Very fast, high-resolution aggregation 3D detection CAM to quickly and accurately find facial fracture areas.

Background And Objective: The incidence of facial fractures is on the rise globally, yet limited studies are addressing the diverse forms of facial fractures present in 3D images. In particular, due to the nature of the facial fracture, the direction in which the bone fractures vary, and there is no clear outline, it is difficult to determine the exact location of the fracture in 2D images. Thus, 3D image analysis is required to find the exact fracture area, but it needs heavy computational complexity and expensive pixel-wise labeling for supervised learning.

Validation and measurement uncertainty of analytical methods for various azo dye adulterants in Curcuma longa L.

Food adulteration involving the illegal addition of dyes to foodstuffs has become an alarming issue in recent years. This study developed and validated a high-performance liquid chromatography (HPLC)-DAD (diode array detector) method for the simultaneous determination of nine azo dyes (Butter Yellow, Sudan Orange G, Para Red, Sudan I, Sudan II, Sudan III, Sudan IV, Sudan Red 7B, and Scarlet 808). Moreover, a qualitative analysis method using liquid chromatography-tandem mass spectrometry was developed to more accurately identify peaks detected in HPLC-DAD.

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department.

Investigating the different transformations of tetracycline using birnessite under different reaction conditions and various humic acids.

Prior studies have successfully used manganese oxides to facilitate the transformation of tetracycline in aqueous solution. To further understand the kinetic and the transformation pathway of tetracycline via birnessite (δ-MnO) under different conditions, experiments were conducted at pH levels of 3, 6, and 9 in the presence or absence of Aldrich humic acid (ADHA). Tetracycline removal followed the pseudo-second-order reaction model in all investigated cases, and the removal efficiency (g mg h ) followed the following trend: pH 3 (0.

Combination of UHPLC-MS/MS with context-specific network and cheminformatic approaches for identifying bioactivities and active components of propolis.

Discovering new bioactivities and identifying active compounds of food materials are major fields of study in food science. However, the process commonly requires extensive experiments and can be technically challenging. In the current study, we employed network biology and cheminformatic approaches to predict new target diseases, active components, and related molecular mechanisms of propolis.

The Impact of Union Membership on Nursing Turnover and Job Satisfaction.

Objective: The present study examines the scope of nursing unions and the relationship with turnover and job satisfaction among RNs.

Background: There is no recent empirical literature documenting evidence on workplace performance measures (turnover and job satisfaction) among unionized nurses at the national level.

Methods: This cross-sectional study analyzed secondary data (n = 43 960), the 2018 National Sample Survey of Registered Nurses.

Molecularly Imprinted Chemiresistive Sensor for Specific Recognition of Furaneol as a Biomarker of Strawberry Flavor Conditions.

This work introduces the concept of a molecularly imprinted gas sensor to monitor the condition of naturally ripened strawberries. Furaneol, 2,5-dimethyl-4-hydroxy-3(2)-furanone, is considered as an important biomarker related to the strawberry flavor. Identification of furaneol concentration is still a challenge because of its weak adsorption, nonpolar, and unreactive properties.

Polyaniline/Graphene-Functionalized Flexible Waste Mask Sensors for Ammonia and Volatile Sulfur Compound Monitoring.

A flexible resistive-type polyaniline-based gas sensor was fabricated by simple dip-coating of graphene combined with in situ polymerization of aniline on a flexible waste mask substrate. The prepared polypropylene/graphene/polyaniline (PP/G/PANI) hybrid sensor demonstrated a fast response (114 s) and recovery time (23 s), ppb-level detection limit (100 ppb), high response value (250% toward 50 ppm NH, which is over four times greater than that of the pristine PANI sensor), acceptable flexibility, excellent selectivity, and long-term stability at room temperature. The morphological and structural properties of the composite sensor materials were characterized by scanning electron microscopy and energy-dispersive spectroscopy characterization, and the surface chemistry of the hybrid sensors was analyzed by Fourier transform infrared spectroscopy.

Nutritional composition and phytochemical screening in different parts of L.

As the national flower of Korea, the L. (Rose of Sharon) is symbolic in its abundance and is a prominent feature of Korean culture.  has played an important role in Korea, not only as an ornamental plant but also as an essential ingredient in folk remedies through its various parts.

Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.

Background: Accurate and rapid measurement of the MRI volume of meningiomas is essential in clinical practice to determine the growth rate of the tumor. Imperfect automation and disappointing performance for small meningiomas of previous automated volumetric tools limit their use in routine clinical practice.

Purpose: To develop and validate a computational model for fully automated meningioma segmentation and volume measurement on contrast-enhanced MRI scans using deep learning.

Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

Background: Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported.

Purpose: To develop a deep learning-based auto-segmentation algorithm (DL-AS) for the detection of HCC and to predict MVI using computed tomography (CT) texture analysis.

Structural characteristics of sediment humins from South Korean lakes and their phenanthrene binding compared to other carbon sources.

Sediment humins are extremely important for binding hydrophobic organic contaminants in rivers and lakes. Nonetheless, little is known about their structure and binding. We, therefore, examined the structure and phenanthrene sorption affinity of sediment humin samples upstream, midstream, and downstream from two artificial lakes in South Korea by using the elemental C-NMR analysis, Freundlich model, and Langmuir model.

