Accurate Size Estimation Research Articles

Comparative detection, density, and reproductive performance of Kirtland's warbler in jack and red pine

AbstractThe formerly endangered Kirtland's warbler (Setophaga kirtlandii) is among a growing number of conservation‐reliant species that depend on active management to avoid reverting to endangered status. Because the Kirtland's warbler is a habitat specialist of young, even‐aged jack pine (Pinus banksiana), managers of the recovery effort stressed creating new jack pine stands and monitoring numbers of singing males through an annual census using single visits to individual stands. Kirtland's warbler will occupy and breed in red pine (P. resinosa), but red pine has not been surveyed for Kirtland's warblers in the annual population census. Furthermore, the current monitoring approach cannot determine their species detection probability or individual detection probability, which is essential to evaluate both red pine use and the accuracy of the census. From 2016–2018 we estimated density and detection probabilities in jack pine and red pine stands through repeated visits to a limited number of stands rather than single visits to many stands. Estimates of species detection probability indicated that ≥1 male Kirtland's warbler would be detected on most sites when any were present, but individual detection probabilities were less and varied by stand type, indicating that single visits to sites would underestimate numbers and that accurate estimation of detection probability was important for estimation of density in different stand types. We offer quantitative estimates of detection probabilities for determination of Kirtland's warbler population size in jack pine versus red pine stands in the same areas and breeding seasons. Managers of Kirtland's warblers should incorporate detection probabilities into population surveys to achieve more accurate estimates of population size.

Uncertainty in Grain Size Estimations of Volatiles on Trans-Neptunian Objects and Kuiper Belt Objects

Abstract We analyze the uncertainty in grain size estimation of pure methane (CH4) and nitrogen saturated with methane (N2:CH4) ices, the most abundant volatile materials on trans-Neptunian objects (TNOs) and Kuiper Belt objects (KBOs). We compare the single scattering albedo, which determines the grain size estimation of outer solar system regolith, of these ices using the Mie scattering model and two other Hapke approximations (Hapke 1993) in radiative transfer scattering models (RTMs) at near-infrared (NIR) wavelengths (1–5 μm). The equivalent slab (Hapke slab) approximation model predicts results much closer to Mie scattering over the NIR wavelengths at a wide range of grain sizes. In contrast, even though the internal scattering model predicts an approximate particle diameter close to the Mie model for particles with a 10 μm radii, it exhibits higher discrepancies in the predicted estimation for larger grain sizes (e.g., 100 and 1000 μm radii). Owing to the Rayleigh effect on single-scattering properties, neither Hapke approximate models could predict an accurate grain size estimation for the small particles (radii ≤5 μm). We recommend that future studies should favor the Hapke slab approximation when employing RTMs for estimating grain sizes of the vast number of TNOs and KBOs in the outer solar system.

Ultra-Wideband Microwave Imaging System for Root Phenotyping.

The roots are a vital organ for plant growth and health. The opaque surrounding environment of the roots and the complicated growth process means that in situ and non-destructive root phenotyping face great challenges, which thus spur great research interests. The existing methods for root phenotyping are either unable to provide high-precision and high accuracy in situ detection, or they change the surrounding root environment and are destructive to root growth and health. Thus,we propose and develop an ultra-wideband microwave scanning method that uses time reversal to achieve in situ root phenotyping nondestructively. To verify the method’s feasibility, we studied an electromagnetic numerical model that simulates the transmission signal of two ultra-wideband microwave antennas. The simulated signal of roots with different shapes shows the proposed system’s capability to measure the root size in the soil. Experimental validations were conducted considering three sets of measurements with different sizes, numbers and locations, and the experimental results indicate that the developed imaging system was able to differentiate root sizes and numbers with high contrast. The reconstruction from both simulations and experimental measurements provided accurate size estimation of the carrots in the soil, which indicates the system’s potential for root imaging.

Use of transmission error for a quantitative estimation of root-crack severity in gears

Gear transmission error (TE) has been acknowledged as a prominent diagnostic tool in condition monitoring. Its advantages vs vibration include being closer to the source and less affected by transmission path effects. TE has recently demonstrated its enormous capabilities in gear wear severity assessment. For crack diagnostics, despite some promising preliminary results, a methodology for an accurate and reliable TE-based estimation of crack size was previously not available. In order to achieve this result two main obstacles needed to be overcome: (i) the removal of dynamic TE effects due to speed and (ii) the separation of profile error and compliance-related tooth deflections. This paper proposes a new crack-severity-estimation methodology that solves these problems. The proposed technique exploits different speeds and loads, often experienced by geared transmissions, and includes an automated identification of the cracked tooth and a crack-depth estimation based on a comparison with a theoretical tooth stiffness model. The proposed methodology is validated using experimental encoder measurements collected from a spur gear test rig with artificially seeded root cracks.

