Indoor air pollution drives a substantial share of respiratory, allergic and thermal-comfort morbidity in residential buildings, yet continuous multi-hazard monitoring remains rare in low-cost Internet-of-Things deployments, which typically report a single composite pollution index and ignore the multidimensional natur...
Azaz Ahmed Lipu· Zenodo (CERN European Organi...· 0 citations
This Zenodo archive deposits the foundational research white paper series for the **IronClad AI Agent**, a Rust-native autonomous agent orchestration runtime engineered specifically for local Large Language Models (LLMs) executing under strict consumer hardware constraints (8–24 GB VRAM, finite 8K–32K context windows,...
Wael Sahli· Zenodo (CERN European Organi...· 0 citations
DECISION: REJECT ELEMENT: No element survives — the ACCUMULATION-phase filter is a regime proxy, not an E8-geometry timing edge. It does not align with the Gods-Clock rhythm logic or FADE polarity mechanics; it is a macro overlay that would distort the model's core timing signal. EXPECTED IMPACT: Win-rate improvement i...
Andrew Stewart Caldin· Zenodo (CERN European Organi...· 0 citations
Indoor air pollution drives a substantial share of respiratory, allergic and thermal-comfort morbidity in residential buildings, yet continuous multi-hazard monitoring remains rare in low-cost Internet-of-Things deployments, which typically report a single composite pollution index and ignore the multidimensional natur...
Azaz Ahmed Lipu· Zenodo (CERN European Organi...· 0 citations
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For much of the history of computing, the material boundary of a computational system could be represented with relative simplicity: processors, memory, storage, and software execution were located within machines whose participation in the system was architecturally specified in advance. Distributed computing complica...
Joaquim Santos Albino· Zenodo (CERN European Organi...· 0 citations
This tutorial presents a step-by-step calculation of the Curvature Polarization Transport Gravity (CPTG) galaxy-limit equation using three worked rotation-curve examples: DDO-154, NGC-3198, and NGC-7814. Starting from SPARC-style rotation-curve inputs, the calculation converts the observed radius and velocity columns i...
Carter L Glass· Zenodo (CERN European Organi...· 0 citations
DECISION: REJECT ELEMENT: No element survives — the ACCUMULATION-phase filter is a regime proxy, not an E8-geometry timing edge. It does not align with the Gods-Clock rhythm logic or FADE polarity mechanics; it is a macro overlay that would distort the model's core timing signal. EXPECTED IMPACT: Win-rate improvement i...
Andrew Stewart Caldin· Zenodo (CERN European Organi...· 0 citations
Modern connectivity is supplied by a portfolio of technologies rather than by a single dominant network. Ethernet and passive optical networks provide stable high-capacity infrastructure; Wi-Fi supplies flexible local access; cellular systems add managed mobility and wide-area coverage; low-power wide-area networks sup...
This paper introduces a novel quantum state computation model based on graph structures, leveraging the inherent properties of quantum states to enable adaptive computation. Traditional quantum computing approaches often struggle with complex quantum states, presenting a significant challenge for efficient computation....
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Two structural results on the possibility of a genuinely noncommutative arithmetic thermodynamics. First, a universal no-go, the abelian scaling bottleneck: for a right LCM semigroup with scalar one-parameter dynamics driven by a multiplicative weight N, every KMS state is tracial on the gauge-fixed algebra, the classi...
Ruqing Chen· Zenodo (CERN European Organi...· 0 citations
This paper investigates the challenges and proposes a novel approach to distributed edge computing resource scheduling and optimization. The core claim is to design an efficient algorithm that dynamically allocates resources based on task requirements and edge computing node capabilities, ultimately enhancing computati...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026
