Number of found documents: 1253
Published from to

Mathematics and Optimal control theory meet Pharmacy: Towards application of special techniques in modeling, control and optimization of biochemical networks
Papáček, Štěpán; Matonoha, Ctirad; Duintjer Tebbens, Jurjen
2021 - English
Similarly to other scienti c domains, the expenses related to in silico modeling in pharmacology need not be extensively apologized. Vis a vis both in vitro and in vivo experiments, physiologically-based pharmacokinetic (PBPK) and pharmacodynamic models represent an important tool for the assessment of drug safety before its approval, as well as a viable option in designing dosing regimens. In this contribution, some special techniques related to the mathematical modeling, control and optimization of biochemical networks are presented on a paradigmatic example of enzyme kinetics. Keywords: Dynamical system; Systems pharmacology; Biochemical network; Input-output regulation; Optimization Fulltext is available at external website.
Mathematics and Optimal control theory meet Pharmacy: Towards application of special techniques in modeling, control and optimization of biochemical networks

Similarly to other scienti c domains, the expenses related to in silico modeling in pharmacology need not be extensively apologized. Vis a vis both in vitro and in vivo experiments, ...

Papáček, Štěpán; Matonoha, Ctirad; Duintjer Tebbens, Jurjen
Ústav teorie informace a automatizace, 2021

Institutions, Financial Development, and Small Business Survival: Evidence from European Emerging Economies
Iwasaki, I.; Kočenda, Evžen; Shida, Y.
2020 - English
In this paper, we traced the survival status of 94,401 small businesses in 17 European emerging markets from 2007–2017 and empirically examined the determinants of their survival, focusing on institutional quality and financial development. We found that institutional quality and level of financial development exhibit statistically significant and economically meaningful impacts on the survival probability of the SMEs being researched. The evidence holds even when we control for a set of firm-level characteristics such as ownership structure, financial performance, firm size, and age. The findings are also uniform across industries and country groups and robust beyond the difference in assumption of hazard distribution. Keywords: small business; survival analysis; European emerging markets Fulltext is available at external website.
Institutions, Financial Development, and Small Business Survival: Evidence from European Emerging Economies

In this paper, we traced the survival status of 94,401 small businesses in 17 European emerging markets from 2007–2017 and empirically examined the determinants of their survival, focusing on ...

Iwasaki, I.; Kočenda, Evžen; Shida, Y.
Ústav teorie informace a automatizace, 2020

Financial Crime and Punishment: A Meta-Analysis
de Batz, L.; Kočenda, Evžen
2020 - English
We examine how the publication of intentional financial crimes committed by listed firms is interpreted by financial markets, using a systematic and quantitative review of existing empirical studies. Specifically, we conduct a meta-regression analysis and investigate the extent and nature of the impact that the publication of financial misconducts exerts on stock returns. We survey 111 studies, published between 1978 and 2020, with a total of 439 estimates from event studies. Our key finding is that the average abnormal returns calculated from this empirical literature are affected by a negative publication selection bias. Still, after controlling for this bias, our meta-analysis indicates that publications of financial crimes are followed by statistically significant negative abnormal returns, which suggests the existence of an informational effect. Finally, the MRA results demonstrate that crimes committed in common law countries, alleged crimes, and accounting crimes carry particularly weighty information for market participants. The results call for more transparency on side of enforcers along enforcement procedures, to foster timely and proportionate market reactions and support efficient markets. Keywords: Meta-Analysis; Event study; Financial Misconduct; Fraud; Financial Markets; Returns; Listed Companies; Information and Market Efficiency Fulltext is available at external website.
Financial Crime and Punishment: A Meta-Analysis

We examine how the publication of intentional financial crimes committed by listed firms is interpreted by financial markets, using a systematic and quantitative review of existing empirical studies. ...

