scholarly journals Longevity of Nelore Cows of the Bolivian Tropics. Is It Possible to Explain It Through Productive Variables?

2019 ◽  
Vol 8 (4) ◽  
pp. 28
Author(s):  
Atsuko Ikeda ◽  
Ivana Barbona ◽  
Yoichiro Hayashi ◽  
Juan A. Pereira ◽  
Pablo R. Marini
Keyword(s):  
Live Weight ◽  
Multiple Linear Regression Model ◽  
Principal Component ◽  
Productive Efficiency ◽  
P Value ◽  
San Juan ◽  
Total Variability ◽  
Grazing Systems ◽  
Breeding Efficiency ◽  
Main Components

The objective of this work was to evaluate the longevity and its relationship with productive variables of Nelore cows in grazing systems of the Bolivian tropics. Retrospective data were used corresponding to 259 Nelore breed cows, primiparous and multiparous discarded with a total of 800 births, in the period between 2005 and 2019, belonging to the Cooperativa Agropecuaria Integral San Juan de Yapacaní (CAISY) located in the San Juan Japanese Communities, Santa Cruz, Bolivia. The variables analyzed were: Live weight of cow (WC) in kg, Weight of the calf at birth (WCB) in kg, Weight of calf at weaning (WCW) in kg, Total weight of weaned calf (WWC) in kg, Age at first calving (AFC) in months, Number of calvings (NC), Longevity (L) in days, Calf Index (CI) in kg, Accumulated Productivity (PAC) in kg, Total calf production (CP) in kg, Efficiency of Stock (ES) in kg. In order to respond to the main objective of this work, the relationship between the life longevity of the cow and the other productive variables was studied. For this, first principal component analysis (PCA) was carried out, by means of which the space dimension of the productive variables was reduced creating new linearly independent variables and in this way avoid problems of multicollinearity in the model, because the productive variables in some cases turned out to be correlated. Then, the first three main components that explain 77% of the total variability of the data were retained and interpreted as follows: The PC1 was high and directly correlated with the variables NC, Kg produced total, % of stock efficiency, PAC and Kg produced meat / day, therefore can be thought of as an indicator of "productive efficiency". PC2 was an indicator of "efficiency in rebreeding" since it presented altar and direct correlations with WC and AFC. PC3 was high and directly correlated with birth weight and weaning weight, which is interpreted as an indicator of "breeding efficiency". Finally, a multiple linear regression model was adjusted considering Longevity as a function of productive efficiency, breeding efficiency and rebreeding efficiency (p-value <0.0001 in the three cases). 87% of the total variability of L (days) is explained by the model. It is concluded that Longevity is related to productive indicators for this group of Nelore cows in grazing systems of the Bolivian tropics.

scholarly journals Welfare Assessment: Correspondence Analysis of Welfare Score and Hematological and Biochemical Profiles of Dairy Cows in Sardinia, Italy

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 854
Author(s):  
Federica Loi ◽  
Giovannantonio Pilo ◽  
Giulia Franzoni ◽  
Rossana Re ◽  
Francesca Fusi ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Animal Welfare ◽  
Health Planning ◽  
Clinical Signs ◽  
Principal Component ◽  
P Value ◽  
Holstein Breed ◽  
Welfare Evaluation ◽  
Total Variability ◽  
Future Evaluation

The need for animal welfare definition and assessment is increasing worldwide, and several studies have been conducted to help fill the knowledge gaps regarding the welfare of cattle. However, further studies are needed to provide valid synthetized measures for welfare evaluation. The aim of this study was to assess the welfare status of 16 Sardinian dairy cattle farms, based on the developed Animal Welfare and Biosecurity Evaluation checklist (AWB-EF) and the corresponding hematological, biochemical, and electrophoretic profiles of these animals. Considering the AWB-EF as gold standard, blood samples were collected from 230 Holstein breed dairy cattle, aged between 3 and 8 years, out of the periparturient period, and with no clinical signs of specific pathologies. Principal Component (PC) and correlation analyses were performed to simplify phenomena interpretation and assess positive/negative associations. Four PCs were able to explain 76% of the total variability, and six laboratory parameters were strongly associated with the AWB-EF score (Spearman’s correlation coefficient ≥0.40, p-Value < 0.05), reflecting the real health status of the animals. Given the complexity of animal welfare as a multidimensional concept and the need to include both animal-based and non-based measures in welfare evaluation, the present work represents a sound basis for future evaluation and veterinary health planning.

