The study employed multi-variate methods to generate vulnerability maps for acid sulfate soils (AS) in the Norrbotten county of Sweden. In this study, the relationships between the reclassified datasets and each biogeochemical element was carefully evaluated with ANOVA Kruskal Wallis and PLS analysis. The sta-tistical results of ANOVA Kruskall-Wallis provided us a useful knowledge of the relationships of the preliminary vulnerability ranks in the classified datasets ver-sus the amount of each biogeochemical element. Then, the statistical knowledge and expert knowledge were used to generate the final vulnerability ranks of AS soils in the classified datasets which were the input independent variables in PLS analyses. The results of Kruskal-Wallis one way ANOVA and PLS analyses showed a strong correlation of the higher levels total Cu2+, Ni2+ and S to the higher vulnerability ranks in the classified datasets. Hence, total Cu2+, Ni2+ and S were chosen as the dependent variables for further PLS analyses. In particular, the Variable Importance in the Projection (VIP) value of each classified dataset was standardized to generate its weight. Vulnerability map of AS soil was a result of a lineal combination of the standardized values in the classified dataset and its weight. Seven weight sets were formed from either uni-variate or multi-variate PLS analyses. Accuracy tests were done by testing the classification of measured pH values of 74 soil profiles with different vulnerability maps and evaluating the areas that were not the AS soil within the groups of medium to high AS soil probability in the land-cover and soil-type datasets. In comparison to the other weight sets, the weight set of multi-variate PLS analysis of the matrix of total Ni2+& S or total Cu2+& S had the robust predictive performance. Sensitivity anal-ysis was done in the weight set of total Ni2+& S, and the results of sensitivity analyses showed that the availability of ditches, and the change in the terrain sur-faces, the altitude level, and the slope had a high influence to the vulnerability map of AS soils. The study showed that using multivariate analysis was a very good approach methodology for predicting the probability of acid sulfate soil.

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Several papers have reported the enhancing effects of opiate peptides, like Met-enkephalin, on natural killer (NK) cell activity. We examined the actions of Met-enkephalin on NK activity in blood obtained from 18 different donors, of different ages, many of them on several occasions, at several ratios of effector to target cells, several concentrations of peptide, in several types of flasks, with the purity and identity of the pentapeptide verified by chromatography, in a system responsive to interferon, and with results calculated in different ways. No significant increase was found for the peptide for any ratio of cells, any concentration of peptide, or any single subject, even when the subjects with the lowest baseline NK cell activity were used or when the subjects were more than 60 years old. Instead of an increase, the combined results for all subjects at all ratios at all concentrations of Met-enkephalin showed an overall decrease of 31.3 % specific cytotoxicity. These results fail to support the reports of an enhancing effect of Met-enkephalin on NK cell activity.

The first reported case of COVID-19 in Tennessee (TN) occurred on March 5, 2020, growing to 580,809 cases state-wide by the end of 2020. A GIS dashboard was developed using data from the TN Department of Health to communicate state-wide COVID-19 spread, and a relationship between pandemic development and rurality was observed during the first wave (through September 2020), noted in other US and global research. Because > 90% of TN counties are designated rural or mixed-rural, we examined metrics to describe development as it relates to rurality. Metrics included days to the first case/hospitalization/fatality, days between state and county peak, and days to an incidence rate of ten per 100,000. Metrics were compared within different classes of rurality, using seven rurality classification schemes. Significant differences were noted in four of the five metrics between classes of rurality. Rural counties in TN experienced significant lags to the first case, hospitalization, and fatality, and the peak cases in rural counties were delayed relative to urban counties when outlier counties with early state prison outbreaks were excluded. In rural TN counties, regardless of rurality definition, cases, hospitalizations, and fatalities were slower to appear. However, once community spread was established, rurality no longer had a protective effect.

