Question As an employee of an IT service company, You will often be required to deploy new desktops, laptops and servers for your clients. One of your clients, a software company called SYSMECH has requested a new Linux desktop, running the latest LTS version of Ubuntu. TASKS: Document the following steps so that they can be repeated by another IT technician. Create USB install media for Ubuntu – using the latest LTS version available. Document the version, and where it was sourced. Install the operating system. Document each stage of the process, and the option you have selected Document the size of the HDD or SSD being used Document the available RAM in the system. Document how long the Installation process took.

Suppose you want to use A* techniques to create NxN panmagic squares. That is, the elements are the integers between 1 and N2 inclusive, and the sum along all rows and all columns and the mam diagonals is the same, like this one for N=4. 13 2 16 3 127 9 6 1 144 15 8 115 10 OOP olu What are a g function and an admissible h function?

Asap please Thank you❤ lodine-131 is used to treat Graves disease, a disease of the thyroid gland. The amount of 1311 used depends on the size of the gland. If the dose is 86 microcuries per gram of thyroid gland, how many grams of 1311 should be administered to a patient with a thyroid gland weighing 30 g? Assume all the iodine administered accumulates in the thyroid gland. x 10 PA 8 131 294 In 2006, the synthesis of 118 Uuo (an isotope of element 118) was reported to involve the bombardment of 248Cf with 48Ca. Select an equation for the nuclear reaction, being sure to include any other products of the reaction. 248 48 118 98 248 118 n 0 Cf + 20 Ca → 19Uuo + He 294 Uuo +ó Cf + 294 Uuo + 2 n Cf + 294 Uuo + 2 ) n+2e 98 248 48 Cf + Ca → 20 48 Ca → 20 98 248 48 Ca → 20 98 At 25 °C, the following concentrations were found for the gases in an equilibrium mixture for the reaction N2O(g) + NO2(g) = 3NO(g) [NO2] = 0.18 M, [NO] = 5.1 x 10-8 M, and [N2O) = 0.078 M. What is the value of Kp for this reaction? Enter your answer in scientific notation. Kp i x 10 i

please I badly need to know the right answer tysm lodine 131 is used to treat Graves disease, a disease of the thyroid gland. The amount of 191 used depends on the size of the land. It the dose is B6 microcuries per gram of thyroid gland, how many grams of 154 should be administered to a potient with a thyroid gland weighing 34 g? Assume all the iodine administered accumulates in the thyroid gland. x 10 8134 The fuel for a thermonuclear bomb (hydrogen bomb) is lithium deuteride, a salt composed of the ions Land; H. Considering the nuclear reaction + n - He + H explain how a 23Su fission bomb could serve as a trigger for a fusion bomb. A 235 92 Uproduces and the Uhssion bomb could serve as a trigger for fusion bomb because the reaction of could be used in the reaction of Li-6 to form He-4 and H-3. Select all the appropriate balanced nuclear equations for this process. 11 215 U +- Kr + Ba + 3 U + He 3 He+ Ra Select all the appropriate balanced nuclear equations for this process. 235 94 36 56 235 227 88 D 92 235 92 235 92 Cs + U +ón → Kr + '3% Ba +3;n U - U + He → 3, He + 23% Ra 2U → He + 3, Th U +on → Xe +3% Sr + n U ton → Rb +on Kr + Baton 2U +ón y Cs + Rb + 3) n. 24 He + "38 Ra U +1e3e+ 75 U + n = 44 Xe + + 231 90 140 54 140 55 94 36 140 55 227 235 92 235 94 38 93 37 139 56 93 37 5U + n 72- 92 235 U 92 235 92 225 92 235 Pu 94 140 54 Sr + 20 38

