Assessment Techniques Research Articles

Advances in Aerosol Nanostructuring: Functions and Control of Next-Generation Particles.

Nanostructured particles (NSPs), with their remarkable properties at the nanoscale, possess key functions required for unlocking a sustainable future. Fabricating these particles using aerosol methods and spraying processes enables precise control over the particle morphology, structure, composition, and crystallinity during in-flight transformation. In this Perspective, the significant impact of NSPs on technological advancement for energy and environmental applications is discussed. Furthermore, incorporating in situ/operando assessment techniques alongside machine and deep learning is explored. Finally, the future development trends and the perspective on the advancing NSPs synthesis via aerosol process are elaborated for further driving innovations for supersmart and carbon-neutral society.

Unveiling Critical Thinking Pedagogy: Classroom-Based Assessment Strategies in Higher Education

Promoting critical thinking (CT) skills has largely attracted the concern of numerous relevant stakeholders, including teachers, students, and policymakers, with the assumption that CT is a vitally learned skill needed by graduates. This study explores the extent of classroom-based assessment strategies used to promote the CT ability of undergraduate students in Vietnam. Qualitative research approaches were employed through in-depth interviews, classroom observations, and assignment analysis with a curriculum review of the Global Citizens Program at Swinburne Vietnam Alliance Program with FPT Education. The findings show that teachers have widely applied a couple of assessment techniques to increase the CT capability of students, including peer review, reflective writing, case study analysis and evaluation, teamwork projects, research-type assessments, and problem-solving. Furthermore, lecturers who are more aware of the importance of CT and those who are more flexible and skilled in testing self-developing techniques have more strategies for incorporating CT into their assessments. The study reveals that if CT is explicitly stated in the program learning outcomes and incorporated into the course outlines, it is more likely to be implemented.

Technical Condition Assessment and Modelling of Reed Valves in Vehicle Engine Intake Systems

Technical Condition Assessment and Modelling of Reed Valves in Vehicle Engine Intake Systems

Unlocking the mysteries of drought: integrating snowmelt dynamics into drought analysis at the Narayani River Basin, Nepal

AbstractDrought is among the most impactful natural hazards, undermining water security, agriculture, and livelihoods worldwide. Analysing droughts in large catchments presents several unique challenges, primarily related to the complexity of land surface characteristics and data availability limitations. Conducting drought analysis in the Narayani River Basin, which encompasses a vast area within the Himalayan region of Nepal, is extremely challenging but crucial for maintaining the river basin's social, economic, and environmental balance. In response, this study develops a new combined drought index (CDI), integrating satellite-based reanalysis parameters [i.e., Land Surface Temperature (LST), Snow Cover (SC), and Normalised Difference Vegetation Index (NDVI)] with a meteorological parameter [i.e., Standardised Precipitation (std_prec)]. The novel CDI was applied at the Narayani Basin to assess the droughts over the 2004–2013 period, and the results were independently evaluated using streamflow observations to validate the accuracy of the novel drought index. The principal component analysis (PCA) technique was used to determine the contribution of input parameters to the multivariate drought index. The PCA results show a strong positive correlation (0.78) between the CDI and standardised streamflow, indicating the effectiveness of the novel index in monitoring drought conditions. Accordingly, it can be concluded that surface water availability is interdependent on landscape characteristics, such as LST, SC, and NDVI, in addition to the effects of precipitation. Also, the novel CDI can identify the specific drought-affected areas in the Narayani River Basin, offering insights into its drought characteristics beyond traditional drought assessment techniques.

Multi-institutional Validation of the Interarytenoid Assessment Protocol for Pediatric Laryngeal Cleft.

