Estimation Of Correlation Coefficient Research Articles

Reproducibility of diaphragm thickness measurements by ultrasonography in patients on mechanical ventilation

AIMTo prospectively evaluate the reproducibility of diaphragm thickness measurement by ultrasonography at the bedside by critical care physicians in patients on invasive mechanical ventilation.METHODSIn a prospective observational study of 64 invasively ventilated patients, diaphragmatic thickness measurement was taken by 2 different observers at the same site. Three measurements were taken by each observer and averaged. The intraobserver and interobserver variability was assessed by estimation of intraclass correlation coefficient. The limits of agreement were plotted as the difference between two observations against the average of the two observations in Bland and Altman analysis.RESULTSThe mean diaphragm thickness at the functional residual capacity was 2.29 ± 0.4 mm and the lower limit of the normal, i.e., the 5th percentile was 1.7 mm (95%CI: 1.6-1.8). The intraclass correlation coefficient for intraobserver variability was 0.986 (95%CI: 0.979-0.991) with a P value of < 0.001. The intraclass correlation coefficient for interobserver variability was 0.987 (95%CI: 0.949-0.997) with a P value of < 0.001. In Bland and Altman analysis, both intraobserver and interobserver measurements showed high limits of agreement.CONCLUSIONOur study demonstrates that the measurement of diaphragm thickness by ultrasound can be accurately performed by critical care physicians with high degree of reproducibility in patients on mechanical ventilation.

Influences of sampling size and pattern on the uncertainty of correlation estimation between soil water content and its influencing factors

In this study, seven random combination sampling strategies were applied to investigate the uncertainties in estimating the hillslope mean soil water content (SWC) and correlation coefficients between the SWC and soil/terrain properties on a tea + bamboo hillslope. One of the sampling strategies is the global random sampling and the other six are the stratified random sampling on the top, middle, toe, top + mid, top + toe and mid + toe slope positions. When each sampling strategy was applied, sample sizes were gradually reduced and each sampling size contained 3000 replicates. Under each sampling size of each sampling strategy, the relative errors (REs) and coefficients of variation (CVs) of the estimated hillslope mean SWC and correlation coefficients between the SWC and soil/terrain properties were calculated to quantify the accuracy and uncertainty. The results showed that the uncertainty of the estimations decreased as the sampling size increasing. However, larger sample sizes were required to reduce the uncertainty in correlation coefficient estimation than in hillslope mean SWC estimation. Under global random sampling, 12 randomly sampled sites on this hillslope were adequate to estimate the hillslope mean SWC with RE and CV ≤10%. However, at least 72 randomly sampled sites were needed to ensure the estimated correlation coefficients with REs and CVs ≤10%. Comparing with all sampling strategies, reducing sampling sites on the middle slope had the least influence on the estimation of hillslope mean SWC and correlation coefficients. Under this strategy, 60 sites (10 on the middle slope and 50 on the top and toe slopes) were enough to ensure the estimated correlation coefficients with REs and CVs ≤10%. This suggested that when designing the SWC sampling, the proportion of sites on the middle slope can be reduced to 16.7% of the total number of sites. Findings of this study will be useful for the optimal SWC sampling design.

Estimation of correlation coefficient among yield and attributing traits of field pea (Pisum sativum L.)

In order to best exploit the available genetic wealth in the crop, the information would have paramount important. Therefore, this study was conceived to examine the variability and determines the relative importance of primary and secondary traits as selection criteria to improve productivity. Field pea (Pisum sativum L. var. arvense) is amongst the most important legume crop of India. The experimental material comprised of 120 field pea germplasm including 40 indigenous and 10 exotic collections of pea and 4 check varieties viz., HUDP-15, HFP-4, HUP-2, Rachna. Five competitive plants from each plot were randomly selected for recording observations for all the quantitative characters except days to 50 per cent flowering and days to maturity, which were recorded on line basis. In present study a strong and positive association of seed yield per plant observed with harvest index, biological yield per plant, plant height, number of seeds per pod, number of primary branches per plant, number of pods per plant and 100-seed weight. Days to maturity and number of seeds per pod showed positive correlation with days to 50 per cent flowering and number of primary branches per plant respectively. Days to maturity and 100-seed weight and number of pods per plant showed weak association with seed yield per plant in positive direction. Thus, these characters emerged as most vital component traits and associated positively with seed yield per plant.

