Wave CharacterMany of the things that light does are only expla.pdf

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aravlitraders2012

>> Wave Character Many of the things that light does are only explained sufficiently by thinking of light as a wave. Refraction and diffraction are two examples. Light refracts when it travels from one medium to another, because waves travel at different speeds through different media. In a similar way, light diffracts when it travels between or around objects, because obstacles make the light waves bend. So, obviously we\'re not wrong about light behaving like a wave. We even use the wave diffraction of light by reading interference patterns in X-ray crystallography. >> Particle Behaviour photoelectric effect, which describes the way electrons are excited and emitted from matter when they absorb the energy from light. In 1887, Heinrich Hertz observed that a charged object would create a bigger, faster spark if it was treated with ultraviolet light because the light was actually exciting the electrons. Further studies by other scientists showed that electrons really could be knocked out of a metal in response to a beam of light. For a while, scientists thought that the electrons were just absorbing the energy in the light wave, and then using that energy to jump out of the metal. The more energy the electrons could absorb, the more energy they could use to jump out. A photon is a nearly massless particle carrying a small amount of energy. We use photons to quantify, or measure the amount of, the energy in light and other electromagnetic waves. Each photon can excite only one electron at a time. When the intensity of light is increased, then the number of photons is increased, so a higher number of electrons are knocked loose from the metal. The energy of electrons does not change because the energy of each photon is still the same. Solution >> Wave Character Many of the things that light does are only explained sufficiently by thinking of light as a wave. Refraction and diffraction are two examples. Light refracts when it travels from one medium to another, because waves travel at different speeds through different media. In a similar way, light diffracts when it travels between or around objects, because obstacles make the light waves bend. So, obviously we\'re not wrong about light behaving like a wave. We even use the wave diffraction of light by reading interference patterns in X-ray crystallography. >> Particle Behaviour photoelectric effect, which describes the way electrons are excited and emitted from matter when they absorb the energy from light. In 1887, Heinrich Hertz observed that a charged object would create a bigger, faster spark if it was treated with ultraviolet light because the light was actually exciting the electrons. Further studies by other scientists showed that electrons really could be knocked out of a metal in response to a beam of light. For a while, scientists thought that the electrons were just absorbing the energy in the light wave, and then using that energy to jump out of the metal. The more energy the electr.

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$>> Wave Character Many of the things that light does are only explained sufficiently by thinking of light as a wave. Refraction and diffraction are two examples. Light refracts when it travels from one medium to another, because waves travel at different speeds through different media. In a similar way, light diffracts when it travels between or around objects, because obstacles make the light waves bend. So, obviously we're not wrong about light behaving like a wave. We even use the wave diffraction of light by reading interference patterns in X-ray crystallography. >> Particle Behaviour photoelectric effect, which describes the way electrons are excited and emitted from matter when they absorb the energy from light. In 1887, Heinrich Hertz observed that a charged object would create a bigger, faster spark if it was treated with ultraviolet light because the light was actually exciting the electrons. Further studies by other scientists showed that electrons really could be knocked out of a metal in response to a beam of light. For a while, scientists thought that the electrons were just absorbing the energy in the light wave, and then using that energy to jump out of the metal. The more energy the electrons could absorb, the more energy they could use to jump out. A photon is a nearly massless particle carrying a small amount of energy. We use photons to quantify, or measure the amount of, the energy in light and other electromagnetic waves. Each photon can excite only one electron at a time. When the intensity of light is increased, then the number of photons is increased, so a higher number of electrons are knocked loose from the metal. The energy of electrons does not change because the energy of each photon is still the same. Solution >> Wave Character Many of the things that light does are only explained sufficiently by thinking of light as a wave. Refraction and diffraction are two examples. Light refracts when it travels from one medium to another, because waves travel at different speeds through different media. In a similar way, light diffracts when it travels between or around objects, because obstacles make the light waves bend. So, obviously we're not wrong about light behaving like a wave. We even use the wave diffraction of light by reading interference patterns in X-ray crystallography. >> Particle Behaviour photoelectric effect, which describes the way electrons are excited and emitted from matter when they absorb the energy from light. In 1887, Heinrich Hertz observed that a charged object would$

create a bigger, faster spark if it was treated with ultraviolet light because the light was actually
exciting the electrons. Further studies by other scientists showed that electrons really could be
knocked out of a metal in response to a beam of light. For a while, scientists thought that the
electrons were just absorbing the energy in the light wave, and then using that energy to jump out
of the metal. The more energy the electrons could absorb, the more energy they could use to
jump out.
A photon is a nearly massless particle carrying a small amount of energy. We use photons to
quantify, or measure the amount of, the energy in light and other electromagnetic waves. Each
photon can excite only one electron at a time. When the intensity of light is increased, then the
number of photons is increased, so a higher number of electrons are knocked loose from the
metal. The energy of electrons does not change because the energy of each photon is still the
same.

