Weibull Function Research Articles

Response of eolian quartz flux and grain size in the Parece Vela Basin sediment to the mid-Pleistocene transition

The most significant climate changes in the Quaternary occurred in the mid-Pleistocene transition (MPT). However, as the main component of eolian dust, it remains unknown how the fluxes and components of quartz responded to the MPT. We recovered a sediment core from the Parece Vela Basin (PVB), which dated back to 2.1 Ma, and quantitatively separated quartz from the sediments in order to track source area and transport mechanism. The grain size compositions, morphological characteristics, oxygen isotope compositions, and crystallinity indices of quartz showed that quartz minerals in the sediments were composed of fine-grained endmembers (EM1) with a mode grain size at 3.2 μm, and coarse-grained endmembers (EM2) with a mode grain size at 9.5 μm. The EM1 quartz mainly came from the Mongolian Gobi and Taklimakan Desert, and the EM2 quartz was predominantly derived from volcanic island arc. By fitting the grain size composition with the Weibull function, we were able to quantitatively separated EM1 and EM2 quartz fractions, and calculated the contents and mass accumulation rates (MARs) of eolian quartz. The mode grain sizes of eolian quartz increased at 1.2 Ma, but fluctuated during the mid-Pleistocene. The MARs of the eolian quartz have increased significantly since the mid-Pleistocene, most likely due to enhanced aridity in the Asia interior. Our study demonstrates that eolian quartz in the northwest Pacific can be used to trace the long-term paleoclimate change in the Asia continent.

A life extrapolation model using accelerated equivalent luminance and its application

Aiming at predicting the life of vacuum fluorescent display (VFD) accurately, four groups of constant-stress accelerated degradation tests (ADTs) were conducted, and the life extrapolation model of accelerated equivalent luminance (LEMAEL) based on each test sample was proposed. In this model, firstly, Weibull function was employed to fit luminance degradation data of each sample at each stress. Secondly, Logistic function was determined by Anderson-Darling test to respectively describe the distributions of shape and scale parameters, and the degradation formula of accelerated equivalent luminance was obtained to estimate accelerated life. Finally, Power function was selected by comparing determination coefficients to fit the data points formed by accelerated life and stress, and thereby VFD life was extrapolated. The results indicate that the collected test data of each sample objectively reflect VFD luminance characteristics; the degradation formula intuitively exhibits the luminance variation law at each accelerated stress, and Power function accurately reveals the relationship between life and stress; LEMAEL is characterized by high precision and large amount of data information, which not only actualizes the accurate life estimation for light-emitting devices without conventional life tests, but also provides entirely new modeling ideas and thoughts for reliability evaluation and life prediction of products.

First estimates of diffuse gastric cancer risks for carriers of CTNNA1 germline pathogenic variants

BackgroundPathogenic variants (PV) of CTNNA1 are found in families fulfilling criteria for hereditary diffuse gastric cancer (HDGC) but no risk estimates were available until now. The aim of this study...

Prediction of Wildfire Fuel Load for Pinus densiflora Stands in South Korea Based on the Forest-Growth Model

A prediction model was developed for the wildfire fuel load of Korean red pine (Pinus densiflora) stands with susceptibility to forest fire based on the forest-growth model. Furthermore, a time-series analysis was performed on the variation in forest-fire fuel load according to forest management. National Forest Inventory stand data of 1434 plots for P. densiflora stands were used, and the final forest-fire fuel load prediction model was developed using the Weibull function and mortality model. The fit index of the diameter distribution model ranged from 0.58 (0th percentile) to 0.96 (50th percentile), and that of the mortality model was 0.68. The prediction of the stand growth variation after 20 years based on the growth data of managed and unmanaged stands indicated a mean stand density of 1518 trees per ha for unmanaged stands, and 885 trees per ha for managed stands. Regarding the variation in the available canopy fuel load distribution, the predicted annual increase was approximately 0.7 ton/ha for unmanaged stands and approximately 0.5 ton/ha for managed stands. These findings will contribute to setting fuel management criteria to prevent forest fire spread while providing the quantitative data of the characteristics of stand growth variation and the predicted wildfire fuel load.

Interactive Effects of Temperature and Plant Host on the Development Parameters of Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae).

