Descent to the Underworld in the Aeneid by Virgil and the Odyssey by Ho

Descent to the Underworld in the Aeneid and the Odyssey I chose to compare the Odyssey written by the Greek poet Homer and the Aeneid by the Roman poet Virgil. I will focus my interest on Book 11 of the Odyssey and Book 6 of the Aeneid, since that is when both of the main characters make an educational visit to the underworld. The description of the underworld created by Homer's wild imagination, inspired Virgil eight centuries later. Virgil's masterpiece was planned as an imitation of Homer's poems, so one automatically starts comparing the creations of the two authors. They were separated by eight centuries and by the cultural differences of their people. These differences are reflected on the structure of their compositions. At first the reasons for Aeneas's and Odysseus's voyage to the world below seem similar. Both of them want to receive information from the people who have already died. This knowledge is necessary in order for them to continue a successful life in the real world, amongst the real people. Aeneas wants to ask his wise father Anchises for advise about the foundation of a new state - Rome. His father tells him about the future of his family. This prophecy includes the history of Rome all the way until the days of Virgil himself. What glories follow Dardan generations ====================================== In after years, and from Italian blood What famous children in your line will come, Souls of the future, living in our name, I shall tell clearly now, and in the telling Teach you your destiny.[1] The need for Odysseus to travel to the underworld doesn't seem to be motivated at all... ...not only the characters but also the poets who wrote the two outstanding compositions, on which all of the world's literature is based. Homer who glorifies the great value of a person and Virgil who glorifies the grandeur of the State - Rome. [IMAGE] Works Cited Fagles, Robert. The Odyssey. New York: Penguin Books USA Inc. 1996 Fitzgerald, Robert. The Aeneid. Penguin Books. --------------------------------------------------------------------- [1] Virgil Aeneid B.6 line 1015 [2] Homer Odyssey B.11 line 111 [3] Homer Odyssey B.11 line 129 [4] Homer Odyssey B.11 line 153 [5] Homer Odyssey B.11 line 614 [6] Homer Odyssey B.11 line 540 [7] Virgil Aeneid B.6 line 883 [8] Virgil Aeneid B.6 line 824 [9] Virgil Aeneid B.6 line 835 [10] Virgil Aeneid B.6 line 1230

Extracting Dna from Bananas

Extracting DNA from Bananas In the Lab: Extracting DNA from Bananas, DNA was removed from bananas that had been blended with water in order to examine how DNA is seen from the naked eye. DNA stands for deoxyribonucleic acid, which is a nucleic acid that contains the sugar deoxyribose. DNA is made up of a series of monomers called nucleotides. Each nucleotide has three parts: a deoxyribose molecule, a phosphate group, and a nitrogenous base. In addition, there are four kinds of nitrogenous bases in DNA. Two of the nitrogenous bases, adenine and guanine, belong to a group of compounds known as purines. The remaining two bases, cytosine and thymine, are known as pyrimidines. The actual DNA structure is seen as a double helix in which two strands are wound around each other. Each strand is made up of a chain of nucleotides. The two strands are held together by hydrogen bonds between adenine and thymine and between guanine and cytosine. In 1944, a group of scientists led by Canadian biologist Oswald Avery performed an experiment that would determine which molecule in a heat-killed bacterium was most important for transformation to occur. Avery and the other scientists discovered that DNA is the nucleic acid that stores and transmits the genetic information from one generation of an organism to the next. Thus, DNA is present in all living organisms. It holds the instructions necessary for the organism to grow and function, and is passed on from generation to generation through heredity. During the procedure of the lab, a ratio of one banana per one cup (250 milliliters) of distilled water had to be mixed together in a blender. The solution had to be blended for 15 to 20 seconds, until it became a dense mixture. In a separate five-ounce cup, a solution consisting of one teaspoon of shampoo and two pinches of salt was made. 20 milliliters (four teaspoons) of distilled water was then added to the mixture. Then the salt and shampoo had to be dissolved into the mixture by stirring slowly by avoiding foaming. Three heaping teaspoons of the banana mixture that was made in the beginning of the experiment was then added to the shampoo, salt, and water solution and mixed with a spoon for five to ten minutes. While the banana solution was being mixed, a number two cone coffee filter was laced inside a second five-ounce cup. The coffee filter was specifically placed in the cup so that it did not touch the bottom. After stirring for five to ten minutes, the mixture of banana and shampoo was filtered by pouring it into the coffee filter and letting the solution drain for several minutes until there was approximately five milliliters of filtrate to test. A test tube of cold alcohol was then obtained. Then a plastic pipette was filled with the filtrate two times and added to the alcohol. The solution then sat for two to three minutes without a single disruption such as shaking the test tube. The white DNA could be seen precipitating out of the alcohol layer. Lastly, when good results were obtained, there was enough DNA to spool onto a rod or a plastic loop. Throughout the entire experiment there were many possible ways that the ending result of the appearance of the DNA could have differed. The order in which the procedure is stated is very important because the cells must first be broken down in order to release the DNA to be seen. If the steps were altered then the yield or the amount of DNA per banana could have been very small because the DNA would get trapped inside the cells or bound to lipids. Although nowadays very few errors are made due to scientists using biotechnology equipment that allows them to look at DNA to see exactly how organisms are different, and find out how they work. Each living organism has its own unique DNA sequence. Three examples of why scientists might need to indentify DNA are for genetic testing, body identification, and analysis of forensic evidence. Genetic testing can best be defined as a process in which an individual’s DNA is isolated and tested for the presence of specific genes or defects that could indicate the future onset of some disease. Body identification is a subfield of forensic science wherein investigators need to identify a body. Furthermore, analysis of forensic evidence is defined as the application of forensic science and technology to identify specific objects from the trace evidence they leave, often at a crime scene or the scene of an accident. Overall, the Lab: Extracting DNA from Bananas demonstrated and visualized the process of how DNA can be seen from the naked eye by removing DNA directly from bananas.

