Risks that induce bicycle accidents: Measurement and analysis of bicyclist behavior while going straight and turning right using a bicycle simulator.

In 2021, 69 % of those who died in Japan while riding a bicycle were of an older age. Preventing such accidents is an important issue because older bicyclists are more likely to be fatally injured in an accident. We developed a bicycle simulator that can safely simulate dangerous traffic environments by combining VR technology, motion capture technology, and various sensors to investigate the driving behavior of bicyclists who are involved in accidents.

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste.

Municipal and agricultural organic waste can be treated to recover energy, nutrients, and carbon through resource recovery and carbon capture (RRCC) technologies such as anaerobic digestion, struvite precipitation, and pyrolysis. Data science could benefit such technologies by improving their efficiency through data-driven process modeling along with reducing environmental and economic burdens via life cycle assessment (LCA) and techno-economic analysis (TEA), respectively. We critically reviewed 616 peer-reviewed articles on the use of data science in RRCC published during 2002-2022.

Long-Range Thermal Target Detection in Data-Limited Settings Using Restricted Receptive Fields.

Long-range target detection in thermal infrared imagery is a challenging research problem due to the low resolution and limited detail captured by thermal sensors. The limited size and variability in thermal image datasets for small target detection is also a major constraint for the development of accurate and robust detection algorithms. To address both the sensor and data constraints, we propose a novel convolutional neural network (CNN) feature extraction architecture designed for small object detection in data-limited settings.

Association of APOE gene with longitudinal changes of CSF amyloid beta and tau levels in Alzheimer's disease: racial differences.

Background: The Apolipoprotein E (APOE) ε4 allele is a risk factor for late-onset Alzheimer's disease (AD). However, no investigation has focused on racial differences in the longitudinal effect of APOE genotypes on CSF amyloid beta (Aβ42) and tau levels in AD.

Methods: This study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 222 participants with AD, 264 with cognitive normal (CN), and 692 with mild cognitive impairment (MCI) at baseline and two years follow-up.

Interdisciplinary Inquiry via PanelGPT: Application to Explore Chatbot Application in Sports Rehabilitation.

Background: ChatGPT showcases exceptional conversational capabilities and extensive cross-disciplinary knowledge. In addition, it possesses the ability to perform multiple roles within a single chat session. This unique multi-role-playing feature positions ChatGPT as a promising tool to explore interdisciplinary subjects.

Improvement of growth, yield and associated bacteriome of rice by the application of probiotic and .

Plant probiotic bacteria enhance growth and yield of crop plants when applied at the appropriate time and dose. Two rice probiotic bacteria, strain BRRh-4 and sp. strain BTL-M2 promote growth and yield of plants.

Topic modeling in density functional theory on citations of condensed matter electronic structure packages.

With an increasing number of new scientific papers being released, it becomes harder for researchers to be aware of recent articles in their field of study. Accurately classifying papers is a first step in the direction of personalized catering and easy access to research of interest. The field of Density Functional Theory (DFT) in particular is a good example of a methodology used in very different studies, and interconnected disciplines, which has a very strong community publishing many research articles.

Empowering beginners in bioinformatics with ChatGPT.

The impressive conversational and programming abilities of ChatGPT make it an attractive tool for facilitating the education of bioinformatics data analysis for beginners. In this study, we proposed an iterative model to fine-tune instructions for guiding a chatbot in generating code for bioinformatics data analysis tasks. We demonstrated the feasibility of the model by applying it to various bioinformatics topics.

Toward a computational theory of manifold untangling: from global embedding to local flattening.

It has been hypothesized that the ventral stream processing for object recognition is based on a mechanism called cortically local subspace untangling. A mathematical abstraction of object recognition by the visual cortex is how to untangle the manifolds associated with different object categories. Such a manifold untangling problem is closely related to the celebrated kernel trick in metric space.

An exploratory simulation study and prediction model on human brain behavior and activity using an integration of deep neural network and biosensor Rabi antenna.

The plasmonic antenna probe is constructed using a silver rod embedded in a modified Mach-Zehnder interferometer (MZI) ad-drop filter. Rabi antennas are formed when space-time control reaches two levels of system oscillation and can be used as human brain sensor probes. Photonic neural networks are designed using brain-Rabi antenna communication, and transmissions are connected via neurons.

Parallel CNN-ELM: A multiclass classification of chest X-ray images to identify seventeen lung diseases including COVID-19.

Numerous epidemic lung diseases such as COVID-19, tuberculosis (TB), and pneumonia have spread over the world, killing millions of people. Medical specialists have experienced challenges in correctly identifying these diseases due to their subtle differences in Chest X-ray images (CXR). To assist the medical experts, this study proposed a computer-aided lung illness identification method based on the CXR images.

Lane line detection at nighttime on fractional differential and central line point searching with Fragi and Hessian.