Smoothed Spectra, Ogives, and Error Estimates for Atmospheric Turbulence Data

A systematic evaluation is conducted of the smoothed spectrum, which is a spectral estimate obtained by averaging over a window of contiguous frequencies. The technique is extended to the ogive, as well as to the cross-spectrum. It is shown that, combined with existing variance estimates for the periodogram, the variance—and therefore the random error—associated with these estimates can be calculated in a straightforward way. The smoothed spectra and ogives are biased estimates; with simple power-law analytical models, correction procedures are devised, as well as a global constraint that enforces Parseval’s identity. Several new results are thus obtained: (1) The analytical variance estimates compare well with the sample variance calculated for the Bartlett spectrum and the variance of the inertial subrange of the cospectrum is shown to be relatively much larger than that of the spectrum. (2) Ogives and spectra estimates with reduced bias are calculated. (3) The bias of the smoothed spectrum and ogive is shown to be negligible at the higher frequencies. (4) The ogives and spectra thus calculated have better frequency resolution than the Bartlett spectrum, with (5) gradually increasing variance and relative error towards the low frequencies. (6) Power-law identification and extraction of the rate of dissipation of turbulence kinetic energy are possible directly from the ogive. (7) The smoothed cross-spectrum is a valid inner product and therefore an acceptable candidate for coherence and spectral correlation coefficient estimation by means of the Cauchy–Schwarz inequality. The quadrature, phase function, coherence function and spectral correlation function obtained from the smoothed spectral estimates compare well with the classical ones derived from the Bartlett spectrum.

Joint estimation of multiple high‐dimensional Gaussian copula graphical models

SummaryA joint estimation approach for multiple high‐dimensional Gaussian copula graphical models is proposed, which achieves estimation robustness by exploiting non‐parametric rank‐based correlation coefficient estimators. Although we focus on continuous data in this paper, the proposed method can be extended to deal with binary or mixed data. Based on a weighted minimisation problem, the estimators can be obtained by implementing second‐order cone programming. Theoretical properties of the procedure are investigated. We show that the proposed joint estimation procedure leads to a faster convergence rate than estimating the graphs individually. It is also shown that the proposed procedure achieves an exact graph structure recovery with probability tending to 1 under certain regularity conditions. Besides theoretical analysis, we conduct numerical simulations to compare the estimation performance and graph recovery performance of some state‐of‐the‐art methods including both joint estimation methods and estimation methods for individuals. The proposed method is then applied to a gene expression data set, which illustrates its practical usefulness.

Comparative morphometric traits differentiation and phenotypic correlations between Achatina achatina (Linne, 1758) and Achatina fulica (Bowdich, 1822) snails with four and five whorls

Four hundred (400) adult black-skinned snails, two hundred (200) each of the Achatina achatina and Achatina fulica with 4 and 5 whorls were used respectively for the study.&nbsp; Identification and sorting of the snails sourced from a reputable snail vendor in Ibadan into breeds was done using the appropriate profile and template.&nbsp; The body weights of Achatina achatina and Achatina fulica snails with 4 whorls ranged from 83.00 to 180.50 g (average 156.90 g) and from 30.60 to 85.20 g (average 49.70 g) respectively. That for Achatina achatina and Achatina fulica snails with 5 whorls ranged from 132.70 to 272.80 g (average 138.95 g) and from 50.60 to 119.30 g (average 59.58 g) respectively. Results obtained from the study showed that Achatina achatina snails with 4 and 5 whorls were genetically heavier and larger than Achatina fulica with 4 and 5 whorls. Results of phenotypic correlation coefficient among morphometric traits of the two breeds indicated negative, weak, low significant (P&lt;0.05) and mostly non-significant (P&gt;0.05) differences between body weight and most body components (morphometric traits) studied.&nbsp; The only positive, low non-significant (P&gt;0.05) phenotypic correlation coefficient (rp) obtained was r = 0.420 between body weight and aperture width for Achatina fulica snails with 4 whorls.&nbsp; Whereas, for Achatina achatina snails with 5 whorls, positive, low significant (P&lt;0.05) phenotypic correlation coefficients obtained was r = 0.529 between body weight and aperture width and r = 0.660 between spiral width and aperture width respectively. Achatina fulica snails recorded the only positive highly significant (P&lt;0.01) phenotypic correlation coefficient of r = 0.602 between aperture width and shell width for the snails with 5 whorls. Breed type, age and size differences of snails used, body weight ranges, as well as number of whorls on snail shell have high effects of morphometric traits differentiation and phenotypic correlation coefficient estimates. Thus, the morphometric traits of the two breeds (Achatina achatina and Achatina fulica) of snails studied could be chosen to differentiate as well as characterize snails.

