Stillborn Babies

Still Born Babies What is stillbirth? The clinical meaning of a despite everything birth is the point at which a child is conceived with no indications of life at or following 20 weeks or gauging more than 500g before work. Demise in the baby may have happened during pregnancy, which is intrauterine passing, work, or birth. Most despite everything births are intrauterine. As uncommon as stillbirth may be, it happens once in each 160 pregnancies. What causes a stillbirth? There are various known reasons for stillbirth. Once in a while more than one of these causes may add to the baby’s passing exposition essayist reviews.Common causes include: * Birth absconds: Such as Down condition. Others have other birth abandons coming about because of hereditary, natural or obscure causes. * Placental issues: Placental unexpectedness. In this condition, the placenta strips away, incompletely to totally, from the uterine divider before conveyance. It brings about substantial draining that can compromise the life of mother and child. Now and then it can make the embryo bite the dust from absence of oxygen. * Poor fetal development: Fetuses who are developing also gradually are at expanded danger of stillbirth.About 40 percent of stillborn infants have poor development. Expanded hazard by smoking or hypertension. * Infections: Infections including the mother, hatchling or placenta seem to cause around 10 to 25 percent of stillbirths. These incorporate genital and urinary tract contaminations that may go undiscovered until they cause genuine intricacies * Chronic wellbeing conditions in the pregnant lady: About 10 percent of stillbirths are identified with constant wellbeing conditions in the mother, for example, hypertension, diabetes, kidney infections, and blood thickening issue. Umbilical rope mishaps: These remember a bunch for the line or irregular arrangement of the rope into the placenta, causing there to be a deficiency of oxygen to the hatchling. Different rea sons for stillbirth incorporate injury, (for example, auto crashes), postdate pregnancy (a pregnancy that keeps going longer than 42 weeks), Rh malady (a contrariness between the blood of mother and infant), and absence of oxygen (asphyxia) during a troublesome conveyance. These causes are exceptional. What are a few factors that expansion a mother’s possibility of a stillbirth? Ladies 35 years of age or more established: As age expands, there are more dangers to pregnancy and all around wellbeing. * Malnutrition: Just like us, the embryo will just make due for such a long time with practically no nourishment. * Inadequate pre-birth care: Women who are a high hazard pregnancy must be increasingly cautious with their day by day exercises. Indeed, even a customary pregnancy requires rest, low pressure and monitoring your environmental factors. * Smoking: Cigarette smoke contains in excess of 4,000 synthetics, including things like cyanide, lead, and in any event 60 malignant gr owth causing compounds.When you smoke during pregnancy, that harmful mix gets into your circulatory system, the fetus’ just wellspring of oxygen and supplements. * Alcohol and medication misuse: Alcohol and medications, poison the circulation system to the hatchling, it’s just wellspring of oxygen and supplements. * African-American ethnicity: It isn't known why African American ladies are about twice as likely as other American ladies to have a stillborn child. How is fetal demise analyzed? A ultrasound can tell if the embryo has kicked the bucket by indicating the fetus’ heartbeat. It once in a while can help clarify why the embryo died.The specialist likewise can do some blood tests on the lady to help affirm why the baby kicked the bucket. What occurs after the determination? Subsequent to discovering that the embryo has passed on in the belly, the mother must proceed with the introduction of her stillborn. Regardless of whether the guardians need to hold up until work falls into place without a hitch or if they’d like work to be actuated is their decision. Testing for the reason for the stillbirth requires consent from the two guardians. A particular specialist will play out a post-mortem examination on the child to uncover the cause.This is generally done to forestall a rehashed stillbirth. What are the odds of a recurrent stillborn? The probability of an intermittent stillbirth relies on the reason for your underlying stillbirth. While rehashed stillbirths do occur, they are exceptionally phenomenal. Indeed, even on account of hereditary deformities, repetitive stillbirths are far-fetched. Book index 1. Babycenter. â€Å"When an infant is stillborn †BabyCenter Canada. † Pregnancy, infant and little child wellbeing data at BabyCenter Canada †BabyCenter Canada. Babycenter, n. d. Web. <http://www. babycenter. an/a1014800/when-a-child is-stillborn#section1>. 2. Walk of Dimes. â€Å"Stillbirth | Baby | Loss and grief | March of Dimes. † Pregnancy, Baby, Prematurity, Birth Defects | March of Dimes. http://www. marchofdimes. com/child/loss_stillbirth 3. â€Å"Stillbirth: Trying to Understand †American Pregnancy Association. † American Pregnancy Association †Promoting Pregnancy Wellness. National Stillbirth society, n. d. Web. 10 Apr. 2013. <http://americanpregnancy. organization/pregnancyloss/sbtryingtounderstand. html>. 4. Walk of Dimes. â€Å"StillbirthA †Loss and misery. Pregnancy, Baby, Prematurity, Birth DefectsA |A March of Dimes. Walk Of Dimes, n. d. Web. 12 Apr. 2013. <http://www. marchofdimes. com/child/loss_stillbirth. html>. 1. â€Å"Understanding stillbirth †analysis and treatment. † WebMD †Better data. Better wellbeing.. WebMD, 23 Apr. 2012. Web. 11 Apr. 2013. <http://www. webmd. com/child/understanding-stillbirth-treatment>. 2. Epigee. organization. â€Å"Pregnancy Help and Information: Stillbirth. † Epigee Pregnancy Resource. http://www. epigee. organization/pregnancy/stillbirth. html (got to April 11, 2013).

