Similar Tests Research Articles

Interspecific niche overlap and climatic associations of native Quercus species in the Zagros forests of Iran

In the arid regions surrounding southwestern Asia, oak trees play an important role in the environment by conserving water and preserving soil and supporting wildlife. There are concerns for the health and continued productivity of these forests, and there is a widespread oak decline. In this study, ecological niche modeling (ENM) and multivariate principal component analysis (PCA) were used to determine the environmental variations among Quercus brantii, Q. infectoria, and Q. libani in the Zagros forests of western Iran. Based on the area under the curve (AUC > 0.9) and the true skill statistic (TSS > 0.8), three algorithms, including random forest (RF), maximum entropy (MaxEnt), and maximum picking neural net (MAXnet), were used in an ensemble approach to explore the most important environmental variables within the projected suitable habitat of each species. Environmental variables related to climate, including annual precipitation (bio12) and annual mean temperature (bio1), were among the most important drivers of habitat suitability for oak species. The results illustrated that suitable areas for Q. infectoria and Q. libani often occur in the northern parts of the Zagros, which are humid and cooler than the southern areas. The results suggested that Q. brantii has a higher tolerance for harsh conditions in Zagros and therefore inhabits almost all areas of Zagros, including the southern parts. The climatic overlap between pairs of species was found to be significant based on equivalency and similarity tests, suggesting that the environmental conditions of the two species compared are more similar than would be expected by chance. The gap analysis for the three oak species revealed that only a few protected areas currently exist within their suitable habitats, with most of the highly suitable habitats located on non-protected lands, particularly for Q. libani and Q. infectoria. In addition, deforestation is known to sometimes occur within the boundaries of protected areas. Improving the level of protection by upgrading the current protected areas to national parks can help with conservation.

Jurisdictional challenges under section 67 and section 30(1)(b): reflections on procedural irregularity in tribunal constitution

Abstract This article explores the Law Commission’s proposed reforms to section 67 of the English Arbitration Act 1996 and, in particular, the missed opportunity to establish a threshold test for challenges to the substantive jurisdiction of an arbitral tribunal. The current reforms are chiefly concerned with the manner through which the English Courts are to conduct a section 67 challenge, rather than the principles to be applied. Through a comparative assessment of the approach in other jurisdictions, we propose that a two-factor test be introduced that requires any challenge of substantive jurisdiction to demonstrate a breach that (i) is more than de minimis and (ii) results in material prejudice. Such a test would help to dissuade frivolous challenges, bolster England as a pro-arbitration destination, and bring England further into line with other, well-respected jurisdictions that impose similar tests.

Development of Low-Cost Technology-Based Learning Aids for Heat Radiation Material

This study aims to develop low-cost technology-based learning aids in physics, specifically on heat radiation, using Student Worksheets (LKS). The Suyanto method of research and instructional media development was employed, including internal testing and variance similarity testing of the learning aids. The results consist of physics learning aids and LKS that have been internally validated, in line with theoretical expectations. The LKS validation yielded a score of 3.14, indicating suitability for use, while the external test using a One-Shot Case Study showed a student learning outcome score of 3.61, signifying good learning quality. Assessment of the appeal of the learning aids and LKS yielded a score of 3.32, and ease of use scored 3.17, indicating positive reception. Improvements were made before the production stage, which only involved prototyping.

Missing data and missed infections: investigating racial and ethnic disparities in SARS-CoV-2 testing and infection rates in Holyoke, Massachusetts.

Routinely collected testing data have been a vital resource for public health response during the COVID-19 pandemic and have revealed the extent to which Black and Hispanic persons have borne a disproportionate burden of SARS-CoV-2 infections and hospitalizations in the United States. However, missing race and ethnicity data and missed infections due to testing disparities limit the interpretation of testing data and obscure the true toll of the pandemic. We investigated potential bias arising from these 2 types of missing data through a case study carried out in Holyoke, Massachusetts, during the prevaccination phase of the pandemic. First, we estimated SARS-CoV-2 testing and case rates by race and ethnicity, imputing missing data using a joint modeling approach. We then investigated disparities in SARS-CoV-2 reported case rates and missed infections by comparing case rate estimates with estimates derived from a COVID-19 seroprevalence survey. Compared with the non-Hispanic White population, we found that the Hispanic population had similar testing rates (476 tested per 1000 vs 480 per 1000) but twice the case rate (8.1% vs 3.7%). We found evidence of inequitable testing, with a higher rate of missed infections in the Hispanic population than in the non-Hispanic White population (79 infections missed per 1000 vs 60 missed per 1000).

