Smaller Coefficient Of Variation Research Articles

A note on selection of basis quantities for dimensional analysis

Dimensional analysis transforms a dimensionally homogeneous model into its simplest form; the number of input variables can be reduced. Such a reduction is very helpful in statistical design and analysis. Although the Buckingham π theorem provides a method of transforming the model based on the basis quantities (BQ’s), the choice of the BQ’s in general is not unique. In practice, a different choice of the BQ’s may lead to a different performance in statistical analysis. A new criterion, based on the BQ’s with a small coefficient of variation, is proposed to choose the optimal BQ’s. It is anticipated that such a criterion will be popularly used in practice. The distribution of the newly proposed criterion is derived to statistically differentiate the performance via different choices of the BQ’s. Three case studies are provided for illustration.

An information theory model for optimizing quantitative magnetic resonance imaging acquisitions

Acquisition parameter selection is currently performed empirically for many quantitative MRI (qMRI) acquisitions. Tuning parameters for different scan times, tissues, and resolutions requires some amount of trial and error. There is an opportunity to quantitatively optimize these acquisition parameters in order to minimize variability of quantitative maps and post-processing techniques such as synthetic image generation. The objective of this work is to introduce and evaluate a quantitative method for selecting parameters that minimize image variability. An information theory framework was developed for this purpose and applied to a 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) signal model for qMRI. In this framework, mutual information is used to measure the information gained by a measurement as a function of acquisition parameters, quantifying the information content of potential acquisitions and allowing informed parameter selection. The information theory framework was tested on artificial data generated from a representative mathematical phantom, measurements acquired on a qMRI multiparametric imaging standard phantom, and in vivo measurements in a human brain. The phantom measurements showed that higher mutual information calculated by the model correlated with smaller coefficient of variation in the reconstructed parametric maps, and in vivo measurements demonstrated that information-based calibration of acquisition parameters resulted in a decrease in parametric map variability consistent with model predictions.

Hydrological impacts of a wildfire in a Boreal region: The Västmanland fire 2014 (Sweden)

The largest forest wildfire in Swedish modern history burnt 14,000 ha of Boreal forest in the Västmanland County (south-central Sweden) during the summer of 2014. Here, we assess the impacts of this wildfire on the hydrological regime during the three years after it happened. In the empirical experiment carried out, four catchments (two burnt and two non-burnt nearby) with similar character and climate and with mean area of 20 km2 were compared. A total of 23 descriptors accounting for climate, land cover and flow signatures were defined and evaluated before and after the wildfire, using both remote sensing products and in situ streamflow observations. The results show three main changes in the hydrological behaviour of the burnt areas: (i) variation in duration and timing of snow season, with shorter and later beginning of the season; (ii) more dynamic behaviour of the streamflow, with smaller variation coefficient, a reduction in duration of high and low flows conditions and a more oscillating pattern; and, (iii) variations in catchment response (flashiness, runoff coefficient and actual evapotranspiration) from rainfall-events mainly during summer, but also in late autumn The study also reflects the usefulness of the combined analysis of flow signatures and remote sensing products to detect changes in catchment hydrology.

A novel approach to characterize the direct shear pullout behavior of single hooked steel fibers

Fibers crossing sliding crack planes have a positive influence on capacity because they can transfer shear load as dowels. Such behavior was evidenced by several researches that investigated the direct shear performance of Fiber-Reinforced Concrete. However, there is limited literature on the direct shear pullout behavior of single fibers, which certainly provides a deeper understanding of the mechanisms involved in direct shear. Therefore, this paper presents a new approach to perform direct shear pullout (or dowel pullout) of single fibers with a developed portable test apparatus, which enables performing the typical pullout with aligned fiber and load as well. From the comparison between the dowel and aligned pullouts, the energy dissipation capacity and the bond strength of the samples tested under direct shear were found 3.13 and 1.77 times greater than the aligned ones, respectively. The remarkable differences are attributed to the increase in fiber/matrix friction due to the shear load and the continuous occurrence of plastic strains, evidenced by the fiber shape at the end of the dowel pullout. Both mechanisms can be associated with the snubbing effect. Furthermore, the test methodology presented small coefficients of variation (CV) for pullout work and bond strength. For the direct shear pullout, the CVs were 9.57% and 10.42%, respectively, and for the aligned pullout were 16.73% and 18.95%, respectively.

