Approximately 80% of reproductive age women experience physical or emotional symptoms prior to onset of menses. Of these women, approximately 20% experience symptoms severe enough to interfere with social functioning and life activities and meet criteria for premenstrual syndrome (PMS). More than 100 different symptoms are associated with PMS, the most common of which include breast tenderness, headache, anger, and depression. Symptom groupings tend to be stable within an individual but can vary distinctly between women. Potential differences in the etiology of symptoms suggest that PMS should not be considered a single condition in research or clinical studies, but rather may represent distinct entities that group by symptom patterns. The primary goal of this study was to identify symptom patterns using factor and cluster analysis. Analysis included: 1) a cohort of healthy women aged 18-30 (n =414); and 2) the subgroup of women meeting established criteria for PMS (n=80). All participants provided information on the occurrence and severity of 26 menstrual symptoms by validated questionnaire. Four distinct symptom patterns emerged: Emotional, Psychological, Physical, and Consumption. Cronbach’s alpha levels demonstrating reliability were high in both the total population (0.71 – 0.90) and in the PMS subset (0.69-0.80). Additionally, cluster analysis identified 4 clusters in both the total population and PMS subset. These symptom patterns were consistent with those identified in prior studies in diverse populations. These observations suggest that distinct subtypes of PMS may exist, and should be considered when recommending treatments and evaluating risk factors.

The purpose of master’s thesis is to project virtualization solution together with replication of the servers. Thesis is divided into the three parts and that it theoretical, analytical and projection part. In analytical part there are basic information about virtualization technologies, in analytical part there is analysis of the present status of the company and mainly about status of the IT infrastructure and in the end projection part there is realization of the virtualization solution from choosing the right type of cluster to choosing hardware solution.

The project deals with design and solution of plug-in for a Jenkins server, which allows management of jobs running on the nodes in the cluster of continuous integration system servers. This plug-in should allow pause the long time job, done process with higher priority and restore original job in state where it was interrupted.

A system running cost calculations for construction project items in Node.js needs improvement. The solution should preferably be implemented within the Node.js environment. Optimization of the application requires improving the function code to decrease run time. Other technical solutions were also examined. Through a literature survey, suggestions for solutions to improving system performance were found. The cluster module in Node.js was tested as the technical solution for improving performance. The solutions managed to lower execution time of the prototype by 50%. Showing that multithreading on Node.js is a viable solution for improving processing-heavy applications.

>Magister Scientiae - MSc / The thesis aims to determine the depositional environments, rock types and petrophysical characteristics of the reservoirs in Wells E-S3, E-S5 and F-AH4 of Area X in the Bredasdorp Basin, offshore South Africa. The three wells were studied using methods including core description, petrophysical analysis, seismic facies and multivariate statistics in order to evaluate their reservoir potential. The thesis includes digital wireline log signatures, 2D seismic data, well data and core analysis from selected depths. Based on core description, five lithofacies were identified as claystone (HM1), fine to coarse grained sandstone (HM2), very fine to medium grained sandstone (HM3), fine to medium grained sandstone (HM4) and conglomerate (HM5). Deltaic and shallow marine depositional environments were also interpreted from the core description based on the sedimentary structures and ichnofossils. The results obtained from the petrophysical analysis indicate that the sandstone reservoirs show a relatively fair to good porosity (range 13-20 %), water saturation (range 17-45 %) and a predicted permeability (range 4- 108 mD) for Wells E-S3, E-S5 andF-AH4. The seismic facies model of the study area shows five seismic facies described as parallel, variable amplitude variable continuity, semi-continuous high amplitude, divergent variable amplitude and chaotic seismic facies as well as a probable shallow marine, deltaic and submarine fan depositional system. Linking lithofacies to seismic facies maps helped to understand and predict the distribution and quality of reservoir packages in the studied wells. Multivariate statistical methods of factor, discriminant and cluster analysis were used. For Wells E-S3, E-S5 and F-AH4, two factors were derived from the wireline log data reflecting oil and non- oil bearing depths. Cluster analysis delineated oil and non-oil bearing groups with similar wireline properties. This thesis demonstrates that the approach taken is useful because petrophysical analysis, seismic facies and multivariate statistics has provided useful information on reservoir quality such as net to gross, depths of hydrocarbon saturation and depositional environment.

