While the site currently serves as a base of information, it could be much more than that. It could be a portal that facilitates interaction between EDP and other organizations on the local, national and international scales. Embedding some sort of interactive feature like tuning into a live-streaming radio signal or video chat could enhance the product and build the conversation going forward. The site could also provide more links to other sustainability initiatives or open-source hubs so that access to these resources is available to anyone that visits the site. We could also include fully translated versions of every page in multiple languages to increase accessibility.
This film was incredibly powerful. The way they exposed not only the vicious practices, but also the ways in which proponents of dolphin fishing lied about it or rationalized it. The most powerful moment for me was when the documentarian was showing these people the footage right after they had denied using the methods shown in the video. Having a camera on him and seeing his reaction was priceless, and that human element really sealed the deal for me. The decision to film in cinema-quality fidelity was incredibly ambitious and the fact that they pulled it off made it that much more amazing. This was truly one of the most effective documentaries I’ve seen. It fully fleshed out the problem, identified the players involved and actually made an impact on their lives instead of just the viewers.
Another fine documentary because of its ability to include both cinema-quality imagery and the all important emotional human element. This started as a story of one man’s problems with fracking in his home state, but quickly grew to being the vehicle for many other peoples’ stories who may have had it way worse. The characters he met along the way really enriched my interest in this problem. I was aware of fracking and some of it’s negative effects before this, but viewing the documentary really made me care about the people who it affects. The juxtaposition of stunning visual imagery with homemade, handheld live footage really gave this film an enhanced sense of credibility. It gave you the sense that the guy filming could have literally been any of us sitting in the room watching, and that was inspiring. The medium is the message in this case. It provoked thoughts about activism in general, not just anti-fracking activism.
The DU Earth Month Farmer’s Market is a great local sustainability initiative that has been going on for the past three years. They were very successful with their event on May 21 at Driscoll Green. I attended and saw that they were working with several sustainable local businesses that endorsed policies of organic, locally-sourced foods. There was also an open market feeling that just spoke to the social justice and equity side of sustainability. I think initiatives like this that center around college campuses are extremely important because that age group of people is the next group of major influencers in our community at large. Also being at an institution of higher education affords this group skills, connections and prestige which then gives them more influence than people who do not have that opportunity. This is why this group is crucial to gaining support for sustainability in general.
DU Solar is a student-run initiative to engineer cultural change on DU’s campus towards a more progressive, sustainable mindset by bringing solar panels to campus. Solar energy is a clearly identifiable sustainable practice. By having such a highly visible example of sustainability, the hope is that students may recognize their community’s involvement and become more involved themselves, or at least see a shift in thinking towards a more progressive, sustainable mindset. I facilitated a cross-pollination of ideas between DU Solar and GreenEDP by having DU Solar president Kyle Sundman meet with Tim Weaver’s Spring 2015 Sustainable Design class, which kickstarted an evaluation of Shwayder Art Building for solar retrofitting.
Transcoding and Protein Music
Partners: Gus Kitchell & Charles Elmer
This project was our first stab at transcoding – converting one source of information into another format. In this case, we converted biological information (the amino acid sequence of a protein) into an auditory output. The specific protein we chose was the ZENK protein (also known as the Early Growth Response Protein 1, or EGRP1) found in the forebrain of the Zebra Finch (Figure 1), a species that has been studied extensively and for which a great deal of genetic information is available. The ZENK protein is involved in vocal communication, and studies have suggested that its production may be triggered when songbirds hear the songs of other individuals of the same species (Mello and Ribeiro, 1998). For this reason, we saw a parallel between the function of the ZENK protein and the goal of our project.