Statistical evaluation of bearing resistance and related strength functions for bolted connections

The paper is concerned with the statistical analysis of strength functions for bolted connections, namely the bearing resistance, the block tearing resistance, the net cross-section resistance and the resistance of angles in tension connected by a single row of bolts in one leg to obtain partial factors. These strength functions are proposed in the second generation of EN 1993-1-8 and EN 1993-1-1. The statistical analysis is performed using 884 test results available in the background documentation to Eurocode 3 and an additional 380 test results of lap connections with different bolt arrangements, which are available in the literature. A suitable sampling criterion of the test results allowed sufficiently large data sets with a small coefficient of variation, which allowed the assumption of partial factor γM2 = 1.25. EN 1993-1-8 provides the design check of the effective net cross-cross section resistance of angles connected by a single row of bolts in one leg (EN 1993-1-8, 3.10.3). It is demonstrated that this design check is superfluous and can be completely replaced by the design block tearing resistance, taking into account the design upper limit of the net cross-section resistance.

Engineered gold nanoparticles as multicolor labels for simultaneous multi-mycotoxin detection on the immunochromatographic test strip nanosensor

Herein, we report a multicolor immunochromatographic test strip (ICTS) nanosensor for the rapid and simultaneous visual detection of fumonisin B1 (FB1), zearalenone (ZEN), ochratoxin A (OTA), and aflatoxin B1 (AFB1). Four colored AuNPs, including gold nanospheres (red), gold nanocacti (purple), gold nanoflowers (blue), and hyperbranched Au plasmonic blackbodies (black), were synthesized and functionalized with the corresponding antibodies to target each analyte. The developed multicolor platform improved bare-eye-based visual detection ability with cut-off values of 120, 60, 2.5, and 5 ng/mL for FB1, ZEN, OTA, and AFB1, respectively. The limits of detection for FB1, ZEN, OTA, and AFB1 were calculated as 3.27, 0.70, 0.10, and 0.06 ng/mL, respectively, and the average recoveries of the four mycotoxins ranged from 82.36% to 116.23% with a small coefficient of variation (below 12.98%). Accuracy, stability, reliability, and practicability were demonstrated by analyzing artificially and naturally contaminated corn samples. In summary, the designed multicolor ICTS nanosensor can serve as an alternative rapid diagnostic platform enabling the sensitive, simultaneous, and on-site screening detection of mycotoxins and other analytes.

PROSPECTS FOR THE USE OF CMS LINES WITH DIFFERENT SOURCES OF STERILITY IN THE SELECTION OF SORGHUM

To improve the genetic-breeding characteristics of maternal forms, to increase their adaptive potential in breeding hybrids of agricultural crops (sorghum, African millet, corn, rice, sunflower, winter rye, etc.), various types of CMS are used. The article presents the results of studying the collection of CMS sorghum lines obtained on the basis of new sources of sterility (A1, A2, A3, A4, A5, A6, 9E and M-35-1A) by agronomic characteristics. On the experimental field of the Institute in 2014-2018. 21 lines were sown in a wide-row way with row spacing of 70 cm and a density of standing of 100 thousand plants per 1 ha. The allocation of plots of 7.7 m2 is randomized, in triplicate. The use of cluster analysis for the minimum of Euclidean distances allowed us to group CMS lines according to similar studied features: the 1st group includes 9; 2nd - 4; 3rd and 4th - 3 each; 5th and 6th - 1 line each. One-way analysis of variance confirms the validity of differences between groups by 18 selection criteria, with the exception of the extension of the panicle leg. A significant variation in vegetative (V = 11.0-21.6%) and generative traits (V = 13.2-28.4%) was found. The smallest coefficient of variation was revealed by the duration of the seedling-flowering interphase period — 4.8%, which indicates the maturity of most lines (in A2 KVV 181, A2 Suzern light, A2 AGS - 46.6 days). A five-year test of the source material made it possible to identify productive lines of the 5th and 6th groups (grain productivity 5.07-5.36, biomass - 18.30-20.70 t / ha); weakly growing lines of the 3rd group (total and productive bushiness 1.12-1.14), low-growing lines of the 1st group (plant height 81.0 cm). A1 Efremovskoye 2 is distinguished by tallness (143.3 cm), large sizes of flag and largest leaves (areas of 150.0 and 254.2 cm2, respectively). The selection of sterile lines with predetermined traits helps to optimize the selection process and their targeted use in crossbreeding programs.