Four Women in American Music History Free Essays

American music history has grown a unimaginable sum over the most recent hundred years. Before that time, there were not many styles of music that began in America. Be that as it may, with the coming of jazz and related styles, American music culture was conceived. We will compose a custom article test on Four Women in American Music History or on the other hand any comparable theme just for you Request Now Blues is one of the early styles of music that is genuinely American, and there are numerous American specialists who sang or acted in that style. Truth be told, blues is as yet well known today, despite the fact that it has changed after some time. Blues is a significant and long haul American melodic style, which has effectsly affected melodic culture from the mid 1900s through today. Bessie Smith was an early blues vocalist. She was famous during the 1920s and 30s, and was known as much for her hard-drinking, unpleasant life as much as her music. She sang about what she knew. Bessie was an African American lady who enjoyed sex and liquor, and had a solid temper. She never surrendered without a battle, either in her music or her life. Getting into a battle with Bessie wasn’t something an individual needed to do, either, in light of the fact that she was more than six feet tall and weighed around 200 pounds. Bessie had a background marked by getting into clench hand battles with individuals, male or female. She additionally took off after her ex with a weapon when she discovered him undermining her, in the wake of pummeling his darling. In any case, Bessie herself was known for laying down with various the two people (Whitney). Musically, Bessie was not so much prepared. She was unable to understand music, and depended on different artists to record her tunes for her. She wrote her own verses, however. She was an imposing nearness in front of an audience, ready to sing uproariously and emphatically as a result of her size, and her propensity to sing in the range that was most effortless for her. Recorded as a hard copy her music, Bessie would in general change existing tunes, and here and there make new ones, with the goal that they lay well in her â€Å"good† run (Whitney). Here is a case of Bessie’s verses, which give her sentiments about existence clearly: â€Å"I ain’t no high yella, I’m a profound executioner earthy colored. /I ain’t going to wed, ain’t going to settle down. /I’m going to drink great moonshine and rub these browns down. /See that long bereft street, Lawd you know it’s going to end,/and I’m a decent lady and I can get bounty men† (Whitney). Bessie was otherwise called something of a supremacist. While her fans were both high contrast, she was inconsiderate to the two whites and lighter-cleaned blacks. Indeed, even at the tallness of her vocation, when she had enough cash to live as she picked (even as a white individual may, in the mid 30s), she decided to remain in the city and to carry on with the existence that was natural to her. Her verses here give her deduction on this issue: â€Å"Mister rich man, rich man, open up your heart and psyche,/Mister rich man, rich man, open up your heart and brain;/Give the poor man an opportunity, help stop these hard, difficult situations. /While you’re livin’ in your manor you don’t recognize what tough situations implies,/While you’re livin’ in your house you don’t comprehend what difficult situations implies;/Poor working man’s spouse is starving your better half is livin’ like a queen† (Whitney). Ethel Waters is a blues vocalist who started performing later in Bessie’s profession. While Bessie was principally performing and notable during the 1920s, Ethel turned out to be better known during the 1930s (her vocation did authoritatively start in 1921, however). Ethel was explicitly an alternate sort of blues artist than Bessie, and in certainty was not quite the same as her from various perspectives. Ethel is additionally of African American not too bad, however she experienced childhood in the North and was vigorously affected by white entertainers. At the point when she started performing expertly, Ethel joined a gathering of blacks who called themselves â€Å"Cakewalk singers,† which was particularly not quite the same as the more customary blues artists, as Bessie (PBS). Ethel’s acknowledgment of whites can be followed to what was an unpleasant start for her. She was conceived when her mom was just 12. Her mom had been assaulted by a white man, John Waters. Ethel, at that point, is half-white, and conveys her father’s last name. She was raised by her maternal grandma in destitution, and started singing at age 5. Her beginnings are significantly more like Bessie’s, yet what she did to occupy her time later contrasts generally (Myers). Ethel worked with various renowned jazz entertainers, including Duke Ellington. Notwithstanding her singing profession, Ethel was likewise an entertainer, a part of her life that in the long run went to the cutting edge. Her singing style was not so solid as Bessie’s, yet she performed dramatically and figured out how to catch the audience’s enthusiasm for every last bit of her music. This proved to be useful, as she kept performing through the 1960s and 70s, working around then with Billy Graham (PBS). At last, Bessie’s effect on Ethel was extremely aberrant. Both were jazz artists in when African Americans were first on the ascent in fame on the stage. Bessie’s coarseness may have given Ethel openings she probably won't have in any case had. From various perspectives, however, the two were totally different; demeanor, style, and the sky is the limit from there. Dinah Washington is another significant artist in this chain of history. Her original name was Ruth Jones, and she was conceived in 1924. She is fundamentally more youthful than both Ethel and Bessie, whose professions were close to their pinnacles when she was conceived. Music was in Dinah’s family from the earliest starting point. Her mom was a congregation piano player, and instructed her to play at a youthful age. She was join and visiting when she was 16, and had won prizes. Be that as it may, in spite of the fact that her underlying roots were in the congregation, Dinah ached