History of Washing Machines

History of Washing Machines Early washing machines were invented back in the 1850s, but people have been doing laundry since they graduated from wearing fig leaves. Over the course of centuries, the technology for washing clothes has evolved from crude manual labor to high tech. Laundry Before Machines In many ancient cultures, peoples cleaned their clothes by pounding them on rocks or rubbing them with abrasive sands and washing the dirt away in streams or rivers. The Romans invented a crude soap, similar to lye, that contained ash and fat from sacrificed animals. In colonial times, the most common way of washing clothes was to boil them in a large pot or cauldron, then lay them on a flat board, and beat them with a paddle called a dolly. The metal washboard, which many people associate with pioneer life, wasnt invented until about 1833. Before that, washboards were made entirely of wood, including the carved, ridged washing surface. As late as the Civil War, laundry was often a communal ritual, especially in places near rivers, springs, and other bodies of water, where the washing was done. The First Washing Machines By the mid-1800s, the United States was in the midst of an industrial revolution. As the nation expanded westward and industry grew, urban populations mushroomed and the middle class emerged with money to spare and boundless enthusiasm for labor-saving devices. A number of people can lay claim to inventing some kind of manual washing machine that combined a wooden drum with a metal agitator. Two Americans, James King in 1851 and Hamilton Smith in 1858, filed and received patents for similar devices that historians sometimes cite as the first true modern washers. However, others would improve on the basic technology, including  members of the Shaker communities in Pennsylvania. Expanding on ideas begun in the 1850s, the Shakers built and marketed large wooden washing machines designed to work on a small commercial scale. One of their most popular models was displayed at the Centennial Exposition in Philadelphia in 1876. Fast Facts: Washing Machine Trivia A washing machine invented in France in the early 1800s was called the ventilator. The device consisted of a barrel-shaped metal drum with holes that was turned by hand over a fire.One of the first African-American inventors of note in the 19th century, George T. Sampson, received a patent for a clothes dryer in 1892. His invention  used the heat from a stove to dry clothes.The first electrical clothes dryers appeared in the United States in the years prior to World War I.In 1994, Staber Industries released the System 2000 washing machine, which is the only top-loading, horizontal-axis washer to be manufactured in the United States.The first computer-controlled consumer washer appeared in 1998. Fisher Paykels SmartDrive washing machines used a computer-controlled system to determine load size and to adjust the wash cycle to match.   Electric Machines Thomas Edisons pioneering work in electricity accelerated Americas industrial progress. Until the late 1800s, home washing machines were hand-powered, while commercial machines were driven by steam and belts. That all changed in 1908 with the introduction of the Thor, the first commercial electric washer. The Thor, the invention of Alva J. Fisher, was marketed by the Hurley Machine Company of Chicago. It was a drum-type washing machine with a galvanized tub. Throughout the 20th century, Thor continued to make innovations in washing machine technology. In 2008, the trademark was bought out by Los Angeles-based Appliances International and soon introduced a new line under the Thor name. Even as Thor was changing the commercial laundry business, other companies had their eye on the consumer market, perhaps most notably the Maytag Corporation that got its start in 1893 when F.L. Maytag began manufacturing farm implements in Newton, Iowa. Business was slow in winter, so to add to his line of products, Maytag introduced a wooden-tub washing machine in 1907. Not long after, Maytag decided to devote himself full-time to the washing machine business. The Whirlpool Corporation, another well-known brand, debuted in 1911 as the Upton Machine Co., in St. Joseph, Mich., producing electric motor-driven wringer washers. Sources Marton, Barry. Washing Machine. Encyclopedia.com. Accessed 16 Mar. 2018 Museum staff. The Shaker Improved Washing  Machine. Shaker Museum. 20 July 2016.Staff editors. Clothes Washing Machines. Edison Tech Center. 2014.Telegraph staff. A Timeline of Inventions. Telegraph.co.uk. 6 July 2000.

