This is a fake article. It fully plagiarizes another legitimate article while simply changing author names and changing the article text (possibly AI generated).

doi.org/10.1101/2025.11.04.2...

The author's ORCID profile also seems to be fake as he/she has multiple papers in several unrelated fields (possibly an AI spambot).

orcid.org/0009-0003-9596-4602

Please take down this article, send a warning email to the author at drakaur86@gmail.com and ban this "author" from adding any new publications to your website.​

As the year winds down and temperatures (hopefully) drop for the holidays, we share a methodological contribution on the opposite problem. This paper presents an automated, open-source workflow for mapping Surface Urban Heat Island Intensity using globally available remote-sensing data, with a focus on reproducibility, scalability, and transparent downstream processing. The work was born in a grassroots climate-activism context, where the need for accessible, transferable, and openly auditable tools was central, and we welcome discussion on assumptions, limitations, and extensions within open urban climate research https://doi.org/10.1016/j.susgeo.2025.100006

IG @scif_officina

#climatejustice #opendata #EarthObservation #climactivism

A7-HBM–ΩΦ: An Integrated Seven-Band

Neurogeometric Model of Cognition Combining

Computational Simulations, Neurogeometry, and Experimental Frameworks

Abstract

The Al-Olofi Seven-Band Hierarchical Brain Model (A7-HBM–ΩΦ) presents an integrative neurogeometric and computational architecture describing multiscale brain oscillations through seven hierarchically organized frequency bands: δ (0.5–4 Hz), θ (4–8 Hz), α (8–12 Hz), σ (12–16 Hz), β (13–30 Hz), γ (30–80 Hz), and Ω (80–200 Hz).

The framework applies nonlinear coupled-oscillator dynamics, phase–amplitude coupling (PAC), and golden-ratio scaling (Φ ≈ 1.618) to define optimal cross-band relations. Using fourth-order Runge–Kutta simulations with Lyapunov stability analysis, the system self-organizes into Φ-consistent clusters with robust PAC coherence and globally negative Lyapunov exponents, confirming dynamic stability.

Each band corresponds to a specific geometric primitive, neural substrate, and cognitive role, forming a neurogeometric pyramid from interoceptive integration (δ) to metacognitive resonance (Ω). A proposed EEG/MEG experimental protocol tests predicted σ–Ω and β–γ PAC interactions.

The A7-HBM–ΩΦ thus unites mathematics, neural dynamics, and cognition within a single testable model, with implications for neuro-inspired AI, brain–computer interfaces, neuromodulation, and clinical diagnostics.

DOI: doi.org/10.21203/rs.3.rs-806...

@Sciety_User ​This work sets a new benchmark in backorder prediction by demonstrating that the combination of accessible high-performance computing platforms and well-selected machine learning algorithms can deliver state-of-the-art results without requiring enterprise-level infrastructure. It thus opens a promising avenue for practitioners and researchers seeking scalable, accurate, and interpretable solutions for complex supply chain challenges. We believe this contribution will encourage further research into the integration of cloud-based computing and AI in real-time supply chain risk mitigation, and support the development of agile, data-driven strategies to strengthen supply chain resilience in an increasingly volatile global environment.

Improving Project Accuracy Through Better Estimating Practices

In today’s fast-moving construction environment, having reliable cost insights isn’t just helpful it’s essential for making informed decisions. Many builders, engineers, and project managers are now relying on professional construction estimating consultants in Australia to minimize risk, improve accuracy, and streamline the early planning phase.

Clear and precise estimating allows teams to understand material requirements, labour needs, and potential cost fluctuations before committing resources. This not only reduces unnecessary delays but also ensures smoother communication across the entire project lifecycle.

For organisations aiming to improve efficiency and transparency, partnering with experienced consultants offers a practical edge. Their data-driven insights help identify hidden risks, refine budgets, and provide the clarity needed to move forward confidently.