Average Coefficient Of Variation Research Articles

New adaptive EWMA CV control chart with application to the sintering process

This research presents a new adaptive exponentially weighted moving average control chart, known as the coefficient of variation (CV) EWMA statistic to study the relative process variability. The production process CV monitoring is a long-term process observation with an unstable mean. Therefore, a new modified adaptive exponentially weighted moving average (AAEWMA) CV monitoring chart using a novel function hereafter referred to as the "AAEWMA CV" monitoring control chart. the novelty of the suggested AAEWMA CV chart statistic is to identify the infrequent process CV changes. A continuous function is suggested to be used to adapt the plotting statistic smoothing constant value as per the process estimated shift size that arises in the CV parametric values. The Monte Carlo simulation method is used to compute the run-length values, which are used to analyze efficiency. The existing AEWMA CV chart is less effective than the proposed AAEWMA CV chart. An industrial data example is used to examine the strength of the proposed AAEWMA CV chart and to clarify the implementation specifics which is provided in the example section. The results strongly recommend the implementation of the proposed AAEWMA CV control chart.

Development of Macrotexture Test Method for Dense-Graded Asphalt Mixtures

The design and construction of pavements necessitate careful consideration of longevity, cost-effectiveness, sustainability, and safety, with a focus on enhancing the durability and lifespan of dense-graded asphalt (DGA) surface mixtures. This paper discusses a research project the Federal Highway Administration (FHWA) initiated to assess the macrotexture characteristics of DGA mixture pavement—particularly concerning safety at higher speeds. The project aims to develop an efficient testing procedure for measuring macrotexture during mixture design and field-testing processes, striking a balance between longevity, cost-effectiveness, sustainability, and safety in pavement design and construction. The study began with a comprehensive review of existing practices, leading to the selection and testing of a unique laser texture scanner capable of noncontact macrotexture measurement. The subsequent phase involved validating the suggested macrotexture measurement system through data collected from State-sponsored projects under the FHWA Mobile Asphalt Technology Center program. Macrotexture measurements were collected from field cores and laboratory-compacted specimens from various State departments of transportation projects and analyzed. Preliminary analysis of the limited dataset to date revealed a positive correlation between average macrotexture measurements from gyratory specimens’ top surface and field core macrotexture measurements. The FHWA developed a draft test method for measuring macrotexture on laboratory specimens and field cores, thereby aiming to reduce procedural variability. Interlaboratory macrotexture test results demonstrated good reproducibility, with an average coefficient of variation of approximately 20%. Overall, this research project seeks to advance the understanding and measurement of macrotexture in DGA mixture pavements and thereby contribute to the development of safe pavements.

Inheritance analysis of major lignan contents in Schisandra chinensis hybrid progeny

Schisandra chinensis (Turcz.) Baill. has been used in traditional Chinese medicine for more than 2000 years and is classified as a superior herb. To examine the inheritance of lignan content traits, we measured the contents of six lignan constituents in the fruit and stem of 142 individuals from the cross ‘Jinwuwei 1’ × ‘Zaohong’ for three successive years. The optimal genetic model for each trait was screened using a mixed major gene + polygene inheritance model. The lignan contents differed in degree of variation, with the annual average coefficient of variation ranging from 22.31% to 79.80% across the three years. Significant transgressive heterosis was observed for schisandrol B content both in the fruit and stem, whereas negative heterosis was detected for γ-schisandrin content both in the fruit and stem. The optimal genetic models were inconsistent among different lignans in the same organ and between different organs for the same lignan, which may be associated with specific gene expression patterns. The additive effects of the lignan contents were mostly positive, whereas the dominance effects were mainly negative. The results of this study provide a theoretical basis for quantitative trait locus mapping and marker-assisted breeding of lignan contents in S. chinensis.

