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The objectives of the present study were to estimate the heritability for daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to perform genome-wide association studies (GWAS) to identify genomic regions and candidate genes influencing the genetic variation of CH4 and CH4res. Methane emission phenotypes of 743 Nellore animals belonging to 3 breeding programs were evaluated. CH4 was measured using the sulfur hexafluoride (SF6) tracer technique (which involves an SF6 permeation tube introduced into the rumen, and an appropriate apparatus on each animal), and CH4res was obtained as the difference between observed CH4 and CH4 adjusted for dry matter intake. A total of 6,252 genotyped individuals were used for genomic analyses. Data were analyzed with a univariate animal model by the single-step GBLUP method using the average information restricted maximum likelihood (AIREML) algorithm. The effects of single nucleotide polymorphisms (SNPs) were obtained using a single-step GWAS approach. Candidate genes were identified based on genomic windows associated with quantitative trait loci (QTLs) related to the 2 traits. Annotation of QTLs and identification of candidate genes were based on the initial and final coordinates of each genomic window considering the bovine genome ARS-UCD1.2 assembly. Heritability estimates were of moderate to high magnitude, being 0.42 ±â€…0.09 for CH4 and 0.21 ±â€…0.09 for CH4res, indicating that these traits will respond rapidly to genetic selection. GWAS revealed 11 and 15 SNPs that were significantly associated (P < 10-6) with genetic variation of CH4 and CH4res, respectively. QTLs associated with feed efficiency, residual feed intake, body weight, and height overlapped with significant markers for the traits evaluated. Ten candidate genes were present in the regions of significant SNPs; 3 were associated with CH4 and 7 with CH4res. The identified genes are related to different functions such as modulation of the rumen microbiota, fatty acid production, and lipid metabolism. CH4 and CH4res presented sufficient genetic variation and may respond rapidly to selection. Therefore, these traits can be included in animal breeding programs aimed at reducing enteric methane emissions across generations.

Genetic selection designed to reduce the amount of enteric methane emission from livestock is a mitigation strategy to ensure more sustainable production over generations since genetic gains are cumulative. Brazil is a large producer of beef, and the Nellore breed (Bos taurus indicus) plays a very important role in this production. There are a few studies evaluating genetic and genomic aspects of enteric methane emission in Nellore cattle. The objectives of the present study were to estimate the heritability of daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to identify genomic regions and candidate genes associated with genetic variation of these traits. The heritability estimates for CH4 and CH4res were of moderate to high magnitude (0.42 ±â€…0.09 and 0.21 ±â€…0.09, respectively). Genome-wide association analyses revealed new loci associated with methane emission in Nellore cattle on chromosomes 5, 11, 17, and 20, where 10 candidate genes were identified, 3 for CH4 and 7 for CH4res. The 2 traits possess sufficient genetic variability to be included as selection criteria in breeding programs.

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The exact accuracy of estimated breeding values can be calculated based on the prediction error variances obtained from the diagonal of the inverse of the left-hand side (LHS) of the mixed model equations (MME). However, inverting the LHS is not computationally feasible for large datasets, especially if genomic information is available. Thus, different algorithms have been proposed to approximate accuracies. This study aimed to: 1) compare the approximated accuracies from 2 algorithms implemented in the BLUPF90 suite of programs, 2) compare the approximated accuracies from the 2 algorithms against the exact accuracy based on the inversion of the LHS of MME, and 3) evaluate the impact of adding genotyped animals with and without phenotypes on the exact and approximated accuracies. Algorithm 1 approximates accuracies based on the diagonal of the genomic relationship matrix (G). In turn, algorithm 2 combines accuracies with and without genomic information through effective record contributions. The data were provided by the American Angus Association and included 3 datasets of growth, carcass, and marbling traits. The genotype file contained 1,235,930 animals, and the pedigree file contained 12,492,581 animals. For the genomic evaluation, a multi-trait model was applied to the datasets. To ensure the feasibility of inverting the LHS of the MME, a subset of data under single-trait models was used to compare approximated and exact accuracies. The correlations between exact and approximated accuracies from algorithms 1 and 2 of genotyped animals ranged from 0.87 to 0.90 and 0.98 to 0.99, respectively. The intercept and slope of the regression of exact on approximated accuracies from algorithm 2 ranged from 0.00 to 0.01 and 0.82 to 0.87, respectively. However, the intercept and the slope for algorithm 1 ranged from -0.10 to 0.05 and 0.98 to 1.10, respectively. In more than 80% of the traits, algorithm 2 exhibited a smaller mean square error than algorithm 1. The correlation between the approximated accuracies obtained from algorithms 1 and 2 ranged from 0.56 to 0.74, 0.38 to 0.71, and 0.71 to 0.97 in the groups of genotyped animals, genotyped animals without phenotype, and proven genotyped sires, respectively. The approximated accuracy from algorithm 2 showed a closer behavior to the exact accuracy when including genotyped animals in the analysis. According to the results, algorithm 2 is recommended for genetic evaluations since it proved more precise.

