Investigation of the Effect of the Passivation on the Charge Transfer from MAPbI to Electron Transport Layer Using a Heterodyne Transient Grating Spectroscopic Technique.

We fabricated MAPbI perovskite thin films with ZnO on a glass substrate, in which a passivation layer (Phenethylammonium iodide (PEAI); p-methoxyphenethylammonium iodide (CHO-PEAI); 2-methoxyethylammonium iodide (MEAI)) was inserted between two layers. In order to understand the effect of the insertion of each passivation material on the transfer efficiency of the photo-generated electrons from MAPbI to ZnO, we observed the near-field heterodyne transient grating (NF-HD-TG) responses of each film and investigated the component arising from the recombination of the trapped electrons at the ZnO surface. Based on the accelerated recombination between photo-generated holes remaining in the MAPbI layer and surface-trapped electrons in ZnO and the increase in the number of the trapped electrons in ZnO when either CHO-PEAI or PEAI was applied, we successfully revealed that the charge transfer efficiency was enhanced by the insertion of the passivation materials including a benzene ring stabilizing the defect states.

Polygenic risk score model for renal cell carcinoma in the Korean population and relationship with lifestyle-associated factors.

Background: The polygenic risk score (PRS) is used to predict the risk of developing common complex diseases or cancers using genetic markers. Although PRS is used in clinical practice to predict breast cancer risk, it is more accurate for Europeans than for non-Europeans because of the sample size of training genome-wide association studies (GWAS). To address this disparity, we constructed a PRS model for predicting the risk of renal cell carcinoma (RCC) in the Korean population.

Development of microcatheter tube extrusion angle estimation system using convolutional neural network segmentation.

This study presents a deep learning-based monitoring system for estimating extrusion angles in the manufacturing process of microcatheter tubes. Given the critical nature of these tubes, which are directly inserted into the human body, strict quality control is imperative. To mitigate potential quality variations stemming from operator actions, a system utilizing a convolutional neural network to precisely measure the extrusion angle-a parameter with profound implications for tube quality-is developed.

Novel GSK-3β Inhibitor Neopetroside A Protects Against Murine Myocardial Ischemia/Reperfusion Injury.

Recent trends suggest novel natural compounds as promising treatments for cardiovascular disease. The authors examined how neopetroside A, a natural pyridine nucleoside containing an α-glycoside bond, regulates mitochondrial metabolism and heart function and investigated its cardioprotective role against ischemia/reperfusion injury. Neopetroside A treatment maintained cardiac hemodynamic status and mitochondrial respiration capacity and significantly prevented cardiac fibrosis in murine models.

A Wearable Textile-Embedded Dielectric Elastomer Actuator Haptic Display.

With advances in mobile computing and virtual/augmented reality technologies, communicating through touch using wearable haptic devices is poised to enrich and augment current information delivery channels that typically rely on sight and hearing. To realize a wearable haptic device capable of effective data communication, both ergonomics and haptic performance (i.e.

Comparative efficacy and safety of fimasartan in patients with hypertension: A network meta-analysis of randomized controlled trials.

Hypertension is a prevalent risk factor for cardiovascular disease. Angiotensin II receptor blockers are widely prescribed to patients with hypertension, while new drugs are continuously developed. However, data on comparative efficacy and safety of novel agents, such as fimasartan, are scarce.

Development of a Cs-free negative hydrogen ion source system using multi-pulsed plasma sources.

The Korea Atomic Energy Research Institute has recently proposed and developed a novel cesium-free negative hydrogen/deuterium ion source system based on two pulsed plasma sources for fusion and particle accelerator applications. The main feature of this ion source system is the use of both magnetic filters and plasma pulsing (also called the temporal filter). The system operates with two alternate pulsing sequences related to the respective plasma sources, thereby switching the plasmas in the after-glow state in an alternating manner.

Three-Dimensional Postoperative Results Prediction for Orthognathic Surgery through Deep Learning-Based Alignment Network.

To date, for the diagnosis of dentofacial dysmorphosis, we have relied almost entirely on reference points, planes, and angles. This is time consuming, and it is also greatly influenced by the skill level of the practitioner. To solve this problem, we wanted to know if deep neural networks could predict postoperative results of orthognathic surgery without relying on reference points, planes, and angles.

Deep-Learning-Based Detection of Cranio-Spinal Differences between Skeletal Classification Using Cephalometric Radiography.

The aim of this study was to reveal cranio-spinal differences between skeletal classification using convolutional neural networks (CNNs). Transverse and longitudinal cephalometric images of 832 patients were used for training and testing of CNNs (365 males and 467 females). Labeling was performed such that the jawbone was sufficiently masked, while the parts other than the jawbone were minimally masked.

Deep learning based prediction of necessity for orthognathic surgery of skeletal malocclusion using cephalogram in Korean individuals.

