answer:Here is a Python solution using the datetime module:```pythonimport datetimedef julian_to_gregorian(julian_date): try: if len(str(julian_date)) != 7: return "Invalid Input: Please input Julian Date in format YYYYDDD." year = int(str(julian_date)[:4]) day = int(str(julian_date)[4:]) if day < 1 or day > 366: return "Invalid Input: Day of Julian Date is out of range." # Check for validity of date especially for leap years if day > 365: if year%400 == 0 or (year%4 == 0 and year%100 != 0): pass # it's a leap year else: return "Invalid Input: This year is not a leap year." gregorian_date = datetime.datetime(year, 1, 1) + datetime.timedelta(day - 1) return gregorian_date.strftime("%d-%m-%Y") except Exception as e: return "An error occurred: " + str(e)# Test the functionprint(julian_to_gregorian(2021365))print(julian_to_gregorian(2020366))print(julian_to_gregorian(2021366))print(julian_to_gregorian("wrongInput"))print(julian_to_gregorian(20211234))```In this solution, we first check for the length of the input string, that it needs to be 7. Then we split the year and the day. The day needs to be between 1 and 366. After that, if we have more than 365 days, the given year needs to be a leap year (either divisible by 400 or divisible by 4 but not divisible by 100). We then convert it into the Gregorian date using datetime and timedelta. Finally, we return the date in "%d-%m-%Y" format. If there are any other errors, it will be caught in the exception block.

answer:The least common multiple (LCM) of two integers a and b, usually denoted by LCM(a, b), is the smallest positive integer that is divisible by both a and b. In Python, we can find the LCM of two numbers using the in-built functions math.gcd() and the formula to find the LCM of two numbers which is (a*b) // gcd(a, b)Below is the Python code:```pythonimport mathdef lcm(a, b): return abs(a*b) // math.gcd(a, b)print(lcm(24, 36))```When you run this code, it will display 72 which is option C) 72.

answer:The error that you're encountering is "invalid_json", meaning your JSON formatting is incorrect in your cURL request.You should use standard quotation marks ( "") instead of smart quotes (“ ”) for keys and string values in your JSON data. This is how your corrected cURL request would look:```curl --request POST --url https://slack.com/api/conversations.setTopic --header 'Authorization: Bearer xxxxxxx' --header 'Content-type: application/json; charset=utf-8' --data '{"channel": "xxxxxxxxx", "topic": "this is a test"}'```Please make sure to replace `xxxxxxxx` and `xxxxxxx` with your token and channel_id respectively.Also, note that the `text` parameter should be `topic`. The topic parameter defines the new topic string to apply to the conversation.

answer:Here is a PostgreSQL implementation for this problem. This implementation assumes that we have a table named `your_table` with a numeric column named `your_column`. Adjust these placeholders to your actual table and column names. ```SQLWITH sorted AS ( SELECT your_column FROM your_table ORDER BY your_column), counted AS ( SELECT COUNT(*) as total_count FROM your_table),medians AS ( SELECT AVG(your_column) as median FROM ( SELECT your_column, NTILE(2) OVER(ORDER BY your_column) AS bucket FROM sorted ) AS x WHERE bucket = 1 OR (bucket = 2 AND total_count % 2 != 0)),final AS ( SELECT * FROM your_table WHERE EXISTS ( SELECT * FROM medians WHERE median < 20 ))SELECT * FROM final;```This script uses a window function `NTILE(2)` to divide the sorted rows into two equal parts. If there are an odd number of rows, the middle one is placed into the second bucket. This allows to calculate median as an average of the elements in the first bucket and, in case of an odd total, the first element in the second one.Note that window functions are supported by most modern SQL databases, but the specific syntax might differ. Also, retrieving large amounts of data with such a query might be inefficient for large databases. Be sure to add indexes on columns involved in sorting or filtrations.

answer:Currently, Google's BigQuery SDK does not support Swift. However, you can use Google's RESTful API to access your BigQuery data from Swift. Here is an example using URLSession for GET request to BigQuery API:```swiftimport Foundationlet url = URL(string: "https://www.googleapis.com/bigquery/v2/projects/{projectId}/queries")!var request = URLRequest(url: url)request.httpMethod = "POST"request.addValue("application/json", forHTTPHeaderField: "Content-Type")request.addValue("Bearer YOUR_ACCESS_TOKEN", forHTTPHeaderField: "Authorization")// Query jsonlet json: [String: Any] = ["query": "SELECT * FROM `project.dataset.users_activity` LIMIT 1000"]let jsonData = try? JSONSerialization.data(withJSONObject: json)// Insert the json data to the requestrequest.httpBody = jsonDatalet task = URLSession.shared.dataTask(with: request) { data, response, error in if let error = error { print ("error: (error)") } else if let data = data { do { if let json = try JSONSerialization.jsonObject(with: data, options: []) as? [String:AnyObject] { print(json) // Insert your Anomaly Detection code here. } else { print("Could not parse data as json") } } catch let parseError { print ("Could not parse the data as json '(parseError.localizedDescription)'") } }}task.resume()```Here, you need to replace `{projectId}` with your GCP Project ID and `YOUR_ACCESS_TOKEN` with a valid OAuth 2.0 token. This code will return the json representation of the response from BigQuery. You can then parse that JSON and use the response. Please remember that using BigQuery API needs the appropriate scopes and authorised OAuth 2.0 credentials.

answer:The issue may not lie with the Cypress test case but rather with the website you are trying to access. Some websites don't allow for automation tools like Cypress to access them. Microsoft Teams, for instance, could potentially block requests coming from Cypress.You can also potentially try logging in using a different method. For instance, you could try using `cy.request()` method to perform a login by sending a POST request. However, keep in mind that automating login for websites that don't have a public API is generally considered bad practice and is often limited or blocked by the server.Do ensure to protect such sensitive information as your login credentials. Cypress supports environment variables which can be useful for storing and using such information. Here is an example of how you could implement this:```javascriptit('logs in programmatically without using the UI', function () { const username = Cypress.env('username') const password = Cypress.env('password') cy.request({ method: 'POST', url: '/login', // replace with real login endpoint body: { username, password } }) cy.visit('/')})```You would then store the actual username and password in your `cypress.json` or `cypress.env.json` file as environment variables:```json{ "username": "your_username", "password": "your_password"}```Lastly, always remember to ignore these files in your `.gitignore` file to not expose your sensitive credentials.Do note that this is a general approach and would need to be modified based on how the actual login is implemented in the website you are testing.