Solar System Science Project Ideas

Solar System Science Project Ideas Do you have a science fair project in your future? If so, consider focusing on the solar system. Outer space is rich with mysteries and scientific questions to explore, from the phases of the moon to the existence of space dust (micrometeorites). Start with this list of solar system science fair projects. Build a Working Sundial The ancients used sundials to tell time using the position of the Sun in the sky.  You can build your own sundial with two simple materials: a flat surface (e.g. paper, cardboard) and a thin object that can stand up (e.g. a popsicle stick or straw). Once your sundial is functional, test it for accuracy a few times per day by comparing the sundials reading to your watch or clock. Make Your Own Telescope Build a telescope. Galileo did, and so can you. Learn about the basics of telescopes  here, then check out  NASAs page on building your own. The easiest one to build is a Galileoscope, made out of a cardboard tube and some lenses.   Build a Model of the Solar System You can make a scale-model solar system out of paper or in a diorama. First, find out the distances between solar system objects, then do some math to get the distances to scale within your own model. Some tabletop scale-model solar systems contain marbles for the planets, a tennis ball for the Sun, and other smaller pebbles for asteroids and comets. Make a Spacecraft Model Build a model of a NASA space probe. Many of the major probes and space-based observatories have patterns you can download and use to make scale model, including the  Hubble Space Telescope and the NASA Jet Propulsion Laboratory. Track the Lunar Phases First, read about the phenomenon of lunar phases here. Then, for a few months, observe the Moon in the sky each night, recording how, where, and when it appears. Record the information in a chart and include a drawing of the moons shape each day.  If you have the materials, you can construct a 3D model of the sun using small balls and a light source to show how the Sun illuminates the Moon and Earth throughout the month.   Study Renewable Energy For many years, NASA and other space agencies have been using solar panels to power their satellites and the International Space Station. Here on Earth, people use solar power for everything from household electricity to powering their watches and other electronics. For a science fair project on solar power, study how the Sun generates light and heat and how we convert that light and heat into usable solar power. Collect Bits of Space Micrometeorites are tiny bits of asteroid that drift through our atmosphere and land on the surface of the Earth.  You can collect them by looking in places theyre likely to end up. For example, rain and snow can wash them off of roofs, and they can flow down the drainpipes and storm gutters. You might also try looking in the piles of dirt and sand at the bottom of a rain spout.  Collect that material, remove anything that obviously is not a micrometeorite (e.g. large rocks and leaves), and spread out the remaining material on a piece of paper. Place a magnet underneath the paper and tilt it. Most of the material will slide right off; anything that does not slide off is magnetic. Study the remaining magnetic material under a magnifying glass or microscope. Micrometeorites will appear rounded and may have pits. Edited and updated by  Carolyn Collins Petersen

Comparing Brazilian Culture to American Culture Research Paper

Comparing Brazilian Culture to American Culture - Research Paper Example These segments include ‘Power Distance’, ‘Individualism’, ‘Masculinity’, ‘Uncertainty Avoidance’, ‘Pragmatism’, and ‘Indulgence’ (The Hofstede Center, 2014). The discussion henceforth will give an elaborative account of these cultural segments as observable in the prospective market of the Canadian company, i.e. in Brazil. Power distance exhibits the acceptance of power hierarchy and the inequalities among people residing within a given society. Observably, Brazil scores 69, where Canada scores 39 as per the Hofstede’s model when examining this factor (The Hofstede Center, 2014). This further reveals that where Canada believes in egalitarianism, Brazilian communities believe in power hierarchy and accept the inequality as a part of their culture (Ferguson, 2007). It is thus necessary for the Canadian company to understand the power distance of Brazil and formulate their organizational decision-making structure accordingly. Individualism, another facet of the Hofstede’s cultural model, indicates whether people prefer group oriented lifestyle practices or individualism. Brazil scores 38 in this section according to Hofstede’s model analysis, where Canada scores 80 (The Hofstede Center, 2014). This implies that Brazilian people are group oriented where Canadians are highly individualistic in nature. Certainly, in the business world, group orientation attitude among employees and customers can create the difference of opinions as well as communication gap. Due to the huge difference of nature, it is better for the company to use Polycentrism to connect with the culture of Brazil (Ferguson, 2007). The paradigm of masculinity in the Hofstede’s model replicates whether the cultural backbone of the country is success oriented, achievement-oriented or it is based on the quality of life.  

