```
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import time
import random
print("starting")
start = time.time()
x_data = []
y_data = []
x2_data = []
y2_data = []
x3_data = []
y3_data = []
x4_data = []
y4_data = []
x5_data = []
y5_data = []
x6_data = []
y6_data = []
x7_data = []
y7_data = []
x8_data = []
y8_data = []
x9_data = []
y9_data = []
x10_data = []
y10_data = []
x11_data = []
y11_data = []
fig, ax = plt.subplots()
#ax.set_xlim(-10000, 10000)
#ax.set_ylim(-10000, 10000)
line, = ax.plot(0,0)
line2, = ax.plot(0,0)
line3, = ax.plot(0,0)
line4, = ax.plot(0,0)
line5, = ax.plot(0,0)
line6, = ax.plot(0,0)
line7, = ax.plot(0,0)
line8, = ax.plot(0,0)
line9, = ax.plot(0,0)
line10, = ax.plot(0,0)
line11, = ax.plot(0,0)
r=1.2
r2=1.5
r3=1.5
count=1
count2=0
count3=0
def animation_frame(i):
print(i)
print(np.sin(i))
x=round(i/30)+0.02
x2=round(x/30)+0.1
y_data.append(abs((x+50)/120*np.sin(i*np.pi/15)))
x_data.append(-(x+50)/300*(np.sin(i*np.pi/15/2)*np.sin(i*np.pi/15)+3*np.sin(i*np.pi/15/2)))
x2_data.append(x/100*np.sin(i*np.pi/30))
y2_data.append(-0.5+x/100*np.cos(i*np.pi/30))
x5_data.append(0.35+x/1200*np.sin(i*np.pi/30))
y5_data.append(x/1200*np.cos(i*np.pi/30))
x6_data.append(-0.35-x/1200*np.sin(i*np.pi/30))
y6_data.append(-x/1200*np.cos(i*np.pi/30))
y7_data.append(-1.5+abs(x/250*np.sin(i*np.pi/15)))
x7_data.append(0.8-x/1000*(np.sin(i*np.pi/15/2)*np.sin(i*np.pi/15)+3*np.sin(i*np.pi/30/2)))
y8_data.append(-1.5+abs(x/250*np.sin(i*np.pi/15)))
x8_data.append(-0.8+x/1000*(np.sin(i*np.pi/15/2)*np.sin(i*np.pi/15)+3*np.sin(i*np.pi/30/2)))
#y4_data.append(x/60*np.cos(i*np.pi/30))
#x4_data.append(x/200*(np.cos(i*np.pi/30/2)*np.cos(i*np.pi/30)))
#x3_data.append(x/220*np.sin(i*np.pi/30))
#y3_data.append(-0.5-abs(x/70*(np.sin(i*np.pi/30)*np.sin(i*np.pi/30))))
#x4_data.append(x/125*np.sin(i*np.pi/30))
#y4_data.append(-0.3-abs(x/105*(np.sin(i*np.pi/30)*np.sin(i*np.pi/30))))
x9_data.append(x/500*np.sin(i*np.pi/30))
y9_data.append(-1+abs(x/800*(np.sin(i*np.pi/30)*np.sin(i*np.pi/30))))
##LIGHTNINGBOLT
#x10_data.append(x/100-x2)
#y10_data.append(x/100+
##WHISKERS
#x10_data.append(0.05+(x2/200*30*(np.sin(i*np.pi/30)*np.sin(i*np.pi/30))))
#y10_data.append(-0.7+x2/1000*30*np.sin(i*np.pi/30))
#x11_data.append(-0.05-(x2/200*30*(np.sin(i*np.pi/30)*np.sin(i*np.pi/30))))
#y11_data.append(-0.7+x2/1000*30*np.sin(i*np.pi/30))
#x4_data.append((x/1000*np.cos(i))+2)
#y4_data.append((x/1000*np.sin(i))-1.5)
##Loveheart nose
y10_data.append(-0.5+x/800*np.sin(i*np.pi/30))
x10_data.append(x/1500*(np.sin(i*np.pi/30/2)*np.sin(i*np.pi/30)+np.sin(i*np.pi/60)))
line.set_xdata(x2_data)
line.set_ydata(y2_data)
line2.set_xdata(x_data)
line2.set_ydata(y_data)
line3.set_xdata(x3_data)
line3.set_ydata(y3_data)
line4.set_xdata(x4_data)
line4.set_ydata(y4_data)
line5.set_xdata(x5_data)
line5.set_ydata(y5_data)
line6.set_xdata(x6_data)
line6.set_ydata(y6_data)
line7.set_xdata(x7_data)
line7.set_ydata(y7_data)
line8.set_xdata(x8_data)
line8.set_ydata(y8_data)
line9.set_xdata(x9_data)
line9.set_ydata(y9_data)
line10.set_xdata(x10_data)
line10.set_ydata(y10_data)
line11.set_xdata(x11_data)
line11.set_ydata(y11_data)
ax.set_xlim(-2,2)
ax.set_ylim(-1.5,1.5)
line2.set_linewidth(3)
line10.set_linewidth(0.5)
line10.set_linewidth(0.5)
line2.set_color('saddlebrown')
line.set_color('chocolate')
line3.set_color('chocolate')
line4.set_color('chocolate')
line5.set_color('black')
line6.set_color('black')
line7.set_color('saddlebrown')
line8.set_color('saddlebrown')
line9.set_color('black')
line10.set_color('black')
line11.set_color('black')
return line, line3, line4, line2, line5, line6, line7, line8, line9, line10, line11
z_data = []
#counter=2000*np.pi
counter=0
#counter=1000*np.pi
for z in range(1, round(5000*np.pi)):
counter=counter+1
z_data.append(counter)
animation = FuncAnimation(fig, func=animation_frame, frames=z_data, interval=60, blit=True)
animation.save('puppy2.mp4', dpi=500, bitrate=-1, codec="libx264", extra_args=['-pix_fmt','yuv420p'])
#plt.show()
end = time.time()
print(end - start)
#print("done", "frame=",animation.frame_seq)
```

