Variance In Weight Research Articles

Local optimized Stokes polarimetry for specific polarization states.

In this Letter, we propose a locally optimized Stokes polarimetry. Focusing on the effect on polarization measurements by Poisson noise, the studies establish a new, to the best of our knowledge, optimization function combining the equally weighted variance with the condition number. This method considers both the stability and the precision of polarization measurements; by trading an increase in the condition number by 2.48%, we realize a decrease in equal-weighted variance by 19.1% near the north pole. The advantages of this local optimization method are demonstrated based on Monte Carlo (MC) simulations and experiments of continuous polarization state modulation. Finally, an imaging demonstration using a 4 µm pathological section implies the potential of this new local optimization method in improving polarization measurements and applying it to more biomedical research.

Chromosome-scale assembly and quantitative trait locus mapping for major economic traits of the Culter alburnus genome using Illumina and PacBio sequencing with Hi-C mapping information.

Topmouth culter (Culter alburnus) is an economically important freshwater fish with high nutritional value. However, its potential genetic advantages have not been fully exploited. Therefore, we aimed to determine the genome sequence of C. alburnus and examine quantitative trait loci (QTLs) related to major economic traits. The results showed that 24 pseudochromosomes were anchored by 914.74Mb of the C. alburnus genome sequence. De novo sequencing identified 31,279 protein-coding genes with an average length of 8507 bp and average coding sequ ence of 1115bp. In addition, a high-density genetic linkage map consisting of 24 linkage groups was constructed based on 353,532 high-quality single nucleotide polymorphisms and 4,710 bin markers. A total of 28 QTLs corresponding to 11 genes, 26 QTLs corresponding to 11 genes, and 12 QTLs corresponding to 5 genes were identified for sex, intermuscular spine number and body weight traits, respectively. In this study, we assembled an accurate and nearly complete genome of C. alburnus by combining Illumina, PacBio, and high-throughput Chromosome conformation capture (Hi-C) technologies. In addition, we identified QTLs that explained variances in intermuscular spine number, body weight, and sex differences in C. alburnus. These genetic markers or candidate genes associated with growth traits provide a basis for marker-assisted selection in C. alburnus.

Psychometric Properties and Measurement Invariance of The Fear of Missing Out Scale (FoMOs) In Chilean University Students

Introduction: social networks can harm university students' mental health; therefore, it is urgent to have valid instruments to measure new phenomena such as FoMO. Objective: this study aimed to examine the psychometric properties of the Fear of Missing Out Scale (FoMOs) in a sample of Chilean university students. Methods: confirmatory factor analyses (CFA) were carried out and estimated using the Weighted Leasts Square Means and Variance (WLSMV). Results: the FoMOs evaluation had an internal consistency of 0.863 (Cronbach's Alpha). The confirmatory factor analysis (CFA) showed two factors and good indicators: CFI = 0,991, TLI = 0,987, and an RMSEA of 0,054. Conclusion: the FoMOs is a good instrument for measuring the fear of missing out in the Chilean University population

Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection.

Short-term, intense artificial selection drives fast phenotypic changes in domestic animals and leaves imprints on their genomes. However, the genetic basis of this selection response is poorly understood. To better address this, we employed the Pekin duck Z2 pure line, in which the breast muscle weight was increased nearly 3-fold after 10 generations of breeding. We denovo assembled a high-quality reference genome of a female Pekin duck of this line (GCA_003850225.1) and identified 8.60 million genetic variants in 119 individuals among 10 generations of the breeding population. We identified 53 selected regions between the first and tenth generations, and 93.8% of the identified variations were enriched in regulatory and noncoding regions. Integrating the selection signatures and genome-wide association approach, we found that 2 regions covering 0.36 Mb containing UTP25 and FBRSL1 were most likely to contribute to breast muscle weight improvement. The major allele frequencies of these 2 loci increased gradually with each generation following the same trend. Additionally, we found that a copy number variation region containing the entire EXOC4 gene could explain 1.9% of the variance in breast muscle weight, indicating that the nervous system may play a role in economic trait improvement. Our study not only provides insights into genomic dynamics under intense artificial selection but also provides resources for genomics-enabled improvements in duck breeding.