Precocity of fruiting in Pinus yunnanensis revealed by common garden experiment and association analysis with molecular markers

Shortening the growth cycle and maintaining high yields are the goals pursued by all breeders. Under the distinct ecological conditions of tropical and rainy and dry seasons, many plants experience the phenomenon of early flowering and fruiting under adverse conditions. However, there is still no clear conclusion as to whether early flowering and fruiting will affect the vegetative growth of plants. In this study, the vegetative and reproductive growth traits of 270 families of Pinus yunnanensis of 6 years old in common garden were analyzed. There were significant differences in phenotypic traits of different populations, indicating that the trait differences were genetically stable. The variation of vegetative growth traits mainly comes from within populations, and the variation of reproductive growth traits mainly comes among populations. The average coefficient of variation of reproductive growth traits was significantly higher than that of vegetative growth traits. There was a positive correlation between vegetative growth traits and precocity of fruiting. Ecological environment factors have impact on phenotypic variation, among which the temperature of the wettest season has the greatest impact. According to cluster analysis, the nine populations could be divided into three categories. These cluster results were not due to geographic distances, indicating the discontinuity of phenotypic variation. By association analysis, 9 and 3 SSR loci were found to be significantly associated with the trait of precocity of fruiting, respectively. Among them, PK840 locus had the highest interpretation rate for the trait of precocity of fruiting. There were 10 and 7 unique haplotypes in precocity and non-precocity of fruiting individuals, with 179 bp and 183 bp bands, respectively. According to the breeding goal of high productivity and precocity of fruiting, 54 superior families and 200 superior individuals were selected. This study explored the adaptation strategies of tree growth traits to environmental changes.

Abstract PO2-02-02: BREAst Cancer Personalized NuTrition (BREACPNT): dietary intervention in HR+ breast cancer patients treated with endocrine therapy

Abstract BACKGROUND Breast cancer patients treated with adjuvant endocrine therapy commonly experience weight gain, which has been associated with low adherence to therapy and worse breast cancer prognosis. Dietary interventions are the first-line treatment for weight management in breast cancer patients and have beneficial results. Yet, the ability to maintain these outcomes requires further research. Here, we aimed to assess whether a personalized postprandial glucose targeting (PPT) diet is beneficial for weight management and metabolic health as compared with the recommended Mediterranean (MED) diet in this population. DESIGN AND METHODS BREACPNT is a phase-2 randomized trial in HR+ patients with breast cancer, treated with adjuvant endocrine therapy. We randomly assigned participants to follow a MED diet or a PPT diet for a 6-month dietary intervention and additional 6-month follow-up. The PPT diet is based on a machine-learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGRs). During the intervention, participants were monthly followed by a registered dietitian, they were additionally connected to a 2-week continuous glucose monitoring (CGM) on 3-timepoints, provided stool and blood samples and self-reported dietary intake using a smartphone application. RESULTS Among 127 randomized patients (mean ± SD age 53 ± 10 years, BMI 28.6 ± 5 kg/m2), 103 (81%) completed the 6-month intervention period. A total of 94 participants provided 12-month follow-up data. Both interventions led to a significant weight loss. The PPT-diet showed numerically greater weight loss with median change of -1.45kg (IQR -3.75 – 0) compared to the MED-diet with median change of -1kg (IQR -3.2 - 0.1) , however this was not significant (p=0.9). Notably, at the 12-month time point , participants in the PPT arm were more likely to maintain the weight loss (median -1.2kg, IQR -4 - 0.1) compared to participants in the MED-arm (median -0.15kg , IQR -4.25 - 1.5), p=0.14) and had significantly improved waist circumference (median, IQR; -5 cm, -8-(-2) in the PPT arm, compared to -1cm, -6.5-3 in the MED arm, p=0.01). In terms of glucose metabolism the PPT-diet led to improved glycemic control as measured by CGM, with significant lower average postprandial glucose responses (PPGRs) and glucose coefficient of variation (CV) compared to the MED-diet arm (mean 6-month change in PPGR was 2.1 ± 7.5 mg/dL × h for MED and −3.4 ± 5.6 mg/dL × h for PPT, p< 0.001, and the 6-month mean change for CV was 0.15 ± 2.76 for MED and −1.37 ± 3.2 for PPT, p< 0.01). Within the entire cohort, participants who experienced the greatest weight loss (upper quartile) were more likely to be postmenopausal compared to participants in the lower quartile. Additionally, participants who did not achieve weight loss (lower quartile) were significantly more likely to be treated with tamoxifen than AI (p=0.015). CONCLUSIONS In this dietary intervention in HR+ breast cancer patients, both PPT diet and MED diet led to weight loss and improved food quality, with a slight advantage to PPT diet. PPT diet additionally improved glycemic features as compared to MED diet, which are linked to lower risk of obesity and disease recurrence, suggesting an advantage in a glucose targeting approach. Premenopausal and Tamoxifen treated patients were less likely to lose weight through the intervention. These findings may have implications for dietary advice in clinical practice. Citation Format: Michal Rein, Maya Dadiani, Anastasia Godneva, Michal Bakalenik-Gavry, Dana Morzaev-Sulzbach, Maya Lotan-Pompan, Adina Weinberger, Eran Segal, Einav Gal-Yam. BREAst Cancer Personalized NuTrition (BREACPNT): dietary intervention in HR+ breast cancer patients treated with endocrine therapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-02-02.

