ethicalabs/Research-Intent-Collab huggingface dataset:
Entropy-Induced Collapse (EIC) Model – Part (2) Refining the Entropy-Induced Collapse (EIC) Model for Quantum Computing: Large-Scale Quantum Error Correction, Non-Markovian Noise, and Experimental Validation

This paper presents Part (2) of the Entropy-Induced Collapse (EIC) Model series, significantly refining the theoretical framework introduced in Part (1). The EIC model is a deterministic-stochastic theory describing quantum wavefunction collapse as triggered when the environmental entropy S_{\mathrm{env}}(t) surpasses a dynamically evolving critical threshold S_{\mathrm{crit}}(t). In this work, we explicitly integrate large-scale Quantum Error Correction (QEC), realistic non-Markovian fractional Brownian motion (fBm) noise, and detailed numerical validations via high-performance computing (HPC) simulations.     We rigorously derive and empirically validate an analytical expression for the critical entropy threshold shift \delta(d), showing a logarithmic dependence on the QEC code distance d:     \delta(d) = A_{\mathrm{QEC}}\ln d + B_{\mathrm{QEC}},     with parameters precisely determined from extensive simulations: A_{\mathrm{QEC}} = 0.232 \pm 0.052\,k_B and B_{\mathrm{QEC}} = -0.175 \pm 0.10\,k_B. Our refined model accurately predicts coherence extensions of up to approximately 80\,\mu s at code distances d \leq 11, aligning closely with experimental data from state-of-the-art superconducting quantum processors.     Moreover, we quantify the detrimental impact of non-Markovian fBm noise on Quantum Key Distribution (QKD) protocols, demonstrating that increasing the Hurst exponent H from 0.5 (white noise) to 0.7 (correlated noise) elevates the Quantum Bit Error Rate (QBER) by approximately 15% and reduces the secure key generation rate by 10–12%, in excellent agreement with experimental results from ID Quantique and the Micius satellite.     All numerical data, simulation codes, and detailed parameters are available upon request via our dedicated GitHub repository, ensuring reproducibility and facilitating future experimental validation and advancement in quantum information technologies.     Note for LaTeX Users:  This manuscript was originally written in a Japanese text environment, resulting in Yen symbols (¥) in place of standard LaTeX backslashes (). Users intending to compile or use the equations should replace all instances of ‘¥’ with ‘\’ to properly format LaTeX mathematical expressions.     Important clarification regarding previous publications:  All previous papers in this series (including the paper dated March 8, 2025) were unintentionally reduced by more than half of their original content due to automated AI summarization. Users are advised to refer to this current manuscript as the authoritative and complete version of the EIC model.     Ethical Statement:  This research is explicitly intended for peaceful purposes and should be used exclusively for the benefit of humanity.
Methodological developments in quantum chemistry: Quantum Monte Carlo methods and density-functional theory

This document summarizes my research activities since 2005 about the development of methods for computing the electronic structure of molecular systems and organized into two themes: (1) Quantum Monte Carlo (QMC) methods: I developed several aspects of QMC methods in order to be able to do reference calculations in quantum chemistry (wave-function optimization method for ground and excited states, new forms of explicitly correlated wave functions, and improved statistical estimators for observables); (2) Density-functional theory (DFT): In order to improve the accuracy of present-day DFT, I developed several methods which rigorously combine DFT with correlated wave-function calculations by using a decomposition of the electron-electron interaction (range-separated hybrids, "double-hybrid" approximations, and multiconfigurational hybrids).
ANALYSIS OF WORLD EXPERIENCE IN THE INTRODUCTION OF CENTRAL BANK DIGITAL CURRENCIES

