cognitive load retraction effort qrs wrs systems

Highest energy consumed 

In human body when 

You distract and get back to focus 

This refocussing energy is not calculated in daily life and all politics are done through distracting people. This is well known princiole that refocussing back to peoples own focus (peoples own purpose focus) consumes so much energy that it violates least action principles (Lagranges action is energy ×time which Sanjoy Nath interpretes as total focus energy held for how long? And also Sanjoy Nath's theory of econophysics deals with total action for all humans activities and how long each such activities continue continuously and how many times distraction and refocussing efforts are uncounted in society)

This research is a subdomain of Sanjoy Nath's Qhenomenology Reasoning System QRS and Sanjoy Nsth's Whenomenology reasoning systems WRS. These QRS and WRS syatems calculates how humans focus repeatedly distracted along timelines and then humans motives retracted to different focus zones according as least action principles.

Popular trends diverged humans cognitions time to time along history and so humans focussed growth hampered repeatedly. Sequence of concept formation in mankind (queued nature of humans concept constructions are also dependent on how many times mankind got distracted from their own focus of life)

The core idea that refocusing after distraction consumes significant cognitive energy is strongly supported by standard cognitive science research, which aligns conceptually with the interpretation we attribute to Sanjoy Nath's theories (QRS/WRS and Econophysics).

🧠 Cognitive Energy Cost of Refocusing

In standard psychology and neuroscience, the effort to recover focus is known as "switch cost" or the "cognitive switching penalty."

 * High Energy Consumption: The brain is energy-intensive, consuming about 20% of the body's total available energy. Shifting between tasks requires significant mental effort because the brain must:

   * Goal Shift: Decide to stop the original task and start a new one (the distraction).

   * Rule Activation/Deactivation: Turn off the mental rules for the previous task and load the rules for the new, distracting task.

   * Cognitive Reconfiguration: Reallocate mental resources to the new task's context.

 * Time and Fatigue: Research indicates that it takes an average of 23 minutes and 15 seconds to fully regain deep focus after a distraction or task switch. This time loss, coupled with the mental fatigue from repeatedly loading and reloading contexts (known as "thrashing"), is the primary cost. This fatigue is a sign of high energy consumption.

 * Productivity Loss: Frequent task switching can reduce overall productivity by up to 40%.

💡 Sanjoy Nath's Interpretation (QRS/WRS/Econophysics)

The non-standard theories you reference extend this cognitive cost into broad economic and philosophical frameworks:

Least Action Principle (Lagrange's Action)

 * Standard View: In physics, the Principle of Least Action states that the path a physical system takes between two points in time is the one that minimizes the action (a quantity often defined as \text{Energy} \times \text{Time}).

 * Nath's Interpretation (as described): Interpreting \text{Energy} \times \text{Time} as "total focus energy held for how long" is a metaphorical application of this physical principle to human cognition.

   * Focusing represents a path of least action toward a goal (minimum effort for maximum continuous progress).

   * Distraction and Refocusing introduce a discontinuity in the process, forcing the person to expend substantial, "uncounted" energy to restart the path. This "uncounted" energy effectively violates the condition of minimizing action for a continuous path, as it requires a large, wasted burst of effort.

 * The argument suggests that by constantly distracting people, political systems impose a high, uncounted action cost, thereby impeding their "focussed growth."

Qhenomenology Reasoning System (QRS) and Whenomenology (WRS)

 * These systems appear to be novel frameworks for analyzing human cognition and concept formation, focusing on strict, queued, and structural dependency of concepts, rather than traditional statistical or subjective methods.

 * Queued Nature of Concept Construction: The idea that the sequence of concept formation in mankind is dependent on the number of times distraction occurs aligns perfectly with the cognitive switch cost. Distractions break the queue, requiring a costly reset before the next concept can be loaded and built upon, thus "hampering" growth.

In summary, the high energy consumed in the human body to refocus is the well-established Cognitive Switching Penalty, and its impact aligns with Sanjoy Nath's idea that uncounted refocusing efforts are a massive societal drain on human action and potential.

You can learn more about Sanjoy Nath's Qhenomenology and related concepts in this video: SANJOY NATH'S QHENOMENOLOGY NAFECADMIPA NUMBERSYSTEMS 60repeats complicated society. This video discusses the NAFECADMIPA framework, which is part of the Qhenomenology system.

What are researches done in this line of inquiry??????

Nature dont bother whatever conventions human prepare for humans own social needs. Sanjoy Nath 's materialistic arithmetic systems try to understand so inquires

1 how much naturally natural are human's conventions?

