National Repository of Grey Literature 354 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Predicting local structural properties from antibody sequence
Beňo, Roman ; Příhoda, David (advisor) ; Hoksza, David (referee)
Predicting local structural properties of antibodies at residual level is vital for detecting the presence of post-translational modifications (PTMs), which often induce structural change in the antibody, negatively impact its shelf-life and possibly lead to the loss of the therapeutic potential. In this work, we predict relative solvent accessibility (RSA) of individual residues. This property is, alongside with the type of amino acid in question, the key indicator for presence of methionine oxidations and other types of PTMs. Due to the conservation of the antibody structure, we identified that different classes of prediction methods yield almost interchangeable results - total mean absolute error (MAE) of 5.64 RSA percentage units measured for the best performing machine learning pipeline compared to the 5.96 measured for the best performing statistical pipeline. The significant prediction quality improvement observed within comparison to the random prediction method with MAE of 35.996 may be as well attributed to the sequence conservancy. In CDR regions, RSA values are harder to predict. Although the range of methods and procedures employed throughout this work is by far not able to yield complex structure predictions, it might constitute a modular, high-throughput tool to support one's choices when...
Dlouhodobý finanční plán společnosti AGROSTROJ Pelhřimov, a.s.
Měchurová, Adéla
The objective of the diploma thesis is to develop a long-term financial plan of AGROSTROJ Pelhřimov, a. s. The financial plan spans a five-year period from 2022 to 2026 and encompasses three distinct scenarios representing potential future development: realistic, optimistic, and pessimistic. The plan comprises a projected income statement, forecasted a balance sheet and a cash flow projection. Upon completion, the financial plan is assessed to determine the future financial situation of the company.
Prediction of therapeutical response to neoadjuvant therapy in rectal cancer
Pazdírek, Filip ; Hoch, Jiří (advisor) ; Martínek, Lubomír (referee) ; Šimša, Jaromír (referee)
The treatment of locally advanced rectal cancer is multimodal. It includes neoadjuvant radiochemotherapy (NCHRT), which reduces the risk of local recurrence. However, this treatment is also accompanied by side effects. Accordingly, there is an unmet need to identify predictive markers allowing to identify non-responders to avoid its adverse effects. We monitored circulating tumor DNA (ctDNA) as a potential liquid biopsy-based biomarker. We have investigated ctDNA changes plasma during the early days of NCHRT and its relationship to the immediate tumor response as well as overall patients survival. In all patients, ctDNA was strongly reduced or completely eliminated from plasma by the end of the first week of NCHRT, with no correlation to any of the parameters analyzed. As ctDNA was reduced indiscriminately from the circulation of all patients, therefore the dynamics during the first week of NCHRT is not suitable for predicting the immediate therapeutic response in rectal cancer. The baseline ctDNA presence represented a statistically significant negative prognostic biomarker for the overall patient survival. However, the general effect of rapid ctDNA disappearance apparently occurring during the initial days of NCHRT is noteworthy and should further be studied. Keywords: rectal cancer, neoadjuvant...
Prediction of radiotherapy response in rectal cancer by MR
Chmela, Radek ; Nohel, Michal (referee) ; Mézl, Martin (advisor)
This diploma thesis deals with the issue of predicting the response of rectal cancer to radiotherapy. The work is divided into four chapters. In the first two, the anatomy of the rectum, types of cancer and individual diagnostic methods are described, together with algorithms for detecting objects in images. In the third chapter, there is a description of the solution for automatic segmentation and prediction of the effectiveness of radiotherapy. In the fourth chapter, the achieved results are discussed.
The use of convolutional neural networks for predicting the financial failure of a company
Šebestová, Monika ; Chramcov, Bronislav (referee) ; Lenort, Radim (referee) ; Režňáková, Mária (referee) ; Dostál, Petr (advisor)
The doctoral thesis deals with the use of convolutional neural networks for predicting the financial failure of companies. A bibliometric analysis was used during the processing of the literature review, which enabled a better orientation in scientific works oriented to the methods and approaches used in the past to predict the financial failure of companies. On the basis of the obtained knowledge, a deep learning model based on the GoogLeNet architecture was proposed, with inputs consisting of financial and macroeconomic indicators of companies. The modeling was based on the transfer learning method, in which it is possible to fine-tune the parameters of the pre-established networks to accelerate the learning process of the convolutional neural network. The initial set of financial and macroeconomic indicators was compiled from the variables that were most often used in business failure prediction models in scientific papers. Appropriate statistical methods were used for the specific selection of indicators from which the model is built. Since convolutional neural networks work best with image processing, the quantitative values of the input indicators were graphically interpreted and it was investigated which type of graphical processing is most suitable for predicting the failure of companies. Due to the existence of an unbalanced data set, the effect of the SMOTE method on the accuracy of the model's prediction was analyzed in the thesis. The method was used to increase the number of samples of the minority class of firms. To model the prediction of financial default, several variants of models were proposed, which differed in the form of input data. It was tested how the removal of outliers from the data set, the point in time from which the data come or the method of predictor selection will affect the accuracy of the prediction. The parameters of the resulting model were further fine-tuned so that it was able to classify businesses from new real data. The research conducted showed that using the right type of graphical processing of input data, SMOTE technique and appropriate parameter settings, convolutional neural networks can predict the financial failure of companies with high accuracy.
