Results 131 to 140 of about 451,682 (258)

An Object-Oriented Framework for Statistical Simulation: The R Package simFrame

open access: yesJournal of Statistical Software, 2010
Simulation studies are widely used by statisticians to gain insight into the quality of developed methods. Usually some guidelines regarding, e.g., simulation designs, contamination, missing data models or evaluation criteria are necessary in order to ...
Andreas Alfons   +2 more
doaj  

Nitride MXenes Beyond Carbides: Bridging the Gap Between Computational Prediction and Experimental Realization

open access: yesAdvanced Functional Materials, EarlyView.
Nitride MXenes remain constrained by a persistent gap between computational prediction and experimental realization. This Review identifies the thermodynamic, kinetic, and chemical barriers limiting their synthesis, critically evaluates emerging fabrication routes, and proposes a multidimensional computational‐experimental framework to accelerate the ...
Naresh Varnakavi, Masoud Soroush
wiley   +1 more source

Comparison of Isolation Forest and Clustering Methods for Outlier Detection [PDF]

open access: yes
openIn this thesis, we study the relationship between the notion of outlier employed by Isolation Forest and the 3-approximation algorithm for solving the k-center with z outliers problem. Both algorithms’ strategy is influenced by the concept of density,
BEJAJ, XHACU
core  

Near‐Infrared Light‐Activated Polydopamine Nanoparticles Conjugated With Transferrin Peptides for Enhanced Brain Accumulation

open access: yesAdvanced Healthcare Materials, EarlyView.
This study demonstrates that Tf‐PDA NPs combine a receptor‐mediated targeting with mild photothermal activation to enhance nanoparticle accumulation in the brain. NIR‐activated Tf‐PDA NPs increase BBB permeability to NPs in vitro and in vivo without inducing cytotoxicity or adverse immune responses.
Rafaela Ferrão   +5 more
wiley   +1 more source

Comparing probabilistic methods for outlier detection. [PDF]

open access: yes
This paper compares the use of two posterior probability methods to deal with outliers in linear models. We show that putting together diagnostics that come from the mean-shift and variance-shift models yields a procedure that seems to be more effective ...
Guttman, Irwin, Peña, Daniel
core  

Transparent Perovskite Light‐Emitting Diodes with Conductive Oxide Top Electrodes

open access: yesAdvanced Materials, EarlyView.
Transparent perovskite light‐emitting diodes (TrPeLEDs) enable simultaneous display and transparency, expanding application possibilities. Using a metal oxide buffer layer and pulsed laser deposition, TrPeLEDs with diverse compositions and architectures are demonstrated.
Michele Forzatti   +11 more
wiley   +1 more source

Robust regression in Stata. [PDF]

open access: yes
In regression analysis, the presence of outliers in the data set can strongly distort the classical least squares estimator and lead to unreliable results.
Croux, Christophe, Verardi, Vincenzo
core  

Azobenzene's Cross‐Scale Optics and Photonics: Molecular Photoswitching, Mesoscopic Material Motions, and Adaptive Devices

open access: yesAdvanced Materials, EarlyView.
Azobenzene photoswitches translate molecular‐scale E/Z photoisomerization into macroscopic material responses and device‐level photonic functions. This Review highlights how azobenzene research has evolved from molecular photochemistry to photoalignment, mass migration, photomechanics, and heat release, ultimately enabling holography, reconfigurable ...
Heeju Son   +20 more
wiley   +1 more source

Robust Forecasting of Non-Stationary Time Series [PDF]

open access: yes
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency.
Mahieu, K.   +3 more
core  

Data‐Driven Materials Science for Energy‐Sustainable Applications

open access: yesAdvanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

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