Simple SummaryThe beet armyworm Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae) is an economic pest that causes significant damage to various vegetables and field crops in Korea. Timely forecasting of pest emergence and occurrence plays a vital role in pest management. To predict the spring emergence and population dynamics of S. exigua, constant temperature-mediated developmental parameters of S. exigua were studied with linear and nonlinear models on different plant hosts. The temperature and plant host significantly influenced the development of S. exigua. The total developmental time decreased with the increase in temperature, although there was no development at extreme temperatures. We developed a forecasting model, and our findings predicted the spring emergence of S. exigua in June. Thus, continuous monitoring of S. exigua in crop fields is needed to be ready to take advanced management measures against S. exigua.This study investigated the effects of different temperatures (15, 20, 25, 27, 30, 35, and 40 °C) on the development rate of Spodoptera exigua (Hübner) eggs, larvae, pupae, and total immatures on plant hosts (soybean, maize, potato, and green pea). The eggs of S. exigua developed successfully at all the tested temperatures, except at 40 °C. The total developmental time (egg-adult) decreased with an increasing temperature from 15 to 35 °C on plant hosts. Stage-specific parameters such as the lower threshold temperature (TH) were determined using linear and nonlinear models (Sharpe-Schoolfield-Ikemoto [SSI]). The lower developmental threshold (LDT) and thermal constant (K) were determined using a linear model. The LDT and K for the total immature stage had respective values of 11.9 °C and 397.27° -day (DD) on soybean, 11.6 °C and 458.34° -day (DD) on maize, 11.2 °C and 446.23° -day (DD) on potato, 10.7 °C and 439.75° -day (DD) on green pea, and 12.2 °C and 355.82° -day (DD) on the artificial diet. The emergence frequency of adult S. exigua over the full range of constant temperatures was simulated using nonlinear developmental rate functions and the Weibull function. This study predicted the spring emergence date in the first to second weeks of June, with approximately five generations for plant hosts. The interaction of temperature and plant host also influenced the development and longevity of the adults. Overall, the findings of this study may be useful for predicting the number of generations, occurrence, population dynamics in crop fields, and management of S. exigua.

Temperature-Dependent Development of the Post-Diapause Periods of the Apricot Seed Wasp Eurytoma maslovskii (Hymenoptera: Eurytomidae): An Implication for Spring Emergence Prediction Models.

Simple SummaryEurytoma maslovskii is an important stone fruit pest whose control relies on application timing, which requires a reliable tool for predicting spring emergence. The most common approach in insect phenological modeling is based on temperature-dependent development and thermal bioparameters. However, not a lot is known regarding E. maslovskii. In the present study, we investigate the development of E. maslovskii after diapause breaks at various temperatures. The lower temperature threshold and thermal constant of the species after diapause are estimated. The results confirm that the field emergence of E. maslovskii can be predicted by a model using accumulated degree days starting from 1 January, thereby providing an efficient tool for pest-control decision making.The present study investigates the influence of temperature on the development of Eurytoma maslovskii after a diapause break up until adulthood. The insect development rate was fitted to both linear and nonlinear models to estimate thermal bioparameters, which served as the basis for constructing prediction models. Chilled apricot seeds collected in November were used for the experiments in March. Experiment 1 used intact seeds, while experiment 2 used overwintered larvae obtained by cracking the endocarp cover. Both larvae and intact seeds were subjected to seven constant temperatures (14.5, 18.8, 21.3, 24.0, 27.0, 30.2, and 34.3 °C). The post-diapause larvae of E. maslovskii developed into adults at a temperature range of 14.5–30.2 °C, and no larvae pupated at 34.3 °C. The lower temperature thresholds (LTs) for post-diapause larva and pupa and the total post-diapause period until adult emergence and until adult exit were 8.1, 8.2, 8.2, and 7.3 °C, respectively, whose thermal constants (DD) were 66.2, 180.2, 246.9, and 336.7 degree days, respectively. The distribution of E. maslovskii at all post-diapause stages was described using a two-parameter Weibull function. The data predicted by the model using accumulated degree days starting from January 1 did not differ by more than three days from the observed field emergence of E. maslovskii. Our data provide insights into the development of E. maslovskii after diapause. Temperature-dependent development supports the use of a degree day model to predict field emergence for pest timing control.