The development of a magnetic resonance imaging index for fistulising Crohn's disease.

Magnetic resonance imaging (MRI) is the gold standard for assessment of perianal fistulising Crohn's disease (CD). The Van Assche index is the most commonly used MRI fistula index. To assess the reliability of the Van Assche index, and to modify the instrument to improve reliability and create a novel index for fistulising CD. A consensus process developed scoring conventions for existing Van Assche index component items and new items. Four experienced radiologists evaluated 50 MRI images in random order on three occasions. Reliability was assessed by estimates of intraclass correlation coefficients (ICCs). Common sources of disagreement were identified and recommendations made to minimise disagreement. A mixed effects model used a 100mm visual anologue scale (VAS) for global severity as outcome and component items as predictors to create a modified Van Assche index. Intraclass correlation coefficients (95% confidence intervals) for intra-rater reliability of the original and modified Van Assche indices and the VAS were 0.86 (0.81-0.90), 0.90 (0.86-0.93) and 0.86 (0.82-0.89). Corresponding ICCs for inter-rater reliability were 0.66 (0.52-0.76), 0.67 (0.55-0.75) and 0.58 (0.47-0.66). Sources of disagreement included number, location, and extension of fistula tracts, and rectal wall involvement. A modified Van Assche index (range 0-24) was created that included seven component items. Although "almost perfect" intra-rater reliability was observed for the assessment of MRI images for fistulising CD using the Van Assche index, inter-rater reliability was considerably lower. Our modification of this index should result in a more optimal instrument.

Component traits influencing seed yield in recombinant inbred lines of lentil (Lens culinaris Medik.)

One hundred and thirty five RILs (Recombinant Inbred Lines) developed from a cross between an indigenous and exotic line of lentil (Lens culinarisMedik.)were evaluated for seed yield and component traits during rabi 2012-13 and 2013-14. Pooled analysis of variance revealed significant differences among the RILsfor all the traits studied. This suggested that there was ample scope for selection of promising RILs for yield improvement in lentil. Phenotypic and genotypic coefficients of variation were high for pods per plant(32.49% and 26.75%) followed by biological yield per plot(24.38% and 21.28%). Genetic advance was highest for 100-seed weight(47.75%)followed by pods per plant(45.39%). Estimation of phenotypic correlation coefficients indicated that seed yield per plot expressed highly significant and positive correlation with biological yield per plot(0.634), harvest index(0.300) and seeds per pod(0.156). Path coefficient analysis revealed that the traits; biological yield per plot , harvest index, number of pods per plant, days to 50% flowering, days to maturity , plant height and primary branches per plant had positive direct effect on seed yield per plot. The selection of these traits would be helpful for further yield improvement in lentil.