Guppies (Poecilia reticulata) are deceived by visual illusions during obstacle negotiation.

Animals travelling in their natural environment repeatedly encounter obstacles that they can either detour or go through. Gap negotiation requires an accurate estimation of the opening's size to avoid getting stuck or being injured. Research on visual illusions has revealed that in some circumstances, transformation rules used to generate a three-dimensional representation from bidimensional retinal images fail, leading to systematic errors in perception. In Ebbinghaus and Delboeuf illusions, the presence of task-irrelevant elements causes us to misjudge an object's size. Susceptibility to these illusions was observed in other animals, although with large intraspecific differences. In this study, we investigated whether fish can accurately estimate gap size and whether during this process they may be deceived by illusory patterns. Guppies were extremely accurate in gap negotiation, discriminating holes with a 10% diameter difference. When presented with two identical holes surrounded by inducers to produce Ebbinghaus and Delboeuf patterns, guppies misperceived gap size in the predicted direction. So far, researchers have principally considered illusions as useful tools for exploring the cognitive processing underlying vision. Our findings highlight the possibility that they have important ecological implications, affecting the everyday interactions of an animal with its physical world besides its intra- and interspecific relationships.

Imaging somatosensory cortex responses measured by OPM-MEG: Variational free energy-based spatial smoothing estimation approach

SummaryIn recent years, optically pumped magnetometer (OPM)-based magnetoencephalography (MEG) has shown potential for analyzing brain activity. It has a flexible sensor configuration and comparable sensitivity to conventional SQUID-MEG. We constructed a 32-channel OPM-MEG system and used it to measure cortical responses to median and ulnar nerve stimulations. Traditional magnetic source imaging methods tend to blur the spatial extent of sources. Accurate estimation of the spatial size of the source is important for studying the organization of brain somatotopy and for pre-surgical functional mapping. We proposed a new method called variational free energy-based spatial smoothing estimation (FESSE) to enhance the accuracy of mapping somatosensory cortex responses. A series of computer simulations based on the OPM-MEG showed better performance than the three types of competing methods under different levels of signal-to-noise ratios, source patch sizes, and co-registration errors. FESSE was then applied to the source imaging of the OPM-MEG experimental data.

Effect of body mass index on the conventional method of templating in uncemented total hip arthroplasty: A prospective study

BACKGROUND: Preoperative templating is an important step in total hip arthroplasty (THA). Results of traditional as well as digital method of templating are well established in various studies. Very few studies have evaluated the effect of body mass index (BMI) and gender on templating. Our study was undertaken to evaluate the effect of BMI and gender in accurate size estimation in uncemented THA components by conventional method of templating. MATERIALS AND METHODS: Preoperative radiographs were templated for 60 patients who underwent primary uncemented THA. BMI and gender of patients were noted during preoperative evaluation. Patients were grouped as per gender and divided into three groups as per BMI (underweight <18.5, normal 18.5-24.9, overweight >25). The estimated preoperative template size was compared with the actual implant size used. P-value of <0.05 was considered to be significant. RESULTS: Acetabular component was exactly templated in 63.33% and femoral component in 76.6% cases. Gender and BMI had no statistical difference in component size prediction. Post-operative analysis of THA performed showed statistically significant association between high BMI and limb length discrepancy and restoration of femoral offset. CONCLUSION: In our study, we found that femoral component is more accurately predicted. No statistically significant effect of gender and BMI was seen in accuracy of conventional method of templating in implant size estimation. However, BMI is found to affect limb length assessment during surgery and restoration of femoral offset.

