Apache Storm 2.0.0 includes significant improvements in terms of performance, new features, and integration with external systems. The new Java-based implementation has improved performance significantly, and made Storm’s internal APIs more maintainable and extensible. Topology jars should depend on the following artifact as of Storm 2.0.0:

Projects using for testing will additionally need to depend on the Storm server jar:

Keep an eye on the Apache Storm blog for additional posts by Storm contributors for more in-depth discussions of new features in Storm 2.0.0 including:

Special thanks are due to all those who have contributed to Apache Storm — whether through direct code contributions, documentation, bug reports, or helping other users on the mailing lists.

Maine lawmakers have passed a bill that will prevent internet providers from selling consumers’ private internet data to advertisers. The bill, if signed into law by state governor Janet Mills, will force the national and smaller regional internet providers operating in the state to first obtain permission from residents before their data can be sold or passed on to advertisers or other third parties. The Republican-controlled Federal Communications Commission voted in 2017 to allow internet providers to sell customers’ private and personal internet data and browsing histories — including which websites a user visits and for how long — to advertisers for the biggest buck.

By default, it will install z3 executable at , libraries at , and include files at , where installation prefix if inferred by the script. If you use a non standard prefix you can use the option to change the Python package directory used for installation. For example:

If you do need to install to a non standard prefix a better approach is to use a Python virtual environment and install Z3 there.

The talk was about the thing that scares me most about the future of free culture, free software, and peer production. In my talk, I argue that the firms pioneering these new models have learned and adapted processes from commons-based peer production projects like free software, Wikipedia, and CouchSurfing. The result is an important shift: A decade ago,  the kind of mass collaboration that made Wikipedia, GNU/Linux, or Couchsurfing possible was the exclusive domain of people producing freely and openly in commons.

Here are some examples:

While there are clearly more complicated examples (typically the bigger the company, the more complicated the formula becomes), this actually follows some of the basic principles of traditional Silicon Valley equity pretty closely:

There’s also a lot that’s different about this plan. It also dilutes the vested equity of those who leave the company faster than the traditional method, since your equity is directly tied to the total amount of time you’ve spent at the company. Some other notable differences include:

There are a ton of open questions with this equity model.

Recently developed automated machine-learning (AutoML) systems iteratively test and modify algorithms and those hyperparameters, and select the best-suited models. In case studies with science graduate students, who were AutoML novices, the researchers found about 85 percent of participants who used ATMSeer were confident in the models selected by the system. Results indicate three major factors — number of algorithms searched, system runtime, and finding the top-performing model — determined how users customized their AutoML searches.

Before the early 1950s, Brenner told me, many scientists “thought that proteins were sort of fuzzy polymers,” just patterns of beads that repeated or had undefined sequences. But by 1953, proteins were found to have defined sequences of beads, and DNA looked like a secret code built from four letters: A, T, G, and C. Each gene in DNA seemed to be an instruction set for assembling a protein’s beads in the right order. Crick proposed that in the DNA code, there might exist special “sense” words, which could dictate a reading frame to the protein-making machinery.

Compassion in Technology: My first year as an engineer at Chick-fil-A
by Caleb Hurd
Chick-fil-A has cutting edge technology. This blog post is a reflection on my personal journey as an engineer at Chick-fil-A with a focus on what the engineering culture is like at Chick-fil-A… all to answer the question that some of you have which is “What is it like to work in technology at Chick-fil-A?” Even though I had been at Chick-fil-A for a while, at one of the first “all hands technology” meetings I made it to I witnessed our CIO go around a room of over 150 people, personally apologize to quite a few of them for mistakes he had made, and thank them for challenging him on those mistakes and for pushing back on his decisions.

In 2018, however, the evolutionary parasitologist Sarah Reece at the University of Edinburgh and her colleagues reported an intriguing new detail absent from the centuries of earlier accounts: The timing of this phase of the malaria parasite life cycle seemed to be linked to the circadian rhythms of the host. Reece and other scientists are exploring an idea that is making waves in biology: If the body is on a circadian clock, then invasion of the body — whether by a parasite, virus or bacterium — may be governed by a clock as well, either in the host or in the invader. Yet when they repeated the experiment with mice engineered to lack BMAL1, one of the core clock proteins, the active period’s protective effect disappeared: In cells without a working clock, both times were equally good for the virus.

The first laser spectroscopic determination of the change in the nuclear charge radius for a five-electron system is reported. This is achieved by combining high-accuracy ab initio mass-shift calculations and a high-accuracy measurement of the isotope shift in the ground state transition in boron atoms. These results are the foundation for a laser spectroscopic determination of the charge radius of the proton-halo candidate .