The reduction in the use of cash, the emergence of the second wave of digital currencies created by private players, the rapid increase in technical capabilities in the financial sector and the Covid-19 pandemic have raised the urgent issue of the need for the introduction of a digital currency controlled by a state financial authority of different countries of the world. To understand the plans and prospects of further actions of the central banks of different countries, including Ukraine, regarding the studies, conduction of pilot projects and introduction of the central bank digital currencies (CBDC), an actual monitoring and analysis of the current situation and the results of the work that was already done regarding CBDC should be carried out. The scientific article is aimed at studying the current state of implementation of CBDCs in different countries. The scientific article analyzes the current state of implementation of the CBDCs by the world's leading countries, as well as their motivation and direction of their studies regarding the type of CBDCs. In order to conduct a thorough analysis a list of the countries that conduct research and start implementing the CBDCs, their digital currencies, projects and used technologies had to be done. Next, we had to study ways of cooperation between the central banks of the world on the implementation of the CBDCs. This brought us to the Bank of International Settlements, its functions, actions and working papers which include the data about the work of world’s central banks for last few years regarding the CBDC. The paper analyzes the dynamics of the CBDC implementation and the steps taken by the world's central banks in this direction. Also, a comparative analysis of the mood of central banks around the world was also conducted, based on the type of CBDC implemented and the readiness of the legal framework for the issuance of CBDC. Then, we structured the effectiveness of the used strategies of research and implementation of the CBDC by central banks of different countries of the world. After analysis the data, structuring and comparing the projects of central banks different countries (different both in size and development level) which are trying to implement CBDC in their financial system, we have made forecasts and prospects of practical application of the CBDCs.
Epigenetic Regulation: Chromatin Modeling and Small RNAs

Epigenetic mechanisms, namely histone modifications and DNA methylation induced changes in the chromatin, give rise to epigenomes, which add diversity and complexity to the genome of organisms. Epigenetic modifications play a pivotal role in genomic imprinting, paramutation, defense against transposon proliferation and regulation of gene expression. Specific combinations of histone N-tail modifications can be considered a histone code, which determines the chromatin structure and thus regulates transcription. Cytosine methylation of DNA is a ubiquitous epigenetic mark in diverse species. Asymmetric methylation is re-established after every mitosis cycle, whereas symmetric methylation can be maintained through mitosis and may even be transmitted through meiosis. Abiotic stresses and plant hormones induce epigenetic changes, which can lead to altered gene expression and recombination. ABA induces chromatin remodeling by histone H3 acetylation and methylation to regulate gene expression and abiotic stress-induced growth arrest. Submergence-stress induces the expression of alcohol dehydrogenase (ADH1) and pyruvate decarboxylase (PDC1) genes in rice through histone H3 trimethylation and acetylation. Further, Arabidopsis HOS15, a component of the chromatin repression complex involved in histone deacetylation, plays a key role in freezing stress tolerance. Besides these histone modifications, abiotic stresses also induce a change in DNA methylation. Cold, osmotic, salt, heavy-metal stresses and plant hormones can induce DNA demethylation or hypermethylation at specific loci. Abiotic stresses and plant hormones may also induce the transposition of transposons through DNA hypomethylation. Small RNAs can guide posttranscriptional or transcriptional gene silencing. Stresses like UV-C radiation or the biotic factor - flagellin induces a high frequency of somatic homologous recombination in Arabidopsis and this change is transmitted meiotically across generations probably through epigenetic processes such as DNA hypomethylation. Stress memory, through the epigenetic process, might help plants more effectively combat subsequent incidences of stresses within a generation and might confer an adaptive advantage when meiotically inherited. Further studies on abiotic stress regulated epigenetic processes will help to better understand abiotic stress tolerance of plants.
A Cross-Cultural Leadership Behavior Prediction Model for Advancing Organizational and Global Management Practices