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GameOfLife.cs using System; using System.Collections.Generic;.pdf

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With the vast increase in technology, the number of ways that the use of cybertechnology impact the personalities are also increasing. Many of the social scientists has proofs for this. One incident, in the 1980s, that quickly caught their attention involved a male psychologist who joined an online forum for disabled persons, where he identified himself as a woman who had become crippled as a result of an automobile accident. Mitch Parsell (2008) describes the Internet as a \"powerful new force\" for what he calls \"the manufacture of identity.\" He believes that this technological medium offers an unparalleled ability to create ourselves in our own image. It gives users an unprecedented capacity to determine their initial presentations to others.In short, it enables users to be masters of their identity. Now when we talk about Ethics and Technology: Controversies, Questions, and Strategies for Ethical Computing: Cybertechnology as a \"Medium of Self-Expression\" Sherry Turkle (2005) notes that by the mid-1980s, computers had become an \"evocative object\"—i.e., an object that \"provoked self- reflection.\" Turkle suggested that a computer could be viewed as a model for analyzing and constructing one\'s identity. She also noted that the computer has become a medium through which people could discover their personal identity; for example, computers provide a context in which individuals can try out different cognitive styles and different methods of problem solving to ultimately discover which style or method they prefer. Because people develop their own unique style of computing, Turkle argues that the computational environment becomes an extension of themselves, in much the same way that their manner of dress is an extension of their personality. So, in her view, a computer can function as a \"medium for self-expression\" as well as for \"self-discovery. Impact of cybertechnology on Sense of Self We have examined some effects that one\'s interactions in virtual or computer-mediated environments, including MOOs and MUDs, can have for one\'s personal identity. 2 main factors are: our relation to nature, our relation to (and sense of place in) the universe. Williams notes that in the aftermath of these milestones, we have a much humbler view of our place in the universe than our ancestors did. How, exactly, has cybertechnology also has influenced the way that we see ourselves in relation to both the factors—i.e., how has this relatively recent technology already begun to define us as human beings? To support Bolter\'s thesis that we have come to see ourselves more and more in computer-like ways, we have only to reflect for a moment on some of the expressions that we now use to describe ourselves. For example, Bolter points out that when psychologists speak of \"input and output states of the brain,\" or of the brain\'s hardware and software, they exemplify Turing\'s men. And when cognitive psychologists study the \"mind\'s algorithm for searchi.

With the vast increase in technology, the number of ways that the us.pdf

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//Let n = size of the hash table // hashTable = array of size n, which represents the hash table // hashIndex = represents the index of array // If the list is EMPTY, we add the element into the list /*If the list is NOT EMPTY then we compare the newNode to the node already in the list in such a way to get sorted.*/ struct node { int key; T value; struct node *next; }; struct node *hashTable[n] = {NULL}; struct node * createNode(int key, char *name, int age) { struct node *newnode; newnode = (struct node *)malloc(sizeof(struct node)); newnode->key = key; newnode->value = value; newnode->next = NULL; return newnode; } add(int key, T value) { int hashIndex = key % n; struct node *newNode = creteNode(key,value); /*Adding new node to the list with No element */ if (hashTable[hashIndex] == NULL) { hashTable[hashIndex] = newnode; return; } /*Adding new node to the sorted list */ struct node *temp1; struct node *temp2 = hashTable[hashIndex]; temp1 = temp2; while(temp2 -> key < newNode -> key) { temp1 = temp2; temp2 = temp2 ->next; } newnode->next = temp2; temp1->next = newNode; return; } Solution //Let n = size of the hash table // hashTable = array of size n, which represents the hash table // hashIndex = represents the index of array // If the list is EMPTY, we add the element into the list /*If the list is NOT EMPTY then we compare the newNode to the node already in the list in such a way to get sorted.*/ struct node { int key; T value; struct node *next; }; struct node *hashTable[n] = {NULL}; struct node * createNode(int key, char *name, int age) { struct node *newnode; newnode = (struct node *)malloc(sizeof(struct node)); newnode->key = key; newnode->value = value; newnode->next = NULL; return newnode; } add(int key, T value) { int hashIndex = key % n; struct node *newNode = creteNode(key,value); /*Adding new node to the list with No element */ if (hashTable[hashIndex] == NULL) { hashTable[hashIndex] = newnode; return; } /*Adding new node to the sorted list */ struct node *temp1; struct node *temp2 = hashTable[hashIndex]; temp1 = temp2; while(temp2 -> key < newNode -> key) { temp1 = temp2; temp2 = temp2 ->next; } newnode->next = temp2; temp1->next = newNode; return; }.

