Author:
Joseph A. Sprute
Founder, ERES Institute for New Age Cybernetics
Contact:
eresmaestro@gmail.com
33 Westbury Dr.
Bella Vista, Arkansas 72714
Collaborative Development:
Claude (Anthropic AI)
Technical specification, mathematical formalization, implementation architecture
Date: December 30, 2025
Version: 1.0
- Executive Summary
- Foundational Concept
- Bio-Energetic State Vector (BESV)
- Resonance Calculation
- BEST: Bio-Electric Signature Time
- Contribution Quality Score (CQS)
- Scale Dimensions
- Integration with ERES Frameworks
- Implementation: BERA-PY Library
- Applications
- Ethical Framework
- Validation Strategy
- Theoretical Foundations
- References
- License and Usage Terms
BERA (Bio-Energetic Resonance Architecture) represents a paradigm shift in how we understand and measure human coordination, wellbeing, and collective intelligence. By transforming subjective experiences of "sensing someone's energy" or "reading auras" into quantifiable, verifiable measurements across five physiological modalities, BERA bridges ancient wisdom with modern biometric science.
Core Innovation: BERA quantifies what humans intuitively experience as "telepathy," "empathy," or "aura reading" through sophisticated measurement of bio-energetic broadcasts across acoustic, electromagnetic, chemical, thermal, and photonic channels. These signals trigger cascading physiological synchronization through the psychoneuroimmunology axis, enabling real-time measurement of individual states, interpersonal resonance, and collective coherence.
Practical Applications: BERA enables merit-based economic systems (Meritcoin/Gracechain), optimizes team composition, provides early conflict detection, facilitates collective flow states, supports preventive healthcare, enhances educational outcomes, enables transparent governance, and coordinates emergency response at scales from personal to planetary.
Implementation Status: Complete technical specification, mathematical formalization, and production-ready Python library (BERA-PY v0.1.0) with integration to all major ERES Institute frameworks including PBJ Tri-Codex, Emission Resonance Index (ERI), PlayNAC KERNEL, Gracechain blockchain, and UBIMIA economic system.
For millennia, humans have reported subjective experiences of "knowing" another person's emotional or physiological state without apparent sensory input—colloquially termed telepathy, intuition, or empathic knowing. Simultaneously, traditions across cultures describe "auras"—energetic fields surrounding individuals that encode internal states.
Despite 150+ years of parapsychological investigation, no reliable evidence for paranormal mechanisms has emerged, yet the phenomena persist with remarkable cross-cultural consistency. BERA proposes these experiences are real but misidentified: They result from sophisticated, unconscious processing of physical bio-energetic signals that trigger cascading physiological synchronization through the neuroendocrine-immune axis.
| Term | Definition |
|---|---|
| Aura | Measurable bio-energetic broadcast via acoustic, electromagnetic, chemical, and thermal channels |
| Resonance | Physiological synchronization between individuals in proximity |
| Telepathy | Unconscious detection of biometric state information |
| BESV | Bio-Energetic State Vector - complete physiological signature at time t |
| BEST | Bio-Electric Signature Time - timestamp encoding bio-energetic state |
The complete physiological signature of an individual at time t is represented as:
BESV_i(t) = [A(t), E(t), C(t), T(t), P(t)]
A(t) = [f_inf(t), f_pros(t), f_speech(t), HRV_a(t), BR(t)]
| Component | Range | Measures |
|---|---|---|
| f_inf(t) | 0.5-20 Hz | Cardiac and respiratory rhythms (infrasonic) |
| f_pros(t) | 20-300 Hz | Emotional tone, stress markers (prosodic envelope) |
| f_speech(t) | 300-8000 Hz | Semantic content, cognitive load (speech spectral) |
| HRV_a(t) | Derived | Heart rate variability extracted from voice |
| BR(t) | cycles/min | Breathing rate from respiratory patterns |
Measurement Protocol:
- Sampling rate: ≥48 kHz