PIXEL-BY-PIXEL ESTIMATION OF SCENE MOTION IN VIDEO

Abstract. The paper considers the effectiveness of motion estimation in video using pixel-by-pixel recurrent algorithms. The algorithms use stochastic gradient decent to find inter-frame shifts of all pixels of a frame. These vectors form shift vectors’ field. As estimated parameters of the vectors the paper studies their projections and polar parameters. It considers two methods for estimating shift vectors’ field. The first method uses stochastic gradient descent algorithm to sequentially process all nodes of the image row-by-row. It processes each row bidirectionally i.e. from the left to the right and from the right to the left. Subsequent joint processing of the results allows compensating inertia of the recursive estimation. The second method uses correlation between rows to increase processing efficiency. It processes rows one after the other with the change in direction after each row and uses obtained values to form resulting estimate. The paper studies two criteria of its formation: gradient estimation minimum and correlation coefficient maximum. The paper gives examples of experimental results of pixel-by-pixel estimation for a video with a moving object and estimation of a moving object trajectory using shift vectors’ field.

Human ancestry correlates with language and reveals that race is not an objective genomic classifier

Genetic and archaeological studies have established a sub-Saharan African origin for anatomically modern humans with subsequent migrations out of Africa. Using the largest multi-locus data set known to date, we investigated genetic differentiation of early modern humans, human admixture and migration events, and relationships among ancestries and language groups. We compiled publicly available genome-wide genotype data on 5,966 individuals from 282 global samples, representing 30 primary language families. The best evidence supports 21 ancestries that delineate genetic structure of present-day human populations. Independent of self-identified ethno-linguistic labels, the vast majority (97.3%) of individuals have mixed ancestry, with evidence of multiple ancestries in 96.8% of samples and on all continents. The data indicate that continents, ethno-linguistic groups, races, ethnicities, and individuals all show substantial ancestral heterogeneity. We estimated correlation coefficients ranging from 0.522 to 0.962 between ancestries and language families or branches. Ancestry data support the grouping of Kwadi-Khoe, Kx’a, and Tuu languages, support the exclusion of Omotic languages from the Afroasiatic language family, and do not support the proposed Dené-Yeniseian language family as a genetically valid grouping. Ancestry data yield insight into a deeper past than linguistic data can, while linguistic data provide clarity to ancestry data.

Validation of an instrument for measuring satisfaction of patients undergoing hemodialysis

BackgroundPatients’ satisfaction is an indicator of the quality of healthcare services. Its measurement involves developing and validating complex instruments. The purpose of this study was to validate a scale for measuring hemodialysis patients’ satisfaction with the provided care, the Scale for Evaluation of Hemodialysis Patient’s Satisfaction with Service provided at a Chronic Kidney Disease Unit (or ESUR-HD, its acronym in Spanish).MethodsThe instrument was applied to 370 patients undergoing hemodialysis for undertaking exploratory and confirmatory analyses, internal consistency assessment, and Rasch analysis. In order to assure test-retest reliability, the instrument was applied once again to 54 patients after 2 days. Convergent validity was assessed by estimating correlation coefficients based on the results of 2 instruments (ESUR-HD and SDIALOR) simultaneously applied in 70 patients. Sensitivity to change was assessed in 40 patients by comparing the scale scores before and after an intervention consisting of improved care conditions.ResultsIn the 44 items of the scale a 9-factor structure was found (1: Facilities and organization of the service. 2: Care provided by the attending nurses and/or nursing assistants. 3: Attention to psychological and administrative issues. 4: Contact and social work personnel. 5: Medical attention and care. 6: Nutritional attention and care. 7: Medications supply and quality. 8: Features of the admission process. 9: Attention and care provided by head nurses). Chronbach alpha for the scale was 0.96. Lin’s concordance correlation for the whole scale was 0.85. Although statistically different from 0, low correlation values with dimensions from another scale measuring the same attribute were found. The scale could detect construct changes through increased scores in specific dimensions following an intervention aimed at enhancing satisfaction. Rasch analysis located improperly fit items and suggested reducing items measurement levels. Despite the effect encountered, Rasch analysis showed the scale might not capture variability in upper attribute levels.ConclusionThe ESUR-HD scale measures hemodialysis patients’ satisfaction in one dimension with 9 domains. Validity and reliability are adequate. The instrument may detect changes in the construct. Subsequent versions of the scale should include new items allowing improved discrimination amongst high satisfaction levels.Trial registrationISRCTN45318400. April 05, 2017

EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features.

Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for electroencephalogram (EEG)-based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30%-8.30%, and increase the estimation correlation coefficient by 6.59%-11.13%.