Let n = size of the hash table hashTable = array of size n, w.pdf

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What is the need of the t Distribution? According to the central limit theorem, the sampling distribution of a statistic (like a sample mean) will follow a normal distribution, as long as the sample size is sufficiently large. Therefore, when we know the standard deviation of the population, we can compute a z-score, and use the normal distribution to evaluate probabilities with the sample mean. But sample sizes are sometimes small, and often we do not know the standard deviation of the population. When either of these problems occur, statisticians rely on the distribution of the t statistic (also known as the t score), whose values are given by: t = [ x - ? ] / [ s / sqrt( n ) ] where x is the sample mean, ? is the population mean, s is the standard deviation of the sample, and n is the sample size. The distribution of the t statistic is called the t distribution or the Student t distribution. The t distribution allows us to conduct statistical analyses on certain data sets that are not appropriate for analysis, using the normal distribution. Degrees of Freedom There are actually many different t distributions. The particular form of the t distribution is determined by its degrees of freedom. The degrees of freedom refers to the number of independent observations in a set of data. When estimating a mean score or a proportion from a single sample, the number of independent observations is equal to the sample size minus one. Hence, the distribution of the t statistic from samples of size 8 would be described by a t distribution having 8 - 1 or 7 degrees of freedom. Similarly, a t distribution having 15 degrees of freedom would be used with a sample of size 16. Solution What is the need of the t Distribution? According to the central limit theorem, the sampling distribution of a statistic (like a sample mean) will follow a normal distribution, as long as the sample size is sufficiently large. Therefore, when we know the standard deviation of the population, we can compute a z-score, and use the normal distribution to evaluate probabilities with the sample mean. But sample sizes are sometimes small, and often we do not know the standard deviation of the population. When either of these problems occur, statisticians rely on the distribution of the t statistic (also known as the t score), whose values are given by: t = [ x - ? ] / [ s / sqrt( n ) ] where x is the sample mean, ? is the population mean, s is the standard deviation of the sample, and n is the sample size. The distribution of the t statistic is called the t distribution or the Student t distribution. The t distribution allows us to conduct statistical analyses on certain data sets that are not appropriate for analysis, using the normal distribution. Degrees of Freedom There are actually many different t distributions. The particular form of the t distribution is determined by its degrees of freedom. The degrees of freedom refers to the number of independent observations in a set of da.

What is the need of the t Distribution According to the central.pdf

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We can see in course of evolution of plant there was a transition from aquatic to terrestrial life has taken place.They have adapted lots of features to servive on land. 1.Thay became so large comparative ao aquatic plants.This feature evolve to colonise the land. 2.They have developed well organised vascular system allowing plant to absorb water from soil. 3 .They have evolved strong roots to adhere by the substratum.They can go few meters inside the soil. Solution We can see in course of evolution of plant there was a transition from aquatic to terrestrial life has taken place.They have adapted lots of features to servive on land. 1.Thay became so large comparative ao aquatic plants.This feature evolve to colonise the land. 2.They have developed well organised vascular system allowing plant to absorb water from soil. 3 .They have evolved strong roots to adhere by the substratum.They can go few meters inside the soil..