# Month: August 2020

I am joined by Dr. Sarah Pearson, the current Deputy Director-General for Innovation at Advance Queensland. We discuss Sarah’s career that started in Particle Physics but has since included, cancer research, Cadbury confectionary, and the Department of Foreign Affairs and Trade (DFAT), with a huge focus on collaborative innovation.

Sarah’s LinkedIn https://www.linkedin.com/in/sarahpearsoninnovation

Sarah’s Twitter https://twitter.com/InnovationSarah

Advance Queensland Website https://advance.qld.gov.au/

Timestamps:

00:01:14 – Sarah’s current work at Advance Queensland

00:02:14 – Innovation out of COVID-19

00:03:40 – The ups and downs of Sarah’s Oxford PhD

00:09:00 – Careers Highlights

00:11:17 – Moving to Australia

00:11:47 – Working at McKinsey

00:12:52 – Becoming a parent – refocusing priorities

00:14:40 – Moving to Armidale – moving back into Physics and restructuring

00:16:36 – Breast Cancer research

00:18:23 – Outreach programs to get young people, especially women into STEM

00:19:18 – Open Innovation at Cadbury

00:22:33 – Back to Australia – struggled for a bit

00:23:08 – CEO at ANU Enterprise + Night jobs like the Scaling Frontier Innovation Program

00:26:54 – Canberra Innovation Network – company to build an ecosystem. Mass collaboration.

00:28:33 – Brief UoN stint

00:28:37 – Chief Innovation Officer at DFAT

00:30:29 – Head of Innovation Queensland

00:30:44 – Work-life balance

00:32:11 – Important Networks and influential people

00:36:10 – Childhood impacts on career. Moving around a lot.