Measurement method for live chicken shank length based on improved ResNet and fused multi-source information

Phenotypic parameters are crucial reference indicators in poultry breeding. However, the chickens shank length is still manually measured, which is time-consuming and labor-intensive. Additionally, the measurement results are difficult to unify due to the subjective factors of different individuals. To address this issue, this paper proposed a method for live chicken shank length measurement (SLM). It enriches chicken shank feature by fusing visible images and infrared images. The fusion images are then input into a deep regression model based on the improved ResNet. The measurement model used ResNet as its backbone and introduces Squeeze-and-Excitation (SE) blocks and a Spatial Pyramid Pooling (SPP) block, resulting in more precise and stable shank length measurements. The average coefficient of variation, average floating error, average standard deviation and Pearson correlation coefficient for shank length measurements using the fusion images are 0.21 %, 0.49 %, 0.181 mm and 0.996, respectively, compared with using single visible or infrared image, the accuracy and stability are obviously improved. That indicated combining deep learning model and fusion information, the SLM proposed in this paper can achieve a more precise, reliable and standardized measurement of live chicken shank length.

Practical applications of quality assurance and quality control in mineral exploration, resource estimation and mining programmes: a review of recommended international practices

Independent quality assurance and quality control (QA/QC) programmes are required by reporting codes for publicly listed companies and are necessary to optimize data quality at all stages of the sampling, preparation and analytical processes involved in mineral exploration, resource estimation and mining grade control. QA/QC programmes should be adjusted over time to meet changing requirements in data quality at different stages of mineral resource development and exploitation. Certified reference materials are used to monitor accuracy and bias at the project laboratory relative to consensus values for the material from round-robin certification analyses. They are also used to monitor drift over time within an individual laboratory and to identify significant failures in QC at the analytical batch level caused by abrupt changes in concentration related to re-calibration of instruments or procedural changes at the laboratory. Duplicate analyses of sample material are generated at key stages of sampling and preparation to estimate the precision of data generated at each stage. Invariably, the largest source of uncertainty occurs during the initial sampling. Coarse blanks are used to monitor cross-contamination between samples or from sample preparation equipment. Furthermore, each of these QC sample types can be used to discover possible sample mix-ups. Supplementary material: An Excel spreadsheet for the calculation of the average coefficient of variation (CV AVE ) (Appendix C) is available at https://doi.org/10.6084/m9.figshare.c.7070137 Thematic collection: This article is part of the Reviews in Exploration Geochemistry collection available at: https://www.lyellcollection.org/topic/collections/reviews-in-exploration-geochemistry

SCALiR: A Web Application for Automating Absolute Quantification of Mass Spectrometry-Based Metabolomics Data.

Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming an important approach for studying complex biological systems but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process that is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (standard curve application for determining linear ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signals into absolute quantitative data (https://www.lewisresearchgroup.org/software). SCALiR uses an algorithm that automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from the LC-MS signal. Using a standard mix containing 77 metabolites, we show a close correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99 for a y = x curve fitting). Moreover, we demonstrate that SCALiR reproducibly calculates concentrations of midrange standards across ten analytical batches (average coefficient of variation 0.091). SCALiR can be used to calculate metabolite concentrations either using external calibration curves or by using internal standards to correct for matrix effects. This open-source and vendor agnostic software offers users several advantages in that (1) it requires only 10 s of analysis time to compute concentrations of >75 compounds, (2) it facilitates automation of quantitative workflows, and (3) it performs deterministic evaluations of compound quantification limits. SCALiR therefore provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.