Validity Of The Capm And Alternative Theories Finance Essay - Free Essay Example

Sample details Pages: 5 Words: 1428 Downloads: 7 Date added: 2017/06/26 Category Finance Essay Type Analytical essay Did you like this example? A major sector in finance is the optimization of portfolio. The target is to maximize the excepted return and minimize the risk. In 1952 Harry Markowitz with his theory about portfolio selection made two observations. Don’t waste time! Our writers will create an original "Validity Of The Capm And Alternative Theories Finance Essay" essay for you Create order The first one was that the combinations of two risky assets provide non-cumulative standard deviations since the two assets are positive correlated. Secondly, when a portfolio of risky assets is built, the standard deviation risk of the portfolio is less than the sum of the standard deviations of its contents. Tobin (1958) suggested a methodology to recognize the appropriate portfolios among the efficient ones. Economists William Sharpe (1964) and John Lintner (1965) simplified this first model by measuring the systematic risk which is related with the general market and it is often called market risk. The result was the development of the Capital Asset Pricing Model (CAPM) which became the groundwork of portfolio measurement. CAPM is applied to help investors, managers and owners to solve decision problems of modern financial management. CAPM is used as a measurement of risk and return and shows the relationship between these two factors. The CAPM relates expected returns of an a sset with the risk factor. Moreover it estimates the asset returns and try to modify the risk. In efficient markets the expected returns are correlated by a linear function of their characteristic degrees with market risk. The CAPM says that the expected risk on each asset is relative to its beta. Beta measures the role of a stock to the risk of the market portfolio. The Capital Asset Pricing Model can be defined as: R = rf + B ( rm rf ) where: R = the expected return on asset rf = a risk free rate B = a risk measure of asset rm = the expected market return The CAPM is developed under quite strong assumptions and that means it is hold only in specific situations. The major assumptions of the CAPM are: Investors have homogeneous beliefs There is no limitation on borrowing and lending There are no transactions costs and taxes Mean-Variance is optimal Any investment is equilibrium Investors behave competitively Capital market Line (CML) and Security Market Line (SML) are two deep-rooted models that are useful for derivation of CAPM. Capital Market Line (CML) and efficient frontier The CML shows the expected return for a given level of risk in a combined portfolio. CML measures the risk by à Ã†â€™. CML is hold for efficient portfolios and is applicable by investors with combined and final portfolio which is efficiently diversified. The efficient frontier says that a set of po rtfolio has the maximum return with a given risk or the minimum risk with a given return. The objective is to move up and left so that investors have low risk and high return. Return Risk Security Market Line (SML) The SML is a linear function between market risk and expected return. SML is applicable to portfolio analysis to experiment whether the securities are comparatively priced or not. The SML expresses the return an investor can expect in terms of a free-risk rate and the relative risk of a portfolio. In the SML risk is measured by Icirc; ² and every asset, security or portfolio is positioned on it. Assets over the SML are underpriced relative to CAPM and assets under the SML are overpriced. Empirical tests Tests of the CAPM are quite difficult to perform. The CAPM and its alterations have been generally tested in the literature but many problems have risen, mainly in the variables bias. Recent papers with the use of highly complicated techniques managed t o increase the efficiency of the tests by working with more classified data. Studies on individual security returns by Lintner (1965) and Douglas (1969) werenacirc;â‚ ¬Ã¢â€ž ¢t so hopeful. Fama and McBeth (1973) investigated the relationship between the average returns and beta using data in a durable period. Roll (1977) made two observations by testing the CAPM. The first one is that the market portfolio is mean-variance efficient when beta and expected return is linear correlated. The second is that if you do not know exactly the market portfolio is ineffective to judge the validity of CAPM. A lot of studies (Banz, 1981; Basu, 1983; Chan et al., 1991; Rosenberg et al., 