We can see in course of evolution of plant there was a transition fr.pdf

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The solvent doesnt interfere with the purification process Oil Bath Assembly Mineral oil or silicone oil is typically used for oil baths in research labs for reactions that require heating/reflux temperatures up to 200 °C. Oil baths provide more uniform heat in comparison to other heating devices. A laboratory oil bath is made of an aluminum or stainless steel pan, a heavy porcelain dish or thick walled Pyrex® glass to withstand breakage and accidental spill. The electric heating coil (or oil bath on a hot plate) is controlled using a variable voltage controller (i.e., Variac). The voltage controller is adjusted to increase or decrease the temperature setting of the oil bath. Heating mantles should NEVER be plugged directly into an outlet. Bath Material Useful Range Flash Point Advantage/Disadvantage Risk Silicone Oil 25 °C to 230 °C 150 °C to 350 °C Acceptable MODERATE Water (rotary evaporator) 0 °C to 70 °C Acceptable. LOW Sand 25°C to 500+ °C NA Acceptable. LOW Hazards Hazards associated with the use of oil baths include hot temperatures and fire. Medical Attention and Emergency Treatment Use cold water and rinse the affected skin immediately for at least for 15 minutes; remove any hot oil residue without rubbing the skin. If the affected area is on the hand, wrap with a clean bandage to prevent further irritation and injury. DO NOT apply any ointments and avoid breaking blisters. Seek medical attention as necessary. Medical Attention and Emergency Treatment information is provided on the EHS website. Personal Protective Equipment (PPE) Slip-resistant insulated thermal gloves. Safety glasses with side shields or a face shield. Lab coat (and wear pants that cover the legs). Prudent Safety Practices Storage Spill Cleanup Granular clay absorbents, universal polypropylene sorbent pads, or other oil-specific absorbent pads can be used for cleanup of small incidental spills of both bath oil and vacuum pump oil. Solid waste from the cleanup can be scooped, bagged, and placed in a metal container or other compatible container. Oil-specific absorbents absorb only oil and not aqueous materials. For questions, contact EHS for proper cleanup and disposal procedures. Disposal of Used Oil advantages techniques are understandably used only for samples containing a significant amount of combustible or organic material as the matrix. With this in mind, let\'s look at the major advantages · The ability to decompose large sample sizes. · The need for little or no reagents. · The technique is relatively safe. · The ability to prepare samples containing volatile combustion elements such as sulfur, fluorine and chlorine (the Schöniger oxygen flask combustion technique is very popular in this case). · The technique lends itself to mass production. The technique of graphite furnace atomic absorption spectrometry (GFAA) incorporates sample ashing as part of an automatic measurement cycle. Trace analysts have learned a great deal about the loss of volatile componen.

The solvent doesnt interfere with the purification processOil Bath.pdf

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/* An object of class StatCalc can be used to compute several simple statistics for a set of numbers. Numbers are entered into the dataset using the enter(double) method. Methods are provided to return the following statistics for the set of numbers that have been entered: The number of items, the sum of the items, the average, the standard deviation, the maximum, and the minimum. */ public class Stats { private int count; // Number of numbers that have been entered. private double sum; // The sum of all the items that have been entered. private double squareSum; // The sum of the squares of all the items. private double max = Double.NEGATIVE_INFINITY; // Largest item seen. private double min = Double.POSITIVE_INFINITY; // Smallest item seen. int[] myList; public int getCount() { System.out.println(myList.size()); count = myList.size(). // Return number of items that have been entered. return count; } public double getSum() { int sum = 0; for (int i = 0; i < myList.length; i++) { sum +=mylist[i]; } return sum; } public double getMean() { int sum = 0; for (int i = 0; i < myList.length; i++) { sum +=mylist[i]; } if(count > 0) return sum / count; else return -1; } public double getMin() { int smallest = myList[0]; int largetst = myList[0]; for(int i=1; i< mylist.length; i++) { if(mylist[i] > largetst) largetst = numbers[i]; else if (mylist[i] < smallest) smallest = numbers[i]; } return smallest; } public double getMax() { int smallest = myList[0]; int largetst = myList[0]; for(int i=1; i< mylist.length; i++) { if(mylist[i] > largetst) largetst = numbers[i]; else if (mylist[i] < smallest) smallest = numbers[i]; } return largetst; } stats(int [] data) { if(data.count <= count) { if(myList.size() > 0) System.arraycopy( myList, 0, data, 0, count ); } } stats() { Scanner s = new Scanner(System.in); int count = s.nextInt(); s.nextLine(); // throw away the newline. int [] numbers = new int[count]; Scanner numScanner = new Scanner(s.nextLine()); for (int i = 0; i < count; i++) { if (numScanner.hasNextInt()) { numbers[i] = numScanner.nextInt(); } else { System.out.println(\"You didn\'t provide enough numbers\"); break; } } System.arraycopy( myList, 0, numbers, 0, count ); } stats(int size) { setValue(size); } private void setValue(int size) { count = size; myList = new int[size]; } } // end class StatCalc public class SimpleStats { public static void main(String[] args) { Stat calc; // Computes stats for numbers entered by user. calc = new Stat(100); int arry[] = {20.20.40,30.80,,70,4,5,6,7,10} calc.setvalue(array); double item; // One number entered by the user. TextIO.putln(\"Enter your numbers. Enter 0 to end.\"); TextIO.putln(); do { TextIO.put(\"? \"); item = TextIO.getlnDouble(); if (item != 0) calc.enter(item); } while ( item != 0 ); TextIO.putln(\"\ Statistics about your calc:\ \"); TextIO.putln(\" Count: \" + calc.getCount()); TextIO.putln(\" Sum: \" + calc.getSum()); TextIO.putln(\" Minimum: \" + calc.getMin()); TextIO.putln(\" Maximum: \" + ca.