A life testing system design and life prediction for plant lighting LED-based luminaires

With the increasing demand for plant lighting LED-based luminaires, the reliability is facing a severe test, and the collection and the research of their life information is imminent. Firstly, the life testing system of plant lighting LED-based luminaires is constructed independently by conducting the preliminary tests of samples. Secondly, the test steps are designed to collect the luminance attenuation data of samples. Finally, the data pretreatment scheme is proposed to optimize the test data under conventional stress, and the life prediction is achieved by three-parameter Weibull right approximation method (TPWRAM). The results indicate that the collected test data well reflect the luminance attenuation characteristics of plant lighting LED-based luminaires, and the developed life test system has higher feasibility. The self-designed data preprocessing scheme is scientific and reasonable, and the processed test data objectively describe the luminance attenuation trend. In addition, the most important thing is that three-parameter Weibull function fits well with test data, which can accurately predict the normal life of plant lighting LED-based luminaires. The above results can provide technical reference for engineers to improve the performance of plant lighting LED-based luminaire.

Обобщенная модель распределения диаметров деревьев в сосновых древостоях

A generalized statistical model for the distribution of tree diameters for pine forest plantations, developed on the basis of a three-parameter Weibull function, is presented. Its parameters were restored using data from 231 distribution series on 24 permanent sample plots in the Forest Experimental Station of the Russian State Agrarian University — Moscow Timiryazev Agricultural Academy from the first and second central moments of the distribution. It is shown that their estimates can be obtained from the equations of connection with the root-mean-square diameter of trunks in a forest stand. It was revealed that the developed model approximates with high accuracy the actual distributions of tree diameters in maturing, middle-aged and mature forest stands, and in young stands there may be deviations between the actual and predicted frequency values. It is shown that the main purpose of the developed model is to predict the distribution of diameters of tree trunks in future ages of forest stands to optimize the management of forest plantations.

Parameters estimation and fatigue life prediction of sisal fibre reinforced foam concrete

Based on the Glivenko-Cantelli theorem and Weibull distribution functions, the fatigue life of foam concrete with different sisal fibre volume fraction (0–0.3% vol.) was performed. When the two-parameter Weibull function was selected, a linear regression analysis showed that the fatigue life had high correlation between the independent and dependent variables (correlation coefficients above 0.75). But the three-parameter Weibull analysis gave more accurate results (correlation coefficients above 0.90). Then, the corresponding Weibull probability density function distributions of the fatigue lives were compared. Based on the parameters obtained, the fatigue lives of foam concrete with different survival probabilities were analyzed and compared with results taken from the literature. Finally, for specific survival probabilities, the fatigue limit and fatigue life of foam concrete under specified stress level were predicted.

Assessment of Destructive and Nondestructive Analysis for GGBS Based Geopolymer Concrete and Its Statistical Analysis.

Geopolymer is the alternative to current construction material trends. In this paper, an attempt is made to produce a sustainable construction composite material using geopolymer. Ground granulated blast furnace slag (GGBS)-based geopolymer concrete was prepared and tested for different alkaline to binder ratios (A/B). The effect of various temperatures on compressive strength properties was assessed. The cubes were exposed to temperature ranging from 50 to 70 °C for a duration ranging from 2 to 10 h, and the compressive strength of the specimens was analyzed for destructive and non-destructive analysis and tested for 7, 28, and 90 days. The obtained compressive strength (CS) results were analyzed employing the probability plot (PP) curve, distribution overview curve (DOC), probability density function (PDF), Weibull, survival, and hazard function curve. Maximum compressive strength was achieved for the temperature of 70 °C and an A/B of 0.45 for destructive tests and non-destructive tests with 44.6 MPa and 43.56 MPa, respectively, on 90 days of testing. The survival and hazard function curves showed incremental distribution characteristics for 28 and 90 days of testing results with a probability factor ranging from 0.8 to 1.0.

Assessing the Potential of Wind Energy as Sustainable Energy Production in Ramallah, Palestine

The meteorological statistics collected from six-year wind speed data of Ramallah in Palestine are used to evaluate the potential of wind energy. The Weibull function is utilized to statistically assess the wind performance. An examination of the wind data using hourly wind directions and speeds throughout the six-year period between 2016 and 2021. The investigation revealed that the Weibull model provided a precise explanation of the actual wind data using the maximum likelihood estimator approach for scale and shape parameters. The most prevalent wind direction in Ramallah was west-northwest, accounting for 29.5% of all occurrences. Summer months have the maximum power density, reaching 129.9 at 50 m, 196.0 at 75 m, and 268.9 W/m2 at 100 m. In the conclusion, yearly energy outputs, capacity factors, and economic potential for fifteen wind turbines ranging in size from 0.5 to 5 MW had been evaluated. It was revealed that the greatest capacity factor is about 36% and has a high economic potential at a cost of less than 0.07 $/kWh for an appropriate selection of wind turbine models. This baseline research will be utilized as a decision-making basis for the best and most economical wind energy investment in Palestine.