The genomic estimated breeding value (GEBV) represents an animal's genetic merit calculated using a combination of phenotypes, pedigree, and genomic information through a procedure known as single-step genomic best linear unbiased prediction (ssGBLUP). The accuracy of a GEBV reflects how closely it correlates with the true breeding value. However, calculating accuracies is not computationally feasible for large datasets with genomic information. In this context, methods for approximating accuracies have been proposed and implemented into genetic evaluations. This study aimed to compare 2 algorithms to approximate accuracies for ssGBLUP. In algorithm 1, genomic contributions are based on the diagonal of the genomic relationship matrix (G), combined with contributions from animal records and pedigrees. In turn, algorithm 2 combines accuracies with and without genomic information through effective record contributions. The data for this study were provided by the American Angus Association and included datasets of growth, carcass, and marbling traits. Genotypes were available for 1,235,930 animals, and the pedigree had 12,492,581 animals. We showed that algorithm 2 is better suited for approximating accuracies, as its approximations closely matched the exact accuracy values obtained from the inverse of the mixed model equations.

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Taylor's power law (TPL) describes the expected range of parameters of the mean-variance scaling relationship and has been extensively used in studies examining temporal variations in abundance. Few studies though have focused on biological and ecological covariates of TPL, while its statistical inherences have been extensively debated. In the present study, we focused on species-specific features (i.e. functional traits) that could be influential to temporal TPL. We combined field surveys of 180 fish species from 972 sites varying from small streams to large rivers with data on 31 ecological traits describing species-specific characteristics related to three main niche dimensions (trophic ecology, life history, and habitat use). For each species, the parameters of temporal TPL (intercept and slope) were estimated from the log-log mean-variance relationships while controlling for spatial dependencies and biological covariates (species richness and evenness). Then, we investigated whether functional traits explained variations in TPL parameters. Differences in TPL parameters among species were explained mostly by life history and environmental determinants, especially TPL slope. Life history was the main determinant of differences in TPL parameters and thereby aggregation patterns, with traits related to body size being the most influential, thus showing a high contrast between small-sized species with short lifespans and large-bodied migratory fishes, even after controlling for phylogenetic resemblances. We found that life history traits, especially those related to body size, mostly affect TPL and, as such, can be determinants of temporal variability of fish populations. We also found that statistical effects and phylogenetic resemblances are embedded in mean-variance relationships for fish, and that environmental drivers can interact with ecological characteristics of species in determining temporal fluctuations in abundance.

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In Mexico, there is a deficit in the production of pine resin, because it relies on natural forests only. Therefore, it is necessary to select provenances and phenotypes of potential species such as P. oocarpa. The objective was to determine the difference between provenances and the variation in resin components and quality, as well as the effect of geographic and climatic factors. Resin from five provenances was collected from southern Mexico. The percentage of rosin, turpentine and water was obtained, as well as the acidity and saponification index. P. oocarpa resin had 80.94% rosin, 7.7% turpentine and 11.49% water. The saponification and acidity index was 125.47 and 117.49 mg KOH.g-1, respectively. All variables showed differences (p ≤ 0.0001) between provenances. The provenance contributed between 6.44 and 11.71% to the total variance, the error contributed between 88.29 and 93.56%. Geographic and climatic variables only had an effect on the percentage of turpentine; the correlation was negative with altitude and longitude, but positive with temperature and precipitation. The results allow defining seed collection sites for resin plantations and orienting the selection for a P. oocarpa improvement program.