Who would you rather study with. Aristotle or Plato Essay

Who would you rather study with. Aristotle or Plato - Essay Example Aristotle on the other hand believed in logical reasoning. He is credited with laying the foundation of the use of logic as a basis for study and scientific thought. Thus, whereas Aristotle’s philosophical values are heavily influenced by Plato, there exist huge differences in their way of thinking. Based on my personal values, ethics, religion affiliation, beliefs, and philosophical orientation, I would rather study with Aristotle than Plato. Aristotle believed that when we breakdown and classify the natural world in a systematic and analytic way, we can reach a true argument where we can come up with a conclusion that is concrete and correct. This is against the arguments brought forward by Plato who insisted on making valid arguments that made sense logically but could not be either considered factually true or false. An example of a valid argument would be to suggest that old people are bad drivers. Therefore, when you meet let’s say Jack, who is old, you out righty judge him as being a bad driver. While this may be a valid argument, it may not be entirely true without seeing him driving. On the other hand, a true argument as presented by Aristotle would probably suggest that all fruits have seeds. Therefore, regardless of whether he picks an apple or an orange, he will know that these are fruits and thus they all have seeds. Therefore, Aristotle would make a better person to learn with because of his valid sci entific arguments. While both Plato and Aristotle contributed hugely to political philosophy and shared some sentiments on the ideal state, Aristotle still had some of his reservations on some of Plato’s philosophical teachings. While Plato advocated for communism in which he called for abolition of ownership of private property, Aristotle was a harsh critic on the abolition of private property. Plato was of the

Nutrition - Obesity Essay Example for Free

Nutrition Obesity Essay Objective: To assess the association between the consumption of fast food (FF) and body mass index (BMI) of teenagers in a large UK birth cohort. Methods: A structural equation modelling (SEM) approach was chosen to allow direct statistical testing of a theoretical model. SEM is a combination of confirmatory factor and path analysis, which allows for the inclusion of latent (unmeasured) variables. This approach was used to build two models: the effect of FF outlet visits and food choices and the effect of FF exposure on consumption and BMI. Results: A total of 3620 participants had data for height and weight from the age 13 clinic and the frequency of FF outlet visits, and so were included in these analyses. This SEM model of food choices showed that increased frequency of eating at FF outlets is positively associated with higher consumption of unhealthy foods (b ? 0. 29, Po0. 001) and negatively associated with the consumption of healthy foods (b ? A1. 02, Po0. 001). The SEM model of FF exposure and BMI showed that higher exposure to FF increases the frequency of visits to FF outlets (b ? 0. 61, Po0.001), which is associated with higher body mass index standard deviation score (BMISDS; b ? 0. 08, Po0. 001). Deprivation was the largest contributing variable to the exposure (b ? 9. 2, Po0. 001). Conclusions: The teenagers who ate at FF restaurants consumed more unhealthy foods and were more likely to have higher BMISDS than those teenagers who did not eat frequently at FF restaurants. Teenagers who were exposed to more takeaway foods at home ate more frequently at FF restaurants and eating at FF restaurants was also associated with lower intakes of vegetables and raw fruit in this cohort. International Journal of Obesity (2011) 35, 1325–1330; doi:10. 1038/ijo. 2011. 120; published online 28 June 2011 Keywords: fast food; overweight; ALSPAC Introduction Childhood obesity prevalence have risen dramatically in the last 30 years in the Western world with the most recent figures for England and Wales show that 17% of boys and 16% of girls are obese. 1 An increase in the availability of calorie dense foods is implicated as one of the factors in the aetiology of the obesity epidemic. Fast food (FF) is one section of the food market that has grown steadily over the last few decades and it was worth d8. 9 billion in the United Kingdom in 2005. 2 FF is typically quick, convenient, cheap and Correspondence: Dr LK Fraser, School of Geography, University of Leeds, University road, Leeds LS2 9JT, UK. E-mail: l. k. [emailprotected] ac. uk Received 6 February 2011; revised 21 April 2011; accepted 12 May 2011; published online 28 June 2011 uniform in its production,3 but FF is often high in saturated fats, energy dense and has low micronutrient content. 4–9 Studies from the United States of America have shown that children who consume FF (when compared with children who do not eat FF) have higher energy intake and higher fat intakes9,10 as well as lower vegetable and milk intake. 