The production environment is known to have a large influence on extensively managed beef cows. A better understanding of the relationship between the beef cow and her environment should be useful in the pursuit of improving beef cow efficiency. The influence of the production environment on the efficiency of extensively managed Bonsmara cows was investigated through a series of research objectives. It was found that VEGMAP’s bioregion classification system can be used to describe the South African beef production regions. The environmental characteristics with the potential to influence beef cow efficiency were identified as temperature, rainfall, cation exchange capacity, soil pH, soil organic carbon, soil P and grazing capacity. A dataset was created that contains the historical cow production records for every Bonsmara breeder. GIS tools were then used to link the cow production records with the production region in which the farm is located, as well as the environmental characteristics for that specific location. The combined dataset was then statistically analysed to investigate the research objectives. The influence of the geographic location, production region and breeder on Bonsmara production traits was investigated by cluster analysis and ANOVA. Results from ANOVA indicate that production region has a statistically significant (p < 0.05) influence on production traits. The influence of the breeders on the same production traits was, however, statistically much larger (p < 0.0001) than production region. Bonsmara production traits are therefore influenced to a greater extent by the breeders rather than production environment. Stepwise regression analysis was used to determine the influence of the combined environment on production traits. The combined environment has a statistically significant (p < 0.0001) influence on all the production traits. The results indicate that the extent of the influence of the environment on production change through the growth curve. The environment’s influence was the greatest at weaning (9%) and yearling age (10%). Bonsmara weaning and yearling weights therefore show the largest potential for manipulation through management. The influence of individual environmental characteristics on all the Bonsmara cow production traits was then investigated by the same stepwise regression analysis. Most of the environmental characteristics were found to have a statistically significant (p < 0.0001) influence on the production traits. Rainfall and temperature had the largest influence on Bonsmara production traits. The negative influence of rainfall was attributed to the influence of rainfall on the quality of the grazing. The influence of temperature on production traits was small. The small negative influence of temperature could indicate that Bonsmara cows are well adapted to the main South African beef production regions. Finally, the relationship between Bonsmara cow size and reproduction was investigated by linear regression analysis. Results indicate that larger Bonsmara cows are to some extent more reproductive than smaller cows. The study confirmed that production environment influences beef cow efficiency. Bonsmara breeders however have a much larger influence on the efficiency of their cows through the implementation of management practices and breeding objectives. / Dissertation (MSc(Agric))--University of Pretoria, 2012. / Animal and Wildlife Sciences / unrestricted

The purpose of this study was to determine factors that impact the final grades of full admission and developmental students who were enrolled in selected 22 undergraduate business courses during the fall 2015 and spring 2016 semesters. Also, this study examined the interaction of students’ ethnicity, gender, age, and classification on their final course grades in selected business courses at a rural public HBCU. The research design for this study was casual-comparative research. A 2X2 and a 2X4 factorial ANOVA was used to determine whether there was a main effect on students’ final grades considering each independent variable. Out of a population of 393 students enrolled, 320 students participated in this study. After the data were collected and analyzed, the researcher determined that there was a statistically significant relationship between student’s final grade and course delivery, ethnicity, and classification. There was no statistically significant interaction on student’s final grades between course delivery and student admission status, gender, age, ethnicity, and classification. Conclusion and recommendations based on the findings in this study indicated that students attending the rural public HBCU and enrolled in business courses that offered the same courses in both face-toace and online formats performed better in face-toace courses than in the online courses.

This paper studies castor oil’s potential as a biodiesel feedstock. Base-catalyzed transesterification batch reactions were conducted at various experimental conditions while measuring the concentration of the reaction components over time. A gas chromatograph with a flame-ionization detector analyzed these samples. A factorial design of experiments was used to determine how conversion was affected by reaction temperature, sodium methoxide concentration, and ratio of methanol to oil. Conversion was maximized (0.9964) at 30 °C, 0.5% catalyst, and 9:1 molar ratio. The concentration data were used to study the reaction kinetics. Modeling the reaction as three equilibria yielded six rate constants. These values indicate that castor oil transesterifies faster than soybean oil. The fuel properties were determined by ASTM D 6751. Viscosity was excessively high, but specifications were met for the remaining tests. Despite the promising yield and kinetics of the reaction, the fuel viscosity limits castor oil’s viability as a biodiesel feedstock.

