scholarly journals Electrochemical Detection of Glucose Molecules Using Laser-Induced Graphene Sensors: A Review

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2818
Author(s):  
Jingrong Gao ◽  
Shan He ◽  
Anindya Nag
Keyword(s):  
Electrochemical Detection ◽  
Roll To Roll ◽  
Wide Range ◽  
Induction Technique ◽  
Metallic Nanomaterials ◽  
Categorical Classification ◽  
The Many ◽  
Laser Induction ◽  
Second Category

This paper deals with recent progress in the use of laser-induced graphene sensors for the electrochemical detection of glucose molecules. The exponential increase in the exploitation of the laser induction technique to generate porous graphene from polymeric and other naturally occurring materials has provided a podium for researchers to fabricate flexible sensors with high dynamicity. These sensors have been employed largely for electrochemical applications due to their distinct advantages like high customization in their structural dimensions, enhanced characteristics and easy roll-to-roll production. These laser-induced graphene (LIG)-based sensors have been employed for a wide range of sensorial applications, including detection of ions at varying concentrations. Among the many pivotal electrochemical uses in the biomedical sector, the use of these prototypes to monitor the concentration of glucose molecules is constantly increasing due to the essentiality of the presence of these molecules at specific concentrations in the human body. This paper shows a categorical classification of the various uses of these sensors based on the type of materials involved in the fabrication of sensors. The first category constitutes examples where the electrodes have been functionalized with various forms of copper and other types of metallic nanomaterials. The second category includes other miscellaneous forms where the use of both pure and composite forms of LIG-based sensors has been shown. Finally, the paper concludes with some of the possible measures that can be taken to enhance the use of this technique to generate optimized sensing prototypes for a wider range of applications.

2. The different types of trust

2018 ◽  
Author(s):  
Richard Clements ◽  
Ademola Abass
Keyword(s):  
Modern World ◽  
Family Wealth ◽  
Wide Range ◽  
The Family ◽  
Different Types ◽  
Complete Series ◽  
Explanatory Text ◽  
The Many ◽  
Primary Materials

Titles in the Complete series combine extracts from a wide range of primary materials with clear explanatory text to provide readers with a complete introductory resource. This chapter examines the different types of trust, how they are used, and the nature of a trust. The many uses of trusts in the modern world, from pensions to the ownership of the family home and the preservation of family wealth are explained. The discussions cover the meanings of trust and property; what trusts are used for; what an equitable interest is; classification of trusts; resulting trusts; constructive trusts; implied trusts; Quistclose-type trusts; and wills and intestacies.

The Many Pasts of Detective Fiction

2020 ◽  
Vol 1 (2) ◽  
pp. 157-172
Author(s):  
Thomas Leitch
Keyword(s):  
Detective Fiction ◽  
Golden Age ◽  
Public History ◽  
Detective Novel ◽  
Sherlock Holmes ◽  
Detective Story ◽  
The Past ◽  
Wide Range ◽  
Detective Novels ◽  
The Many

Building on Tzvetan Todorov's observation that the detective novel ‘contains not one but two stories: the story of the crime and the story of the investigation’, this essay argues that detective novels display a remarkably wide range of attitudes toward the several pasts they represent: the pasts of the crime, the community, the criminal, the detective, and public history. It traces a series of defining shifts in these attitudes through the evolution of five distinct subgenres of detective fiction: exploits of a Great Detective like Sherlock Holmes, Golden Age whodunits that pose as intellectual puzzles to be solved, hardboiled stories that invoke a distant past that the present both breaks with and echoes, police procedurals that unfold in an indefinitely extended present, and historical mysteries that nostalgically fetishize the past. It concludes with a brief consideration of genre readers’ own ambivalent phenomenological investment in the past, present, and future each detective story projects.

Effectiveness of Supervised Classification Models for Hate Speech on Twitter

2020 ◽  
Author(s):  
Kunal Srivastava ◽  
Ryan Tabrizi ◽  
Ayaan Rahim ◽  
Lauryn Nakamitsu
Keyword(s):  
Supervised Classification ◽  
Hate Speech ◽  
The Internet ◽  
Classification Models ◽  
Personal Attack ◽  
Political Beliefs ◽  
The Many ◽  
Primary Medium ◽  
Offensive Speech

<div> <div> <div> <p>Abstract </p> <p>The ceaseless connectivity imposed by the internet has made many vulnerable to offensive comments, be it their physical appearance, political beliefs, or religion. Some define hate speech as any kind of personal attack on one’s identity or beliefs. Of the many sites that grant the ability to spread such offensive speech, Twitter has arguably become the primary medium for individuals and groups to spread these hurtful comments. Such comments typically fail to be detected by Twitter’s anti-hate system and can linger online for hours before finally being taken down. Through sentiment analysis, this algorithm is able to distinguish hate speech effectively through the classification of sentiment. </p> </div> </div> </div>

