Post-Brexit: out of the ashes, a Kingdom of Londinium?

badge - county of londonPost-Brexit, could London become a separate kingdom within the United Kingdom?

londiniumThe UK and its federated daughter states – former colonies such as Australia and Canada – may not be much different. Canada is a collection of independent provinces, each with its own powers, conjoined as a federation for shared purpose.

The UK is a united kingdom of different kingdoms.

With mechanisms, for centuries, to add or remove territories, change the laws, and change common custom.

Could some of the United Kingdom’s constituent kingdoms stay in the EU, and some parts leave, without damage to the unified UK?

Could the capital of England move back to Winchester? or go Birmingham? or to England’s geographic centre? Even as the Parliament of Great Britain and office of Prime Minister continues in London?

Precedents: coats-of-arms-image



Coat of Arms of the London County Council: By Notscott ((Source: R. Crosley, London’s Coats of Arms (1928)) [Public domain], via Wikimedia Commons:
Seal of the Brussels Capital-Region: By SVG by SiBr4 [Public domain], via Wikimedia Commons:
Seal of the District of Columbia: By District of Columbia –, Public Domain,
Coat of Arms of Berlin: Ottfried Neubecker (1908–1992), [Public domain] via Wikimedia Commons:
Coat of Arms of Lübeck: By SVG by David Liuzzo [Public domain], via Wikimedia Commons:

Parasuits – uplifting humanity, uplifting industry

Parasuit R&D – a competitive edge?


The amazingly good CSS 3D Solar System coding at is by@JulianGarnier. Click the picture to see the code in action! Use the controls at right to change display options.

When reading about IIT Madras graduate Naga Naresh Karutura, I do not see a “double amputee”. Instead, high potential to be an ISRO astronaut flight specialist candidate.

naresh-karutura-parasuit* Software engineer at Alphabet (aka Google).
* Professional problem-solver.
* Eternally dogged optimist.
* Amputean°

In micro-gravity, Parasuit°-enabled Amputean° and Paraplegian° Astronauts may have the competitive edge. Industries and cultures embracing the perspective shift gain competitive edge, too.

parasuits - enabling r&d

° I’ve coined these words, having noticed they somehow convey a sense of uplifting. Everyone needs an uplift, now and then.

Images: image by Julian Gardner: – The basis of this proposal of mine from 1993/4? NEO delta-V is a technically and profitably-usable resource.

Constellation EVA Spacesuit: NASA:
(Image modified with removal of lower extremities)

Mr. Naga Naresh Karutura:

Astronaut Double Amputeans and Paraplegians?

It’s all about perspective.

And tenacity.

And determination.

And character.

tom-reaching-for-lab-umbilicals-sts098-330-0071After NASA Astronaut Scott Kelly and Russian cosmonaut Mikhail Kornienko of Roscosmos got home from a year in space this past spring, the US Congress began examining whether to provide lifetime health benefits to astronauts. Many are ex-military and get benefits that way. NASA will monitor recipients for long-duration mission health planning.
At industrial design school, one of my human factors projects was a spider-like astrogeology exoskeleton, designed so geologists could move along a cliff face looking at strata. And the thinking fed into iteration #1 of my design thesis: one of the first social web wearables; a performance tool for whitewater slalom athletes. But a bigger aspect of the thinking keeps coming back to me: A question that might help address the dilemma of bone loss. A question that keeps coming back after doing WarriorHealth CombatCare and finding out about the fine work done at Walter Reed National Military Medical Center in Bethseda, MD.

USMC Cororal Todd LoveIs a veteran with paraplegia or no legs the natural spacecraft driver?

Since bone density loss is a key barrier to long-term low gravity living…aren’t technically-trained veteran paraplegians and double amputees great candidates for the astronaut corps? Does a fighter pilot have the discipline, skill and temperament to be a launch driver? Does an armored division tanker have the skills to be an in-flight systems specialist?

Does USMC Corporal Todd Love (an incredibly inspirational guy! seen here) really need legs to operate in micro-gravity, when he might only need wheels on the ground? (As you can see, he does not need legs whatsoever).

I ask you…


Could this approach create uplifting new opportunities to serve and thrive in a way that makes the unavoidable SCI injury extraordinarily valuable?

Aren’t two-legged people naturally less abled in the spaceflight environment?