Estimating Age and Growth of Largemouth Bass in Southwestern Reservoirs by Using Otoliths and Scales

Abstract Age and growth data are frequently used to monitor and manage important North American sport fishes such as Largemouth Bass Micropterus salmoides. Continental and regional growth standards have been developed for this species to assess fish growth over time and across space. However, Largemouth Bass age and growth data are infrequently collected in Arizona and the reliability of age estimates derived from typical structures (e.g., scales, otoliths) in the Southwest is uncertain. Our objectives were to 1) compare precision and bias of age estimates from scales with those from otoliths and 2) estimate Largemouth Bass growth in several southwestern warmwater reservoirs by using otoliths. We collected Largemouth Bass from three Arizona reservoirs—Alamo, Peña Blanca, and Roosevelt—by boat electrofishing in spring 2021. We removed scales and sagittal otoliths from fish and then prepared and independently aged them three times. We compared differences in precision and bias between scales and otoliths using reader agreement percentages, confidence ratings, average coefficients of variation, and age-bias plots. We used age estimates from Largemouth Bass otoliths to calculate mean lengths-at-age at capture and relative growth indices based on published growth standards in each reservoir. Largemouth Bass scale age estimates were less precise, overestimated ages of younger fish, and underestimated age of older fish compared with those of otoliths. Growth was lower in Peña Blanca Lake than in the other two reservoirs according to mean length-at-age estimates, and relative growth indices suggested that Largemouth Bass growth in all three reservoirs was above average at younger ages, but less so at older ages. The results from this study add to a growing body of literature supporting the use of otoliths for estimating age and growth of Largemouth Bass.

Distribution of daily protein intake and appendicular skeletal muscle mass in healthy free-living Chinese older adults.

Evidence regarding impact of protein intake distribution on skeletal muscle mass in older adults is limited and inconsistent. This study aims to investigate the relationship of evenness of dietary protein distribution and number of meals exceeding a threshold with appendicular skeletal muscle mass (ASM) in healthy and free-living Chinese older adults. Repeated measured data of 5689 adult participants aged ≥ 60 years from the China Health and Nutrition Survey (CHNS) 2015 and 2018 waves were analyzed. Mixed-effects linear regression model was performed to examine the relationship between coefficient of variance (CV) of protein intake across meals, number of meals ≥ 0.4g protein/kg BW and ASM, respectively. Analyses were conducted separately for male and female. The average CV of protein intake in each wave was in the range of 0.34-0.35. More than 40% male and female participants in each wave had no meal reaching 0.4g protein/kg BW. Female participants in the highest quartile of protein intake CV had significantly lower ASM (β = -0.18, 95%CI = -0.32, -0.04) compared with those in the lowest quartile, after adjustment for multiple confounders. Significant negative trends were observed across dietary protein CV quartiles with ASM both in male (P trend = 0.043) and female (P trend = 0.007). Significant positive association between number of meals exceeding 0.4g protein /kg BW and relative ASM were observed in females (2 meals vs. 0 meal: β = 0.003, 95%CI = 0.0007,0.006;≥3 meals vs. 0 meal: β = 0.008, 95%CI = 0.003,0.013), after adjusting for multiple covariates. A more even-distributed protein intake pattern and more meals reaching protein intake threshold were respectively associated with higher appendicular skeletal muscle mass in healthy and free-living older Chinese adults. Prospective studies and intervention trials are needed to confirm these cross-sectional findings.

Quantitation of propofol metabolites by LC–MS/MS demonstrating long detection window for urine drug monitoring

IntroductionChromatographic methods for analysis of propofol and its metabolites have been widely used in pharmacokinetic studies of propofol distribution, metabolism, and clearance. Application of chromatographic methods is also needed in clinical and forensic laboratories for detecting and monitoring propofol misuse. ObjectiveWe report a method for sensitive analysis of propofol, propofol 1-glucuronide (PG), 4-hydroxypropofol 1-glucuronide (1-QG), 4-hydroxypropofol 4-glucuronide (4-QG) and 4-hydroxypropofol 4-sulfate (4-QS) in urine by LC–MS/MS analysis. The method employs a simple dilute-and-analyze sample preparation with stable isotope internal standardization. ResultsValidation studies demonstrate a linear calibration model (100–10,000 ng/mL), with dilution integrity verified for the extended range of concentrations experienced in propofol use. Criteria-based validation was achieved, including an average coefficient of variation of 6.5 % and a percent bias of −4.2 ng/mL. The method was evaluated in 12 surgical patients, with monitoring periods lasting up to 30 days following intravenous propofol administrations of 100–3000 mg on the day of surgery. While the concentration ratio of PG to 4-hydroxy propofol metabolite decreased significantly in the days following surgery, PG maintained the highest concentration in all specimens. Both PG and 1-QG were detectable throughout the monitoring periods, including in a patient monitored for 30 days. Lower concentrations were determined for 4-QG and 4-QS, with evidence of detection up to 20 days. Propofol was not detectable in any urine specimens, thereby proving ineffective for identifying drug use. ConclusionThe validated method for quantifying propofol metabolites demonstrates its applicability for the sensitive detection of propofol misuse over a long window of drug-use detection.