00:38:37 – Merging innovation with encouraging women in STEM

00:43:14 – How to build inclusive new economies?

00:44:07 – How will innovation change the future?

Intro Music by Supakarn Nakavisuit (https://bit.ly/33ZtIh8)

Outro Music by Kasimir Gregory

SMArt – “Puppy” by Kasimir Gregory

Podcast: Play in new window | Download

## E2C – Butterflying

I’ve decided to leave some of the messiness in – turns out this one is reasonably clean – but some of the upcoming codes are a little messier.

```
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import time
import random
print("starting")
start = time.time()
x_data = []
y_data = []
x2_data = []
y2_data = []
x3_data = []
y3_data = []
x4_data = []
y4_data = []
fig, ax = plt.subplots()
#ax.set_xlim(-10000, 10000)
#ax.set_ylim(-10000, 10000)
line, = ax.plot(0,0)
line2, = ax.plot(0,0)
line3, = ax.plot(0,0)
line4, = ax.plot(0,0)
r=1.2
r2=1.5
r3=1.5
count=1
count2=0
count3=0
def animation_frame(i):
print(i)
print(np.sin(i))
x=round(i/30)+0.1
y4_data.append(x/120*np.sin(i*np.pi/30))
x4_data.append(x/100*(np.sin(i*np.pi/30/2)*np.sin(i*np.pi/30)))
x2_data.append(x/100*np.sin(i*np.pi/30))
y2_data.append(x/100*(np.sin(i*np.pi/30/2)*np.sin(i*np.pi/30))+0.02)
y_data.append(x/200*np.cos(i*np.pi/30))
x_data.append(x/300*(np.cos(i*np.pi/30/2)*np.cos(i*np.pi/30)))
x3_data.append(x/1000*np.sin(i*np.pi/30))
y3_data.append(abs(x/150*(np.sin(i*np.pi/30)*np.sin(i*np.pi/30))))
#x4_data.append((x/1000*np.cos(i))+2)
#y4_data.append((x/1000*np.sin(i))-1.5)
line.set_xdata(x_data)
line.set_ydata(y_data)
line2.set_xdata(x2_data)
line2.set_ydata(y2_data)
line3.set_xdata(x3_data)
line3.set_ydata(y3_data)
line4.set_xdata(x4_data)
line4.set_ydata(y4_data)
ax.set_xlim(-0.4,0.4)
ax.set_ylim(-0.4,0.4)
line.set_linewidth(1)
line2.set_linewidth(5)
line3.set_linewidth(0.5)
line4.set_linewidth(3)
line4.set_color('orange')
line2.set_color('purple')
line3.set_color('black')
line.set_color('black')
return line4, line, line2, line3
z_data = []
#counter=2000*np.pi
#counter=-300*np.pi
counter=0
for z in range(1, 10000):
if counter < 10000:
counter=counter+0.1
#else:
# counter=counter - 300*np.pi
z_data.append(counter)
animation = FuncAnimation(fig, func=animation_frame, frames=z_data, interval=60, blit=True)
animation.save('Butterfly2.mp4', dpi=500, bitrate=-1, codec="libx264", extra_args=['-pix_fmt','yuv420p'])
#plt.show()
end = time.time()
print(end - start)
#print("done", "frame=",animation.frame_seq)
```

Brent and I discuss the future of Universities, the importance of soft networks and clusters of competence, creativity and the 6 thinking hats. New music in the introduction by Supakarn Nakavisut (@BARE MUSIC – https://bit.ly/33ZtIh8)

00:00:43 – Intro (Music by Supakarn Nakavisut)

00:01:25 – Specialising/decentralising Universities?

00:04:45 – Future of Universities

00:08:10 – Purpose built cities/communities

00:13:08 – Implementing the change despite pushback? Improving quality of life.