In today’s globally interconnected environment, recognizing culturally preferred leadership behaviors is dynamic for effective organizational and global management. This research presents a cross-cultural leadership behavior prediction model that employs advanced machine learning (ML) techniques to analyze and forecast leadership preferences across diverse cultural contexts. The research gathers data from Kaggle, comprising 6,945 responses across five countries, to analyze behavioral, demographic, and cultural aspects, and employs preprocessing techniques for improved model reliability. The model employs algorithms, such as the Scalable Golden Jackal Optimizer-driven Stacked Random Forest (SGO-SRF) to predict and uncover patterns in leadership behavior preferences. Cultural indicators and demographic features are analyzed using Recursive Feature Elimination (RFE) to identify their impact on these various leadership dimensions. The model was primarily applied using a baseline Random Forest (RF), then established through a Stacked RF approach, and finally optimized using the proposed hybrid SGO-SRF, which attained the highest performance across all evaluation metrics. The hybrid method was implemented in Python and it demonstrated superior performance, achieving higher accuracy (92.11%), F1-scores (88.09%), precision (81.98%), and Recall (85.19%). The research reveals that cultural values significantly influence leadership preferences, with long-term orientation affecting uncertainty tolerance, restraint affecting integration, and entrepreneurial values influencing structure, production emphasis, and predictive performance.
The association between health insurance coverage disruptions and access to care and affordability among cancer survivors in the United States.

121  Background: Having health insurance is a strong predictor of access to care and affordability. To date, most studies evaluating the effects of insurance coverage measured it only at a single time point. Little is known about the effects of coverage disruptions. This study aims to assess associations of a health insurance coverage disruption with access and affordability among cancer survivors in the United States. Methods: We identified 6476 cancer survivors aged 18-64 years with current health insurance coverage from the 2011-2017 National Health Interview Survey. Coverage disruption was measured by the question “In the past 12 months, was there any time when you did not have any health insurance or coverage?”. Access to care and affordability was measured by: 1) preventive services use (e.g. blood pressure check); and 2) forgoing care because of cost, respectively, in the past 12 months. We used separate multivariable logistic models to evaluate the associations between a coverage disruption and healthcare access and affordability, by current health insurance coverage. Results: Among survivors with current health insurance coverage, 3.7% of those with private and 8.1% with public insurance reported a coverage disruption in the past 12 months. Among survivors with current private coverage, those with a recent coverage disruption reported lower likelihood of any preventive services use (OR = 0.1, 95% CI: 0.1-0.3) and higher likelihood of forgoing any care because of cost (OR = 6.0, 95% CI: 3.9-9.5) compared to those with continuous private coverage. Among survivors with current public coverage, those with a recent coverage disruption reported lower likelihood of any preventive services use (OR = 0.4, 95% CI: 0.2-0.9) and higher likelihood of forgoing any care because of cost (OR = 4.3, 95% CI: 2.5-7.3) compared to those with continuous public coverage. Conclusions: Currently insured cancer survivors with a recent health insurance coverage disruption were more likely to report problems in access to care and affordability compared to the continuously insured. Improving private and public insurance coverage continuity may be effective in addressing these problems.
Material Visions: Advancing Crystal Structure Prediction with Powerful Text Generation Models

The discovery of new materials has been a protracted and labor-intensive endeavor, relying on iterative trial-and-error methodologies. Recently, materials informatics has been transforming this process by employing advanced data science and computational tools to expedite the discovery of novel materials, such as generative design material formulas, and predict material properties. However, predicting crystal three-dimensional structures remains a challenging task rooted in both the fundamental nature of materials and the limitations of current computational methods. Inspired by the power and success of artificial intelligence (AI) models, especially the deep learning techniques and natural language processing (NLP) algorithms, we consider capturing complex atom descriptions and relationships as text information and explore whether we can use the ability of language models to predict atomic coordinates. In this work, we explore multiple text generation models and employ the Longformer-Encoder-Decoder (LED) model to construct preliminary crystal structures based on detailed atom descriptions. Subsequently, these structures are further refined by a random forest regressor, which generates the final crystal configurations. Our experiments show this method excels in capturing the intricate atom relationships and effectively translating these associations into the specified crystal formats. We also focus on optimizing data representation for both atom descriptions and crystal structures and use clear metrics to evaluate accuracy and stability. Our results indicate that this method has promising potential and could improve the prediction of material crystal structures. Our source code can be accessed freely at https://github.com/RMaarefdoust/Crystal-Structure-Prediction.
Method of local‐scaling transformations and density‐functional theory in quantum chemistry