Current assessment techniques for determining whether a patient has normal interarytenoid anatomy, a deep interarytenoid notch, or a minor laryngeal cleft are highly variable. However, differentiating between these three entities is important, given it may distinguish whether a patient should be considered for surgical intervention. The Interarytenoid Assessment Protocol (IAAP) was developed to provide standardization of interarytenoid anatomy evaluations. We aimed to assess the reliability of the IAAP for assessment of interaytenoid mucosal height (IAMH) through a multi-institutional validation study. Reliability of the IAAP was assessed by 10 pediatric otolaryngologists all from different academic centers. 30 de-identified endoscopic videos of interarytenoid assessments were rated at two separate time points, 2 months apart. Intra-class correlation (ICC) coefficients with two-way models were used to evaluate inter- and intra-rater reliability. Thirty endoscopic videos were collected for patients with a median (IQR) age of 4.9 years (59 months; range: 1 month to 20 years). On the first video assessment, inter-rater reliability was 0.74 (95% CI 0.63-0.84), and on the second video assessment, inter-rater reliability was 0.75 (95% CI 0.63-0.85) indicating strong inter-rater reliability. Overall intra-rater test-retest reliability was 0.75 (95% CI 0.69-0.79) indicating strong agreement. In almost half, 14 (46.6%) raters chose IAAP classification levels within 1 level of each other. Multi-institutional validation of the IAAP demonstrates strong inter- and intra-rater reliability for assessment of IAMH when evaluated through pictorial analysis. Standardization of anatomical evaluations may improve our ability to perform more reliable outcomes studies of pediatric pharyngeal dysphagia in the future. NA Laryngoscope, 2024.

Evaluating small-scale eucalyptus growers’ experience of the EVO mobile application: a comparative analysis of quantitative and qualitative assessment techniques

ABSTRACT Mobile applications (apps) have become widely available as decision support tools in agriculture and forestry worldwide. Owing to the above-mentioned development trend, identifying testing methods that can be easily implemented for evaluating mobile app development targeting rural livelihood-related topics is urgently required. This study examined user experiences with a previously launched and published mobile app (EVO) that small-scale eucalyptus growers can utilize to estimate their gross income and net profit from timber sales. The survey incorporated three user experience assessment methods. The study involved two rounds of data collection regarding the mobile app: the first round concerned version 1.0, whereas the second round referred to version 2.0. The aim was to identify the user experience of the EVO app for guiding further software development to improve its suitability among potential user groups, as well as to estimate the feasibility and usability of survey methods for evaluating mobile apps among smallholders and related stakeholders. The results indicated a remarkable improvement in user satisfaction between the two rounds. Using a combination of system usability scale, user acceptance testing, and quality questions is recommended for collecting valuable and useful feedback for the development of mobile apps.

Research hotspots and evolution trends of food safety risk assessment techniques and methods

AbstractFood safety incidents frequently occur in China and other countries. Food safety risk management has evolved from harm‐based to risk‐based approaches to control risks more scientifically and effectively. Risk assessment is at the core of risk control and provides a scientific basis for the development of risk management measures. Therefore, analyzing the research status and development trends of food safety risk assessment technologies and methods is important for improving food safety risk assessment and risk management. In this study, CiteSpace software was used to analyze a knowledge graph of popular research topics in the field of food safety risk assessment over the past 14 years, identify research keywords, and provide centrality statistics. Food safety risk assessments primarily focus on in vitro high‐throughput testing, computational toxicology, predictive microbiology, mechanistic research, and other technical methods. In the future, international coordination, cooperation, and cross‐integration of relevant disciplines should be strengthened, and research on and application of innovative technologies for food safety risk assessment should be promoted. Research on food safety risk assessment technologies and methods is in an active development stage and has good prospects for further exploration and application.

Geomatics Technology Education – Assessment of Learning Pedagogy

Abstract. The paper investigates multidisciplinary education and specialization at the master's level, analyzes assessment methods, and proposes a technique for evaluating geospatial technology education. It emphasises is on pedagogical approaches, and highlights the importance of capacity building to meet the growing demand for skilled professionals in spatial information management. The research provides guidelines for improving course content, structure, and teaching methodologies, aiming to enhance the quality and relevance of geospatial education for both students and stakeholders. This paper is based on online data gathered from 115 universities across the globe, who are imparting geospatial education, campus-based and e-learning, also a survey was conducted of two thousand students. It supported in analysis and suggestion to develop a specific robust technique for assessment of the geospatial technology education and provides the corrective measures to the users of the technique. It proposed a framework aimed at enhancing the course content, organization, and teaching methods substantially. Further an attempt was made to adopt AHP model for investigating the statistical approach. It was aimed to know the actual values and significance of each parameter used for analysis of the study. In order to prepare a common guideline for improving the course structure, course content and teaching methodology, ANFIS architecture (Artificial Neural Fuzzy-Inference System) was adopted. Spatial information represented in the form of thematic maps in relation with the respective attribute data in Geographical Information System (GIS) environment is now used by all spectrum of the society, be it government organizations, industry, and academia. The result of the study has designed the criteria and common guidelines, which may be implemented, would able to help and curtail the challenges of the geospatial education as global vision for Local Action.