10,11 Therefore, the consumption of such foods could possibly result in a positive energy balance; and hence, weight gain. There is some evidence from longitudinal studies in the United States of America that consuming FF as a teenager can result in weight gain in both early12 and middle adulthood. 13 FF is often marketed to children and adolescents through television, internet and movie advertising,14–17 with brand recognition being present from an early age. 18 The addition of toys as gifts with FF meals also attracts children. There is growing body of literature that has assessed the location of FF outlets and has found that areas of higher deprivation Fast food and body mass index LK Fraser et al 1326 have more FF outlets19–21 and that FF outlets are often located close to schools. 22–24 The majority of research to date has been undertaken in the United States of America, but a study that analysed the fat content of a FF meal in McDonald’s and Kentucky Fried Chicken outlets in 35 countries showed that the amount of fat varied considerably between countries, within the same FF outlet. 25 This means that results from studies in the United States of America may not be generalisable to other countries. This study aims to assess the cross-sectional association between the consumption of FF and the body mass index (BMI) of teenagers in a large UK birth cohort. Methods The data for this study were obtained from the Avon Longitudinal Study of Parents and Children (ALSPAC),26 which is a birth cohort study where pregnant mothers who lived in the old Avon County in the United Kingdom (the Bristol region) were recruited in the early 1990s. A total of 14 541 mothers completed recruitment. Because of retrospective recruitment the total sample size was 15 224 fetuses and 14 610 live births. This paper presents data on the teenagers who attended the year 13 clinic and completed the year 13 questionnaire. Variables The food frequency data were collected from the questionnaires completed by mother (or carer) and separate questionnaires completed by the teenagers themselves at age 13 years. The data used from the carer questionnaire (collected at the same time point) referred to the questions ‘How often does s/he eat in a FF restaurant? The responses to this question were collected as never/rarely, once a month, once every 2 weeks, once or twice per week, 3–4 times a week, 5 or more times a week. The carers were also asked ‘In total, how many portions of vegetables does s/he eat in a week (do not include potatoes)’, ‘In total, how many portions of raw fruit does s/he eat in a week? ’ These were free numerical responses, which were retained as a continuous variable for analyses. In the food frequency part of the teenager completed questionnaire the teenagers were asked ‘If you ever buy food yourself from outside school, or from school vending machines, how often do you buy and eat each of the following things (include after school and weekends): chips, burger, pizza, sandwich, pies or pasties, chocolate, crisps, fruit and other food. ’ The height and weight data were collected at clinic visits at B13 years. The exact age, sex, height and weight were used to calculate a BMI standard deviation score (BMISDS) for each participant (1990 UK reference dataset). 27 The teenagers International Journal of Obesity were classified as obese if their BMISDS was greater than the 95th percentile (BMISDS41. 64). The physical activity data were collected via accelerometry at the age 13 clinic visit. 28 The participants wore an accelerometer for seven consecutive days and the measure used from this is mean counts per minute, which is a continuous variable. A deprivation score was assigned to each participant by matching the coordinates of their residential address (when carer questionnaire was completed) to the appropriate lower super output area. Each lower super output area has an index of multiple deprivation score (Index of Multiple Deprivation 2007 (IMD))29 assigned from the local census data. This is a continuous variable in which a higher number indicates an area of higher deprivation. Ethnicity was assigned as per the child’s ethnicity into a binary variable of ‘white British’ and ‘other’ ethnicity. Statistical modelling Descriptive statistics were performed in STATA version 10 (StataCorp LP, College Station, TX, USA). A structural equation modelling (SEM) approach was chosen to allow direct statistical testing of a theoretical model. SEM has many benefits over traditional regression techniques, which include the ability to model equations simultaneously and the incorporation of latent variables. 30 SEM is a combination of confirmatory factor and path analysis, which allows for the inclusion of latent (unmeasured) variables. 31 This approach was used to build two models: the effect of FF outlet visits and food choices and the effect of FF exposure on consumption and BMI. The SEM analyses were undertaken in AMOS version 17. 