Towards Higher Education for Sustainable Development in BRICS: Focus on Brazil and South Africa

Scholarly literature informs that education for sustainable development (ESD) has become a significant educational initiative to address global challenges in the past decades. However, academic attention was mainly devoted to primary and secondary education. Some scholars report that the main focus on these two levels of education has averted scholarly attention from research exploring the relationship between higher education and sustainable development (SD). Academic dialogue about ESD in higher education has only recently gained momentum. Although all levels of education have an essential role to play in sustainability, the role of higher education is critical as higher education institutions (HEIs) are responsible for ensuring that future leaders understand the needs of the present and future. This responsibility is delegated to HEIs since they educate professionals who will take up leadership positions within society and incorporate sustainability into their organisations’ operations. In addition, the commitment of HEIs to sustainability serves as an example to other institutions. It is evident from the findings that maximising the implementation of ESD in higher education first calls for thorough identification of challenges limiting such implementation. Driven by the need to fill the gap in the existing literature, this study, based on systematic document analysis, brings attention to challenges associated with implementing ESD in institutions under investigation in the two BRICS countries, namely Brazil and South Africa. The two-folded research purpose was to (a) systematically examine relevant documents to explore the effectiveness of HEIs in South Africa and Brazil in implementing ESD and (b) provide recommendations for how HEIs in both contexts can enhance the implementation of ESD

Genomics of heifer pregnancy, days open, and days to conception in Red Angus heifers

Although it is challenging to collect information on reproductive traits, fertility traits are believed to play a significant role in the growth of the beef industry and bring revenue to the producers. It has been challenging to make genetic improvement of fertility traits because of scarce records and their low heritability. The joint analyses of economic and indicator traits provided much information for the analysis of other production traits, resulting in favorable improvement. The same method can be applied to reproductive traits to increase prediction accuracy. Furthermore, the ubiquity of high-throughput genotypes and the development of advanced computational methods give hope that there is a possibility of determining the genetic influence on fertility traits. The advancement in phenotypic collection technology eases the keeping of records on both economic and indicator fertility traits. Also, it allows the development of new traits to be analyzed while reducing the cost of data availability. Heifer Pregnancy (HP) - the ability for a heifer to conceive by the end of the breeding season; Days Open (DO) - days of breeding season a heifer remained open; and Days to Conception (DC) -- the number of days it took for a heifer to get pregnant, are easy to measure fertility traits with enough information to make beef reproductive genetic improvement in the industry. The objective of the current study is to identify DNA markers tagging genes influencing HP, DC, and DC among 18,039 Red Angus heifers, find the genetic relationship among those traits, and creating the genomic predictions of days to conception and days open. The results show a small heritability of 0.119 to 0.131, 0.10 to 0.102, and 0.0749 to 0.112 for HP, DO, and DC, respectively. The DC model resulted in higher accuracy than other models. There was a high correlation between HP and DO (r = - 0.61 and 0.85 from the linear model and the liability scale model, respectively). The de-regressed estimated breeding value (EBV) genomewide association (GWAS) yielded 58 and 2 significant SNPs at suggestive significant level (pvalue [less than] 1.0e-05) for HP and DC, respectively. This study found GRID2 and ZMIZ1 genes to be associated with heifer pregnancy, and it has been speculated that the central nervous system related genes ontology and the hormones it controls might suggest the physiology behind some of the reproductive differences. The present study confirms the low heritability status of fertility traits and shows the possibilities of genetic enhancement based on the obtained accuracies. The identified genes and gene terms will serve as starting points for future studies that might focus on different phenotypes while reducing the cost of phenotyping and improving the accuracy of fertility traits genomic predictions.Includes bibliographical references

Lifestyle risk score: handling missingness of individual lifestyle components in meta-analysis of gene-by-lifestyle interactions

Recent studies consider lifestyle risk score (LRS), an aggregation of multiple lifestyle exposures, in identifying association of gene-lifestyle interaction with disease traits. However, not all cohorts have data on all lifestyle factors, leading to increased heterogeneity in the environmental exposure in collaborative meta-analyses. We compared and evaluated four approaches (Naive, Safe, Complete and Moderator Approaches) to handle the missingness in LRS-stratified meta-analyses under various scenarios. Compared to "benchmark" results with all lifestyle factors available for all cohorts, the Complete Approach, which included only cohorts with all lifestyle components, was underpowered due to lower sample size, and the Naive Approach, which utilized all available data and ignored the missingness, was slightly inflated. The Safe Approach, which used all data in LRS-exposed group and only included cohorts with all lifestyle factors available in the LRS-unexposed group, and the Moderator Approach, which handled missingness via moderator meta-regression, were both slightly conservative and yielded almost identical p values. We also evaluated the performance of the Safe Approach under different scenarios. We observed that the larger the proportion of cohorts without missingness included, the more accurate the results compared to "benchmark" results. In conclusion, we generally recommend the Safe Approach, a straightforward and non-inflated approach, to handle heterogeneity among cohorts in the LRS based genome-wide interaction meta-analyses.Functional Genomics of Systemic Disorder