A three-year study was conducted at a commercial vineyard site in California’s Edna Valley AVA to evaluate the physiological and agronomical effects of the timing of cluster thinning on Pinot noir (clone 115) grapevines. Vines were thinned to one cluster per shoot at three selected time-points during the growing season (bloom, bloom + 4 weeks, bloom + 8 weeks), and fruit from each treatment was harvested and made into wine. Across all growing seasons, yield decreased 43% in thinned vines relative to un-thinned control vines. No effect of cluster thinning or interaction with growing season was found in vine shoot diameter, internode length, fruit zone light level, or cluster weight. Growing season significantly affected more fruit and wine parameters than did cluster thinning treatment, with interactions between treatment and growing season found in fruit Brix, titratable acidity, and anthocyanins, as well as wine anthocyanins and wine b* (yellow component). For example, bloom + 8 and bloom + 12 thinning treatments advanced Brix in 2017 but had no effect in 2018. Cluster thinning treatments increased berry anthocyanins by 43% in 2017 and by 103% in 2018 relative to the control. Similarly, cluster thinning increased berry total phenolics by 87% in 2017 and by 140% in 2018 relative to the control, with no significant differences found between the different thinning treatments. However, the levels of anthocyanins and total phenolics were generally not affected by cluster thinning treatment in the resulting wines. The fact that different cluster thinning treatments resulted in nil or minor effects on fruit and wine suggests that the vines tested were at or below a balanced crop load prior to the application of cluster thinning. Edna Valley AVA could likely support higher crop loads than 3.2 on the Ravaz index without negatively impacting fruit or wine composition and reducing crop load below that level is unlikely to increase fruit or wine quality.

No description available.

My thesis is focused on the presentation of a scoring model for companies in chemical industry with use of cluster analysis methods. There is a description of financial risks, financial analysis indicators and models which are used to evaluate financial risks of a company. There is also a mathematical description of hierarchical cluster methods.

Orientador: Thiago de Melo / Banca: Sergio Tsuyoshi Ura / Banca: Marcio Fuzeto Gameiro / Resumo: Neste trabalho estudamos networks e métodos de Clustering Hierárquico de forma axiomática. Apresentamos alguns programas na linguagem Python aplicados à análise de dados de migração populacional, com o intuito de ilustrar os métodos estudados / Abstract: In this work we study networks and an axiomatic construction of Hierarchical Clustering. We present some Python programs used to analyze human migration data and illustrate the studied methods / Mestre

There is a need for reliable rules of thumb for various applications in the area of biochemistry, supramolecular chemistry and material sciences. Simultaneously, the amount of information, which we can gather from X-ray crystal geometries about the nature of recognition processes, is limited. Deeper insight into the noncovalent interactions playing the most important role is needed in order to revise these universal rules governing any recognition process. In this thesis, systematic development and study of the accuracy of the computational chemistry methods followed by their applications in protein DNA and host guest systems, are presented. The non-empirical quantum mechanical tools (DFT-D, MP2.5, CCSD(T) etc. methods) were utilized in several projects. We found and confirmed unique low lying interaction energies distinct from the rest of the distributions in several amino acid−base pairs opening a way toward universal rules governing the selective binding of any DNA sequence. Further, the predictions and examination of changes of Gibbs energies (ΔG) and its subcomponents have been made in several cases and carefully compared with experiments. We determined that the choline (Ch+) guest is bound 2.8 kcal/mol stronger (calculated ΔG) than acetylcholine (ACh+) to self-assembled triple helicate rigid...