scholarly journals Kinetic and Microhydrodynamic Modeling of Fenofibrate Nanosuspension Production in a Wet Stirred Media Mill

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1055
Author(s):  
Gulenay Guner ◽  
Dogacan Yilmaz ◽  
Ecevit Bilgili
Keyword(s):  
Rate Constant ◽  
Kinetic Models ◽  
Multiple Linear Regression Model ◽  
Empirical Correlation ◽  
P Value ◽  
Order Kinetic ◽  
Stirrer Speed ◽  
Predictive Capability ◽  
Breakage Rate ◽  
The Impact

This study examined the impact of stirrer speed and bead material loading on fenofibrate particle breakage during wet stirred media milling (WSMM) via three kinetic models and a microhydrodynamic model. Evolution of median particle size was tracked via laser diffraction during WSMM operating at 3000–4000 rpm with 35–50% (v/v) concentration of polystyrene or zirconia beads. Additional experiments were performed at the center points of the above conditions, as well as outside the range of these conditions, in order to test the predictive capability of the models. First-order, nth-order, and warped-time kinetic models were fitted to the data. Main effects plots helped to visualize the influence of the milling variables on the breakage kinetics and microhydrodynamic parameters. A subset selection algorithm was used along with a multiple linear regression model (MLRM) to delineate how the breakage rate constant k was affected by the microhydrodynamic parameters. As a comparison, a purely empirical correlation for k was also developed in terms of the process/bead parameters. The nth-order model was found to be the best model to describe the temporal evolution; nearly second-order kinetics (n ≅ 2) was observed. When the process was operated at a higher stirrer speed and/or higher loading with zirconia beads as opposed to polystyrene beads, the breakage occurred faster. A statistically significant (p-value ≤ 0.01) MLRM of three microhydrodynamic parameters explained the variation in the breakage rate constant best (R2 ≥ 0.99). Not only do the models and the nth-order kinetic–microhydrodynamic correlation enable deeper process understanding toward developing a WSMM process with reduced cycle time, but they also provide good predictive capability, while outperforming the purely empirical correlation.

scholarly journals Mid-Infrared Spectroscopy as a Rapid Tool to Qualitatively Predict the Effects of Species, Regions and Roasting on the Nutritional Composition of Australian Acacia Seed Species

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 1879
Author(s):  
Oladipupo Q. Adiamo ◽  
Yasmina Sultanbawa ◽  
Daniel Cozzolino
Keyword(s):  
Principal Component ◽  
Nutritional Composition ◽  
Human Consumption ◽  
Mid Infrared ◽  
Mir Spectroscopy ◽  
As Species ◽  
Before And After ◽  
Mir Spectra ◽  
Main Components ◽  
Rapid Tool

In recent times, the popularity of adding value to under-utilized legumes have increased to enhance their use for human consumption. Acacia seed (AS) is an underutilized legume with over 40 edible species found in Australia. The study aimed to qualitatively characterize the chemical composition of 14 common edible AS species from 27 regions in Australia using mid-infrared (MIR) spectroscopy as a rapid tool. Raw and roasted (180 °C, 5, 7, and 9 min) AS flour were analysed using MIR spectroscopy. The wavenumbers (1045 cm−1, 1641 cm−1, and 2852–2926 cm−1) in the MIR spectra show the main components in the AS samples. Principal component analysis (PCA) of the MIR data displayed the clustering of samples according to species and roasting treatment. However, regional differences within the same AS species have less of an effect on the components, as shown in the PCA plot. Statistical analysis of absorbance at specific wavenumbers showed that roasting significantly (p < 0.05) reduced the compositions of some of the AS species. The results provided a foundation for hypothesizing the compositional similarity and/or differences among AS species before and after roasting.

scholarly journals The food patterns of a multicenter cohort of Brazilian nulliparous pregnant women

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria J. Miele ◽  
Renato T. Souza ◽  
Iracema M. Calderon ◽  
Francisco E. Feitosa ◽  
Débora F. Leite ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Dietary Patterns ◽  
Principal Component ◽  
Good Representation ◽  
Processed Foods ◽  
Food Groups ◽  
Dietary Recall ◽  
Complex Process ◽  
Nutrient Consumption ◽  
Main Components