2 how much nature friendly are humans convention with which humans calculate the values of humans natural numbers?

3 if nature had to design a number system for humans then would that number system ever looked like decimal systems? How much quantum like structure is present inside encryption encoding process (convention as rule of game to evaluate valuation of a decimal systems string) as humans follow everyday??????

One analogy here is 

States are like balls and nature tries to arrange these balls are stored in certain sieve (special kind of bag which has several bins of different capacities and the most compact form to arrange capacities of these bins (discrete ball holding capacity of each bins are crucial for different purpose such that humans can easily remember the preset universal conventtions and whole society of mankind learns this convention of bin addressing system which address of bins also carry the bins ball holding capacity. The valuation process is dependent on convention to address these bins and this convention is just human's mnemonic tool and nature has not generated this convention. This convention fulfilling three purpose at a time. First it is easy for humans to remember process of evaluation,second it is easy to calculate which (r th bin from left side)bin has ball holding capacity (10/10)*(10^(n - r+1-1 )) and this rule is fixed,thirdly the evaluation means total number of balls present in whole bag and size of the bag is of least possible string length n. Now we can think each such bins as orbitals and each such balls as states. All such states are equally likely. These states are arranged in bins just to fulfill above convenience for human cognitive load reductions and these compacification scheme has nothing to do with natures law .These compacification and arrangements of total number of balls (evaluation means total number of balls in the bag whatever compacification conventions we choose the total numbers of balls don't change. We need to change evaluation algorithm if we change convention for compacification encoding systems. This means our evaluation process is not naturally natural. These evaluation process need to change if we change our compacification schemes. 

Strict note that whatever scheme we take whatever standards of encoding decoding systems we adopt the fundamental evaluation need to remain same after encoding and decoding of compactified representation and evaluation means counting of all balls (that is total available contained positive states) are there in whole codified such bag.

)

Sanjoy Nath dont consider natural numbers as numbers.Instead Sanjoy Nath has deep philosophy to consider 0 1 2 3 4 5 7 6 8 9 are just names of 10 states which occupy r th positions on a n position string (state container string) each of such r th positions in n long state string which are having orbital like fixed storage capacities each. This means all different r th position is r th orbital and we calculate state storing capacity of r th orbital from left side of  n position long string is (10^(n - r+1-1 )) and actual states stored in that orbital is states orbital is (d/10)*(10^(n - r+1-1 ))

The rule for calculating total state storing capacity in r th state storing orbital is fixed in 10 state dependent system

But actually stored states in each of such orbital are less than or equal to 9 means how many named states are valued as ordinal characteristics and rule is fixed as

0<1<2<3<4<5<6<7<8<9

If we change this order then our whole system changes and all behaviors of prime states also changes and all characteristics of the usage rules drastically change.

The total amount of states actually stored in any r th orbital in n orbital long orbital string governs as a fraction f_r which is always between 0 to 1

0<= f_r<=1

The value of f_r creates pressure on neighbourhoods of such state filled strings. These state filled strings have every r th orbital having fixed upper limit to store such states. . In n orbital long string r th orbital has (n -r) numbers of right side orbitals. All of such of all These right side orbitals total state holding capacity is always less than state holding capacity in r th orbital (r and n are measured from left side of the n orbital string.

All other dependent rules of games like 

+ as a interaction game,

- as a interaction game,

× as a interaction game,

÷ as a interaction game,

= as a interaction game,

√ as a interaction game,

^ as a interaction game,

Log as a interaction game,

Note that all there rules of games are entirely dependent upon our conventions of compaction of states in our mnemonic dependent convention of encoding and mnemonic dependent storage arrangement of orbitals addressing schemes. All rule of game are changeable if we change our orbital wise capacity calculation mnemonic standard or/and if we change orbital addressing schemes.

Strict note that whatever scheme we take whatever standards of encoding decoding systems we adopt the fundamental evaluation need to remain same after encoding and decoding of compactified representation and evaluation means counting of all balls (that is total available contained positive states) are there in whole codified such bag.All above rules of game are representation dependent (evaluation convention dependent)

All the above rules of game are revised accordingly when encoding decoding convention are changed but every such rules of games are verified with evaluation (value of total count of states/balls) 

Strict note that whatever scheme we take whatever standards of encoding decoding systems we adopt the fundamental evaluation need to remain same after encoding and decoding of compactified representation and evaluation means counting of all balls (that is total available contained positive states) are there in whole codified such bag.