Statistical Analysis of the Vertical Temperature Gradient of the Web Plate of Steel Box Girder Bridges in Cold Regions

To understand the actual vertical temperature gradient mode of steel box girder webs in cold regions, nearly 1.5 million data measured for over a year by a comprehensive temperature collection system of a steel box girder bridge in a cold region were used to verify the typicality of the temperature screening samples, and a cluster analysis was performed to verify the statistical symmetry of temperature at the symmetry points of webs on both sides of the bridge. One years' worth of daily temperature difference data were used to investigate the vertical temperature difference distribution on the web and to determine the probability distribution curve form. After selecting the extreme temperature difference samples, the standard vertical temperature difference of the web was calculated, and the actual vertical temperature gradient model of the steel box girder web was established. Results show that the probability distribution model of temperature at the symmetrical points of webs on both sides of the steel box girder was symmetric. The vertical temperature differences of the web demonstrated significant seasonal changes. The probability distribution of the positive and negative temperature differences can be described based on the sum of two Weibull distribution functions. The temperature gradients at all levels in the proposed vertical temperature gradient model were generally greater than the values indicated in the relevant specifications.

Physiologically Based Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs.

For successful oral drug development, defining a bioequivalence (BE) safe space is critical for the identification of newer bioequivalent formulations or for setting of clinically relevant in vitro specifications to ensure drug product quality. By definition, the safe space delineates the dissolution profile boundaries or other drug product quality attributes, within which the drug product variants are anticipated to be bioequivalent. Defining a BE safe space with physiologically based biopharmaceutics model (PBBM) allows the establishment of mechanistic in vitro and in vivo relationships (IVIVR) to better understand absorption mechanism and critical bioavailability attributes (CBA). Detailed case studies on how to use PBBM to establish a BE safe space for both innovator and generic drugs are described. New case studies and literature examples demonstrate BE safe space applications such as how to set in vitro dissolution/particle size distribution (PSD) specifications, widen dissolution specification to supersede f2 tests, or application toward a scale-up and post-approval changes (SUPAC) biowaiver. A workflow for detailed PBBM set-up and common clinical study data requirements to establish the safe space and knowledge space are discussed. Approaches to model in vitro dissolution profiles i.e. the diffusion layer model (DLM), Takano and Johnson models or the fitted PSD and Weibull function are described with a decision tree. The conduct of parameter sensitivity analyses on kinetic dissolution parameters for safe space and virtual bioequivalence (VBE) modeling for innovator and generic drugs are shared. The necessity for biopredictive dissolution method development and challenges with PBBM development and acceptance criteria are described.

Evaluation of wind power generation projects to reduce air pollution using multi-criteria decision-making methods in Saudi Arabia.

Currently, Saudi Arabia has very limited renewable energy generation capacity, as most of the country's electricity sector is dependent on cheap fossil fuels. However, in recent years, the Saudi government has announced a national development program called "the Saudi Vision 2030," whereby the country intends to increase the share of renewable energies in its total power generation to 20% by 2030. This research is aimed on the possibility of developing wind farms in Saudi Arabia's Al-Jawf area, which is known to be rich in wind sources. The potential of wind energy in the region was examined in the first phase of the research, which focused at the environmental, economic, and technical aspects. For this goal, the two-parameter Weibull function was used to model wind energy in the area. The economic assessment was performed in terms of the Levelized Cost of Energy and payback period. Multi-criteria decision-making approaches were employed in the second phase of the study to determine the most proper sites for harvesting wind energy in the study region based on eight factors including technical, economic, environmental, and social aspects. The most proper site for wind farms was identified by the combined use of Stepwise Weight Assessment Ratio Analysis and Weighted Aggregated Sum Product Assessment. The results showed that the most proper site for locating wind farms in the study area is the city of Al-Qurrayyat, where, using 1 MW turbines, it will be possible to produce 2357 MWh/year of electricity at a cost of 0.092 $/kWh, resulting in a payback period of 8.1 years. From the environmental perspective, wind power generation in Al-Qurrayyat will result in 1124.15 ton/year of CO2 emissions reduction.