AbstractAssessment of human nutrition is a complex process, in pregnant women identify dietary patterns through mean nutrient consumption can be an opportunity to better educate women on how to improve their overall health through better eating. This exploratory study aimed to identify a posteriori dietary patterns in a cohort of nulliparous pregnant women. The principal component analysis (PCA) technique was performed, with Varimax orthogonal rotation of data extracted from the 24-h dietary recall, applied at 20 weeks of gestation. We analysed 1.145 dietary recalls, identifying five main components that explained 81% of the dietary pattern of the sample. Dietary patterns found were: Obesogenic, represented by ultra-processed foods, processed foods, and food groups rich in carbohydrates, fats and sugars; Traditional, most influenced by natural, minimally processed foods, groups of animal proteins and beans; Intermediate was similar to the obesogenic, although there were lower loads; Vegetarian, which was the only good representation of fruits, vegetables and dairy products; and Protein, which best represented the groups of proteins (animal and vegetable). The obesogenic and intermediate patterns represented over 37% of the variation in food consumption highlighting the opportunity to improve maternal health especially for women at first mothering.

A Semantic Differential for Evaluating the Sound Quality of Fan Systems

2017 ◽  
Author(s):  
Carolin Feldmann ◽  
Thomas Carolus ◽  
Marc Schneider
Keyword(s):  
Principal Component ◽  
Semantic Differential ◽  
Sound Quality ◽  
Heat Pumps ◽  
First Case ◽  
Objective Metrics ◽  
Main Components ◽  
Air Conditioning Systems ◽  
The University

Fans are main components e.g. in heating, ventilating and air conditioning systems for vehicles or buildings, cooling units of engines and electronic circuits, and household appliances such as kitchen exhaust hoods or vacuum cleaners. End-users increasingly demand a high sound quality of their system or device. The overall objective of a recent research project at the University of Siegen is a multidimensional assessment of fan sound quality. In a first step an advanced novel semantic differential for the assessment of fan-related sounds is established with the aid of carefully designed jury tests. Eventually, this semantic differential is employed for sound quality jury tests of fans in kitchen exhaust hoods, heat pumps and air purifiers as a first case. Finally, a prediction model is suggested, which relates the outcome from the jury tests to objective metrics. A principal component analysis is carried out and yields five main assessment criteria with 23 relevant adjective scales. The results show that the perceived sound quality of fan systems is mainly determined by the loudness and tonality of the sound. The spectral content (represented by the sharpness) as well as the time structure (represented by the roughness) have no significant impact on perceived sound quality of the fan systems investigated.

scholarly journals Person - job fi t and the work commitment of IT Personnel

2016 ◽  
Vol 26 (2) ◽  
pp. 218 ◽  
Author(s):  
Therasa C. ◽  
C. Vijayabanu
Keyword(s):  
Regression Analysis ◽  
Principal Component ◽  
Attrition Rate ◽  
P Value ◽  
Work Commitment ◽  
Key Factors ◽  
Coeffi Cients ◽  
Work Autonomy ◽  
Major Factors ◽  
The Impact

Introduction: There have been given a much higher importance to employee commitment and retention since India is experiencing the highest attrition rate globally Economic Times, 2015. Hence, considering the factors of Person-job fi t to interpret the impact towards work commitment is very well essential, especially in the current scenario. Work Commitment is a vital element in any organization which has outstanding impact on productivity and functioning and hence it is very much vital to have a committed workforce which is necessary in this competitive environment and tight labour market. In the same way, there is considerable amount of evidence that if P-J fi t is high then it will have a direct impact on organization commitment also. Person-job fi t is the compatibility between person’s competency and abilities and the requirements of the job Zheng et al.2. If there exists a mismatch between person-job fi t then the consequences might result in poor work commitment, low job satisfaction and extremely lower involvement in the job. Objective: This study analyzed the key factors that contribute to Person- job compatibility among IT workers and also analyzed the relationship and impact of Person- job compatibility towards work commitment. Methods: Exploratory Factor Analysis (EFA) was used to fi lter the key factors initially, followed by a linear regression technique to determine the impact of Person- job compatibility factors in work commitment on a sample of 300 employees. EFA used Principal Component analysis for extraction and Promax for rotation. Finally regression analysis was carried out to predict the work commitment through statistically significant person-job compatibility variables. Results: The impact of person-job compatibility on work commitment was studied through regression analysis and it imply that for every unit increase in HR Policy, a 0.52 (unstandardised coeffi cients) increase in work commitment is predicted and it has been turned out as a most impacting variable to predict work commitment. The coeffi cients for Relationship (B =.330, sig =.000), HR Policies (B =.519, sig =.000), Pay and Benefi ts (B =.386, sig =.000) and Employee Growth (B =.290, sig =.001) were statistically significant, since its p-value is .000 which is smaller than .05. The coeffi cients for Work Autonomy (B =.154, sig = .081) was not statistically signifi cant, since its p-value is 0.081 which is greater than.05. Conclusion: The major factors responsible for creating work commitment among IT employees are Relationship, HR Policies and strategies, Pay and benefi ts, Work autonomy and Employee growth. The most contributing regressors which accounts for creating work commitment are HR policies, Pay and benefi ts, Employee growth and work autonomy.