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In proteomic studies, the reliability and reproducibility of results hinge on well-executed protein extraction and digestion protocols. Here, we systematically compared three established digestion methods for macrophages, namely filter-assisted sample preparation (FASP), in-solution, and in-gel digestion protocols. We also compared lyophilization and manual lysis for liver tissue protein extraction, each of them tested using either sodium deoxycholate (SDC)- or RIPA-based lysis buffer. For the macrophage cell line, FASP using passivated filter units outperformed the other tested methods regarding the number of identified peptides and proteins. However, a careful standardization has shown that all three methods can yield robust results across a wide range of starting material (even starting with 1 µg of proteins). Importantly, inter and intra-day coefficients of variance (CVs) were determined for all sample preparation protocols. Thus, the median inter-day CVs for in-solution, in-gel and FASP protocols were respectively 10, 8 and 9%, very similar to the median CVs obtained for the intra-day analysis (9, 8 and 8%, respectively). Moreover, FASP digestion presented 80% of proteins with a CV lower than 25%, followed closely by in-gel digestion (78%) and in-solution sample preparation (72%) protocols. For tissue proteomics, both manual lysis and lyophilization presented similar proteome coverage and reproducibility, but the efficiency of protein extraction depended on the lysis buffer used, with RIPA buffer showing better results. In conclusion, although each sample preparation method has its own particularity, they are all suited for successful proteomic experiments if a careful standardization of the sample preparation workflow is carried out.

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Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However, the economic value of wheat lines is not only influenced by their additive component but also encompasses a non-additive part (e.g., additive × additive epistasis interaction). In this study, genomic prediction models were implemented in three target populations of environments (TPE) in South Asia. Four models that incorporate genotype × environment interaction (G × E) and genotype × genotype (GG) were tested: Factor Analytic (FA), FA with genomic relationship matrix (FA + G), FA with epistatic relationship matrix (FA + GG), and FA with both genomic and epistatic relationship matrices (FA + G + GG). Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests, leading us to infer that the FA + G model effectively captures certain epistatic effects. The wheat lines tested in sites in different TPE were predicted with different precisions depending on the cross-validation employed. In general, the best prediction accuracy was obtained when some lines were observed in some sites of particular TPEs and the worse genomic prediction was observed when wheat lines were never observed in any site of one TPE.

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SUMMARY: The study of the shape variation in geometric morphometrics has an important limitation known as the Pinocchio effect. The Pinocchio effect produces artifactual variances of the landmarks and implies that it is not possible to know the morphological change structure of an object, other than by dividing the landmark sets and then comparing them. This, however, involves making prior assumptions about the pattern of variation of an object. In this study, we provide a code in R to iterate over a complete set of landmarks and test all possible combinations of landmarks until deliver those landmarks associated with the largest to the smallest morphological changes. We tested this on a sample of 28 landmarks in 143 3D models of human skulls. The results indicated that this process can result in a pooled variance of a subset of landmarks that is an order of magnitude larger than that of several other regions of the skull. This method makes it possible to describe the pattern of variation of any 2D or 3D object represented by fixed landmarks, to distinguish the shape features that have more morphological dispersion, and to avoid any aprioristic assumptions about how the morphological changes of an object behave.

El estudio de la variación de la forma en morfometría geométrica tiene una limitación importante conocida como efecto Pinocho. El efecto Pinocho produce variaciones artefactos de los puntos de referencia e implica que no es posible conocer la estructura del cambio morfológico de un objeto, salvo dividiendo los conjuntos de puntos de referencia y luego comparándolos. Sin embargo, esto implica hacer suposiciones previas sobre el patrón de variación de un objeto. En este estudio, proporcionamos un código en R para iterar sobre un conjunto completo de puntos de referencia y probar todas las combinaciones posibles de puntos de referencia hasta entregar aquellos puntos de referencia asociados con los cambios morfológicos más grandes a los más pequeños. Probamos esto en una muestra de 28 puntos de referencia en 143 modelos 3D de cráneos humanos. Los resultados indicaron que este proceso puede dar como resultado una variación combinada de un subconjunto de puntos de referencia que es un orden de magnitud mayor que el de varias otras regiones del cráneo. Este método permite describir el patrón de variación de cualquier objeto 2D o 3D representado por puntos de referencia fijos, distinguir las características de forma que tienen más dispersión morfológica y evitar suposiciones apriorísticas sobre cómo se comportan los cambios morfológicos de un objeto.