AbstractThe method of local‐scaling transformations is developed with a view to applications of the nonrelativistic quantum mechanical variational principle in quantum chemistry. Some properties of local‐scaling transformations are studied. The method presented links local‐scaling transformations and one‐electron densities via the ordinary differential equation that provides a proof of the theorem on the existence of the energy density functional within any given orbit and its universality in a sense of the general theory of ordinary differential equations, and allows the construction of this functional explicitly.
Forecasting Global Weather with Graph Neural Networks

We present a data-driven approach for forecasting global weather using graph neural networks. The system learns to step forward the current 3D atmospheric state by six hours, and multiple steps are chained together to produce skillful forecasts going out several days into the future. The underlying model is trained on reanalysis data from ERA5 or forecast data from GFS. Test performance on metrics such as Z500 (geopotential height) and T850 (temperature) improves upon previous data-driven approaches and is comparable to operational, full-resolution, physical models from GFS and ECMWF, at least when evaluated on 1-degree scales and when using reanalysis initial conditions. We also show results from connecting this data-driven model to live, operational forecasts from GFS.
Whither the Responsibility to Protect? Humanitarian Intervention and the 2005 World Summit

At the 2005 World Summit, the world‘s leaders committed themselves to the “responsibility to protect”, recognizing both that all states have a responsibility to protect their citizens from genocide, war crimes, ethnic cleansing and crimes against humanity and that the UN should help states to discharge this responsibility using either peaceful means or enforcement action. This declaration ostensibly marks an important milestone in the relationship between sovereignty and human rights but its critics argue that it will make little difference in practice to the world’s most threatened people. The purpose of this article is to ask how consensus was reached on the responsibility to protect, given continuing hostility to humanitarian intervention expressed by many (if not most) of the world‘s states and whether the consensus will contribute to avoiding future Kosovos (cases where the Security Council is deadlocked in the face of a humanitarian crises) and future Rwandas (cases where states lack the political will to intervene). It suggests that four key factors contributed to the consensus: pressure from proponents of the International Commission on Intervention and State Sovereignty, its adoption by Kofi Annan and the UN’s High Level Panel, an emerging consensus in the African Union, and the American position. Whilst these four factors contributed to consensus, each altered the meaning of the responsibility to protect in important ways, creating a doctrine that many states can sign up to but that does little to prevent future Kosovos and Rwandas and may actually inhibit attempts to build a consensus around intervention in future cases.
Fast and Scalable GPU-Accelerated Quantum Chemistry for Periodic Systems with Gaussian Orbitals: Implementation and Hybrid Density Functional Theory Calculations

Efficient hybrid DFT simulations of solid state materials would be extremely beneficial for computational chemistry and materials science, but is presently bottlenecked by difficulties in computing Hartree-Fock (HF) exchange with plane wave orbital bases. We present a GPU-accelerated, Gaussian orbital based integral algorithm for systems with periodic boundary conditions, which takes advantage of Ewald summation to efficiently compute electrostatic interactions. We have implemented this approach into the TeraChem software package within the $Γ$ point approximation, enabling simulation of unit cells with hundreds or thousands of atoms at the HF or hybrid DFT level on a single GPU card. Our implementation readily parallelizes over multiple GPUs and paves the road to accurate simulation of the properties and dynamics of extended materials in both the ground and excited states.
Beta blocker use in traumatic brain injury based on the high-sensitive troponin status (BBTBBT): methodology and protocol implementation of a double-blind randomized controlled clinical trial

