoring may have several side effects. Therefore, careful and continuing consideration and evaluation studies are necessary to maintain the devices’ quality and performance. This study aims to evaluate the ability of UV lights as laboratory devices to impair viral components. Clinical RNA samples were provided by the COVID-19 laboratory examiner as blinded samples without any subject information. SARS-CoV2 RNA (a viral representative RNA material) extract was exposed to 5 different UV lights, with different distances and exposure duration. The exposed RNA was then sequentially used as a cDNA template and DNA amplification. Amplification products were visualized by electrophoresis and densitometry analysis. Visualization and densitometry analysis showed that the UV-LED Nichia NCSU 334 had the most significant disruptive ability among the tested lights. The exposure duration and distance altered the effectiveness of UV light in damaging viral genetic material. UV-LED Nichia NCSU 334 could be suggested as an alternative UV source in a UV light-based disinfection system. This study proposed direct evidence for evaluating decontamination devices to ensure the effectiveness of the decontamination process.

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Identification of the quality of premium and non-premium rice based on physical characteristics using artificial neural networks and digital image processing

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AIP Conference Proceedings 2024年第1期3065卷

作者： Endah Sekar Palupi Riries Rulaningtyas Toetik Rahayuningsih Ahmad Yudianto Department of Forensic Science Postgraduate School Department of Health Faculty of Vocational Studies Universitas Airlangga Surabaya Indonesia Biomedical Engineering Study Program Department of Physics Universitas Airlangga Surabaya Indonesia Criminal Law Department of Law Faculty of Law Universitas Airlangga Surabaya Indonesia Department of Forensic Medicine and Medicolegal Faculty of Medicine Universitas Airlangga Surabaya Indonesia

Counterfeiting of quality rice was rife in Indonesia. This research was conducted to develop technology to identify differences in premium and non-premium rice quality based on pre-existing digital images. Artificial neural networks and digital image processing methods to identify premium and medium (non-premium) rice quality were applied in this research. Statistical analysis of this study used the SPSS program. This research is observation-type research. This research design uses an artificial neural network with uses 3 layers, namely the results of shape feature extraction on the metric, eccentricity, area, and perimeter parameters as input or input layers, hidden or hidden layers, and premium rice and non-premium (medium) rice as output or output layers. This research uses 52 images as training and 20 images as testing. The obtained image was taken at a distance of 25 cm. This research showed that the results of training using artificial neural networks (ANN) on 52 images obtained an accuracy of 92%. The test results using 20 images obtained 95% accuracy, 63.33% sensitivity, and 10% specificity. Based on statistical analysis using the Mann-Whitney test, it obtained the asymph value. Sig (2-tailed) < 0.05 indicates the difference between premium and non-premium rice using metric, eccentricity, perimeter, and area parameters.

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Assessing the inter-annual variability of separation distances around odour sources to protect the residents from odour annoyance

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Journal of Environmental Sciences 2019年第5期31卷 11-24页

作者： Marlon Brancher Martin Piringer Davide Franco Paulo Belli Filho Henrique De Melo Lisboa Gunther Schauberger Postgraduate Program in Environmental Engineering (PPGEA) Federal University of Santa Catarina (UFSC) 88040900 Florianopolis Brazil.CAPES Foundation scholarship holder (main author) Brazilian Ministry of Education Brasilia Brazil WG Environmental Health Department of Biomedical Sciences University of Veterinary Medicine ViennaVeterinarplatz1 A-1210Vienna Austria Central Institute for Meteorology and Geodynamics Hohe Warte 38 A-1190 Vienna Austria

In recent years, there has been a growing concern about potential impacts on public health and wellbeing due to exposure to environmental odour. Separation distances between odour-emitting sources and residential areas can be calculated using dispersion models, as a means of protecting the neighbourhood from odour annoyance. This study investigates the suitability of using one single year of meteorological input data to calculate reliable direction-dependent separation distances. Accordingly, we assessed and quantified the inter-annual variability of separation distances at two sites with different meteorological conditions, one in Brazil and the other in Austria. A 5-year dataset of hourly meteorological observations was used for each site. Two odour impact criteria set in current regulations were selected to explore their effect on the separation distances. The coefficient of variation was used as a statistical measure to characterise the amount of annual variation. Overall,for all scenarios, the separation distances had a low degree of inter-annual variability(mean coefficient of variation values from 8% to 21%). Reasonable agreements from year to year were therefore observed at the two sites under investigation, showing that one year of meteorological data is a good compromise to achieve reliable accuracy. This finding can provide a more cost-effective solution to calculate separation distances in the vicinity of odour sources.