- Window: 5-second sliding, 50% overlap
- Processing: Fast Fourier Transform (FFT) into frequency bands
- Hardware: Professional audio interface (RME Fireface UCX) or smartphone microphone
E(t) = [ECG(t), EEG(t), HRV_e(t), HR(t)]
| Component | Units | Sampling | Measures |
|---|---|---|---|
| ECG(t) | mV | 500 Hz | Cardiac waveform, heart electrical activity |
| EEG(t) | μV | 256 Hz | Neural oscillations (δ, θ, α, β, γ bands) |
| HRV_e(t) | ms | Derived | Time-domain HRV (SDNN, RMSSD) |
| HR(t) | BPM | Real-time | Instantaneous heart rate |
EEG Frequency Bands:
- δ (Delta): 0.5-4 Hz - Deep sleep, unconscious processes
- θ (Theta): 4-8 Hz - Meditation, creativity, light sleep
- α (Alpha): 8-13 Hz - Relaxed wakefulness, calm focus
- β (Beta): 13-30 Hz - Active thinking, concentration
- γ (Gamma): 30-100 Hz - Higher cognitive functions, consciousness
Measurement Protocol:
- ECG: Lead II configuration or photoplethysmography (PPG)
- EEG: 10-20 system placement, minimum 8 channels (Fp1, Fp2, C3, C4, P3, P4, O1, O2)
- Hardware: Polar H10 chest strap (ECG), OpenBCI Cyton (EEG), Empatica E4 (PPG/EDA)
C(t) = [CORT(t), OXY(t), CYT(t), VOC(t)]
| Component | Units | Marker Type | Sampling |
|---|---|---|---|
| CORT(t) | nmol/L | Stress marker | Salivary ELISA, 4x/day |
| OXY(t) | pg/mL | Bonding marker | Venous blood, immunoassay |
| CYT(t) | pg/mL | Immune state | IL-6, TNF-α, IL-10, IL-1β |
| VOC(t) | Various | Metabolic state | Breath/skin GC-MS or e-nose |
T(t) = [T_core(t), T_periph(t), ΔT(t), T_pattern(t)]
| Component | Measurement | Clinical Significance |
|---|---|---|
| T_core(t) | Tympanic or sublingual (°C) | Core body temperature |
| T_periph(t) | Infrared thermography | Hands, feet, face temperature |
| ΔT(t) | T_core - T_periph | Autonomic balance indicator |
| T_pattern(t) | Thermal imaging (64×64) | Facial thermal signature pattern |
Measurement Protocol:
- Hardware: FLIR One Pro or similar thermal camera
- Resolution: ≥0.1°C temperature resolution
- Applications: Stress detection, autonomic function assessment, emotional state inference
P(t) = [biophoton_flux, spectral_distribution, coherence_measure]
Ultra-weak photon emission from biological tissues, measured in the visible to near-infrared spectrum. This modality remains experimental and is included for completeness. Research suggests biophotons may encode information about cellular metabolic states and electromagnetic field coherence.
The resonance between two individuals i and j is calculated as a weighted combination of component resonances:
PRC(i,j) = α·R_acoustic + β·R_em + γ·R_chemical + δ·R_thermal
Default weights: α=0.4, β=0.3, γ=0.2, δ=0.1
| Component | Calculation Method |
|---|---|
| R_acoustic | Gaussian kernel similarity of frequency spectra across bands |
| R_em | Pearson correlation of HRV time series + EEG band coherence |
| R_chemical | Mahalanobis distance in cytokine-cortisol-oxytocin space |
| R_thermal | Spatial correlation of thermal patterns + ΔT similarity |
| PRC Range | Interpretation | Recommendation |
|---|---|---|
| 0.0 - 0.3 | Low resonance | Conflict potential - monitor interactions |
| 0.3 - 0.6 | Moderate resonance | Neutral - standard collaboration protocols |
| 0.6 - 0.8 | High resonance | Optimal collaboration - leverage synergy |
| 0.8 - 1.0 | Very high resonance | Collective flow state - maximize co-creation |
For a group G with n members, the collective coherence is measured as:
GRF(G,t) = (2 / (n(n-1))) × Σ_i Σ_j>i PRC(i,j,t)
This represents the average pairwise resonance across all unique pairs in the group, providing a single metric for organizational coherence. GRF values above 0.6 indicate high-functioning teams; values below 0.4 suggest significant internal friction requiring intervention.
Conflict_Potential(i,j) = 1 - PRC(i,j) when PRC < threshold
Real-time monitoring enables early warning when pairwise resonance drops below critical thresholds (typically 0.3). This allows proactive intervention before conflicts escalate, including mediation facilitation, team restructuring, or workload redistribution.
