Neuromorphic devices that emulate biological synaptic behavior are emerging as key enablers for in-sensor intelligence. While visible-light-responsive systems have dominated the field, recent efforts have expanded toward invisible spectral regions: ultraviolet (UV), infrared (IR), and X-ray, where unique photon-matter interactions offer new avenues for optical plasticity. These invisible-wavelength stimuli enable synaptic functions such as short-term and long-term potentiation through mechanisms like persistent photoconductivity, defect ionization, and interfacial charge trapping, often without the need for external programming circuitry. Although these devices are increasingly important for intelligent imaging, radiation-tolerant electronics, and secure communication, related studies are still fragmented across different fields and lack an organized overview. In this review, we systematically categorize and analyze optoelectronic synapses that operate under UV, IR, and X-ray illumination. We highlight representative material systems including Ga₂O₃, perovskites, wide-bandgap oxides, and hybrid nanocomposites, and discuss their device architectures, synaptic behaviors, and operational metrics. Special emphasis is placed on the underlying physical mechanisms, spectral selectivity, and integration prospects for artificial retinas, neuromorphic vision systems, and multimodal sensing arrays. We also provide outlooks for scalable, multispectral, and energy-efficient neuromorphic platforms beyond the visible.

Tunable analog activation functions are essential for energy-efficient artificial intelligence (AI) hardware. Two transistor designs are presented: the sigmoid-like activation function transistor (SA-transistor) and the Gaussian-like activation function transistor (GA-transistor), which implement analog sigmoid and Gaussian functions using a screen gate structure. In the SA-transistor, adjusting the screen gate voltage (V_Screen-G) enables precise control of the sigmoid slope and saturation level. In the GA-transistor, the amplitude and standard deviation of the Gaussian response are tunable through the same mechanism. These transistors enable precise and continuous tuning of analog activation parameters such as slope, amplitude, and width at the device level. This controllability allows hardware-optimized neural computations tailored to specific tasks or datasets. Applied in real-world tasks, the SA-transistor improved lung magnetic resonance imaging (MRI) classification accuracy from 77% to 84%, and the GA-transistor raised the time-series forecasting coefficient of determination (R²) from 0.82 to 0.93. Furthermore, by assembling these devices into a hardware-based multilayer perceptron (MLP), robust inference is demonstrated on the IRIS dataset with 96.7% overall accuracy. This system-level validation highlights that analog activation transistors can directly support neuromorphic accelerators without digital post-processing, reducing circuit complexity and power consumption while maintaining high classification fidelity.

This study presents an advanced in vitro model that closely recapitulates in situ tumorigenesis and provides novel insights into the metastatic cascade. The pdECM system enables the reconstruction of EMT dynamics, highlighting the critical role of ECM composition in metastasis and offering a physiologically relevant platform for the development of targeted therapies.

The current study introduces photocurable macromolecular resin (KIS resin) and aims to assess its use as a basic material for implant surgical stent fabrication using 3D printing and the digital light processing (DLP) technique. The biological and physical properties of KIS resin were evaluated, and radiological analysis was performed to assess the clinical accuracy of a 3D-printed surgical stent. The physical characteristics were analyzed in accordance with the guidelines of certified standards, and cell adhesion analysis was performed to evaluate the viability of human gingival fibroblast (hGF) cells exposed to KIS resin and conventional orthodontic acrylic resin. Radiological analysis of animals was carried out by pairwise overlap of pre-and postoperative images. The physical characteristics of KIS resin met the ISO 20795-1, ASTM D695, and ASTM D638 standards. The hGF cells on KIS resin samples exhibited better cell attachment and connection compared to those exposed to conventional resins. The findings of the radiological analyses showed statistically significant differences in the deviations between DLP-printed surgical stents and conventional stents, with the horizontal linear deviations being smaller in the coronal and middle levels of the former. Moreover, the angular deviation was also smaller in the DLP stent group. Therefore, KIS resin exhibited favorable physical properties and cell viability, highlighting its potential for use as a basic material for 3D-printed implant surgical guides. Further evaluation of the use of implant surgical stents fabricated using KIS resin and the DLP method as a proper tool for implant placement with clinical utility should be carried out.

Tooth autotransplantation refers to tooth transplantation from the donor to the recipient site of the same individual. Occasionally, there are situations where autotransplantation cannot be carried out immediately at clinic. In such cases, donor teeth cryopreservation is necessary to overcome limited indications. Cryopreservation media and nutrients play essential roles in preserving the periodontal ligament cells' activity. Several studies have focused on cryopreservation media and nutrients. Platelet-rich plasma (PRP) contains lots of growth factors without inducing immunologic responses or pathologic complications. Therefore, self serum and PRP might be positive factors in the cryopreservation process for preserving the periodontal ligaments (PDLs) viability. In this study, beagle dog's incisors were cryopreserved for three months in different cryopreservation media, including Dulbecco's modified eagle medium (DMEM, containing DMSO), DMEM+20% self serum, DMEM+20% self serum+PRP, and DMEM+20% fetal bovine serum (FBS). Histological results revealed that DMEM+20% self serum+PRP and DMEM+20% FBS groups showed significantly less root resorption and higher regeneration of periodontal ligament cells and that PRP is a positive factor in the cryopreservation process to preserve PDLs viability. Therefore, cryopreservation media with PRP will be a good periodontal tissue regeneration option after long-term cryopreservation in a tooth autotransplantation procedure.