MR tomographic evaluation of the effectiveness of neoadjuvant chemotherapy for breast cancer based on pharmacokinetic numerical analysis of tumor uptake of paramagnetic contrast in intravenous contrast enhancement

Background. In clinical practice, MRI pathophysiological and pharmacokinetic models with calculations of contrast transport indicators are unacceptably little used.Aim of the study. To propose a pharmacokinetic technique for the quantitative assessment of primary tumors and metastases, the effectiveness of breast cancer chemotherapy (BC), from dynamic contrast enhancement MRI. Material and methods. 18 patients were included who underwent neoadjuvant chemotherapy (NACHT) in four cycles for breast cancer T1-3N0-1M0, followed by radical surgical removal of the tumor. According to the results of a three — year follow-up, patients with a relapse — free course (n = 11) formed group 1, and seven patients with detected metastatic lesions (3 in the liver, 2 in the lungs, 2 in the brain) — group 2. For the initial 120–180 s of MRI with contrast after the injection of a paramagnetic, the simplification is valid for concentrations in tumor and blood and for tranfer coefficient: d{СОПУХОЛЬ(t)} / dt = ККр-Оп * СКРОВЬ (t) , from which it is obvious: ККр-Оп = (СОПУХОЛЬ(Т)) / (∫CКРОВЬ(t) dt), which was used in all calculations of the contrast transfer constant. Gadobutrol contrast is 0.1M/10 kg of body weight, TR = 5.5–6 ms, TE = 2.5 ms. Results. If, after the first cycle of NACHT, the ККр-Оп of the primary breast cancer is < 0.22 ml/min/g of tissue, the probability of subsequent relapse-free course = 0.78. Similarly, a decrease in the KCr-Op Ккр-Оп of the sentinel lymph node after the first cycle of NAHT < 0.08 ml/min/g of tissue with a probability of 0.75 predicts a relapse-free course. Conclusion. The proposed method for calculating the ККр-Оп transfer coefficient allows obtaining additional diagnostic and prognostic information in patients with local and locally advanced forms of breast cancer.

Research on Financial Investment Risk Assessment Techniques and Applications

In recent years, the financial markets have undergone rapid development and significant volatility, leading to a pronounced urgency and complexity in investment risk assessment. This study explores the technologies and applications of financial investment risk evaluation, offering an in-depth analysis of the theoretical foundations and practical operations of quantitative, qualitative, and hybrid assessment methodologies. Traditional quantitative techniques, such as the Value at Risk (VaR) model, provide crucial objective data support, while qualitative approaches enrich the breadth of risk identification through expert opinions and seasoned experience. Hybrid methods synergistically combine the strengths of both, adapting to the intricacies of the market environment. The integration of big data and artificial intelligence technologies injects innovative momentum into risk assessment, enabling more precise and timely risk monitoring. Case applications span multi-layered risk management strategies within banks, insurance companies, and hedge funds, offering valuable insights for diverse financial institutions. The study posits that efficient risk assessment relies not only on technological advancements but also necessitates consideration of market dynamics and regulatory environment fluctuations. Continual innovation and practical optimization are pivotal in addressing future challenges.

The Effect of Teaching Strategies on English Language Learning in Libya

This study examines the impact of teaching strategies on English language learning in Libya, focusing on the challenges Libyan teachers face in secondary schools. The research investigates the effectiveness of different teaching methods and explores innovative strategies, including interactive technologies, in the classroom. The primary aim is to assess how these strategies influence student engagement, language proficiency, and overall learning outcomes. A mixed-method approach was employed, incorporating a quantitative analysis of survey data from ten high school English instructors in Hoon. The results indicate that educators frequently employ supportive techniques, including offering comments and encouraging task completion. The study reveals substantial deficiencies in self-assessment and contemporary evaluation techniques, suggesting a dependence on conventional pedagogical methods. The absence of modern methodologies, such as student reflection and peer assessment, may restrict students' active engagement and impede their linguistic advancement. This research paper also identifies differences in teaching practices based on teacher demographics, including gender and years of experience. More experienced teachers were found to employ a broader range of strategies, suggesting the need for mentorship and professional development for newer educators. The study emphasizes integrating technology-enhanced tools and reflective assessment techniques to foster a more effective and engaging learning environment. The conclusions drawn from this research paper recommend that targeted professional development programs be implemented to support teachers in adopting more reflective and modern teaching methods. These programs should focus on enhancing teachers' skills in self-assessment techniques, peer evaluation, and technology integration in the classroom. By doing so, English language instruction in Libya can be significantly improved, contributing to better student outcomes and excellent English proficiency. Overall, the study underscores the need for a dynamic and adaptable approach to teaching English, where traditional methods are supplemented by innovative strategies that actively engage students and equip them with the necessary skills to succeed in a globalized world.