Selected Lifestyle Practices in Urban African American Women—Relationships to Pregnancy Outcome, Dietary Intakes and Anthropometric Measurements

The relationships of selected lifestyle factors (cigarette smoking, consumption of alcoholic beverages, recreational drug use, and exercise during pregnancy), all self-reported, to pregnancy outcomes, dietary intake during pregnancy, and maternal anthropometric measurements, were investigated in a group of urban African American pregnant women. The 234 subjects were aged 16-35 years and were free of diabetes and abnormal hemoglobins. The lifestyle data were collected by trained interviewers during the subjects' prenatal clinic visits, and the dietary data by monthly, quantitative 24-hour food recalls conducted during these same visits. Maternal anthropometric measurements were obtained from the subjects' hospital records, and pregnancy outcome data during physical examinations of the newborn infants. Both cigarette smoking and drug use were associated with significantly lower mean birth weight, length, and head circumference, while exercise was associated with a significantly higher mean birth weight, and head circumference (P < 0.05). Drug use during pregnancy was associated with a significantly higher intake of vitamin C, and a significantly lower intake of iron; while women reporting drug use before pregnancy had significantly higher mean intakes of food energy, protein, total and saturated fat, and zinc. Prepregnancy weight, percent ideal prepregnancy body weight, prepregnancy body mass index, and delivery weight were significantly lower among those reporting drug use before pregnancy. Multiple regression analyses indicated that smoking explained a relatively small proportion of the variance in infant birth weight compared with delivery weight and percent of ideal prepregnancy body weight.

A calculation method for GNSS positioning precision based on the posteriori unit weight variance

Abstract The precision index is the primary basis for judging the GNSS positioning result, and the positioning mean error is usually used as the precision index in practical applications. In order to solve the problem of mismatch between positioning deviation and mean error in the priori situation, this paper proposed a positioning precision calculation method based on the posteriori unit weight variance and deduced the formulas combining sequential adjustment or Kalman filter, respectively. This method uses the characteristic that there are system errors in error corrections to calculate and screen the posterior unit weight variance. This method introduces the system error’s influence into the mean error, which can improve positioning precision. The application of static difference and RTK proved that this method has remarkable effects, which can significantly alleviate the problem of false high precision and improve the reliability of positioning mean errors.

Adaptive Two-Stage Monte Carlo Algorithm for Accuracy Estimation of Total Least Squares

The existing theory of the total least squares (TLS) accuracy estimation contains the following problems: (1) the approximation function method based on the Taylor series expansion cannot avoid the derivative operation; (2) the selection of the number of simulations for the Monte Carlo method is subjective; and (3) the adaptive Monte Carlo algorithm is complex. Aiming at these problems, we introduce the adaptive two-stage Monte Carlo (ATMC) algorithm into the theory of accuracy estimation of the TLS. In order to consider the biases of estimation for parameters, residuals, and the estimation of the variance of unit weight, the computing process for accuracy estimation of the TLS contains bias estimation and accuracy estimation, and the algorithm is provided. In addition, based on the quasi-Monte Carlo method, an adaptive two-stage quasi-Monte Carlo (ATQMC) algorithm is proposed for the calculation of the expected bias in parameter estimates, and the algorithm flow is given. The experimental results verified the effectiveness of the ATMC and ATQMC algorithms. Compared with the ATMC algorithm, the ATQMC algorithm proposed in this paper is more efficient in the calculation of the expected bias in parameter estimates.

Identifying Process Deterioration in Weighted Exponentially Distributed Time Between Events

In observational studies, the probability of selection of sampling units is not always equal. The recorded observations are biased in this scenario. The unweighted distributions in such situations are not useful until the inclusion probability of each item is same. The theory of weighted distributions offers a unifying approach for these types of conditions because it considers the adjustment bias. Failure to comply with such adjustment may lead to inappropriate results. In this article, an efficient mentoring scheme (Weighted-TBE chart) for time between events (TBE) using weighted exponential distribution has been proposed based on weighted variance (WV) method. A comparison has been established between CC based on weighted and unweighted probability distributions. The performance measure ARL has been calculated using Monte Carlo simulations. The Weighted-TBE chart has provided least values of ARL in the presence of unwanted process variations and proved to be more effective than the existing scheme. Further the proposed control chart has been applied to time between failures data to show its practical applicability.

A polygenic basis for birth weight in a wild population of red deer (Cervus elaphus).