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This study aims to evaluate the performance of industrial engineering programs across various Higher Education Institutions (HEIs) in Colombia, focusing on the SaberPRO test outcomes from 2016 to 2018. The evaluation considers three primary dimensions: the type of funding (public vs. private HEIs), geographical region, and program accreditation status. The methodology involved gathering and analyzing Saber Pro test results from students enrolled in industrial engineering programs at 82 Colombian HEIs during the specified period. In Colombia, the SaberPRO Exam, administered by the Colombian Institute for the Evaluation of Education (ICFES), is a critical measure for assessing the quality of future industrial engineering graduates. This research employs an analytical framework that includes Analysis of Variance (ANOVA) and hypothesis testing for mean comparisons to scrutinize the performance of these programs. Findings reveal notable disparities in performance between public and private institutions and between accredited and non-accredited programs. Additionally, through Multiple Factor Analysis (MFA), the study identifies the competencies with the highest discriminative capacity, recognizing 15 exemplary programs out of the 82 evaluated.

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Abstract In soybean breeding program, continuous selection pressure on traits response to yield created a genetic bottleneck for improvements of soybean through hybridization breeding technique. Therefore an initiative was taken to developed high yielding soybean variety applying mutation breeding techniques at Plant Breeding Division, Bangladesh Institute of Nuclear Agriculture (BINA), Bangladesh. Locally available popular cultivar BARI Soybean-5 was used as a parent material and subjected to five different doses of Gamma ray using Co60. In respect to seed yield and yield attributing characters, twelve true breed mutants were selected from M4 generation. High values of heritability and genetic advance with high genotypic coefficient of variance (GCV) for plant height, branch number and pod number were considered as favorable attributes for soybean improvement that ensure expected yield. The mutant SBM-18 obtained from 250Gy provided stable yield performance at diversified environments. It provided maximum seed yield of 3056 kg ha-1 with highest number of pods plant-1 (56). The National Seed Board of Bangladesh (NSB) eventually approved SBM-18 and registered it as a new soybean variety named 'Binasoybean-5' for large-scale planting because of its superior stability in various agro-ecological zones and consistent yield performance.

Resumo No programa de melhoramento da soja, a pressão pela seleção contínua para a resposta das características de rendimento criou um gargalo genético para melhorias da soja por meio da técnica de melhoramento por hibridação. Portanto, foi desenvolvida uma variedade de soja de alto rendimento, aplicando técnicas de reprodução por mutação, na Divisão de Melhoramento de Plantas, no Instituto de Agricultura Nuclear de Bangladesh (BINA), em Bangladesh. A cultivar popular BARI Soybean-5, disponível localmente, foi usada como material original e submetida a cinco doses diferentes de raios gama usando Co60. Em relação ao rendimento de sementes e às características de atribuição de rendimento, 12 mutantes genuínos foram selecionados a partir da geração M4. Altos valores de herdabilidade e avanço genético com alto coeficiente de variância genotípico (GCV) para altura da planta, número de ramos e número de vagens foram considerados atributos favoráveis ​​ao melhoramento da soja, garantindo, assim, a produtividade esperada. O mutante SBM-18, obtido a partir de 250Gy, proporcionou desempenho de rendimento estável em ambientes diversificados e produtividade máxima de sementes de 3.056 kg ha-1 com o maior número de vagens planta-1 (56). O Conselho Nacional de Sementes de Bangladesh (NSB) finalmente aprovou o SBM-18 e o registrou como uma nova variedade de soja, chamada 'Binasoybean-5', para plantio em larga escala por causa de sua estabilidade superior em várias zonas agroecológicas e desempenho de rendimento consistente.