1985) showed that not only the market beta affects the expected return but also other variables like the size, macroeconomics variables, p/e ratio and book to market value ratio have an important impact on security returns. Fama and French (1992) testing the validity of CAPM found that to reduce errors in beta me asurement is powerful to take into account also non-market risk factors such as differences between return and low/high book to market stocks or portfolio of small/large stocks. Kothari et al,( 1995); instead of monthly returns data used twelve-monthly to approximate beta and found a considerable relationship between cross-sectional returns and beta. A study on US-stocks during 1926-1990 made by Pettengill et al, (1995) described a systematic correlation on beta and return for the whole period when market varies up and down. Downs and Ingram (2000) found that the average of returns are positive correlated with beta, negative with total risk and far from firm-size. Galagedera and Silvapulle (2003) reported strong empirical evidence to show the bond between returns and systematic co-moments in markets. Another approach in 2005 by Galagedera and Faff who developed a three-beta (low-neutral-high) asset pricing model to observe if the relation beta-return varies on up and down market env ironment was encouraging. Validity of the CAPM and the alternative theory of APT After many empirical tests through the years on the CAPM by literature it is commonly accepted by financial world and it is used to approximate the cost of capital. It is a safe method to measure the expected return with risk and show strong correlation between them. That does not guarantee that the CAPM is infallible but certainly is a practical model until now. However alternative theories came out and a well known is Stephen Rossacirc;â‚ ¬Ã¢â€ž ¢s (1976) Arbitrage Pricing Theory (APT). Like the CAPM, Arbitrage Pricing Theory deals with expected return and risk but also assumes macroeconomic factors and applies to well-diversified portfolios where unique risk does not exist. The main idea is the measurement of systematic risk with more than one ways. Market and efficient portfolios are not the objective of APT in contrast with the Capital Asset Pricing Model. Both models have advantages and d isadvantages but there are undeniable useful tools for financial aims. Implications of CAPM to investors and financial managers The CAPM shed light on many fields of security analysis and portfolio management. Progress on the analysis of stock exchange-market exists from early practical applications of CAPM. Many studies involved with the course of risk redaction by diversification and the measurement of systematic risk by beta factor. Beta is in a great interest for investors and financial managers as help them to choose the best portfolio by representing the expected returns and shows the level of risk. Beta associates security return with market return so when the market goes up investments behave with the same way and that forces investors for better decisions. The CAPM gave a framework to estimate the performance of investments. Moreover beta-equity can be useful for a company without debt to point the systematic risk of assets. The debt of a company increases the risk of shareholders and therefore the rate of return that is required. An additional risk exists from financial influence and that drives to a higher beta. The CAPM consequently specifies the foundation that a firms-adjusted risk cost of capital must be measured to find out its going concern. . Conclusion This study uses theoretically earlier information about the CAPM and presents empirical facts to support the validity of this model. A summary of the principals of the CAPM are analyzed such as the assumptions under the CAPM, the Security Market Line (SML) and the Capital Market Line (CML). The CAPM provides a practical method to handle both return and risk. Market risk is measured by beta factor and is actually related to the investment decision. It is a substantial variable for portfolio management. Using CAPM is important not only for investors but also for financial managers for choosing the efficient projects. Benefits exist also for individuals and the economy as the CAPM built the foundations of finance theory. In addition the alternative theory of Arbitrage Pricing Theory (APT) is also useful and significant but more theories have to be developed. However more empirical tests and examinations should be done in the future regarding the assumptions of the CAPM a nd the suitable measure of risk to object the best performance.