Quantifying Lower Extremity Blood Flow using Low-Dose CT Perfusion: Validation in a swine model

Abstract Background Quantitative assessment of blood flow in peripheral extremities in conjunction with simultaneous CT angiography measurements can improve risk assessment and provide a critical decision-making tool for patients across a wide spectrum of vascular disease severity. Purpose This study assessed the reproducibility and accuracy of lower extremity blood flow measurements with a low-dose first-pass analysis CT perfusion technique. Materials and Methods This prospective study utilized 16 Yorkshire Swine to obtain lower extremity blood flow CT measurements at baseline and under induced femoral stenosis using a vascular occluder. Thirty-three pairs of CT measurements evaluated reproducibility, and 43 CT measurements assessed accuracy against ultrasound flow probe references. Contrast agent and saline chaser were both injected peripherally at a rate of 5 mL/s. Bolus tracking was used, and a pre-contrast and post-contrast helical scan were acquired at the base and approximately the peak of the femoral enhancement (CT angiogram), respectively. The acquired data were then used as analytical inputs into a first-pass analysis model to derive perfusion in mL/min/g. The reproducibility and accuracy of lower extremity perfusion measurements were assessed via Mixed model regression and Bland-Altman analysis. Results Calculated CT perfusion measurements derived from first-pass analysis technique (PCT), and the reference standard ultrasound perfusion measurements (Pref) were related by PCT = 1.06 Pref + 0.00 (r2= 0.90, Root-Mean-Square Error = 0.01 mL/min/g). The first (P1) and second (P2) CT perfusion measurements were related by P2 = 0.98 P1 + 0.02 (r = 0.97, Root-Mean-Square Error = 0.11 mL/min/g). The average effective dose of perfusion measurement using first-pass analysis technique was calculated to be only 2.13 mSv. Conclusion : The low-dose quantitative CT perfusion technique can accurately measure lower extremity perfusion (mL/min/g) using only two helical scans. The CT angiogram and perfusion measurements can be used as a comprehensive technique for morphological and physiological assessment of limb ischemia.

Use of Augmentative and Alternative Communication Technology to Retrain Attention and Enhance Functional Communication Following Severe Traumatic Brain Injury: A Clinical Case Report

Purpose: This case report outlines the use of high-tech assistive technology in the form of an augmentative and alternative communication device to assess and treat a veteran with severe speech, language, and cognitive impairments status post severe blast injury. Method: The patient is a right-handed male Veteran of the United States Marine Corps who sustained catastrophic injury after stepping on a dismounted improvised explosive device. He presented to the outpatient clinic 4 years status post injury for continued speech, language, and cognitive interventions. Based on assessments and observations, the patient was diagnosed with spastic anarthria, probable apraxia of speech, aphasia, and attentional impairments. His functional communication was restricted to limited facial expression and eye movements interpreted by those who knew him well. This case reviews the detailed informal and novel assessment techniques and training methods used to implement high-tech assistive technologies as part of the rehabilitation plan designed to enhance functional communication. Results: Through systematic instruction and retraining visual and sustained attention, the patient was able to engage meaningfully with a high-tech device to increase functional personal choice when supported by a partner. Conclusion: This case demonstrates the role high-tech assistive technologies can play in the rehabilitation and functional communication efforts for persons with severe traumatic brain injury and cerebrovascular accidents.

Induced pluripotent stem cell-derived cardiomyocyte in vitro models: benchmarking progress and ongoing challenges.