Biphasic calcium phosphate (BCP), which is a -tricalcium phosphate (TCP) and hydroxyapatite (HA) composite, is used mainly as a bone graft material. However, it has recently been used for orthopedic, oral, and maxillofacial surgeries. The use of BCP to produce an absorbable screw and plate to reconstruct fractures has been suggested. Nevertheless, further research on using BCP in the surgical field will be needed. In particular, studies on the physical properties of BCP and in vivo analysis are essential. In this study, TCP and HA were mixed at a ratio of 7:3 and heat-treated to form BCP. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffraction, and an MTT assay were conducted to evaluate the surface characteristics and physical and biological properties of each sample. In addition, BCP was used to produce a screw to be implanted into the mandible of beagles. An analysis of the physical properties of BCP confirmed the intermediate properties between TCP and HA. The cell viability was better with BCP than TCP, and significant differences were observed on days 1 and 3. Histological analysis at eight weeks after inserting the BCP screw into the mandible of beagles revealed osseointegration between the BCP screw and bone. The results showed that BCP had better mechanical properties than TCP and excellent biocompatibility, highlighting its potential clinical use. In addition, according to its processing, BCP may be used to produce screws and plates for fracture repair or as membranes and space-modeling tents for guided bone regeneration.

Recently, The world is making efforts to develop Renewable energy for low carbon green growth. In Korea, Localization technology development of hydro power is necessary because almost every hydro power in Korea depends on overseas company. Especially, Hydro power studies are actively underway on approach of modernization of existing hydro power plants. Technical design of the small hydro power has been secured. Therefore, The technology of big hydro power has become necessary such as design, test, manufacture, installation. In this study, we studied the hydro power plant three-dimensional shape information obtaining method for securing technology for the design of hydropower plants. As a result of scanning using the non-contact 3D scanning technique, it was possible to obtain a precise 3D shape that satisfies the international standard IEC-60193. Using the shape, it was used for CFD analysis and model turbine testing to confirm its performance, and subsequently succeeded in developing a turbine runner with a novel design.

Neuromorphic devices that emulate biological synaptic behavior are emerging as key enablers for in-sensor intelligence. While visible-light-responsive systems have dominated the field, recent efforts have expanded toward invisible spectral regions: ultraviolet (UV), infrared (IR), and X-ray, where unique photon-matter interactions offer new avenues for optical plasticity. These invisible-wavelength stimuli enable synaptic functions such as short-term and long-term potentiation through mechanisms like persistent photoconductivity, defect ionization, and interfacial charge trapping, often without the need for external programming circuitry. Although these devices are increasingly important for intelligent imaging, radiation-tolerant electronics, and secure communication, related studies are still fragmented across different fields and lack an organized overview. In this review, we systematically categorize and analyze optoelectronic synapses that operate under UV, IR, and X-ray illumination. We highlight representative material systems including Ga₂O₃, perovskites, wide-bandgap oxides, and hybrid nanocomposites, and discuss their device architectures, synaptic behaviors, and operational metrics. Special emphasis is placed on the underlying physical mechanisms, spectral selectivity, and integration prospects for artificial retinas, neuromorphic vision systems, and multimodal sensing arrays. We also provide outlooks for scalable, multispectral, and energy-efficient neuromorphic platforms beyond the visible.

Tunable analog activation functions are essential for energy-efficient artificial intelligence (AI) hardware. Two transistor designs are presented: the sigmoid-like activation function transistor (SA-transistor) and the Gaussian-like activation function transistor (GA-transistor), which implement analog sigmoid and Gaussian functions using a screen gate structure. In the SA-transistor, adjusting the screen gate voltage (V_Screen-G) enables precise control of the sigmoid slope and saturation level. In the GA-transistor, the amplitude and standard deviation of the Gaussian response are tunable through the same mechanism. These transistors enable precise and continuous tuning of analog activation parameters such as slope, amplitude, and width at the device level. This controllability allows hardware-optimized neural computations tailored to specific tasks or datasets. Applied in real-world tasks, the SA-transistor improved lung magnetic resonance imaging (MRI) classification accuracy from 77% to 84%, and the GA-transistor raised the time-series forecasting coefficient of determination (R²) from 0.82 to 0.93. Furthermore, by assembling these devices into a hardware-based multilayer perceptron (MLP), robust inference is demonstrated on the IRIS dataset with 96.7% overall accuracy. This system-level validation highlights that analog activation transistors can directly support neuromorphic accelerators without digital post-processing, reducing circuit complexity and power consumption while maintaining high classification fidelity.