Studies on Genetic Diversity for Yield, Growth and Quality Traits in Sweet Potato [Ipomoea batatas (L.) Lam.

The experiment was conducted at main Experimental Station of Department of Vegetable Science, Narendra Deva University of Agriculture and Technology, Narendra Nagar, Kumarganj, Faizabad. During October 2013 to February 2014, to assess variability, heritability and genetic advance for quantitative characters, estimate correlation coefficients among the important economic traits and to find out the direct and indirect effect of yield components, yield by path coefficient analysis and genetic divergence. Experiment at material for the study consisted of 33 genotypes including two checks (NDSP-10, NDSP-65). The experiment was conducted in Randomized Block Design with three replications. Observations were recorded on thirteen quantitative characters. A total of 33 genotypes was grouped in to 5 clusters. The highest numbers of entries were present in cluster I which contained 20 genotypes followed by cluster II which carried 10 genotypes. Other clusters such as III, IV and V recorded minimum contained one genotype each in cluster. The maximum intra-cluster distance was recorded for cluster II (95.07) followed by cluster I (53.91), cluster III, No intra-cluster distance was recorded IV and V since the value was recorded zero in these cluster. The maximum inter cluster distance was found by cluster I with V (353.16) which suggested that member of these genotypes are genetically very diverse to each other. The minimum inter-cluster distance was observed between clusters I with II (99.45). Highest per cent contribution towards total genetic divergence was exhibited by length of vine (26.33%), followed by branches per vine (19.89%), internodal length (17.61%) average weight of tuber (10.80), width of leaves (9.47%), leaves per vine (5.87), length of leaves (5.68%), girth of tuber (1.89%), yield per hectare (0.95%), yield per plant (0.57%), tuber per vine and days to bud initiation is not having any contribution. Thus, there exists ample variation and as a result scope of improvement after selection in the available germplasm of sweet potato.

Phase Code to Mitigate the Copolar Correlation Coefficient Bias in PPAR Weather Radar

One of the main challenges to the use of phased array radar for weather observations is the implementation of dual polarization with acceptable levels of cross-polar fields induced by the antenna. For example, to achieve acceptable differential reflectivity bias (i.e., less than 0.1 dB) using simultaneous transmission and reception of horizontally and vertically polarized waves, the isolation between coaxial cross-polar and copolar beams needs to be in excess of 50 dB. This presents a formidable challenge, because sufficient isolation cannot be achieved at an affordable price by the antenna hardware alone. Hence, additional approaches are required to reduce the differential reflectivity bias due to cross-polar fields. One proposed technique is a 180° pulse-to-pulse phase change of signals injected in either the horizontal or vertical ports of the transmission elements. This approach mitigates the differential reflectivity bias but may increase the bias of the copolar correlation coefficient estimates and, in some cases, the bias of the differential phase estimates. Herein, a modified phase code is proposed, which maintains the differential reflectivity bias suppression but reduces the copolar correlation coefficient and differential phase bias with respect to the originally proposed phase code.

Targeted Traits for Enhancement of Seed Iron and Zinc Concentrations in Pigeonpea

Iron and zinc malnourishment is consistent pan Asia–Pacific and Africa, as their intake and absorption is limiting. Breeding for high seed iron and zinc concentrations advocate to evaluate their association with various nutritional and anti-nutritional traits, which will assist in the selection process. Pigeonpea is a good source of protein and is being adopted widely as it can be grown on low-input, marginal lands. One hundred and four diversified genotypes of pigeonpea were scored for seven nutritional traits and significant differences were observed among them. The estimates of correlation coefficients and path analysis indicated that bolder seeds with high zinc concentration, lipid content and lesser contents of phytic acid should be aimed for enhancement of seed iron concentration, while, seed protein content can be used as a secondary variable for selection of this trait. On the other hand, small seeds with high lipid and iron concentrations and lesser contents of phytic acids and proteins should be targeted for improvement of seed zinc concentration in pigeonpea.