The genetic architecture of traits under selection has important consequences for the response to selection and potentially for population viability. Early QTL mapping studies in wild populations have reported loci with large effect on trait variation. However, these results are contradicted by more recent genome-wide association analyses, which strongly support the idea that most quantitative traits have a polygenic basis. This study aims to re-evaluate the genetic architecture of a key morphological trait, birth weight, in a wild population of red deer (Cervus elaphus), using genomic approaches. A previous study using 93 microsatellite and allozyme markers and linkage mapping on a kindred of 364 deer detected a pronounced QTL on chromosome 21 explaining 29% of the variance in birth weight, suggesting that this trait is partly controlled by genes with large effects. Here, we used data for more than 2,300 calves genotyped at >39,000 SNP markers and two approaches to characterise the genetic architecture of birth weight. First, we performed a genome-wide association (GWA) analysis, using a genomic relatedness matrix to account for population structure. We found no SNPs significantly associated with birth weight. Second, we used genomic prediction to estimate the proportion of variance explained by each SNP and chromosome. This analysis confirmed that most genetic variance in birth weight was explained by loci with very small effect sizes. Third, we found that the proportion of variance explained by each chromosome was slightly positively correlated with its size. These three findings highlight a highly polygenic architecture for birth weight, which contradicts the previous QTL study. These results are probably explained by the differences in how associations are modelled between QTL mapping and GWA. Our study suggests that models of polygenic adaptation are the most appropriate to study the evolutionary trajectory of this trait.

Analyses of growth performance and realized heritability of the second generation of Indo-Pacific Pampus argenteus.

Silver pomfret (Pampus argenteus) is one of the most important fishery products in the Indo-Pacific Ocean. Nonetheless, little is known about the genetic parameters of economic traits. To determine whether the selective breeding programme would improve economic traits, the authors evaluated the growth performance of the selected group and the control group at 60, 90 and 120 days, and the growth performance parameters of the selected group were higher than those of the control group. Through Pearson correlation analysis, the authors found that the morphological traits that are highly related to the weight of P. argenteus are body length and body height. Genetic gain and realized heritability for body weight were highest at day 90, which were 12.72% and 0.23%, respectively. Therefore, the authors speculate that day 90 may be a critical time for screening. The average coefficient of variation for body weight reached over 30%. All three morphological traits reached moderate realized heritability at day 90 after hatching. These implied that selective breeding has the potential to improve the growth traits of P. argenteus. In addition, the reproductive performance of P. argenteus parent fish was obviously improved after gonadal strengthening. These results provide important information for future breeding programmes for P. argenteus.

Differential sensitivity of climate conditions on birth weight genetic values in mice divergently selected for birth weight residual variance.

After 32 generations of a divergent selection experiment for residual variance of birth weight in mice, two divergent lines were thus obtained: the heterogeneous line (H-line) and the homogeneous line (L-line). Throughout the generations, differences were observed between the two lines in traits such as litter size, survival at weaning and birth weight variability caused by unidentified environmental conditions. The L-line exhibited advantages in terms of higher survival rates, larger litter sizes, and less sensitivity to changes in food intake. The study is an examination of the effects of climate as an environmental factor on the performance of these animals. Climate factors including maximum, minimum, and mean temperature (T), humidity (H), and TH index; at three stages (the fecundation, a week before the parturition and the parturition), were linked to a birth weight dataset consisting of 22,614 records distributed as follows: 8,853 corresponding to the H-line, 12,649 to the L-line and 1,112 to the initial population. Out of the 27 analysed climatic variables, the maximum temperature one week before parturition (MXTW) was identified as the most influential when comparing heteroscedastic models with the deviance information criterion. The order of Legendre polynomial to apply in the following random regression model was tested by a cross-validation using homoscedastic models. Finally, MXTW was compared on how it affected the two divergent lines by analyzing predicted breeding values (PBV) obtained from a random regression heterosdedastic model. The mean PBV of the H-line in the first generation showed a range of 0.070g with a negative slope, which was 35 times higher than the range obtained for the L-line, which varied within 0.002g. In the last generation of selection, the H-line exhibited greater instability of PBV across temperatures, with a difference of 0.101g between the maximum and minimum mean PBV, compared to 0.017g for the L-line. The standard deviations of the slopes in the H-line were more dispersed than in the L-line. Unlike the H-line, the L-line had slopes that were not significantly different from 0 throughout the generations of selection, indicating greater stability in response to MXTW variations. The H-line exhibited a higher sensitivity to changes in MXTW, particularly in birth weight, with the L-line being more stable. The selection for uniformity of birth weight could lead to less sensitive animals under environmental changes.

Estimation of genetic parameters for weight and length gains in tambaqui (Colossoma macropomum).

The goal of this study was to determine the genetic parameters for growth traits in tambaqui (Colossoma macropomum) fish of similar age and weight. The data set included monthly measurements of body weight and length from120 fish for a year (1,440 measurements). The study found that weight gain had a heritability estimate of 0.01, while length gain had a heritability estimate of 0.27. There was a high positive correlation (0.84) between weight and length gains. The genetic variance and heritability of body weight decreased with age. This study suggests that breeding programs should select for body weight and weight gain to promote genetic gain in tambaqui. Selecting younger animals can also help reduce costs while still achieving genetic gains.