Remote sensor camera traps provide the first density estimate for the largest natural population of the numbat (Myrmecobius fasciatus)

Context Accurate estimates of population size is fundamentally important for effective conservation management of threatened species. Remote sensor camera traps often capture cryptic species that are difficult to sight or capture. When animals are individually identifiable, camera traps can be used in conjunction with mark–recapture methods to provide a robust estimate of density. This has been effective for medium and large mammals such as felid and quoll species. Less is known about whether this may be an effective approach for smaller species. The numbat (Myrmecobius fasciatus), a small diurnal marsupial once widespread across southern Australia, is now highly restricted. Low densities and crypsis make them challenging to survey, and current population monitoring methods (driving transects and sign surveys) do not provide accurate density estimates. Aims This study aimed to: (1) assess whether numbats can be individually identified using camera trap images; and (2) use spatial and non-spatial capture–recapture methods to investigate whether camera trapping is a viable population monitoring tool for numbats in the largest extant population. Methods We conducted spatial and non-spatial population modelling using images captured incidentally during a large camera-trapping project. Key results We found numbats could be individually identified by stripe patterns from camera images that, in conjunction with capture–recapture modelling, could provide a density estimate. From 6950 trap nights there were 116 numbat detections on 57 of 250 cameras. Of these, 61 detections were used to identify 29 individuals and provide a density estimate of 0.017 ha−1 ± 0.004 (CV = 0.26). This density applied across the estimated extent of distribution suggests a substantially larger numbat population in the Upper Warren, Western Australia (~1900 adults) than previously assumed. Conclusions Camera trapping is a potential method for monitoring the population density of small uniquely marked species, such as the numbat, and for monitoring population trends in response to conservation efforts such as introduced predator control and translocations, as well as management actions such as prescribed burning and timber harvesting. Implications This study contributes to the understanding of situations where camera traps can be utilised to survey small, cryptic species. To provide a more reliable density estimate, and to develop an optimal sampling layout for numbats, further studies would be required.

Attitude and Size Estimation of Satellite Targets Based on ISAR Image Interpretation

The attitude and size of satellite targets are essential information for their activity analysis. This article proposes a novel approach to estimate the absolute attitude and size of satellite targets in the 3-D stable coordinates based on inverse synthetic aperture radar (ISAR) image interpretation. In an ISAR image of a satellite, the satellite&#x2019;s body is chosen as an individual structure segmented from each ISAR image by employing pix2pix generative adversarial network (Pix2pixGAN). By exploring the shape feature of the satellite body with principal component analysis (PCA), the satellite attitude and size are estimated jointly through solving an optimization based on the gradient iteration method. The optimization is established by bridging range-Doppler (RD) images and the target feature parameters (attitude and size) with the accommodation of target trajectory information and the ISAR geometric projection model. In the experiments, the simulation data are generated from real satellite orbital parameters and the computer-aided-design (CAD) models of two satellite targets: TianGong (TG) and KeyHole (KH). Compared with the factorization-based reconstruction method, the proposed method can estimate the attitude and size of the satellite simultaneously and has a higher size estimation accuracy.

ModEst: Accurate estimation of genome size from next generation sequencing data.

Accurate estimates of genome sizes are important parameters for both theoretical and practical biodiversity genomics. Here we present a fast, easy-to-implement and accurate method to estimate genome size from the number of bases sequenced and the mean sequencing depth. To estimate the latter, we take advantage of the fact that an accurate estimation of the Poisson distribution parameter lambda is possible from truncated data, restricted to the part of the sequencing depth distribution representing the true underlying distribution. With simulations we show that reasonable genome size estimates can be gained even from low-coverage (10×), highly discontinuous genome drafts. Comparison of estimates from a wide range of taxa and sequencing strategies with flow cytometry estimates of the same individuals showed a very good fit and suggested that both methods yield comparable, interchangeable results.

Highway Safety Manual Calibration: Estimating the Minimum Required Sample Size

Crash frequency has been identified by many experts as one of the most important safety measures, and the Highway Safety Manual (HSM) encompasses the most commonly accepted predictive models for predicting the crash frequency on specific road segments and intersections. The HSM recommends that the models be calibrated using data from a jurisdiction where the models will be applied. One of the most common start-up issues with the calibration process is how to estimate the required sample size to achieve a specific level of precision, which can be a function of the variance of the calibration factor. The published research has indicated great variance in sample size requirements, and some of the sample size requirements are so large that they may deter state departments of transportation (DOT) from conducting calibration studies. In this study, an equation is derived to estimate the sample size based on the coefficient of variation of the calibration factor and the coefficient of variation of the observed crashes. Using this equation, a framework is proposed for state and local agencies to estimate the required sample size for calibration based on their desired level of precision. Using two recent calibration studies, South Carolina and North Carolina, it is shown that the proposed framework leads to more accurate estimates of sample size compared with current HSM recommendations. Whereas the minimum sample size requirement published in the HSM is based on the summation of the observed crashes, this paper demonstrates that the summation of the observed crashes may result in calibration factors that are less likely to be equally precise and the coefficient of the variation of the observed crashes can be considered instead.

