Deep learning-based image classification of sea turtles using object detection and instance segmentation models.

Sea turtles exhibit high migratory rates and occupy a broad range of habitats, which in turn makes monitoring these taxa challenging. Applying deep learning (DL) models to vast image datasets collected from citizen science programs can offer promising solutions to overcome the challenge of monitoring the wide habitats of wildlife, particularly sea turtles. Among DL models, object detection models, such as the You Only Look Once (YOLO) series, have been extensively employed for wildlife classification.

Cobalt-Doped Ceria Sensitizer Effects on Metal Oxide Nanofibers: Heightened Surface Reactivity for High-Performing Chemiresistive Sensors.

Chemiresistive gas sensors based on semiconducting metal oxides typically rely on noble metal catalysts to enhance their sensitivity and selectivity. However, noble metal catalysts have several drawbacks for practical utilization, including their high cost, their propensity for spontaneous agglomeration, and poisoning effects with certain types of gases. As such, in the interest of commercializing the chemiresistive gas sensor technology, we propose an alternative design for a noble-metal-free sensing material through the case study of Co-doped ceria (Co-CeO) catalysts embedded in a SnO matrix.

Deep learning-based image classification of turtles imported into Korea.

Although turtles play a key role in maintaining healthy and balanced environments, these are endangered due to global trade to meet the high demand for food, medicine, and pets in Asia. In addition, imported non-native turtles have been controlled as alien invasive species in various countries, including Korea. Therefore, a rapid and accurate classification of imported turtles is needed to conserve and detect those in native ecosystems.

Two-Dimensional Electrically Conductive Metal-Organic Frameworks as Chemiresistive Sensors.

Metal-organic frameworks (MOFs) have emerged as attractive chemical sensing materials due to their exceptionally high porosity and chemical diversity. Nevertheless, the utilization of MOFs in chemiresistive type sensors has been hindered by their inherent limitation in electrical conductivity. The recent emergence of two-dimensional conductive MOFs (2D c-MOFs) has addressed this limitation by offering enhanced electrical conductivity, while still retaining the advantageous properties of MOFs.

Surface Modulation of CoO Yolk-Shell Spheres with Tungsten Doping for Superior Acetone Sensitivity.

This study introduces a promising technique to enhance the sensitivity of p-type semiconductors in gas-sensing applications. By utilizing a glycerate-templated synthesis approach, a unique hierarchical W-doped CoO yolk-shell sphere (YSS)-based sensor was developed, exhibiting exceptional sensitivity toward acetone gas. The synthesized YSSs feature a yolk-shell structure with a diameter of approximately 500 nm and a large surface area of 117.

A case study on DNA barcoding for pet food mislabeling in South Korea.

Due to the close relationship between pets and humans, pet owners are highly invested in proper diets for their pets. Even though pet food mislabeling is concerning, there are few studies on this topic. This study investigated pet food mislabeling in South Korea's market based on DNA barcoding.

Facile Synthesis of CoO/CoMoO Heterostructure Nanosheets for Enhanced Acetone Detection.

Although p-type semiconductors exhibit highly selective and stable chemiresistive gas sensing performances compared to conventional n-type semiconductors, their low sensitivity had long impeded their practical development. In this work, we developed highly porous CoO/CoMoO heterostructure nanosheets (NSs) with enhanced sensitivity and superior stability toward acetone gas through a facile solution-based approach with Mo-impregnated Co-based metal-organic frameworks as the starting material. The spontaneous formation of a large number of p-p heterojunctions at the CoO-CoMoO interface would facilitate the adsorption of oxygen and acetone molecules, as verified by density functional theory calculations.

Image Classification of Amazon Parrots by Deep Learning: A Potentially Useful Tool for Wildlife Conservation.

Parrots play a crucial role in the ecosystem by performing various roles, such as consuming the reproductive structures of plants and dispersing plant seeds. However, most are threatened because of habitat loss and commercial trade. Amazon parrots are one of the most traded and illegally traded parrots.

Ultrafast Ambient-Air Exsolution on Metal Oxide via Momentary Photothermal Effect.

The process of exsolution for the synthesis of strongly anchored metal nanoparticles (NPs) on host oxide lattices has been proposed as a promising strategy for designing robust catalyst-support composite systems. However, because conventional exsolution processes occur in harsh reducing environments at high temperatures for long periods of time, the choice of support materials and dopant metals are limited to those with inherently high thermal and chemical stability. Herein, we report the exsolution of a series of noble metal catalysts (Pt, Rh, and Ir) from metal oxide nanofibers (WO NFs) supports in an entirely ambient environment induced by intense pulsed light (IPL)-derived momentary photothermal treatment (>1000 °C).

Treatment of purely ligamentous dorsoulnar radiocarpal dislocation with ulnar translation of the carpus: A case report.

Rationale: Radiocarpal fracture-dislocations are extremely infrequent injuries caused by high-energy trauma and involve significant osseous and ligamentous injuries. If not treated properly, it can lead to serious complications such as ulnar translation of the carpus, multidirectional instability, loss of motion, and post-traumatic arthritis. Purely ligamentous injuries are rarer than fracture-dislocation injuries.

Effects of Aerobic Exercise on Tau and Related Proteins in Rats with Photochemically-Induced Infarction.

Background: Recent evidence indicates brain ischemia is associated with accumulations of abnormal tau and related proteins. However, the effects of aerobic training on these proteins have not been evaluated.

Objective: We aimed to evaluate the effect of aerobic exercise on the phosphorylation and acetylation of tau and on the expressions of tau related proteins in a rat stroke model and to compare the effects of aerobic exercise with those observed in our previous study on task specific training (TST).

Comparison of implant position and joint awareness between fixed- and mobile-bearing unicompartmental knee arthroplasty: a minimum of five year follow-up study.

Purpose: To compare the implant position and patient-reported outcomes (PROs) regarding joint awareness using the Forgotten Joint Score (FJS) following between fixed-bearing (FB) and mobile-bearing (MB) unicompartmental knee arthroplasty (UKA) with a minimum of five years' follow-up.

Methods: One hundred fifteen consecutive UKAs (58 FB UKAs and 57 MB UKAs) performed were retrospectively evaluated. We compared the radiographic parameters including component positions and relationships as well as lower extremity alignment.

Finite element analysis of cornea deformation and curvature change during the keratoplasty suturing process.

Keratoplasty, which is cornea transplant surgery, is one of the treatment methods for patients with turbidity or keratitis. Recently, keratoplasty using a surgical robot was studied to increase precision. In this study, the effect of surgical factors on the deformation and curvature of the cornea were analyzed in order to improve the accuracy of keratoplasty and derive the optimal surgical factors using finite element method (FEM).