Results 71 to 80 of about 30,407 (243)

Subtree weight ratios for optimal binary search trees [PDF]

open access: yes, 1986
For an optimal binary search tree T with a subtree S(d) at a distance d from the root of T, we study the ratio of the weight of S(d) to the weight of T.
Hirschberg, D. S.   +2 more
core   +2 more sources

Visual Soil Structure Quality Is Mostly Explained by Small‐Size Structural Pores

open access: yesEuropean Journal of Soil Science, Volume 76, Issue 5, September–October 2025.
ABSTRACT Visual assessment of soil structure receives growing interest but its physical meaning is still to be explored. This study examined the relationships between soil pore systems volume and size distribution and visual structure quality scores in undisturbed soil samples from Swiss cropland soils covering a wide range of soil organic carbon (SOC)
Cédric Deluz   +4 more
wiley   +1 more source

KAJIAN BARISAN FIBONACCI DAN APLIKASINYA PADA SUKU BARISAN YANG POSITIF [PDF]

open access: yes, 2009
In general, the problems that occur in the fibonacci sequence is to determine the n- tribe ( ) . So to find , so please be at least two tribes, regardless of the number-the number that are in sequence if the number is positive ornegative. \ud , From the
Rofitasari, Rosma
core  

AI in Neurology: Everything, Everywhere, All at Once Part 1: Principles and Practice

open access: yesAnnals of Neurology, Volume 98, Issue 2, Page 211-230, August 2025.
Artificial intelligence (AI) is rapidly transforming healthcare, yet it often remains opaque to clinicians, scientists, and patients alike. This review, part 1 of a 3‐part series, provides neurologists and neuroscientists with a foundational understanding of AI's key concepts, terminology, and applications.
Matthew Rizzo, Jeffrey D. Dawson
wiley   +1 more source

Some properties of Fibonacci numbers, Fibonacci octonions, and generalized Fibonacci-Lucas octonions [PDF]

open access: yesAdvances in Difference Equations, 2015
In this paper we determine some properties of Fibonacci octonions. Also, we introduce the generalized Fibonacci-Lucas octonions and we investigate some properties of these elements.
openaire   +3 more sources

From Genes to Shapes: Exploring Local Adaptation in Carpathian Ox‐Eye Daisies

open access: yesJournal of Biogeography, Volume 52, Issue 8, August 2025.
ABSTRACT Aim Historical processes have shaped the Carpathian biogeography, yet ongoing evolutionary forces continue to drive population differentiation. We aimed to test whether local adaptation in the Carpathian subendemic Leucanthemum rotundifolium correlates with genetic, morphological and environmental factors, and to assess how these patterns ...
Kamil Konowalik, Olga Łuczak
wiley   +1 more source

Numerical Analysis on Burn Injury of Human Skin Exposed to Varying Flash Fire Conditions

open access: yesEngineering Reports, Volume 7, Issue 7, July 2025.
A 3D prototype model of human skin, comprising epidermis, dermis, and subcutaneous tissue, analyzes temperature impacts for flash fire Q = 83,200 W/m2, conductivity (ke = 0.21, kd = 0.37, ks = 0.16) and specific heat capacities (Cpe = 3578, Cpd = 3200, Cps = 2288).
Salma Parvin   +4 more
wiley   +1 more source

A General Approach to Predict and Tailor the Nanoscale Permeability of Comb‐Shaped Polymer Coatings

open access: yesSmall Methods, Volume 9, Issue 7, July 19, 2025.
Comb‐shaped polymers are used to produce ‘molecular sieving’ coatings. The steric and size‐selective permeability characteristics of comb‐polymer coatings are systematically explored in silico across a very broad parameter space. All features of the data can be understood when three distinct regimes are considered: i) no‐interactions, ii) weak ...
Nicole Drossis   +2 more
wiley   +1 more source

Cubic binomial Fibonacci sums [PDF]

open access: yesElectronic Journal of Mathematics, 2021
Kunle Adegoke   +2 more
doaj   +1 more source

TEEMLEAP—A New Testbed for Exploring Machine Learning in Atmospheric Prediction for Research and Education

open access: yesJournal of Advances in Modeling Earth Systems, Volume 17, Issue 7, July 2025.
Abstract In the past 5 years, data‐driven prediction models and Machine Learning (ML) techniques have revolutionized weather forecasting. Meteorological services around the world are now developing ML components to enhance (or even replace) their numerical weather prediction systems.
J. Wilhelm   +9 more
wiley   +1 more source

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