Background: Posteroanterior and lateral cephalogram have been widely used for evaluating the necessity of orthognathic surgery. The purpose of this study was to develop a deep learning network to automatically predict the need for orthodontic surgery using cephalogram.

Methods: The cephalograms of 840 patients (Class ll: 244, Class lll: 447, Facial asymmetry: 149) complaining about dentofacial dysmorphosis and/or a malocclusion were included.

Deep learning based prediction of extraction difficulty for mandibular third molars.

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).

Structural and Dynamical Characteristics of Short-Chain Branched Ring Polymer Melts at Interface under Shear Flow.

We present a detailed analysis of the interfacial chain structure and dynamics of confined polymer melt systems under shear over a wide range of flow strengths using atomistic nonequilibrium molecular dynamics simulations, paying particular attention to the rheological influence of the closed-loop ring geometry and short-chain branching. We analyzed the interfacial slip, characteristic molecular mechanisms, and deformed chain conformations in response to the applied flow for linear, ring, short-chain branched (SCB) linear, and SCB ring polyethylene melts. The ring topology generally enlarges the interfacial chain dimension along the neutral direction, enhancing the dynamic friction of interfacial chains moving against the wall in the flow direction.

Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs.

Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether convolutional neural networks (CNNs) can judge soft tissue profiles requiring orthognathic surgery using facial photographs alone. 822 subjects with dentofacial dysmorphosis and / or malocclusion were included.

Investigation of thermal conductivity for liquid metal composites using the micromechanics-based mean-field homogenization theory.

For the facile use of liquid metal composites (LMCs) for soft, stretchable and thermal systems, it is crucial to understand and predict the thermal conductivity of the composites as a function of liquid metal (LM) volume fraction and applied strain. In this study, we investigated the effective thermal conductivity of LMCs based on various mean-field homogenization frameworks including Eshelby, Mori-Tanaka, differential and double inclusion methods. The double inclusion model turned out to make the prediction closest to the experimental results in a wide range of LM volume fractions.

Head-compliant microstrip split ring resonator for non-invasive healing monitoring after craniosynostosis-based surgery.

A soft and highly directive, proximity-coupled split-ring resonator fabricated with a liquid alloy, copper and polydimethylsiloxane (PDMS) is presented. The same was designed for sensing osteogenesis of calvarial bone. As dielectric properties of bone grafts in ossifying calvarial defects should change during the osteogenesis process, devices like this could monitor the gradual transformation of the defect into bone by differentiating changes in the dielectric properties as shifts in the resonance frequency.

Exchange protein directly activated by cAMP (Epac) 1 plays an essential role in stress-induced exercise capacity by regulating PGC-1α and fatty acid metabolism in skeletal muscle.

Exchange protein directly activated by cAMP (Epac) mediates cAMP-mediated cell signal independent of protein kinase A (PKA). Mice lacking Epac1 displayed metabolic defect suggesting possible functional involvement of skeletal muscle and exercise capacity. Epac1 was highly expressed, but not Epac 2, in the extensor digitorum longus (EDL) and soleus muscles.

Phase Changing Materials-Based Variable-Stiffness Tensegrity Structures.

Soft robots leverage deformable bodies to achieve different types of locomotion, improve transportability, and safely navigate cluttered environments. In this context, variable-stiffness structures provide soft robots with additional properties, such as the ability to increase forces transmitted to the environment, to lock into different body configurations, and to reduce the number of actuators required for morphological change. Tensegrity structures have been recently proposed as a biologically inspired design principle for soft robots.

Bio-inspired untethered fully soft robots in liquid actuated by induced energy gradients.

Soft robotics with new designs, fabrication technologies and control strategies inspired by nature have been totally changing our view on robotics. To fully exploit their potential in practical applications, untethered designs are preferred in implementation. However, hindered by the limited thermal/mechanical performance of soft materials, it has been always challenging for researchers to implement untethered solutions, which generally involve rigid forms of high energy-density power sources or high energy-density processes.

High transmittance and deep RGB primary electrochromic color filter for high light out-coupling electro-optical devices.

We report a transmittance controllable electrochromic color filter (TCECF) by incorporating new electrochromic leuco dyes and their optimized composition. Each primary color red (R), green (G), and blue (B) electrochromic filter has an excellent transmittance of more than 84% at 650 nm, 540 nm, 450 nm, and the color coordinates are controllable from white (0.332, 0.

Tetrahydrobiopterin enhances mitochondrial biogenesis and cardiac contractility via stimulation of PGC1α signaling.

Tetrahydrobiopterin (BH4) shows therapeutic potential as an endogenous target in cardiovascular diseases. Although it is involved in cardiovascular metabolism and mitochondrial biology, its mechanisms of action are unclear. We investigated how BH4 regulates cardiovascular metabolism using an unbiased multiple proteomics approach with a sepiapterin reductase knock-out (Spr) mouse as a model of BH4 deficiency.