A simulation study of extrapolation uncertainty in exposure assessment – Use of pilot study results for site investigation

Accurate characterization of soil contaminant concentrations is often crucial for assessing risks to human and ecological health. However, fine-scale assessments of large tracts of land can be cost prohibitive due to the number of samples needed. One solution to this problem is to extrapolate sampling results from one area to another unsampled area. In the absence of a validated extrapolation methodology, regulatory agencies have employed policy-based techniques for large sites, but the likelihood of decision errors resulting from these extrapolations is largely unexplored. This study describes the results of a simulation study aimed at guiding environmental sampling for sites where extrapolation concepts are of interest. The objective of this study is to provide practical recommendations to regulatory agencies for extrapolating sampling results on large tracts of land while minimizing errors that are detrimental to human health. A variety of site investigation scenarios representative of environmental conditions and sampling schemes were tested using adaptive sampling when collecting discrete samples or applying incremental sampling methodology (ISM). These simulations address extrapolation uncertainty in cases where a Pilot Study might result in either false noncompliance or false compliance conclusions. A wide range of plausible scenarios were used that reflect the variety of heterogeneity seen at large sites. This simulation study demonstrates that ISM can be reliably applied in a Pilot Study for purposes of extrapolating the outcome to a large area site because it decreases the likelihood of false non-compliance errors while also providing reliable estimates of true compliance across unsampled areas. The results demonstrate how errors depend on the magnitude of the 95% upper confidence limit for the mean concentration (95UCL) relative to the applicable action level, and that error rates are highest when the 95UCL is within 10%–40% of the action level. The false compliance rate can be reduced to less than 5% when 30% or more of the site is characterized with ISM. False compliance error rates using ISM are insensitive to the fraction of the decision units (DUs) that are characterized with three replicates (with a minimum of 10 percent), so long as 95UCLs are calculated for the DUs with one replicate using the average coefficient of variation from the three replicate DUs.

Abstract 3090: Development and performance of the National Cancer Institute’s HTS384 NCI60 screen: A modernized platform to support drug discovery and development by the worldwide cancer research community

Abstract The NCI60 screen was established in the 1980s and introduced in the 1990s as a screening service for the worldwide cancer research community. The screen features 60 human tumor cell lines that represent 9 cancer types including non-small cell lung, colon, central nervous system, ovarian, renal, prostate and breast, as well as leukemia and melanoma. On a weekly basis, synthetic molecules, natural products, and biologics are screened against the 60-cell line panel to evaluate their anticancer potential. On average, more than 13,000 compounds are screened annually for investigators throughout the world. Cell growth and cytotoxicity were assessed by the sulforhodamine B (SRB) assay, performed in a 96-well format, that measures cellular protein content with an absorbance readout and enabled unprecedented throughput in the 1980s. Although the SRB assay supported a robust screening platform for three decades, its sensitivity and throughput are limited. Recently the NCI’s DCTD introduced the HTS384 NCI60 as a modernized screening platform. While the same 60 cell lines are evaluated, the HTS384 NCI60 is fully automated and performed in a 384-well format to enable a higher throughput. Additionally, the 48-h test agent exposure period of the SRB assay was increased to 72 h, which may result in lower 50% growth inhibition values (GI50) for some agents. A highly sensitive CellTiter-Glo luminescence readout for cell viability, based on cellular ATP content, was selected to enable comparisons of the NCI60 monolayer data to 3D cell culture models where the same assay chemistry can be applied. The HTS384 NCI60 was evaluated by screening a library of 1,003 U.S. Food and Drug Administration-approved and investigational oncology agents at five concentrations. Assay performance of the 60 cell lines was assessed from the controls of 30 - 60 microplates per cell line. The average doubling time of the 60 cell lines during the 72-h exposure period ranged between 19 h for NCI-H460 (17 - 23 h, n = 57) to 117 h for MDA-MB-468 (43 - 272 h, n = 60). The average signal-to-background ratio of all 60 cell lines was 89 (3,413 microplates) and ranged from 6 for OVCAR-5 (3 - 13, n = 54) to 229 for SF-539 (141 - 566, n = 60). The average coefficient of variation for microplate vehicle controls (n = 14) of all 60 cell lines (n = 3,413) was 5.2% and ranged from 3.2% for SK-MEL-28 (1.4 - 7.7%, n = 60) to 11.1% for HL-60(TB) (5.2 - 20.2%, n = 59). The average Z’-factor value of all 60 cell lines (n = 3,413) was 0.82 and ranged between 0.66 for HL-60(TB) (0.39 - 0.84, n = 59) to 0.89 for MALME-3M (0.79 - 0.95, n = 59), SF-295 (0.49 - 0.97, n = 59), SK-MEL-28 (0.74 - 0.95, n = 60), and UO-31 (0.8 - 0.94, n = 54). The development and performance of the HTS384 NCI60 screen will be described. This project was funded in part with federal funds from the NCI, NIH, under contract no. HHSN261201500003I. Citation Format: Nathan P. Coussens, Thomas S. Dexheimer, Eric M. Jones, Thomas Silvers, John R. Britt, Ronald C. Taylor, Mark W. Kunkel, James H. Doroshow, Beverly A. Teicher. Development and performance of the National Cancer Institute’s HTS384 NCI60 screen: A modernized platform to support drug discovery and development by the worldwide cancer research community [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3090.