0 (IBM SPSS, USA). The hypothesised model for food choices is shown in the results section (Figure 2). The observed variables are displayed as boxes and latent variables as circles. Each observed variable has an associated random error term and each latent variable has an associated disturbance term, which represents the variance in the latent variable that has not been explained by the observed variables associated with that latent variable. Regression paths are shown by singleheaded arrows and covariances by double-headed curved arrows. The model fit was assessed by two indices; the comparative fit index (CFI) and the root mean square error of approximation (RMSEA). The CFI is a comparison of the hypothesised model compared with an independence model where all parameters are assumed to be independent. The RMSEA gives an indication of ‘how well would the model, with unknown but optimally chosen values, fit the population covariance matrix if it were available’. 32 A combination of CFI40. 95 and a RMSEA of o0. 50 is a sign of good model fit. The w2-test of overall fit is very sensitive to large sample size so has not been used in these models. 30 The two models were constructed a priori using previous research. The nutritional content of chips, burgers, pizza and Fast food and body mass index LK Fraser et al 1327 pies are known to be high in saturated fat and energy and therefore are ‘unhealthy’,4–9,33 whereas fruit and vegetables are known to contain fibre and vitamins and so are classified as ‘healthy’. Exposure to FF outlets is known to be higher in areas of higher deprivation. 19–21 In the food choices model, unhealthy consumption (latent variable) was modelled from the frequency of consumption of chips, burger, pizza and pies (reported by the teenagers themselves), and the healthy consumption was modelled from the number of pieces of vegetables and raw fruit consumed by the teenager (maternal report). The number of times that the teenager visited a FF outlet (maternal report) was regressed on the unhealthy and healthy consumption variables. The model for the effect of FF exposure on consumption and BMISDS is shown in Figure 3. Here exposure is a latent variable modelled from maternal and paternal takeaway frequency and deprivation score. The exposure is regressed on the number of visits to FF outlet. The BMISDS at age 13 years is the main outcome of this model. Ethical approval for the study was obtained from the ALSPAC Law and Ethics Committee and the local research ethics committees. Results A total of 3620 participants have data for height and weight from the age 13 clinic and the frequency of FF outlet visits, and were included in these analyses (SEM cannot use individuals with missing data). A total of 1711 (47. 3%) were boys and 456 (12.6%) obese. The descriptive statistics are shown in Table 1. Frequency of visiting FF outlets and food consumption frequencies are shown in Figure 1. The results of model 1 are shown in Figure 2 with regression weights shown in Table 2. This model showed that increased frequency of eating at FF outlets was positively associated with higher consumption of unhealthy foods (b ? 0. 29, Po0. 001) and negatively associated with the consumption of healthy foods (b ? A1. 02, Po0. 001). The CFI for model 1 was 0. 98 and the RMSEA was 0. 05 (90% confidence interval 0. 044, 0. 058). These represent good approximate model fit. Table 1. The results of model 2 are shown in Figure 3 with regression weight shown in Table 3. This model showed that increased exposure to FF increased the frequency of visits to FF outlets (b ? 0. 61, Po0. 001), which in turn was associated with higher BMISDS (b ? 0. 08, Po0. 001). Deprivation was the largest contributing variable to the exposure (b ? 9. 2, Po0. 001). The CFI for model 2 was 0. 98, and the RMSEA was 0. 021 (90% confidence interval 0. 009, 0. 033). These represent very good approximate model fit. Discussion This study shows that teenagers who are exposed to more unhealthy foods at home are more likely to eat at FF restaurants and have a higher BMISDS. The negative association of increased visits to FF outlets on consumption of healthy foods (fruit and vegetables) has also been demonstrated. The FF restaurant use in this analysis was reported by the mother or main carer of the teenager and showed that nearly 60% of all the teenagers ate at a FF restaurant at least once a month. This appears to be less frequently than in the United States of America, where studies showed that 60% of older children and adolescents ate FF more than once per week34 and that B30% of children ate at a FF restaurant on any typical day. 9. As one part of the SEM this study showed that eating at a FF outlet was associated with a higher BMISDS. There were no previous UK studies to compare these results with, but previous studies from the United States of America have not found consistent results. Boutelle et al. 11 found no association between frequency of FF consumption and adolescent BMI or weight status, and an Australian study Descriptive statistics Mean BMISDS Deprivation (IMD 2007)29 Physical activity (c. p. m. ) Raw fruit (portions per week) Vegetables (portions per week) s. d. Median IQR 0. 