Textual Transformations

2019 ◽  
Keyword(s):  
Early Modern ◽  
Financial Incentives ◽  
Book History ◽  
John Dryden ◽  
Book Production ◽  
Original Essays ◽  
Wide Range ◽  
Lucy Hutchinson ◽  
The Many ◽  
The Impact

This collection of twelve original essays by an international team of eminent scholars in the field of book history explores the many ways in which early modern books were subject to reworking, re-presentation, revision and reinterpretation. Their history is often the history of multiple, sometimes competing, agencies as their texts were re-packaged, redirected and transformed in ways that their original authors might hardly recognize. The essays discuss the processes of editing, revision, redaction, selection, abridgement, glossing, disputation, translation and posthumous publication that resulted in a textual elasticity and mobility that could dissolve distinctions between text and paratexts, textuality and intertextuality, manuscript and print, author and reader or editor, such that title and author’s name are no longer sufficient pointers to a book’s identity or contents. The essays are alive to the impact of commercial and technological aspects of book production and distribution (discussing, for example, the career of the pre-eminent bookseller John Nourse, the market appeal of abridgements, and the financial incentives to posthumous publication), but their interest is also in the many additional forms of agency that shaped texts and their meanings as books were repurposed to articulate, and respond to, a variety of cultural and individual needs. They engage with early modern religious, political, philosophical and scholarly trends and debates as they discuss a wide range of genres and kinds of publication (including fictional and non-fictional prose, verse miscellanies, abridgements, sermons, religious controversy) and of authors and booksellers (including Lucy Hutchinson, Richard Baxter, Thomas Burnet, Elizabeth Rowe, John Dryden, and Samuel Taylor Coleridge, Lucy Hutchinson, Henry Maundrell, John Nourse; Jonathan Swift, Samuel Richardson, John Tillotson, Isaac Watts and John Wesley).

Future Directions

2020 ◽  
pp. 476-479
Author(s):  
Marc N. Potenza ◽  
Kyle A. Faust ◽  
David Faust
Keyword(s):  
Technology Development ◽  
Digital Technologies ◽  
World Health ◽  
International Classification Of Disease ◽  
Levels Of Use ◽  
Pornography Use ◽  
Negative Impacts ◽  
Mental Health Treatments ◽  
The Many

As digital technology development continues to expand, both its positive and negative applications have also grown. As such, it is essential to continue gathering data on the many types of digital technologies, their overall effects, and their impact on public health. The World Health Organization’s inclusion of Gaming Disorder in the eleventh edition of the International Classification of Disease (ICD-11) indicates that some of the problematic effects of gaming are similar to those of substance-use disorders and gambling. Certain behaviors easily engaged in via the internet may also lead to compulsive levels of use in certain users, such as shopping or pornography use. In contrast, digital technologies can also lead to improvements in and wider accessibility to mental health treatments. Furthermore, various types of digital technologies can also lead to benefits such as increased productivity or social functioning. By more effectively understanding the impacts of all types of digital technologies, we can aim to maximize their benefits while minimizing or preventing their negative impacts.

Using Motion Detection to Measure Social Polarization in the U.S. House of Representatives

2020 ◽  
pp. 1-10
Author(s):  
Bryce J. Dietrich
Keyword(s):  
Motion Detection ◽  
House Of Representatives ◽  
Social Science Research ◽  
Image Data ◽  
Science Research ◽  
Video Data ◽  
Social Scientists ◽  
Wide Range ◽  
Party Voting ◽  
The Many

Abstract Although previous scholars have used image data to answer important political science questions, less attention has been paid to video-based measures. In this study, I use motion detection to understand the extent to which members of Congress (MCs) literally cross the aisle, but motion detection can be used to study a wide range of political phenomena, like protests, political speeches, campaign events, or oral arguments. I find not only are Democrats and Republicans less willing to literally cross the aisle, but this behavior is also predictive of future party voting, even when previous party voting is included as a control. However, this is one of the many ways motion detection can be used by social scientists. In this way, the present study is not the end, but the beginning of an important new line of research in which video data is more actively used in social science research.

scholarly journals Modes of Interaction in Naturally Occurring Medical Encounters With General Practitioners: The “One in a Million” Study

