Numerous authors note failure of private insurance markets to provide affordable and comprehensive crop insurance. Economic logic suggests that index contracts potentially may have some advantages when compared with traditional (farm based) crop insurance. It is also a matter of common knowledge that weather is an important production factor and at the same time one of the greatest sources of risk in agriculture. Hence introduction of crop insurance contracts, based on weather indexes, might be a reasonable approach to mitigate problems, associated with traditional crop insurance products, and possibly lower the cost of insurance for end users. In spite of the fact that before the financial crisis of 2008-09 market for weather derivatives was the fastest growing derivatives market in the USA, agricultural producers didn’t express much interest in application of weather derivatives to management of their systematic risk. There are several reasons for that, but the most important one is the presence of high basis risk, which is represented by its two major components: technological (i.e. goodness of fit between yield and weather index) and geographical basis. Majority of the researchers is focusing either on pricing of weather derivatives or on mitigation of geographical basis risk. At the same time the number of papers researching possible ways to decrease technological basis is quite limited, and always assumes linear dependency between yields and weather variables, while estimating the risk reducing efficiency of weather contracts, which is obviously large deviation from reality. The objective of this study is to estimate the risk reducing efficiency of crop insurance contracts, based on weather derivatives (indexes) in the state of Texas. The distributions of representative farmer’s profits with the proposed contracts are compared to the distributions of profits without a contract. This is done to demonstrate the risk mitigating effect of the proposed contracts. Moreover the study will try to account for a more complex dependency structures between yields and weather variables through usage of copulas, while constructing joint distribution of yields and weather data. Selection of the optimal copula will be implemented in the out-of-sample efficient framework. An effort will be done to identify the most relevant periods of year, when weather has the most significant influence on crop yields, which should be included in the model, and to discover the most effective copula to model joint weather/yield risk. Results suggest that effective insurance of crop yields in the state of Texas by the means of proposed weather derivatives is possible. Besides, usage of data-mining techniques allows for more accurate selection of the time periods to be included in the model than ad hoc procedure previously used in the literature. Finally selection of optimal copula for modeling of joint weather/yield distribution should be crop and county specific, while in general Clayton and Frank copula of Archimedean copula family provide the best out-of-sample metric results.