to work in common music, to be specific jazz (Dahl). At age 19, Dinah got her enormous break, singing with Lionel Hampton’s Big Band, at that point one of the most well known music styles. By 1945, she was recording her own performance work for the Apollo mark and Mercury records, and by 1948, she was en route to significant fame. 1959 was her greatest year, when she sang â€Å"What a Dif’rence a Day Makes† (Dahl). In her own life, Dinah was like Bessie. She had numerous spouses, and she drank a great deal. Truth be told, liquor and medications in the end murdered her toward the finish of 1963 (Dahl). What's more, she additionally cherished the better things, including hide, garments, and vehicles. Her character was known as â€Å"feisty,† and she could be snapping one moment and liberal the following (Cohodas). From the outset, Christina Aguilera doesn’t look a lot of like different stars. For one, she isn’t dark. For another, she was brought into the world after the entirety of different vocalists had kicked the bucket. Notwithstanding, it is her underlying foundations and impacts that she is like them. Like Dinah, she is biracial, with a mother who is Irish and a dad who is Ecuadorian. Her dad was in the military, which implied that Christina voyaged a great deal as a youngster (Biggest Stars). Additionally like different artists, Christina was keen on singing and performing from the time she was a little youngster. Her family was additionally melodic, with her mom performing on violin and piano expertly. Christina had a short, two-year spell on The Mickey Mouse Club when she was a youngster, working with different artists who later got renowned, as Britney Spears and Justin Timberlake (Biggest Stars). Christina’s starting music was certainly fly, with her first number one single titled â€Å"Genie in a Bottle. † The single beat both the U. S. what's more, UK diagrams in 1999. For some time longer, Christina proceeded in the pop kind, recording for the film Mulan, and singing another form of â€Å"Lady Marmalade† with a few other female pop stars (Biggest Stars). Christina’s work in the long run started to appear to be less critical to her, and she chose to record her 2002 collection â€Å"Stripped. † The collection was the main that truly gave her experience and impacts. Her remarks about this collection: â€Å"Coming off of the stature of being a piece of such a major pop-rage wonder, that symbolism of that cutout darling, without it being me, I simply needed to bring everything down and get it away from me. What's more, that is the reason I really named the collection Stripped, in light of the fact that it is tied in with being genuinely stripped down and truly uncover to open my inner self and heart. † This collection utilized a wide range of impacts, including soul, RB, rock, hip-bounce and Latin (Biggest Stars). Aguilera’s impacts were like the previous stars referenced. She looked to soul and RB, the two of which are styles commonly recorded by African Americans. The blues part of RB, specifically, is intriguing to note. Aguilera was following in the strides of the other female jazz vocalists with this style. Additionally, like Dinah Washington, Aguilera sang pop (Dinah did fly notwithstanding her jazz roots). When all is said in done, each of the four of these ladies share things practically speaking, and things that are unique. Each grew up under comparative conditions, frequently with generally maternal impacts. Most had a melodic foundation at home. Most grew up poor, and all had an early ability for music and singing. Most additionally had a desire for sex, medications, and some more unpleasant things throughout everyday life, and made some hard memories at some point. Be that as it may, every wa exceptional. Bessie was surely the greatest and generally gruff of the gathering, while Christina remained of the furthest edge as the â€Å"sweetheart† of fly for a little while. Christina was likewise unique in that she was not of African American nice at all, despite the fact that Ethel was additionally half-white. A portion of the artists, to be specific Dinah, had their beginning in gospel music, while others went straight for jazz or pop. By and large, it is intriguing how strikingly comparative the craftsmen are, despite the fact that there are additionally exceptionally huge contrasts in their lives and styles. Their accounts and back

bloggers.addAll( newBloggers);

bloggers.addAll( newBloggers); This summer we (Matt, Kris, Chris, the ‘15s, and I), after a rigorous and emotional selection process, hired, from among 62 applicants (including Snively), four freshman bloggers and two seniors (not including Snively). In addition, we are welcoming a new guest blogger from GEL, the Gordon Engineering Leadership Program. Thank you to everyone who applied. Reading your applications was a huge joy to all of us, and the final decisions were not easy. If you applied and didn’t make it this year, I highly recommend trying again next summer. I got in as a sophomore, the second time I applied. Without further ado, our new bloggersâ€" Freshmen Joe B. ‘18  is from Falmouth, MA, an hour and a half from MIT, where there are faeries and sprites and an undiagnosed dark force. Right now he lives in East Campus. He is planning to major in course 6 or course 18, in part to find out what will happen to the Earth once the rabbit population collectively weighs more than the planet it lives on. Joe is also an extremely talented musician. I tried to listen to one of his songs and I ended up listening to his entire SoundCloud. Here is one of my favorites: Joe wants to show you something that might be cuter than the cutest thing. Joel G. ‘18’s mind palace is his living room floor. He plays by his own rules, which is fine, because there are many ways to skin a rabbit (and besides, his rules are pretty good). His hobbies include breeding carnivorous plants, genetically modified spiders, and dragons. This sentence is a lie. So is the sentence before it. Right now he lives in Burton-Conner and is thinking about majoring in course 6, maybe. Joel wants to show you this. Michelle G. ‘18  is from somewhere in New Jersey, where she may or may not have had a dark, traumatizing life experience involving rabbits. She