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Finite element analysis on the near field properties of metallic cavities with atomic sharpness

Qiyuan Dai, Liang Ma, Li Li, Guangjun Tian • Results in Physics (2023)

Using finite element calculations, we investigated the near field properties of two types of commonly used metal nanostructures (a tip-substrate model representing a scanning tunneling microscope type setup (TS) and a nanoparticle-on-mirror...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rinp.2023.106360

Explainable machine learning in materials science

Xiaoting Zhong, Brian J. Gallagher, Shusen Liu, Bhavya Kailkhura et al. • npj Computational Materials (2022)

Abstract Machine learning models are increasingly used in materials studies because of their exceptional accuracy. However, the most accurate machine learning models are usually difficult to explain. Remedies to this problem lie in explaina...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41524-022-00884-7

Phase-field models in materials science

Ingo Steinbach • Modelling and Simulation in Materials Science and Engineering (2009)

The phase-field method is reviewed against its historical and theoretical background. Starting from Van der Waals considerations on the structure of interfaces in materials the concept of the phase-field method is developed along historical...

OPENALEX DOI: https://doi.org/10.1088/0965-0393/17/7/073001

Is there a relationship between research sponsorship and publication impact? An analysis of funding acknowledgments in nanotechnology papers.

Jue Wang, Philip Shapira • PLoS ONE (2015)

This study analyzes funding acknowledgments in scientific papers to investigate relationships between research sponsorship and publication impacts. We identify acknowledgments to research sponsors for nanotechnology papers published in the ...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0117727

Roles of the peroxisome proliferator-activated receptors (PPARs) in the pathogenesis of diabetic kidney disease (DKD)

Zhi Zheng, Yunkuo Li, Yujie Pan • Cell Death Discovery (2026)

Abstract Diabetic kidney disease (DKD), a prevalent microvascular complication of diabetes, is a leading cause of chronic kidney disease and end-stage renal disease. Moreover, it plays a crucial role in the morbidity and mortality of diabet...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41420-026-03117-8

Nanotechnology and Cancer

James R. Heath, Mark E. Davis • Annual Review of Medicine (2007)

The biological picture of cancer is rapidly advancing from models built from phenomenological descriptions to network models derived from systems biology, which can capture the evolving pathophysiology of the disease at the molecular level....

OPENALEX Open Access DOI: https://doi.org/10.1146/annurev.med.59.061506.185523 PMC: 3706454

Balagrae in the light of new discoveries at the campus of Omar al-Mukhtar University

Dr.Moftah Othman, Dr.Saleh al-Agab, M.Mohamed Al- Touati • مجلة الاتحاد العام للأثاريين العرب (2019)

As a result of the excavation work carried out by the Turkish company for the purpose of building an additional building beside the central library of the University of Omar al- Mukhtar discovered an archaeological site at a depth of a mete...

DOAJ Open Access (DOAJ) DOI: 10.21608/JGUAA.2019.6304.1034

The Archaeology of Rank

Paul K. Wason • Cambridge University Press eBooks (1994)

Social archaeology is concerned with how one might use the archaeological record of the present to elucidate how social interactions were ordered in a past society. This requires a meaningful model of society, considerable archaeological da...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511521195

Models in Archaeology

David L. Clarke • Routledge eBooks (2014)

This major study reflects the increasing significance of careful model formation and testing in those academic subjects that are struggling from intuitive and aesthetic obscurantism toward a more disciplined and integrated approach to their...

OPENALEX DOI: https://doi.org/10.4324/9781315748474

Symbolic and Structural Archaeology

• Cambridge University Press eBooks (1982)

This volume presents a searching critique of the more traditional archaeological methodologies and interpretation strategies and lays down a firm philosophical and theoretical basis for symbolist and structuralist studies in archaeology. A ...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511558252

Obtaining new resolutions in carnivore tooth pit morphological analyses: A methodological update for digital taphonomy.

Lloyd A Courtenay, Darío Herranz-Rodrigo, Rosa Huguet, Miguel Ángel Maté-González et al. • PLoS ONE (2020)

Modern day investigation in fields of archaeology and palaeontology can be greatly characterised by an exponential growth of integrated new technologies, nevertheless, while these advances are of great significance to multiple lines of rese...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0240328

Handbook of Archaeological Sciences

A. Mark Pollard, Don R. Brothwell • University of Groningen research database (University of Groningen / Centre for Information Technology) (2001)

List of Contributors. Foreword: Martin Aitken FRS. Acknowledgements. Introduction: Archaeological Science: A current Perspective (D. Brothwell & A. Pollard). DATING.Overview -- Dating in Archaeology: Past, Present and Future (R. Hedges). Qu...

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A Generic Formula and Some Special Cases for the Kullback–Leibler Divergence between Central Multivariate Cauchy Distributions

Nizar Bouhlel, David Rousseau • Entropy (2022)

This paper introduces a closed-form expression for the Kullback–Leibler divergence (KLD) between two central multivariate Cauchy distributions (MCDs) which have been recently used in different signal and image processing applications where ...

DOAJ Open Access (DOAJ) DOI: 10.3390/e24060838

Core Scouring Dynamics and Gravitational Wave Consequences: Constraints on Supermassive Black Hole Binary Hardening

C. J. Harris, Kayhan Gültekin, Laura Blecha • The Astrophysical Journal (2026)

We present a multimessenger investigation of supermassive black hole binary (SBHB) hardening by jointly comparing models to the observed stellar mass deficits of nearby core galaxies and to nanohertz gravitational-wave background measuremen...

DOAJ Open Access (DOAJ) DOI: 10.3847/1538-4357/ae9767

Testing the Physical Parameter Constraining Power of HCN and HNC with Neural Networks

Erica Behrens, Jeffrey G. Mangum, Mathilde Bouvier, Cosima Eibensteiner et al. • The Astrophysical Journal (2026)

We quantify the utility of HCN and HNC to characterize gas conditions in the nearby starburst galaxy NGC 253. We use measurements from the Atacama Large Millimeter/Submillimeter Array (ALMA) Large Program ALCHEMI: the ALMA Comprehensive Hig...

DOAJ Open Access (DOAJ) DOI: 10.3847/1538-4357/ae3567

Constraining young massive cluster properties with radio-continuum observations: The Arches cluster

Cano-González M., Schödel R., Alberdi A., Najarro F. et al. • Astronomy & Astrophysics (2026)

Context. The Arches cluster, located in the Galactic Centre (GC) is one of the best astrophysical laboratories to study the properties of massive stars and young massive clusters (YMCs). However, despite having been observed for decades at ...

DOAJ Open Access (DOAJ) DOI: 10.1051/0004-6361/202660846

Integrability from point symmetries in a family of cosmological Horndeski Lagrangians

N. Dimakis, Alex Giacomini, Andronikos Paliathanasis • European Physical Journal C: Particles and Fields (2017)

Abstract For a family of Horndeski theories, formulated in terms of a generalized Galileon model, we study the integrability of the field equations in a Friedmann–Lemaître–Robertson–Walker space-time. We are interested in point transformati...

DOAJ Open Access (DOAJ) DOI: 10.1140/epjc/s10052-017-5029-9

Power Load Probabilistic Prediction Based on Multi-Value Quantile Regression and Timing Fusion Ensemble Learning Model

Yuhang Liu, Fei Mei, Jun Zhang, Xiang Dai et al. • Entropy (2026)

The core component to ensure the refined and safe operation of distribution network scheduling is 10 kV bus load probabilistic prediction. However, existing probabilistic prediction methods suffer from insufficient dynamic feature extractio...

DOAJ Open Access (DOAJ) DOI: 10.3390/e28030329