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Abstract In soybean breeding program, continuous selection pressure on traits response to yield created a genetic bottleneck for improvements of soybean through hybridization breeding technique. Therefore an initiative was taken to developed high yielding soybean variety applying mutation breeding techniques at Plant Breeding Division, Bangladesh Institute of Nuclear Agriculture (BINA), Bangladesh. Locally available popular cultivar BARI Soybean-5 was used as a parent material and subjected to five different doses of Gamma ray using Co60. In respect to seed yield and yield attributing characters, twelve true breed mutants were selected from M4 generation. High values of heritability and genetic advance with high genotypic coefficient of variance (GCV) for plant height, branch number and pod number were considered as favorable attributes for soybean improvement that ensure expected yield. The mutant SBM-18 obtained from 250Gy provided stable yield performance at diversified environments. It provided maximum seed yield of 3056 kg ha-1 with highest number of pods plant-1 (56). The National Seed Board of Bangladesh (NSB) eventually approved SBM-18 and registered it as a new soybean variety named Binasoybean-5 for large-scale planting because of its superior stability in various agro-ecological zones and consistent yield performance.

Resumo No programa de melhoramento da soja, a pressão pela seleção contínua para a resposta das características de rendimento criou um gargalo genético para melhorias da soja por meio da técnica de melhoramento por hibridação. Portanto, foi desenvolvida uma variedade de soja de alto rendimento, aplicando técnicas de reprodução por mutação, na Divisão de Melhoramento de Plantas, no Instituto de Agricultura Nuclear de Bangladesh (BINA), em Bangladesh. A cultivar popular BARI Soybean-5, disponível localmente, foi usada como material original e submetida a cinco doses diferentes de raios gama usando Co60. Em relação ao rendimento de sementes e às características de atribuição de rendimento, 12 mutantes genuínos foram selecionados a partir da geração M4. Altos valores de herdabilidade e avanço genético com alto coeficiente de variância genotípico (GCV) para altura da planta, número de ramos e número de vagens foram considerados atributos favoráveis ao melhoramento da soja, garantindo, assim, a produtividade esperada. O mutante SBM-18, obtido a partir de 250Gy, proporcionou desempenho de rendimento estável em ambientes diversificados e produtividade máxima de sementes de 3.056 kg ha-1 com o maior número de vagens planta-1 (56). O Conselho Nacional de Sementes de Bangladesh (NSB) finalmente aprovou o SBM-18 e o registrou como uma nova variedade de soja, chamada Binasoybean-5, para plantio em larga escala por causa de sua estabilidade superior em várias zonas agroecológicas e desempenho de rendimento consistente.

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Integral controllers are commonly employed in astronomical adaptive optics. This work presents a novel tuning procedure for integral controllers in adaptive optics systems which relies on information about the measured disturbances. This tuning procedure consists of two main steps. First, it models and identifies measured disturbances as continuous-time-damped oscillators using Whittles´s likelihood and the wavefront sensor output signal. Second, it determines the integral controller gain of the adaptive optics system by minimizing the output variance. The effectiveness of this proposed method is evaluated through theoretical examples and numerical simulations conducted using the Object-Oriented Matlab Adaptive Optics toolbox. The simulation results demonstrate that this approach accurately estimates the disturbance model and can reduce the output variance. Our proposal results in improved performance and better astronomical images even in challenging atmospheric conditions. These findings significantly contribute to adaptive optics system operations in astronomical observatories and establish our procedure as a promising tool for fine-tuning integral controllers in astronomical adaptive optics systems.

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ABSTRACT In this study, some transformation methods that are applied when the assumptions of analysis of variance are not met are evaluated in terms of type I error rate and the test power, under circumstances with different distributions, number of groups, number of observations, variance ratios, and different standard deviation differences. The data set used in the study consisted of random numbers generated from N (0,1), and χ2(3) distributions using the random function of the Numpy library in the Python programming language. The logarithmic, square root and root transformations were evaluated on ANOVA based on simulation combinations. It was observed that the transformation techniques of taking the square root after adding 0.5 and 0.375 to the data were relatively more reliable compared to other transformations in terms of type I error rate. However, in every case, type I error rate determined at the beginning of the experiment increased both before and after the transformation was applied. In particular, interestingly, the third and fourth degree root transformations gave better results of test power in the right skewed distribution. In addition, we compared the transformation techniques in question to determine the normality of the data and the homogeneity of variances by a real data.

