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Abstract This study compared the safety of general anesthesia (GA) and intravenous sedation (IVS) in patients who underwent extraction of one or more third molars. Data from 1260 patients (GA group, n = 1043; IVS group, n = 217) were retrospectively analyzed, including demographics, preoperative data, intraoperative hemodynamic parameters (blood pressure, heart rate, and oxygen saturation level), and medications administered intraoperatively and postoperatively. The incidence of intraoperative circulatory variations, surgery and anesthesia durations, postoperative complications, and medication use were assessed and compared. The GA group had longer anesthesia and surgery durations, a higher incidence of hypotension, and a higher frequency of postoperative analgesic use than the IVS group. Dexmedetomidine was the most frequently used sedative agent. The IVS group had a lower incidence of intraoperative hypotension but they had a higher need for vasopressors in the recovery room. Both anesthesia methods maintained satisfactory oxygen saturation levels and sufficient anesthesia throughout the procedure, but they showed different characteristics regarding the duration of surgery and anesthesia duration, hemodynamic stability, and postoperative analgesic needs. IVS may be preferable for patients at risk of cardiovascular complications such as hypotension or tachycardia during surgery.

Abstract Tuning the properties of a pair of entangled electron and hole in a light-induced exciton is a fundamentally intriguing inquiry for quantum science. Here, using semiconducting hybrid perovskite as an exploratory platform, we discover that Nd2+-doped CH3NH3PbI3 (MAPbI3) perovskite exhibits a Kondo-like exciton-spin interaction under cryogenic and photoexcitation conditions. The feedback to such interaction between excitons in perovskite and the localized spins in Nd2+ is observed as notably prolonged carrier lifetimes measured by time-resolved photoluminescence, ~10 times to that of pristine MAPbI3 without Nd2+ dopant. From a mechanistic standpoint, such extended charge separation states are the consequence of the trap state enabled by the antiferromagnetic exchange interaction between the light-induced exciton and the localized 4 f spins of the Nd2+ in the proximity. Importantly, this Kondo-like exciton-spin interaction can be modulated by either increasing Nd2+ doping concentration that enhances the coupling between the exciton and Nd2+ 4 f spins as evidenced by elongated carrier lifetime, or by using an external magnetic field that can nullify the spin-dependent exchange interaction therein due to the unified orientations of Nd2+ spin angular momentum, thereby leading to exciton recombination at the dynamics comparable to pristine MAPbI3.

Summary: While most dizygotic twins have a dichorionic placenta, rare cases of dizygotic twins with a monochorionic placenta have been reported. The monochorionic placenta in dizygotic twins allows in utero exchange of embryonic cells, resulting in chimerism in the twins. In practice, this chimerism is incidentally identified in mixed ABO blood types or in the presence of cells with a discordant sex chromosome. Here, we applied whole-genome sequencing to one triplet and one twin family to precisely understand their zygotic compositions, using millions of genomic variants as barcodes of zygotic origins. Peripheral blood showed asymmetrical contributions from two sister zygotes, where one of the zygotes was the major clone in both twins. Single-cell RNA sequencing of peripheral blood tissues further showed differential contributions from the two sister zygotes across blood cell types. In contrast, buccal tissues were pure in genetic composition, suggesting that in utero cellular exchanges were confined to the blood tissues. Our study illustrates the cellular history of twinning during human development, which is critical for managing the health of chimeric individuals in the era of genomic medicine.

Recent advances in neural text-to-speech (TTS) systems have achieved high-quality speech synthesis, but maintaining naturalness while controlling utterance duration remains a challenging task. Existing approaches for controlling utterance duration rely on post-processing techniques compromising naturalness. These techniques are not effective in all scenarios, particularly when addressing variable utterance durations. This study presents a novel masked duration model that enables controllable utterance duration in TTS synthesis. This approach utilizes audio prompts, text prompts, and masks to predict phone durations within the masked span, which corresponds to the utterance duration. This enables precise control of the utterance duration by determining the target duration initially and predicting the phone durations. The model allows for fine-grained control over utterance duration, enabling more nuanced and realistic speech outputs. Additionally, an adversarial training strategy is employed to enhance the robustness of the alignment between audio and text prompts. The experimental results demonstrate that the proposed model outperformed the baseline model regarding utterance duration control. Ablation studies validate the effectiveness of adversarial training in enhancing model performance. This technology is suitable for applications requiring precise control over utterance duration, such as automatic voice dubbing.

Transcutaneous auricular vagus nerve stimulation (taVNS) could be a promising treatment for epilepsy, a neurological disorder primarily characterized by seizures. One of the primary causes of premature mortality in patients with epilepsy is sudden unexpected death in epilepsy (SUDEP). Considering that reduced heart rate variability (HRV) is strongly associated with SUDEP, whether taVNS can modify the autonomic nervous system while simultaneously suppressing seizures in a rat model of epilepsy should be investigated. In this study, epileptic seizures were induced in anesthetized rats by administering pentylenetetrazol (PTZ) and performing taVNS twice. After completing the experiments, changes in HRV measurements were analyzed to investigate the function of the autonomic nervous system. From a histological perspective, the Iba-1, c-Fos, and GAD65 expression levels were examined to evaluate the antiepileptic effects of taVNS. Our study results revealed that taVNS significantly improved the HRV, including root mean square of differences between N–N intervals, standard deviation of all N–N intervals, high-frequency power, and total power. However, no significant difference was observed in the low-frequency power. Histological analysis revealed a significant reduction in Iba-1 and c-Fos expressions following taVNS, with no statistically significant difference observed in GAD65 expression. This study suggests that (1) taVNS could enhance the parasympathetic activity by improving the HRV and (2) potentially exhibit antiepileptic effects by protecting cells from damage caused by epileptic seizures.