is a YouTuber, a tumblerer, and a listener of angsty acoustic music. Right now she lives in Senior Haus and is thinking about majoring in course 6-3 and linguistics. Michelle wants to show you her favorite blog post on her second-favorite admissions-related blog. Yuliya K. ‘18  is from Donetsk, Ukraine, where she almost had a pet rabbit, and, more recently, Powell, Ohio. Right now she lives in East Campus, where she recently pulled her first ever all-nighter. Yuliya has an uncommon perspective in and enthusiasm for mathematics; appropriately, she is planning to major in course 18 (theoretical). Yuliya wants to show you something that might also be cuter than the cutest thing. Seniors Chel R. ‘15  lives in Simmons. Her major is a unique combination of the technical and the human: course 21E (CMS and course 6) and course 21W. She has written several novels, and is currently working on another one for her senior thesis. In a past life, she was my roommate at Random. Chel has previously appeared on the blogs to talk about stories in the age of the Internet. You might have met her in the Sherlock fandom, among others. Right now she is really into The X-Files. She wants to show you this video about science. And the rabbits? They were delicious. Danny B.-D. ‘15  grew up a few blocks away from the American Museum of Natural History. Today, he is East Campus historian. Danny is majoring in “8, with EECS classes sprinkled to taste.” He has also appeared on the blogs before: once as EC historian and once as the creator of CourseRoad, an invaluable tool for procrastination planning your future at MIT. Danny wants to show you the thought-provoking making of the machine that makes.  He didn’t tell us much about rabbits, but apparently the teddy bear was almost a possum. GEL Neerja A. ‘16  is majoring in course 6-1 and minoring in theatre. Her professional interests are in optics, electronics, signals, and international development. Through GEL she is hoping to develop the skills necessary to truly apply what she is learning at MIT and take technology to market. My experience with GEL is limited to a guest lecture in 6.UAT by Professor Joel Schindall, co-director of GEL. 6.UAT is course 6’s mandatory soft-skills class. I’m still growing (which has come into stark visibility in my first few weeks as a TA), but the things that I learned about punctuality, public speaking, negotiation, and presenting myself I learned largely from 6.UAT. Dr. Schindall’s guest lecture was specifically about being an effective employee: applying work in the right directions, interacting productively with superiors, and delivering on promises even when the delivery is ostensibly in someone else’s control. There were a few short modules in 6.UAT that ended up having a massive positive impact on the way that I think about the work that I do and the way that I interact with the people around me. One of them was the negotiation section and one of them was Dr. Schindall’s lecture. We had a short conversation after lecture about my non-punctuality (“Hi there! My name is Lydia. I am the least punctual person I know.”) and my work experiences. He was surprisingly appreciative of my honesty and my enthusiasm for growth, and his approval helped me believe in myself enough to improve. I didn’t end up applying to GEL but I am extremely glad to have experienced Dr. Schindall’s lecture. Below is a talk that Dr. Schindall gave at the MIT Club of Northern California. He covers some of the same ideas that he covered in 6.UAT: in particular, I think it’s worth your time to listen to his “A Tale of Two Employees,” which starts at 6:50. That’s all! I’m excited for our seven new bloggers to start blogging soon (immediately, to be specific). They’ll be able to tell you more about themselves and their stories, past and the unfolding future at MIT. Once again, thank you to everyone who applied, and please join me in welcoming our new bloggers!

A Evolving Information Assurance Landscape - 764 Words

1. INTRODUCTION: In a constantly evolving information assurance landscape, it has become increasingly challenging for organizations to protect their information resources. The changing ecosystem in which industries operates, adoption of new technologies by organizations, integration of IT into organization’s core business processes, and substantial increase in the use of internet based services by consumers for daily activities like banking, communications, online shopping etc., pose new threats to organizations. A recent Gartner survey states that 77% of the 500 business leaders of companies having revenues over $1 billion confirmed to increased levels and new types of risks posed by the digital world. Also, majority of the participants agreed that organizations are not investing the required levels for mitigating the new risks (Gartner, 2015). The low cost computing power has also enabled organizations to aggregate a wide variety of consumer information like credit card details, Social Security Number (SSN) etc., which when fallen into wrong hands could jeopardise the security of common people. The cancellation of UK National Identity Card due to this very reason is a classic example of the dangers of collecting personal information of consumers (Davies, 2011). A breach could also result in loss of revenues and credibility to organizations. For example, the data breach at Target in the year 2013 resulted in 46% fall in revenues and costed over $61 million in expenseShow MoreRelatedSecurity Issues Of Cloud Environments : A Survey Essay797 Words   |  4 Pagesbreaking into data centers, malicious employees, and exploits by those in the community who search for vulnerabilities. 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Since such security risks are always going to present in the cyberRead MoreCloud Computing And Its Effect On The Security Of Service Users Data2052 Words   |  9 Pagesof whom providers offering applications for software companies which helps in decrease costs in deployment or nomination( install) of applications.in this project we will be rating SaaS service delivery model, and presenting several advises for evolving the SaaS work and solution for business. and talking about ( how the SaaS increased security issues and challenges) ?! 2- related work and trends According to a Gartner Group estimate, SaaS sales in 2015 reached $150 billion in yearly incomesRead MoreAn International Financial Services Group6096 Words   |  25 Pages2014 †¢ ~2.1% increase in new business profit †¢ Jackie Hunt: new CEO of Prudential UK Europe (Former CEO: Tidjane Thiam ) History of Prudential 1848 Prudential is established as Prudential Mutual Assurance Investment and Loan Association in Hatton Garden, London, offering loans and life assurance to professional people. 1854 Prudential opens the Industrial Department to sell a new type of insurance, Industrial Insurance, to the working classes, for premiums of a penny and upwards. 1871 The Company