Effect of Different Cooking Methods on Proton Dynamics and Physicochemical Attributes in Spanish Mackerel Assessed by Low-Field NMR.

The states of protons within food items are highly related to their physical attributes. In this study, the effect of cooking methods including boiling, steaming, roasting and frying on proton dynamics, physicochemical parameters and microstructure of Spanish mackerel was assessed by low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) techniques. The treatment of cooking resulted in a significant reduction of proton mobility and declined freedom of protons. The state changes of protons can be monitored easily in an intuitive and non-destructive manner during various cooking process. The treatments of boiling, steaming, roasting and frying resulted in different cooking loss and similar water-holding capability. A significant increase of total carbonyl content and thiobarbituric acid reactive substances was found, while a decrease of the values for free thiols and surface hydrophobicity was observed. The analysis of circular dichroism spectroscopy and cryo-scanning electron microscopy showed significant structural change. The correlation coefficients of Rcal2 and Rcv2 from partial least squares (PLS) regression models were more than 0.980, suggesting good correlation between LF-NMR data and hardness, resilience, springiness, chewiness, gumminess, and adhesiveness. Good recoveries and a relatively small coefficient of variation (CV) were obtained from the PLS regression models, indicating good reliability and accuracy in predicting texture parameters for mackerel samples.

An analysis of dieback areas of Zagros oak forests using remote sensing data case study: Lorestan oak forest, Iran

The main purpose of the present study was to evaluate and analyze the dieback-affected areas of middle Zagros oak forests in Lorestan, Iran. For this purpose, using programming tools, dieback indices, such as DVI, GEMI, IPVI, MSAVI2, NDVI, EVI, OSAVI, Sarvi2, SR, and VHI, were derived from 110 points of oak forests in the underlying area, between 2001 and 2015. Finally, a 23 × 110 matrix (for each year) and a 345 × 110 matrix (for the total period) were developed as a database to detect the dieback areas. Also, we applied cluster analysis to detect the dieback areas and discriminant function analysis was subsequently used to validate the results of cluster analysis. After detecting dieback areas, regression analysis was used for trend analysis of dieback indices, followed with harmonic spectrum analysis for the identification of dominant fluctuations on these indices. The results showed that middle Zagros oak forest could be divided into four zones in terms of dieback incidence, including areas without dieback and small coefficient of variation, areas with moderate dieback and large coefficient of variation, areas with very high dieback rate and large coefficient of variation, and areas with very low dieback rate and small coefficient of variation. According to the results obtained from trend analysis, dieback indices demonstrated a significant downward trend in dieback areas. Also, spectrum analysis revealed that dominant fluctuations on dieback indices of middle Zagros oak forest were mostly short term (2–4 years).

Quality of Element-Level Bridge Inspection Data

Bridge inspection results provide input for several important functions such as maintenance, repair, and rehabilitation, bridge load capacity ratings, truck load routing/permitting, and future safety/condition predictions. As a result, the quality and reliability of inspection data are important for bridge management and to ensure the safety and serviceability of bridges. Element-level data collection has been required nationwide for bridges on the National Highway System since 2014, and therefore is relatively new to some bridge owners. The objective of the research reported here was to assess the quality of element-level bridge inspection data by comparing bridge inspection results between different bridge inspectors assessing the same bridges. This paper reports results from two research studies completed to collect data on the quality (i.e., variability) of element-level inspection data. Results of field trials indicated that there was significant variability in the data for bridge elements reported in the study. Based on these data, the element-level inspection results were widely dispersed—the smallest coefficient of variation calculated from the current studies was 18%, but typical values were found to be greater than 50% in most cases, and often greater than 100%. These data provide examples from a series of field trials that illustrate the need for improving the quality of element-level inspections to ensure the reliability of the data provided.

