Sixteen years of Twisted Grooves in the high desert

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DavidBarsantiDavid Barsanti is a Santa Fe-based musician, drummer, DJ and GIS analyst and has lived in the City Different since the early 1990s. When not playing in various bands around town, he is actively DJing around Santa Fe and northern New Mexico under the moniker Spinifex. He and I created the Twisted Groove radio show that aired in the midnight slot on community station KSFR back in 2000. Although I left Santa Fe for the Bay Area, David has continued the show, going from strength to strength, and in the process, gaining a more sleep-friendly 10pm timeslot. Following up on the 16th anniversary of the show, I recently chatted to David about the Twisted Groove, the Santa Fe music scene and how music and radio has changed in the intervening years.

Tell us about how you got to Santa Fe

I first came to Santa Fe after getting a sociology degree with an anthropology focus from Keene State College where I’m originally from. After college I was still working in New England in archeology, but really looking for a change in environment. I was also really struggling to find work in archeology during the winter – you couldn’t find just work everywhere – it’s definitely hard to excavate then! So in November 1991, my girlfriend at the time had contacts here and we planned to come here together but that didn’t work out but I needed winter work so I was driven to find work here in SF. I was hired to do field work in the winter, and I stayed. Now by day I work as a GIS analyst for the City of Santa Fe.

What got you into music?

Sylvania-tubeI have always been into music, it was a big part of the family growing up. My oldest brother grew up in the Woodstock era so I always heard a lot of music from that time. And although my parent’s weren’t musicians themselves there was always music around the house, my Dad had worked for Sylvania, an early TV manufacturer that was eventually acquired by General Telephone and Electronics. So we always had TVs and radio stereo of the best quality around the house, which was another way I really got into sound and music.

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Decoding Turnbull: what his 2015 acceptance speech really said

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On the day of the 2016 Australian Federal election, let’s rewind to last year.  On September 14, 2015, Malcolm Turnbull ascended to the party Liberal Party leadership, and Australia breathed a collective sigh of relief as the brief, but strange and destructive, reign of Tony Abbott came to an abrupt end.  There was a sense, especially amongst Australian progressives, that we might see a return to a more moderate Liberal Party. And if you cursorily examine Turnbull’s acceptance speech, it sounds thoroughly sensible and moderate, touching on now-familiar bromides of “creativity” and “innovation”:

“This will be a thoroughly Liberal Government. It will be a thoroughly Liberal government committed to freedom, the individual and the market. It’ll be focused on ensuring that in the years ahead as the world becomes more and more competitive and greater opportunities arise, we are able to take advantage of that. The Australia of the future has to be a nation that is agile, that is innovative, that is creative. We can’t be defensive, we can’t future-proof ourselves. We have to recognise that the disruption that we see driven by technology, the volatility in change is our friend if we are agile and smart enough to take advantage of it. There has never been a more exciting time to be alive than today and there has never been a more exciting time to be an Australian. We will ensure that all Australians understand that their government recognises the opportunities of the future and is putting in place the policies and the plans to enable them to take advantage of it.”

Who can be against any of that?  Sounds good, right?  Being agile, creative, innovative! Yeaah! But having lived in the United States through the first dot-com boom, the Global Financial Crisis, and now the current tech-boom that creates only a relatively small number of jobs (and wealth for only a few of those in those jobs) and the rise of the predatory “sharing economy” of AirBnB and Uber, many of these phrases ring hollow to me. Phrases that use words like agility, creativity and innovation are very handy because they sound great as sound-bites, but are more often used as a fig leaf to disguise the true agenda.  Cognitive linguist George Lakoff in Don’t Think of an Elephant and Moral Politics has written extensively about how US right-wing think-tanks like the Heritage Foundation and the American Enterprise Institute have been successfully using words and metaphors to “frame” otherwise unpalatable policies for decades.  These think-tanks have, in turn, been diligently exporting these framings around the world through exchanges with Australian equivalents like the Institute for Public Affairs. Creativity and innovation used in the context of the LNP are code for a corporatist neoliberal set of policies that is focused on one thing and one thing only: enriching those already wealthy with even more wealth.

Many progressive Australians didn’t really see this true agenda clearly and wanted to believe that this would be a kinder, gentler Coalition government. I, too, shared this hope (although there were some commentators at the time who were not buying it). And, while the rhetoric on social issues like gay marriage has clearly shifted in a more moderate direction, in the areas that affect the most people: economics, benefits, job security and investments to build a better future, the Turnbull government has doubled-down on the economic rationalism. (The Labor Party under Shorten, by mostly sticking to economic rationalism-lite, has failed to offer a truly compelling alternatives).

