Eye-tracking technology applications for supporting individuals with autism spectrum disorder: insights, challenges, and opportunities.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterised by deficits in social communication and restricted, repetitive behaviours, with significant impacts on individuals and their families. In recent years, eye-tracking technology has emerged as a valuable tool for examining the cognitive and perceptual differences associated with ASD. Despite technological advancements, the diversity and complexity of this technology may pose challenges for researchers, particularly in fields such as psychology and special education.

A multifaceted approach to drug-drug interaction extraction with fusion strategies.

Objective: Drug-drug interactions (DDIs) occur when one medication affects the efficacy of another, potentially leading to unforeseen patient outcomes. Existing studies primarily focus on textual data, but overlook a wealth of the drug's multimodal information. This study aims to enhance DDI extraction by integrating diverse data modalities and evaluating various fusion strategies.

A compact design of MIMO patch antenna with high gain and symmetrical radiation pattern.

This paper presents a compact design of multiple-input multiple-output (MIMO) microstrip patch antenna with high gain and symmetrical radiation pattern. The proposed antenna consists of dual-polarized crossed patches and T-junction power dividers. This combination makes the proposed design achieve high gain and high isolation with compact size and not requiring any additional decoupling structure.

A simple approach in balancing the slider-crank mechanisms applied to new systems.

This study presents a simple method for balancing a slider-crank mechanism which is applied to a new system. A counterweight is designed and located on the crank link to solve the vibration of slider-crank mechanism. The calculation of counterweight design is proposed to balance the single and double slider-crank mechanisms which are exploited to develop the fast scanning module of scanning acoustic microscopy (SAM) system.

Antibacterial and electrical performance of triboelectric nanogenerators based on polyhexamethylene guanidine hydrochloride in high humidity environments.

A humidity-resistant, antibacterial triboelectric nanogenerator (TENG) was developed using polyhexamethylene guanidine hydrochloride (PHMG) as the primary functional material. To enhance performance stability, PHMG was integrated with natural chitosan (CS) to create a positively charged triboelectric electrode. When combined with a negatively charged fluorinated ethylene propylene (FEP) membrane, the TENG demonstrated outstanding electrical output, achieving a maximum peak-to-peak voltage ( ) of 1470.

High-efficiency microfluidic chip integrated with micro-patterned planar spiral sensors for magnetic nanoparticle detection.

Magnetic nanoparticles have garnered significant attention in the biomedical field due to their remarkable biocompatibility and diverse applications. However, existing methodologies for quantifying magnetic-labeled samples face limitations, particularly regarding the stringent requirements for magnetic sensors and the complexities associated with integrating these systems into microfluidic platforms. This study introduces an innovative planar magnetoimpedance sensor for magnetic nanoparticle detection, designed with a micropatterned spiral configuration and integrated into a microfluidic channel.

A novel approach for the fabrication of SERS substrates based on 3D urchin-like TiO@Gr-AuNPs architecture.

3D urchin-like titanium dioxide@graphene-gold nanoparticles (UT@Gr-AuNPs) architectures with a core@shell structure of UT@Gr were successfully synthesized on silicon substrates thermal chemical vapor deposition (CVD) technique using sodium deoxycholate surfactant (SDC) as a carbon source, followed by depositing AuNPs onto the surface of UT@Gr a cold plasma (CP) process. The as-prepared samples were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman, X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), and ultraviolet-visible (UV-vis) spectroscopy. Thanks to the hot spots created by the AuNPs onto the surface of UT@Gr, the UT@Gr-AuNPs SERS substrates show significantly enhanced SERS sensitivity to detect hazardous pollutants and pesticide residue substances, , rhodamine 6G (R6G) and malathion with a low detection limit (LOD) of about 5.

An EEG signal smoothing algorithm using upscale and downscale representation.

Effective smoothing of electroencephalogram (EEG) signals while maintaining the original signal's features is important in EEG signal analysis and brain-computer interface. This paper proposes a novel EEG signal-smoothing algorithm and its potential application in cognitive conflict (CC) processing.Instead of being processed in the time domain, the input signal is visualized in increasing line width, the representation frame of which is converted into a binary image.