Developing an Artificial Hummingbird Algorithm for Probabilistic Energy Management of Microgrids Considering Demand Response

This study proposes an artificial hummingbird algorithm (AHA) for energy management (EM) for optimal operation of a microgrid (MG), including conventional sources and renewable energy sources (RES), with an incentive-based demand response (DR). Due to the stochastic nature of solar and wind output power and the uncertainty of prices and load, a probabilistic EM with hybrid AHA and point estimation method (PEM) is proposed to model this uncertainty by utilizing the normal and Weibull distribution functions. The PEM method is considered a good tool for handling stochastic EM problems. It achieves good results using the same procedures used with the deterministic problems while maintaining low computational efforts. The proposed AHA technique is employed to solve a deterministic incentive DR program, with the goal of reducing the overall cost, which includes the cost of conventional generator fuel and the cost of power transaction with the main grid while taking into account the load demand. Two different case studies are tested. The simulation results of the proposed AHA is compared with the results of well-known metaheuristic algorithms to demonstrate its efficacy. According to AHA’s results, a total reduction of energy consumption by 104 KWh for the first case study and 2677 MWh for the second case study is achieved while achieving the lowest overall operating cost. The results demonstrate that the AHA is adequate for tackling the EM problem. Then, to examine the effect of uncertainty on the MG state, a probabilistic EM problem is solved using AHA-PEM.

Wavelength trends of photoproduction of reactive transient species by chromophoric dissolved organic matter (CDOM), under steady-state polychromatic irradiation

The formation quantum yields of photochemically produced reactive intermediates (PPRIs) by irradiated CDOM (in this study, Suwannee River Natural Organic Matter and Upper Mississippi River Natural Organic Matter) decrease with increasing irradiation wavelength. In particular, the formation quantum yields of the excited triplet states of CDOM (3CDOM*) and of singlet oxygen (1O2) have an exponentially decreasing trend with wavelength. The •OH wavelength trend is different, because more effective •OH production occurs under UVB irradiation than foreseen by a purely exponential function. We show that the parameter-adjustable Weibull function (which adapts to both exponential and some non-exponential trends) is suitable to fit the mentioned quantum yield data, and it is very useful when CDOM irradiation is carried out under polychromatic lamps as done here. Model calculations suggest that, thanks to the ability of CDOM to also absorb visible radiation, and despite its decreasing quantum yield of •OH generation with increasing wavelength, CDOM would be able to trigger •OH photogeneration in deep waters, to a higher extent than UVB-absorbing nitrate or UVB + UVA-absorbing nitrite.

Development of a population pharmacokinetic/pharmacodynamic model for various oral paclitaxel formulations co-administered with ritonavir and thrombospondin-1 based on data from early phase clinical studies

PurposeOrally administered paclitaxel offers increased patient convenience while providing a method to prolong exposure without long continuous, or repeated, intravenous infusions. The oral bioavailability of paclitaxel is improved through co-administration with ritonavir and application of a suitable pharmaceutical formulation, which addresses the dissolution-limited absorption of paclitaxel. We aimed to characterize the pharmacokinetics of different paclitaxel formulations, co-administered with ritonavir, and to investigate a pharmacodynamic relationship between low-dose metronomic (LDM) treatment with oral paclitaxel and the anti-angiogenic marker thrombospondin-1 (TSP-1).MethodsFifty-eight patients treated with different oral paclitaxel formulations were included for pharmacokinetic analysis. Pharmacodynamic data was available for 36 patients. All population pharmacokinetic/pharmacodynamic modelling was performed using non-linear mixed-effects modelling.ResultsA pharmacokinetic model consisting of gut, liver, central, and peripheral compartments was developed for paclitaxel. The gastrointestinal absorption rate was modelled with a Weibull function. Relative gut bioavailabilities of the tablet and capsule formulations, as fractions of the gut bioavailability of the drinking solution, were estimated to be 0.97 (95%CI: 0.67–1.33) and 0.46 (95%CI: 0.34–0.61), respectively. The pharmacokinetic/pharmacodynamic relationship between paclitaxel and TSP-1 was modelled using a turnover model with paclitaxel plasma concentrations driving an increase in TSP-1 formation rate following an Emax relationship with an EC50 of 284 ng/mL (95%CI: 122–724).ConclusionThe developed pharmacokinetic model adequately described the paclitaxel plasma concentrations for the different oral formulations co-administered with ritonavir. This model, and the established pharmacokinetic/pharmacodynamic relationship with TSP-1, may facilitate future development of oral paclitaxel.