Essay about Virtual Situated Learning Environment (VSLE)

There is a embarrassment of changes facing society as new interactive communication knowledge accelerates the achievements of economies of depth. of knowledge holds considerable untapped potential for performance gains. the workplace as being a stable place in a single central location, with normal daily hours confined to 9-5 daylight hours, is being replaced by global organizations (through globally positioned parts of the business, global outsourcing, and/or global supply chains) and global communication networks (email, global blogs, diaries, The new global workplace requires managers factor of production, knowledge, and thus managers manage by the consent of the assist the growing number of knowledge workers to handle a large†¦show more content†¦Despite criticism that the on-line learning environment has the potential to return carefully, the on-line environment it does provide opportunities to design a learning on designing on-line learning opportunities that are cheap er rather than adding value and value-adding on-line learning opportunities that do more than deliver information to use the on-line learning environment to network, share their tacit knowledge, and engage in continuous learning, particularly those located in global workplaces. This learning environment to a focus on re-designed management learning opportunities that opportunities need to cater for the time and place requirements of the global manager. VSLE can be designed to be accessible by all managers at all times and from all parts The focus in this section is on how the on-line environment can be used to design designed to complement rather than replaced the F2F learning environment, and thus our conclusions can only relate to this mixed learning environment. other a practicing manager working as a

Montecarlo Simulation Free Essays

string(115) " random number generator functions as inputs for your model, automates Monte Carlo simulation, and creates charts\." RiskSim is a Monte Carlo Simulation add-in for Microsoft Excel 2000–2010 (Windows) and Microsoft Excel 2004 (Macintosh). RiskSim provides random number generator functions as inputs for your model, automates Monte Carlo simulation, and creates charts. You read "Montecarlo Simulation" in category "Papers" Your spreadsheet model may include various uncontrollable uncertainties as input assumptions (e. We will write a custom essay sample on Montecarlo Simulation or any similar topic only for you Order Now g. , demand for a new product, uncertain variable cost of production, competitor reaction), and you can use simulation to determine the uncertainty associated with the model’s output (e. g. , annual profit).RiskSim automates the simulation by trying hundreds of what-ifs consistent with your assessment of the uncertainties. To use RiskSim, you (1) (2) (3) (4) (5) (6) create a spreadsheet model optionally use SensIt to identify critical inputs enter one of RiskSim’s fourteen random number generator functions in each input cell of your model in Excel 2007 or 2010, choose Add-Ins | Risk Simulation | One Output; in Excel 2003 and earlier versions, choose Tools | Risk Simulation | One Output from Excel’s menu specify the model output cell and the number of what-if trials interpret RiskSim’s histogram and cumulative distribution charts.RiskSim facilitates Monte Carlo simulation by providing: Fourteen random number generator functions Ability to set the seed for random number generation Automatic repeated sampling for simulation Frequency distribution of simulation results Histogram and cumulative distribution charts All of RiskSim’s functionality, including its built-in help, is a part of the RiskSim XLA file. There is no separate setup file or help file.When you use RiskSim on a Windows computer, it does not create any Windows Registry entries (although Excel may use such entries to keep track of its addins). 98 Chapter 10 Monte Carlo Simulation Using RiskSim 10. 2 USING RISKSIM FUNCTIONS RiskSim adds fourteen random number generator functions to Excel. You can use these functions as inputs to your model by typing in a worksheet cell or by using the Function Wizard. From the Insert menu choose Function, or click the Function Wizard button. RiskSim’s functions are listed in a User Defined category.The fourteen functions are: RANDBINOMIAL(trials,probability_s) RANDBIVARNORMAL(mean1,stdev1,mean2,stdev2,correl12) RANDCUMULATIVE( value_cumulative_table) RANDDISCRETE(value_discrete_table) RANDEXPONENTIAL(lambda) RANDINTEGER(bottom,top) RANDLOGNORMAL(Mean,StDev) RANDNORMAL(mean,standard_dev) RANDPOISSON(mean) RANDSAMPLE(population) RANDTRIANGULAR(minimum,most_likely,maximum) RANDTRUNCBIVARNORMAL(mean1,stdev1,mean2,stdev2,correl12, min1,max1,min2,max2) RANDTRUNCNORMAL(Mean,StDev,MinValue,MaxValue)) RANDUNIFORM(minimum,maximum) RiskSim’s RAND†¦ functions include extensive error checking of arguments.After verifying that the functions are working properly, you may want to substitute RiskSim’s FAST†¦ functions which have minimal error checking and therefore run faster. From the Edit menu choose Replace; in the Replace dialog box, type =RAND in the â€Å"Find What† edit box, type =FAST in the â€Å"Replace with† edit box, and click the Replace All button. 10. 