Optimizing antibiotic management for patients with acute appendicitis: A quality improvement study

BackgroundTo decrease surgical site infections after appendectomy for acute appendicitis, preoperative broad-spectrum antibiotics are often used in clinical practice. However, this treatment strategy has come under scrutiny because of increasing rates of antibiotic-resistant infections. MethodsThe aim of this multisite quality improvement project was to decrease the treatment of uncomplicated acute appendicitis with piperacillin-tazobactam without increasing the rate of surgical site infections. Our quality improvement intervention had 2 distinct components: (1) updating electronic health record orders to encourage preoperative administration of narrow-spectrum antibiotics and (2) educating surgeons and emergency department clinicians about selecting appropriate antibiotic therapy for acute appendicitis. Patient demographics, clinical characteristics, and outcomes were compared 6 months before and after implementation of the quality improvement intervention. ResultsA total of 352 laparoscopic appendectomies were performed during the 6-month preintervention period, and 369 were performed during the 6-month postintervention period. The preintervention period and postintervention period groups had similar baseline demographics, vital signs, and laboratory test values. The rate of preoperative piperacillin-tazobactam administration significantly decreased after the intervention (51.4% preintervention period vs 20.1% postintervention period, P < .001). The rate of surgical site infections was similar in both groups (superficial surgical site infections = 1.4% preintervention period vs 0.8% postintervention period, P = .50; deep surgical site infections = 1.1% preintervention period vs 0.0% postintervention period, P = .06; and organ space surgical site infections = 3.1% preintervention period vs 3.0% postintervention period, P > .99). Rates of 30-day readmission, reoperation, and Clostridioides difficile infection also did not differ between groups. ConclusionOur quality improvement intervention successfully decreased piperacillin-tazobactam administration without increasing the rate of surgical site infections in patients with acute appendicitis.

Hybrid Framework To Exclude Similar and Faulty Test Cases In Regression Testing

Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar &amp; Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to identity and exclude redundant, similar and faulty test cases from the given regression suite. Our experimental results clearly show the benefits of the ETCPM framework in terms of reduction in the testing time, optimization of the resource allocation, and improvement in the overall quality of regression test suite. ETCPM enables software development teams to achieve faster and reliable regression testing by intelligent exclusion of similar and fault test cases, which yields in reduction in the software delivery cycles and better end user satisfaction.

Automated One-Sided Learning Fault Detection System for Reaction Wheel Bearing Friction Anomalies

Monitoring a satellite’s health during a mission has become critical in space engineering. In-flight anomaly detection is difficult for ground operators, placing space missions at risk of failure. Machine learning algorithms are data-driven methods that could autonomously detect faults in situ. In this paper, a new application of machine learning algorithms in space engineering is introduced for detecting reaction wheel bearing anomalies that only relies on nominal data (no failure data) for training and with no prior knowledge of the system dynamics. Using a one-sided regression method, an automated fault detection system was designed to monitor the attitude dynamics control system for a small satellite. The proposed detection algorithm was first trained using a simulated attitude dynamics control system for the small satellite. Next, the detection system was trained with only nominal behavioral data of the control system for a designated period of time. Then, different types of bearing friction failures were added to the simulated system to test the trained fault detection system. The empirical rule (68-95-99.7 rule) was used as a failure detection criterion to differentiate failure data from nominal. Similar physical tests were conducted using a combination of a brushless motor and drone propellers. Both simulation and experimental results demonstrated the robustness of detection accuracy, were model-free, and verified the feasibility of an easy-to-use, accurate, and autonomous anomaly detection system for reaction wheels that could be extended to other space systems.