de Batz, L.; Kočenda, Evžen
Ústav teorie informace a automatizace, 2020

Selective Attention in Exchange Rate Forecasting
Kapounek, S.; Kučerová, Z.; Kočenda, Evžen
2020 - English
We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market participants process only a limited amount of information. Our analysis includes more than 100,000 news articles relevant to the six most-traded foreign exchange currency pairs for the period of 1979–2016. We employ a dynamic model averaging approach to reduce model selection uncertainty and to identify time-varying probability to include regressors in our models. Our results show that smaller sizes models accounting for the presence of selective attention offer improved fitting and forecasting results. Specifically, we document a growing impact of foreign trade and monetary policy news on the euro/dollar exchange rate following the global financial crisis. Overall, our results point to the existence of selective attention in the case of most currency pairs. Keywords: exchange rate; selective attention; news; forecasting; dynamic model averaging Fulltext is available at external website.
Selective Attention in Exchange Rate Forecasting

We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market ...

Kapounek, S.; Kučerová, Z.; Kočenda, Evžen
Ústav teorie informace a automatizace, 2020

Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach
Švorc, Jan; Vomlel, Jiří
2020 - English
The objective of this paper is to explore the associations between the subjective well-being (SWB) and the subjective and objective measures of the individual material situation in the four post-communist countries of Central Europe (the Czech Republic, Hungary, Poland, and Slovakia). The material situation is measured by income, relative income compared to others, relative income compared to one’s own past, perceived economic strain, financial problems, material deprivation, and housing problems. Our analysis is based on empirical data from the third wave of European Quality of Life Study conducted in 2011. Bayesian networks as a graphical representation of the relations between SWB and the material situation have been constructed in five versions. The models have been assessed using the Bayesian Information Criterion (BIC) and SWB prediction accuracy, and compared\nwith Ordinal Logistic Regression (OLR). Expert knowledge, as well as three different algorithms (greedy, Gobnilp, and Tree-augmented Naive Bayes) were used for learning the network structures. Network parameters were learned using the EM algorithm. Parameters based on OLR were learned for a version of the expert model. The Gobnilp model, the Markov equivalent to the greedy model, is BIC optimal. The OLR predicts SWB slightly better than the other models. We conclude that the objective material conditions' influence on SWB is rather indirect, through the subjective situational assessment of various aspects related to the individual material conditions. Keywords: Subjective Well-Being; Income; Economic Strain; Material Deprivation; Bayesian Networks; Central Europe Fulltext is available at external website.
Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach

The objective of this paper is to explore the associations between the subjective well-being (SWB) and the subjective and objective measures of the individual material situation in the four ...

Švorc, Jan; Vomlel, Jiří
Ústav teorie informace a automatizace, 2020

Bayesian Selective Transfer Learning for Patient-Specific Inference in Thyroid Radiotherapy
Murray, Sean Ernest; Quinn, Anthony
2020 - English
This research report outlines a selective transfer approach for Bayesian estimation of patient-specific levels of radioiodine activity in the thyroid during the treatment of differentiated thyroid carcinoma. The work seeks to address some limitations of previous approaches [4] which involve generic, non-selective transfer of archival data. It is proposed that improvements in patient-specific inferences may be achieved via transferring external population knowledge selectively. This involves matching the patient to a similar sub-population based on available metadata, generating a Gaussian Mixture Model within the partitioned data, and optimally transferring a data predictive distribution from the sub-population to the specific patient. Additionally, a performance evaluation method is proposed and early-stage results presented. Keywords: Bayesian estimation; thyroid carcinoma; patient-specific inferences Fulltext is available at external website.
Bayesian Selective Transfer Learning for Patient-Specific Inference in Thyroid Radiotherapy

This research report outlines a selective transfer approach for Bayesian estimation of patient-specific levels of radioiodine activity in the thyroid during the treatment of differentiated thyroid ...