So before today’s election I offer this handy decoded version of Turnbull’s acceptance speech to reveal what he really means:

“This will be a thoroughly NeoLiberal Government. It will be a thoroughly NeoLiberal government committed to freedom, the individual and the converting any  remaining  institutions devoted to the public good over to market-based solutions even in areas where they demonstrably do not work like healthcare, labor markets, carbon emissions regulation and financial regulation. It’ll be focused on ensuring that in the years ahead as the world becomes more and more competitive because we’ve engineered it to be so through deregulation and capital market expansions and flexible labor market policies and there is greater misery opportunities for ordinary people, we are able to the lucky and the wealthy can take advantage of that. The Australia of the future has to be a nation that is agile and jumps when transnational corporate interests want us to jump as specified in “trade” agreements like the TPP, that is innovative in creating wealth for a smaller number of people with fewer stable jobs through more complicated financial services and instruments, that is creative in moving money around but is not creative in challenging corporate interests and we will defund the those in the sciences or arts organizations that do so. We can’t be defensive, we can’t future-proof ourselves by collectively deciding where we allocate our resources democratically. We have to recognise that the disruption that we see driven by technology  neoliberal policies that deliberately transfer wealth up the hierarchy by invoking an outdated notion of  technological determinism to disguise those policies, and that the volatility in change is our friend if we are for those of us who are agile and smart enough to take advantage of it, and we will heap scorn and derision and demonize those who question these policies. There has never been a more exciting time to be alive than today if you’re in the 1% and there has never been a more exciting time to be an Australian in that 1%. We will ensure that all Australians understand that their government recognises the opportunities of the future for its wealthy friends in the corporate class and is putting in place the policies and the plans to enable them to take advantage of it, by privatizing Medicare, deregulating the public university system and introduce US-style student loans and removing people or groups in positions of authority in institutions such as the CSIRO or the ABC that question these policies.

In the Turnbull/Liberal National Party “vision” there is no sense of the common good, of building a democratic future together, of supporting and strengthening civil society, of investing in basic science (outside of narrowly defined biomedical science, funded through cuts to Medicare), or growing sustainable (i.e. non-venture-capital based) small and medium sized businesses that create long term value for Australians. Just every agile man and women for him or herself in the global marketplace.

Get jumping!!

Open Science and Its Discontents

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My first post on the Ronin Institute blog:

Open science has well and truly arrived. Preprints. Research Parasites. Scientific Reproducibility. Citizen science. Mozilla, the producer of the Firefox browser, has started an Open Science initiative. Open science really hit the mainstream in 2016. So what is open science? Depending on who you ask, it simply means more timely and regular releases of data sets, and publication in open-access journals. Others imagine a more radical transformation of science and scholarship and are advocating “open-notebook” science with a continuous public record of scientific work and concomitant release of open data. In this more expansive vision: science will be ultimately transformed from a series of static snapshots represented by papers and grants into a more supple and real-time practice where the production of science involves both professionals and citizen scientists blending, and co-creating a publicly available shared knowledge. Michael Nielsen, author of the 2012 book Reinventing Discovery: The New Era of Networked Science describes open science, less as a set of specific practices, but ultimately as a process to amplify collective intelligence to solve scientific problems more easily:

To amplify collective intelligence, we should scale up collaborations, increasing the cognitive diversity and range of available expertise as much as possible. This broadens the range of problems that can be easy solved … Ideally, the collaboration will achieve designed serendipity, so that a problem that seems hard to the person posing it finds its way to a person with just the right microexpertise to easily solve it.

Read the rest at the Ronin Institute blog

A spring surprise: computational analysis unearths potential prions in plants

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Biosystems Analytics

With warm weather finally kicking in in New England, it was nice to get a Spring surprise in the form of a new paper on prions seeing the light of day.  Prions are particular kind of protein that propagate by imbuing an altered shape, or “confirmation”, on other proteins of the same type.  They essentially act as a kind of protein “zombie”, and there has been some speculation that they may support a kind of “memory function” due to their ability to transmit state across generations.  Prions were first discovered in the context of diseases like scrapie and variant Creutzfeldt–Jakob Disease (vCJD) but have shown up in all kinds of unexpected places, such as yeast and possibly – providing the aforementioned Spring suprise – plants.  Scientific American has a nice blog post on a recently-published study  from the Whitehead Institute, authored by Sohini Chakrabortee, Can Kayatekin, Greg…

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The limitations of Big Data in life science R&D

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Biosystems Analytics

Big Data has become an increasingly large presence in the life science R&D world, but as I have blogged about previously, increasingly larger datasets and better machine algorithms alone, will not leverage that data into bankable knowledge and can lead to erroneous inferences.  My Amber Biology colleague, Gordon Webster has a great post over on LinkedIn leavening the hype around Big Data, pointing out that analytics and visualizations alone are insufficient for making progress in extracting knowledge from biological datasets:

Applying the standard pantheon of data analytics and data visualization techniques to large biological datasets, and expecting to draw some meaningful biological insight from this approach, is like expecting to learn about the life of an Egyptian pharaoh by excavating his tomb with a bulldozer

“-omics” such as those produced by transcriptomic and proteomic analyses are ultimately generated by dynamic processes consisting of individual genes, proteins and other molecules…

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Table of contents preview for Python for the Life Sciences

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Biosystems Analytics

book-coverOur Amber Biology book Python For The Life Sciences is now nearing publication – we anticipate sometime in the early summer of 2016 for the publication date. As requested by many folks we are releasing the first draft of the table of contents.  If you’re interested in updates you can sign up for our book mailing list.  You can also checkout a preview chapter on Leanpub.