RESUMO Neste estudo, alguns métodos de transformação, aplicados quando as premissas da análise de variância não são cumpridas, são avaliados em termos de taxa de erro tipo I e poder de teste, em circunstâncias com diferentes distribuições, número de grupos, número de observações, razões de variância e diferenças de desvio-padrão. O conjunto de dados utilizados no estudo consistiu em números aleatórios gerados a partir das distribuições N(0,1) e χ2(3), utilizando a função aleatória da biblioteca Numpy, na linguagem de programação Python. As técnicas de transformação logarítmica, raiz quadrada e raiz foram avaliadas na ANOVA, com base em combinações de simulação. Observou-se que as técnicas de transformação de tomar a raiz quadrada após adicionar 0,5 e 0,375 aos dados foram relativamente mais confiáveis em comparação com outras transformações em termos de taxa de erro tipo I. No entanto, em todos os casos, a taxa de erro tipo I determinada no início do experimento aumentou tanto antes quanto depois da aplicação da transformação. Em particular, curiosamente, as transformações de raiz de terceiro e de quarto grau deram melhores resultados de poder de teste na distribuição assimétrica à direita. Além disso, foram comparadas as técnicas de transformação em questão para determinar a normalidade dos dados e a homogeneidade das variâncias por meio de dados reais.

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Sociability is a fundamental trait that social animals need to survive and reproduce in societies. Sociability predicts how an individual can consistently interact with its conspecifics across time and situations. By studying capuchin monkeys (Sapajus libidinosus), a neotropical primate with complex social behavior and high cognitive capacity, our research aims to analyze the development of the social axis of personality of immature individuals, from birth to the third year of life. We studied wild monkeys belonging to a group with infants, juveniles, and adults of both sexes that inhabits northeastern Brazil. We analyzed the behavior of 12 immature capuchins (6 males and 6 females) in 94 h of videos recorded weekly from birth until 36 months, through daily focal sampling. We verified whether there was intraindividual consistency throughout development by fitting regression models for the effect of age on initiating affiliative social behaviors, controlling for monkey identity and sex. Our results indicate that the individuals of this study exhibit high variation in the initiation of behaviors at the beginning of infancy; there was low repeatability and high intra-individual variation during the first 3 years of life of these individuals, indicating that the social personality is not consolidated in this period. Immature females were more sociable than immature males. Therefore, differences in sociability in early life of bearded capuchin monkeys are best explained by sex rather than personality. We suggest that the high initial behavioral variation in the social axis of personality allows for plasticity influenced by the environment throughout development. The high sociability of females in infancy may be related to female philopatry and their high sociability in adulthood.

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Shoulder pain is one of the most common musculoskeletal conditions, and for people over 40 years old, it represents the musculoskeletal pain with the greatest impact on quality of life. Psychological factors, such as fear-avoidance beliefs, are associated with musculoskeletal pain, and several studies suggest that they can influence various treatment outcomes. Our objective was to explore the cross-sectional association between fear-avoidance beliefs and shoulder pain intensity and disability in subjects with chronic shoulder pain. A cross-sectional study was conducted, and 208 participants with chronic unilateral subacromial shoulder pain were recruited. The shoulder pain and disability index assessed pain intensity and disability. The Spanish fear-avoidance components scale assessed the presence of fear-avoidance beliefs. The association between fear-avoidance beliefs and pain intensity and disability was analyzed by means of multiple linear regression models and proportional odds models, reporting odds ratios and 95% confidence intervals. Shoulder and pain disability scores were significantly associated with fear-avoidance beliefs (p < 0.0001, adjusted R-square 0.93, multiple linear regression). There was no evidence of an association between sex and age in this study. The regression coefficient for shoulder pain intensity and disability score was 0.67446. The proportional odds model showed an odds ratio of 1.39 (1.29-1.50) for shoulder pain intensity and disability total score. This study suggests that greater levels of fear-avoidance beliefs are associated with greater levels of shoulder pain and disability in adults with chronic shoulder pain.

