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Non-invasive paper-based sensors containing rare-earth-doped nanoparticles for the detection of D-glucose

Author(s): López-Peña G; Ortiz-Mansilla E; Arranz A; Bogdan N; Manso-Silván M; Martín Rodríguez E;

Today, diabetes mellitus is one of the most common diseases that affects the population on a worldwide scale. Patients suffering from this disease are required to control their blood-glucose levels several times a day through invasive methods such as piercing their fingers. Our NaGdF4: 5% Er3+, 3% Nd3+ nanoparticles demonstrate a remarkable ability to det ...

Article GUID: 38729020


Brain tumor detection based on a novel and high-quality prediction of the tumor pixel distributions

Author(s): Sun Y; Wang C;

The work presented in this paper is in the area of brain tumor detection. We propose a fast detection system with 3D MRI scans of Flair modality. It performs 2 functions, predicting the gray level distribution and location distribution of the pixels in the tumor regions and generating tumor masks with pixel-wise precision. To facilitate 3D data analysis a ...

Article GUID: 38493601


Tailoring plasmonic sensing strategies for the rapid and sensitive detection of hypochlorite in swimming water samples

Author(s): Sadiq Z; Al-Kassawneh M; Safiabadi Tali SH; Jahanshahi-Anbuhi S;

A tunable plasmonic sensor has been developed by varying the dextran content in the initially synthesized dextran-gold nanoparticle (dAuNPs) solution. A colloidal nanogold solution (dAuNPs-Sol) was initially prepared using dextran and gold salt in alkaline media by a one-pot green synthetic route. The dAuNPs-Sol was combined with varying amounts of dextra ...

Article GUID: 38451315


Deep learning approach to security enforcement in cloud workflow orchestration

Author(s): El-Kassabi HT; Serhani MA; Masud MM; Shuaib K; Khalil K;

Supporting security and data privacy in cloud workflows has attracted significant research attention. For example, private patients' data managed by a workflow deployed on the cloud need to be protected, and communication of such data across multiple stakeholders should also be secured. In general, security threats in cloud environments have been stud ...

Article GUID: 36691661


Unique Photoactivated Time-Resolved Response in 2D GeS for Selective Detection of Volatile Organic Compounds

Author(s): Mohammadzadeh MR; Hasani A; Jaferzadeh K; Fawzy M; De Silva T; Abnavi A; Ahmadi R; Ghanbari H; Askar A; Kabir F; Rajapakse RKND; Adachi MM;

Volatile organic compounds (VOCs) sensors have a broad range of applications including healthcare, process control, and air quality analysis. There are a variety of techniques for detecting VOCs such as optical, acoustic, electrochemical, and chemiresistive sensors. However, existing commercial V ...

Article GUID: 36658730


Gold Nanoparticles-Based Colorimetric Assays for Environmental Monitoring and Food Safety Evaluation

Author(s): Sadiq Z; Safiabadi Tali SH; Hajimiri H; Al-Kassawneh M; Jahanshahi-Anbuhi S;

Recent years have witnessed an exponential increase in the research on gold nanoparticles (AuNPs)-based colorimetric sensors to revolutionize point-of-use sensing devices. Hence, this review is compiled focused on current progress in the design and performance parameters of AuNPs-based sensors. The review begins with the characteristics of AuNPs, followed ...

Article GUID: 36629748


Stable Cavitation-Mediated Delivery of miR-126 to Endothelial Cells

Author(s): He S; Singh D; Yusefi H; Helfield B;

In endothelial cells, microRNA-126 (miR-126) promotes angiogenesis, and modulating the intracellular levels of this gene could suggest a method to treat cardiovascular diseases such as ischemia. Novel ultrasound-stimulated microbubbles offer a means to deliver therapeutic payloads to target cells and sites of disease. The purpose of this study was to inve ...

Article GUID: 36559150


Novelty detection in rover-based planetary surface images using autoencoders

Author(s): Stefanuk B; Skonieczny K;

In the domain of planetary science, novelty detection is gaining attention because of the operational opportunities it offers, including annotated data products and downlink prioritization. Using a variational autoencoder (VAE), this work improves upon state-of-the-art novelty detection performance in the context of Martian exploration by > 7 % (measured ...

Article GUID: 36313243


A Deep Learning Approach to Capture the Essence of Candida albicans Morphologies

Author(s): Bettauer V; Costa ACBP; Omran RP; Massahi S; Kirbizakis E; Simpson S; Dumeaux V; Law C; Whiteway M; Hallett MT;

We present deep learning-based approaches for exploring the complex array of morphologies exhibited by the opportunistic human pathogen Candida albicans. Our system, entitled Candescence, automatically detects C. albicans cells from differential image contrast microscopy and labels each detected ...

Article GUID: 35972285


Trust-Augmented Deep Reinforcement Learning for Federated Learning Client Selection

Author(s): Rjoub G; Wahab OA; Bentahar J; Cohen R; Bataineh AS;

In the context of distributed machine learning, the concept of federated learning (FL) has emerged as a solution to the privacy concerns that users have about sharing their own data with a third-party server. FL allows a group of users (often referred to as clients) to locally train a single machine learning model on their devices without sharing their ra ...

Article GUID: 35875592


Microfluidic Platforms for the Isolation and Detection of Exosomes: A Brief Review

Author(s): Raju D; Bathini S; Badilescu S; Ghosh A; Packirisamy M;

Extracellular vesicles (EVs) are a group of communication organelles enclosed by a phospholipid bilayer, secreted by all types of cells. The size of these vesicles ranges from 30 to 1000 nm, and they contain a myriad of compounds such as RNA, DNA, proteins, and lipids from their origin cells, offering a good source of biomarkers. Exosomes (30 to 100 nm) a ...

Article GUID: 35630197


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