Spatial-temporal Evolution and Driving Factors Analysis of Ecological Environment Quality in Daihai Basin based on AWRSEI

Watersheds are an important ecological security barrier and social and economic development area. In order to evaluate the ecological environment quality of arid and semi-arid watersheds more objectively and accurately, based on the remote sensing ecological index (RSEI), the salinity index was introduced to construct a remote sensing ecological index (AWRSEI) suitable for arid and semi-arid watersheds, and the Daihai watershed was taken as an example to analyze its applicability. Based on the AWRSEI model, four phases of Landsat TM/OLI composite images were used to quantitatively evaluate the ecological and environmental quality of the Daihai Basin from 2001 to 2020. The spatio-temporal evolution of the ecological and environmental quality of the Daihai Basin was analyzed using the coefficient of variation and spatial autocorrelation, and the cause analysis and driving factor explanation power analysis were carried out using geographic detectors. The results showed that:① the average correlation coefficient between AWRSEI and various ecological factors was 0.860, which was more representative than that of a single index component. The load positive and negative values and ranking of the first principal component were consistent with those of RSEI, the contribution rate of eigenvalues was 3.69% higher than those of RSEI, and the evaluation results were closer to the real surface conditions, which is suitable for the ecological environment quality assessment of arid watersheds. ② The annual average of the AWRSEI index in the Daihai Basin from 2001 to 2020 was 0.427, which indicated a poor ecological environment quality basis. During the study period, the average of AWRSEI showed a fluctuating trend and reached the highest value of 0.502 in 2020. The overall ecological environment quality improved significantly, the deterioration area decreased by 20.51%, and the improvement area increased by 12.71%. In terms of spatial distribution, the ecological environment quality of forest land in the southern and northwestern high-altitude areas of the Daihai Basin was good, whereas that in the northern and southern mid-altitude areas was poor, and that in the northern area was better than that in the southern area. ③ The average variation coefficient of AWRSEI in the Daihai Basin was 0.280, the ecological environment quality was stable, and the overall change fluctuation was small; the high fluctuation was mainly concentrated in the southern part of the lake and the residential area. There was a significant spatial autocorrelation in the ecological environment quality of the Daihai Basin, and the high-high agglomeration area was mainly distributed in the forest area at high altitude and the cultivated land area at low altitude. Low-low concentration areas were scattered in the middle altitude area. ④ The improvement of the ecological environment in Daihai Basin from 2001 to 2020 was mainly due to the increase in NDVI and the decrease in NDBSI and NDSI. NDVI and NDBSI were the combination with the strongest interaction and the strongest interpretation of the ecological environment. Land use was the dominant factor of AWRSEI and had the strongest explanatory power. The combination of land use and meteorological factors was the strongest interaction, and the relationship between each driving factor was enhanced.