Orthorectification of Skin Nevi Images by Means of 3D Model of the Human Body.

Melanoma is the most lethal form of skin cancer, and develops from mutation of pigment-producing cells. As it becomes malignant, it usually grows in size, changes proportions, and develops an irregular border. We introduce a system for early detection of such changes, which enables whole-body screening, especially useful in patients with atypical mole syndrome. The paper proposes a procedure to build a 3D model of the patient, relate the high-resolution skin images with the model, and orthorectify these images to enable detection of size and shape changes in nevi. The novelty is in the application of image encoding indices and barycentric coordinates of the mesh triangles. The proposed procedure was validated with a set of markers of a specified geometry. The markers were attached to the body of a volunteer and analyzed by the system. The results of quantitative comparison of original and corrected images confirm that the orthorectification allows for more accurate estimation of size and proportions of skin nevi.

Pre-procedural determination of device size in left atrial appendage occlusion using three-dimensional cardiac computed tomography

The complex structure of the left atrial appendage (LAA) brings limitations to the two-dimensional-based LAA occlusion (LAAO) size prediction system using transesophageal echocardiography. The LAA anatomy can be evaluated more precisely using three-dimensional images from cardiac computed tomography (CT); however, there is lack of data regarding which parameter to choose from CT-based images during pre-procedural planning of LAAO. We aimed to assess the accuracy of measurements derived from cardiac CT images for selecting LAAO devices. We retrospectively reviewed 62 patients with Amplatzer Cardiac Plug and Amulet LAAO devices who underwent implantation from 2017 to 2020. The minimal, maximal, average, area-derived, and perimeter-derived diameters of the LAA landing zone were measured using CT-based images. Predicted device sizes using sizing charts were compared with actual successfully implanted device sizes. The mean size of implanted devices was 27.1 ± 3.7 mm. The perimeter-derived diameter predicted device size most accurately (mean error = − 0.8 ± 2.4 mm). All other parameters showed significantly larger error (mean error; minimal diameter = − 4.9 ± 3.3 mm, maximal diameter = 1.0 ± 2.9 mm, average diameter = − 1.6 ± 2.6 mm, area-derived diameter = − 2.0 ± 2.6 mm) than the perimeter-derived diameter (all p for difference < 0.05). The error for other parameters were larger in cases with more eccentrically-shaped landing zones, while the perimeter-derived diameter had minor error regardless of eccentricity. When oversizing was used, all parameters showed significant disagreement. The perimeter-derived diameter on cardiac CT images provided the most accurate estimation of LAAO device size regardless of landing zone eccentricity. Oversizing was unnecessary when using cardiac CT to predict an accurate LAAO size.

Cancer immunotherapy trial design with random delayed treatment effect and cure rate.

Immunotherapies are increasingly used for treating patients with advanced-stage cancers. However, cancer immunotherapy trials often present delayed treatment effects and long-term survivors which result nonproportional hazard models and challenge the immunotherapy trial designs. In this article, we proposed a general random delayed cure rate model for designing cancer immunotherapy trials. A sample size formula is derived for a weighted log-rank test. The accuracy of sample size estimation is assessed and compared with the existing methods via simulation studies. The sensitivities for misspecifying the random delay time are also studied through simulations.

The Estimation of Standard Portion Sizes Using Food Photographic Booklet Among University Students in Turkey

Objective: To examine estimation of standard portion size and, the influence of different food plates on the estimation of food portion size, using photograph booklet in students.&#x0D; Methods: The sample consisted of 300 students, aged 18-35 years old from different academic departments. The student’s general characteristics were asked by using a questionnaire, and anthropometric measurements were taken. Students were asked to select the standard portion sizes of each food from a photographic booklet, which was developed by the researchers. Dietary guidelines for Turkey were used for assessing the quantity of standard portion size of foods of a photographic booklet (1).&#x0D; Results: The findings of the present study indicate that the food group which the most students provided the accurate estimation was protein foods (36.0%), pursued by grains (35.1%), dairy (29.2%), fruits and vegetables group (28.9%). The most and the least accurate estimated foods were found boiled potato (64%) and cheese (3.7%), respectively. The percentages of the accurate estimation of standard portion size for five foods (meatball, meat cubes, shredded chicken, egg, yogurt) in 24 foods were higher in females than men (p

Evaluations of the sum-score-based and item response theory-based tests of group mean differences under various simulation conditions.

