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6. If you want to pass values received from a form, select the Form Parameters option. 7. Click OK when you re finished.
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Niacin (vitamin B3) cures pellagra, a fatal disease associated with a subsistence diet composed largely of maize. It is characterised by the 4 Ds : diarrhoea, dermatitis, dementia and ultimately death. Thiamin (vitamin B1) cures beriberi, another potentially fatal disease associated with a diet heavily dependent upon polished (white) rice. It is characterised by degeneration of sensory and motor nerves, loss of peripheral sensation, paralysis, brain damage, oedema and heart failure. Iodine supplements cure goitre and the iodine de ciency diseases which are still endemic in many areas where the soil iodine content is low. They are characterised by low metabolic rate and mental deterioration in adults (myxoedema), severe and irreversible impairment of mental and physical development in children (cretinism), and high risk of miscarriage, stillbirth and birth defects. Vitamin D cures rickets, a disease once prevalent amongst children in the northern industrialised cities of Europe owing to a combination of a poor diet and low exposure of the skin to summer sunlight. Rickets leads to characteristic abnormalities in the skeleton such as bow legs (which may not be entirely reversible) as well as poor growth, muscle weakness and increased susceptibility to infection. Vitamin A prevents xerophthalmia and can reverse some cases in which there is a progressive deterioration of the eyes leading ultimately to permanent and irreversible blindness. Vitamin A de ciency also increases susceptibility to, and death from, infectious diseases. De ciency occurs in populations subsisting largely upon starchy foods where the staple diet contains practically no animal fats and few brightly coloured fruits or vegetables. Some of these diseases are still prevalent in some parts of the world. Vitamin A de ciency (xerophthalmia) causes hundreds of thousands of children in developing countries to go blind each year and is a major contributory factor to the high child and infant mortality rates in some countries. Iodine de ciency and goitre still affect hundreds of millions of people around the world. Iodine de ciency is the most common preventable cause of mental de ciency in the world. Most people who now live in one of the wealthy industrialised countries will have had no direct experience of any of the classical dietary de ciency diseases with the possible exception of iron de ciency anaemia. This was not true in the nineteenth century and the rst half of the twentieth century when these diseases were not con ned to developing countries; some, such as the examples below, were prevalent even in countries that are now part of the industrialised world. Pellagra (niacin de ciency) caused tens of thousands of deaths in the southern states of the USA in the early twentieth century and epidemics also occurred in parts of southern Europe where maize was a staple food. In the rst decades of the twentieth century, beriberi (thiamin de ciency) exacted a heavy toll in the countries of the Far East such as Japan and the Philippines where white rice was the dietary staple. In the early decades of the twentieth century, the majority of children from poor families living in the northern industrialised cities of Britain would have been affected by rickets (vitamin D de ciency).
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Table 6.1 Hierarchy of energy modelling methods. Treatment Conduction heat transfer Modelling Options Conventional time domain (1.3) Response factor method (1.3) Transfer function method (1.3) Radiant time series (2.3) Frequency response (1.3) Numerical nite difference (2.1) Lumped capacitance (1.4) Simpli ed xed parameters (2.2) Optical properties (2.2) Simpli ed surface-targeted (2.2) Mapped (2.2) Simpli ed surface fractions (2.2) Rigorous (2.2) Constant coef cients (3.2) Modelled coef cients (3.2) Zone moisture balance only (2.4) Fabric moisture sorption (3.1) Constant air change rate Zonal ventilation model (3.3) Perfectly mixed Strati ed multi-zonal (3.3) Strati ed rigorous (3.2) Constant set point tracking Steady-state model (4.2, 4.3, 4.5) Dynamic-state model (5.1, 5.2, 5.3) Not treated (i.e. close-coupled) Steady-state models (4.4) Dynamic-state models (5.2) Sum of loads Steady-state models (4.2, 4.3, 4.5) Dynamic-state model (5.1, 5.2, 5.3) Applicable Pathway Steps 1, 2, 4, 5
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Error 0.0890 0.1196 0.1220 0.1120 0.0978
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2. Place the terminals and decals inside the battery compartments as shown in Figure 10-16, snaking the leads down the holes. generate data matrix
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Divisions are a higher level of block formatting, usually reserved for groups of related paragraphs, entire pages, or sometimes only a single paragraph. The division tag (<div>) provides a simple solution for formatting larger sections of a document. For example, if you need a particular section of a document outlined with a border, you can de ne an appropriate style and delimit that part of the document with <div> tags, as in the following example:
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Invalid HTML Toggles the highlighting of invalid tags in Code view when Design view is refreshed. Invalid tags are always highlighted in the Design view. Coloring Syntax coloring makes code easier to read. Basic tags and keywords are shown in one color, with text in another color. Three different types of code are given different colors: Reserved Keywords, Other Keywords, and Strings. These colors are set in the Code Color category of Preferences. You can also set a color for an individual tag to further distinguish it if you like.
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SQLite allows at most one term of an index to be constrained by an inequality, such as less than (<), greater than (>), less than or equal to (<=), or greater than or equal to (>=). The column that the inequality constrains is the right-most term used with the index. For example, in the following query:
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is to some small extent modified in other forms of traditional retailing such as mail order or phone purchasing. With e-commerce, shopping can be done at any time by using our fingertip^'^ instead of our feet . Furthermore, the geographical barrier becomes a blur. A shop located in another country and a shop next to your home are both one finger-click7 away. By using search engines, we can quickly select and compare different brands of products around the world. For some products such as software and music, we can even download the goods instantly. In the future, we may even send out intelligent software programs called mobile agents to shop around the internet for us.
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An important aspect of applying any machine learning technique to bioinformatics problems, but especially identi cation trees, is the use of test data. Often in bioinformatics problems the number of data records available for an experiment (especially in the case of microarray experiments) can be small relative to the number of attributes. Therefore it may not be feasible to split the data into separate large training and test sets. Instead, cross-validation can be used where the algorithm is run repeatedly on different training and test sets. Cross-validation splits the entire dataset into a number of folds, which is determined by the experimenter and the amount of data available. If the data is split into ve folds, then the machine learning technique is trained on four fths of the data and then tested on the remaining one fth. This is then repeated for all the other four folds in the dataset, testing on a different fold each time. The measure of accuracy is determined by the average error of each run on each fold of the dataset. Figure 6.2 shows this process graphically. In this example, the training dataset is split into eight sections, seven of which are combined and used to train the identi cation tree and the remaining fold used to test the example. This is repeated for the N (in this case eight) folds in the dataset and the average accuracy or error reported over the N runs of the algorithm. One advantage of this approach is that, at the end of the ve-fold process, there will be ve possibly different identi cation trees. Future samples with unknown class can then be fed to all ve identi cation trees and a majority vote taken as to which class the new sample falls into. As described previously, the number of folds chosen is usually determined by the computational time available to the experimenter (more folds take more time to run) and the amount of data in the dataset. A popular speci c cross-validation technique is leave-one-out crossvalidation which, as its name suggests, leaves one example out of the dataset for testing and trains the algorithm on the remaining data. This is still N-fold cross-validation, but where N is equal to the number of data records (individuals or samples) in the dataset, and is the most computationally demanding cross-validation technique as N trials must be run. The cross-validation process gives a good impression of the accuracy of
with the Search field set to Text You re still left with the task of tracking down the alt attribute and making that change as well. Dreamweaver enables you to act on both content and programming text in one operation a major savings in time and effort, not to mention aggravation. To find and replace text in both the content and the code, follow these steps:
FIGURE 10-33: The tact switch and spacers attached to the engraving plastic.
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