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Organic Light-Emitting Diodes (OLEDs) require several organic layers, including carrier injection layers, charge transport layers, and light-emitting layers (EML). Recently, many panel companies have been using layers with a dual function of charge transport and blocking to simplify the layer structure. At the same time, efficient charge injection into the EML is required to improve the device characteristics. In particular, the hole injection properties are important in devices using phosphorescent emitters because it is a major factor in forming the broad recombination zone. This study reports the factors influencing the device performances using three OLEDs with different electron-blocking layers (EBL). By adjusting the EBL’s energy levels, it is possible to form a broad recombination zone and reduce hole accumulation and polaron-induced stress at the interface. In addition, the wide dispersion of exciton formation reduces the overcrowding of exciton which induces exciton quenching and relieves an efficiency roll-off at high luminance. Consequently, the external quantum efficiency of N-([1,1'-biphenyl]-4-yl)-N-(9,9-dimethyl-9H-fluoren-2-yl)-11,11-dimethyl-11H-benzo[b]fluoren-3-amine with a relatively deep HOMO level is increased by more than 2% with a relaxed roll-off of 7% at 3000 cd/m2 and a device lifetime is increased fivefold compared to those of N-([1,1′-biphenyl]-4-yl)-N-(9,9-dimethyl-9H-fluoren-2-yl)-11,11-dimethyl-11H-benzo[b]fluoren-2-amine with a relatively shallow HOMO level.

Abstract Amyloid-β (Aβ) oligomers are implicated in the onset of Alzheimer’s disease (AD). Herein, quinoline-derived half-curcumin-dioxaborine (Q-OB) fluorescent probe was designed for detecting Aβ oligomers by finely tailoring the hydrophobicity of the biannulate donor motifs in donor-π-acceptor structure. Q-OB shows a great sensing potency in dynamically monitoring oligomerization of Aβ during amyloid fibrillogenesis in vitro. In addition, we applied this strategy to fluorometrically analyze Aβ self-assembly kinetics in the cerebrospinal fluids (CSF) of AD patients. The fluorescence intensity of Q-OB in AD patients’ CSF revealed a marked change of log (I/I 0 ) value of 0.34 ± 0.13 (cognitive normal), 0.15 ± 0.12 (mild cognitive impairment), and 0.14 ± 0.10 (AD dementia), guiding to distinguish a state of AD continuum for early diagnosis of AD. These studies demonstrate the potential of our approach can expand the currently available preclinical diagnostic platform for the early stages of AD, aiding in the disruption of pathological progression and the development of appropriate treatment strategies.

Even with a plenty amount of normal samples, anomaly detection has been considered as a challenging machine learning task due to its one-class nature, i. e., the lack of anomalous samples in training time. It is only recently that a few-shot regime of anomaly detection became feasible in this regard, e. g., with a help from large vision-language pre-trained models such as CLIP, despite its wide applicability. In this paper, we explore the potential of large text-to-image generative models in performing few-shot industrial anomaly detection. Specifically, recent text-to-image models have shown unprecedented ability to generalize from few images to extract their common and unique concepts, and even encode them into a textual token to “personalize” the model: so-called textual inversion. Here, we question whether this personalization is specific enough to discriminate the given images from their potential anomalies, which are often, e. g., open-ended, local, and hard-to-detect. We observe that standard textual inversion exhibits a weaker understanding in localized details within objects, which is not enough for detecting industrial anomalies accurately. Thus, we explore the utilization of model personalization to address anomaly detection and propose Anomaly Detection via Personalization (ADP). ADP enables extracting fine-grained local details shared in the images with simple-yet an effective regularization scheme from the zero-shot transferability of CLIP. We also propose a self-tuning scheme to further optimize the performance of our detection pipeline, leveraging synthetic data generated from the personalized generative model. Our experiments show that the proposed inversion scheme could achieve state-of-the-art results on two industrial anomaly benchmarks, MVTec-AD and VisA, in the regime of few normal samples.

Engineering excitation wavelength of photosensitizers allows to enhanced reactive oxygen species but controlling the wavelength corresponding to operating conditions remains challenging. Here, the authors implement a wavelength-engineerable imidazolium-based porous organic polymer and demonstrate tuning of the optimal wavelength for maximum performance by modifying the linker system.