The use of patient-reported outcomes measures is gaining popularity in clinical trials for comparing patient groups. Such comparisons typically focus on the differences in group means and are carried out using either a traditional sum-score-based approach or item response theory (IRT)-based approaches. Several simulation studies have evaluated different group mean comparison approaches in the past, but the performance of these approaches remained unknown under certain uninvestigated conditions (e.g. under the impact of differential item functioning (DIF)). By incorporating some of the uninvestigated simulation features, the current study examines Type I error, statistical power, and effect size estimation accuracy associated with group mean comparisons using simple sum scores, IRT model likelihood ratio tests, and IRT expected-a-posteriori scores. Manipulated features include sample size per group, number of items, number of response categories, strength of discrimination parameters, location of thresholds, impact of DIF, and presence of missing data. Results are summarized and visualized using decision trees.

Improving particle detection and size estimation accuracy in digital in-line holography using autoregressive interpolation.

The accuracy of particle detection and size estimation is limited by the physical size of the digital sensor used to record the hologram in a digital in-line holographic imaging system. In this paper, we propose to utilize the autoregressive (AR) interpolation of the hologram to increase pixel density and, effectively, the quality of hologram reconstruction. Simulation studies are conducted to evaluate the influence of AR interpolation of a hologram on the accuracy of detection and size estimation of single and multiple particles of varying sizes. A comparative study on the performance of different interpolation techniques indicates the advantage of the proposed AR hologram interpolation approach. An experimental result is provided to validate the suitability of the proposed algorithm in practical applications.

Virtual scale function of gastrointestinal endoscopy for accurate polyp size estimation in real-time: a preliminary study.

.Significance: Polyp size is important for selecting the surveillance interval or treatment policy. Nevertheless, it is challenging to accurately estimate the polyp size during endoscopy. An easy and cost-effective function to assist in polyp size estimation is required.Aim: To propose a virtual scale function for endoscopy and evaluate its performance and expected accuracy.Approach: An adaptive virtual scale behavior was demonstrated. The measurement error of the virtual scale along the distance between the tip of the endoscope and the object plane was evaluated using graph paper. The accuracy of polyp size estimation by an expert endoscopist was compared with the accuracy of the biopsy forceps method using phantom images.Results: The measurement errors of the virtual scale were when the distance to the graph paper, which faced the tip of the endoscope, varied from 4 to 30 mm. The accuracy with the virtual scale was significantly higher than that obtained with biopsy forceps ( versus , ).Conclusions: The virtual scale function, which operates in real-time without any additional device, can be used to estimate polyp sizes easily and accurately with endoscopy.

Target length estimation based on quadratic statistical CFAR processing

Estimating the radial size of targets using radar high resolution range profile (HRRP) can provide important feature criteria for target classification and recognition. In practice, the bi-directional constant false alarm rate (CFAR) threshold method is often used to discriminate the signal support area and noise area of targets. Under the condition of low signal-to-noise ratio, the size estimation accuracy of existing methods is low, and it is easy to miss detection when the edge signal of target support area is weak. In order to solve the above problems, this paper judges the target-noise boundary by multiple detections with low threshold, and further improves the size estimation accuracy by edge optimization after searching the target-noise boundary. Experimental verification and comparative analysis show that the average estimation error of this method is less than 10%, which is significantly lower than the existing CFAR threshold size estimation method, and can effectively avoid missing detection of edge weaknesses and strong noise interference.

Predicting ecosystem responses by data-driven reciprocal modelling.

Treatment effects are traditionally quantified in controlled experiments. However, experimental control is often achieved at the expense of representativeness. Here, we present a data-driven reciprocal modelling framework to quantify the individual effects of environmental treatments under field conditions. The framework requires a representative survey data set describing the treatment (A or B), its responding target variable and other environmental properties that cause variability of the target within the region or population studied. A machine learning model is trained to predict the target only based on observations in group A. This model is then applied to group B, with predictions restricted to the model's space of applicability. The resulting residuals represent case-specific effect size estimates and thus provide a quantification of treatment effects. This paper illustrates the new concept of such data-driven reciprocal modelling to estimate spatially explicit effects of land-use change on organic carbon stocks in European agricultural soils. For many environmental treatments, the proposed concept can provide accurate effect size estimates that are more representative than could feasibly ever be achieved with controlled experiments.