Results 91 to 100 of about 1,338,681 (301)

Decoupling the Size and Loading Effects in Silver Nanoparticles for Efficient Paired Carbon Dioxide and Formaldehyde Electrolysis

open access: yesAdvanced Functional Materials, EarlyView.
We investigate size‐dependent CO selectivity on Ag nanoparticles, where optimized Ag loading achieves nearly 100% Faradaic Efficiency for CO at −100 mA·cm−2. In situ SERS and XPS reveal the crucial role of optimized loading in catalytic performance. The Ag/C catalyst further exhibits bifunctional activity, enabling efficient electrolysis of CO2 and ...
Venkata S. R. K. Tandava   +16 more
wiley   +1 more source

Robust Estimation of Mean and Dispersion Functions in Extended Generalized Additive Models [PDF]

open access: yes
Generalized Linear Models are a widely used method to obtain parametric es- timates for the mean function. They have been further extended to allow the re- lationship between the mean function and the covariates to be more flexible via Generalized ...
Gijbels, I., Prosdocimi, I., Croux, C.
core   +2 more sources

Analysis of Robust Quasi-deviances for Generalized Linear Models

open access: yesJournal of Statistical Software, 2004
Generalized linear models (McCullagh and Nelder 1989) are a popular technique for modeling a large variety of continuous and discrete data. They assume that the response variables Yi , for i = 1, . . .
Eva Cantoni
doaj   +1 more source

Structure‐Guided Balancing of Ambipolar Transport Enables Symmetric Switching in Heterojunction Bilayer Organic Transistor Inverters

open access: yesAdvanced Functional Materials, EarlyView.
Balancing the spatially separated p‐ and n‐type transport pathways in heterojunction‐bilayer OTFTs enables symmetric inverter switching (VM ≈ 0.5VDD), whereas discrete integration of unipolar OTFTs gives polarity‐dependent and resistive responses. ABSTRACT High inverter performance in ambipolar organic electronics requires balanced channel strengths ...
Sohyun Choi   +3 more
wiley   +1 more source

Nonparametric estimation of mean and dispersion functions in extended generalized linear models. [PDF]

open access: yes
In this paper the interest is in regression analysis for data that show possibly overdispersion or underdispersion. The starting point for modeling are generalized linear models in which we no longer admit a linear form for the mean regression function ...
Prosdocimi, Ilaria   +2 more
core  

Sub‐1 ms Optoelectronic Synapse Based on {ZnCdO/ZnO} Multilayer Structure for High‐Speed Neuromorphic Vision Systems

open access: yesAdvanced Functional Materials, EarlyView.
Eu‐doped {ZnCdO/ZnO} structures grown on Si are developed, showcasing dual‐functionality controlled by europium doping. While high europium concentration transforms the device into an ultrafast, self‐powered photodetector, low‐doped structures can be used as an optoelectronic synapse.
Igor Perlikowski   +3 more
wiley   +1 more source

Nonparametric Quasi-likelihood in Longitudinal Data Analysis [PDF]

open access: yes, 2004
This dissertation proposes a nonparametric quasi-likelihood approach to estimate regression coefficients in the class of generalized linear regression models for longitudinal data analysis, where the covariance matrices of the longitudinal data are ...
Jiang, Xiaoping
core   +1 more source

A flexible quasi-likelihood model for microbiome abundance count data. [PDF]

open access: yesStat Med, 2023
Shi Y   +9 more
europepmc   +1 more source

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

A New Partially Linear Regression with an Application to the Price of Coffee Before and After the Pandemic

open access: yesStats
We propose a partially linear regression linear model to explain coffee prices before and after the COVID-19 pandemic. This new regression model incorporates the fundamental assumption of linearity and nonlinearity between these variables.
Edwin M. M. Ortega   +3 more
doaj   +1 more source

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