This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The ...applied dataset includes a total of 1053 mandibular third molars from 600 preoperative panoramic radiographic images. The extraction difficulty was evaluated based on the consensus of three human observers using the Pederson difficulty score (PDS). The classification model used a ResNet-34 pretrained on the ImageNet dataset. The correlation between the PDS values determined by the proposed model and those measured by the experts was calculated. The prediction accuracies for C1 (depth), C2 (ramal relationship), and C3 (angulation) were 78.91%, 82.03%, and 90.23%, respectively. The results confirm that the proposed CNN-based deep learning model could be used to predict the difficulty of extracting a mandibular third molar using a panoramic radiographic image.
The quantitative label-free detection of neurotransmitters provides critical clues in understanding neurological functions or disorders. However, the identification of neurotransmitters remains ...challenging for surface-enhanced Raman spectroscopy (SERS) due to the presence of noise. Here, we report spread spectrum SERS (ss-SERS) detection for the rapid quantification of neurotransmitters at the attomolar level by encoding excited light and decoding SERS signals with peak autocorrelation and near-zero cross-correlation. Compared to conventional SERS measurements, the experimental result of ss-SERS shows an exceptional improvement in the signal-to-noise ratio of more than three orders of magnitude, thus achieving a high temporal resolution of over one hundred times. The ss-SERS measurement further allows the attomolar SERS detection of dopamine, serotonin, acetylcholine, γ-aminobutyric acid, and glutamate without Raman reporters. This approach opens up opportunities not only for investigating the early diagnostics of neurological disorders or highly sensitive biomedical SERS applications but also for developing low-cost spectroscopic biosensing applications.
This review outlines problems and progress in development of solution-processed organic light-emitting diodes (SOLEDs) in industry and academia. Solution processing has several advantages such as low ...consumption of materials, low-cost processing, and large-area manufacturing. However, use of a solution process entails complications, such as the need for solvent resistivity and solution-processable materials, and yields SOLEDs that have limited luminous efficiency, severe roll-off characteristics, and short lifetime compared to OLEDs fabricated using thermal evaporation. These demerits impede production of practical SOLED displays. This review outlines the industrial demands for commercial SOLEDs and the current status of SOLED development in industries and academia, and presents research guidelines for the development of SOLEDs that have high efficiency, long lifetime, and good processability to achieve commercialization.
Hydrogen is regarded as an ideal fuel for vehicle applications owing to its high chemical energy. However, for on-board energy storage, fuel cell electric vehicles need compact, light, and affordable ...hydrogen storage system to replace the pressurized hydrogen tanks. In this regard, various materials and composites have been developed for denser and safer hydrogen storage. Among them, Mg is considered as a highly promising material to store the hydrogen in terms of gravimetric and volumetric capacity. However, because of its higher thermodynamic stability and sluggish hydrogen sorption kinetics, the sorption temperature is high and the sorption time is long, limiting for practical usage. Nanoscale material designs with various dimensionalities that have been extensively studied and used in countless research and development sectors, which can provide new strategies to tackle the limitations of Mg based hydrogen storage system. This review describes the fundamental properties, preparation, activation kinetics and thermodynamic stability of various nanostructured Mg/MgH2 materials (including bulk particles, nanofilms, nanowires and nanoparticles confined in nanoporous carbon structures and encapsulated by polymers) for feasible hydrogen storage applications, and summarizes their dimensional effects.
Highly efficient organic/inorganic hybrid perovskite light‐emitting diodes (PeLEDs) based on graphene anode are developed for the first time. Chemically inert graphene avoids quenching of excitons by ...diffused metal atom species from indium tin oxide. The flexible PeLEDs with graphene anode on plastic substrate show good bending stability; they provide an alternative and reliable flexible electrode for highly efficient flexible PeLEDs.
Abstract Perovskite light-emitting diodes (PeLEDs) based on three-dimensional (3D) polycrystalline perovskites suffer from ion migration, which causes overshoot of luminance over time during ...operation and reduces its operational lifetime. Here, we demonstrate 3D/2D hybrid PeLEDs with extremely reduced luminance overshoot and 21 times longer operational lifetime than 3D PeLEDs. The luminance overshoot ratio of 3D/2D hybrid PeLED is only 7.4% which is greatly lower than that of 3D PeLED (150.4%). The 3D/2D hybrid perovskite is obtained by adding a small amount of neutral benzylamine to methylammonium lead bromide, which induces a proton transfer from methylammonium to benzylamine and enables crystallization of 2D perovskite without destroying the 3D phase. Benzylammonium in the perovskite lattice suppresses formation of deep-trap states and ion migration, thereby enhances both operating stability and luminous efficiency based on its retardation effect in reorientation.