00:19:15 – Importance of teams and networks

00:23:58 – What recruiters say about networking skills

00:27:50 – Work hrs vs pay research (correlations)

00:32:01 – The 7 Habits of Highly Effective People

00:33:20 – Six Thinking Hats

00:37:35 – Creativity and Innovation – “The literature of life is something we shouldn’t devalue”

00:45:22 – Accelerated Learning

00:48:31 – Tools and Drills for creativity?

00:50:52 – Clusters of Competence

00:53:43 – The impact of the coffee shop

00:54:25 – The Manhattan Project (20 Nobel Laureates)

00:55:14 – Gambling with Maths cluster; Silicon Valley; Musical crossovers

01:00:02 – What is the causal factor? What aren’t we measuring?

01:02:00 – Accounting is about making things visible

01:05:40 – Find Brent at ResearchGate https://www.researchgate.net/profile/Brent_Gregory

Intro Music by Supakarn Nakavisut (https://kaensupakarn.wixsite.com/bare-music/music)

Outro music by Kasimir Gregory

Podcast: Play in new window | Download

## E2B – Time To Unwind

```
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import time
print("starting")
start = time.time()
x_data = []
y_data = []
x2_data = []
y2_data = []
x3_data = []
y3_data = []
fig, ax = plt.subplots()
line, = ax.plot(0,0)
line2, = ax.plot(0,0)
line3, = ax.plot(0,0)
r=1
r2=1.2
r3=1.5
def animation_frame(i):
print(i)
x=round(i+1)
r2=r*(x+1)
if (((x+1) % 3 == 0)):
x2_data.append(x*r2*np.cos(i))
y2_data.append(x*r2*np.sin(i))
elif ((x % 3 == 0)):
x_data.append((x*r2*np.cos(i)))
y_data.append((x*r2*np.sin(i)))
else:
x3_data.append((x*r2*np.cos(i)))
y3_data.append((x*r2*np.sin(i)))
line.set_xdata(x_data)
line.set_ydata(y_data)
line2.set_xdata(x2_data)
line2.set_ydata(y2_data)
line3.set_xdata(x3_data)
line3.set_ydata(y3_data)
line.set_linewidth(1)
line2.set_linewidth(0.3)
line3.set_linewidth(0.3)
ax.set_xlim(-(i+1)*(i+1),(i+1)*(i+1))
ax.set_ylim(-(i+1)*(i+1),(i+1)*(i+1))
line.set_color('orange')
line2.set_color('purple')
line3.set_color('green')
return line, line2, line3
z_data = []
count=0
for z in range(1, 4000):
count=(count+z)/3
z_data.append(count)
animation = FuncAnimation(fig, func=animation_frame, frames=z_data, interval=10, blit=True)
animation.save('TimeToUnwind.mp4', dpi=500, bitrate=-1, codec="libx264", extra_args=['-pix_fmt','yuv420p'])
#plt.show()
end = time.time()
print(end - start)
```

Brent and I discuss Accounting and its role in society, touching on COVID-19. We than walk through his career, with a slight divergence to discuss the Earle Page College Coast Run, that has now was over half a million dollars for the Children’s Medical Research Institute (CMRI).

00:00:45 – What inspired a career in Accounting?

00:07:00 – Impact of COVID-19 on our Economy. Are we valuing the right things?

00:18:15 – Accounting research – Sustainability.

00:27:20 – Researching student outcomes – a holistic approach.

00:32:10 – “Student DNA”

00:35:35 – Career – Postmaster General – Things learnt on the job.

00:55:02 – Starting a movement – The Earle Page College Coast Run

01:10:17 – Post-Sydney/Uni Career – Applied research

01:16:35 – Time off – working online

01:18:05 – The inspiration to become an Academic

01:19:15 – PhD idea “How the Capitalist system is failing society” – Why this PhD got stopped – “Elephant in the (University) room”

01:21:45 – Research for the students. Applied research in teaching.

01:23:54 – The RENT model – Recording, Environment, Needs, Teams

01:28:25 – Scalable “personalisation” of teaching.