29 13. 7 541 9. 5 9. 5 1. 14 11. 4 190 7 7 0. 024 10. 6 511 8 8 A0. 47, 1. 06 5. 9, 17. 0 404, 653 5, 14 5, 12 Abbreviations: BMISDS, body mass index standard deviation score for age and sex; c. p. m. , cycles per minute; IMD 2007, Index of Multiple Deprivation 2007; IQR, interquartile range. Figure 1 Food frequency data. International Journal of Obesity Fast food and body mass index LK Fraser et al 1328 Figure 2 Results of SEM model of food choices. Table 2 Results of SEM model of food choices Regression weights a Unhealthy’fast food Healthy’fast food Chips’unhealthy Burger’unhealthy Fruit’healthy Vegetables’healthy Pizza’unhealthy Pies’unhealthy Estimate s. e. CR P 0. 285 A1. 023 1. 000 0. 732 1. 000 1. 157 0. 774 0. 530 0. 021 0. 124 13. 439 A8. 274 o0. 001 o0. 001 0. 016 45. 243 o0. 001 0. 148 0. 018 0. 016 7. 802 42. 483 32. 720 o0. 001 o0. 001 o0. 001 Abbreviations: CR, critical ratio; SEM, structural equation modeling. aAll consumption variables units: never/rarely, once a month, once every 2 weeks, once or twice per week, 3–4 times a week, 5 or more times a week. showed that FF eaten at home (but not away from home) was associated with higher BMI in adolescents (MacFarlane). Two longitudinal studies using data from the CARDIA study found that higher FF intake in adolescence was associated with higher BMI in young adulthood12 and those who ate FF more than twice a week had put on an extra 4. 5 kg of weight 15 years later. 13 The teenagers who ate more frequently at FF restaurants were more likely to eat less fruit and vegetables, as well as consume more unhealthy foods (chips, burger, pizza, pies) than those teenagers who ate at FF restaurants less frequently. This is an indication that the consumption of unhealthy foods may displace healthy food choices. This is similar to previous research in the United States of America, International Journal of Obesity which showed that children who ate FF consumed 45 g less vegetables per day than children who did not eat FF. 10 At age 13 years the food frequency data were a combination of maternal and self-report from the teenagers, but the total macro- and micronutrient values could not be assessed in this study as these data were not yet available at the time of writing. Deprivation was the largest contributor to the FF exposure variable. This could be explained by the fact that those of higher deprivation eat more FF because of the relative cheapness of FF. It has also been shown in many studies in the United Kingdom and the United States of America that areas of higher deprivation have more FF outlets than more affluent areas therefore, FF is more readily available. 35 An interesting economics paper from the United States of America showed that increasing the cost of FF by $1 could decrease BMI by 0. 78 units. 36 The increased consumption of unhealthy foods (chips, burger, pizzas and pies) by those teenagers who ate more frequently at FF outlets was not surprising, but the associated negative effect of the consumption of fruit and vegetables by these participants is important. These teenagers will not only be consuming more of the saturated fat and salt from the burgers, and so on, but at the same time they are not consuming important nutrients from fruit and vegetables. Although many FF outlets now offer more healthy alternatives such as fruit and vegetables, the consumers may still be choosing the unhealthy foods. Fast food and body mass index LK Fraser et al 1329 The FF question completed by the carer did not specify what constituted FF so some respondents may only count large franchises as FF whereas others may use a broader definition that includes independent takeaways. Although the frequency of eating at a FF restaurant was asked, the carers were not asked about the food eaten from these establishments and many FF restaurants now offer more ‘healthy’ alternatives. Although the majority of FF items do not meet the Food Standards Agency nutrient standards for total fat, saturated fat, sugar and sodium there are wide variations in similar products from different FF outlets with sodium content varying by up to four times in fried chicken products. 37 Therefore, having data on which food items were consumed from which FF outlet would further enhance future studies. There was no information on why the teenagers ate at FF restaurants, and key questions for the future include; was there no alternative eating establishments in their neighbourhood? Did they prefer FF to other meals or was the cost of food important? Conclusions This study has shown that the teenagers who ate at FF restaurants consumed more unhealthy foods and were more likely to have higher BMISDS than those teenagers who did not eat frequently at FF restaurants. Teenagers who were exposed to more takeaway foods at home ate more frequently at FF restaurants. Eating at FF restaurants was also associated with lower intakes of vegetables and raw fruit in this cohort. Figure 3 The SEM model of FF exposure and BMI. Table 3 Results of SEM model of FF exposure and body mass index Regression weights Fast food ’exposure. Maternal fast food’exposure Deprivation’exposure Paternal fast food’exposure BMISDS’fast food BMISDS’c. p. m. a Estimate s. e. CR 0. 