3 UPDATING LINKS TO RISKSIM FUNCTIONS When you insert a RiskSim random number generator function in a worksheet cell, th e function is linked to the disk location of the RiskSim XLA file you are currently using.During the current Excel session, the formula bar shows only the name of the RiskSim function. But when you save and close the workbook, Excel saves the complete path to the disk location of RiskSim function. For example, after closing and reopening the workbook, the formula bar might show C:MyAddIns isk240s. xlaRandNormal(100, 10). This is standard behavior for Excel user defined functions like the ones contained in the RiskSim XLA file. When you open the workbook, Excel looks for the RiskSim XLA file using the saved path. If Excel cannot find the RiskSim XLA file at the saved path location (e. . , if you deleted the RiskSim XLA file from the C:MyAddIns folder or if you opened the workbook on another 10. 3 Updating Links To RiskSim Functions 99 computer where the RiskSim XLA file is not located at the same path), Excel displays a dialog box like the one shown below. Figure 10. 1 Excel 2003 Warning To Update Links If you see this dialog box or a similar warning when you open an Excel file, choose the â€Å"Don’t Update† option. The workbook will be opened, but any cell containing a reference to a RiskSim function will display the #NAME? or similar error code.To update the links after the workbook is open, be sure that a RiskSim XLA file is open. Then choose Edit | L inks to see the dialog box shown below. In Excel 2007 or 2010, if you open a workbook with RiskSim functions referring to a RiskSim file location that no longer exists, you may see a warning. In Excel 2007, if you click the Options button of the security warning, you can click OK in the Security Options dialog box to dismiss the warning. Before you update the links, be sure that the RiskSim XLA file is open. In Excel 2007, choose Office Button | Prepare | Edit Links to Files to see the dialog box shown below.In Excel 2010, choose File | Info | Edit Links to Files to see the Edit Links dialog box. Figure 10. 2 Edit Links Dialog Box To update the links, click the Change Source button. A file browser window will open, where you can navigate to the RiskSim XLA file that is open. After you select the file using the file browser, click OK. Back in the Edit Links dialog box, click the Close button. 100 Chapter 10 Monte Carlo Simulation Using RiskSim In Excel 2003 the Edit Links dialog box has a Startup Prompt button. To avoid possible problems when Excel tries to automatically update links while a ile is being opened, we recommend the default â€Å"Let users choose to display the alert or not. † Figure 10. 3 Excel 2003 Startup Prompt Dialog Box 10. 4 MONTE CARLO SIMULATION After specifying random number generator functions as inputs to your model, from the Tools choose Risk Simulation | One Output. Figure 10. 4 RiskSim Dialog Box Optionally, select the â€Å"Output Label Cell† edit box, and point or type a reference to a cell containing the name of the model output (for example, a cell whose contents is the text label â€Å"Net Profit†). Select the â€Å"Output Formula Cell† edit box, and point to a single cell on your worksheet or type a cell reference.The output cell of your model must contain a formula that depends, usually indirectly, on the model inputs determined by the random number generator functions. Leave the Random Number Seed unchanged, or select the â€Å"Random Number Seed† edit box, and type a number between 1 and 2,147,483,647. Use an integer value without commas or other separators. Select the â€Å"Number Of Trials† edit box, and type an integer value between 2 and 32,000. This value, sometimes called the sample size or number of iterations, specifies the number of times the worksheet will be recalculated to determine output values of your model. 0. 5 Random Number Seed 101 10. 5 RANDOM NUMBER SEED The â€Å"Random Number Seed† edit box on the RiskSim dialog box allows you to set the seed for RiskSim’s random number generator functions. The seed must be an integer in the range 1 through 2,147,483,647. RiskSim’s random number generator functions depend on RiskSim’s own uniform random number function that is completely independent of Excel’s built-in RAND(). Random numbers generated by the computer are actually pseudo-random. The numbers appear to be r andom, and they pass various statistical tests for randomness.But they are actually calculated by an algorithm where each random number depends on the previous random number. Such an algorithm generates a repeatable sequence. The seed specifies where the algorithm starts in the sequence. A Monte Carlo simulation model usually has uncontrollable inputs (uncertain quantities using random number generator functions), controllable inputs (decision variables that have fixed values for a particular set of simulation iterations), and an output variable (a performance measure or operating characteristic of the system).For example, a simple queuing system model may have an uncertain arrival pattern, a controllable number of servers, and total cost (waiting time plus server cost) as output. To evaluate a different number of servers, you would specify the same seed before generating the uncertain arrivals. Then the variation in total cost should depend on the different number of servers, not o n the particular sequence of random numbers that generates the arrivals. 10. 6 ONE-OUTPUT EXAMPLE In this example the decision maker has described his subjective uncertainty using normal, triangular, and discrete probability distributions.Figure 10. 5 One-Output Example Model Display 1 2 3 4 5 6 7 8 9 A B Software Decision Analysis Unit Price Units Sold Unit Variable Cost Fixed Costs Net Cash Flow $29 739 $8. 05 $12,000 $3,485 C D E F G H Price is controllable and constant. Normal Mean = 700, StDev = 100 Triangular Min = $6, Mode = $8, Max = $11 Discrete Value Probability $10,000 0. 25 $12,000 0. 50 $15,000 0. 25 Figure 10. 6 One-Output Example Model Formulas 1 2 3 4 5 6 7 8 A Software Decision Analysis Unit Price Units Sold Unit Variable Cost Fixed Costs Net Cash Flow B 29 =INT(RANDNORMAL(700,100)) =RANDTRIANGULAR(6,8,11) =RANDDISCRETE(E7:F9) =B4*(B3-B5)-B6 102 Chapter 10 Monte Carlo Simulation Using RiskSim Figure 10. 7 RiskSim Dialog Box for One-Output Example 10. 7 RISKSIM OUTPU T FOR ONE-OUTPUT EXAMPLE When you click the Simulate button, RiskSim creates a new worksheet in your Excel workbook named â€Å"RiskSim Summary 1. † A summary of your inputs and the output is shown in cells L1:R9 with the accompanying histogram and cumulative distribution charts. 