The efficiency of run rules schemes for the multivariate coefficient of variation in short runs process

In real industries, multivariate process monitoring is crucial as there are many instances that involve at least two quality variables to be monitored simultaneously. The short runs process is commonly seen in production after the industry moved toward flexible manufacturing. Monitoring the coefficient of variation (CV) is useful in a wide variety of scientific areas. In a view of the importance in monitoring the CV and the fact that most real-life data in process monitoring are multivariate in nature, this paper proposes to monitor the multivariate CV in short runs process by means of run rules (RR) control charts. A Markov chain model is established for designing the proposed charts. The statistical performances of the RR multivariate CV (MCV) and Shewhart MCV (SH MCV) charts are compared in terms of the truncated average run length and the expected truncated average run length. The results show that the proposed charts surpass the SH MCV chart for detecting small and moderate multivariate CV shifts. The implementation of the RR MCV chart in the short runs process is illustrated with an example using a real dataset.

Deep Learning Improved Clinical Target Volume Contouring Quality and Efficiency for Postoperative Radiation Therapy in Non-small Cell Lung Cancer.

Purpose: To investigate whether a deep learning-assisted contour (DLAC) could provide greater accuracy, inter-observer consistency, and efficiency compared with a manual contour (MC) of the clinical target volume (CTV) for non-small cell lung cancer (NSCLC) receiving postoperative radiotherapy (PORT).Materials and Methods: A deep dilated residual network was used to achieve the effective automatic contour of the CTV. Eleven junior physicians contoured CTVs on 19 patients by using both MC and DLAC methods independently. Compared with the ground truth, the accuracy of the contour was evaluated by using the Dice coefficient and mean distance to agreement (MDTA). The coefficient of variation (CV) and standard distance deviation (SDD) were rendered to measure the inter-observer variability or consistency. The time consumed for each of the two contouring methods was also compared.Results: A total of 418 CTV sets were generated. DLAC improved contour accuracy when compared with MC and was associated with a larger Dice coefficient (mean ± SD: 0.75 ± 0.06 vs. 0.72 ± 0.07, p < 0.001) and smaller MDTA (mean ± SD: 2.97 ± 0.91 mm vs. 3.07 ± 0.98 mm, p < 0.001). The DLAC was also associated with decreased inter-observer variability, with a smaller CV (mean ± SD: 0.129 ± 0.040 vs. 0.183 ± 0.043, p < 0.001) and SDD (mean ± SD: 0.47 ± 0.22 mm vs. 0.72 ± 0.41 mm, p < 0.001). In addition, a value of 35% of time saving was provided by the DLAC (median: 14.81 min vs. 9.59 min, p < 0.001).Conclusions: Compared with MC, the DLAC is a promising strategy to obtain superior accuracy, consistency, and efficiency for the PORT-CTV in NSCLC.

Gaussian Processes for Hydrocarbon Depth Estimation in Forward Modeling of Seabed Logging

Seabed logging (SBL) is an application of the marine controlled-source electromagnetic (CSEM) technique to discover offshore hydrocarbon reservoirs underneath the seabed. This application is based on electrical resistivity contrast between hydrocarbon and its surroundings. In this paper, simulation and forward modeling were performed to estimate the hydrocarbon depths in one-dimensional (1-D) SBL data. 1-D data, consisted offset distance (input) and magnitude of electric field (output), were acquired from SBL models developed using computer simulation technology (CST) software. The computer simulated outputs were observed at various depths of hydrocarbon reservoir (250 m–2,750 m with an increment of 250 m) with frequency of 0.125 Hz. Gaussian processes (GP) was employed in the forward modeling by utilizing prior information which is electric field (E-field) at all observed inputs to provide E-field profile at unobserved/untried inputs with uncertainty quantification in terms of variance. The concept was extended for two-dimensional (2-D) model. All observations of E-field were then investigated with the 2-D forward GP model. Root mean square error (RMSE) and coefficient of variation (CV) were utilized to compare the acquired and modeled data at random untried hydrocarbon depths at 400 m, 950 m, 1,450 m, 2,100 m and 2,600 m. Small RMSE and CV values have indicated that developed model can fit well the SBL data at untried hydrocarbon depths. The measured variances of the untried inputs revealed that the data points (true values) were very close to the estimated values, which was 0.003 (in average). RMSEs obtained were very small as an average of 0.049, and CVs found as very reliable percentages, an average of 0.914%, which implied well fitting of the GP model. Hence, the 2-D forward GP model is believed to be capable of predicting unobserved hydrocarbon depths.