The use of eye-tracking technology in supporting children and adolescents with attention deficit/hyperactivity disorder: a comprehensive review.

Purpose: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental conditions marked by symptoms of inattention, impulsivity, and hyperactivity. These symptoms significantly impact affected individuals, particularly children and adolescents, who benefit from timely assessment, diagnosis, and intervention. In recent years, eye movement research has increasingly provided insights into neurological function, presenting eye-tracking technology as a valuable tool for supporting ADHD.

Efficient photocatalytic degradation of methylene blue using 3D urchin-like TiO@rGO-hBN architecture.

3D urchin-like TiO@rGO-hBN architectures were produced by a hydrothermal method, followed by a cold plasma jet process. The morphology, crystal structure, composition and photocatalytic performance of the 3D urchin-like TiO@rGO-hBN architectures towards methylene blue (MB) were evaluated using SEM, Raman, XRD, EDS and UV-vis-NIR spectrophotometry. The obtained results indicated that under the same conditions, the MB degradation efficiencies were ∼72%, ∼81%, ∼87%, and ∼98% for 3D urchin-like TiO, 3D urchin-like TiO@rGO, 3D urchin-like TiO@hBN, and 3D urchin-like TiO@rGO-hBN, respectively, within 70 min under ultraviolet (UV) light irradiation with a wavelength of 365 nm.

Effect of Eu ion concentration on optical and magnetic properties of oriented GdO/CTAB nanoparticles as multifunctional optical-magnetic probes in biomedicine.

The GdO:Eu nanoparticles were synthesized using a multi-step chemical method with urea as a reactant to control the ratio of different Eu activation centers: 2, 4, 6, 8, 10, and 12 mol% combined with CTAB surfactant to improve surface quality. The study aimed to determine the optimal concentration of Eu in the presence of CTAB to increase biocompatibility and achieve the best fluorescence. The structure, surface morphology, optical properties, and magnetic properties of the materials were analyzed through FSEM, XRD, HRTEM, XPS, UV-vis, fluorescence, fluorescence excitation, time-resolved fluorescence, vibrating sample magnetometry (VSM), and magnetic heating measurements.

FDG-PET-based brain network analysis: a brief review of metabolic connectivity.

Background: Over the past decades, the analysis metabolic connectivity patterns has received significant attention in exploring the underlying mechanism of human behaviors, and the neural underpinnings of brain neurological disorders. Brain network can be considered a powerful tool and play an important role in the analysis and understanding of brain metabolic patterns. With the advantages and emergence of metabolic-based network analysis, this study aims to systematically review how brain properties, under various conditions, can be studied using Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) images and graph theory, as well as applications of this approach.

Quantitative trait loci for grain mineral element accumulation in Vietnamese rice landraces.

Rice (Oryza sativa L.) is a staple food for half of the world's population, and its biofortification is a key factor in fighting micronutrient malnutrition. However, harmful heavy metals tend to accumulate in rice grains due to soil and water contamination.

The use of eye tracking in supporting individuals with dyslexia: a review.

Dyslexia is defined as a specific learning disorder that impairs a person's ability to read fluently and accurately. A growing number of assistive technologies have been used to support individuals with dyslexia. Eye-tracking technology is one such technology, and it is gaining increasing attention from the research community due to its potential to be a valuable support tool for identifying underlying neural differences in language processing among this population.

Various CVD-grown ZnO nanostructures for nanodevices and interdisciplinary applications.

This work presents a simple chemical vapour deposition (CVD) method to grow ZnO nanostructures. By annealing Zn powder under atmospheric pressure conditions, we collected nanocrystals with various morphologies, including rods, pencils, sheets, combs, tetrapods, and multilegs. Raman scattering study reveals that the samples are monophasic with a hexagonal structure, and fall into the 6 space group.

Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

Background: Ablation zone segmentation in contrast-enhanced computed tomography (CECT) images enables the quantitative assessment of treatment success in the ablation of liver lesions. However, fully automatic liver ablation zone segmentation in CT images still remains challenging, such as low accuracy and time-consuming manual refinement of the incorrect regions.