To detect lanes at night, each detecting image is the fusion of the multiple images in a video sequence. The valid lane line detection region is identified on region merging. Then, the image preprocessing algorithm based on the Fragi algorithm and Hessian matrix is applied to enhance lanes; to extract the lane line center feature points, the image segmentation algorithm based on Fractional differential is proposed; and according to the possible lane line positions, the algorithm detects the centerline points in four directions.

Deciphering Alloy Composition in Superconducting Single-Layer FeSeS on SrTiO(001) Substrates by Machine Learning of STM/S Data.

Scanning tunneling microscopy (STM) is a powerful technique for imaging atomic structure and inferring information on local elemental composition, chemical bonding, and electronic excitations. However, a plain visual analysis of STM images can be challenging for such determination in multicomponent alloys, particularly beyond the diluted limit due to chemical disorder and electronic inhomogeneity. One viable solution is to use machine learning to analyze STM data and identify hidden patterns and correlations.

prediction of highly promising natural fungicides against the destructive blast fungus .

causes destructive blast disease in more than 50 species of the major cereal crops rice, wheat and maize and destroys food of millions of people worldwide. Application of synthetic chemical fungicides are environmentally hazardous and unreliable in controlling . Conversely, naturally occurring biofungicides with multiple modes of actions are needed to be discovered for combatting the blast fungus.

Nanoparticle localization within chiral liquid crystal defect lines and nanoparticle interactions.

Self-assembly of colloidal particles into predefined structures is a promising way to design inexpensive manmade materials with advanced macroscopic properties. Doping of nematic liquid crystals (LCs) with nanoparticles has a series of advantages in addressing these grand scientific and engineering challenges. It also provides a very rich soft matter platform for the discovery of unique condensed matter phases.

Changes in life expectancy and house prices in London from 2002 to 2019: hyper-resolution spatiotemporal analysis of death registration and real estate data.

Background: London has outperformed smaller towns and rural areas in terms of life expectancy increase. Our aim was to investigate life expectancy change at very-small-area level, and its relationship with house prices and their change.

Methods: We performed a hyper-resolution spatiotemporal analysis from 2002 to 2019 for 4835 London Lower-layer Super Output Areas (LSOAs).

Quantification methods comparing in vitro and in vivo percutaneous permeation by microneedles and passive diffusion.

Microneedles (MNs) are needles with a tip diameter ranging from 10 to 100 um and a length ranging up to 1 mm. The first patent for drug delivery device for percutaneous administration filed by Alza corporation dates back to 1976 (Gerstel and Place, 1976), and in between 1989 and 2021 the filed patents for MNs are >4500 [1]. These devices can potential overcome some drawbacks of traditional needles, such as the pain generated during insertion, requirement for trained personnel to manipulate syringes, and difficulty of performing injections in elderly and obese patients.

Macular outer nuclear layer, ellipsoid zone and outer photoreceptor segment band thickness, axial length and other determinants.

The study aims to assess the thickness of the retinal outer nuclear layer (ONL), ellipsoid zone (EZ) and photoreceptor outer segment (POS) band in various macular regions and its associations with axial length and other parameters. Participants of the Beijing Eye Study 2011 underwent a series of examinations including spectral-domain optical coherence tomography of the macula. The current study included 2213 participants without retinal or optic nerve diseases (age: 61.

MedViT: A robust vision transformer for generalized medical image classification.

Convolutional Neural Networks (CNNs) have advanced existing medical systems for automatic disease diagnosis. However, there are still concerns about the reliability of deep medical diagnosis systems against the potential threats of adversarial attacks since inaccurate diagnosis could lead to disastrous consequences in the safety realm. In this study, we propose a highly robust yet efficient CNN-Transformer hybrid model which is equipped with the locality of CNNs as well as the global connectivity of vision Transformers.

Empowering Beginners in Bioinformatics with ChatGPT.

The impressive conversational and programming abilities of ChatGPT make it an attractive tool for facilitating the education of bioinformatics data analysis for beginners. In this study, we proposed an iterative model to fine-tune instructions for guiding a ChatGPT in generating code for bioinformatics data analysis tasks. We demonstrated the feasibility of the model by applying it to various bioinformatics topics.

Hatemongers ride on echo chambers to escalate hate speech diffusion.

Recent years have witnessed a swelling rise of hateful and abusive content over online social networks. While detection and moderation of hate speech have been the early go-to countermeasures, the solution requires a deeper exploration of the dynamics of hate generation and propagation. We analyze more than 32 million posts from over 6.

An Adaptive Traffic-Flow Management System with a Cooperative Transitional Maneuver for Vehicular Platoons.

Globally, the increases in vehicle numbers, traffic congestion, and road accidents are serious issues. Autonomous vehicles (AVs) traveling in platoons provide innovative solutions for efficient traffic flow management, especially for congestion mitigation, thus reducing accidents. In recent years, platoon-based driving, also known as vehicle platoon, has emerged as an extensive research area.