Development and validation of an analytical procedure for the determination of residual protein A in active substances of therapeutic monoclonal antibodies

SCIENTIFIC RELEVANCE. An important quality-control issue for therapeutic monoclonal antibodies (mAbs) is the determination of residual protein A leaching from the carrier during the purification of mAbs by affinity chromatography. However, unrelated compounds (immunoglobulins) present in the sample can complicate the immunoenzymatic detection of protein A (matrix effect), potentially leading to false-negative test results. To increase the efficiency of enzyme-linked immunosorbent assay (ELISA), it is necessary to develop a sample preparation step that can irreversibly break the bond in the protein A–mAb complex.AIM. This study aimed to develop and validate an analytical procedure for the determination of residual protein A in active substances of therapeutic mAbs by ELISA with a test kit comprising in-house reagents.MATERIALS AND METHODS. Recombinant protein A was used as an antigen. Polyclonal antibodies to protein A were produced by immunising chickens, selecting immunised eggs, and isolating antibodies from these eggs. Protein A-specific antibodies were purified by affinity chromatography. Residual protein A was determined using sandwich ELISA with preliminary sample preparation. The analytical procedure was validated in accordance with the requirements of the State Pharmacopoeia of the Russian Federation (Validation of Analytical Procedures, OFS.1.1.0012).RESULTS. The authors obtained, isolated, and purified chicken IgY antibodies to recombinant protein A. The authors selected sample preparation conditions for the determination of residual protein A by ELISA and optimum compositions of buffer solutions, including the composition of a denaturing buffer to disrupt the protein A–mAb complex. The developed analytical procedure was validated. According to the measurements of protein A, the accuracy of the analytical procedure ranged within 83–108% of the nominal value, the interlaboratory precision ranged within 96–116%, and the repeatability was up to 13%. The lower limit of quantitation was 10 ng/mL with a minimum required dilution of 1:10. The analytical range extended from 10 to 40 ng/mL. The analytical procedure showed results comparable to those obtained with a similar test kit from an international manufacturer.CONCLUSIONS. The developed analytical procedure for the determination of residual protein A by ELISA with a test kit comprising in-house reagents can minimise the matrix effect in therapeutic mAbs. This analytical procedure will alleviate import substitution and reduce quality control costs for Russian immunobiologicals.

Mechanism of Stratum Instability and Dynamic Deformation under Discontinuous Boundary Conditions

A fault disrupts the continuity of the rock strata in a mining area. To study the law governing the fracture of overlying strata in mining areas under discontinuous boundary conditions, the overlying strata were redefined and grouped based on the activity characteristics of each rock layer during the overall movement of the overlying strata. The activity patterns of different layers of the fault were obtained through the movement and failure forms of each group of rock layers. The relationship among the size of the coal pillar at the boundary of the fault, the dip angle of the fault, and the movement angle of the rock strata was considered. A model of the spatial relationship between the overlying rock movement zone of the quarry and the fault surface was established. The limit equilibrium equations of the key layer in the fault zone before breaking were established based on the tensile strength of the rock layer. In addition, the mechanical slip instability criterion and the deflection instability criterion of the discontinuous-boundary rock mass are given herein. Based on a field case, a double criterion was used to determine the initiating activated rock layers of the fault in the cases where the fault dip was smaller than the rock movement angle. Rock movement during excavation was simulated by similar simulation tests, and different levels of rock movement patterns in the boundary fault zone were focused on monitoring and analyzing. The stress and displacement changes in different rock layers in the fault zone were analyzed with numerical simulation results. The results show the following: if the dip angle of the fault is smaller than the movement angle of the rock layer, the delamination space of the fault surface is mainly distributed in the bending and sinking zone of the overlying rock; with an increase in the working-face advancement distance, the vertical pressure of the upper part of the fault gradually decreases, and the stress-concentration area in the middle and lower part of the fault gradually increases; the rock layer of the upper part of the fault, which is mainly composed of the key stratum, is the main area of activation of the fault.

The Problem-Based Learning Model Assisted with the Ethlaf Application Contains Ethnomathematics to Improve Students' Conceptual Understanding Capability

Mathematics learning plays an important role in the world of education. However, the high demands for mastery of mathematics are not in accordance with current student learning outcomes. This is because learning is direct, so students' ability to understand concepts is low. This research aims to test the average ability of students to understand concepts by applying a problem-based learning model containing ethnomathematics supported by ETHLAF APPS, which is better than applying a direct learning model. This type of research is quantitative, using quasi-experimental methods and a nonequivalent pretest-posttest control group design. The sampling technique uses purposive sampling. This research was carried out in class X of Senior High School. The data collection technique uses tests, and the instrument uses concept understanding test questions. Data analysis includes the normality test, homogeneity test, similarity test, and final data analysis, namely the independent sample t-test. The research results show that the average ability of students to understand concepts when applying the problem-based learning model based on ethnomathematics assisted by ETHLAF APPS is better than when applying the direct learning model. This research concludes that students' ability to understand concepts using the ethnomathematics-based problem-based learning model supported by ETHLAF APPS is better than using direct learning. The ability to understand concepts is the main goal and important factor in learning mathematics.