Prescription medicine samples are a product based promotion designed to facilitate brand switching or uptake of a new product. Marketing of pharmaceuticals differs from other products since the primary decision maker (doctor) is not the ultimate consumer (patient). Marketing of medicines also has an overlay of government regulations and political influence. It is argued whether free samples of prescription medicines provided to doctors constitute a “gift” or a trial quantity with which to initiate therapy and test patient tolerance of the drug concerned. Either way, samples are an integral part of the prescription medicine marketing tapestry and they have become woven into the “fabric” of drug promotion. The international literature abounds with papers describing pharmaceutical promotion and myriads of surveys obtaining prescribers’ opinions about pharmaceutical promotion. Few studies have been conducted or reported to ascertain the reasons behind the opinions expressed as disagreement/agreement scales to specific statements. Interventions to alter practice targeting alternative methods of distribution of samples (rather than direct from company to prescriber) are also rare; therefore the aim of this research was to qualitatively explore opinions regarding samples to develop an intervention to ensure samples do not have an adverse effect on prescribing practice and to test the model in a practice environment. In order to assess the place of samples within the totality of pharmaceutical promotion, a model was derived from the literature and tested with a hypothetical, but realistic practice-based scenario. This highlighted the interplay between the various methods involved in pharmaceutical promotion, their target audiences and the potential interplay and synergism that could be achieved through a co-ordinated campaign. Quantification of the expenditure on samples was also required in the Australian context to assess the potential impact of interventions targeting this promotional mode. Samples were found to account for approximately 5% of the total marketing spend in Australia. No clear relationship could be found between sample expenditure and drug sales, utilizing data on the proton pump inhibitor therapeutic class. However, a pattern of decaying spending was found between the amount spent on samples per unit pack dispensed and the time a product had been available on the market. A range of interested parties were then interviewed to gain their opinions about free prescription medicine samples. The interviews were split into two groups: consumers, pharmacists and practicing general practitioners (GPs) provided an operational level focus, while a range of key informants from organisations involved in Quality Use of Medicines in Australia provided a strategic overview. The transcripts of the focus groups and interviews were qualitatively analysed to extract key themes which were quite similar. Examples included ‘pay’ in the operational group compared to ‘cost’ in the strategic group. These concepts express a similar sentiment, yet ‘pay’ is a more personal action whereas ‘cost’ does not imply who must meet the financial outlay. These resultant themes formed the basis of the intervention developed to pilot in a practice environment to assess its practicality for wider study. In addition to the extensive interview process, a mail survey was conducted in three divisions (geographical groupings) of general practice. Each family doctor (General Practitioner (GP)) and community pharmacist within the divisions received a questionnaire to gather their opinions about samples. This was the first time GPs and pharmacists had been surveyed simultaneously to gather comparative results. No differences were found between the metropolitan division and the accumulated results from the two regional divisions. Pharmacists and GPs differed predominantly in their perceptions of promotional influence of samples, appropriateness of self use and meeting legal requirements for labelling dispensed medicines. These factors were incorporated in the pilot study design. An action research methodology was utilised to assess the practicality of community pharmacist dispensing of starter packs for antihypertensives and antidepressants in two regional GP practices in Queensland, Australia. In this pilot study, a total of 32 starter packs were prescribed to 31 patients over the four months of the intervention period, with 29 (91%) dispensed at a study pharmacy and 17 (53%) of subsequent full prescriptions able to be tracked through Medicare Australia data or the study pharmacies. Antidepressants comprised the majority of prescriptions (n=16, 55%) Each of the 29 patients who received a starter pack completed a patient survey which demonstrated high levels of support (n=22, 76%) for the model in the pilot. GPs and pharmacists involved in the pilot were also generally supportive of the pilot model. In conclusion, opinions held about free prescription medicine samples by a wide range of apparently disparate groups show similar themes and community pharmacist involvement in dispensing starter (or sample) packs has general acceptance. The model piloted in this research was applicable in daily practice for general practitioners and community pharmacists in Australia. Consumers accepted the pilot model as an acceptable change to current procedures. The research presented in this thesis provides a solid foundation for development of a more widespread trial for dispensing of all prescription medicine starter packs through community pharmacies to be rigorously evaluated in Australia.

Thesis (M.S.)--Brigham Young University. Dept. of Educational Psychology. / Subjects taken from Timpview High School Seminary classes. Bibliography: leaves 27-31, 45-49.

Thesis (MSc.(Chemical pathology))--University of Pretoria, 2009. / Includes bibliographical references.

Thesis--University of Oklahoma. / Bibliography: leaves 82-83.

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abstract: In many classication problems data samples cannot be collected easily, example in drug trials, biological experiments and study on cancer patients. In many situations the data set size is small and there are many outliers. When classifying such data, example cancer vs normal patients the consequences of mis-classication are probably more important than any other data type, because the data point could be a cancer patient or the classication decision could help determine what gene might be over expressed and perhaps a cause of cancer. These mis-classications are typically higher in the presence of outlier data points. The aim of this thesis is to develop a maximum margin classier that is suited to address the lack of robustness of discriminant based classiers (like the Support Vector Machine (SVM)) to noise and outliers. The underlying notion is to adopt and develop a natural loss function that is more robust to outliers and more representative of the true loss function of the data. It is demonstrated experimentally that SVM's are indeed susceptible to outliers and that the new classier developed, here coined as Robust-SVM (RSVM), is superior to all studied classier on the synthetic datasets. It is superior to the SVM in both the synthetic and experimental data from biomedical studies and is competent to a classier derived on similar lines when real life data examples are considered. / Dissertation/Thesis / Source Code for RSVM(MATLAB) / Presentation on RSVM / M.S. Computer Science 2011