A self-degradable hydrogel sensor for a nerve agent tabun surrogate through a self-propagating cascade.

Nerve agents that irreversibly deactivate the enzyme acetylcholinesterase are extremely toxic weapons of mass destruction. Thus, developing methods to detect these lethal agents is important. To create an optical sensor for a surrogate of the nerve agent tabun, as well as a physical barrier that dissolves in response to this analyte, we devise a network hydrogel that decomposes via a self-propagating cascade.

Clinical application of 3D virtual and printed models for cerebrovascular diseases.

Objective: Three-dimensional (3D) printing techniques are rapidly advancing in the medical industry and in clinical practice. We aimed to evaluate the usefulness of 3D virtual and printed models of 6 representative cerebrovascular diseases using the software we developed.

Methods: Six cases consisted of 4 intracranial aneurysms (IAs) including complex ones with intrasaccular thrombosis, large size and a skull base location; 1 cavernous malformation in the pons; and 1 arteriovenous malformation in the parietal lobe.

Clinical application of patient-specific 3D printing brain tumor model production system for neurosurgery.

The usefulness of 3-dimensional (3D)-printed disease models has been recognized in various medical fields. This study aims to introduce a production platform for patient-specific 3D-printed brain tumor model in clinical practice and evaluate its effectiveness. A full-cycle platform was created for the clinical application of a 3D-printed brain tumor model (3D-printed model) production system.

Deep Reinforcement Learning Designed Shinnar-Le Roux RF Pulse Using Root-Flipping: DeepRF.

A novel approach of applying deep reinforcement learning to an RF pulse design is introduced. This method, which is referred to as DeepRF, is designed to minimize the peak amplitude or, equivalently, minimize the pulse duration of a multiband refocusing pulse generated by the Shinar Le-Roux (SLR) algorithm. In the method, the root pattern of SLR polynomial, which determines the RF pulse shape, is optimized by iterative applications of deep reinforcement learning and greedy tree search.

Removal of 1,4-Naphthoquinone by Birnessite-Catalyzed Oxidation: Effect of Phenolic Mediators and the Reaction Pathway.

This study investigated the birnessite (-MnO) catalyzed oxidative removal of 1,4-naphthoquinone (1,4-NPQ) in the presence of phenolic mediators; specifically, the kinetics of 1,4-NPQ removal under various conditions was examined, and the reaction pathway of 1,4-NPQ was verified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The removal rate of 1,4-NPQ by birnessite-catalyzed oxidation (pH = 5) was faster in the presence of phenolic mediators with electron-donating substituents (pseudo-first-order initial stage rate constant () = 0.380-0.

Chemically Triggered Synthesis, Remodeling, and Degradation of Soft Materials.

Polymer topology dictates dynamic and mechanical properties of materials. For most polymers, topology is a static characteristic. In this article, we present a strategy to chemically trigger dynamic topology changes in polymers in response to a specific chemical stimulus.

Artificial neural network for myelin water imaging.

Purpose: To demonstrate the application of artificial neural network (ANN) for real-time processing of myelin water imaging (MWI).

Methods: Three neural networks, ANN-I , ANN-I , and ANN-II, were developed to generate MWI. ANN-I and ANN-I were designed to output myelin water fraction (MWF) and geometric mean T of intra- and extra-cellular water signal (GMT ), respectively, whereas ANN-II generates a T distribution.

Inhalation toxicity of benzalkonium chloride and triethylene glycol mixture in rats.

Benzalkonium chloride (BAC), a disinfectant, and triethylene glycol (TEG), an organic solvent/sanitizer, are frequently combined in commercially available household sprays. To assess the respiratory effect of this combination, Sprague-Dawley rats were exposed to an aerosol containing BAC (0.5%, w/v) and TEG (10%, w/v) for up to 2 weeks in a whole-body inhalation chamber.

Evaluation of pulmonary toxicity of benzalkonium chloride and triethylene glycol mixtures using in vitro and in vivo systems.

Benzalkonium chloride (BAC) is a widely used disinfectant/preservative, and respiratory exposure to this compound has been reported to be highly toxic. Spray-form household products have been known to contain BAC together with triethylene glycol (TEG) in their solutions. The purpose of this study was to estimate the toxicity of BAC and TEG mixtures to pulmonary organs using in vitro and in vivo experiments.

Advances in gradient echo myelin water imaging at 3T and 7T.

Gradient echo myelin water imaging (GRE-MWI) is an MRI technique to measure myelin concentration and involves the analysis of signal decay characteristics of the multi-echo gradient echo data. The method provides a myelin water fraction as a quantitative biomarker for myelin. In this work, a new sequence and post-processing methods were proposed to generate high quality GRE-MWI images at 3T and 7T.

Enhanced Gas-Sensing Performance of GO/TiO₂ Composite by Photocatalysis.

Few studies have investigated the gas-sensing properties of graphene oxide/titanium dioxide (GO/TiO₂) composite combined with photocatalytic effect. Room temperature gas-sensing properties of the GO/TiO₂ composite were investigated towards various reducing gases. The composite sensor showed an enhanced gas response and a faster recovery time than a pure GO sensor due to the synergistic effect of the hybridization, such as creation of a hetero-junction at the interface and modulation of charge carrier density.