Python at the bench:
In which we introduce some Python fundamentals and show you how to ditch those calculators and spreadsheets and let Python relieve the drudgery of basic lab calculations (freeing up more valuable time to drink coffee and play Minecraft)

Building biological sequences:
In which we introduce basic Python string and character handling and demonstrate Python’s innate awesomeness for handling nucleic acid and protein sequences.

Of biomarkers and Bayes:
In which we discuss Bayes’ Theorem and implement it in Python, illustrating in the…

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Where is this cancer moonshot aimed?

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Biosystems Analytics

Much has been made of the recent announcement of VP Biden’s cancer moonshot program.  In these days of ever tightening research funding, every little bit helps, and the research community is obviously grateful for any infusion of funds.   However, large-scale approaches to tackling cancer have been a staple of funding ever since Nixon announced his “War on Cancer” back in the 1970s, and any new approaches must grapple with the often complicated history of research funding in this area.  Ronin Institute Research Scholar, Curt Balch, has a interesting post over on LinkedIn breaking down some of these issues.

What seems relatively new in this iteration of the “war”, however, is a greater awareness of the lack of communication between different approaches to those working on cancer.  Biden has specifically mentioned this need and has pledged to “break down silos and bring all cancer fighters together”.  This…

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Hollywood’s take on Wall Street: The Big Systemic Corruption

Left to right: Steve Carell plays Mark Baum and Ryan Gosling plays Jared Vennett in The Big Short from Paramount Pictures and Regency Enterprises

The Big Short is just about the best film I’ve seen in quite a while. It’s as if Guy Ritchie and Michael Moore took some coke together and decided to make a film about the almost-complete financial meltdown of the world.  Based on Michael Lewis’ 2010 bestseller, it delves deeply into both the mechanics of the crash and the mentality that drove us there.  It doesn’t pander, isn’t emotionally overwrought and gives just about the best explanation that I’ve heard of a synthetic CDO thanks to Selena Gomez and behavioural economist Richard Thaler.

THE BIG SHORT

The casting is spot on with Steve Carrell giving an amazing career-defining performance.  It has a fast-based, but not overly hyper-kinetic style, and is leavened through with a kind of gallows-humour, as expected given director Adam McKay’s background in comedy.  It’s also a film that treats the underlying ideas seriously, but it also never feels too complicated and plot-driven, no mean feat for a director. 

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From The Secret River to Stan Grant’s debate

Secret-River

The current longest non-stop flight in the world is the Qantas route from Sydney to Dallas: 14.5 hours in the air in an Airbus A-380.  A couple of weeks ago I was sitting on  that Airbus flipping through the inflight entertainment system in that semi-catatonic state that all long-haul flights seem to induce, when I stumbled across an intriguingly-titled television series: The Secret River.  It turned out to be a two-part mini-series originally broadcast by the Australian Broadcasting Corporation based on a novel by author Kate Grenville.  The blurb promised an exploration of an emancipated convict in the early days of the colony of New South Wales, carving out a new life on the Hawkesbury River (the Secret River of the title).

I thought to myself, this seem promising, and settled back expecting a mildly diverting period piece about early Australian history that I had never seen dramatized.  I imagined it might be a little dry and slow, but would have great images of the bushland that I was familiar with growing up (the Hawkesbury is just a 20-30 minute drive away from where I grew up), I was interested to see how the producers recreated the early Australian colony, and at the very least it would while away about 3 of the remaining hours until touchdown in Dallas.  Instead I found myself watching a graphic and unsentimental depiction of the often brutal confrontation between the early European settlers and the indigenous people, the Australian Aborigines. Read more

“Adventures in Transcription Factor Networks”: preview chapter from our book

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Biosystems Analytics

As I blogged about previously my Amber Biology colleague, Gordon Webster and I are writing a book Python For The Life Sciences, and today we are releasing a sample chapter.

amazing-adventures In this chapter we show you how to extract and examine data generated from cellular interaction networks, sometimes affectionately known as “hairball” data. In particular, we’ll show  you an example of reading in data on transcription factor networks from yeast. We will take you through the steps of reading in files; creation of set data structures and simple queries.  To give you a flavour, here’s a brief extract from the Chapter (the full sample chapter is available as a PDF download):

A set, as you might recall from distantly remembered introductory maths classes, contains only unique members.  In the context of the data structures for transcription networks, this means for each transcription factor, we only need…

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