In this paper, we propose a novel approach to enhance the generalization performance of deep neural networks. Our method employs a hierarchical hypersphere-based constraint that organizes weight vectors hierarchically based on observed data. By diversifying the parameter space of hyperplanes in the classification layer, we aim to encourage discriminative generalization. We introduce a self-supervised grouping method designed to unveil hierarchical structures in scenarios with unknown hierarchy information. To maximize distances between weight vectors on multiple hyperspheres, we propose a novel metric that combines discrete and continuous measures. This regularization encourages diverse orientations, consequently leading to improved generalization. Extensive evaluations on datasets, including CUB200-2011, Stanford-Cars, CIFAR-100, and TinyImageNet, consistently demonstrate enhancements in classification performance compared to baseline settings.

Fluorescence imaging of amyloid beta (Aβ) polypeptide using a small‐molecule fluorophore is a practical system for Alzheimer's disease (AD) diagnosis in clinical and research fields. Herein, a molecular designing strategy for a new fluorogenic probe that equips bathochromic emission shift and enhanced binding affinity toward Aβ fibril through structural optimization is suggested. Thioflavin T (ThT)‐derived fluorescent dyes are developed by adjusting the hydrophobicity of electron donor moiety in D–π–A structures with biannulated ring expansion. Indeed, probes are tuned to have redshifted fluorescence emission wavelength and optimized binding affinities for Aβ fibrils in vitro and cortical imaging. Detection of background signal is minimized by maintaining the photophysical properties of twisted intramolecular charge transfer (TICT), resulting in significantly sensitive fluorogenic probes for outstanding bioimaging in AD.

The pathological origin of Alzheimer's disease (AD) is still shrouded in mystery, despite intensive worldwide research efforts. The selective visualization of β-amyloid (Aβ), the most abundant proteinaceous deposit in AD, is pivotal to reveal AD pathology. To date, several small-molecule fluorophores for Aβ species have been developed, with increasing binding affinities. In the current work, two organic small-molecule dioxaborine-derived fluorophores were rationally designed through tailoring the hydrophobicity with the aim to enhance the binding affinity for Aβ1-42 fibrils —while concurrently preventing poor aqueous solubility—via biannulate donor motifs in D-π-A dyes. An unprecedented sub-nanomolar affinity was found (Kd = 0.62 ± 0.33 nM) and applied to super-sensitive and red-emissive fluorescent staining of amyloid plaques in cortical brain tissue ex vivo. These fluorophores expand the dioxaborine-curcumin-based family of Aβ-sensitive fluorophores with a promising new imaging agent.

Abstract Vernalization, an acceleration of flowering after long-term winter cold, is an intensively studied flowering mechanism in winter annual plants. In Arabidopsis, Polycomb Repressive Complex 2 (PRC2)-mediated suppression of the strong floral repressor, FLOWERING LOCUS C (FLC), is critical for vernalization and a PHD finger domain protein, VERNALIZATION INSENSITIVE 3 (VIN3), recruits PRC2 on FLC chromatin. The level of VIN3 was found to gradually increase in proportion to the length of cold period during vernalization. However, how plants finely regulate VIN3 expression according to the cold environment has not been completely elucidated. As a result, we performed EMS mutagenesis using a transgenic line with a minimal promoter of VIN3 fused to the GUS reporter gene, and isolated a mutant, hyperactivation of VIN3 1 (hov1), which showed increased GUS signal and endogenous VIN3 transcript levels. Using positional cloning combined with whole-genome resequencing, we found that hov1 carries a nonsense mutation, leading to a premature stop codon on the HEAT SHOCK TRANSCRIPTION FACTOR B2b (HsfB2b), which encodes a repressive heat shock transcription factor. HsfB2b directly binds to the VIN3 promoter, and HsfB2b overexpression leads to reduced acceleration of flowering after vernalization. Collectively, our findings reveal a novel fine-tuning mechanism to regulate VIN3 for proper vernalization response.