Assessing Economic Situation of a Company and Proposals for Its Improvement
Baracskaiová, Nikol ; Hrubá, Iveta Musil (referee) ; Doubravský, Karel (advisor)
The thesis deals with the assessment of the economic situation of the company XYZ using financial analysis and statistical methods. The theoretical part focuses on financial and statistical theory. In the practical part, financial ratios are calculated, some of which are selected for the statistical analysis. Based on the selected models, the expected development of the indicators in the following years is calculated. At the end of the analytical part, the dependencies of the selected pairs are examined by correlation analysis. The proposal part is devoted to the identification of problem areas, based on which possible proposals for improving the current economic situation of the company have been described.
Assessing Economic Situation of a Company and Proposals for Its Improvement
Zlámal, Aleš ; Kašpar, Jan (referee) ; Doubravský, Karel (advisor)
The diploma thesis is focused on finding out the economic situation of the company XYZ s.r.o. by using financial analysis and statistical methods. In the introductory part of the thesis, economic indicators and the financial analysis itself are defined, as well as time series and correlation and regression analysis. In the second part of the thesis, calculations of economic indicators are carried out and, for selected indicators, their development in the next two years is predicted using statistical methods. At the end of the chapter, the dependence between two indicators is determined. In the last part of the thesis, proposals are made that could help the analyzed company to improve its current state.
Využití běžeckého wattmetru STRYD pro stanovení úrovně VO2max u vytrvalostních běžců
Bekr, Ondřej ; Kundera, Václav (referee) ; Pavelka, Jan (advisor)
Determining the limits of general endurance, critical power and maximal oxygen consumption is now a common part of the training process of professional athletes and their preparation to achieve the best possible sports results. Power is a very useful metric in cycling, but in recent years runners have also been trying to exploit its potential. Running power is only functional if it represents well the metabolic load of the organism. This thesis investigates the relationship between running power PO and oxygen consumption VO2, a representative of the metabolic load of the organism, in indoor and outdoor environments. Furthermore, thesis verifies the possibility of determining the VO2max level of runners using running power. The relationship between PO and VO2 is linear, for individual subjects the R2 is 0,95±0,07 in the indoor and 0,97±0,02 in the outdoor. For all subjects (TO) in the indoor the R2 takes the value of 0,67 and in the outdoor the value of 0,79. There was a difference of 1,2% (PO) and 3,7% (VO2max) between the values measured in the different environments. The model prediction from all TO in the indoor environment has an error of 3,5%.
Econometric Modelling of Natural Gas Consumption in the Electricity Sector in the Midwest Europe Region
Kunc, Tomáš ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
The thesis deals with econometric modeling of natural gas consumption within the electricity industry for the purpose of electricity production. The first part of the thesis focuses on theoretical foundations, describing the electricity market and econometric modeling, with a particular focus on regression analysis. In the analytical part, this knowledge is applied to the selection and adjustment of potential factors. As part of the proposed solution, a regression model is constructed that describes natural gas consumption in electricity production as a function of selected factors. The predictive ability of the model is verified using data from a testing period.
Assessing Economic Situation of a Company and Proposals for Its Improvement
Svobodová, Gabriela ; Slavíčková, Šárka (referee) ; Doubravský, Karel (advisor)
The master thesis deals with the assessment of the current economic situation of the selected company. The theoretical part describes the selected financial indicators, time series, regression and correlation analysis. The analytical part includes calculations of selected financial indicators and their evaluation. Some indicators are then subjected to statistical analysis. Thanks to this analysis, a prediction of values for the next two economic periods is made. It also includes a correlation analysis of the dependency of individual indicators. The final part consists of a description of individual proposals for measures leading to a possible improvement of the economic situation.

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