Operating minimally intelligent agent-based manufacturing systems across the Average demand Interval – coefficient of variation (ADI-CV) demand state space

ABSTRACT Minimally Intelligent Agent-Based Manufacturing concerns the provision of agents with the minimal intelligence required to autonomously negotiate and broker work across machines and jobs. The minimal intelligence of agents can be updated in real-time and when coupled with technologies, such as Additive Manufacturing (AM), robotics, automated inventory, and Computer Numerical Control (CNC) affords highly flexible, re-configurable, resilient and responsive systems. The concept has become topical as changes to global supply chains are necessitating a shift to responsive and resilient on-demand manufacturing. However, understanding and characterising how these systems operate under various demand profiles is required to support operators operating these future systems. This paper reports a numerical study into the operating behaviour of minimally intelligent agent-based manufacturing systems operating across the Average Demand Interval and Coefficient of Variation (ADI-CV) demand state space. An established state space used in spare part supply chain research. The results show minimally intelligent manufacturing systems are stable across much of the ADI-CV demand space 85%, 63% and 76–84% for constant, triangular and lognormal manufacturing time distribution profiles respectively. The stability is largely independent of the combination of intelligence. Rather, the combination of intelligence impacts job Time-in-System and system response.

Performance Evaluation of L1-Norm-Based Blind Deconvolution after Noise Reduction with Non-Subsampled Contourlet Transform in Light Microscopy Images

Noise and blurring in light microscope images are representative factors that affect accurate identification of cellular and subcellular structures in biological research. In this study, a method for l1-norm-based blind deconvolution after noise reduction with non-subsampled contourlet transform (NSCT) was designed and applied to a light microscope image to analyze its feasibility. The designed NSCT-based algorithm first separated the low- and high-frequency components. Then, the restored microscope image and the deblurred and denoised images were compared and evaluated. In both the simulations and experiments, the average coefficient of variation (COV) value in the image using the proposed NSCT-based algorithm showed similar values compared to the denoised image; moreover, it significantly improved the results compared with that of the degraded image. In particular, we confirmed that the restored image in the experiment improved the COV by approximately 2.52 times compared with the deblurred image, and the NSCT-based proposed algorithm showed the best performance in both the peak signal-to-noise ratio and edge preservation index in the simulation. In conclusion, the proposed algorithm was successfully modeled, and the applicability of the proposed method in light microscope images was proved based on various quantitative evaluation indices.

ALIKE-APPLE: A Lightweight Method for the Detection and Description of Minute and Similar Feature Points in Apples

Current image feature extraction methods fail to adapt to the fine features of apple image texture, resulting in image matching errors and degraded image processing accuracy. A multi-view orthogonal image acquisition system was constructed with apples as the research object. The system consists of four industrial cameras placed around the apple at different angles and one camera placed on top. Following the image acquisition through the system, synthetic image pairs—both before and after transformation—were generated as the input dataset. This generation process involved each image being subjected to random transformations. Through learning to extract more distinctive and descriptive features, the deep learning-based keypoint detection method surpasses traditional techniques by broadening the application range and enhancing detection accuracy. Therefore, a lightweight network called ALIKE-APPLE was proposed for surface feature point detection. The baseline model for ALIKE-APPLE is ALIKE, upon which improvements have been made to the image feature encoder and feature aggregation modules. It comprises an Improved Convolutional Attention Module (ICBAM) and a Boosting Resolution Sampling Module (BRSM). The proposed ICBAM replaced max pooling in the original image feature encoder for downsampling. It enhanced the feature fusion capability of the model by utilizing spatial contextual information and learning region associations in the image. The proposed BRSM replaced the bilinear interpolation in the original feature aggregator for upsampling, overcoming the apple side image’s geometric distortion and effectively preserving the texture details and edge information. The model size was shrunk by optimizing the number of downsampling operations from the image encoder of the original model. The experimental results showed that the average number of observed keypoints and the average matching accuracy were improved by 166.41% and 37.07%, respectively, compared with the baseline model. The feature detection model of ALIKE-APPLE was found to perform better than the optimal SuperPoint. The feature point distribution of ALIKE-APPLE showed an improvement of 10.29% in average standard deviation (Std), 8.62% in average coefficient of variation (CV), and 156.12% in average feature point density (AFPD). Moreover, the mean matching accuracy (MMA) of ALIKE-APPLE improved by 125.97%. Thus, ALIKE-APPLE boasts a more consistent allocation of feature points and greater precision in matching.

Method to derive the infrared complex refractive indices n(λ) and k(λ) for organic solids from KBr pellet absorption measurements.