Who is the more-natural space-athlete?

Who is the more-natural astronaut?

David Huer


US veterans with Spinal Cord Injury (SCI) as of 2008: 26,000 veterans

US citizens with SCI: 240,000 and 337,000 people
New injuries per year, as of 2015: 12,500 people

Latest EVA suit made by Oceaneering Inc. (Houston, TX):

Interesting aspects of design/safety aspects
* Effect to bone mass/density and to body functions
* Pant legs + boots: removedaperture and material needs cut by ~40%, with 5 apertures (head, left & right arm, left & right leg) reduced to 3.
* Electronic components & new designs for torso & new “thighboots”
* “Thighboots” reduce the dangers of entanglement & provide push-off tasking as needed
* External prosthetics designed to attach to thighboots

Healthcare research outcome:
Could NASA, the VA and DoD assess impact on SCI to help society groundside?


US Astronaut Tom Jones (STS-129):

USMC Corporal Todd Love and Team X-T.R.E.M.E. competing in The Spartan Race, Leesburg, VA, 2012:

Constellation EVA Spacesuit: NASA
(Image modified with removal of lower extremities in image)

The Flu, Transmitted Infection Vectors & Healthcare Labour

800px-Students_assisting_surgeryCould in-house Facility Epidemiology manage healthcare $compensation costs?
David Huer, Vancouver, Canada.



In Health Care as in all public safety and assurance occupations, it is vital to protect the trained caregiver from inadvertent harm because that person’s loss damages society’s ability to serve everyone.


I’ve been at home with flu for a week. Friends from the States came to visit throughout the Lower Mainland and up the coast, then we had a visit. Shortly thereafter, I got walloped. And then, whilst talking to them on the phone later, learned that a group of students, coughing and sniffly, came onto their connecting flight. And learned from my family physician that flu symptoms do not show for 12 hours after exposure. Making us suspect they might be the source vector.

Periodically, I volunteer business services to health clinics, and it was in thinking about that, and the vectoring of this flu, that I’ve been wondering:

Could we recognize a role for Transmitted Infection Vector (TIV) in $compensation rates at a healthcare facility?

Could we alter our definition of effectiveness in patient-centred care, to one where Health Worker salary $compensation is weighted to account for exposure to Patient Transmitted Infection (PTI). Recognizing the likelihood that the worker could become a Transmitted Infection Vector (TIV)?

  • Identifying different risks of exposure of different classes of health worker?
  • Recognizing that different classes have different risk to become TI Vector transmitters?
  • Could this become the means to improve $compensation package effectiveness?

TIV Proximity Risk



Dartmouth’s Chris Trimble neatly summarizes healthcare innovation pathways at the Dec 2015 article here:

  1. Standardize and delegate
  2. Coordinate
  3. Prevent
  4. Improve treatment decisions

All 4 paths influence this idea, and gathering the data set is enormously challenging if collected with traditional paper and interviews. But, local WiFi/GPS (Smartphone, Geo-fenced In-House Smartphones, Active ID cards) and machine-learning – accessed through programs like Samsung’s Enterprise Alliance Program – offer a nearly automated data-gathering method, that could make this an effective, scalable process and tool for private, public, and mixed-model social enterprise health facilities.


Building the Combined Model (Actuarial Model + Epidemiological Model) from source data


  1. Determine Facility Factors
  2. Determine Human Factors
  3. Determine Budget Factors.

Building the Actuarial Model from source data


  1. Build and test the Actuarial Model


  1. Gather “employee path-taking data” to develop epidemiological data for analysis of likely TIV source-paths and source-points.
  2. Develop Epidemiological Model


  1. Combine Actuarial and Epidemiological Models
  2. Negotiate $Compensation Packages


Using the University of New Mexico’s Dental Clinic and Surgery Center.

Rough calculations look interesting:
(see supplementary calculations below coloured hospital maps)

In a traditional payout, the RN Administrator might have highest pay, derived from:

  • Years of Service
  • Seniority
  • Assumed accumulated technical expertise
  • Assumed accumulated humane-contact expertise
  • Terms of a Collective Agreement

In this model, the RN Surgery Nurse is deemed to be likely to face higher risk of becoming a TI Vector. Therefore, to protect the continuing presence of this person as a public resource, s/he is:

  • Deemed to require higher compensation for the risk.
  • Able to choose career paths using the Risk/Compensation ratio [ R/C ].
  • Able to pre-select or accept shift assignments shifts using R/C Ratio guidelines.