01:30:00 – Next episode information

SMArt – “Time to Unwind” by Kasimir Gregory

Podcast: Play in new window | Download

## 3 – Distracted

I’ve found myself easily distracted as of late. Jumping on and off my phone. Scrolling social media mindlessly. A rapid succession, from one app to the next. Indecisiveness when choosing a leisure activity. Living in a state of hyperstimulation. Almost missing the privilege of boredom over the burden of infinite choice.

This perhaps came to a tipping point last night when I felt all too aware of my unsocial behaviour in the lounge room when a group of us were hanging out. I wasn’t quite present. It was enough of a self-realisation to do something about it.

I’ve been meaning to reignite my meditation habit. I’ve been suffering from a case of “but will it really make me feel any better”. Despite a great track record of it making me feel better, I somehow often manage to convince myself that it’s more effort than it’s worth. This same dilemma can appear in multiple facets of my life – exercise, diet, outdoors.

The one place I haven’t quite found that to be true, has been sleep. I know it should, and perhaps I just haven’t built the habits, but I can feel worse after 8+hrs than 5. I need to note – I’m basically always tired. I am most probably suffering from a mild form of sleep apnea due to a deviated septum and swollen turbinates. It is almost like always having a mildly blocked nose; breathing through a valve. Another way I’d describe breathing through my nose oftentimes is like this:

- Place a hand over your mouth, with no space between your fingers.
- Now let just enough air in through the gaps so you can breath, but not comfortably.

You can survive, but its not comfortable and not particularly relaxing. There is also a bit of day to day variability – similar to the different pressures that you might use with your hand in the above exercise.

Now, thankfully I can also breath through my mouth. I’m often a mouth breather. Yet, I daresay my quality of life is somewhat depleted by this and its affect on my sleep. Thankfully, I should be getting it fixed in a month and a half – so I’ll keep you posted for updates on that matter.

Anyway, that distraction to talk about sleep instead of distractions was relevant to my point about distractions. I find that when I am more tired I am also more easily distracted and less motivated. Basically every basic task feels harder.

This is where my meditation comes into play. I think the effects of poor sleep can snowball these mindless habits. However, I believe I can combat that with meditation. The act of mindfulness to sharpen the skill of focus. To ask myself, before I pick up my phone, the simple question. Why?

This simple question might be enough to realise I don’t have an answer. It was a habitual act. Yet, it doesn’t limit when there is an answer – “I need to call my parents.”, “I want to do my daily Japanese lesson.” and even “I have worked hard this morning – I have 5min still till my next meeting – I’ll see what’s going on in the news or stock market.”

I want to strive to do a meditation each day of August – I feel this is a good timestamp to get an idea as to where my heads at, so I can compare in a month. I started using the app “Waking Up” last night – so far I’m really liking it. I was previously using “Smiling Mind” – but I think I had just become too used to the 15min meditation that it was easier to tune out – and therefore felt less effective in helping guide me through a session.

Today I went orienteering. I drove the 30min there and back with no radio or music, and of course had nothing but a map for the 75min run. There is something incredibly freeing about it being just you and your thoughts. The mono-tasking felt good. I didn’t get bored in the absence of the stereo. I think I actually just found myself noticing more about my surroundings.

When I got home I had a shower and nap. Then I watch Vikings for a few episodes – I treated myself to relax. What was different to a lot of the time when I am watching TV, was I didn’t do anything else – except rehydrate. I focused on the show – and enjoyed it more. No computer. No phone. Just me, some water and the TV. Perhaps, counterproductive to limiting hyperstimulation, but I enjoyed my Sunday and taught myself a little about just enjoying what I’m doing.

Hopefully, I can write a piece in September called “Focused”. I’m looking forward to this self-experimental training block of using meditation as my “focus weights”, with “Waking Up – Sam Harris” as my coach.

Keep Anion The Future.