Interoceptive Brain Processing Influences Moral Decision Making.

Not harming others is widely regarded as a fundamental tenet of human morality. Harm aversion based on the consequences of an action is called utilitarianism while focusing on the action itself is associated with deontology. This study investigated how interoceptive processing affects the neural processing of utilitarian and deontological moral decision-making.

Multiple-agent promotion in a grocery store: effects of modality and variability of agents on customer memory.

The use of social robots for product advertising is becoming prevalent. Previous studies have demonstrated that social robots can positively impact sales recommendations. However, the essential question of "how effectively customers remember the advertised content" remains unexplored.

Control of Tissue Strain Is Essential for Enhanced Dermal Innervation in the Three-Dimensional Skin Engineering.

Engineered skin models with sensory innervation are a growing and challenging field of research aimed at applications in regenerative medicine, biosensing, and drug screening. Researchers are attempting to fabricate innervated skin tissues using collagen sponges, cell culture inserts, and microfluidic devices to partially mimic the layered structure of the skin. However, innervation of the full-thickness skin model has not yet been achieved.

Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI.

Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnostics due to its ability to produce high-contrast images across a variety of sequences, each highlighting distinct tissue characteristics. This study focuses on enabling multimodal MRI sequences to advance the automatic segmentation of low-grade astrocytomas, a challenging task due to their diffuse and irregular growth patterns.

Surgical skill analysis focused on tissue traction in laparoscopic wet lab training.

Background: Tissue handling is one of the pivotal parts of surgical procedures. We aimed to elucidate the characteristics of experts' left-hand during laparoscopic tissue dissection.

Methods: Participants performed tissue dissection around the porcine aorta.

Modeling long-term nutritional behaviors using deep homeostatic reinforcement learning.

The continual generation of behaviors that satisfy all conflicting demands that cannot be satisfied simultaneously, is a situation that is seen naturally in autonomous agents such as long-term operating household robots, and in animals in the natural world. Homeostatic reinforcement learning (homeostatic RL) is known as a bio-inspired framework that achieves such multiobjective control through behavioral optimization. Homeostatic RL achieves autonomous behavior optimization using only internal body information in complex environmental systems, including continuous motor control.

Deep generative abnormal lesion emphasization validated by nine radiologists and 1000 chest X-rays with lung nodules.

A general-purpose method of emphasizing abnormal lesions in chest radiographs, named EGGPALE (Extrapolative, Generative and General-Purpose Abnormal Lesion Emphasizer), is presented. The proposed EGGPALE method is composed of a flow-based generative model and L-infinity-distance-based extrapolation in a latent space. The flow-based model is trained using only normal chest radiographs, and an invertible mapping function from the image space to the latent space is determined.

Calibrating position and orientation of multiple ultrasound phased array units using Bayesian optimization.

Airborne ultrasound phased arrays (AUPAs) generate non-contact tactile sensations and enable acoustic levitation with specific focus fields. Using multiple units together offers numerous advantages, such as increased stimulus intensity and the ability to overcome occlusion. The AUPA units are typically mounted on a fixed frame, with their poses manually measured using tools such as a ruler for calibration.

Protocol to visualize a bodily map of musical uncertainty and prediction.

Music deeply influences our bodies as well as minds. Here, we present a protocol to visualize a bodily sensation map elicited by music perception using body-mapping tests and emotional evaluations. We describe steps for setting the body-map test and musical stimuli based on prediction.

A deep learning approach to predict differentiation outcomes in hypothalamic-pituitary organoids.

We use three-dimensional culture systems of human pluripotent stem cells for differentiation into pituitary organoids. Three-dimensional culture is inherently characterized by its ability to induce heterogeneous cell populations, making it difficult to maintain constant differentiation efficiency. That is why the culture process involves empirical aspects.

Evaluating correlations between reading ability and psychophysical measurements of dynamic visual information processing in Japanese adults.

The reading ability of English readers has been shown to correlate with psychophysical measurements of dynamic visual information processing. This study investigated the relationship between reading ability and dynamic visual information processing in healthy adult native Japanese readers (n = 46). Reading ability was assessed using three different tests: the Japanese Adult Reading Test (JART), transposed-letter detection task, and oral reading.

Taming Prolonged Ionic Drift-Diffusion Dynamics for Brain-Inspired Computation.

Recent advances in neural network-based computing have enabled human-like information processing in areas such as image classification and voice recognition. However, many neural networks run on conventional computers that operate at GHz clock frequency and consume considerable power compared to biological neural networks, such as human brains, which work with a much slower spiking rate. Although many electronic devices aiming to emulate the energy efficiency of biological neural networks have been explored, achieving long timescales while maintaining scalability remains an important challenge.

Silent Speech Eyewear Interface: Silent Speech Recognition Method Using Eyewear and an Ear-Mounted Microphone with Infrared Distance Sensors.

As eyewear devices such as smart glasses become more common, it is important to provide input methods that can be used at all times for such situations and people. Silent speech interaction (SSI) has the potential to be useful as a hands-free input method for various situations and people, including those who have difficulty with voiced speech. However, previous methods have involved sensor devices that are difficult to use anytime and anywhere.