Converting biological concepts or transcoding biological information into music has been done by a variety of artists – we are certainly not the first to take on this project. However, we feel that the music produced by these projects tends to be rather abstract and cacophonous. Perhaps this should not be a surprise; there is no inherent reason that a sequence of amino acids should magically transform into a chart-topping pot hit. However, Charles and I were still very interested in the idea of protein music, and thought that it might be beneficial to produce a musical piece that is more accessible for modern listeners. In short, we wanted to create something that sounds more like a popular song that you might hear on the radio, while still using biological information as the foundation of our project. Our reasoning was fairly simple: although we were intrigued by the dissonant music produced by past transcoding artists, we found it hard to understand. For the average listener, it can be hard to understand the connection between the dissonant sounds and their biological source material. As a result, they may feel overwhelmed and ultimately uninterested. It is hard to interact with something which you don’t understand. Thus, we sought to produce music that would be more familiar to the average listener, and might spur them to ask questions. What protein sequence did you use to create the bass-line? How can the same sequence be used to create a guitar melody and a drum solo? How is it possible to convert a protein sequence into a catchy song? While these questions still show a general lack of understanding from the listener, we hope that they can at least conceptualize what they are listening to. If we have done our job well (that is, produced a catchy tune), we hope that it will prompt more listeners to engage with the idea of transcoding and protein music. Thus, the ZENK protein, which is involved in vocal communication in the Zebra Finch, seemed like a particularly suitable foundation for our project, which attempts to communicate the concept of protein music to a general audience.
We began by downloading the amino acid sequence for the ZENK protein, found on the RCSB Protein Data Bank.
CDRRFSRSDE LTRHIRIHTG QKPFQCRICM RNFSRSDHLT THIRTHTGEK PFACDICGRK FARSDERKRH TKIHLRQKDK KVEKAAPAST ASPIPAYSSS VTTSYPSSIT TTYPSPVRTA YSSPAPSSYP SPVHTTFPSP SIATTYPSGT ATFQTQVATS FSSPGVANNF SSQVTSALSD INSAFSPRTI EIC
The sequence is listed in the conventional amino acid “single letter code,” which is listed below.
Single Letter Code
- G – Glycine (Gly)
- P – Proline (Pro)
- A – Alanine (Ala)
- V – Valine (Val)
- L – Leucine (Leu)
- I – Isoleucine (Ile)
- M – Methionine (Met)
- C – Cysteine (Cys)
- F – Phenylalanine (Phe)
- Y – Tyrosine (Tyr)
- W – Tryptophan (Trp)
- H – Histidine (His)
- K – Lysine (Lys)
- R – Arginine (Arg)
- Q – Glutamine (Gln)
- N – Asparagine (Asn)
- E – Glutamic Acid (Glu)
- D – Aspartic Acid (Asp)
- S – Serine (Ser)
- T – Threonine (Thr)
We then ran the amino acid sequence through a MIDI note converted created in MAX by our professor, Tim Weaver. This program reads the single letter code of the amino acid sequence and converts each letter into a MIDI note. Factors such as the volume, duration, note range, and instrument type can all be altered in the MAX patch, shown in the screenshot below. In order to create a melody that sounds more similar to a pop song, we converted each amino acid into a note within a G pentatonic scale. MIDI operates in a 127 note chromatic scale, meaning a random assortment of notes tends to sound a-melodic. Thus, we only assigned amino acids to MIDI notes that fall within a G pentatonic scale. This required us to look up the MIDI note conversion chart (Figure 3).
Figure 3. MIDI note conversion chart.
As noted above, we assigned each amino acid in the ZENK sequence to a note that falls within the G pentatonic scale (G, A, B, D, E, G), beginning with a 2nd octave G (MIDI note #55). The result was a text sequence that looks like the one shown below.
However, due to the arrangement of the amino acid sequence, this note assignment still produced consecutive notes that were multiple octaves apart, creating a jumpy and disconnected tune. To correct this, we took a simple shortcut, assigning the same set of notes to multiple amino acids. We selected a single octave, from G to G (#55 to #67), and created the text file shown below.
Once our notes had been restricted to a single octave (minimizing the large jumps between consecutive notes), we played the protein sequence and recorded the output in the music-editing program Logic. This allowed us to arpeggiate notes and add a variety of other effects in order to create a more modern sound. We repeated this process using multiple different instrument sounds, then overlaid each track to create a song that involved drums, bass, guitar, and synth, in a variety of octaves and tempos.
This is the song we put together, titled Zenk Pop: https://soundcloud.com/charles-elmer/zenk-pop
Overall, we found this project to be both difficult and enjoyable. Creating a pop song prom a protein sequence is not an easy process. While our first attempt may not be a #1 hit, we think it is a decent first demonstration of the overlap between protein sequences and popular music, and hope that it will generate new interest in transcoding and protein music.
