사료첨가용 항생제 대체 생균제의 산업화를 위한 생산공정의 최적화

학위논문(석사)--서울대학교 대학원 :농업생명과학대학 농생명공학부,2019. 8. 최윤재.Probiotics are microorganisms confer a health benefit on the host with special focus on modulation of the host intestinal microbiota. Due to Korea has created a blanket ban on all antibiotics in animal feed in July 2011, the volume of research related to probiotics has been expanding rapidly. Consequently, technological advances in the large-scale production and lyophilization are needed by probiotic-related industries for producing probiotic lactic acid bacteria (LAB) for commercial use. Lactobacillus plantarum GS1 (LP-GS1), as a variant produced by genome shuffling, has stronger antibacterical activity against E.coli K99 (one of the leading bacterial causes of diarrhea in young livestocks) than the wild type. Therefore it has a good business prospect and a huge market value as an antibiotic alternative. We used response surface methodology technology (RSM) to establish the best conditions for mass production of LP-GS1 while ensuring low production cost and high survival rate. Through feeding experiments, we also found that dietary supplementation of probiotics benefited growth performance and intestinal flora health at the early stage of the post-weaning period in piglets. It was proved that LP-GS1 could be used as a substitute for antibiotics by animal feeding experiment.Introduction 1 Review of Literature 6 1. Antibiotics 6 1) Development and problems of antibiotics. 6 2) Antibiotic resistance of bacteria 7 2. Probiotics. 12 1) The development history of probiotics 12 2) Mechanism of probiotics. 14 3) Lactobacillus plantarum 19 3. Factors that affect the mass production of lactic acid bacteria 24 1) Medium composition. 25 2) Culture conditions . 28 3) Freeze-drying process 28 4. Mass production strategy . 37 1) Screening of variables . 42 2) Choice of the experimental design 42 3) Running the experiment 43 4) Evaluation of the fitted model . 43 5) Determination of the optimal conditions. 43 Study 1. Optimization of large-scale production process of Lactobacillus plantarum GS1 45 1. Introduction. 45 2. Materials and Methods. 51 1) Materials 51 2) Strain preparation 51 3) Co-culture for antimicrobial activity . 51 4) Preparation of cryoprotectant 54 5) Vacuum freeze-drying process. 54 6) Calculation of survival rate . 55 7) Central composite design 55 8) Plackett-Burman design. 56 9) Model validation and confirmation . 57 10) Statistical analysis . 58 3. Results 59 1) Optimization of medium compositions. 59 2) Optimization of culture conditions 72 3) Optimization of freeze-drying process 82 4) Batch culture pH control . 99 5) Comparison of existing production conditions and optimal production conditions 101 6) Changes of antibacterial ability before and after freeze-drying 103 7) Investigation of the shelf-life. 105 4. Discussion. 107 Study 2. In vivo efficacy and antibacterial ability as an alternative probiotic substitute for feed additives of Lactobacillus plantarum GS1. 112 1. Introduction. 112 2. Materials and Methods. 114 1) Preparation of probiotic feed additives 114 2) Animals and experimental design 115 3) DNA extraction and sequencing 120 4) Quantitative real-time PCR . 120 5) Blood component analysis. 123 6) Statistical analysis . 123 3. Results 124 1) Growth performance and diarrheal incidence . 124 2) Microbial analysis in weaning piglets. 129 3) The change of blood metabolites. 137 4. Discussion. 142 Overall Conclusion. 144 Literature Cited 148 Summary in Korean. 156Maste

Odhad rizika a zpětné testování

The financial market always fluctuates. The most popular risk measures is Value of Risk. We introduce the four methods for VaR estimation.They are historical simulation method, filtered historical simulation, analytical solution and Monte Carlo method. In order to verify the different VaR estimation approaches, we utilize backtesting on chosen time series, which are Kupiec's unconditional coverage test and Christoffersen's conditional coverage test. In order to show the calculation steps of VaR estimation and backtesting procedures clearly, we present simplified examples in the beginning of each empirical study. Then the VaR estimation is calculated with different probability levels based on different observed periods. In the end, we find out the most accuracy model on chosen time series.The financial market always fluctuates. The most popular risk measures is Value of Risk. We introduce the four methods for VaR estimation.They are historical simulation method, filtered historical simulation, analytical solution and Monte Carlo method. In order to verify the different VaR estimation approaches, we utilize backtesting on chosen time series, which are Kupiec's unconditional coverage test and Christoffersen's conditional coverage test. In order to show the calculation steps of VaR estimation and backtesting procedures clearly, we present simplified examples in the beginning of each empirical study. Then the VaR estimation is calculated with different probability levels based on different observed periods. In the end, we find out the most accuracy model on chosen time series.154 - Katedra financívýborn