New Regression Equations for Estimating the Maximal Oxygen Uptake of College of Physical Education and Sports Students in Turkey

Aerobic endurance describes the ability of the body’s cardio-respiratory system to perform physical activity for an extended period of time and resist fatigue. Standard tests to determine aerobic endurance involves measuring the maximum volume of oxygen (VO2max) an athlete uses up while exercising at maximal capacity. Given that the tests of direct measurement of VO2max needs expensive equipment, a great deal of time, and trained staff with expertise, many researchers have attempted to find indirect and simpler ways of predicting VO2max based on prediction equations. The aim of this study is to establish new prediction equations for estimating the VO2max from gender, age, height, weight, body mass index (BMI), maximal heart rate (HRmax) and test time (TT) for college-aged students in Turkey. Particularly, 18 students from the College of Physical Education and Sports at Gazi University volunteered for this study. Gender has been used as a common predictor variable in all prediction models. By using different combinations of the rest of predictor variables together with the common predictor variable, twelve VO2max prediction equations have been established with the help of Multiple Linear Regression (MLR). The performance of the prediction equations have been evaluated using two well-known metrics, namely standard error of estimate (SEE) and multiple correlation coefficient (R). The results reveal that the regression equation, VO2max = - (12.331 x gender) - (0.805 x age ) + (0.883 x height) - (1.167 x weight) - (0.052 x HRmax) - (0.158 x TT) + 6.473, gave the lowest SEE (i.e3.49 mL.kg-1.min-1) and the highest R (i.e. 0.88). Application of this VO2max regression equation on an independent validation group including 6 subjects yielded an SEE of 6.24 mL.kg-1.min-1.It can be concluded that in situations where it is difficult or even not possible to measure VO2max using exercise tests, coaches and trainers may use the given equation to predict VO2max of College of Physical Education and Sports students with acceptable error rates.

New Regression Equations for Estimating the Maximal Oxygen Uptake of College of Physical Education and Sports Students in Turkey

Aerobic endurance describes the ability of the body’s cardio-respiratory system to perform physical activity for an extended period of time and resist fatigue. Standard tests to determine aerobic endurance involves measuring the maximum volume of oxygen (VO2max) an athlete uses up while exercising at maximal capacity. Given that the tests of direct measurement of VO2max needs expensive equipment, a great deal of time, and trained staff with expertise, many researchers have attempted to find indirect and simpler ways of predicting VO2max based on prediction equations. The aim of this study is to establish new prediction equations for estimating the VO2max from gender, age, height, weight, body mass index (BMİ), maximal heart rate (HRmax) and test time (TT) for college-aged students in Turkey. Particularly, 18 students from the College of Physical Education and Sports at Gazi University volunteered for this study. Gender has been used as a common predictor variable in all prediction models. By using different combinations of the rest of predictor variables together with the common predictor variable, twelve VO2max prediction equations have been established with the help of Multiple Linear Regression (MLR). The performance of the prediction equations have been evaluated using two well-known metrics, namely standard error of estimate (SEE) and multiple correlation coefficient (R). The results reveal that the regression equation, VO2max = - (12.331 x gender) - (0.805 x age ) + (0.883 x height) - (1.167 x weight) - (0.052 x HRmax) - (0.158 x TT) + 6.473, gave the lowest SEE (i.e3.49 mL.kg-1.min-1) and the highest R (i.e. 0.88). Application of this VO2max regression equation on an independent validation group including 6 subjects yielded an SEE of 6.24 mL.kg-1.min-1.İt can be concluded that in situations where it is difficult or even not possible to measure VO2max using exercise tests, coaches and trainers may use the given equation to predict VO2max of College of Physical Education and Sports students with acceptable error rates.