10. 7 RiskSim Output for One-Output Example 103 Figure 10. RiskSim Summary Output for One-Output Example 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 L RiskSim Date Time Workbook Worksheet Output Cell Output Label Seed Trials M (current date) (current time) (file name) Simulation Model for One Output $B$8 Net Cash Flow 9999 1000 RiskSim  ? Histogram 80 70 60 N O P Q Mean St. Dev. Mean St. Error Minimum First Quartile Median Third Quartile Maximum Skewness R $2,207 $2,816 $89 -$5,917 $184 $2,281 $4,148 $11,291 0. 0409 Frequency 50 40 30 20 10 0 ? 6,000 ? $4,000 ? $2,000 $0 $2,000 $4,000 $6,000 $8,000 $10,000 $12,0 00 Net  Cash  Flow RiskSim  ? Cumulative  Chart 1. 0 0. 9 Cumulative  Probability 0. 8 0. 7 0. 6 0. 5 0. 4 0. 3 0. 2 0. 1 0. 0 ? $6,000 ? $4,000 ? $2,000 $0 $2,000 $4,000 $6,000 $8,000 $10,000 $12,000 Net  Cash  Flow The histogram is based on the frequency distribution in columns I:J. The cumulative distribution is based on the sorted output values in column C and the cumulative probabilities in column D. 104 Chapter 10 Monte Carlo Simulation Using RiskSim Figure 10. 9 RiskSim Numerical Output for One-Output ExampleA 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 B Trial Net Cash Flow 1 $2,815 2 -$1,381 3 -$496 4 -$866 5 $5,795 6 -$3,320 7 $3,295 8 $8,360 9 -$2,157 10 $4,313 11 -$1,375 12 $2,198 13 -$744 14 $3,104 15 -$2,814 16 $4,165 17 -$2,575 18 $2,643 19 -$3,676 20 $2,186 21 -$3,492 22 -$847 23 $3,335 24 $4,641 25 $4,814 26 $536 27 -$909 28 $4,477 29 -$597 30 $4,018 31 $3,012 32 $4,590 33 $174 34 $3,257 3 5 $6,952 36 $6,252 37 $4,017 38 $5,386 C D Sorted Cumulative -$5,917 0. 0005 -$5,860 0. 0015 -$5,422 0. 025 -$4,702 0. 0035 -$4,646 0. 0045 -$4,601 0. 0055 -$4,513 0. 0065 -$4,439 0. 0075 -$4,057 0. 0085 -$4,037 0. 0095 -$4,027 0. 0105 -$3,884 0. 0115 -$3,846 0. 0125 -$3,715 0. 0135 -$3,684 0. 0145 -$3,676 0. 0155 -$3,561 0. 0165 -$3,525 0. 0175 -$3,492 0. 0185 -$3,468 0. 0195 -$3,320 0. 0205 -$3,285 0. 0215 -$3,250 0. 0225 -$3,178 0. 0235 -$3,118 0. 0245 -$3,104 0. 0255 -$3,071 0. 0265 -$3,065 0. 0275 -$3,054 0. 0285 -$2,960 0. 0295 -$2,957 0. 0305 -$2,830 0. 0315 -$2,820 0. 0325 -$2,814 0. 0335 -$2,795 0. 0345 -$2,671 0. 0355 -$2,654 0. 0365 -$2,638 0. 375 E F Percent 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% G Percentile -$5,917 -$2,459 -$1,405 -$809 -$196 $184 $694 $1,032 $1,442 $1,835 $2,281 $2,634 $2,972 $3,324 $3,737 $4,148 $4,617 $5,142 $5,673 $6,736 $11,291 H I J Upper Limit Frequency -$6,000 0 -$5,500 2 -$5,000 1 -$4,500 4 -$4,000 4 -$3,500 7 -$3,000 11 -$2,500 19 -$2,000 23 -$1,500 26 -$1,000 35 -$500 39 $0 62 $500 47 $1,000 65 $1,500 59 $2,000 64 $2,500 63 $3,000 75 $3,500 65 $4,000 57 $4,500 58 $5,000 49 $5,500 51 $6,000 30 $6,500 22 $7,000 18 $7,500 15 $8,000 7 $8,500 7 $9,000 7 $9,500 2 $10,000 4 $10,500 0 $11,000 1 $11,500 1 $12,000 0In column D, the cumulative probabilities start at 1/(2*N), where N is the number of trials, and increase by 1/N. The rationale is that the lowest ranked output value of the sampled values is an estimate of the population’s values in the range from 0 to 1/N, and the lowest ranked value is associated with the median of that range. Column B contains the original sampled output values. Columns F:G show percentiles based on Excel’s PERCENTILE worksheet function. Refer to Excel’s online help for the interpolation method used by the PERCENTILE function.The summary measures in columns Q:R are also based on Excel worksheet functions: AVERAGE, STDEV, QUARTILE, an d SKEW. 10. 8 CUSTOMIZING RISKSIM CHARTS If the labels on the horizontal axis are numbers with many digits, some of the labels may wrap around so that some of the digits display below the others. One way to remedy this anomaly is to 10. 8 Customizing RiskSim Charts 105 widen the chart (click just inside the outer border of the chart so that eight chart handles are shown and then drag the middle chart handle on the left or right to widen the chart).Another way is to select the horizontal axis (click between the labels on the horizontal axis so that â€Å"Value (X) axis† appears in the name box in the upper left of Excel) and change to a smaller font size using the Font Size drop-down edit box on the the Formatting tool bar. The histogram chart is a combination chart using a column chart type for the vertical bars and an XY (Scatter) chart type for the horizontal axis. The two chart types align properly as long as the horizontal axis retains the same minimum and maximum values. For example, if you want more spacing between the dollar labels on the horizontal axis, select the horizontal axis (so that â€Å"Value (X) axis† appears in the name box in the upper left of Excel), choose Format | Selected Axis | Scale, and change the â€Å"Major unit† from 1000 to 2000. In Excel 2007 or 2010, select the axis, right-click, and choose Format Axis | Axis Options. Do not change the Minimum = –6000 or the Maximum = 12000. The histogram appears as shown below. Figure 10. 0 Original Histogram With Modified Horizontal Axis Major Unit RiskSim  ? Histogram 80 70 60 Frequency 50 40 30 20 10 0 ? $6,000 ? $4,000 ? $2,000 $0 $2,000 $4,000 $6,000 $8,000 $10,000 $12,000 Net  Cash  Flow The cumulative chart is a standard XY (Scatter) chart type, so you can change the major unit as described above, but you can also change the minimum and maximum without affecting the integrity of the chart. Another way to obtain more spacing on the horizontal axis of the histogram or cumulative chart is to use a custom format.For example, if you want to show values in thousands instead of the original units, select the horizontal axis (click between the labels on the horizontal axis so that â€Å"Value (X) axis† appears in the name box in the upper left of Excel), choose Format | Selected Axis | Number | Custom, and enter a comma at the end of the current format shown in the â€Å"Type:† edit box. In Excel 2007 or 2010, right-click the horizontal axis, choose Format Axis | Number, change the Format Code, and click the Add button. After changing the original format â€Å"$#,##0† to â€Å"$#,##0,† and modifying the horizontal axis title, the cumulative chart appears as shown below. 