Influence of Strengthening Material Behavior and Geometry Parameters on Mechanical Behavior of Biaxial Cruciform Specimen for Envelope Material.

The stratospheric airship envelope material is operated in biaxial stress, so it is necessary to study the in-plane biaxial tensile strength. In this paper, a theoretical model is developed to evaluate the mechanical properties of in-plane biaxial specimens. Being applied to the finite element analysis, the theoretical model is employed to evaluate the influence of strengthening material behavior (E*) and geometry parameters on the mechanical behavior in the central. The follows results are drawn: (i) smaller the length of the central region (Lcen), E* and larger the central region corner radius (r) contribute to smaller coefficient of variation (CV); (ii) smaller Lcen and larger E* contribute to smaller stress concentration factor (k), k in the limit state of r is larger than that in other conditions. (iii) The CV and k under stress ratio of 1:1 are smaller than those under other stress ratios. The study can provide a useful reference for the design of biaxial specimens.

Measurement and analysis of choroidal vascularity index and subfoveal choroidal thickness in central serous chorioretinopathy

Objective To observe the choroidal vascularity index (CVI) and the subfoveal choroidal thickness (SFCT) of central serous chorioretinopathy (CSC), and to compare the stability and consistency of the two methods of measurement. Methods A retrospective study. Thirty-one patients with unilateral acute CSC who visited the Department of Ophthalmology of Beijing Friendship Hospital for the first time during the period from Nov 1st, 2016 to Mar 18th, 2018 were included in the study. Thirty-one healthy age-matched subjects were enrolled as controls. All CSC affected eyes and their fellow eyes and healthy eyes were scanned by single-line enhanced depth imaging of OCT through central fovea of macula to measure their SFCT. The image was binarized and then the CVI of a 1500 μm range below fovea was calculated, i.e. the ratio of vascular (or lumen) area to total choroidal area. CVI and SFCT were compared among CSC eyes, fellow eyes and healthy eyes by variance analysis. Intra-group correlation coefficient (ICC), Bland-Altman curve and coefficient of variation (CV) were used to analyze the repeatability, consistency and stability of CVI and SFCT; and Medcalc18.2.1 software was used to draw the Bland-Altman curve and observe the consistency of the two measurement methods. Results There were statistically significant differences in CVI and SFCT between CSC affected eyes and fellow eyes (t=3.470, 2.844; P=0.001, 0.006), CSC affected eyes and healthy eyes (t=6.977, 6.277; P<0.001,<0.001), fellow eyes and healthy eyes (t=3.508, 3.433; P=0.001, 0.001). Relative consistency analysis of CVI and SFCT showed that the ICC of single measurement and average measurement of CVI were 0.967 and 0.983 respectively, and that of single measurement and average measurement of SFCT were 0.937 and 0.967 respectively. The consistency of CVI and of SFCT was very good. The ICC value of CVI was slightly higher than that of SFCT. The results of repeatability analysis of CVI and SFCT showed that the difference between the two CVI measurements was smaller, and the difference between the two SFCT measurements was larger. And CVI and SFCT stability analysis results showed that the CV of CVI and SFCT were 10.5% and 25.3% respectively. CVI has smaller CV than SFCT. Conclusions Compared with healthy eyes, CVI and SFCT are increased in CSC affected eyes and fellow eyes. And compared with SFCT, CVI has better consistency, repeatability and stability. Key words: Central serous chorioretinopathy; Tomography, optical coherence; Choroidal vascularity index; Subfoveal choroidal thickness

Temporal Effects of Groundwater on Physical and Biotic Components of a Karst Stream

Although most lotic ecosystems are groundwater dependent, our knowledge on the relatively long-term ecological effects of groundwater discharge on downstream reaches remains limited. We surveyed four connected reaches of a Chinese karst stream network for 72 consecutive months, with one reach, named Hong Shi Zi (HSZ), evidently affected by groundwater. We tested whether, compared with other reaches, HSZ had (1) milder water temperature and flow regimes, and (2) weaker influences of water temperature and flow on benthic algal biomass represented by chlorophyll a (Chl. a) concentrations. We found that the maximum monthly mean water temperature in HSZ was 0.6 °C lower than of the adjacent upstream reach, and the minimum monthly mean water temperature was 1.0 °C higher than of the adjacent downstream reach. HSZ had the smallest coefficient of variation (CV) for water temperature but the largest CV for discharge. Water temperature and discharge displayed a significant 12-month periodicity in all reaches not directly groundwater influenced. Only water temperature displayed such periodicity in HSZ. Water temperature was an important predictor of temporal variation in Chl. a in all reaches, but its influence was weakest in HSZ. Our findings demonstrate that longer survey data can provide insight into groundwater–surface water interactions.