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The infrared spectrum of bovine milk is used to predict many interesting traits, whereas there have been few studies on goat milk in this regard. The objective of this study was to characterize the major sources of variation in the absorbance of the infrared spectrum in caprine milk samples. A total of 657 goats belonging to 6 breeds and reared on 20 farms under traditional and modern dairy systems were milk-sampled once. Fourier-transform infrared (FTIR) spectra were taken (2 replicates per sample, 1314 spectra), and each spectrum contained absorbance values at 1060 different wavenumbers (5000 to 930 × cm-1), which were treated as a response variable and analyzed one at a time (i.e., 1060 runs). A mixed model, including the random effects of sample/goat, breed, flock, parity, stage of lactation, and the residual, was used. The pattern and variability of the FTIR spectrum of caprine milk was similar to those of bovine milk. The major sources of variation in the entire spectrum were as follows: sample/goat (33% of the total variance); flock (21%); breed (15%); lactation stage (11%); parity (9%); and the residual unexplained variation (10%). The entire spectrum was segmented into five relatively homogeneous regions. Two of them exhibited very large variations, especially the residual variation. These regions are known to be affected by the absorbance of water, although they also exhibited wide variations in the other sources of variation. The average repeatability of these two regions were 45% and 75%, whereas for the other three regions it was about 99%. The FTIR spectrum of caprine milk could probably be used to predict several traits and to authenticate the origin of goat milk.

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SUMMARY: Distal radius fractures are one of the most common orthopedic injuries encountered by orthopedic surgeons. Correction of dorsal tilt and radial height is essential to restore normal biomechanics of the wrist joint. Comprehensive knowledge of the morphometry of the distal radius of the local population becomes critical for the treating surgeon. This study aims to report the morphometry of the distal radius in the Anatolian population and compare it with similar studies in other races and humans. Radiographs of one hundred and twenty-four people were included in the study. Four radiological parameters were examined on all radiographs: radial height, radial tilt, ulnar variance, and palmar tilt. Radial tilt was 23.35°±1.96; palmar tilt was 15.7°±2,87 radial height (mm) was 10.55±4.34, ulnar variance (mm) was 0.32±1.79. The highest rate of negative ulnar variance was found. According to the study's results, reference data varying by race for anatomical fit should be considered in treating DER injuries.

Las fracturas de la parte distal del radio son probablemente las lesiones ortopédicas más comunes que encuentran los cirujanos ortopédicos. La corrección de la inclinación dorsal y la altura radial es esencial para restaurar la biomecánica normal de la articulación de la muñeca. El conocimiento integral de la morfometría del radio distal de la población local es importante para el cirujano tratante. Este estudio tuvo como objetivo reportar la morfometría de la parte rdistal del radio en la población de Anatolia y compararla con estudios similares en otras razas y humanos. Se incluyeron ciento veinticuatro radiografías simples consecutivas de la articulación de la muñeca. Se examinaron cuatro parámetros radiológicos: altura radial, inclinación radial, variación ulnar e inclinación palmar. El ángulo de inclinación radial fue de 23,35±1,96; el ángulo de inclinación palmar fue de 15,7±, la altura radial (mm) fue de 10,55±4,34, la varianza ulnar (mm) fue de 0,32±1,79. Se encontró la tasa más alta de varianza ulnar negativa (43,5%). Los resultados de este estudio deben tenerse en consideración al tratar fracturas de la parte distal del radio, con datos de referencia que varían según la raza para el ajuste anatómico.