When landing on a product webpage at Amazon.com, customers will find a section called "Customers Who Bought This Item Also Bought" for recommending books, CDs, and other products that are commonly co-purchased with the current product, a feature designed to boost cross-selling. Task 1 : Here we're going to write Python code to process historical transaction data to implement the feature. Suppose that we are using a Python list to maintain all products purchased in different transactions: transactions = [[2, 8, 3, 6, 1, 9], [0, 5, 9], [0, 9], [4, 7, 0, 5, 9], [8, 3], [1, 6, 3, 8], [9, 0, 5], [3, 8], [5, 7, 0, 4], [3, 1, 2, 6, 0]] Elements in each sublist represent product IDs co-purchased in a transaction. Our goal is, for each product in this tiny transaction dataset, recommend products that are most frequently purchased together with the current product. Please complete the following tasks based on the problem description. For each transaction, enumerate all pairs of products that co-occur in the corresponding sublist. For example, processing the sublist [9, 0, 5] should produce three pairs (0, 5), (0, 9), and (5, 9). Pay attention to the order of product IDs in each pair. The same product pair (e.g., product 5 and product 9) can have two different representations (i.e., (5, 9) and (9, 5)). To facilitate the subsequent processing, make sure all pairs each are represented by its ascending representation (e.g., (0, 5) rather than (5, 0)). Moreover, make sure product pairs created from the same sublist are sorted first by the 1st element and then by the 2nd element. E.g., the list of pairs created from the sublist [1, 6, 3, 8] should be presented as [(1, 3), (1, 6), (1, 8), (3, 6), (3, 8), (6, 8)]. Produce a Python list, product_pairs, whose values each are a list of such pairs. The expected output of print(product_pairs) is as follows: [[(1, 2), (1, 3), (1, 6), (1, 8), (1, 9), (2, 3), (2, 6), (2, 8), (2, 9), (3, 6), (3, 8), (3, 9), (6, 8), (6, 9), (8, 9)], [(0, 5), (0, 9), (5, 9)], [(0, 9)], [(0, 4), (0, 5), (0, 7), (0, 9), (4, 5), (4, 7), (4, 9), (5, 7), (5, 9), (7, 9)], [(3, 8)], [(1, 3), (1, 6), (1, 8), (3, 6), (3, 8), (6, 8)], [(0, 5), (0, 9), (5, 9)], [(3, 8)], [(0, 4), (0, 5), (0, 7), (4, 5), (4, 7), (5, 7)], [(0, 1), (0, 2), (0, 3), (0, 6), (1, 2), (1, 3), (1, 6), (2, 3), (2, 6), (3, 6)]] Full credits will be awarded only if your answer is a comprehension implemention. Loop implementations can only get at most 80% of full marks. Task 2 : Next, we will process product_pairs to create a dictionary cooccurences, whose keys are product pairs and whose values represent the number of their co-occurrences across transactions. The expected output of print(cooccurences) should look like the following (the output formatting can be different): {(0, 1): 1, (0, 2): 1, (0, 3): 1, (0, 4): 2, (0, 5): 4, (0, 6): 1, (0, 7): 2, (0, 9): 4, (1, 2): 2, (1, 3): 3, (1, 6): 3, (1, 8): 2, (1, 9): 1, (2, 3): 2, (2, 6): 2, (2, 8): 1, (2, 9): 1, (3, 6): 3, (3, 8): 4, (3, 9): 1, (4, 5): 2, (4, 7): 2, (4, 9): 1, (5, 7): 2, (5, 9): 3, (6, 8): 2, (6, 9): 1, (7, 9): 1, (8, 9): 1} Full credits will be awarded only if the order of keys in your result matches exactly that in the expected output. Task 3 : Process cooccurences to output a new dictionary recommendation whose entries each are a list of recommended products associated with the number of transactions where they were co-purchased. The expected output is as follows: {0: [(5, 4), (9, 4), (4, 2), (7, 2), (1, 1), (2, 1), (3, 1), (6, 1)], 1: [(3, 3), (6, 3), (2, 2), (8, 2), (0, 1), (9, 1)], 2: [(1, 2), (3, 2), (6, 2), (0, 1), (8, 1), (9, 1)], 3: [(8, 4), (1, 3), (6, 3), (2, 2), (0, 1), (9, 1)], 4: [(0, 2), (5, 2), (7, 2), (9, 1)], 5: [(0, 4), (9, 3), (4, 2), (7, 2)], 6: [(1, 3), (3, 3), (2, 2), (8, 2), (0, 1), (9, 1)], 7: [(0, 2), (4, 2), (5, 2), (9, 1)], 9: [(0, 4), (5, 3), (1, 1), (2, 1), (3, 1), (4, 1), (6, 1), (7, 1), (8, 1)], 8: [(3, 4), (1, 2), (6, 2), (2, 1), (9, 1)]} It means that, e.g., for product 5 (corresponding to the entry 5: [(0, 4), (9, 3), (4, 2), (7, 2)]), a list of products (i.e., product 0, 9, 4, and 7), each being represented by a tuple with the 1st element being the ID and the 2nd the number of transactions where it has appeared together with product 5, are recommended. The recommended products are also sorted in descending order by the the number of cooccurences with product 5 (i.e., the 2nd element of inner tuples). # starter code​ transactions = [[2, 8, 3, 6, 1, 9], [0, 5, 9], [0, 9], [4, 7, 0, 5, 9], [8, 3], [1, 6, 3, 8], [9, 0, 5], [3, 8], [5, 7, 0, 4], [3, 1, 2, 6, 0]] Please do not answer the question if u don't really know it.

