That's the title of a short article I just published (it is online here, but beware - for now you need to access from an institution that can access the journal contents), on Nuclear Instruments and Methods - a renowned journal for particle physics and nuclear physics instrumentation. The contents are nothing very new, in the sense that they are little more than a summary of things that the MODE collaboration published last March here. But for the distracted among you, I will summarize the summary below.

Humanity progresses thanks to the diffusion and sharing of human knowledge. In particular, scientific progress is brought forth by the sharing of ideas, measurements and experimental results among scientists, and the distribution of excellent education. We have grown very good at doing that, but can we improve the sharing of knowledge for the common good? 

The answer is certainly yes, as the interconnection of the scientific community and the interdisciplinarity of its efforts are hampered by borders, language barriers, cultural differences, political influences, religious hindrances, education system challenges, and also by different conventions, policies, metrics in the different areas of scientific research.

At about this time of the year I find myself teaching my students about the construction of V-A theory, which is a milestone in the construction of the Standard Model of particle physics. And in so doing I rejoice about having a chance to tell them the details of one of the most brilliant experiments of the twentieth century, one performed in 1957 by Maurice Goldhaber with his colleagues Grodzins and Sunjar, and which has become a cornerstone of the physics of weak interactions and of particle physics in general. 

The DeepLearn school series, now reaching the seventh edition, offers insight into artificial intelligence and applications in a week-long course, tightly packing a significant number of high-profile instructors. The present edition, currently being held at the Technical University of Lulea, in the north of Sweden, features the following:

- Sean Benson, Netherlands Cancer Institute
- Thomas Breuel, Nvidia
- Hao Chen, Hong Kong University of Science and Technology
- Janlin Chen, University of Missouri
- Nadya Chernyavskaya, CERN
- Efstratios Gavves, University of Amsterdam
- Quanquan Gu, University of California Los Angeles

For some reasons, my personal web page features high in web searches for master thesis offers. I got to learn this by inquiring with a few students who asked me to supervise them remotely on some of the offered topics: where did they get to know about my research activities, and what led them to pick my offers? They all answered that they bumped into my web page section "thesis offers". Well, at least that was no wasted time when I wrote it.

In a recent post in this blog I discussed the idea of exploiting the properties of negative muons for a new kind of imaging technique of unknown volumes of material. The idea is based on the fact that negative muons stopped inside matter have a lifetime that is modified by nuclear interactions, so that a precise detection of their lifetime and point of decay becomes a means of inferring the composition of unknown volumes. Here, I want to offer the results of a quick simulation of the processes, to show that the idea is not so far-fetched.

Different techniques for muon tomography