Измерение массы плода с использованием автоматизированной трехмерной модели фракционного объема конечностей

Objective. To investigate the efficacy of using an automated three-dimensional (3D) fractional limb volume model to calculate estimated fetal weight (EFW) and predict fetal macrosomia. Patients and methods. This prospective observational study included 66 pregnant women who reached 30+0 to 41+3 weeks’ gestation. All patients underwent ultrasonography with fractional thigh volume (TVol) and fractional arm volume (AVol) measurements using 5D Limb Vol software (Samsung Medison W10 ultrasound system). Mean percentage error (MPE) was determined to assess the accuracy of fetal weight estimation. Results. Fractional thigh and arm volumes had a strong correlation with fetal weight (0.834 and 0.617, respectively) and increased linearly with gestational age. When performing a ROC analysis, TVol was found to be a predictor of fetal macrosomia with a sensitivity of 82.35% and specificity of 84.21%, and an experimental model including fetometric parameters (head circumference, abdominal circumference, and femur length) and TVol explained 83% of the variance in birth weight (p = 0.001). In our study, the formulas that included TVol and AVol to calculate EFW were less accurate than the Hadlock formula, with MPE of -1.25 ± 5.75, whereas when using the 3D model with TVol and AVol, MPE was 9.65 ± 7.84 and -9.16 ± 7.63, respectively. However, the experimental model with TVol produced more accurate EFW values compared to the Hadlock formula: the proportion of measurements with an estimated error ≤5% was 94.4% and 100% with an estimated error ≤10% (p &lt; 0.001). Conclusion. Fractional limb volume is an easily reproducible and promising parameter, and its use may be helpful to increase the accuracy of standard fetometry. Fractional thigh volume demonstrated high predictive ability for macrosomia, and its addition to standard fetometric parameters improved the model for fetal weight estimation. Key words: estimated fetal weight, fractional thigh and arm volumes, macrosomia, 5D Limb VolTM

Evaluation of the Relationship Between Growth Parameters for Spring-sown Onion Cultivation in Tohoku, Japan

Onion is one of the most productive vegetables in Japan, and onion growth models have been developed to predict its yield. However, onion growth is complex, and the selection of simple parameters is required to estimate bulb weight. This study utilized a 2-year dataset from a sequential growth study of spring-sown onions in the northeastern region of Japan to evaluate the correlation among growth parameters and to determine suitable parameters for estimating the dry weight of bulbs via multiple regression analysis. The results indicated that when bulb dry weight was the objective variable, the coefficients of determination of the single regression equation with plant height and leaf area as explanatory variables were 0.553 and 0.508, respectively, and the leaf parameter explained more than 50% of variance in bulb dry weight. Furthermore, the coefficient of determination was 0.912 when the leaf sheath basal diameter (ball width of the bulb) was used as an explanatory variable to explain the bulb dry weight. This indicates that there is a gap between the top and bulb growth. This study revealed the important parameters for predicting onion yield and demonstrated the switch in onion development from tops to bulbs.

APPLICATION OF STATISTICAL PROCESS CONTROL CHARTS: A CASE STUDY IN DAIRY INDUSTRY

Quality is a major part for entire industrial ecosystem when it comes to achieving, maintaining, and, improving the quality of products and services taking consideration of customer needs. Special causes responsible for controllable variations can be detected with the help of quality control charts-one of the quality management tools. Process can be improved by removing detected causes of variation bringing process under control. Statistical Process Control (SPC) Charts are quality control tools based on statistical principles which help to achieve quality of products by detecting special cause(s) of variation in the process involved. This paper incorporates a case study on application of Statistical Process Control (SPC) Charts tested at Sujal Dairy Pvt Ltd, Kathmandu, Nepal. Corresponding mean charts (Xbar charts) and range charts (R-Charts) represent data regarding quality variation for weight of milk pouch and SNF (Solid-Non-Fats) for both packaging machine 1 and machine 2. Results show that SNF variation for both machine and weight variation for machine 2 have been found to be under control whereas weight variation for machine 1 has been found to be out of control. Possible causes of variation have been grouped with the help of fishbone diagram and then compared with standard operating procedures for machine which led to detection of causes of variation. Finally, process has been better improved after removal of detected causes of variation bringing process under control.

Energy-saving technology for storage of cherry

Results of studies on extension of storage (shelf) life of cherries by treatment with ultraviolet light are presented. The most important indicators characterizing quality of cherry are considered. Analysis of variance of weight of cherries treated with ultraviolet light had been investigated. The Duncan Test for weight loss of cherries treated with ultraviolet rays was performed. Further studies and tests to determine quality of cherry had been carried out as well.