Densidade de nuvens pontos UAV-Lidar na estimativa da altura de eucalipto em diferentes sistemas de manejo

Orientador: Prof. Dr. Carlos Roberto SanquettaCoorientadora: Profa. Dra. Ana Paula Dalla CorteDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Agrárias, Programa de Pós-Graduação em Engenharia Florestal. Defesa : Curitiba, 23/02/2021Inclui referências: p. 44-55Área de concentração: Manejo FlorestalResumo: O manejo florestal evoluiu para a fronteira 4.0, a qual utiliza tecnologias a seu favor, destas, destacam-se os Lasers scanners, os quais podem mensurar a floresta. Contudo, essa ferramenta é onerosa, de modo que uma alternativa mais barata e de alta densidade de pontos é a união destes sensores com veículos aéreos não tripulados (UAV-Lidar). Logo, deve-se verificar a influência da densidade de pontos na acurácia das métricas da floresta. Neste sentido, objetivou-se avaliar o desempenho de diferentes densidades de nuvens de pontos UAV-Lidar na estimativa da altura individual de Eucalyptus benthamii em sistemas agrosilvipastoris, implantados em 2012. O estudo foi conduzido na fazenda Canguiri, Pinhais, Paraná, na qual foi realizado o censo das árvores, medindo-se o diâmetro e altura. Os dados UAV-Lidar foram coletados com o sistema GatorEye. A nuvem de pontos foi pré-processada no LASTOOLS, onde foi unida e recortada para a área de estudo. Posteriormente, em linguagem de programação R, esta foi homogeneizada em nove diferentes densidades: 2.000, 1.500, 1.000, 500, 250, 100, 50, 25 e 5 pts/m². Estas nove nuvens de pontos foram classificadas quanto ao solo e normalizadas, favorecendo a determinação dos modelos digitais de terreno, superfície e copas. Foi extraído a altura máxima das árvores, com base no pixel mais alto presente no modelo digital de copas e na nuvem de pontos normalizada. As alturas derivadas foram avaliadas em relação as alturas medidas em campo pelo coeficiente de correlação de Pearson, raiz quadrada do erro médio, viés, análise gráfica e teste t pareado. A densidade de 2.000 pts/m² melhor representou o perfil da árvore e o solo, obtendo maior correlação (0,79) e menor RMSE (14,55 %). Em todas as densidades, as alturas derivadas e mensuradas foram estatisticamente semelhantes. A redução da densidade de pontos ocasionou divergências no perfil da árvore e modelo de copas, não havendo grandes diferenças no modelo digital do terreno. O sistema GatorEye foi acurado para derivar a altura total do Eucalyptus benthamii. Até 100 pts/m² não há perda de acurácia na derivação da altura.Abstract: The 4.0 frontier has arrived in the forest management, employing technologies in its benefit, among them, Lasers scanners, which measure the forest. However, this tool is expensive, so a cheaper and high point density alternative is the union of these sensors with unmanned aerial vehicles (UAV-Lidar). Therefore, the point density influence on the forest metrics' accuracy should be verified. We evaluate the performance of UAV-Lidar's different point cloud densities in the individual height of the Eucalyptus benthamii estimates on different Crop-Livestock-Forest systems, implemented in 2012. It was conducted at Canguiri Farm, Pinhais, Paraná, where the census of the trees was performed, measuring the diameter and height. The UAV-Lidar data were collected with the GatorEye system. The Point Cloud was pre-processing in the LASTOOLS software, where it was merged and clipped into the study area. Then in R programming language, it was thinned in nine densities: 2,000, 1,500, 1,000, 500, 250, 100, 50, 25 and 5 pts/m². The point clouds were classified in ground and normalized, improving the digital models of terrain, surface, and crown. The highest tree height was extracted, based on the highest pixel on the digital crown model and the normalized point cloud. Heights were evaluated by Pearson's correlation, rootsquare- mean error, bias, graphic analysis, and paired t-test. The processing was performed in R language. The tree's profile and the soil were better represented by 2,000 returns.m-², obtaining higher correlation (0.79) and lower RMSE (14.55 %). At all densities, the derived and measured heights were statistically similar. The point cloud density's reduction produced variances in tree profile and CHM, with few differences in DTM. The GatorEye system was accurate to derive the Eucalyptus benthamii's total height. There is no accuracy decrease in the height's derivation until 100 returns.m-²