BEST provides a cryptographic timestamp that encodes the complete bio-energetic state at the moment of contribution, enabling merit-based economic systems that reward actual bio-energetic investment rather than hours logged.
BEST(t) = hash[BESV(t), context(t), validation(t)]
Components:
| Component | Description | Measurement |
|---|---|---|
| Bio-coherence | Internal physiological synchronization | HRV coherence, EEG phase coupling |
| Metabolic efficiency | Resource conversion effectiveness | ATP production, O₂ consumption ratios |
| Chronobiological alignment | Circadian/ultradian rhythm coherence | Cortisol slope, sleep quality metrics |
| Homeostatic stability | Autonomic balance, allostatic load | HRV SDNN, inflammatory markers |
BEST timestamps serve as immutable proof-of-contribution in blockchain-based economic systems. Unlike traditional time-tracking that measures hours, BEST captures the quality of energetic investment—distinguishing between depleting busywork and regenerative flow states. High-quality BEST scores correlate with sustainable productivity and worker wellbeing.
CQS quantifies the bio-energetic quality of work contributions, enabling differentiation between mechanically compliant labor and authentic engaged contribution.
CQS = ω₁·BEST + ω₂·GRF + ω₃·skill_match + ω₄·outcome_quality
| Factor | Weight | Description |
|---|---|---|
| BEST | ω₁ = 0.35 | Bio-electric signature quality of individual at time of work |
| GRF | ω₂ = 0.25 | Group resonance field during collaborative contributions |
| Skill Match | ω₃ = 0.20 | Alignment between contributor skills and task requirements |
| Outcome Quality | ω₄ = 0.20 | Measured impact of contribution on stated objectives |
Meritcoin Accrual: High CQS contributions accrue more Meritcoin per unit time, rewarding quality over quantity.
Gracechain Recording: Each contribution with BEST timestamp and CQS score is recorded immutably on the Gracechain blockchain, creating verifiable reputation.
UBIMIA Implementation: The formula Income = UBI_base + (Merit_score × Investment_multiplier) ± Awards_bonus incorporates cumulative CQS as the primary Merit component.
BERA operates across five nested scales, from individual bio-energetic optimization to planetary consciousness coordination:
| Level | Scale | Primary Applications | Key Metrics |
|---|---|---|---|
| 1 | Personal (Individual) | Self-awareness, flow states, circadian optimization, health monitoring | BEST, personal BESV trends, bio-coherence |
| 2 | Interpersonal (2-10 people) | Relationship quality, team optimization, conflict prevention | PRC, dyadic resonance patterns |
| 3 | Organizational (10-1000 people) | Culture quantification, productivity enhancement, org design | GRF, departmental coherence, conflict detection |
| 4 | Community (1K-1M people) | Municipal coordination, emergency response, smart city integration | Regional GRF, EMCI readiness, GAIA Centers |
| 5 | Planetary (Global) | Species coherence, millennial planning, consciousness indexing | Global ARI/ERI, planetary stress tracking |
The same fundamental measurements and algorithms apply at every scale, creating fractal consistency. An individual's BESV aggregates to dyadic PRC, which aggregates to organizational GRF, which aggregates to regional coherence metrics, ultimately contributing to planetary consciousness indices. This enables seamless coordination across scales without requiring different measurement paradigms at each level.
BERA serves as the measurement substrate for all major ERES Institute systems, providing quantifiable bio-energetic data that drives governance, economics, environmental monitoring, and healthcare coordination.
| Codex | Full Name | BERA Integration |
|---|---|---|
| PERC | Personal Emission Resonance Codex | Individual BESV tracking over time, personal bio-energetic history |
| BERC | Building Emission Resonance Codex | Organizational GRF monitoring, workplace environment optimization |
| JERC | Job Emission Resonance Codex | Work environment bio-energetic assessment, task-human compatibility |
BERA provides the core measurement data for ERI calculation across five sub-indices:
ERI = f(PEQ, CRF, EHI, JRQ, TRS)
Where PEQ (Personal Energy Quality), CRF (Collective Resonance Field), EHI (Environmental Health Index), JRQ (Job Resonance Quality), and TRS (Temporal Resilience Score) all derive from BERA measurements at appropriate scales.