The implications are interesting:

  • Health workers of all types (nurses, physicians, security guards, waste cleaning workers, nurse practitioners, administrative staff, mechanical engineers, etc.) experience different levels of stress – and each person’s ability to manage their exhaustion, to obtain compensation, can be hugely challenging. As are suicide and trauma experienced from patient violence and administrative overload. Could TIV-adjusted $compensation packages bring about a new harmoniousness of purpose among health facility staff?
  • Could WiFi/GPS/Machine-learning be used to calculate a fluctuating Premium that adjusts to the ability of RNs carrying out their duties?
  • Could a higher status Surgeon Emeritus (SE) get lower compensation relative to an Active Surgeon (AS) when the SE faces lower daily risk? 
  • Could $Premium compensation go up during a full moon or after a sports match? Will workers choose to pick that busy shift knowing the R/C compensation rate?
  • Would unexpected source-points and source paths be discovered? For example, the handling path for medical waste held as evidence by a police constable?







Students assisting surgery in an affiliated hospital of Hebei North University., Author: CMSRC, 1 April 2008, 21:27:07, Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0).

Could Cloudbox Mimics improve the naturalness of machine-learning?

Creating a “Cloudbox Mimic”
to map Rhizome growth choices, as a self-comprehended ‘hypotheses testing’ learning tool of ever-enlarging complexity

Would ‘asymmetric logic’ help machine-learners practice natural learning?

dhuer-cloudboxing-aIn 2014, I developed the Cloudboxing© thinking technique. Teaching myself to stitch together a set of cognitive cloud datapoints to create a place to study the building blocks of coding language, to learn exactly what code was and where it could be located in my data set. ie. Using my first cognitive language (Liquid Membraning) to translate coding language into the “building blocks” of Liquid Membraning language. See Project #5 at

Lately, in between work, consulting, and venturing, I’ve been thinking about machine learning and Google’s DeepMind project, and wondering whether the “flatness” of programmed teaching creates limits to the learning process? For example…whilst reading the Google team’s “Teaching Machines to Read and Comprehend” article

Could we enlarge the possibilities, using spatial constructs to teach multidimensional choice-making?

creating a cloud-box to mimic rhizome growth choicesThis could be a software construct, or a physical object [such as a transparent polymer block, where imaging cameras record choice-making at pre-determined XYZ coordinates to ensure the locations of choices are accurately mapped (especially helpful when there are multiple choices at one juncture)].

Encapsulating and organizing defined space for machine-learned self-comprehension. mimics the “cloudboxing” technique.

And, it mimics the natural self-programmed logic of self-learning…a novel teaching tool for the machine-learning entity:

  • Creating a set of challenges through 3dimensional terrain that mimics pre-defined/pre-mapped subterranean tunnels
  • Creating an opportunity to dimensionally map an emulated (or actual) entity growing through the tunnel system
  • Studying the polar coordinates of the entity traversing the pre-defined space(s)

1) What about using a rhizome?Jiaogulan-Rhizome

. . . Using a natural entity teaches a machine-learning entity to mimic natural learning.

Using a plant creates the possibility that we can map choice-making, using attractants such as H2O and minerals, as a mimic for conscious entities developing learned behaviour.


2) Once you have a defined baseline data set, could machines learn better if being blocked and shunted by an induced stutter?

using stuttering blocks to teach choice-decision-making

Perhaps learning by stuttering and non-stuttering might produce interesting data?

By creating a stuttering event as the baseline, perhaps the program will use this to overcome obstacles to the learning process as well as the object of the lesson to learn to not stutter? This could produce a host of interesting possibilities and implications.

3) Things get incredibly interesting if the program eventually attempts to produce choice options outside the available options . . .

Note: These ideas continue the conceptual work of WarriorHealth CombatCare, re-purposing the anti-stuttering Choral Speech device SpeechEasy for Combat PTSD treatment. The research proposal for that work is here:


Jiaogulan-Rhizome: Own work/Eigenes Foto by Jens Rusch, 29 August 2014  CC Attribution-Share Alike 3.0 Germany license.

Drawings: David Huer © 2014-2015