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The highest prevalence of mental illnesses and mental suffering in contemporary society has raised awareness of the theme and their connection to work. In Brazil, university servants (professors and technical-administrative staff) are a focused occupational group. We developed this research with the objective of exploring the relationship between the perception of working conditions and the mental health of these servants. Structured questionnaires were applied to 285 servants, 33.5% being professors and 66.5% technical-administrative staff. Regarding working conditions, the questionnaires included items that measured 15 primary factors and questions about their contracts and legal conditions. To evaluate mental health, the participants answered a questionnaire about common psychic symptoms, negative and positive affects, self-esteem, and family-work conflict. We composed groups of participants according to their mental health indicator scores (cluster analysis), and after that, we compared the mean scores in working conditions for the groups. Then, we found that the mean scores of 13 from the 15 working condition factors were significantly different between the mental health groups. Our results showed the importance of improving working conditions in universities to prevent mental illnesses. Understanding the content of each working condition factor presents potency to contribute to defining the priorities among different aspects of working conditions.

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Sometimes, analytical chemicals forget that the measurement process begins with the selection of the sample; thus, it must be understood that the measurement uncertainty is constituted by the association of the uncertainty arising from the sampling and the uncertainty arising from the traditional analytical process, that which is carried out in the laboratory. The analytical process is well-controlled, so its uncertainty is well defined; however, the uncertainty arising from sampling, for not having this controlled environment, is often not evident, so that there is still no culture to consider it for the calculation of measurement uncertainty. This study discusses the importance of the sampling uncertainty concerning the analytical uncertainty and details the current approaches available in the literature, such as the classical analysis of variance, the robust analysis of variance, and the range statistics. Moreover, this work highlights the recent manuscripts that are using these mentioned approaches, correlating them to the matrices, chemical and physical-chemical analytes, and analytical techniques. Finally, some case studies using the uncertainty information in compliance assessment show that the measurement uncertainty arising from sampling in chemical and physicochemical analyses cannot always be neglected.

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ABSTRACT: This study analyzed the response of the Bartlett test as a function of sample size and to define the optimal sample size for the test with soybean grain yield data. Six experiments were conducted in a randomized block design with 20 or 30 cultivars and three repetitions. Grain yield was determined per plant, totaling 9,000 sampled plants. Next, sample scenarios of 1, 2, ..., 100 plants were simulated and the optimal sample size was defined via maximum curvature points. The increase in sampled plants per experimental unit favors Bartlett test's precision. Also, the sampling of 17 to 20 plants per experimental unit is enough to maintain the accuracy of the test.

RESUMO: Os objetivos deste estudo foram analisar a resposta do teste de Bartlett em função do tamanho de amostra e definir o tamanho amostral ótimo para o teste com dados de produtividade de grãos de soja. Foram conduzidos seis experimentos em delineamento de blocos ao acaso com 20 ou 30 cultivares e três repetições. A produtividade de grãos foi definida por planta, totalizando 9.000 plantas amostradas. Logo, foram simulados cenários amostrais de 1, 2, ..., 100 plantas e definido o tamanho amostral ótimo via pontos de máxima curvatura. O aumento de plantas amostradas por unidade experimental favorece a precisão do teste de Bartlett. Além disso, a amostragem de 17 a 20 plantas por unidade experimental é suficiente para manter a acurácia do teste.

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The growth differentiation factor 9 (GDF9) gene plays a vital role in the growth and maturation of ovarian follicles in laying hens. However, its messenger ribonucleic acid (mRNA) expression levels in preovulatory ovarian follicles of indigenous chickens remain poorly understood. The study aimed to identify the association between egg weight and egg quality traits, ovarian follicles morphology, and mRNA expression levels of the GDF9 gene in pre-ovulatory ovarian follicles of the South African Potchefstroom Koekoek chicken breed. The correlation results showed that egg weight (EW) had a positively high significant correlation (p<0.01) with egg width (EWD), yolk weight (YW), shell surface area (SSA), albumen weight (AW), albumen ratio (AR) and egg volume (EV), and a positive significant correlation (p<0.05) with egg length (EL). The Student's T-test results revealed that the numbers of large yellow follicles were significantly lower (p<0.05) than those of small yellow follicles. ANOVA findings showed that there was a significant difference (p<0.05) in the average weight of the large yellow follicles. The quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) findings indicated that there were significant differences (p<0.05) in the mRNA expression levels of the GDF9 gene in preovulatory ovarian follicles of the Potchefstroom Koekoek chicken breed. The mRNA expression was more abundant in F1 and F4 than in other ovarian follicles.(AU)

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