Blockchain Architecture: BEST timestamps anchor each blockchain entry, providing cryptographic proof of bio-energetic contribution quality.
Meritcoin Issuance: CQS scores directly determine Meritcoin accrual rates, replacing arbitrary time-based compensation with quality-weighted merit.
Proof-of-Contribution: Bio-energetic verification replaces energy-intensive proof-of-work, enabling sustainable blockchain operation.
Real-time Feedback: Governance participants receive BERA feedback during decision-making processes, enabling awareness of collective coherence.
ARI Derivation: Animacy Resonance Index (ARI) is calculated from aggregated BERA data, measuring actual human flourishing rather than proxy metrics.
Policy Validation: Proposed policies are evaluated against predicted bio-energetic impact before implementation.
Universal Basic Income + Merit × Investment ± Awards:
Income = UBI_base + (Merit_score × Investment_multiplier) ± Awards_bonus
Merit_score is calculated from cumulative CQS over time, ensuring that economic compensation reflects actual bio-energetic contribution quality rather than hours logged or credentials held.
BERA-PY v0.1.0 is a production-ready Python library implementing the complete BERA specification with hardware abstraction, sensor integration, blockchain connectivity, and privacy-preserving analytics.
| Module | Purpose | Key Classes |
|---|---|---|
| bera.core | Fundamental data structures | StateVector, ResonanceCalculator, BEST, CQS |
| bera.sensors | Hardware abstraction layer | BERASensor, AcousticSensor, EMSensor |
| bera.metrics | Resonance & group dynamics | GroupResonanceField, ConflictDetector |
| bera.blockchain | Gracechain integration | Gracechain, Meritcoin, ProofOfContribution |
| bera.integration | ERES framework connectors | PBJTriCodex, ERICalculator, PlayNAC |
| bera.privacy | Data protection | Anonymizer, DifferentialPrivacy, ZKProof |
| bera.api | REST API server | BERAServer, APIClient, WebSocket |
| bera.visualization | Dashboards & plotting | ResonancePlotter, GroupDashboard |
| Modality | Device | Specifications | Cost |
|---|---|---|---|
| Acoustic | RME Fireface UCX | Professional audio interface, 48kHz+ | $1,200 |
| Acoustic | Smartphone microphone | Consumer-grade alternative | Included |
| Cardiac | Polar H10 | Medical-grade ECG chest strap | $90 |
| Cardiac | Empatica E4 | PPG + EDA wearable | $1,700 |
| Neural | OpenBCI Cyton | 8-channel EEG system | $500 |
| Chemical | Point-of-care kits | Cortisol/cytokine immunoassay | $50/month |
| Thermal | FLIR One Pro | Mobile thermal camera, 0.1°C res | $400 |
Basic pairwise resonance calculation in Python:
from bera.core import StateVector, ResonanceCalculator
from bera.sensors import AcousticSensor, EMSensor
# Initialize sensors
acoustic = AcousticSensor(sample_rate=48000)
em_sensor = EMSensor(ecg_enabled=True)
# Collect states
alice = StateVector(individual_id="alice")
alice.acoustic = acoustic.read()
alice.electromagnetic = em_sensor.read()
bob = StateVector(individual_id="bob")
bob.acoustic = acoustic.read()
bob.electromagnetic = em_sensor.read()
# Calculate resonance
calc = ResonanceCalculator()
prc = calc.pairwise(alice, bob)
print(f"Resonance: {prc.overall:.3f}")
print(f"Acoustic: {prc.acoustic:.3f}")
print(f"EM: {prc.electromagnetic:.3f}")Team Composition: Optimize team member selection based on predicted resonance patterns, reducing friction and accelerating collaboration.
Conflict Prevention: Real-time monitoring enables intervention before conflicts escalate, saving organizational resources and preserving relationships.
Flow State Facilitation: Identify conditions that enable collective flow, then replicate those conditions systematically.
Early Disease Detection: Bio-energetic dysregulation often precedes clinical symptoms, enabling preventive intervention.
Mental Health Monitoring: Continuous BERA tracking provides objective metrics for depression, anxiety, and stress disorders.
Psychoneuroimmunology: Direct measurement of chemical-immune-nervous coupling advances understanding of mind-body medicine.