Syftet med studien är att undersöka autentisk femvertising från ett kvinnligt konsumentperspektiv. Detta görs genom att utforma en generaliserad modell av vad som anses vara av betydelse för att femvertising ska upplevas autentiskt. Vidare undersöks hur olika generationer förhåller sig till autentisk femvertising. Studien utgick från en kvantitativ metod med deduktiv ansats, där en enkätstudie genomfördes. Insamlad data från 151 respondenter analyserades med av explorativ faktoranalys för att framställa den generella modellen. Därefter genomfördes ANOVA-analys och Post Hoc test för att studera eventuella skillnader mellan generationer. För att femvertising ska upplevas som autentisk identifierades sex dimensioner av betydelse: Trovärdighet, Kontinuitet, Igenkänning, Mångfald, Respekt och Utmaning av stereotyper. Jämförelse av resultatet med avseende på olika generationer visade att det fanns en signifikant skillnad mellan Generation X och Generation Z för dimensionen Kontinuitet. Övriga dimensioner påvisade ingen skillnad vilket ger slutsatsen att autentisk femvertising har liknande betydelse över generationsgränser.

In this thesis, support structures of a polymer powder based process called XXXXXXXX™ are examined. These structures are crucial for most additive manufacturing processes. The effects of several factors on five industrially important characteristics of support structures are examined by use of the Design of Experiment (DoE) method. It describes the planning as well as the analysis of the experiments. The experiments are planned in a fractional factorial 211-5 design with 64 specimens, resulting in a resolution of IV. The analysis of the data is done by use of the ANOVA method, with which the significance of effects and interaction effects are checked. / I detta examensarbete undersöks stödstrukturer för en polymer-pulverbaserad process kallad XXXXXXXX. Dessa strukturer är väsentliga för de flesta aditiv tillverkning. Med hjälp av metoden "Design of Experiment" (DoE) undersöks effekten av flera faktorer på fem industriellt viktiga egenskaper för stödstrukturer. DoE beskriver både planeringen och analysen av experiment. Experimenten planeras i en fraktionerad faktoriell 211-5 design med 64 provexemplar vilket resulterar i en upplösning av IV. Dataanalysen genomförs med hjälp av ANOVA-metoden, med vilken signifikansen av effekter och interaktionseffekter kan undersökas.

There has been a change of paradigm in which way information is being produced, processed, and consumed as a result of social media. While planning to store the data, it is important to choose a suitable database for the type of data, as unsuitable storage and analysis can have a noticeable impact on the system’s energy consumption. Additionally, effectively analyzing data is essential because deficient data analysis on a large dataset can lead to repercussions due to unsound decisions and inadequate planning. In recent years, an increasing amount of organizations have provided services that cannot be anymore achieved efficiently using relational databases. An alternative data storage is graph databases, which is a powerful solution for storing and searching for relationship-dense data. The research question that the thesis aims to answer is, how do state-of-the-art-graph database and relational database technologies compare with each other from a performance perspective in terms of time taken to query, CPU usage, memory usage, power usage, and temperature of the server? To answer the research question, an experimental study using analysis of variance will be performed. One relational database, MySQL, and two graph databases, ArangoDB and Neo4j, will be compared using a benchmark. The benchmark used is Novabench. The results from the post-hoc, KruskalWallis, and analysis of variances show that there are significant differences between the database technologies. This means the null hypothesis, that there is no significant difference, is rejected, and the alternative hypothesis, that there is a significant difference in performance between the database technologies in the aspects of Time to Query, Central Processing Unit usage, Memory usage, Average Energy usage, and temperature holds. In conclusion, the research question was answered. The study shows that Neo4j was the fastest at executing queries, followed by MySQL, and in last place ArangoDB. The results also showed that MySQL was more demanding on memory usage than the other database technologies.