scholarly journals Application of Chemometrics in Biosensing: A Brief Review

Biosensors ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 100 ◽  
Author(s):  
Ekaterina Martynko ◽  
Dmitry Kirsanov

The field of biosensing is rapidly developing, and the number of novel sensor architectures and different sensing elements is growing fast. One of the most important features of all biosensors is their very high selectivity stemming from the use of bioreceptor recognition elements. The typical calibration of a biosensor requires simple univariate regression to relate a response value with an analyte concentration. Nevertheless, dealing with complex real-world sample matrices may sometimes lead to undesired interference effects from various components. This is where chemometric tools can do a good job in extracting relevant information, improving selectivity, circumventing a non-linearity in a response. This brief review aims to discuss the motivation for the application of chemometric tools in biosensing and provide some examples of such applications from the recent literature.

Author(s):  
Gwendolyn Rehrig ◽  
Reese A. Cullimore ◽  
John M. Henderson ◽  
Fernanda Ferreira

Abstract According to the Gricean Maxim of Quantity, speakers provide the amount of information listeners require to correctly interpret an utterance, and no more (Grice in Logic and conversation, 1975). However, speakers do tend to violate the Maxim of Quantity often, especially when the redundant information improves reference precision (Degen et al. in Psychol Rev 127(4):591–621, 2020). Redundant (non-contrastive) information may facilitate real-world search if it narrows the spatial scope under consideration, or improves target template specificity. The current study investigated whether non-contrastive modifiers that improve reference precision facilitate visual search in real-world scenes. In two visual search experiments, we compared search performance when perceptually relevant, but non-contrastive modifiers were included in the search instruction. Participants (NExp. 1 = 48, NExp. 2 = 48) searched for a unique target object following a search instruction that contained either no modifier, a location modifier (Experiment 1: on the top left, Experiment 2: on the shelf), or a color modifier (the black lamp). In Experiment 1 only, the target was located faster when the verbal instruction included either modifier, and there was an overall benefit of color modifiers in a combined analysis for scenes and conditions common to both experiments. The results suggest that violations of the Maxim of Quantity can facilitate search when the violations include task-relevant information that either augments the target template or constrains the search space, and when at least one modifier provides a highly reliable cue. Consistent with Degen et al. (2020), we conclude that listeners benefit from non-contrastive information that improves reference precision, and engage in rational reference comprehension. Significance statement This study investigated whether providing more information than someone needs to find an object in a photograph helps them to find that object more easily, even though it means they need to interpret a more complicated sentence. Before searching a scene, participants were either given information about where the object would be located in the scene, what color the object was, or were only told what object to search for. The results showed that providing additional information helped participants locate an object in an image more easily only when at least one piece of information communicated what part of the scene the object was in, which suggests that more information can be beneficial as long as that information is specific and helps the recipient achieve a goal. We conclude that people will pay attention to redundant information when it supports their task. In practice, our results suggest that instructions in other contexts (e.g., real-world navigation, using a smartphone app, prescription instructions, etc.) can benefit from the inclusion of what appears to be redundant information.


Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 320
Author(s):  
Emilio Guirado ◽  
Javier Blanco-Sacristán ◽  
Emilio Rodríguez-Caballero ◽  
Siham Tabik ◽  
Domingo Alcaraz-Segura ◽  
...  

Vegetation generally appears scattered in drylands. Its structure, composition and spatial patterns are key controls of biotic interactions, water, and nutrient cycles. Applying segmentation methods to very high-resolution images for monitoring changes in vegetation cover can provide relevant information for dryland conservation ecology. For this reason, improving segmentation methods and understanding the effect of spatial resolution on segmentation results is key to improve dryland vegetation monitoring. We explored and analyzed the accuracy of Object-Based Image Analysis (OBIA) and Mask Region-based Convolutional Neural Networks (Mask R-CNN) and the fusion of both methods in the segmentation of scattered vegetation in a dryland ecosystem. As a case study, we mapped Ziziphus lotus, the dominant shrub of a habitat of conservation priority in one of the driest areas of Europe. Our results show for the first time that the fusion of the results from OBIA and Mask R-CNN increases the accuracy of the segmentation of scattered shrubs up to 25% compared to both methods separately. Hence, by fusing OBIA and Mask R-CNNs on very high-resolution images, the improved segmentation accuracy of vegetation mapping would lead to more precise and sensitive monitoring of changes in biodiversity and ecosystem services in drylands.