Recent innovations in differentiating cardiomyocytes from human induced pluripotent stem cells (hiPSCs) have unlocked a viable path to creating in vitro cardiac models. Currently, hiPSC-derived cardiomyocytes (hiPSC-CMs) remain immature, leading many in the field to explore approaches to enhance cell and tissue maturation. Here, we systematically analyzed 300 studies using hiPSC-CM models to determine common fabrication, maturation and assessment techniques used to evaluate cardiomyocyte functionality and maturity and compiled the data into an open-access database. Based on this analysis, we present the diversity of, and current trends in, in vitro models and highlight the most common and promising practices for functional assessments. We further analyzed outputs spanning structural maturity, contractile function, electrophysiology and gene expression and note field-wide improvements over time. Finally, we discuss opportunities to collectively pursue the shared goal of hiPSC-CM model development, maturation and assessment that we believe are critical for engineering mature cardiac tissue.

Application of the Life Cycle Assessment (LCA) Method in Assessing the Environmental Impact of New Materials Derived from Waste Polymers in Terms of Sustainability

Sustainable socioeconomic development should provide humans with a suitable environment for safe living. It can be debated whether the term “environment” should be used due to the significant anthropogenic transformation of the environment. Therefore, an essential part of solving environmental problems is innovation. Climate, resource conservation, and environmental protection are recognized worldwide as common challenges. Thus, it is necessary to implement solutions that simultaneously protect the environment and the climate with sustainable and rational use of resources. Related to this issue is the principle of a loop/closed-loop economy. Among other things, it refers to using waste to prepare materials that can be used for other purposes. The use of tools such as LCA (life cycle analysis) contributes to supporting environmental protection. With the LCA method, it is possible to analyze environmental risks and compare new technological alternatives. LCA is a methodology that has been used around the world with great success, especially for studying individual stages of the entire product life cycle. The results of studies that have been conducted in various research centers confirm the possibility of also using the LCA technique for the environmental assessment of new technologies or existing modernized technological processes. The purpose of this study was to assess the feasibility of using the LCA method to determine the environmental impact that the potential production and use of new materials will have.

AI MyData: Fostering Middle School Students’ Engagement with Machine Learning through an Ethics-Infused AI Curriculum

As initiatives on artificial intelligence (AI) education in K-12 learning contexts continues to evolve, researchers have developed curricula among other resources to promote AI across grade levels. Yet, there is a need for more effort regarding curriculum, tools, and pedagogy, as well as assessment techniques to popularize AI at the middle school level. Drawing on prior work, we created original curriculum activities with innovative use of existing technology, a new computational teaching tool, and a series of approaches and assessments to evaluate students’ engagement with the learning resources. Our curriculum called AI MyData comprises elements of ML and data science infused with ethical orientation. In this paper, we describe the novel AI curriculum and further discuss how we engaged students in learning and critiquing AI ethical dilemmas. We gathered data from two pilot studies conducted in the Northeast United States, one Artificial Intelligence Afterschool (AIA) program, and one virtual AI summer camp. The AIA program was carried out in a local public school with four middle school students aged 12 to 13; the program consisted of eleven two-hour sessions. The summer camp consisted of two-hour sessions over four consecutive days, with eighteen students aged 12 to 15. We facilitated both pilot programs with hands-on plugged and unplugged activities. The method of capturing data included artifact collection, structured interviews, written assessments, and a pre- to post-questionnaire tapping participants’ dispositions about AI and its societal implication. Participant artifacts, written assessments, survey, observation, and analysis of tasks completed revealed that the children improved in their knowledge of AI. In addition, the AI curriculum units and accompanying approaches developed for this study successfully engaged the participants, even without prior knowledge of related concepts. We also found an indication that introducing ethics of AI to adolescents will help their development as ethically responsive citizens. Our study results also indicate that lessons establishing links with students’ personal lives (e.g., letting students choose personally meaningful datasets) and societal implications using unplugged activities and interactive tools were particularly valuable for promoting AI and the integration of AI in middle school education across the subject domains and settings. Based on these results, we discuss our findings, identify their limitations, and propose future work.

