An unknown compound (A) was soluble in ether but only slightly soluble in water. It burned with a clear blue flame and combustion analysis showed it to have the molecular formula of C5H12O. It gave a positive test with the Jones reagent producing a new compound (B) with a formula of C5H10O. Compound B gave a positive iodoform test and formed a semicarbazone. Compound A on treatment with sulfuric acid produced a hydrocarbon (C) of formula C5H10. Hydrocarbon C readily decolorized a Br2–CH2Cl2 solution, and on ozonolysis, produced acetone as one of the products. Identify the structure of each of the lettered compounds.
Compound A (C7H14) decolorized a Br2–CH2Cl2 chloride solution. It reacted with BH3 • THF reagent, followed by alkaline peroxide solution, to produce compound B. Compound B, on treatment with chromic acid–sulfuric acid solution, gave carboxylic acid C, which could be separated into two enantiomers. Compound A, on treatment with ozone, followed by addition of hydrogen peroxide, produced compound D. Compound D was identical to that material isolated from the oxidation of 3-hexanol with chromic acid–sulfuric acid reagent. Identify the structures of compounds A, B, C, and D.
Compound A (C8H16) decolorized a bromine–methylene chloride solution. Ozonolysis produced two compounds, B and C, which could be separated easily by gas chromatography. Both B and C gave a positive 2,4 dinitrophenylhydrazine test. Carbon–hydrogen analysis and molecular weight determination of B gave a molecular formula of C5H10O.The 1 H NMR spectrum revealed the following information for B:
0.92 ppm 3H, triplet 2.17 ppm 3H, singlet
1.6 ppm 2H, pentet 2.45 ppm 2H, triplet
Compound C was a low-boiling liquid (bp 56°C) The 1 H NMR of this material showed only one singlet. Identify compounds A, B, and C.
Consider the following mean-square differential equation,
driven by a WSS random process with psd
The differential equation is subject to the initial condition , where the random variable has zero-mean, variance 5, and is orthogonal to the input random process .
(a) As a preliminary step, express the deterministic solution to the above differential equation, now regarded as an ordinary differential equation with deterministic input and initial condition , not a random variable. Write your solution as the sum of a zero-input part and a zero-state part.
(b) Now returning to the m.s. differential equation, write the solution random process as a mean-square convolution integral of the input process over the time interval plus a zero-input term due to the random initial condition . Justify the mean-square existence of the terms in your solution.
If a stationary random process is periodic, then we can represent it by a Fourier series with orthogonal coefficients. This is not true in general when the random process, though stationary, is not periodic. Thus, point out the fallacy in the following proposition, which purports to show that the Fourier series coefficients are always orthogonal: First take a segment of length T from a stationary random process Repeat the corresponding segment of the correlation function periodically. This then corresponds to a periodic random process. If we expand this process in a Fourier series, its coefficients will be orthogonal. Furthermore, the periodic process and the original process will agree over the original time interval.
Certain continuous time communications channel can be modeled as signal plus an independent additive noise
(a) The receiver must process for the purpose of determining the value of the message random variable M. Argue that a receiver which computes and bases its decision exclusively on, for
(b) What are the issues in determining which value of to use? Is there a best value?
Let be a random process with constant mean and covariance function,
(a) Show that an m.s. derivative process exists here.
(b) Find the covariance function of
In our derivation of the Kalman filter in Section 11.2, we assumed that the Gauss– Markov signal model (Equation 11.2-6) was zero-mean. Here we modify the Kalman filter to permit the general case of nonzero mean for . Let the Gauss–Markov signal model be
(c) Extend the Kalman filtering Equation 11.2-16 to the nonzero mean case by using the result of (b).
(d) How do the gain and error-covariance equations change?
1. What are the three major categories of resources that need to be managed during implementation?
2. What are three strategies from the modified model of Parkinson and Associates (1982) for implementing health promotion programs?
3. What are some techniques planners can use to enhance the first day of implementation? What does it mean to kick off a program?
4. What is meant by the term informed consent?
5. What can program planners do to ensure the health and safety of program participants?
It is very much necessary to follow certain steps in goal setting learning procedure. At first it is very important to understand the needs there after by making the skills one can uplift the capability of teaching. Again to improve the skills the up gradation of the skills the class management is also necessary. Another thing that needs to be remembered is adding presentations and strategies to involve more students (Jennifer, 2017).
Can you offer how you would accomplish the factors that you have identified? Min 40 words or more.
Jennifer, G.(2017); Goal-Setting for Teachers: 8 Paths to Self-Improvement; Journal of Pedeatology; USA.
Like a book report but this time you actually can just watch the movie! This is a chance for you to earn up to 20 bonus points. Watch a movie with a business theme and write a two page (double spaced typed) report on that movie. The report should tell me why you chose that movie and what business concepts it covers. Explain what you noticed about the movie or what you gained from it when you watched it from the perspective of a business student. What did you learn? What was done well or what was done poorly?
Topic examples can include:
Work/Life Balance Business Ethics Professionalism Entrepreneurism Management Styles Interpersonal Relationships Resourcefulness Persistence Data Analytics and Artificial Intelligence Importance of Digital Marketing Diversity and….