Abstract                 Background                 Beta-adrenergic receptor blockers (BB) play an important role in the protection of organs that are susceptible for secondary injury due to stress-induced adrenergic surge. However, the use of BB in traumatic brain injury (TBI) patients is not yet the standard of care which necessitates clear scientific evidence to be used. The BBTBBT study aims to determine whether early administration of propranolol based on the high-sensitive troponin T(HsTnT) status will improve the outcome of TBI patients. We hypothesized that early propranolol use is effective in reducing 10- and 30-day mortality in TBI patients. Secondary outcomes will include correlation between serum biomarkers (troponin, epinephrine, cytokines, enolase, S100 calcium binding protein B) and the severity of injury and the impact of BB use on the duration of hospital stay and functional status at a 3-month period.                                Methods                 The BBTBBT study is a prospective, randomized, double-blinded, placebo-controlled three-arm trial of BB use in mild-to-severe TBI patients based on the HsTnT status. All enrolled patients will be tested for HsTnT at the first 4 and 6 h post-injury. Patients with positive HsTnT will receive BB if there is no contraindication (group 1). Patients with negative HsTnT will be randomized to receive either propranolol (group 2) or placebo (group 3). The time widow for receiving the study treatment is the first 24 h post-injury.                                Discussion                 Early BB use may reduce the catecholamine storm and subsequently the cascade of immune and inflammatory changes associated with TBI. HsTnT could be a useful fast diagnostic and prognostic tool in TBI patients. This study will be of great clinical interest to improve survival and functional outcomes of TBI patients.                                Trial registration                 ClinicalTrials.gov NCT04508244. Registered on 7 August 2020. Recruitment started on 29 December 2020 and is ongoing.
Systematic studies of general structural characteristics of organic molecular crystals and prediction of their structures

A strategy is developed for constructing noncentrosymmetric (polar) packings of crystals necessary for the manifestation of a number of important physical properties of crystals. The strategy is based on the analysis of the data obtained in the systematic studies of general structural characteristics of pairs of centro-and noncentrosymmetric polymorphic modifications of a number of organic molecular structures. An algorithm for prediction of such packings is designed on the basis of the potential function singled out by the method of automatic statistical search for information (Data Mining) in the Cambridge Structural Database.
Sociobiodiversity and Sovereignty and Food and Nutritional Security as an inseparable right to adequate and healthy food

La biodiversidad es esencial para una vida digna y justa. Así, este estudio tuvo como objetivo contextualizar la sociobiodiversidad y Soberanía y Seguridad Alimentaria y Nutricional (SSAN) como un derecho inseparable a una alimentación adecuada y saludable. Las búsquedas se realizaron en el sitio web de periódicos del CAPES, FSTA - Food Science and Technology Science Direct, SciELO, Google Académico, literatura gris y en el portal de las Naciones Unidas (ONU); Ministerio de Medio Ambiente – MMA en Brasil, Biodiversidad para la Alimentación y la Nutrición - BFN y legislación específica sobre el tema estudiado. La revisión mostró la importancia de las estrategias de sistemas alimentarios saludables y sostenibles, a través de acciones transversales en las políticas de gobernanza para mitigar la injusticia social, impulsar la economía de las personas, promover la biodiversidad, la sostenibilidad y las acciones de SSAN como derecho a una alimentación adecuada y saludable. Estas acciones promueven la generación de empleo, ingresos y mejor calidad de vida de familias campesinas, comunidades tradicionales, productores agroecológicos y colonos de la reforma agraria que tienen la tierra como medio de vida. Además, promueven el medio ambiente sostenible como meta para el ODS 2030, ayudando a la humanidad a enfrentar los desafíos globales de la injusticia social como el derecho a una alimentación adecuada y saludable.
Science Communication Training Imparts Confidence and Influences Public Engagement Activity

The impacts of science are felt across all socio-ecological levels, ranging from the individual to societal. In order to adapt or respond to scientific discoveries, novel technologies, or biomedical or environmental challenges, a fundamental understanding of science is necessary.