Personalized Treatment: Optimize medication and therapy based on individual bio-energetic response patterns.
Learning State Optimization: Identify when students are in optimal states for different types of learning (focus vs. creativity).
Teacher-Student Matching: Pair educators and learners based on resonance compatibility for maximum knowledge transfer.
Attention Tracking: Real-time feedback on collective classroom engagement enables dynamic curriculum adjustment.
Stress Management: Early detection of student overwhelm enables timely support and workload adjustment.
Merit-Based Participation: Democratic systems weighted by demonstrated contribution quality (CQS) rather than wealth or credentials.
Policy Impact Measurement: Real-time tracking of how governance decisions affect citizen bio-energetic wellbeing.
Transparent Algorithms: Open-source governance code with citizen-auditable decision-making processes.
Ombudsmen Oversight: Independent monitors with access to BERA data ensure policies serve human flourishing.
Proof-of-Contribution: Bio-energetic verification replaces energy-intensive proof-of-work in blockchain systems.
Fair Compensation: CQS-based merit rewards quality of contribution, valuing care work and creativity equally with production.
Energy-Based Currency: Meritcoin accrual tied to actual bio-energetic investment rather than arbitrary hours.
Sustainable Allocation: Resource distribution optimized for long-term human and planetary flourishing.
Disaster Coordination: BERA-enabled communication reduces response time through optimized team deployment.
First Responder Monitoring: Real-time stress tracking prevents burnout and enables rotation based on bio-energetic capacity.
Community Resilience: Baseline GRF measurements identify vulnerable populations before disasters strike.
Critical Infrastructure: EMCI (Emergency Management Critical Infrastructure) systems maintain essential services during disruptions.
- Opt-in only, never mandatory participation
- k-anonymity (k ≥ 5) for all personal data
- Differential privacy for aggregate statistics
- Right to deletion and complete withdrawal
- Transparent data usage policies
- No sale or transfer of individual bio-energetic data
- Encrypted storage with user-controlled keys
- Regular independent privacy audits
- Democratic oversight of all algorithms
- Citizen-auditable decision-making processes
- Independent ethics committees with veto power
- Regular equity impact assessments
- Open-source core infrastructure
- Multi-stakeholder governing boards
- Transparent funding and conflict of interest disclosure
Prohibited Applications: BERA technology must never be used for surveillance, manipulation, coercion, discrimination in employment/insurance, or any application that undermines human dignity and autonomy.
Boundaries: Clear technical and legal restrictions prevent weaponization, including hardware kill switches, audit trails, and criminal penalties for misuse.
Oversight: Independent review boards with authority to halt deployments that violate ethical guidelines.
Five-phase implementation pathway from laboratory proof-of-concept to global scaling:
| Phase | Scale | Duration | Objectives |
|---|---|---|---|
| 1 | Laboratory | 6-12 months | Controlled environment testing, correlation with established measures |
| 2 | Small Groups | 12-18 months | 10-50 person cohorts, longitudinal tracking, qualitative assessment |
| 3 | Organizations | 18-24 months | 100-500 person deployments, A/B testing, ROI measurement |
| 4 | Municipal | 24-36 months | Smart City pilots, public health integration, emergency systems |
| 5 | Global | 36+ months | International standards, cross-cultural validation, planetary coordination |
- Technical: Reliability (uptime >99.5%), accuracy (correlation >0.7 with established measures), latency (<100ms real-time processing)
- Clinical: Early disease detection (6+ month lead time), mental health improvement (>30% symptom reduction)
- Organizational: Productivity increase (>20%), conflict reduction (>40%), retention improvement (>25%)
- Economic: ROI >3:1 within 24 months, Meritcoin adoption >10K users, Gracechain transaction volume >1M/month
- Social: User satisfaction >4.5/5, equity impact (reduced disparities), democratic participation increase (>15%)
BERA synthesizes insights from multiple scientific disciplines to create a unified framework for bio-energetic measurement and coordination:
| Discipline | Key Contributions |
|---|---|
| Psychoneuroimmunology | Chemical-immune-nervous system coupling; stress-inflammation pathways; social bonding via oxytocin-cytokine interactions |
| Acoustic Biometrics | Voice-based physiological state detection; emotional prosody; HRV extraction from speech |
| Chronobiology | Circadian and ultradian rhythm optimization; cortisol slope analysis; sleep-wake cycle regulation |
| Systems Theory | Nested cybernetic feedback loops (C = R × P / M); emergence of collective intelligence; fractal scaling |
| Quantum Coherence | Bio-photon emission; electromagnetic field effects; experimental non-local correlations (speculative) |
| Thermodynamics | Energy efficiency and entropy management; metabolic optimization; sustainable resource allocation |
| Network Science | Social contagion of physiological states; graph theory of resonance networks; collective dynamics |
| Information Theory | Signal processing of bio-energetic broadcasts; noise reduction; bandwidth optimization |
[1] Ader, R., Cohen, N., & Felten, D. (1995). Psychoneuroimmunology: interactions between the nervous system and the immune system. The Lancet, 345(8942), 99-103.
