Section G (Questions 25 ~ 27): Taxis looking for customers arrive at a taxi station as a Poisson process with rate 1 per minute, while customers looking for taxis arrive as a Poisson process with rate 1.25 per minute. Suppose taxis will wait, no matter how many taxis are in line before them. However, customers who arrive to find 2 other customers in line go away immediately.  We will set up a Markov chain with states {2, 1, 0, -1, -2, ….} as states. State 2 means two customers waiting at the taxi station; state 1 means one customer waiting at the taxi station; state -1 means one taxi waiting at the taxi station; state -2 means two taxis waiting at the taxi station and so on.   

Well-functioning financial markets

Everything else held constant, when the inflation rate is expected to rise, interest rates will ________; this result has been termed the ________.

Which Javascript code is for refreshing a window?

routes.py @application.route(‘/login’, methods=)def login(): login_form = classes.LogInForm() if login_form.validate_on_submit(): username = login_form.username.data password = login_form.password.data user = classes.User.query.filter_by(username=username).first() if user is not None and user.check_password(password): login_user(user) else: flash(‘Invalid username and password combination!’) return render_template(‘login.html’, form=login_form) flash.html {% with (1) %} {% for message in messages %} {{ message }} {% endfor %}{% endwith %}   In order to make flash.html display flash messages from routes.py, which one of the following should go in (1)?

Which of the following glial cells help fight infection and act as macrophages for foreign object?

If it is Spring (Sp) today, what is the value of the stationary probability for state Sp? If your answer is non-terminating, then report up to four digits after the decimal point. Show your work. 

The road matrix for this CTMC is given below: 

routes.py @application.route(‘/plotly_example’, methods=(‘GET’, ‘POST’))@login_requireddef plotly_example(): locations = classes.Location.query.all() output = plotly_map(locations) return render_template(‘plotly_map.html’, source=output) def plotly_map(locations): data = , lon=, text=, mode=’markers’, )] layout = Layout( autosize=True, hovermode=’closest’, mapbox=dict( accesstoken=mapbox_access_token, bearing=0, center=dict( lat=mean(), lon=mean() ), pitch=100, zoom=10 ), ) fig = dict(data=data, layout=layout) output = plotly.offline.plot(fig, include_plotlyjs=False, output_type=’div’) return(output) plotly_map.html {% block content %} {{ (1) }} {% endblock %} Which filter should be used for (1) to render the json output on plotly_map.html?

Section F (Questions 19 ~ 24): A production line consists of two stations: one for production (Station A) and one for checking (Station B). Station A has job arrivals from outside, following a Poisson arrival process with rate 11/hr (a1 = 11/hr) and internal job arrivals from station B. A study shows that 50% of jobs produced at station A do not require checking but the other 50% of jobs are sent to the checking station (Station B). Station B gets an outside arrivals following a Poisson process with rate 5/hr (a2 = 5/hr). Among jobs at station B (both jobs from the outside and from station A), only 40% do not have defectives and leave the system. But the remaining 60% jobs need to be processed again at Station A and sent back to the end of the wait line of Station A. A defective item can visit stations A and B several times until it is fully fixed. A diagram of the production line is given below:    Station A has three servers and each processes one job at a time with a normally distributed service time with mean 6 minutes and variance 2 minutes2. Station B has one server and its processing time is also normal with mean 3 minutes and variance 0.25 minutes2.