Task 1 :Here we're going to write Python code to process historical transaction data to implement the feature.Suppose that we are using a Python list to maintain all products purchased in different transactions:transactions = [[2, 8, 3, 6, 1, 9], [0, 5, 9], [0, 9], [4, 7, 0, 5, 9], [8, 3], [1, 6, 3, 8], [9, 0, 5], [3, 8], [5, 7, 0, 4], [3, 1, 2, 6, 0]]Elements in each sublist represent product IDs co-purchased in a transaction.Our goal is, for each product in this tiny transaction dataset, recommend products that are most frequently purchased together with the current product.Please complete the following tasks based on the problem description.For each transaction, enumerate all pairs of products that co-occur in the corresponding sublist. For example, processing the sublist [9, 0, 5] should produce three pairs (0, 5), (0, 9), and (5, 9).Pay attention to the order of product IDs in each pair. The same product pair (e.g., product 5 and product 9) can have two different representations (i.e., (5, 9) and (9, 5)). To facilitate the subsequent processing, make sure all pairs each are represented by its ascending representation (e.g., (0, 5) rather than (5, 0)).Moreover, make sure product pairs created from the same sublist are sorted first by the 1st element and then by the 2nd element. E.g., the list of pairs created from the sublist [1, 6, 3, 8] should be presented as [(1, 3), (1, 6), (1, 8), (3, 6), (3, 8), (6, 8)].Produce a Python list, product_pairs, whose values each are a list of such pairs.The expected output of print(product_pairs) is as follows:[[(1, 2), (1, 3), (1, 6), (1, 8), (1, 9), (2, 3), (2, 6), (2, 8), (2, 9), (3, 6), (3, 8), (3, 9), (6, 8), (6, 9), (8, 9)], [(0, 5), (0, 9), (5, 9)], [(0, 9)], [(0, 4), (0, 5), (0, 7), (0, 9), (4, 5), (4, 7), (4, 9), (5, 7), (5, 9), (7, 9)], [(3, 8)], [(1, 3), (1, 6), (1, 8), (3, 6), (3, 8), (6, 8)], [(0, 5), (0, 9), (5, 9)], [(3, 8)], [(0, 4), (0, 5), (0, 7), (4, 5), (4, 7), (5, 7)], [(0, 1), (0, 2), (0, 3), (0, 6), (1, 2), (1, 3), (1, 6), (2, 3), (2, 6), (3, 6)]] Full credits will be awarded only if your answer is a comprehension implemention. Loop implementations can only get at most 80% of full marks.Task 2 :Next, we will process product_pairs to create a dictionary cooccurences, whose keys are product pairs and whose values represent the number of their co-occurrences across transactions.The expected output of print(cooccurences) should look like the following (the output formatting can be different):{(0, 1): 1, (0, 2): 1, (0, 3): 1, (0, 4): 2, (0, 5): 4, (0, 6): 1, (0, 7): 2, (0, 9): 4, (1, 2): 2, (1, 3): 3, (1, 6): 3, (1, 8): 2, (1, 9): 1, (2, 3): 2, (2, 6): 2, (2, 8): 1, (2, 9): 1, (3, 6): 3, (3, 8): 4, (3, 9): 1, (4, 5): 2, (4, 7): 2, (4, 9): 1, (5, 7): 2, (5, 9): 3, (6, 8): 2, (6, 9): 1, (7, 9): 1, (8, 9): 1}Full credits will be awarded only if the order of keys in your result matches exactly that in the expected output.Task 3 :Process cooccurences to output a new dictionary recommendation whose entries each are a list of recommended products associated with the number of transactions where they were co-purchased.The expected output is as follows:{0: [(5, 4), (9, 4), (4, 2), (7, 2), (1, 1), (2, 1), (3, 1), (6, 1)], 1: [(3, 3), (6, 3), (2, 2), (8, 2), (0, 1), (9, 1)], 2: [(1, 2), (3, 2), (6, 2), (0, 1), (8, 1), (9, 1)], 3: [(8, 4), (1, 3), (6, 3), (2, 2), (0, 1), (9, 1)], 4: [(0, 2), (5, 2), (7, 2), (9, 1)], 5: [(0, 4), (9, 3), (4, 2), (7, 2)], 6: [(1, 3), (3, 3), (2, 2), (8, 2), (0, 1), (9, 1)], 7: [(0, 2), (4, 2), (5, 2), (9, 1)], 9: [(0, 4), (5, 3), (1, 1), (2, 1), (3, 1), (4, 1), (6, 1), (7, 1), (8, 1)], 8: [(3, 4), (1, 2), (6, 2), (2, 1), (9, 1)]}It means that, e.g., for product 5 (corresponding to the entry 5: [(0, 4), (9, 3), (4, 2), (7, 2)]), a list of products (i.e., product 0, 9, 4, and 7), each being represented by a tuple with the 1st element being the ID and the 2nd the number of transactions where it has appeared together with product 5, are recommended. The recommended products are also sorted in descending order by the the number of cooccurences with product 5 (i.e., the 2nd element of inner tuples).# starter code​transactions = [[2, 8, 3, 6, 1, 9], [0, 5, 9], [0, 9], [4, 7, 0, 5, 9], [8, 3], [1, 6, 3, 8], [9, 0, 5], [3, 8], [5, 7, 0, 4], [3, 1, 2, 6, 0]]

Can you explain with steps, please? I really wanna learn how todo it. 5.4: Problem 6 Previous Problem Problem List Next Problem (1 point) Find the derivative of the function: y = E Vt sin tødt dy 8x^5sin(x^48)-(sin(x^3))(2x^(1/4)) dx NOTE: Enter a function as your answer. help (formulas)