scholarly journals Feed efficiency of lactating Holstein cows is less reproducible when changing dietary starch and fibre concentrations than within diet over subsequent lactation stages

2021 ◽  
Author(s):  
Amélie Fischer ◽  
Philippe Gasnier ◽  
Philippe Faverdin
Keyword(s):  
Principal Components ◽  
Feed Efficiency ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Holstein Cows ◽  
Diet Change ◽  
Total Variability ◽  
The One ◽  
The Individual ◽  
Starch Diet

ABSTRACTBackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet (diet E+P+), then switched over to a low starch diet (diet E−P−). Near infra-red (NIR) spectroscopy was performed on each individual feed ingredient, diet and individual refusals to check for sorting behaviour. A principal component analysis (PCA) was performed to analyse if the variability in NIR spectra of the refusals was explained by the differences in feed efficiency.ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet over two subsequent lactation stages, which were 2.01 MJ/d within diet E−P− and 2.40 MJ/d within diet E+P+. The coefficient of correlation of concordance (CCC) was 0.64 between feed efficiency estimated within diet E+P+ and feed efficiency estimated within diet E−P−. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet E+P+ and 0.85 within diet E−P−). The first two principal components of the PCA explained 90% of the total variability of the NIR spectra of the individual refusals. Feed efficiency was poorly correlated to those principal components, which suggests that feed sorting behaviour did not explain differences in feed efficiency.ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cow’s ranking for feed efficiency was not significantly affected by diet change. The differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the E+P+ diet nor with the E−P− diet. Those results have to be confirmed with cows fed with more extreme diets (for example roughage only) to ensure that the least and most efficient cows will not change.

scholarly journals Surface Electromyography Based Core Muscle Fatigue Analysis During Repetitive Plank Using Multivariate Dimensionality Reduction Methods in Boys Aged 12-14

2021 ◽  
Vol 21 (3) ◽  
pp. 253-263
Author(s):  
Abir Samanta ◽  
Sabyasachi Mukherjee
Keyword(s):  
Discriminant Analysis ◽  
Muscle Fatigue ◽  
Muscle Activity ◽  
Principal Component ◽  
Erector Spinae ◽  
P Value ◽  
Recruitment Strategies ◽  
Structure Matrix ◽  
Spine Stability ◽  
Wilks Lambda

The aims of the study were: 1. To analyse the discriminative power of neuromuscular components for classifying the pre and post muscle fatigued states. 2. To examine whether the modification of neural recruitment strategies become more/less heterogeneous due to fatigue. 3. To research the effect of Erector Spinae (ES) muscle activity collectively with Rectus Abdominis (RA) and External Oblique (EO) muscle activity to identify the reduced spine stability during fatiguing Plank.  Material and methods. Twelve boys (age – 12-14 years, height 148.75 ± 10 cm, body mass 38.9 ± 7.9 kg) participated in the study. Multivariate Discriminant Analysis (DA) and Principal Component Analysis (PCA) were applied to identify the changes in the pattern of the electromyographic signals during muscle fatigue. In DA the Wilks’ lambda, p-value, canonical correlation, classification percentage and structure matrix were used. To evaluate the component validity the standard limit for Kaiser-Meyer-Olkin (KMO) was set at ≥0.529 and the p-value of Bartlett’s test was ≤0.001. The eigenvalues ≥1 were used to determine the number of Principal Components (PCs). The satisfactory percentage of non-redundant residuals were set at ≤50% with standard value >0.05. The absolute value of average communality (x̄ h2) and component loadings were set at ≥0.6, ≥0.4 respectively.  Results. Standardized canonical discriminant analysis showed that pre and post fatigued conditions were significantly different (p = 0.000, Wilks’ lambda = 0.297, χ2 = 24.914, df=3). The structure matrix showed that the parameter that correlated highly with the discriminant function was ES ARV (0.514). The results showed that the classification accuracy was 95.8% between fatigued conditions. In PCA the KMO values were reduced [0.547Pre fatigue vs. 0.264Post fatigue]; the value of Bartlett’s sphericity test was in pre χ2 = 90.72 (p = 0.000) and post fatigue χ2 = 85.32 (p = 0.000); The Promax criterion with Kaiser Normalization was applied because the component rotation was non-orthogonal [Component Correlation Matrix (rCCM) = 0.520 Pre fatigue >0.3Absolute<0.357Post fatigue]. In pre fatigue two PCs (cumulative s2 – 80.159%) and post fatigue three PCs (cumulative s2 – 83.845%) had eigenvalues ≥1. The x̄ h2 increased [0.802 Pre fatigue vs. 0.838 Post fatigue] and the percentage of nonredundant residuals reduced [50% Pre fatigue vs. 44% Post fatigue] from pre to post fatigue.  Conclusions. The variability and heterogeneity increase in the myoelectric signals due to fatigue. The co-activity of antagonist ES muscle is significantly sensitive to identify the deteriorating spine stability during the fatiguing Plank. Highly correlated motor unit recruitment strategies between ES and RA, providing supportive evidence to the concept of shared agonist-antagonist motoneuron pool or “Common Drive” phenomenon during fatigue.