Rational arrangement of measuring shear wave speed in the liver.

BACKGROUNDShear wave speed has been widely applied to quantify a degree of liver fibrosis. However, there is no standardized procedure, which makes it difficult to utilize the speed universally.AIMTo provide procedural standardization of shear wave speed measurement.METHODSPoint shear wave elastography (pSWE) was measured in 781 patients, and two-dimensional shear wave elastography (2dSWE) was measured on the same day in 18 cases. Regions-of-interest were placed at 12 sites, and the median and robust coefficient-of-variation (CVR) were calculated. A residual sum-of-square (Σdi2) was computed for bootstrap values of 1000 iterations in 18 cases with each assumption of 1 to 12 measurements. The proportion of the Σdi2 (%Σdi2) was calculated as the ratio of Σdi2 to pSWE after converting it based on the correlation between pSWE and 2dSWE.RESULTSThe CVR showed a significantly broader distribution in the left lobe (P < 0.0001), and the smallest CVR in the right anterior segment that covered 95% cases was 40.4%. pSWE was significantly higher in the left lobe than in the right lobe (1.63 ± 0.78 m/s vs 1.61 ± 0.78 m/s, P = 0.0004), and the difference between the lobes became further discrete when the subjects were limited to the cases with a CVR less than 40.4% in any segment (1.76 ± 0.80 m/s vs 1.70 ± 0.82 m/s, P < 0.0001). The highest values of the CVR in every 0.1 m/s interval were plotted in convex upward along pSWE and peaked at 1.93 m/s. pSWE and 2dSWE were significantly correlated (P < 0.0001, r = 0.95). In 216000 resamples from 18 cases, the %Σdi2 of 12 sites was 8.0% and gradually increased as the acquisition sites decreased to reach a significant difference with a %Σdi2 of 7 sites (P = 0.027).CONCLUSIONThese data suggest that shear wave speed should be measured at 8 or more sites of spreading in both lobes.

A Simple Method to Quantify the V˙O2 Mean Response Time of Ramp-Incremental Exercise.

Therefore, we examined the validity and the reproducibility of a novel method to calculate the MRT. On two occasions, 12 healthy men (age, 30 ± 10 yr; V˙O2max: 4.14 ± 0.47 L·min, 53.5 ± 7.3 mL·kg·min) performed a ramp-incremental cycling test (30 W·min) that was preceded by a step transition to 100 W. The ramp power output corresponding to the steady-state V˙O2 at 100 W was determined and the difference between that power output and 100 W was converted to time to quantify the MRT (MRTSS). The values of MRTLIN, τ', and MRTSS were 28 ± 16 s, 27 ± 12 s, and 26 ± 11 s, respectively, which were not different (P > 0.05) from each other. However, compared to the MRT parameters derived from the fitting-based methods, MRTSS had a higher correlation coefficient (R = 0.87) and a smaller coefficient of variation (15% ± 9%) from test-to-test. In conclusion, the novel method proposed in the current study was found to be valid and highly reproducible in a test-retest design. Therefore, we advocate the use of this approach when a precise and accurate determination of the MRT is needed to properly align the V˙O2 data with power output during ramp-incremental exercise.

Intravoxel incoherent motion derived liver perfusion/diffusion readouts can be reliable biomarker for the detection of viral hepatitis B induced liver fibrosis.