2021 ◽  
pp. 104973232199379
Author(s):  
Olaug S. Lian ◽  
Sarah Nettleton ◽  
Åge Wifstad ◽  
Christopher Dowrick
Keyword(s):  
General Practitioners ◽  
Narrative Analysis ◽  
Mode Competition ◽  
General Applicability ◽  
Naturally Occurring ◽  
Wide Range ◽  
The One ◽  
Narrative Mode ◽  
Modes Of Interaction

In this article, we qualitatively explore the manner and style in which medical encounters between patients and general practitioners (GPs) are mutually conducted, as exhibited in situ in 10 consultations sourced from the One in a Million: Primary Care Consultations Archive in England. Our main objectives are to identify interactional modes, to develop a classification of these modes, and to uncover how modes emerge and shift both within and between consultations. Deploying an interactional perspective and a thematic and narrative analysis of consultation transcripts, we identified five distinctive interactional modes: question and answer (Q&A) mode, lecture mode, probabilistic mode, competition mode, and narrative mode. Most modes are GP-led. Mode shifts within consultations generally map on to the chronology of the medical encounter. Patient-led narrative modes are initiated by patients themselves, which demonstrates agency. Our classification of modes derives from complete naturally occurring consultations, covering a wide range of symptoms, and may have general applicability.

scholarly journals Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals

Computers ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 82
Author(s):  
Ahmad O. Aseeri
Keyword(s):  
Deep Learning ◽  
Cardiac Arrhythmias ◽  
Large Scale ◽  
Clinical Decision Making ◽  
Probabilistic Approach ◽  
Classification Model ◽  
Gating Mechanism ◽  
Uncertainty Estimates ◽  
Wide Range

Deep Learning-based methods have emerged to be one of the most effective and practical solutions in a wide range of medical problems, including the diagnosis of cardiac arrhythmias. A critical step to a precocious diagnosis in many heart dysfunctions diseases starts with the accurate detection and classification of cardiac arrhythmias, which can be achieved via electrocardiograms (ECGs). Motivated by the desire to enhance conventional clinical methods in diagnosing cardiac arrhythmias, we introduce an uncertainty-aware deep learning-based predictive model design for accurate large-scale classification of cardiac arrhythmias successfully trained and evaluated using three benchmark medical datasets. In addition, considering that the quantification of uncertainty estimates is vital for clinical decision-making, our method incorporates a probabilistic approach to capture the model’s uncertainty using a Bayesian-based approximation method without introducing additional parameters or significant changes to the network’s architecture. Although many arrhythmias classification solutions with various ECG feature engineering techniques have been reported in the literature, the introduced AI-based probabilistic-enabled method in this paper outperforms the results of existing methods in outstanding multiclass classification results that manifest F1 scores of 98.62% and 96.73% with (MIT-BIH) dataset of 20 annotations, and 99.23% and 96.94% with (INCART) dataset of eight annotations, and 97.25% and 96.73% with (BIDMC) dataset of six annotations, for the deep ensemble and probabilistic mode, respectively. We demonstrate our method’s high-performing and statistical reliability results in numerical experiments on the language modeling using the gating mechanism of Recurrent Neural Networks.

scholarly journals Entangling Lattice-Trapped Bosons with a Free Impurity: Impact on Stationary and Dynamical Properties

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 290
Author(s):  
Maxim Pyzh ◽  
Kevin Keiler ◽  
Simeon I. Mistakidis ◽  
Peter Schmelcher
Keyword(s):  
Structural Changes ◽  
Many Body ◽  
Wide Range ◽  
Entropy Measures ◽  
Particle Level ◽  
The Many ◽  
The One ◽  
Tunneling Dynamics ◽  
The Individual ◽  
Trapped Bosons

We address the interplay of few lattice trapped bosons interacting with an impurity atom in a box potential. For the ground state, a classification is performed based on the fidelity allowing to quantify the susceptibility of the composite system to structural changes due to the intercomponent coupling. We analyze the overall response at the many-body level and contrast it to the single-particle level. By inspecting different entropy measures we capture the degree of entanglement and intraspecies correlations for a wide range of intra- and intercomponent interactions and lattice depths. We also spatially resolve the imprint of the entanglement on the one- and two-body density distributions showcasing that it accelerates the phase separation process or acts against spatial localization for repulsive and attractive intercomponent interactions, respectively. The many-body effects on the tunneling dynamics of the individual components, resulting from their counterflow, are also discussed. The tunneling period of the impurity is very sensitive to the value of the impurity-medium coupling due to its effective dressing by the few-body medium. Our work provides implications for engineering localized structures in correlated impurity settings using species selective optical potentials.

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