A photonic radar has recently received considerable interest as a next-generation radar due to its capability to generate wideband signals beyond the technical limitations of the conventional radar. In this paper, we design and implement an ${X}$ -band photonic radar for a low radar cross-section (RCS) target detection and high-resolution image acquisition in real-time. The implemented photonic radar utilizes the photonic frequency quadrupling for the transmitter and detects the dechirped signal by using a delay interferometer and a balanced photo-detector to improve the signal-to-noise ratio. The performance of the photonic radar is verified using a commercial hexacopter having a diagonal wheelbase of 1133 mm as a low-RCS target in the field experiments. We show that the implemented photonic radar can successfully detect the drone on the move even though it is 2.7 km away from the radar. In addition, a high-resolution image of the drone, which is far away 1.1 km from the radar, can be obtained in real-time.

Hydrogen fuel cell electric vehicles are emerging as a means of transportation using renewable and carbon-free energy due to global warming and air pollution. Hydrogen fuel cell electric vehicles are typically refueled at a wide range of temperatures (−40 °C to 85 °C) in hydrogen refueling stations in accordance with globally accepted standards. Currently, there is no traceable method by which to verify and calibrate the Coriolis mass flowmeters used at hydrogen refueling stations, except for a water calibration process as a conventional method for mass flowrate calibration. To verify the hydrogen flow metering to a suitable level of accuracy under the challenging condition of high pressures and a wide range of temperatures, necessary methodologies and calibration facilities are developed in the present study. A flow measurement characteristic test of the hydrogen mass flowmeter under identical density conditions of the refueled hydrogen was conducted using the high-pressure gas flow standard system of the Korea Research Institute of Standards and Science to assess the effects on the medium and pressure of the mass flowmeter in a density-matching approach. To investigate the pressure dependence of the mass flowmeter at a hydrogen refueling station, a high-pressure water flow test was conducted in the pressure range of 2 bar to 700 bar, which is a pressure-matching approach. Finally, the KRISS Hydrogen Field Test Standard based on the gravimetric principle was developed to verify the measurement accuracy of the mass flowmeter to be used at hydrogen refueling stations for the first time in Korea.

The radio frequency (RF) signal generation method using an external modulator is widely used in microwave photonics applications because it has the advantage of being able to generate coherent and stable RF signals with a higher resolution performance compared to the conventional method. A Mach–Zehnder modulator is widely used as an external modulator due to its high electro-optic coefficients and low attenuation characteristics but has a critical problem in that its electrical characteristics are changed by external environments such as temperature. In this paper, we considered the stabilization configuration to overcome this problem and propose an automatic bias control technique based on the simulated annealing algorithm of a dual-parallel Mach–Zehnder modulator (DPMZM) for quadruple signal generation. The proposed technique searches for the bias voltages of the modulator in real-time through the temperature test. In addition, the output of the quadrupled signal of the DPMZM is constantly controlled throughout the temperature range. Finally, it is confirmed that signals of a 10 GHz and 22 GHz frequency are generated using the intermediate frequency signals of a 2.5 GHz and 5.5 GHz frequency with the proposed automatic bias control technique, respectively.

In this paper, we analyze the radar cross section (RCS) of a battleship equipped with an integrated mast module (IMM). The RCS of a battleship equipped with an IMM is calculated based on physical optics (PO) and the physical theory of diffraction (PTD), and is analyzed in terms of the mast shape, incident angles, and polarization.

In this paper, we propose an X-band photonic-based pulsed radar architecture with a high range resolution. The proposed architecture is operated as a pulsed radar by adding a Mach-Zehnder modulator (MZM) operating as an optical switch to a transmitter of a conventional photonic-based frequency-modulated continuous wave (FMCW) radar. In addition, a balanced photodetector (BPD) is employed to enhance the amplitude of the received signal and remove common-mode noise. A proposed photonic-based pulsed radar prototype is implemented to operate at a center frequency of 10 GHz, a bandwidth of 640 MHz, and a pulse repetition frequency (PRF) of 1 kHz considering the performances of an arbitrary waveform generator (AWG). The implemented prototype is verified through an indoor experiment. As a result, the positions of targets are detected in real-time with 1.6% error rates of a range accuracy and obtained the range resolution of 0.26 m.