Wind Resource Assessment: Optimizing the Weibull Distribution Curve

Abstract: In this paper, it was analyze the wind speed characteristics and provide projections of optimal wind resources by comparing data at different hub heights using wind power law. We have acquired data from an operational project site in the western part of India using data points acquired from the site from August 2017 to February 2018.Weibull distribution probability distribution function and cumulative distribution function for wind speed and other parameters involved in an accurate wind resource assessment methodology. To predict wind regimes, the Weibull probability function is commonly used. A comparison of alternative methods for estimating Weibull parameters of a wind regime is presented in this research. For the estimation, five alternative methods are discussed and employed. The study examined wind speed time series data at two sites over the course of a year. Although all five methods produce similar results when plotting error versus wind speed, the standard deviation method produces the best results.

Impacts of climate change on seasonal extreme waves in the Northwest Atlantic using a Spatial Neural Gas clustering method

Having estimates of wave climate parameters and extreme values play important roles for a variety of different societal activities, such as coastal management, design of inshore and offshore structures, marine transport, coastal recreational activities, fisheries, etc. This study investigates the efficiency of a state-of-the-art spatial neutral gas clustering method in the classification of wind/wave data and the evaluation of extreme values of significant wave heights (Hs), mean wave direction (MWD) and mean wave periods (T0) for two 39-year time periods; from 1979 to 2017 for the present climate, and from 2060 to 2098, for a future climate change scenario in the Northwest Atlantic. These data were constructed by application of a numerical model, WAVEWATCHIII™ (hereafter, WW3), to simulate the wave climate for the study area for both present and future climates. Data from the model was extracted for the wave climate, in terms of the wave parameters, specifically Hs, MWD and T0, which were analyzed and compared for winter and summer seasons, for present and future climates. In order to estimate extreme values in the study area, a Natural Gas (hereafter, NG) clustering method was applied, separate clusters were identified, and corresponding centroid points were determined. To analyze data at each centroid point, time series of wave parameters were extracted, and using standard stochastic models, such as Gumbel, exponential and Weibull distribution functions, the extreme values for 50 and 100-year return periods were estimated. Thus, the impacts of climate change on wave regimes and extreme values can be specified.

Comparative Learning Curves of Microscope Versus Exoscope: A Preclinical Randomized Crossover Noninferiority Study.

BackgroundAn exoscope heralds a new era of optics in surgery. However, there is limited quantitative evidence describing and comparing the learning curve.ObjectivesThis study aimed to investigate the learning curve, plateau, and rate of novice surgeons using an Olympus ORBEYE exoscope compared to an operating microscope (Carl Zeiss OPMI PENTERO or KINEVO 900).MethodsA preclinical, randomized, crossover, noninferiority trial assessed the performance of seventeen novice and seven expert surgeons completing the microsurgical grape dissection task “Star’s the limit.” A standardized star was drawn on a grape using a stencil with a 5 mm edge length. Participants cut the star and peeled the star-shaped skin off the grape with microscissors and forceps while minimizing damage to the grape flesh. Participants repeated the task 20 times consecutively for each optical device. Learning was assessed using model functions such as the Weibull function, and the cognitive workload was assessed with the NASA Task Load Index (NASA-TLX).ResultsSeventeen novice (male:female 12:5; median years of training 0.4 [0–2.8 years]) and six expert (male:female 4:2; median years of training 10 [8.9–24 years]) surgeons were recruited. “Star’s the limit” was validated using a performance score that gave a threshold of expert performance of 70 (0–100). The learning rate (ORBEYE −0.94 ± 0.37; microscope −1.30 ± 0.46) and learning plateau (ORBEYE 64.89 ± 8.81; microscope 65.93 ± 9.44) of the ORBEYE were significantly noninferior compared to those of the microscope group (p = 0.009; p = 0.027, respectively). The cognitive workload on NASA-TLX was higher for the ORBEYE. Novices preferred the freedom of movement and ergonomics of the ORBEYE but preferred the visualization of the microscope.ConclusionsThis is the first study to quantify the ORBEYE learning curve and the first randomized controlled trial to compare the ORBEYE learning curve to that of the microscope. The plateau performance and learning rate of the ORBEYE are significantly noninferior to those of the microscope in a preclinical grape dissection task. This study also supports the ergonomics of the ORBEYE as reported in preliminary observational studies and highlights visualization as a focus for further development.