An object of class StatCalc can be used to compute several simp.pdf

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The answers can be found below as discussed: Part 1) The human genome is highly vast in nature and hence there are some complicating factors in the study of human genetics: 1: Size and packing: The human genome is enoromously large in linear seqeunce which makes it highly difficult to be analysed as a whole. Moreover, the DNA is wounded in complex primary, secondary and tertiary structures which makes is difficult to isolate intact i.e. formation of nucleosomes over histones, solenoid formation, high writhe and twist etc. The human genome is highly compact and along with it, chemical modifications such as acetylation/methylation/sumoylation/phosphorylation of the DNA-associated proteins also occur. Similarly, post-transcriptional modifications of mRNA also occur only in eukaryotes. Compensation: These structural features of the human genome have been well exploited for their analysis. The size cannot be reduced directly but the complexity of packing can be used by action of relaxation enzymes such as topoisomerases. Part 2) The coding sequences: The human genome is not continuously coding in nature, but it has been differentiated into stretches of coding euchromatin exons and non-coding intervening heterochromatin intron sequences. This makes the linearity of the coding sequence highly compromised and a single mechanism of linear transcription or translation cannot take place. Compensation: The human genome contains the intron sequences only in the DNA. These sequences are effectively removed out of the DNA after transcription by mRNA splicing and thus only exons are remained in the mRNA. Thus, this ensures that only exons can reach the translation process. 3. Polymorphism: The human genome shows very high degree of single nucleotide polymorphism (SNP) which shows pattern of inheritance and can be transitted form one person to another genetically. These SNPs are crucial for providing discrete phenotypic features to individuals which can be difficult to assess and identify due to large size of human genome. Compensation: Although there occur SNPs in human genome, the modern techniques such as next-generation seqeuncing have made it possible to effectively, efficiently and quickly screen the whole genome for such targets. Answer part 2) Variations in Mendelian genetics in humans can be described as below: 1. Co-dominance: Unlike Mendelian genetics, the blood group system of humans show co- dominance between the allele A and allele B and both of these alleles are completely dominant over the allele O. This makes occurance of various phenotypes in blood groups i.e. A, B, AB and O. 2. Incomplete dominance: On contrary to Mendel\'s pattern of inheritance, the texture of hair in human is inherited genetically following a pattern of incomplete dominance. This deciphers that an offspring of parents having straight and curly hair will have softly curled hair. 3. Quantitative traits: Unlike Mendel\'s patterns of inheritance, some genes show quantitative.

The answers can be found below as discussedPart 1)The human gen.pdf

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Solution (3)The smallest respiratory bronchioles subdivide into t.pdf

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An asset manager of a hedge fund or a mutual funds is the one who directly handles the client money and is responsible for acting in an ethical manner while discharging their duties. Some of the major ways in which asset managers breach their fiduciary duties are as follows : (i) Asset Managers generally have access to private information of companies\' profits, next business move, major public announcements which have direct effect on the stock price. In order to make their judgement about stocks right, fund managers use manupulative techniques to inflate stock prices with the help of insider information. (ii) Fund managers in normal practice met out prefrential treatment to clients whose asset volume being managed is higher than the rest of the group. In this way only a group of clients gets all the attention of the fund manager. (iii) Fund managers usually undertake complex financial transactions and disclose less of these to the clients and regulators. (iv) Fund managers engage in activities which more oftem result in conflict of interest. Conflicts of interest can be in the form of raise larger funds when insufficient opportunities exist, taking over undisclosed and inappropriate risk in the investment etc. Solution An asset manager of a hedge fund or a mutual funds is the one who directly handles the client money and is responsible for acting in an ethical manner while discharging their duties. Some of the major ways in which asset managers breach their fiduciary duties are as follows : (i) Asset Managers generally have access to private information of companies\' profits, next business move, major public announcements which have direct effect on the stock price. In order to make their judgement about stocks right, fund managers use manupulative techniques to inflate stock prices with the help of insider information. (ii) Fund managers in normal practice met out prefrential treatment to clients whose asset volume being managed is higher than the rest of the group. In this way only a group of clients gets all the attention of the fund manager. (iii) Fund managers usually undertake complex financial transactions and disclose less of these to the clients and regulators. (iv) Fund managers engage in activities which more oftem result in conflict of interest. Conflicts of interest can be in the form of raise larger funds when insufficient opportunities exist, taking over undisclosed and inappropriate risk in the investment etc..

An asset manager of a hedge fund or a mutual funds is the one who di.pdf

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