Mac OS simple sound mixer
Ever wanted to play sound through multiple audio devices on your Mac OS X system? It cannot be done with the normal Mac controls, but to my surprise there is a decent sound mixer built into the base Mac OS.
Step by step instructions: Play sound on multiple devices, including Internal Speakers, on OS X | Best Mac Tips
I have this setup for my 90 year old mother, so we can all watch TV at once:
- HDMI from Mac to our Panasonic TV
- Headphones plugged into the earphone jack on the Mac
- Closed captions turned on for TV
The result is that we can turn her volume way up, while we listen over the TV’s internal speakers. The headphones, even at maximum volume, may not be quite loud enough for her. In that case, I will add a $25 earphone amplifier into the system.
Still missing: I cannot find Bluetooth headphones that are loud enough for her.
Second, I don’t know of anything similar for her phone.
When my colleagues and I developed the theory of real time electricity prices back in the dark ages (1982), we were amused to see that our equations allowed for the optimal price to be negative. Power companies would pay consumers to use more electricity! At the time, we thought it was a paradoxical case that was unlikely in practice, except possibly in the middle of the night in systems with lots of nuclear units.
Fast forward 30 years, and negative prices are a regular occurrence in real systems, including in Texas and California. And now they are even happing in the middle of the day. But there is still a puzzle: why don’t generators stop generating the moment the price goes negative?
Several blog posts from Berkeley’s great Energy Institute, and my response to one of them, show that real power systems can have a lot of unanticipated phenomena. Take together, these probably explain these apparently strange behaviors.
Source: Is Solar Really the Reason for Negative Electricity Prices? – Energy Institute Blog. and from Catherine Wolfram, Is the Duck Sinking?
TL;DR In Southern California should put PV on houses and buildings that are far from the coast, because coastal areas are cloudy much of the summer. But the actual pattern is the opposite. I estimate a 30% magnitude of loss. Even my employer, UCSD, has engaged in this foolishness in order to appear trendy.
The bumpiness of this graph shows the effects of coastal weather in August.
For STEM doctoral students at UCSD who have policy interests but are not in social science fields. I have advised several students in this program, and it has been useful for all of them.
Drawing applicants from UC San Diego’s STEM related programs, each year the School of Global Policy and Strategy (GPS) selects three doctoral students from across campus and pairs them with a GPS faculty advisor to explore the policy implications of their dissertation research.
Should data mining newcomers have to learn programming at the same time? Here is a contrarian view, which advocates a GUI (“drag and drop”) environment. Even though the popularity of R (and recently, Python) is increasing.
According to the author, naval ship handling still relies heavily on craft expertise. His article writes down some formulas and procedures to reduce collision risk. Source: When Am I Committed to Collision? | U.S. Naval Institute My own reaction is in a brief comment at the end of the article.
Here is another article in the same issue of US Naval Institute Proceedings that does a great job of explaining how collisions can happen, and why the captain of a USN ship is always responsible, and never completely safe.
This is the burden of command. A captain puts the lives of several hundred sailors into the hands of a young officer, typically 25 years old and typically green. So what does a captain count on to prevent disaster? The captain has “standing orders.” These are the rules in his or her ship that everyone (especially the OOD) lives by. …”
I have just finished my Big Data course for 2017, and noted some concepts that I want to teach better next year. One of them is how to interpret and use the coefficient estimates from linear regression. All economists are familiar with dense tables of coefficients and standard errors, but they require experience to read, and are not at all intuitive. Here is a more intuitive and useful way to display the same information. The blue dots show the coefficient estimates, while the lines show +/- 2 standard errors on the coefficients. It’s easy to see that the first two coefficients are “statistically significant at the 5% level”, the third one is not, and so on. More important, the figure gives a clear view
of the relative importance of different variables in determining the final outcomes.
The heavy lifting for this plot is done by the function sjp.lm from the sjPlot library. The main argument linreg is the standard results of a linear regression model, which is a complex list with all kinds of information buried in it. Continue reading