关键词： Environmental odour Odour annoyance Impact assessment Dispersion modelling Regulatory criteria Separation distance

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Isolation and anticancer activity assay of stonefish (Synanceia horrida) bioactive stonustoxin

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AIP Conference Proceedings 2022年第1期2537卷 020002页

作者： Anondho Wijanarko Aulia Firdianna Mikael Januardi Ginting Kenny Lischer Muhamad Sahlan Heri Hermansyah Department of Chemical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Marine Science Postgraduate Program Faculty of Mathematics and Natural Science Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia

Breast cancer is a disease in which cells in the breast mutate and turn malignant, where the mutated cells spread to other parts of the body and develop into secondary cancer. In 2018, there were 58,256 new cases of breast cancer. With improper handling, breast cancer can be lethal, where there are 22,692 deaths in 2018 alone. One type of cancer with the most sufferers is estrogen, progesterone, and glucocorticoid receptors. Research on cancer treatment continues by looking for potential substances as new drugs. Toxins from animals that are cytolytic can trigger apoptosis in cancer cells. Some studies suggest that the lethal factor of the stonefish poison, Stonustoxin (SNTX), has cytolytic properties that damage cell membranes. This study discusses the stonefish (Synanceia horrida) venom as a breast anticancer agent. Stonefish poison was milked using a syringe, and the SNTX purification was carried out by the FPLC method using a 5 ml HiTrap Q H.P. substantial anion column. The percentage of inhibition of MCF-7 breast cancer cells will be measured using the MTT Assay method. As a result, MCF-7 breast cancer cells could be inhibited with IC50 values of 8.2771 µg/ml.

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Correction to: Evaluation of fluoride concentration in toothpastes with antimicrobial molecules commercialized in Brazil

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Research on biomedical engineering 2020年第1期37卷 15-15页

作者： Maria da Conceição de Araújo Medeiros Lídia Audrey Rocha Valadas Mara Assef Leitão Lotif Peter Bottenberg Fernanda Roberta Marciano Biomedical Engineering Postgraduate Program Brazil University São Paulo Brazil Development and Technological Innovation in Medicines Postgraduate Program Federal University of Ceara Fortaleza Brazil Oral Health Research Cluster Free University of Brussels (VUB) Brussels Belgium

The original version of this article unfortunately contained mistakes in Tables 1 and 2.

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Coconut waste to green nanomaterial: Large scale synthesis of N-doped graphene nano sheets

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Nano-Structures and Nano-Objects 2023年 36卷

作者： Siburian, Rikson Tang, Liang Wei Alias, Yatimah Tok, Alfred Iing Yoong Goei, Ronn Simanjuntak, Crystina Tarigan, Kerista Paiman, Suriati Goh, Boon Tong Anshori, Isa Kurniawan, Cepi Postgraduate Program Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan 20155 Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan 20155 Indonesia Carbon and Frankincense Research Center Universitas Sumatera Utara Medan 20155 Indonesia Department of Chemistry Faculty of Science Universiti Malaya Kuala Lumpur 50603 Malaysia University Malaya Centre for Ionic Liquids (UMCiL) Universiti Malaya Kuala Lumpur 50603 Malaysia School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore Department of Physics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan 20155 Indonesia Physics Department Faculty of Science Universiti Putra Malaysia Selangor (Serdang) Seri Kembangan 43400 Malaysia Low Dimensional Materials Research Centre Department of Physics Faculty of Science University of Malaya Kuala Lumpur 50603 Malaysia Biomedical Engineering Department School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung 40132 Indonesia Research Center of Nanoscience and Nanotechnology Bandung Institute of Technology Bandung 40132 Indonesia Chemistry Department Faculty of Mathematics and Natural Sciences Universitas Negeri Semarang Semarang 50229 Indonesia Functional Material Research Center Universitas Negeri Semarang Semarang 50229 Indonesia