First Study of the Turkey ( Meleagris Gallopavo ) in Cameroon: Assessing Turkey Biodiversity in the Highlands of West-Cameroon

The study was undertaken from November 2015 to January 2016. It had as a general objective to contribute to the knowledge of turkey’s biodiversity of the Highlands of West-Cameroon for their safeguard and for their genetic improvement. More specifically, it was aimed at evaluating turkeys’ morphobiometric diversity and estimating correlation coefficients between measurements and Live Weight. To achieve these goals, a sample of 236 adult turkeys whose 141 females and 95 males was randomly selected in four Divisions in the zone of study. The principal results show that the turkey’s plumage colouring in the Highlands of West-Cameroon is very varied, with a prevalence of bronzed (54.50%). Head colouring is also very variable, but the blue-red (28.94%) and pink (23.86%) are more frequent. Shanks are most often pink (36.85%), but can also be black-red (21.30%) or clear-pink (20.30%). Eyes are black-chestnut (63.13%), chestnut (16.95%) and grey-black (12.18%). In the same way, studied quantitative characters are very variable, with a sexual dimorphism in favour of the males. Thus, the average weight of the studied animals is of 6.11 ± 0.19 Kg with a variation coefficient of 49%. However, males are approximately 23% heavier (7.93 ± 0.19 Kg) than females (4.89 ± 0.25 Kg). In addition, studied body measurements are significantly (P < 0.05) higher in tom turkeys, although variable with the considered Divisions. All the correlations are positive, but correlations between Live Weight and the length of the snood (r = 0.55) and the thoracic circumference (r = 0.53) are the highest ones.

Regression Algorithms for Detection and Recognition of Non-Centered Non-Stationary Random Signals in the Short-Range Autonomous Information Systems

The article forms the rationale for using the regression algorithms to detect and recognize the non-stationary non-centered signals and noise taking into account the specifics of the short-range autonomous information systems (SRAIS) under conditions of unknown mathematical expectations of informative parameters of signals. When representing each sample realization of the non-stationary processes, subordinated to the normal law of distribution of probabilities, in discrete time, based on the approximate Kotelnikov theorem to solve the problems of signal detection and recognition on the background of band white noise were obtained the expressions for the coefficients of private plausibility of the respective hypotheses. The resulting algorithms require computation of quadratic forms and knowledge of the expectations of selected informative parameters. It is shown that taking into consideration the specific SRAIS – equality relations of mathematical expectation to the RMS values in the samples and high correlation coefficients of the parameter estimates of informative parameters – it is possible to proceed from calculating the quadratic forms in the signal processing algorithms to calculating the modules of errors of multiple initial regression representations for linear correlation. The article justifies the regression algorithms to form the areas of decision-making in which relative distances from the initial regression line are restricted, that is, the algorithms have a clear geometric meaning. Such algorithms can be applied regardless of the probability distribution of estimated random parameters of the signals (for unimodal distributions), since a priori information about the coefficients of the initial regression is obtained when investigating the correlations curves of the random parameters of the signal in the entire area of their change in linear correlation. In non-linear correlation in the SRAIS, using the information on the application conditions it is possible to make alterations of parameters of decision-making algorithms. The article investigates the performance and decision-making regression algorithm to detect the correlated two-dimensional non-centered random vectors for the normal distributions of signal and noise with different primary regression specifications. The considered regression algorithms can be applied in SRAIS to improve noise immunity when solving the tasks of detection and recognition of signals and noise.

Qualitative and quantitative evaluation of in vivo SD-OCT measurement of rat brain.

OCT has been demonstrated as an efficient imaging modality in various biomedical and clinical applications. However, there is a missing link with respect to the source of contrast between OCT and other modern imaging modalities, no quantitative comparison has been demonstrated between them, yet. We evaluated, to our knowledge, for the first time in vivo OCT measurement of rat brain with our previously proposed forward imaging method by both qualitatively and quantitatively correlating OCT with the corresponding T1-weighted and T2-weighted magnetic resonance images, fiber density map (FDM), and two types of histology staining (cresyl violet and acetylcholinesterase AchE), respectively. Brain anatomical structures were identified and compared across OCT, MRI and histology imaging modalities. Noticeable resemblances corresponding to certain anatomical structures were found between OCT and other image profiles. Correlation was quantitatively assessed by estimating correlation coefficient (R) and mutual information (MI). Results show that the 1-D OCT measurements in regards to the intensity profile and estimated attenuation factor, do not have profound linear correlation with the other image modalities suggested from correlation coefficient estimation. However, findings in mutual information analysis demonstrate that there are markedly high MI values in OCT-MRI signals.