61 1. 000 9. 20 0. 66 0. 08 0. 00 0. 07 8. 654 1. 07 0. 08 0. 02 0. 00 8. 605 8. 680 3. 586 A3. 351 P o0. 001 o0. 001 o0. 001 o0. 001 o0. 001 Abbreviations: BMISDS, body mass index standard deviation score for age and sex; c. p. m. , cycles per minute; CR, critical ratio; FF, fast food; IMD 2007, Index of Multiple Deprivation 2007; SEM, structural equation modeling. a All consumption variables units: never/rarely, once a month, once every 2 weeks, once or twice per week, 3–4 times a week, 5 or more times a week. Strengths/limitations This is a large dataset with good-quality height and weight data taken at clinic visits by trained staff using validated equipment. There were food consumption data about the teenagers available from both the teenagers and their carers, but this is a cross-sectional study so causation cannot be implied from this data. As expected in a longitudinal study there is attrition and the subcohort used in this study may not be truly representative of the whole cohort. Conflict of interest The authors declare no conflict of interest. Acknowledgements. We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting and the whole ALSPAC team, which include interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council (grant ref: 74882), The Wellcome Trust (grant ref: 076467) and the University of Bristol provide core support for ALSPAC. LKF was funded by ESRC/MRC studentship. References 1 Craig RS. Health survey for England 2007, 2008. Available from http://www. natcen. ac. uk/study/health-survey-for-england-2007. 2 Keynote.UK fast food and home delivery outlets, 2006. International Journal of Obesity Fast food and body mass index LK Fraser et al 1330 3 DeMaria AN. Of fast food and franchises. J Am Coll Cardiol 2003; 41: 1227–1228. 4 Astrup A. Super-sized and diabetic by frequent fast-food consumption? Lancet 2005; 365: 4–5. 5 Brown K, McIlveen H, Strugnell C. Young consumers and the hospitality spectrum. Appetite 1998; 31: 403. 6 Harnack LJ, French SA, Oakes JM, Story MT, Jeffery RW, Rydell SA. Effects of calorie labeling and value size pricing on fast food meal choices: results from an experimental trial. Int J Behav Nutr Phys Act 2008; 5: 63. 7 Lewis LB, Sloane DC, Nascimento LM, Diamant AL, Guinyard JJ, Yancey AK et al. African Americans’ access to healthy food options in South Los Angeles restaurants. Am J Public Health 2005; 95: 668–673. 8 Paeratakul S, Ferdinand DP, Champagne CM, Ryan DH, Bray GA. Fast-food consumption among US adults and children: dietary and nutrient intake profile. 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Am J Clin Nutr 2007; 85: 201–208. 13 Pereira MA, Kartashov AI, Ebbeling CB, Van Horn L, Slattery M, Jacobs DR et al. Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet 2005; 365: 36–42. 14 Sutherland LA, MacKenzie T, Purvis LA, Dalton M. Prevalence of food and beverage brands in movies: 1996–2005. Pediatrics 2010; 125: 468–474. 15 Powell LM, Szczypka G, Chaloupka FJ. Trends in exposure to television food advertisements among children and adolescents in the United States. Arch Pediatr Adolesc Med 2010; 164: 794–802. 16 Hillier A, Cole BL, Smith TE, Yancey AK, Williams JD, Grier SA et al. Clustering of unhealthy outdoor advertisements around child-serving institutions: a comparison of three cities. Health Place 2009; 15: 935–945. 17 Lingas EO, Dorfman L, Bukofzer E. Nutrition content of food and beverage products on Web sites popular with children. Am J Public Health 2009; 99(Suppl 3): S587–S592. 18 Robinson TN, Borzekowski DLG, Matheson DM, Kraemer HC. Effects of fast food branding on young children’s taste preferences. Arch Pediatr Adolesc Med 2007; 161: 792–797. International Journal of Obesity. 19 Cummins SCJ, McKay L, MacIntyre S. McDonald’s restaurants and neighborhood deprivation in Scotland and England. Am J Prev Med 2005; 29: 308–310. 20 Fraser LK, Edwards KL. The association between the geography of fast food outlets and childhood obesity rates in Leeds, UK. Health Place 2010; 16: 1124–1128. 21 Macdonald L, Cummins S, Macintyre S. Neighbourhood fast food environment and area deprivation-substitution or concentration? Appetite 2007; 49: 251–254. 22 Neckerman KM, Bader MDM, Richards CA, Purciel M, Quinn JW, Thomas JS et al. Disparities in the food environments of New York City public schools. A J Prev Med 2010; 39: 195–202. 23 Davis B, Carpenter C. Proximity of fast-food restaurants to schools and adolescent obesity. 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Rocketry :: Essays Papers