In this paper, a breakthrough was achieved in large-scale production of N-doped Graphene Nano Sheets (N-GNS) using coconut fruits. The main objectives were to produce N-GNS on a large scale and assess its electrical conductivity. The process involved two key steps: first, producing GNS from coconut fruits through pyrolysis, and then generating N-GNS by doping with nitrogen using ammonia solution at room temperature. Various analytical techniques were used to characterize the produced N-GNS, including X-ray Diffraction (XRD), Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM-EDS), Transmission Electron Microscopy (TEM), X-ray Photoelectron Spectroscopy (XPS), Raman spectroscopy, and electrochemical cyclic voltammetry and electrochemical impedance spectroscopy. The XRD data indicated that the C (002) peak of N-GNS shifted to a higher 2θ value (2θ = 24.72°) compared to GNS (2θ = 23.86°), suggesting an incorporation of nitrogen into carbon structure in N-GNS. This was further supported by XPS data, which identified N-pyridine (BE = 402.0 eV) and C-N (BE = 286.8 eV) in N-GNS. TEM images showed that N-GNS had a flat surface, and the distance between graphene layers slightly expanded (0.36 nm) compared to graphene layers (0.34 nm). SEM images and EDX data validated the morphology, resembling honeycomb lattices, with a significant content of N atoms. Raman data successfully identified the D-band and G-band in N-GNS, further validating its production. Most importantly, N-GNS exhibited electrical conductivity, making it a promising candidate for conductive and supporting materials in various applications. The significance of this research extends beyond N-GNS production, opening up new avenues for the sustainable synthesis of valuable nanomaterials from coconut fruit waste, contributing to both graphene technology and environmental conservation. © 2023 Elsevier B.V.

关键词： C-sp2 Electrical conductivity Graphene nano sheets N-graphene nano sheets N-pyridine XPS

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Metrological control of electrolytic sensors for measuring angular deviations: application in monitoring displacements of engineering structures

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Journal of Physics: Conference Series 2021年第1期1826卷

作者： E G Leaño P Rocha Filho J D Hernández M N Frota Civil Engineering Depart. Pontifical Catholic University of Rio de Janeiro RJ 22451-900 Brazil Postgraduate Programme in Metrology Metrology for Quality and Innovation. Pontifical Catholic University of Rio de Janeiro Rio de Janeiro 22451-900 Brazil Research Group GIFOURIER. Faculty of Mechanical Electronic and Biomedical Engineering. Mechanical Engineering Program University Antonio Nariño Puerto Colombia Colombia

The work evaluates the metrological reliability of electrolytic sensors (electrolevels) used to determine angular deviations of elements of engineering structures. The motivation for the work resulted from its strategic application to control the stability of civil engineering structures, notably with application in geotechnics (e.g.: different types of dams of interest in engineering). The methodology used is based on the metrological consistency associated with the quality control process of a set of electrolevels submitted, simultaneously, to a careful calibration process, with traceability ensured to a standard angular deviation pattern. Mounted on a rigid bar, but pivoted at one of its ends to allow angular displacements, the output of each electrolevel is compared with the previously calibrated standard, for different controlled conditions of angular deviation imposed on the bar articulated to a center of rotation. The result of the analysis of typical calibration data for nine electrolevels allowed to show that the expression of the uncertainties associated with the calibration measurements performed constitutes an essential foundation to ensure the metrological reliability of the electrolevels, having allowed to validate a method of discard of electrolevels not meeting the allowable tolerance for a specific engineering application. Among the conclusions of the work, it was possible to qualify the statistical treatment of the levels of uncertainty as a sufficiently robust strategy to validate the electrolevels as a reliable instrument for angular displacement measurements, with a level of confidence appropriate to its application in civil engineering.

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