Research on the mechanism of the effect of music rhythm synchronization training on biomechanics gait optimization and rehabilitation outcome

The integration of movements or activities that match the beat of music is known as music rhythm synchronization (MRS). Excessive musical tempo can enhance motor abilities and general movement efficiency and it requires synchronizing physical activities like walking or exercising. Enhancing the speed of movement that leads to quick walking, longer step length symmetric, and functional walking ability. The training with MRS mechanism, this research aims to analyze the movement in biomechanics, optimization, and the findings of rehabilitation impacts. This research utilizes 75 participants with Parkinson’s illness and they are divided into two categories group A with training in MRS mechanism and received traditional mechanism training in group B. This research explores the training in MRS mechanism-affected biomechanics movements are performed by utilizing the pre-post method by providing more evaluations. The three-week supervised rehabilitation program presenting the MRS has been followed by the two-week follow-up stage as a part of the intervention. There are two significant deviation estimations in the patterns of normal gait like the gait variable score (GVS) and gait profile score (GPS). The regression analysis, Analysis of Variance (ANOVA), regression analysis, and paired sample t-test, which are the data assessment techniques are evaluated by utilizing the SPSS statistical software for the performance. The conclusion demonstrates the MRS mechanism training significantly improved gait biomechanics. The GPS score shows the enhanced overall quality of gait and it decreased significantly. These findings illustrate the potential of the MRS mechanism training mechanism in improving gait biomechanics and producing excellent rehabilitation outcomes.

Development of methodology for calculating flooded area and flood volume in small urban areas based on unmanned aerial vehicle images

Climate change has intensified flooding and increased localized torrential rainfalls, leading to disasters such as landslides, infrastructure collapse, and urban floods. The extent and accuracy of flood damage information significantly impact recovery processes. While previous studies primarily utilized satellite and aerial imagery for broad flood assessments, they often lacked the precision needed for accurate damage analysis. This study addresses the gap between rapid assessment needs and precise damage quantification in flood inundation analysis. This research introduces a novel image-based investigation approach to enhance the speed and accuracy of flood inundation assessment. By leveraging unmanned aerial vehicles (UAVs) and image-based spatial data technology, aerial images of flooded areas are rapidly captured to construct three-dimensional disaster site terrain information. The proposed methodology employs advanced techniques in aerial photography, image processing, and geographic analysis to quantitatively analyze flood inundation scale using only aerial images and geographic information systems (GIS). The research yielded a calculated flood inundation area of 3,847.36 m2 and a flood volume of 13,895.13 m3. This methodology complements existing flood inundation assessment techniques and has the potential to significantly improve disaster management efforts by providing rapid, accurate, and actionable data for decision-makers.

Deep learning based highly accurate transplanted bioengineered corneal equivalent thickness measurement using optical coherence tomography

Corneal transplantation is the primary treatment for irreversible corneal diseases, but due to limited donor availability, bioengineered corneal equivalents are being developed as a solution, with biocompatibility, structural integrity, and physical function considered key factors. Since conventional evaluation methods may not fully capture the complex properties of the cornea, there is a need for advanced imaging and assessment techniques. In this study, we proposed a deep learning-based automatic segmentation method for transplanted bioengineered corneal equivalents using optical coherence tomography to achieve a highly accurate evaluation of graft integrity and biocompatibility. Our method provides quantitative individual thickness values, detailed maps, and volume measurements of the bioengineered corneal equivalents, and has been validated through 14 days of monitoring. Based on the results, it is expected to have high clinical utility as a quantitative assessment method for human keratoplasties, including automatic opacity area segmentation and implanted graft part extraction, beyond animal studies.

Data normalization of plasma miRNA profiling from patients with COVID-19

When using the reverse-transcription quantitative polymerase chain reaction (RT-qPCR) technique for quantitative assessment of microRNA (miRNA) expression, normalizing data using a stable endogenous gene is essential; however, no universally adequate reference gene exists. Therefore, in this study, we aimed to determine, via the RNA-Seq technique, the most adequate endogenous normalizer for the expression assessment of plasma miRNAs in patients with coronavirus disease 2019 (COVID-19). Two massive sequencing procedures were performed (a) to identify differentially expressed miRNAs between patients with COVID-19 and healthy volunteers (n = 12), and (b) to identify differentially expressed miRNAs between patients with severe COVID-19 and those with mild COVID-19 (n = 8). The endogenous normalizer candidates were selected according to the following criteria: (1) the miRNA must have a fold regulation = 1; (2) the miRNA must have a p-value > 0.990; and (3) the miRNAs that were discovered the longest ago should be selected. Four miRNAs (hsa-miR-34a-3p, hsa-miR-194-3p, hsa-miR-17-3p, and hsa-miR-205-3p) met all criteria and were selected for validation by RT-qPCR in a cohort of 125 patients. Of these, only hsa-miR-205-3p was eligible endogenous normalizers in the context of COVID-19 because their expression was stable between the compared groups.