Title: Nonconvex stochastic programming problems - formulations, sample approximations and stability Author: RNDr. Martin Branda Author's e-mail address: branda@karlin.mff.cuni.cz Supervisor: Doc. RNDr. Petr Lachout, CSc. Supervisor's e-mail address: lachout@karlin.mff.cuni.cz Abstract: We deal with problems where integer variables may appear, hence no assumptions on convexity are made throughout this thesis. The goal of Chapter 2 is to introduce stochastic programming problems and to outline the most important tasks connected with solving the problems. In Chapter 3, we compare basic formulations of static stochastic programming problems with chance constraints, with integrated chance constraints and with penalties in the objective function. We show that the problems are asymptotically equivalent under mild conditions. We discuss solving the problems using sample approximation techniques and extend some results on rates of convergence. All the formulations and corresponding sample approximations are compared on an investment problem with real features with Value at Risk constraint, integer allocations and transaction costs. Then, stability of financial decision models where two-stage mixed-integer value function appears as a loss variable is studied. In Chapter 4, we study qualitative properties of the...

Modelling interactions between genes and their regulators is fundamental to understanding how, for example a disease progresses, or the impact of inserting a synthetic circuit into a cell. We use an existing method to infer regulatory networks under multiple conditions: the Joint Graphical Lasso (JGL), a shrinkage based Gaussian graphical model. We apply this method to two data sets: one, a publicly available set of microarray experiments perturbing the gram-positive bacteria Bacillus subtilis under multiple experimental conditions; the second, a set of RNA-seq samples of Mouse (Mus musculus) embryonic fibroblasts (MEFs) infected with different strains of the parasite Toxoplasma gondii. In both cases we infer a subset of the regulatory networks using relatively small sample sizes. For the Bacillus subtilis analysis we focused on the use of these regulatory networks in synthetic biology and found examples of transcriptional units active only under a subset of conditions, this information can be useful when designing circuits to have condition dependent behaviour. We developed methods for large network decomposition that made use of the condition information and showed a greater specificity of identifying single transcriptional units from the larger network using our method. Through annotating these results with known information we were able to identify novel connections and found supporting evidence for a selection of these from publicly available experimental results. Biological data collection is typically expensive and due to the relatively small sample sizes of our MEF data set we developed a novel empirical Bayes method for reducing the false discovery rate when estimating block diagonal covariance matrices. Using these methods we were able to infer regulatory networks for the host infected with either the ME49 or RH strain of the parasite. This enabled the identification of known and novel regulatory mechanisms. The Toxoplasma gondii parasite has shown to subvert host function using similar mechanisms as cancers and through our analysis we were able to identify genes, networks and ontologies associated with cancer, including connections that have not previously been associated with T. gondii infection. Finally a Shiny application was developed as an online resource giving access to the Bacillus subtilis inferred networks with interactive methods for exploring the networks including expansion of sub networks and large network decomposition.

Abstrakt The work deals with the content of iodine in pools samples cow's milk. It provides information about the content of iodine in the Czech Republic within years and districts. Milk was obtained in collaboration with Madeta a.s. Iodine was subsequently determined by spectrophotometry after alkaline combustion of the sample (Sandell-Kolthoff method). A total were evaluated of 149 samples milk (2013-2015). In 2013, the average iodine content in bulk milk samples 289,3 gl-1. In 2014, the average iodine content in bulk milk samples 222,2 microgram.l-1. In terms of food source of iodine in the milk TRÁVNÍČEK et al. (2011) reported the optimal value for the content of iodine in the milk of between 100 to 200 microgram.l-1. The results are thus slightly higher than the optimum. Within the districts was found the highest average in 2013 in the district of Tábor (398,0 microgram.l-1). The highest average content measured in 2014 was found in the district Prachatice (357,0 microgram.l-1), while the lowest average value measured was found in the district Třebíč (163,0 microgram.l-1).