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A novel method of pattern recognition material design based on differential evolution support vector machine was proposed.
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In order to lead the synthesis of recognition materials, four original AOH surrogates have been designed, prepared and characterized.
We present a critical review of the recent developments in nano- and micro-engineered synthetic recognition materials predominantly used for SAW-based organic vapor sensors.
Molecular imprinted polymers (MIPs) have become an important tool in the preparation of artificial and robust recognition materials capable of mimicking natural systems.
Combined with suitably designed molecular recognition materials SAW devices could develop into highly selective and fast responsive miniaturized sensors, which are capable of continuously monitoring a specific organic gas, preferably in the sub-ppm regime.
Quartz crystal microbalance (QCM) sensors have been designed for a number of analytes i.e. from proteins to cells and pollen by combining these gravimetric detectors with different recognition materials.
Bulk-imprinted artificial recognition materials for DMMP yielded detection limits of 0.2 ppm in air on quartz crystal microbalance (QCM) sensor with selectivity factors of >40 towards indoor background contaminants, such as alcohols or acetic esters.
Highly selective artificial recognition materials can be achieved by nanostructuring matrices and making use of a range of non-covalent intermolecular interactions, such as coordinative bonds, hydrogen bonds, and affinity interactions based on the Pearson hardness of both the analyte and the receptor layer.
In contrast to [14] where the dataset is used to study recognition of material categories we will use images from all four material samples as examples of the same class when training the classifier.
For me it's a very important phrase because it suggests the idea of doing something simply for the beauty and pleasure of it, without necessarily expecting recognition or material return.
Social recognition and material rewards matter too.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com