Murray, Sean Ernest; Quinn, Anthony
Ústav teorie informace a automatizace, 2020

Bayesian transfer learning between autoregressive inference tasks
Barber, Alec; Quinn, Anthony
2020 - English
Bayesian transfer learning typically relies on a complete stochastic dependence speci cation between source and target learners which allows the opportunity for Bayesian conditioning. We advocate that any requirement for the design or assumption of a full model between target and sources is a restrictive form of transfer learning. Keywords: autoregression; transfer learning; Fully Probabilistic Design; FPD; food-commodities price prediction Fulltext is available at external website.
Bayesian transfer learning between autoregressive inference tasks

Bayesian transfer learning typically relies on a complete stochastic dependence speci cation between source and target learners which allows the opportunity for Bayesian conditioning. We advocate that ...

Barber, Alec; Quinn, Anthony
Ústav teorie informace a automatizace, 2020

Systems biology analysis of a drug metabolism (with slow-fast. . . )
Papáček, Štěpán; Lynnyk, Volodymyr; Rehák, Branislav
2020 - English
In the systems biology literature, complex systems of biochemical reactions (in form of ODEs) have become increasingly common. This issue of complexity is often making the modelled processes (e.g. drug metabolism, XME induction, DDI) difficult to intuit or to be computationally tractable, discouraging their practical use. Keywords: Dynamical system; Complex system; Optimization Fulltext is available at external website.
Systems biology analysis of a drug metabolism (with slow-fast. . . )

In the systems biology literature, complex systems of biochemical reactions (in form of ODEs) have become increasingly common. This issue of complexity is often making the modelled processes (e.g. ...

Papáček, Štěpán; Lynnyk, Volodymyr; Rehák, Branislav
Ústav teorie informace a automatizace, 2020

Bivariate Geometric Distribution and Competing Risks: Statistical Analysis and Application
Volf, Petr
2020 - English
The contribution studies the statistical model for discrete time two-variate duration (time-to-event) data. The analysis is complicated by partial data observation caused either by the right-side censoring or by the presence of dependent competing events. The case is modeled and analyzed with the aid of a two-variate geometric distribution. The model identifiability is discussed and it is shown that the model is not identifiable without proper additional assumptions. The method of analysis is illustrated both on artificially generated\nexample and on real unemployment data. Keywords: bivariate geometric distribution; competing risks; unemployment data Fulltext is available at external website.
Bivariate Geometric Distribution and Competing Risks: Statistical Analysis and Application

The contribution studies the statistical model for discrete time two-variate duration (time-to-event) data. The analysis is complicated by partial data observation caused either by the right-side ...

Volf, Petr
Ústav teorie informace a automatizace, 2020

A Note on Stochastic Optimization Problems with Nonlinear Dependence on a Probability Measure
Kaňková, Vlasta
2020 - English
Nonlinear dependence on a probability measure begins to appear (last time) in a stochastic optimization rather often. Namely, the corresponding type of problems corresponds to many situations in applications. The nonlinear dependence can appear as in the objective functions so in a constraints set. We plan to consider the case of static (one-objective) problems in which nonlinear dependence appears in the objective function with a few types of constraints sets. In details we consider constraints sets “deterministic”, depending nonlinearly on the probability measure, constraints set determined by second order stochastic dominance and the sets given by mean-risk problems. The last case means that the constraints set corresponds to solutions those guarantee an acceptable value in both criteria. To introduce corresponding assertions we employ the stability results based on the Wasserstein metric and L1 norm. Moreover, we try to deal also with the case when all results have to be obtained (estimated) on the data base. Keywords: Stochastic optimization problem; Nonlinear dependence; Empirical estimates; Static problems Fulltext is available at external website.
A Note on Stochastic Optimization Problems with Nonlinear Dependence on a Probability Measure

Nonlinear dependence on a probability measure begins to appear (last time) in a stochastic optimization rather often. Namely, the corresponding type of problems corresponds to many situations in ...

Kaňková, Vlasta
Ústav teorie informace a automatizace, 2020

About project

NRGL provides central access to information on grey literature produced in the Czech Republic in the fields of science, research and education. You can find more information about grey literature and NRGL at service web

Send your suggestions and comments to nusl@techlib.cz

Provider

http://www.techlib.cz

Facebook

Other bases