We did a few mockups of what SAB could look like with solar panels on it in order to get thinking creatively about that possibility. In the first photo, panels have covered the back side of the building, which faces the sun most of the day. There are rechargeable moped stations, as mopeds are a popular method of transportation for students. If these stations were more available on campus, students may be more inclined the purchase a moped to commute instead of a car because of the immense money-saving benefit of solar powered electric vehicles. In the second image, sun-tracking solar panels adorn the south-facing side of the building so they can get the most out of their position and also provide shade below. These solar awnings would also bring more attention to SAB and possibly more prestige to EDP and the art department.
Amino Acid Sequences
Single Letter Code
• G – Glycine (Gly)
• P – Proline (Pro)
• A – Alanine (Ala)
• V – Valine (Val)
• L – Leucine (Leu)
• I – Isoleucine (Ile)
• M – Methionine (Met)
• C – Cysteine (Cys)
• F – Phenylalanine (Phe)
• Y – Tyrosine (Tyr)
• W – Tryptophan (Trp)
• H – Histidine (His)
• K – Lysine (Lys)
• R – Arginine (Arg)
• Q – Glutamine (Gln)
• N – Asparagine (Asn)
• E – Glutamic Acid (Glu)
• D – Aspartic Acid (Asp)
• S – Serine (Ser)
• T – Threonine (Thr)
ZENK protein (Zebra Finch) — Other Gene names: Early Growth
Response protein 1 ZENK
CDRRFSRSDE LTRHIRIHTG QKPFQCRICM RNFSRSDHLT THIRTHTGEK
PFACDICGRK FARSDERKRH TKIHLRQKDK KVEKAAPAST ASPIPAYSSS
VTTSYPSSIT TTYPSPVRTA YSSPAPSSYP SPVHTTFPSP SIATTYPSGT
ATFQTQVATS FSSPGVANNF SSQVTSALSD INSAFSPRTI EIC
When songbirds hear the song of another individual of the same species or
when they sing, the mRNA levels of the ZENK gene increase rapidly in
forebrain areas involved in vocal communication. This gene induction is
thought to be related to long-term neuronal change and possibly the
formation of song-related memories.
A protein that helps with vocal communication and the formation of
auditory memory. This protein helps in vocal communication, and we’re
trying to use it to aid in the communication of biomedia/transcoding to a
Zenk Protein (Humans)
MAAAKAEMQL MSPLQISDPF GSFPHSPTMD NYPKLEEMML LSNGAPQFLG
AAGAPEGSGS NSSSSSSGGG GGGGGGSNSS SSSSTFNPQA DTGEQPYEHL
TAESFPDISL NNEKVLVETS YPSQTTRLPP ITYTGRFSLE PAPNSGNTLW
PEPLFSLVSG LVSMTNPPAS SSSAPSPAAS SASASQSPPL SCAVPSNDSS
PIYSAAPTFP TPNTDIFPEP QSQAFPGSAG TALQYPPPAY PAAKGGFQVP
MIPDYLFPQQ QGDLGLGTPD QKPFQGLESR TQQPSLTPLS TIKAFATQSG
SQDLKALNTS YQSQLIKPSR MRKYPNRPSK TPPHERPYAC PVESCDRRFS
RSDELTRHIR IHTGQKPFQC RICMRNFSRS DHLTTHIRTH TGEKPFACDI
CGRKFARSDE RKRHTKIHLR QKDKKADKSV VASSATSSLS SYPSPVATSY
PSPVTTSYPS PATTSYPSPV PTSFSSPGSS TYPSPVHSGF PSPSVATTYS
SVPPAFPAQV SSFPSSAVTN SFSASTGLSD MTATFSPRTI EIC
ZENK protein sequence: each amino acid is assigned a
single letter code.
o We run sequence through Tim’s Amino Acid MIDI
o We can explore altering the conversion from a
Explore using granular synthesis on the song of the
Zebra Finch as a new instrument
Make sure to include the pictures of the birds as a
Copy multiple patches to use multiple instruments
o Maybe put drums at half speed of melody
note conversion patch
one-note to a scalar method
I provided the original concept of sensing muscle impulses and using a drum beat to control a robot, which was then expanded on with Gus and Ross’ combined knowledge into what our final project became. I also helped with testing of the impulses and drum hits, created the visualization of our system that is on the documentation page, and provided drumsticks and pads to use for our final presentation/performance.
