Toward Accurate Sleepiness Estimation Modeling from Speech: A Preliminary Study of 25-Hour Sleep Deprivation.

Accurate estimation of sleepiness levels is crucial for managing fatigue risks. Access to speech signals could aid in determining sleepiness across different settings. Previous machine learning (ML) studies faced challenges in accurately estimating sleepiness depths, especially with varied sentence structures.

Multiclass arrhythmia classification using multimodal smartwatch photoplethysmography signals collected in real-life settings.

In the early stages of atrial fibrillation (AF), most cases are paroxysmal (pAF), making identification only possible with continuous and prolonged monitoring. With the advent of wearables, smartwatches equipped with photoplethysmographic (PPG) sensors are an ideal approach for continuous monitoring of pAF. There have been numerous studies demonstrating successful capture of pAF events, especially using deep learning.

Characterization of particulate matter at Mt. Gwanak (at 632 m) and vertical mixing impacts on haze in Seoul during winter.

This study investigates the sources, chemical composition, and vertical transport of particulate matter (PM) at Mt. Gwanak in southeastern Seoul, focusing on differences between surface and elevated altitudes during winter 2021. Using a time-of-flight aerosol chemical species mass spectrometer (ToF-ACSM), PM was measured at 632 m.

Towards real-world wearable sleepiness detection: Electrodermal activity data during speech can identify sleep deprivation.

Accurate assessment of sleepiness is pivotal in managing the fatigue-associated risks stemming from sleep deprivation. Speech signals are easy to obtain, allowing detection of sleepiness anywhere. Previous machine learning (ML) studies using speech have not been successful in achieving reliable estimation of perceived sleepiness levels, which results in inaccurate sleepiness determination.

Internal quality prediction technology for 'Sulhyang' strawberry fruit using organic analysis and hyperspectral imaging.

In recent years, hyperspectral imaging combined with machine learning techniques has garnered significant attention for its potential in assessing fruit maturity. This study proposes a method for predicting strawberry fruit maturity based on the harvest time. The main features of this study are as follows.

Genetic data visualization using literature text-based neural networks: Examples associated with myocardial infarction.

Data visualization is critical to unraveling hidden information from complex and high-dimensional data. Interpretable visualization methods are critical, especially in the biology and medical fields, however, there are limited effective visualization methods for large genetic data. Current visualization methods are limited to lower-dimensional data and their performance suffers if there is missing data.

Language-Independent Sleepy Speech Detection.

Prolonged sleepiness can lead to impairment of cognitive and physical performance and may cause unfortunate accidents. Speech signals are easily accessible using a simple microphone or other means, hence, automated approaches for accurate sleepiness detection from speech signals are desired to prevent degradation in human performance and accidental injury. Sleepiness is known to affect acoustic patterns of speech so that they are different from those of normal speech, and this change is also independent of the language being spoken.

An in-depth look at ventilator-associated pneumonia in trauma patients and efforts to increase bundle compliance, education and documentation in a surgical trauma critical care unit.

Background: Ventilator-associated pneumonia (VAP) is considered the most common hospital acquired infection seen in critical care settings and leading cause of death in Intensive Care Units (ICU). The objective of this study was to assess whether specimen collection impacted diagnosis and if implementation of a VAP bundle would decrease rates at our center.

Methods: This single center study design is a retrospective chart review from 2017 to 2020 utilizing the electronic medical record.

Preliminary Analysis of the Risk Factor Identification Embedding Model for Cardiovascular Disease.

Cardiovascular Disease (CVD) is responsible for a large part of healthcare costs every year, but susceptibility to it is affected by complex biological and physiological variables including patients' genetics and lifestyles. There has not been much work to develop a framework that incorporates these important and clinically relevant risk factors into a comprehensive model for CVD research. Moreover, the data labeling required to do so, such as annotating gene functions, is an extremely challenging, tedious, and time-consuming process.

Effects of postnatal alcohol exposure on hippocampal gene expression and learning in adult mice.

Fetal alcohol syndrome (FAS) is a condition resulting from excessive drinking by pregnant women. Symptoms of FAS include abnormal facial features, stunted growth, intellectual deficits and attentional dysfunction. Many studies have investigated FAS, but its underlying mechanisms remain unknown.

Effects of guanine bases at the central loop on stabilization of the quadruplex DNAs and their interactions with Meso-tetrakis(N-methylpyridium-4-yl)porphyrin.

The thermal stability of the G-quadruplex formed from the thrombin-binding aptamer, 5'G2T2G2TGTG2T2G2, in which the guanine (G) base at the central loop was replaced with an adenine (A) or inosine (I) base, was examined to determine the role of the central G base in stabilizing the quadruplex. Replacement of the central G base by the I base resulted in a slight decrease in thermal stability. On the other hand, the stability of the G-quadruplex decreased to a significant extent when it was replaced with the A base.

Effects of deficient of the Hoogsteen base-pairs on the G-quadruplex stabilization and binding mode of a cationic porphyrin.

Background: In stabilization of the G-quadruplex, formation of a Hoogsteen base-pair between the guanine (G) bases is essential. However, the contribution of each Hoogsteen base-pair at different positions to whole stability of the G-quadruplex has not been known. In this study, the effect of a deficiency of the Hoogsteen type hydrogen bond in the G-quadruplex stability was investigated.

Egr1 mediated the neuronal differentiation induced by extremely low-frequency electromagnetic fields.

Aim: There is a specific frequency of extremely low-frequency electromagnetic field (ELF-EMF) that promotes neuronal differentiation. Although several mechanisms are known to regulate ELF-EMF-induced neuronal differentiation, a key factor that mediates neurogenic potentials by the ELF-EMF is largely unknown. Also, the potential use of ELF-EMF exposure in cell transplantation assays is yet to be determined, including their possible use in ELF-EMF based therapy of neurological diseases.

Application of RAPD and SCAR markers for purity testing of F1 hybrid seed in chili pepper (Capsicum annuum).

A simpler and better method for purity testing of hybrid pepper seed was developed. The simplest method for extracting genomic DNA, the NaOH method, was chosen. Two RAPD markers identifying male and female parents were also developed, and the PCR products of male- and female-specific RAPD markers were cloned and sequenced.

Disruption of a guard cell-expressed protein phosphatase 2A regulatory subunit, RCN1, confers abscisic acid insensitivity in Arabidopsis.

Pharmacological studies have led to a model in which the phytohormone abscisic acid (ABA) may be positively transduced via protein phosphatases of the type 1 (PP1) or type 2A (PP2A) families. However, pharmacological evidence also exists that PP1s or PP2As may function as negative regulators of ABA signaling. Furthermore, recessive disruption mutants in protein phosphatases that function in ABA signal transduction have not yet been identified.