Comparative Study of Different Methods in Vibration-Based Terrain Classification for Wheeled Robots with Shock Absorbers

open access articleAutonomous robots that operate in the field can enhance their security and efficiency by accurate terrain classification, which can be realized by means of robot-terrain interaction-generated vibration signals. In this paper, we explore the vibration-based terrain classification (VTC), in particular for a wheeled robot with shock absorbers. Because the vibration sensors are usually mounted on the main body of the robot, the vibration signals are dampened significantly, which results in the vibration signals collected on different terrains being more difficult to discriminate. Hence, the existing VTC methods applied to a robot with shock absorbers may degrade. The contributions are two-fold: (1) Several experiments are conducted to exhibit the performance of the existing feature-engineering and feature-learning classification methods; and (2) According to the long short-term memory (LSTM) network, we propose a one-dimensional convolutional LSTM (1DCL)-based VTC method to learn both spatial and temporal characteristics of the dampened vibration signals. The experiment results demonstrate that: (1) The feature-engineering methods, which are efficient in VTC of the robot without shock absorbers, are not so accurate in our project; meanwhile, the feature-learning methods are better choices; and (2) The 1DCL-based VTC method outperforms the conventional methods with an accuracy of 80.18%, which exceeds the second method (LSTM) by 8.23%

Plasmonic Nanostructures as Surface-Enhanced Raman Scattering (SERS) Substrate for Protein Biomarker Sensing

Plasmonic nanostructures have attracted considerable interest in biomarker sensing with the goal of rapid diagnostics and personalized nanomedicine. Surface‐enhanced Raman scattering (SERS) is a versatile technique for the characterization of the plasmonic effect of the metallic nanostructures as well as a sensitive read‐out approach for biomarkers detection. In this contribution, we will give a review on the key optical properties of plasmonic nanostructures as SERS substrate for protein biomarkers detection. As a consequence, two approaches, label‐free and SERS labels will be discussed in details for protein biomarkers sensing by using the plasmonic nanostructures as the substrate

Finanční analýza společnosti Fortuna Entertainment Group N.V.

Import 02/11/2016Financial analysis includes several activities that involve the examination of financial and operational information. The original relevant data should be collected from the company’s financial report and organize them. Then, we use the common-size analysis to describe the proportional relation of relevant items and we use the financial ratios to analyze the situation of selected company. The goal of the thesis is to perform financial analysis of Fortuna Entertainment Group in period 2010-2014. Then, we use the DuPont analysis to show the factors impact on the return of equity of Fortuna.Financial analysis includes several activities that involve the examination of financial and operational information. The original relevant data should be collected from the company’s financial report and organize them. Then, we use the common-size analysis to describe the proportional relation of relevant items and we use the financial ratios to analyze the situation of selected company. The goal of the thesis is to perform financial analysis of Fortuna Entertainment Group in period 2010-2014. Then, we use the DuPont analysis to show the factors impact on the return of equity of Fortuna.154 - Katedra financívelmi dobř

Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games

This paper makes progress towards learning Nash equilibria in two-player zero-sum Markov games from offline data. Specifically, consider a $\gamma$-discounted infinite-horizon Markov game with $S$ states, where the max-player has $A$ actions and the min-player has $B$ actions. We propose a pessimistic model-based algorithm with Bernstein-style lower confidence bounds -- called VI-LCB-Game -- that provably finds an $\varepsilon$-approximate Nash equilibrium with a sample complexity no larger than $\frac{C_{\mathsf{clipped}}^{\star}S(A+B)}{(1-\gamma)^{3}\varepsilon^{2}}$ (up to some log factor). Here, $C_{\mathsf{clipped}}^{\star}$ is some unilateral clipped concentrability coefficient that reflects the coverage and distribution shift of the available data (vis-\`a-vis the target data), and the target accuracy $\varepsilon$ can be any value within $\big(0,\frac{1}{1-\gamma}\big]$. Our sample complexity bound strengthens prior art by a factor of $\min\{A,B\}$, achieving minimax optimality for the entire $\varepsilon$-range. An appealing feature of our result lies in algorithmic simplicity, which reveals the unnecessity of variance reduction and sample splitting in achieving sample optimality.Comment: accepted to Operations Researc

Dynamics of COVID-19 models with asymptomatic infections and quarantine measures

Considering the propagation characteristics of COVID-19 in different regions, the dynamics analysis and numerical demonstration of long-term and short-term models of COVID-19 are carried out, respectively. The long-term model is devoted to investigate the global stability of COVID-19 model with asymptomatic infections and quarantine measures. By using the limit system of the model and Lyapunov function method, it is shown that the COVID-19-free equilibrium $V^0$ is globally asymptotically stable if the control reproduction number $\mathcal{R}_{c}<1$ and globally attractive if $\mathcal{R}_{c}=1$, which means that COVID-19 will die out; the COVID-19 equilibrium $V^{\ast}$ is globally asymptotically stable if $\mathcal{R}_{c}>1$, which means that COVID-19 will be persistent. In particular, to obtain the local stability of $V^{\ast}$, we use proof by contradiction and the properties of complex modulus with some novel details, and we prove the weak persistence of the system to obtain the global attractivity of $V^{\ast}$. Moreover, the final size of the corresponding short-term model is calculated and the stability of its multiple equilibria is analyzed. Numerical simulations of COVID-19 cases show that quarantine measures and asymptomatic infections have a non-negligible impact on the transmission of COVID-19