Recent two studies reported that intravoxel incoherent motion (IVIM) analysis can separate healthy livers and viral hepatitis B (VHB) induced liver fibrosis. However, in these two studies the starting b value for bi-exponential decay analysis was b =10 and 15 s/mm2 respectively. The current study has two primary aims. The first is to further confirm the diagnostic value of IVIM in detecting liver fibrosis. The second is to test whether by sampling very low b value densely, then b =0 s/mm2 image could be included to improve IVIM's diagnostic performance. This was a prospective study with data acquired at the Third Xiangya Hospital of Central South University, Changsha, China. Healthy volunteers and patients suspected of VHB induced liver fibrosis with liver biopsy performed, as well as hepatocellular carcinoma patients scheduled for surgery, were recruited. All the hepatocellular carcinoma patients had liver fibrosis. After exclusions based on pre-defined criteria for image data quality, for IVIM analysis this study included 20 healthy volunteers; 4 chronic VHB patients with biopsy showing no liver fibrosis; 11 stage-1 liver fibrosis patients, 10 stage-2 liver fibrosis patients, 2 stage-3 liver fibrosis patients, and 5 stage-4 liver fibrosis patients. In the liver fibrosis patients, 1, 19, and 8 cases had inflammation grade-0, grade-1, and grade-2 respectively. The reference IVIM bi-exponential decay curve fitting analysis was segmented fitting performed with b =2 s/mm2 image as the starting point and a threshold-b of 60 s/mm2. This reference fitting method was compared with threshold-b of 40 s/mm2, full fitting, fitting starting from b =0, 5, and 10 s/mm2 respectively. The potential correlation between IVIM readouts and liver function was assessed for the liver fibrosis patients. Based on the smaller coefficient of variation (CoV) for the volunteer group and the smaller patient/volunteer ratios [= (mean measurement for patient groups)/(mean measurement for healthy volunteers)], the comparison of fitting methods favored the reference approach starting from b =2 s/mm2 with a threshold-b of 60 s/mm2. The IVIM measures of four patients without liver fibrosis resembled those of healthy subjects. PF offered the best diagnostic value for separating healthy livers and fibrotic livers, and a threshold of PF =0.1406 separated all fibrotic livers and healthy livers with an exception of one hepatocellular carcinoma patient (fibrosis grade-2/inflammation grade-2). The correlation between fibrosis grading and inflammation grading was weakly positive; while compared with fibrotic livers with inflammation grade-1, fibrotic livers with inflammation grade-2 showed a trend of higher Dfast. A weak correlation is shown with lower PF and lower Dfast associated with lower total protein, lower albumin; higher alanine transaminase, higher aspartate transaminase; higher total bilirubin, and higher direct bilirubin. Segmented-fitting with threshold-b =60 s/mm2 and starting from non-zero very low b value outperforms other methods. IVIM has high sensitivity in detecting liver fibrosis, and PF and Dfast have potential correlation with serum liver function biomarkers. IVIM measures and liver fibrosis grading are not in a linear relationship.

Genotypic difference in the plasticity of root system architecture of field-grown maize in response to plant density

To investigate genotypic differences in the plasticity of root system architecture in response to increasing planting density and understand how this plastic response affects grain yield. A two-year field study was conducted with eight maize hybrids and three planting densities (60,000, 75,000, and 90,000 plants per ha). High-throughput imaging system and an automatic analysis method with Root Estimator for Shovelomics Traits (REST) software were adopted to study root architecture. The coefficient of variation (CV) was determined to reflect the plastic response of the root traits at different planting densities. Root size and root architecture varied with increasing plant density and among the genotypes. With increasing planting density, root biomass and root length per plant decreased. The average root opening angle in inter-row and intra-row directions (RA), average root maximal width in inter-row direction and intra-row directions (RMW), ratio of root opening angle between intra-row and inter-row directions (RatioRA), and ratio of root maximal width between intra-row and inter-row directions (RatioRMW) were also reduced. These results suggest that plants growing under high planting density have narrower root extension width, steeper root angle, and greater root distribution in inter-row direction. The CV of all the root traits between the neighboring plants increased with increasing plant density. Although significant genotype × planting density interactions occurred with most of the root traits, there was a quadratic correlation between grain yield and most of the root traits, especially at high planting density (R2 = 0.17 ~ 0.48). There was a negative linear relationship between grain yield and the CV of root biomass, root length, RA, RMW, RatioRA, and RatioRMW (R2 = 0.21 ~ 0.37). Among the eight hybrids, JQ202 had medium root size, more inter-row root distribution, and the smallest CV in root traits across three planting densities, and the highest grain yield. LY99, SR999 and DY39 had largest CV for root traits and the smallest grain yield. Genotypes with less variation in root size, medium root size, medium broad root system and more inter-row root distribution help to reduce root-to-root competition and tend to have higher yield at high planting density.