[2] Cacioppo, J. T., & Berntson, G. G. (1992). Social psychological contributions to the decade of the brain: Doctrine of multilevel analysis. American Psychologist, 47(8), 1019-1028.
[3] Hendy, P., Patel, B., & Koriagin, A. (2015). Voice quality and acoustic biomarkers in stress and psychological state detection. In Proc. BIOSIGNALS (pp. 123-129).
[4] Lieberman, M. D., & Eisenberger, N. I. (2015). The dorsal anterior cingulate cortex is selective for pain: Results from large-scale reverse inference. Proceedings of the National Academy of Sciences, 112(49), 15250-15255.
[5] Malik, M., et al. (1996). Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. European Heart Journal, 17(3), 354-381.
[6] McEwen, B. S., & Stellar, E. (1993). Stress and the individual: Mechanisms leading to disease. Archives of Internal Medicine, 153(18), 2093-2101.
[7] Popp, F. A., Li, K. H., & Gu, Q. (Eds.). (1992). Recent advances in biophoton research and its applications. World Scientific.
[8] Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart-brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 33(2), 81-88.
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Sprute, J. A. (2025). Natural Resonance Processing (NRP) and the Basis for Graceful Evolution. ERES Institute Technical Report.
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Sprute, J. A. (2025). PlayNAC KERNEL: Gamified Governance with Real-Time Bio-Energetic Feedback. ERES Institute White Paper.
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Sprute, J. A. (2025). Meritcoin and Gracechain: Bio-Energetic Proof-of-Contribution for Sustainable Economics. ERES Institute Technical Specification.
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Sprute, J. A. (2025). PBJ Tri-Codex: Integrated Personal, Building, and Job Emission Resonance Framework. ERES Institute Standards Document.
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Sprute, J. A. (2025). UBIMIA: Universal Basic Income + Merit × Investment ± Awards Implementation Guide. ERES Institute Policy Paper.
Website: Pending
ERES GitHub Organization:
https://github.com/orgs/ERES-Institute-for-New-Age-Cybernetics
GitHub Repositories:
https://github.com/orgs/ERES-Institute-for-New-Age-Cybernetics/repositories
BERA-PY Library: MIT License
Copyright © 2025 Joseph A. Sprute, ERES Institute for New Age Cybernetics
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
This Report: Creative Commons Attribution 4.0 International (CC BY 4.0)
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Full license text: https://creativecommons.org/licenses/by/4.0/
To cite this report in academic or professional publications:
Sprute, J. A. (2025). BERA: Bio-Energetic Resonance Architecture - Complete Scope and Scale Definition. ERES Institute for New Age Cybernetics Technical Report. Bella Vista, AR.
BibTeX format:
@techreport{sprute2025bera,
author = {Sprute, Joseph A.},
title = {BERA: Bio-Energetic Resonance Architecture},
subtitle = {Complete Scope and Scale Definition},
institution = {ERES Institute for New Age Cybernetics},
year = {2025},
address = {Bella Vista, Arkansas},
type = {Technical Report}
}For questions, collaboration inquiries, or implementation support:
Joseph A. Sprute
Founder and Director
ERES Institute for New Age Cybernetics
33 Westbury Drive
Bella Vista, Arkansas 72714
United States
Email: eresmaestro@gmail.com
GitHub: https://github.com/orgs/ERES-Institute-for-New-Age-Cybernetics
ResearchGate: Joseph A. Sprute
End of Report