Obtaining the complex refractive index vectors n(ν~) and k(ν~) allows calculation of the (infrared) reflectance spectrum that is obtained from a solid in any of its many morphological forms. We report an adaptation to the KBr pellet technique using two gravimetric dilutions to derive quantitative n(ν~)/k(ν~) for dozens of powders with greater repeatability. The optical constants of bisphenol A and sucrose are compared to those derived by other methods, particularly for powdered materials. The variability of the k values for bisphenol A was examined by 10 individual measurements, showing an average coefficient of variation for k peak heights of 5.6%. Though no established standards exist, the pellet-derived k peak values of bisphenol A differ by 11% and 31% from their single-angle- and ellipsometry-derived values, respectively. These values provide an initial estimate of the precision and accuracy of complex refractive indices that can be derived using this method. Limitations and advantages of the method are discussed, the salient advantage being a more rapid method to derive n/k for those species that do not readily form crystals or specular pellets.

The Effect of Three Factors Interaction on the Size Distribution of White Sugar Crystals in the Batch Vacuum Pan

Crystal size disribution is a parameter used to indicate the quality of sugar crystals obtained from the crystallization process. The better the crystal size distribution, the better the quality of the sugar crystals produced. The good quality of sugar crystals has an impact on the easier separation process that will occur in the centrifugal machine and can reduce sugar loss both in the centrifugal machine and in the sugar grader. The purpose of this study is to determine the effect of the number of sugar seeds, the quality of the mother liquor and the length of time used in the crystallization process on the quality of white sugar crystals produced in the Batch Vacuum Pan and to obtain the best interaction from several levels used for each factor, which can be used as a reference for producing sugar products that have crystal size distribution values according to the desired standard. Each treatment was carried out twice. Observations were made on material characteristics (brix, pol, and purity) and product sugar characteristics (average crystal size and coefficient of variation of crystal size). Measurement of the characteristics of sugar using a sieving (granulometer) which is then calculated using the ICUMSA GS2-37 method. The influence of factor’s main effect and interaction were analyzed using analysis of variance at the level of p value ≤ 0.05. Further tests for each factor’s main effect and interaction with p values ≤ 0.05 were carried out using the Duncan Multiple Range Test (DMRT). The best distribution of sugar crystal size was obtained from the interaction of sugar seed factors with levels of 3 m3, 5 m3, or 10 m3 which interacted with the quality factor of mother liquor (fine liquor + 0 m3 molasses), and 2 hours of cooking time, Where the results of the interaction of this factor produce a percentage of sugar with a size larger than 0.8 mm as much as 80%.

Evaluation of corneal endothelial cell morphology off and on treatment by specular microscopy in children and adolescents with attention deficit hyperactivity disorder

Purpose To determine the structure and properties of corneal endothelial cells in children and adolescents with ADHD who received methylphenidate treatment at least six months. Method The prospective, observational study included 33 eyes of 33 patients diagnosed with ADHD who received methylphenidate treatment for at least six months, 33 eyes of 33 patients newly diagnosed with ADHD who did not start medication treatment, and 33 eyes of 33 healthy individuals. Average cell density, coefficient of variation, maximum cell area, normal cell area, minimum cell area, average cell area, and hexagonality ratio values were evaluated by non-contact specular microscopy. The parameters recorded in all three groups were compared. Results The average age of children in the ADHD + MPH, ADHD, and control groups is 9 ± 1.7, 8.9 ± 2.3, and 8.9 ± 1.8 years, respectively. (p > 0.05) The average MPH treatment dose is 0.94 ± 0.19 mg/kg, the average daily MPH intake is 34.12 ± 14.04 mg, and the average duration of use of MPH is 24.03 ± 12.46 months. Central corneal thickness (CCT) was measured as an average of 540.45 ± 31.23 in the ADHD + MPH group, 540.61 ± 29.69 in the ADHD group, and 546.58 ± 27.72 in the control group. (p = 0.499) The average coefficient of variation (CV) values were measured as 25.48 ± 4.22 in the ADHD + MPH group, 26.12 ± 3.48 in the ADHD group, and 26.12 ± 3.64 in the control group. (p = 0.491) The average hexagonality ratio (%) (HEX) values were measured as 69.45 ± 8.41 in the ADHD + MPH group, 68.21 ± 6.82 in the ADHD group, and 68.91 ± 7.97 in the control group. (p = 0.892) No statistically significant difference was observed between all three groups in terms of all parameters. Conclusion Methylphenidate treatment administered for at least six months with a diagnosis of ADHD did not have a toxic effect on the corneal endothelium.