Purpose: Therefore, in this study, we developed a semi-automatic technique to address the remaining drawbacks and improve the accuracy of the liver ablation zone segmentation in the CT images.

AMRomics: a scalable workflow to analyze large microbial genome collections.

Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance.

Friendly Environmental Strategies to Recycle Zinc-Carbon Batteries for Excellent Gel Polymer Electrolyte (PVA-ZnSO-HSO) and Carbon Materials for Symmetrical Solid-State Supercapacitors.

In this report, we introduce a novel idea to prepare a redox additive in a gel polymer electrolyte system of PVA-ZnSO-HSO based on zinc-carbon battery recycling. Here, zinc cans from spent zinc-carbon batteries are dissolved completely in 1 M HSO to obtain a redox additive in an aqueous electrolyte of ZnSO-HSO. Moreover, carbon nanoparticles and graphene nanosheets were synthesized from carbon rod and carbon powder from spent zinc-carbon batteries by only one step of washing and electrochemical exfoliation, respectively, which have good electrochemical capability.

CMAN: Cascaded Multi-scale Spatial Channel Attention-guided Network for large 3D deformable registration of liver CT images.

Deformable image registration is an essential component of medical image analysis and plays an irreplaceable role in clinical practice. In recent years, deep learning-based registration methods have demonstrated significant improvements in convenience, robustness and execution time compared to traditional algorithms. However, registering images with large displacements, such as those of the liver organ, remains underexplored and challenging.

Identification of dragon trees and fruits in ham Thuan Bac growing areas, Phan Thiet city, Binh Thuan province, Vietnam.

With the development of Computer Vision, we can effectively and accurately identify trees, fruit or object images. But to build a high-performance image dataset for tree identification problems in Agriculture is a challenge. Realizing that Vietnam is a country with strong agriculture with many tropical fruits grown widely such as Dragon fruit, Mangosteen, Mango, Orange, Lychee, Longan … We chose the Dragon Fruit tree for the data set.

xCAPT5: protein-protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model.

Background: Predicting protein-protein interactions (PPIs) from sequence data is a key challenge in computational biology. While various computational methods have been proposed, the utilization of sequence embeddings from protein language models, which contain diverse information, including structural, evolutionary, and functional aspects, has not been fully exploited. Additionally, there is a significant need for a comprehensive neural network capable of efficiently extracting these multifaceted representations.

Ensemble learning of myocardial displacements for myocardial infarction detection in echocardiography.

Background: Early detection and localization of myocardial infarction (MI) can reduce the severity of cardiac damage through timely treatment interventions. In recent years, deep learning techniques have shown promise for detecting MI in echocardiographic images. Existing attempts typically formulate this task as classification and rely on a single segmentation model to estimate myocardial segment displacements.

Tracking online low-rank approximations of higher-order incomplete streaming tensors.

In this paper, we propose two new provable algorithms for tracking online low-rank approximations of high-order streaming tensors with missing data. The first algorithm, dubbed adaptive Tucker decomposition (ATD), minimizes a weighted recursive least-squares cost function to obtain the tensor factors and the core tensor in an efficient way, thanks to an alternating minimization framework and a randomized sketching technique. Under the canonical polyadic (CP) model, the second algorithm, called ACP, is developed as a variant of ATD when the core tensor is imposed to be identity.

C-Biomarker.net: A Cytoscape app for the identification of cancer biomarker genes from cores of large biomolecular networks.

Although there have been many studies revealing that biomarker genes for early cancer detection can be found in biomolecular networks, no proper tool exists to discover the cancer biomarker genes from various biomolecular networks. Accordingly, we developed a novel Cytoscape app called C-Biomarker.net, which can identify cancer biomarker genes from cores of various biomolecular networks.

Towards hard-magnetic behavior of CoFeO nanoparticles: a detailed study of crystalline and electronic structures, and magnetic properties.

We have used the coprecipitation and mechanical-milling methods to fabricate CoFeO nanoparticles with an average crystallite size () varying from 81 to ∼12 nm when changing the milling time ( ) up to 180 min. X-ray diffraction and Raman-scattering studies have proved the samples crystalizing in the spinel structure. Both the lattice constant and residual strain tend to increase when () increases (decreases).