Microbial diversity in dairy manure environment under liquid-solid separation systems

ABSTRACT In dairy manure, a wide array of microorganisms, including many pathogens, survive and grow under suitable conditions. This microbial community offers a tremendous opportunity for studying animal health, the transport of microbes into the soil, air, and water, and consequential impacts on public health. The aim of this study was to assess the impacts of manure management practices on the microbial community of manure. The key novelty of this work is to identify the impacts of various stages of manure management on microbes living in dairy manure. In general, the majority of dairy farms in California use a flush system to manage dairy manure, which involves liquid-solid separations. To separate liquid and solid in manure, Multi-stage Alternate Dairy Effluent Management Systems (ADEMS) that use mechanical separation systems (MSS) or weeping wall separation systems (WWSS) are used. Thus, this study was conducted to understand how these manure management systems affect the microbial community. We studied the microbial communities in the WWSS and MSS separation systems, as well as in the four stages of the ADEMS. The 16S rRNA gene from the extracted genomic DNA of dairy manure was amplified using the NovoSeq Illumina next-generation sequencing platform. The sequencing data were used to perform the analysis of similarity (ANOSIM) and multi-response permutation procedure (MRRP) statistical tests, and the results showed that microbial communities among WWSS and MSS were significantly different (p < 0.05). These findings have significant practical implications for the design and implementation of manure management practices in dairy farms.

Quantification of SARS‐CoV‐2 viral load in patients using time‐to‐results in antigen lateral flow tests

AbstractBased upon clinical observations and recent reports, we anticipated there would be an inverse dose–response relationship between the severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) viral load and the time‐to‐positivity after application of the nasal swab sample in two popular home coronavirus disease 2019 (COVID‐19) antigen tests, BinaxNOW COVID‐19 Antigen Self‐Test and Flowflex COVID‐19 Antigen Home Test, both of which are sensitive to the nucleocapsid protein (NP). The relationship among the concentration of NP, WA1, and Omicron XBB.1.5 viral strains and the time‐to‐positive result by visual assessment in the tests was examined. The correlation between reverse transcription‐polymerase chain reaction cycle threshold (Ct) values and time‐to‐positivity in clinical samples (training set) also was determined. Strong inverse correlations were obtained between the concentration of the NP, WA1, XBB.1.5, Ct values for dilutions of both WA1 and XBB.1.5, as well as Ct values from the clinical samples and time‐to‐positivity in both antigen tests. The correlation between the actual and predicted Ct values interpolated from the training set was high with both tests in a second set of clinical samples. These results, together with those of other investigations with similar tests, suggest that the time‐to‐positive visual result in most, if not all, lateral flow COVID‐19 antigen tests can be utilized to estimate SARS‐CoV‐2 viral concentrations.

When Sparse Neural Network Meets Label Noise Learning: A Multistage Learning Framework.

Recent methods in network pruning have indicated that a dense neural network involves a sparse subnetwork (called a winning ticket), which can achieve similar test accuracy to its dense counterpart with much fewer network parameters. Generally, these methods search for the winning tickets on well-labeled data. Unfortunately, in many real-world applications, the training data are unavoidably contaminated with noisy labels, thereby leading to performance deterioration of these methods. To address the above-mentioned problem, we propose a novel two-stream sample selection network (TS3-Net), which consists of a sparse subnetwork and a dense subnetwork, to effectively identify the winning ticket with noisy labels. The training of TS3-Net contains an iterative procedure that switches between training both subnetworks and pruning the smallest magnitude weights of the sparse subnetwork. In particular, we develop a multistage learning framework including a warm-up stage, a semisupervised alternate learning stage, and a label refinement stage, to progressively train the two subnetworks. In this way, the classification capability of the sparse subnetwork can be gradually improved at a high sparsity level. Extensive experimental results on both synthetic and real-world noisy datasets (including MNIST, CIFAR-10, CIFAR-100, ANIMAL-10N, Clothing1M, and WebVision) demonstrate that our proposed method achieves state-of-the-art performance with very small memory consumption for label noise learning. Code is available at https://github.com/Runqing-forMost/TS3-Net/tree/master.