Rocketry, the use of rocket power as a propulsion mechanism, has changed the boundaries of man’s domain.Before the advent of efficient rocket power, space flight was seen as an impossibility and exclusively the subject of science fiction stories.The nature of rocket power changed in the early twentieth century when a man named Robert Hutchings Goddard focused his research and his entire life on efficient rocket propulsion.Rocket power had been thought of long before Goddard’s time, but he was the first to have success with it. The earliest record of rocket propulsion dates to 1232 CE from China.Chinese Chronicles of the battle of Kai-Feng make mention of a â€Å"flying fiery arrow† that was used during battles â€Å"with telling effect against invading Mongol hordes† (xiii Goddard & Pendray).This object was a form of what we now call fireworks that was packaged with more propellant.During the middle ages, other objects were adapted from the Chinese invention in many other countries and were also used as a weapon to confuse, and to a lesser extent attack, the enemy.This practice was continued into the late eighteen hundreds. Rocketry did not progress greatly for a long time after its first uses.The next large advancement came from Hermann Ganswindt (1856-1934) of Germany.Ganswindt was a failed lawyer whose real passion was for science.He predicted rocket propulsion in theory and made the first design that was sound in principle in 1891.Ganswindt proposed his ideas to the German War Ministry, but was sadly rejected and was looked on as a non-professional scientist trying to do professional work.He had made the underlying theory that is used in modern space ships, but the theory was â€Å"too far in advance of his time for it to be understood†(23 Gartmann).Subsequently, Ganswindt had no success or advancement in the field and lost all his money in the aftermath of World War I preceding his death in 1934. Sir Isaac Newton’s laws of motion had been published and widely known for quite some time by this point, but Konstantin Tsiolkovski saw that the third law of motion provided the mechanism for successful rocket propulsion in space.In 1898, Tsiolkovski completed and published The Exploration of Cosmic Space by Rocket.The book meticulously and rigorously set forth the calculations associated with rocket propulsion.This act was the mathematical quantification of rocketry.When the calculations are examined, the physics of the propulsion showed that a liquid fuel, as opposed to a solid or composite propellant, would prove to be a more efficient power source and Tsiolkovski asserted that a liquid fuel would be necessary.

Millennium Development Goals Essay

The term â€Å"sanitation† is applied to a wide range of subjects such as: * Improved sanitation – refers to the management of human faeces at the household level. This terminology is the indicator used to describe the target of the Millennium Development Goal on sanitation, by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation. * On-site sanitation – the collection and treatment of waste is done where it is deposited. Examples are the use of pit latrines, septic tanks, and Imhoff tanks. * Food sanitation – refers to the hygienic measures for ensuring food safety. * Environmental sanitation – the control of environmental factors that form links in disease transmission. Subsets of this category are solid waste management, water and wastewater treatment,industrial waste treatment and noise and pollution control. * Ecological sanitation – an approach that tries to emulate nature through the recycling of nutrients and water from human and animal wastes in a hygienically safe manner. Sanitation can be of three types Personal sanitation Sanitation at home Sanitation at surroundings. â€Å"Wash your hands before you eat†¦ give those germs a clean sweep.† 1) Personal sanitation :- a) Bathing regularly b) Washing your hands after using washroom c) Washing your hands before having food d) Cutting your hairs clean e) Cutting your nails & keeping them clean f) Drinking clean water,using chlorine tablets or boiling it 2) Sanitation at home a) Keeping your home clean b) Keeping washroom at home clean c) Using washroom rather than going in open d) Eating healthy & nutritious food e) Washing fruits before eating 3) Surroundings a) Saniataion at school b) Sitting on clean benches c) Cleanliness while playing at playgrounds d) Dressing/cleaning your wounds e) Don’t play at dirty places f) Stay away from hazardous chemicals Why sanitation is important 1) To keep you healthy 2) You will smell good 3) Waste attracts disease carrying hosts like rats & other scavengers. 4) In our country most of the diseases are caused due to contaminated water and poor sanitation. In tribal areas, there are shortage of water supply and lack of awareness about proper sanitation till today. People depend on the water of polluted rivers or ponds and suffer from lack of sanitation. These cause highly infectious diseases such as – diarrhea, malaria, cholera, jaundice, plague etc. If we follow clean sanitation and use purified water then we can easily control and avoid many of the above diseases.