A Precise and Scalable Indoor Positioning System Using Cross-Modal Knowledge Distillation.

User location has emerged as a pivotal factor in human-centered environments, driving applications like tracking, navigation, healthcare, and emergency response that align with Sustainable Development Goals (SDGs). However, accurate indoor localization remains challenging due to the limitations of GPS in indoor settings, where signal interference and reflections disrupt satellite connections. While Received Signal Strength Indicator (RSSI) methods are commonly employed, they are affected by environmental noise, multipath fading, and signal interference.

Effectiveness of Watching a Kumagai Method Video for Long-Nipple Bottle-Feeding for Children with Cleft Lip and Palate: A Pilot Experimental Before-After Trial Study.

Aim: This study aimed to determine whether the Kumagai method could be followed by watching an instructional video and to compare the feeding actions of specialists and the general population.

Materials And Methods: Eleven adults from diverse backgrounds were recruited and asked to feed a baby doll using a bottle feeder with a long nipple, and their actions were recorded. Then, they watched a 2.

Novel integrated multiomics analysis reveals a key role for integrin beta-like 1 in wound scarring.

Exacerbation of scarring can originate from a minority fibroblast population that has undergone inflammatory-mediated genetic changes within the wound microenvironment. The fundamental relationship between molecular and spatial organization of the repair process at the single-cell level remains unclear. We have developed a novel, high-resolution spatial multiomics method that integrates spatial transcriptomics with scRNA-Seq; we identified new characteristic features of cell-cell communication and signaling during the repair process.

Prevalence and influencing factors with knowledge, attitude, and practice toward anemia among school-going adolescent girls in rural Bangladesh.

Background: Anemia is a major public health concern; however, research on anemia and its contributing variables is scarce. To address the gap, we investigated the prevalence and associated factors of anemia in school-aged adolescent girls in rural Bangladesh.

Methods: We conducted a cross-sectional study in two secondary schools at Chandpur, Bangladesh, from January to April 2022.

Data Processing of Product Ion Spectra: Methods to Control False Discovery Rate in Compound Search Results for Untargeted Metabolomics.

Several database search methods have been employed in untargeted metabolomics utilizing high-resolution mass spectrometry to comprehensively annotate acquired product ion spectra. Recent technical advancements in analyses have facilitated the sorting of the degree of coincidence between a query product ion spectrum, and the molecular structures in the database. However, certain search results may be false positives, necessitating a method for controlling the false discovery rate (FDR).

Ultrasensitive and Stretchable Strain Sensors Based on Laser-Induced Graphene With ZnO Nanoparticles.

Laser-induced graphene (LIG) has attracted considerable attention for its use in flexible and stretchable sensors, owing to its electrical/mechanical properties and scalable fabrication processes. Although laser scanning facilitates the formation of LIG and its strain sensor, the strain-sensing sensitivity enhancement of LIG remains limited by the material's properties and structural design. In this study, we demonstrate a substantial improvement in sensitivity that was achieved by fabricating a LIG using ZnO nanoparticle (NP)-assisted photothermal enhancement.

Enhancing prediction of human traits and behaviors through ensemble learning of traditional and novel resting-state fMRI connectivity analyses.

Recent advances in cognitive neuroscience have focused on using resting-state functional connectivity (RSFC) data from fMRI scans to more accurately predict human traits and behaviors. Traditional approaches generally analyze RSFC by correlating averaged time-series data across regions of interest (ROIs) or networks, which may overlook important spatial signal patterns. To address this limitation, we introduced a novel linear regression technique that estimates RSFC by predicting spatial brain activity patterns in a target ROI from those in a seed ROI.

Inkjet-Printed Localized Surface Plasmon Resonance Subpixel Gas Sensor Array for Enhanced Identification and Visualization of Gas Spatial Distributions from Multiple Odor Sources.

The visualization of the spatial distributions of gases from various sources is essential to understanding the composition, localization, and behavior of these gases. In this study, an inkjet-printed localized surface plasmon resonance (LSPR) subpixel gas sensor array was developed to visualize the spatial distributions of gases and to differentiate between acetic acid, geraniol, pentadecane, and cis-jasmone. The sensor array, which integrates gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and fluorescent pigments, was positioned 3 cm above the gas source.

Simultaneous Recognition and Detection of Adenosine Phosphates by Machine Learning Analysis for Surface-Enhanced Raman Scattering Spectral Data.

Adenosine phosphates (adenosine 5'-monophosphate (AMP), adenosine 5'-diphosphate (ADP), and adenosine 5'-triphosphate (ATP)) play important roles in energy storage and signal transduction in the human body. Thus, a measurement method that simultaneously recognizes and detects adenosine phosphates is necessary to gain insight into complex energy-relevant biological processes. Surface-enhanced Raman scattering (SERS) is a powerful technique for this purpose.

The Kumagai Method: Feeding Techniques Using the Pigeon Baby Cleft Palate Bottle.

Background/objectives: This study aimed to identify the P-bottle feeding techniques systematically organized by Ms. Kumagai, an expert in nursing care for children with a cleft lip and/or palate (CLP), which were developed as she gained expertise in feeding affected children.

Methods: We recruited three nurses who had mastered the Kumagai method for feeding with a P-bottle.