Pengaruh Model Pembelajaran Matematika Knisley terhadap Pemahaman Konsep Matematis Siswa Kelas X

This research aims to determine the effect of the Knisley mathematics learning model on the understanding of mathematical concepts in class X SMA Negeri 2 Kabanjahe. This research was conducted using a sample of 2 classes, namely the Experiment class and the Control class. The form of test that is tested on students is an initial test (pretest), then the researcher provides treatment in the experimental teaching class using the Knisley Mathematics Learning Model and in the control class using the direct learning model, Then a posttest was given to both classes. The data obtained were analyzed using the t test. The results showed that the pretest average in the experimental and control classes was the same as tested using the average similarity test (two-way test) and met namely so accepted. For the posttest average equality test (right side test), it was concluded that the posttest average in the experimental class was greater than the control class because it met the requirements, namely 11.6111559 &gt; 1.66907, so was rejected and the conclusion was obtained that there was an influence Knisley's mathematics learning model for understanding mathematical concepts for class X.

Numerical Analysis of the Overtopping Failure of the Tailings Dam Model Based on Inception Similarity Optimization

The analysis of overtopping dam break caused by extreme rainstorms and other special circumstances is very important in the feasibility analysis of new construction or expansion projects of tailings reservoirs. Reduced-scale physical model tests can directly reflect the topography and dam-break influence range, but the reasonable selection of model dam material is the key to ensure the model’s similarity. Based on the similarity optimization of the limit state of scour inception of sediment particles, a new method for the model material of tailings dams can be proposed, but it needs to be verified by a similar overtopping model test. In this paper, the modeling and numerical calculation analysis of a prototype tailings dam and a similar reduced-scale model are carried out by using FLOW-3D v11.2 numerical software. The calculation results show that the model test scheme optimized by inception similarity can well reproduce the overtopping failure process of the prototype dam.

Development of non-hydrophilic similar materials for weakly cemented rocks and its experimental application in water conservation mining

Abstract The mining of coal mines in western China needs to focus on protecting groundwater. A non-hydrophilic similar material for simulating the development and hydraulic conductivity of weakly cemented overlying strata fractures was developed. Fine sand, coarse sand, and gypsum are used as aggregates. Paraffin and Vaseline are used as binders. The non-hydrophilic material ratios of weakly cemented sandy mudstone and medium-grained sandstone were determined by orthogonal experiments, and used for similar simulation tests. The results show that the non-hydrophilicity of rock-like materials can be adjusted to prevent them from softening and collapsing under the action of water. Non-hydrophilic materials of higher strength and brittleness of rocks can be achieved by adjusting the content of paraffin, fine sand, and gypsum. The non-hydrophilic materials of soft and large particle rocks can be achieved by adjusting the content of paraffin, fine sand, and gypsum. After the coal seam in a similar simulation experiment was extracted, the large area of weakly cemented rock above it underwent overall settlement and fracture. Although this part was located within the failure zone, there was no macroscopic water-conducting cracks generated. The height of the water-conducting fracture zone was lower than the height of the fracture zone classified by the traditional ‘three zone’ theory, which is consistent with the on-site measurements. This indicates that the prepared non-hydrophilic material is reliable. The similarity simulation method based on non-hydrophilic materials can enrich the means for studying the fracture and permeability of weakly cemented overlying rocks in coal mines.

Compensation Method for Current Measurement Errors in the Synchronous Reference Frame of a Small-Sized Surface Vehicle Propulsion Motor

This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as the current harmonic extractor and the compensator, respectively. It can compensate for the dq-axes offset and scaling errors simultaneously, improving phase current distortion while reducing the ripples of motor speed and torque. Compared to the traditional motor model-based compensation strategies, the proposed method is robust against the changes in motor parameters with the online adaptive capability of the ADALINE algorithm. Furthermore, due to the good real-time performance of SOGIs and ADALINEs, the proposed compensation strategy can effectively operate in both the steady state and transient state of the motor. Finally, the effectiveness of the proposed method is verified through the physical and hardware-in-the-loop (HIL) experiments. After compensating for the current measurement errors of a 1 kW test motor with the propeller-characteristics load, the torque ripple and speed ripple are reduced by more than 65% and 80%, respectively. At the same time, the DC component and the second-order and third-order harmonics in the phase currents are also significantly reduced. Similar test results can be also obtained on the HIL platform with a 100 kW permanent magnet motor.