The key biological component of this project consisted of electromyography, which measures the electric potential associated with muscle activity. We began by testing a muscle sensor (Muscle Sensor v3, available on Sparkfun: https://www.sparkfun.com/products/13027), adjusting the positioning of the sensor pads and the sensitivity of the board until we settled on a combination that produced a consistent and controlled output. Given that our demonstration utilized drumming as the means to control the hexbot, we experimented with multiple muscle groups that are active during a drummer’s motion, ultimately targeting the Brachioradialis muscle on the inner forearm.
To convert the muscle impulses into directions for the hexbot, we downloaded an example Arduino code and hacked it to fit the needs of our project. This involved setting a threshold voltage to initiate the command for forward movement and adjusting the regularity of the signal so that the hexbot would respond to muscle activity with minimal lag between the signal and the action. Thus, the regularity of the signal had to be frequent enough that the hexbot could respond to multiple commands made in quick succession (or stop moving shortly after the last command was issued), but with enough space between signals for the mechanical aspects of the hexbot to register and respond to each signal.
Signals were transmitted to the hexbot via the hexbot remote, which we wired to the output ports of the Arduino board. This required a wires to be soldered to the contacts for each command on the remote, allowing the outgoing signals from the Arduino board to be transmitted through the remote’s LED transmitter. Thus, while the remote was still functional, we simply used it as a “transmitting tower.” When the incoming signals from the muscle sensor reached the required threshold, an outgoing signal was sent through the remote to command to hexbot to move forward.
Side-to-side motion was controlled by the vibrations created by drumming. In this case, we placed a piezo element (https://www.sparkfun.com/products/10293) between two notebooks (acting as our drum pad), and wired it to the Arduino board. Vibrations registered by the piezo element were transcoded into a signal that commanded the the hexbot to turn right. While we had hoped to have one piezo element for right turns and another for left turns, we were only able to use one successfully, resulting in a hexbot that only turned right. Again, the outgoing signal created by the Arduino board was wired directly to the “right” command on the hexbot remote, such that any vibrations that passed the command threshold caused to hexbot to turn right.
We used a breadboard to facilitate the wiring involved in this project, connecting the muscle sensor to its batteries, as well as the piezo element and the Arduino board. A basic summary of the wiring for the muscle sensor can be seen in the figure below.
With this project, we aim to create an interactive experience that is both fun and thought provoking. Muscle impulses from the drummer inspire the hexbot to move forward, while hits registered from the sticks influence the direction it travels in. People are moved in many ways by music, whether physically or emotionally, or both. To view the hexbots moved by the biosensed impulses of a drummer’s arm and see it dance to the rhythm is to reimagine our understanding of music. We can become the influencer and the observer- and yet still partake in the experience.
This technology could also be viewed as a way to create a multimedia art piece. While we chose to have our muscle imposes control the movement hexbot, these impulses could be transcoded into a wide array of other formats to create a visual output. So, with muscle sensors hooked up to a drummer (as they are in this demonstration), the muscle impulses involved in the drumming process could be converted into an accompanying visual output that is intrinsically tied to the audio output. Thus, a dynamic multimedia piece is born, creating a bi-sensory experience for the audience. By presenting the muscle impulses of a drummer in a visual format, the audience can suddenly experience and appreciate the skill of the drummer (typically evaluated as an auditory output) in a whole new medium, potentially expanding their enjoyment and understanding of the performance. In addition, this concept could expand far beyond drumming. For example, this technology could be used to convert the muscle impulses from a soccer player’s calf, a weightlifter’s biceps, or an orchestra conductor’s forearm into a musical number, a visual display, or a tactile experience.
1. use a MindWave to capture brain waves while playing different styles of drum beats (switching between rock, funk, hip hop, reggae, jazz, etc.) which is sent to an output that draws in some way. The waves could be controlling biorobots with ballpoint pen tips facing downward while they slide across a piece of paper. a listener could also have the same set up, measuring how the brain waves respond to hearing different styles rather than playing them.
2. hexbots could be reacting to infrared pylons in their environment while acting on the “consciousness” created by data fed from someone playing drums. the input could be electrical muscle impulses, changing the speed of the hexbot with the speed of the drummer. it could also react to brainwaves changing over time as the drummer switches between genres, rhythms, or tempos.
3. hexbots equipped with light sensors could be programmed to chase light, simulating naturally light sensing plants that need sunlight.