Results 111 to 120 of about 428,031 (297)

Micropillar‐Engineered Hybrid Adhesive Patch for Surface‐Conformable and Directional Adhesion

open access: yesAdvanced Materials Technologies, EarlyView.
This work presents a surface‐conformable hybrid adhesive integrating height‐optimized hexagonal micropillars with open‐rectangular cuts. The micropillars enhance rough‐surface contact and microscale crack arrest, while the cuts guide and reverse interfacial cracks for strong and directional adhesion. The multiscale architecture achieves robust pull‐off
Seongjin Park   +4 more
wiley   +1 more source

Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension [PDF]

open access: yes
Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated.
Henderson, Daniel J.   +1 more
core  

Identification of Nonlinear Parameter-Dependent Common-Structured models to accommodate varying experimental conditions and design parameter properties [PDF]

open access: yes, 2006
This study considers the identification problem for a class of nonlinear parameter-varying systems associated with the following scenario: the system behaviour depends on some specifically prescribed parameter properties, which are adjustable.
Billings, S.A., Lang, Z.Q., Wei, H.L.
core  

Microfluidic Engineering of Chitosan‐Coated Nanoemulsions for Controlled Release and Stability in Space Pharmaceutics

open access: yesAdvanced Materials Technologies, EarlyView.
Microfluidic engineering enables the fabrication of chitosan‐coated, melatonin‐loaded nanoemulsions with controlled release and enhanced physicochemical stability for space pharmaceutics. Interfacial biopolymer coating modulates droplet behavior under accelerated thermal stress and simulated microgravity.
Modupe Adebowale   +3 more
wiley   +1 more source

Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models [PDF]

open access: yes
In linear specifications, the bias due to the presence of measurement error in a regressor can be entirely avoided when either repeated measurements or instruments are available for the mismeasured regressor.
Susanne M. Schennach
core  

A Pressure Microsensor Made of Parylene‐C for Use as Medical Implant

open access: yesAdvanced Materials Technologies, EarlyView.
A monolithic parylene‐C pressure sensor with gold strain gauges provides 6.2 μV$\mu{\rm V}$·mmHg$\cdot{\rm mmHg}$−1$^{-1}$ sensitivity. The morphology of a sputtered thin film strain sensor is granular/columnar, which results in a high gauge factor of 7.5. Thermal bonding and parylene‐C coating create a hermetic cavity.
Ann‐Kathrin Klein   +2 more
wiley   +1 more source

Specification Tests Based on Artificial Regressions [PDF]

open access: yes
Many specification tests can be computed by means of artificial linear regressions. These are linear regressions designed to be used as calculating devices to obtain test statistics and other quantities of interest.
James G. MacKinnon, Russell Davidson
core  

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

open access: yesAdvanced Materials Technologies, EarlyView.
ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point ...
Mohsen Hassani   +9 more
wiley   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov   +3 more
wiley   +1 more source

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