Abstract Nanoparticles can be valuable therapeutic options to overcome physical barriers to reach central nervous system. Systemically administered nanoparticles can pass through blood-neural ...barriers; whereas, locally injected nanoparticles directly reach neuronal and perineuronal cells. In this review, we highlight the importance of size, surface charge, and shape of nanoparticles in determining therapeutic effects on brain and retinal diseases. These features affect overall processes of delivery of nanoparticles: in vivo stability in blood and other body fluids, clearance via mononuclear phagocyte system, attachment with target cells, and penetration into target cells. Furthermore, they are also determinants of nano-bio interfaces: they determine corona formation with proteins in body fluids. Taken together, we emphasize the importance of considerations on characteristics of nanoparticles more suitable for the treatment of brain and retinal diseases in the development of nanoparticle-based therapeutics. From the Clinical Editor The central nervous system (CNS) remains an area where drug access and delivery are difficult clinically due to the blood brain barrier. With advances in nanotechnology, many researchers have designed and produced nanoparticle-based systems in an attempt to solve this problem. In this concise review, the authors described the current status of drug delivery to the CNS, based on particle size and shape. This article should stimulate more research to be done on future drug design.
Li‐metal is gaining attention as a next generation anode active material, of which the primary attribute is its energy density. However, Li dendrite formation is the primary challenge. Herein, a ...design strategy with increased structural dimensions and hierarchy for Li‐metal anode is investigated to stabilize the dendrite formation for extending the cycle life with high reversibility. For this, diverse structural current collectors (CCs) are fabricated by manipulating structural design in different length scales and characterized as a Li‐metal anode. The hierarchy (i.e., nanostructures inside the microcavities) can not only reduce the current density on entire anode surface but also concentrate the local electrical field onto inner surfaces of the microstructures, inducing preferential Li nucleation inside microcavities and promoting confined growth of Li. It is confirmed that introduction of structural hierarchy can enhance the cycle life by 364% and the preservation of coulombic efficiency > 90% by 266%. The design strategy is extended by exploring a practical one‐step fabrication of the hierarchical CC with even greater performance via the inward growth mechanism. This work elucidates the mechanism of inward Li growth using tailored surface geometries for Li dendrite suppression, which can be a guideline for designing structured anode CCs for Li‐metal batteries.
Structururally hierarchical current collectors containing nanorods on the inner surface of the microcavities are proposed. Nanorods concentrate the local electrical field onto inner surfaces of the microcavities, inducing preferential Li nucleation inside micropatterns and promoting agglomeration of Li. This work proposes a new pathway to control nucleation sites using tailored surface geometries for Li dendrite suppression.
The development of various flexible and stretchable materials has attracted interest for promising applications in biomedical engineering and electronics industries. This interest in wearable ...electronics, stretchable circuits, and flexible displays has created a demand for stable, easily manufactured, and cheap materials. However, the construction of flexible and elastic electronics, on which commercial electronic components can be mounted through simple and cost-effective processing, remains challenging. We have developed a nanocomposite of carbon nanotubes (CNTs) and polydimethylsiloxane (PDMS) elastomer. To achieve uniform distributions of CNTs within the polymer, an optimized dispersion process was developed using isopropyl alcohol (IPA) and methyl-terminated PDMS in combination with ultrasonication. After vaporizing the IPA, various shapes and sizes can be easily created with the nanocomposite, depending on the mold. The material provides high flexibility, elasticity, and electrical conductivity without requiring a sandwich structure. It is also biocompatible and mechanically stable, as demonstrated by cytotoxicity assays and cyclic strain tests (over 10,000 times). We demonstrate the potential for the healthcare field through strain sensor, flexible electric circuits, and biopotential measurements such as EEG, ECG, and EMG. This simple and cost-effective fabrication method for CNT/PDMS composites provides a promising process and material for various applications of wearable electronics.
Decoding motor commands from noninvasively measured neural signals has become important in brain-computer interface (BCI) research. Applications of BCI include neurorehabilitation after stroke and ...control of limb prostheses. Until now, most studies have tested simple movement trajectories in two dimensions by using constant velocity profiles. However, most real-world scenarios require much more complex movement trajectories and velocity profiles. In this study, we decoded motor commands in three dimensions from electroencephalography (EEG) recordings while the subjects either executed or observed/imagined complex upper limb movement trajectories. We compared the accuracy of simple linear methods and nonlinear methods. In line with previous studies our results showed that linear decoders are an efficient and robust method for decoding motor commands. However, while we took the same precautions as previous studies to suppress eye-movement related EEG contamination, we found that subtracting residual electro-oculogram activity from the EEG data resulted in substantially lower motor decoding accuracy for linear decoders. This effect severely limits the transfer of previous results to practical applications in which neural activation is targeted. We observed that nonlinear methods showed no such drop in decoding performance. Our results demonstrate that eye-movement related contamination of brain signals constitutes a severe problem for decoding motor signals from EEG data. These results are important for developing accurate decoders of motor signal from neural signals for use with BCI-based neural prostheses and neurorehabilitation in real-world scenarios.
PDF