2017 ◽  
Vol 4 (1) ◽  
pp. 191-202 ◽  
Author(s):  
Sayan Dey ◽  
Sumita Santra ◽  
Anupam Midya ◽  
Prasanta Kumar Guha ◽  
Samit Kumar Ray

Nanostructured, Cu-doped nickel oxides serve as excellent, ultra-fast, re-usable heavy metal ion sensors with an ultra-low detection limit and very high selectivity towards toxic Cr(vi) ions.


2019 ◽  
Vol 51 (10) ◽  
pp. 981-988 ◽  
Author(s):  
Xiaolan Rao ◽  
Richard A Dixon

Abstract Co-expression network analysis is one of the most powerful approaches for interpretation of large transcriptomic datasets. It enables characterization of modules of co-expressed genes that may share biological functional linkages. Such networks provide an initial way to explore functional associations from gene expression profiling and can be applied to various aspects of plant biology. This review presents the applications of co-expression network analysis in plant biology and addresses optimized strategies from the recent literature for performing co-expression analysis on plant biological systems. Additionally, we describe the combined interpretation of co-expression analysis with other genomic data to enhance the generation of biologically relevant information.


Author(s):  
Leandro Krug Wives ◽  
José Palazzo Moreira de Oliveira ◽  
Stanley Loh

This chapter introduces a technique to cluster textual documents using concepts. Document clustering is a technique capable of organizing large amounts of documents in clusters of related information, which helps the localization of relevant information. Traditional document clustering techniques use words to represent the contents of the documents and the use of words may cause semantic mistakes. Concepts, instead, represent real world events and objects, and people employ them to express ideas, thoughts, opinions and intentions. Thus, concepts are more appropriate to represent the contents of a document and its use helps the comprehension of large document collections, since it is possible to summarize each cluster and rapidly identify its contents (i.e. concepts). To perform this task, the chapter presents a methodology to cluster documents using concepts and presents some practical experiments in a case study to demonstrate that the proposed approach achieves better results than the use of words.


Author(s):  
Wolff-Michael Roth

To learn by means of analogies, students have to see surface and deep structures in both source and target domains. Educators generally assume that students, presented with images, texts, video, or demonstrations, see what the curriculum designer intends them to see, that is, pick out and integrate information into their existing understanding. However, there is evidence that students do not see what they are supposed to see, which precisely inhibits them to learn what they are supposed to learn. In this extended case study, which exemplifies a successful multimedia application, 3 classroom episodes are used (a) to show how students in an advanced physics course do not see relevant information on the computer monitor; (b) to exemplify teaching strategies designed to allow relevant structures to become salient in students’ perception, allowing them to generate analogies and thereby learn; and (c) to exemplify how a teacher might assist students in bridging from the multimedia context to the real world.


2020 ◽  
Author(s):  
Alon Eden ◽  
Michal Feldman ◽  
Ophir Friedler ◽  
Inbal Talgam-Cohen ◽  
S. Matthew Weinberg

Recent literature on approximately optimal revenue maximization has shown that in settings where agent valuations for items are complement free, the better of selling the items separately and bundling them together guarantees a constant fraction of the optimal revenue. However, most real-world settings involve some degree of complementarity among items. The role that complementarity plays in the trade-off of simplicity versus optimality has been an obvious missing piece of the puzzle. In “A Simple and Approximately Optimal Mechanism for a Buyer with Complements,” the authors show that the same simple selling mechanism—the better of selling separately and as a grand bundle—guarantees a $\Theta(d)$ fraction of the optimal revenue, where $d$ is a measure of the degree of complementarity. One key modeling contribution is a tractable notion of “degree of complementarity” that admits meaningful results and insights—they demonstrate that previous definitions fall short in this regard.


2011 ◽  
Vol 239-242 ◽  
pp. 161-167
Author(s):  
Xiao Zhen Wang ◽  
Yi Feng Zhu ◽  
Xiao Nian Li

A 2 wt % Pd/C catalyst has been prepared by chemical impregnation and used to catalyze the hydrogenation of o-chloronitrobenzene (o-CNB) to o-chloroaniline (o-CAN) in solvent-free conditions. The effects of reaction temperature, H2 pressure, and stirring intensity on the hydrogenation kinetics have been investigated. The hydrogenation reaction showed very high selectivity with dehalogenation side products as low as 0.3% of total yield. The favorable reaction conditions were found to be temperature T = 383 K, stirring speed = 900 rpm, and feeding ratio CNB/catalyst = 200/1 (m/m). The recycled Pd/C still retained more than 98% of its original selectivity after 12 repeat used, indicating the catalyst had strong potentials for commercial application at industrial scale.


Sign in / Sign up

Export Citation Format

Share Document