Full Stokes Polarization Imaging Based on Broadband Liquid Crystal Polarization Gratings

A method for full Stokes polarization imaging based on broadband liquid crystal polarization grating (LCPG) is presented. Firstly, the properties of the LCPG-based polarization detection module, which consists of a phase retarder and a broadband polarization grating in series, were investigated by means of Stokes calculus. The relationship between the polarization state of the incidence and the efficiencies of the diffractions was derived. Then, the azimuth parameters of the polarization detection module were optimized by using an equally weighted variance (EWV) evaluation criterion. Finally, the detection of the linearly and arbitrarily polarized laser beam and a linearly polarized broadband object were experimentally verified. The proposed method provides the design of polarization imaging systems based on LCPGs and has the advantages of compact structure, and broad wavelength coverage, therefore offering potential applications for image polarization information acquisition.

Estimation of Genetic Variance and Heritability of F2 Populations of Corn Plants in Dry Land

This study was aimed to determine the genetic variance of several F2 population traits of maize, broad heritability values and phenotypic correlations between yields and other quantitative traits. The method used is the experimental method. The experiment was designed in a randomized block design, with 6 replications. The number of treatments was 4 populations, namely population F2, Sinta Unram, hybrid NK212 and NK7328. Each population was planted in 4 rows, each consisted of 40 plants. The observed characteristics included plant height, leaf number per plant, leaf angle, ear length, ear diameter, weight of dry ear harvested per plant and yield (dry seed weight per plant). The data were analyzed by simple statistical analysis and analysis of variance at the 5 percent level of significance. The results showed that the genetic variance of plant height, leaf angle, and dry cob weight at harvest per plant population of F2 was higher than that of Sinta Unram's genetic diversity with relatively wide genetic diversity. The genetic variance of leaf number per plant, ear length and ear diameter were also higher than that of Sinta Unram; but the genetic diversity is quite narrow. The genetic diversity of the F2 population's traits is the same as that of Sinta Unram with a broad category. The heritability value of broad meaning classified as high (&gt; 50 %) was obtained on plant height, leave number per plant, ear length, ear diameter, weight of dry ear harvested per plant and yield; while the leaf angle is classified as moderate. Harvested dry cobs weight per plant showed strong phenotypic correlation with yield (0.827); while other properties are classified as very weak to moderate. Improving the yield of the F2 population can be done by indirect mass selection using the weight of harvested dry cobs per plant as the selected trait

Federated learning based on stratified sampling and regularization

Federated learning (FL) is a new distributed learning framework that is different from traditional distributed machine learning: (1) differences in communication, computing, and storage performance among devices (device heterogeneity), (2) differences in data distribution and data volume (data heterogeneity), and (3) high communication consumption. Under heterogeneous conditions, the data distribution of clients varies greatly, which leads to the problem that the convergence speed of the training model decreases and the training model cannot converge to the global optimal solution. In this work, an FL algorithm based on stratified sampling and regularization (FedSSAR) is proposed. In FedSSAR, a density-based clustering method is used to divide the overall client into different clusters, then, some available clients are proportionally extracted from different clusters to participate in training which realizes unbiased sampling for the overall client and reduces the aggregation weight variance of the client. At the same time, when calculating the model local loss function, we limit the update direction of the model by a regular term, so that heterogeneous clients are optimized in the globally optimal direction. We prove the convergence of FedSSAR theoretically and experimentally, and demonstrate the superiority of FedSSAR by comparing it with other FL algorithms on public datasets.

Investigating gripping force during lifting tasks using a pressure sensing glove system

Lifting tasks remain one of the leading causes of musculoskeletal disorders (MSDs), primarily in the low back region. Lifting analysis tools are, therefore, designed for assessing the risk of low back pain. Shoulder musculoskeletal problems have emerged as common MSDs associated with manual handling tasks. It is hypothesized that gripping force is related to lifting conditions and may be used as a supplementary risk metric for MSDs in the shoulder and low back regions, because it measures additional hand exertions for coupling the lifted object during lifting. We assessed the capability tactile gloves for measuring the gripping force during lifting as a means for assessing different task conditions (lifting weight, lifting height, lifting direction, body rotation, and handle). Thirty participants wore the tactile gloves and performed simulated lifting tasks. Regression models were used to analyze the effects of the task variables on estimating the measured gripping force. Results demonstrated that 58% and 70% of the lifting weight variance were explained by the measured gripping force without and with considering the individual difference, respectively. In addition to the lifting risk measures commonly used by practitioners, this study suggests a potential for using gripping force as a supplementary or additional risk metric for MSDs.