scholarly journals IMPLEMENTASI R-SHINY UNTUK ANALISIS BIPLOT KOMPONEN UTAMA (Studi Kasus: Penggunaan Alat Kontrasepsi pada Peserta Aktif KB di Provinsi Jawa Tengah Tahun 2019)

2022 ◽  
Vol 10 (4) ◽  
pp. 499-507
Author(s):  
Andreanto Andreanto ◽  
Hasbi Yasin ◽  
Agus Rusgiyono
Keyword(s):  
Open Source Software ◽  
Birth Rate ◽  
Principal Component ◽  
Contraceptive Device ◽  
Biplot Analysis ◽  
Contraceptive Devices ◽  
The Family ◽  
R Shiny ◽  
Main Components ◽  
The Relationship

The population problem is a fairly complex and complicated problem. Therefore, Indonesia seeks to control the birth rate with the Family Planning program. The implementation of this program can be evaluated through statistical data. The statistical analysis used is biplot principal component analysis to see the relationship between districts/cities in choosing the contraceptive device/method used, the variance of each contraceptive device/method, the correlation between contraceptive devices/methods, and the superiority value of the contraceptive device/method in the population. each district/city. The problem with performing the analysis is the limitations of easy-to-use open source software. As with R, users must understand writing code to perform data analysis. Therefore, to perform a biplot analysis of the principal components, an RShiny application has been created using RStudio. The R-Shiny that has been made has many  advantages,  including  complete  results  which  include  data  display,  data transformation, SVD matrix, to graphs along with plot graph interpretation. The results of the principal component biplot analysis using R-Shiny with α =1 have the advantage of a good principal component biplot, which is 95.63%. This shows that the biplot interpretation of the main components produced can be explained well the relationship between the district/city and the contraceptive methods/devices used. 

scholarly journals Tissue-based metabolomics profiling reveals metabolic signatures and major metabolic pathways of gastric cancer

2021 ◽  
Author(s):  
Yaqin Wang ◽  
Wenchao Chen ◽  
Kun Li ◽  
Gang Wu ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Predictive Ability ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Pentose Phosphate ◽  
P Value ◽  
Pathway Enrichment Analysis ◽  
Dodecanoic Acid ◽  
Orthogonal Projections ◽  
Latent Structures

Abstract Purpose This study was aimed to screen differential metabolites between gastric cancer (GC) and paracancerous (PC) tissues and find new biomarkers of GC. Methods GC (n = 28) and matched PC (n = 28) tissues were collected and LC-MS/MS analyses were performed to detect metabolites of GC and PC tissues in positive and negative models. Principal component analysis (PCA) and orthogonal projections to latent structures-discriminate analysis (OPLS-DA) were conducted to describe distribution of origin data and general separation and estimate the robustness and the predictive ability of our mode. Differential metabolites were screened based on criterion of variables with p value < 0.05 and VIP (variable importance in the projection) > 1.0. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic power of differential metabolites. Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed to search for metabolite pathways and MetaboAnalyst was used for pathway enrichment analysis. Results Several metabolites were significantly changed in GC group compared with PC group. Thirteen metabolites with high VIP were chose and among which 1-methylnicotinamide, dodecanoic acid and sphinganine possessed high AUC values (AUC > 0.8) indicating an excellent discriminatory ability on GC. Pathways such as pentose phosphate pathway and histidine metabolism were focused based on differential metabolites demonstrating their effects on progress of GC. Conclusions In conclusion, we investigated the tissue-based metabolomics profile of GC and several differential metabolites and signaling pathways were focused. Further study is needed to verify those results.

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