06 Chapter 10 Monte Carlo Simulation Using RiskSim Figure 10. 11 Original Cumulative Chart With Horizontal Axis Custom Format RiskSim  ? Cumulative  Chart 1. 0 0. 9 Cumulative  Probability 0. 8 0. 7 0. 6 0. 5 0. 4 0. 3 0. 2 0. 1 0. 0 ? $6 ? $4 ? $2 $0 $2 $4 $6 $8 $10 $12 Net  Cash  Flow,   in  thousands  of  dollars 10. 9 RANDOM NUMBER GENERATOR FUNCTIONS RandBinomial Returns a random value from a binomial distribution. The binomial distribution can model a process with a fixed number of trials where the outcome of each trial is a success or failure, the trials are independent, and the probability of success is constant.RANDBINOMIAL counts the total number of successes for the specified number of trials. If n is the number of trials, the possible values for RANDBINOMIAL are the non-negative integers 0,1,†¦ ,n. RANDBINOMIAL Syntax: RANDBINOMIAL(trials,probability_s) Trials (often denoted n) is the number of independent trials. Probability_s (often denoted p) is the probability of success on each trial. RANDBINOMIAL Remarks Returns #N/A if there are too few or too many arguments. Returns #NAME! if an argument is text and the name is undefined. Returns #NUM! if trials is non-integer or less than one, or probability_s is less than zero or more than one.Returns #VALUE! if an argument is a defined name of a cell and the cell is blank or contains text. RANDBINOMIAL Example A salesperson makes ten unsolicited calls per day, where the probability of making a sale on each call is 70 percent. The uncertain total number of sales in one day is =RANDBINOMIAL(10,0. 7) 10. 9 Random Number Generator Functions 107 Figure 10. 12 RandBinomial Example Probability Mass Function Probability, P(X=x) 0. 30 0. 20 0. 10 0. 00 0 1 2 3 4 5 6 7 8 9 10 Total Numbe r of Sa le s in 10 Ca lls, x Figure 10. 13 RandBinomial Example Cumulative Probability Function 1. 0 0. 9 Cumulative Probability, P(X How to cite Montecarlo Simulation, Papers

The Life Of Ira Remsen Essays - Ira Remsen, Sugar Substitutes

The life of Ira Remsen Ira Remsen was born on February 10, 1846 in New York city. Even though he was born in the United States, he was educated in Germany. He received his M.D. at Columbia University in 1867 and he also earned a Ph.D. at the University of Munich and G?ttingen in Germany. After receiving his degrees, Remsen began his investigation in pure chemistry at the University of T?bingen. It was in Germany and in Europe Remsen did most of his research. In 1876 he returned to the United States where his became one of the original faculty of Johns Hopkins University. There he founded the chemistry department. He was an excellent professor who trained a generation of prominent chemists. He was also the Director of the Chemical Laboratory and secretary of the Academic Council. In 1879, he was the founding editor of American Chemical Journal. Also in that same year, he made a remarkable, accidental discovery with a fellow researcher Constantine Fahlberg when they were working on a derivative of coal tar. One night, after a long day in his laboratory He we was having dinner with wife. When he was eating a regular roll. Remsen noticed that it was quite sweet at first, but it left a bitter after-taste. He made his wife taste the bread and he found nothing wrong or something unusual about the taste. So Remsen decided to taste his fingers and there he found that same sweet then bitter taste despite washing his hands thoroughly after working in his lab. After dinner, he returned to his laboratory and started to taste all the chemicals he was handling. When he found that chemical, it was oxidation of o-toluenesulfonamide and he called it saccharin. In 1880, Remsen and Fahlberg published their findings in the February issue of The Chemical Journal. Many people thought that it was Constantine who discovered saccharin, but he stole the formula from Remsen. When they stopped working together, Constantine patented the formula and became filthy rich. As a result Remsen didn't received any credit for the discovery. Constantine received the recognition that Remsen earned and rightfully deserved. Remsen was furious at first about the matter; it makes my blood boil to see the lies that scoundrel Fahlberg constantly, constantly in print, and to see further, that they are generally believed. Later Remsen would apologize for this outburst. Remsen moved to bigger and better things. In 1901, he was appointed President of Johns Hopkins University, there in that same year, he wrote several important textbooks on chemistry. Remsen also found the School of Engineering at Johns Hopkins. He introduced many German laboratory methods into Johns Hopkins and emphasized the university's function as a research centre. At the time at Johns Hopkins he helped establish the school as a leading graduate science teaching institute in the United States, never seeking fame or fortune for his contributions to science. His work on the research-based Doctoral program at Hopkins was considered important improvement to science in the United States. In 1913, Dr. Ira Remsen stepped down as president at Johns Hopkins University. Remsen still continued to keep chemistry the number one priority in his life. He moved and resided in Carmel, California. Until his passing away on March 4, 1927 of natural causes. Saccharin Saccharin is derived from the Latin word saccharum, meaning sugar. Saccharin is also called Ortho-sulfobenzoic acid imide; the formula is C6H4CONHSO2. Saccharin is a synthetic, white, crystalline powder that melts at 228.08 to 229.7 degrees Celsius and very soluble in water. It is 550 times as sweet as sugar cane. And it is also estimated to have a sweetening power 375 times that of sugar. When saccharin is dissolved in water in large amounts, the solution is very bitter. Sweetness is only evident in a diluted solution. Saccharin cannot be digested by the body and has no food values. Those who are diabetic and people who ate on weight reducing diets use it in place of sugar. They used it for the psychological purpose of satisfying a taste for sweetness. Many critics say that that saccharin can itself stimulate the appetite and the production of insulin in the body. For several years, saccharin has been under investigation as a risk for cancer. It was banned in