A Comparison of 90° Bending for Foldable Electronics

In order to assess the longevity of foldable electronics, folding or bending tests on model systems need to be performed. However, not all bending tests are created equal in that different configurations lead to different amounts of mechanical damage and thus different electrical responses. Two 90° bending instruments were compared using two model metallic thin film systems on polyimide to establish if the two seemingly similar bending tests yield the same results. The two film systems, namely 300 nm Mo and 130 nm Al on 50 nm Mo, were magnetron-sputtered on polyimide substrates and tested in the custom-built FLEX-E-TEST and the commercially available YUASA test that is capable of in situ resistance measurements. For statistics, 10–12 samples were tested of each film system on each folding device using the same applied bending strain and number of cycles. Samples were intermittently characterized with confocal laser scanning microscopy and electrical resistance to correlate the amount of mechanical damage (crack density) with the electrical normalized resistance ratio of the damaged area. The results show that even with the same bending radius, a similar but not identical amount of mechanical damage forms for both bending devices. Additionally, the resistance as a function of cycles also differs after 10,000 cycles. A closer examination of the damage, especially in the Al/Mo film system, indicates that the speed of the bending, and if the samples experience spring back, can alter the received mechanical damage. The in situ resistance data of the YUASA test were further examined and a suggestion of standardizing how folding or bending test results are reported is provided.

Comparison of the Accuracy of Brown's and Holt's Double Exponential Smoothing in LQ45 Stock Price Forecasting

As of May 2022, 787 stocks are listed on the Indonesia Stock Exchange (IDX), and the number of stock indices in Indonesia to date is 38. One interesting and important stock index is the LQ45 index. Because this index is a very important reference index for investors, this research data focuses on stocks in the LQ45 index. There are two essential things in the forecasting process: the data and the right forecasting method. Two forecasting methods that can be used are Brown and Holt's Double Exponential Smoothing (DES). This study examines two methods with the lowest accuracy error in forecasting the LQ45 stock price data. Mean Absolute Percentage Error (MAPE) is used to measure the accuracy of the error. The analysis methods used to compare the MAPE of the two methods are the F test for variance similarity, Boxplot, t-test to test paired means with different cases of variance, and Wilcoxon signed rank test to test paired means nonparametric statistics. The result is that the MAPE average with Holt's DES method is smaller than the average MAPE with Brown's DES method. This is supported by the t-test for paired means with different cases of variance and also supported by the Wilcoxon signed exact rank test. Meanwhile, the MAPE standard deviation with Holt's DES method is smaller than the MAPE standard deviation with Brown's DES method. This is supported by the F test to test the variance similarity and is visually supported by a Boxplot diagram. From this study, LQ45 stocks with the smallest MAPE value accuracy are ICBP stocks. In general, based on the MAPE value, Holt's DES method is better than Brown's DES method in predicting the prices of stocks in the LQ45 index.

Studying the Humoral Response against SARS‐CoV‐2 in Cuban COVID‐19 Recovered Patients

Understanding the immune response generated by SARS‐CoV‐2 is critical for assessing efficient therapeutic protocols and gaining insights into the durability of protective immunity. The current work was aimed at studying the specific humoral responses against SARS‐CoV‐2 in Cuban COVID‐19 convalescents. We developed suitable tools and methods based on ELISA methodology, for supporting this evaluation. Here, we describe the development of an ELISA for the quantification of anti‐RBD IgG titers in a large number of samples and a similar test in the presence of NH4SCN as chaotropic agent for estimating the RBD specific antibody avidity. Additionally, a simple and rapid ELISA based on antibody‐mediated blockage of the binding RBD‐ACE2 was implemented for detecting, as a surrogate of conventional test, the levels of anti‐RBD inhibitory antibodies in convalescent sera. In a cohort of 273 unvaccinated convalescents, we identified higher anti‐RBD IgG titer (1 : 1,330, p &lt; 0.0001) and higher levels of inhibitory antibodies blocking RBD‐ACE2 binding (1 : 216, p &lt; 0.05) among those who had recovered from severe illness. Our results suggest that disease severity, and not demographic features such as age, sex, and skin color, is the main determinant of the magnitude and neutralizing ability of the anti‐RBD antibody response. An additional paired longitudinal assessment in 14 symptomatic convalescents revealed a decline in the antiviral antibody response and the persistence of neutralizing antibodies for at least 4 months after the onset of symptoms. Overall, SARS‐CoV‐2 infection elicits different levels of antibody response according to disease severity that declines over time and can be monitored using our homemade serological assays.