Objective: EuCorVac-19 (ECV-19), an adjuvanted liposome-displayed receptor binding domain (RBD) COVID-19 vaccine, previously reported interim Phase 2 trial results showing induction of neutralizing antibodies 3 weeks after prime-boost immunization. The objective of this study was to determine the longer-term antibody response of the vaccine. Methods: To assess immunogenicity 6 and 12 months after vaccination, participants in the Phase 2 trial (NCT04783311) were excluded if they: 1) withdrew, 2) reported COVID-19 infection or additional vaccination, or 3) exhibited increasing Spike (S) antibodies (representing possible non-reported infection). Following exclusions, of the 197 initial subjects, anti-S IgG antibodies and neutralizing antibodies were further assessed in 124 subjects at the 6-month timepoint, and 36 subjects at the 12-month timepoint. Results: Median anti-S antibody half-life was 52 days (interquartile range [IQR]:42-70), in the “early” period from 3 weeks to 6 months, and 130 days (IQR:97-169) in the “late” period from 6 to 12 months. There was a negative correlation between initial antibody titer and half-life. Anti-S and neutralizing antibody responses were correlated. Neutralizing antibody responses showed longer half-lives; the early period had a median half-life of 120 days (IQR:81-207), and the late period had a median half-life of 214 days (IQR:140-550). Conclusion: These data establish antibody durability of ECV-19, using a framework to analyze COVID-19 vaccine-induced antibodies during periods of high infection.

This paper analyzes the motivations of the British biochemist Joseph Needham for participating in ‘the International Scientific Commission for the Investigation of the Facts Concerning Bacterial Warfare in Korea and China (ISC)’ and his major roles within it during the Korean War. Needham stayed in China for four years starting in 1942 as a scientific counselor and director of the British Scientific Mission in China, which enabled him to interact with many Chinese scientists and politicians. Surprisingly, during this period (1944), Needham conducted an investigation into the Japanese military’s use of bacterial warfare. Through his personal records, Needham repeatedly stated that his experience with bacterial warfare research in 1944 was one of the most important reasons for his participation in ISC activities. In addition, Needham secretly but very actively sought to recruit other investigators within Britain. Needham repeatedly tried to persuade fellow professors at Cambridge University, William Thorpe and Vincent Wigglesworth, to be included in the investigation team. Although Needham had doubts about his own expertise in investigative activities, he actively expressed his desire to become a member of the investigative team through various channels. Primary documents show that he actively and voluntarily led the investigation activities after joining the team in professional discussions, document analysis, and witness interrogations. Needham’s passion and sincerity demonstrated in internal meeting minutes dispel some misunderstandings that the investigation team’s activities were limited to passively approving Chinese data.

Speaker recognition is a technology that identifies the speaker in an input utterance by extracting speaker-distinguishable features from the speech signal. Speaker recognition is used for system security and authentication; therefore, it is crucial to extract unique features of the speaker to achieve high recognition rates. Representative methods for extracting these features include a classification approach, or utilizing contrastive learning to learn the speaker relationship between representations and then using embeddings extracted from a specific layer of the model. This paper introduces a framework for developing robust speaker recognition models through contrastive learning. This approach aims to minimize the similarity to hard negative samples—those that are genuine negatives, but have extremely similar features to the positives, leading to potential mistaken. Specifically, our proposed method trains the model by estimating hard negative samples within a mini-batch during contrastive learning, and then utilizes a cross-attention mechanism to determine speaker agreement for pairs of utterances. To demonstrate the effectiveness of our proposed method, we compared the performance of a deep learning model trained with a conventional loss function utilized in speaker recognition with that of a deep learning model trained using our proposed method, as measured by the equal error rate (EER), an objective performance metric. Our results indicate that when trained with the voxceleb2 dataset, the proposed method achieved an EER of 0.98% on the voxceleb1-E dataset and 1.84% on the voxceleb1-H dataset.

Graphitic carbon plays a pivotal role in numerous technological applications, including energy storage, energy conversion, and different fields of material science. The transformation of amorphous carbon into graphitic carbon, a process known as graphitization, is important for optimizing the properties of carbon materials. In this study, we explore the catalytic graphitization of polyacrylonitrile (PANs) using various metal salts (LiNO3, Ca(NO3)2·4H2O, and Ni(NO3)2·6H2O). We prepared dimethyl sulfoxide (DMSO) solutions of PAN with different salt concentrations of 5, 10, and 15 wt.%. The different prepared metal salt-mixed PAN/DMSO solutions were dried at 45 °C and this was followed by carbonization processes at 950 °C, with a heating rate of 1 °C min−1 for 1 h under an N2 atmosphere. The resulting graphitic carbon was characterized to determine the influence of salt type and concentration on the degree of graphitization. Our findings provide valuable insights into PAN-derived graphitic carbon’s structural and compositional properties. This work underscores the influence of salt concentration in optimizing the graphitization process, offering a pathway to design facile and cost-effective graphitic carbon materials.

Abstract Photonic synaptic transistors are being investigated for their potential applications in neuromorphic computing and artificial vision systems. Recently, a method for establishing a synaptic effect by preventing the recombination of electron–hole pairs by forming an energy barrier with a double-layer consisting of a channel and a light absorption layer has shown effective results. We report a triple-layer device created by coating a novel electron-trapping layer between the light-absorption layer and the gate-insulating layer. Compared to the conventional double-layer photonic synaptic structure, our triple-layer device significantly reduces the recombination rate, resulting in improved performance in terms of the output photocurrent and memory characteristics. Furthermore, our photonic synaptic transistor possesses excellent synaptic properties, such as paired-pulse facilitation (PPF), short-term potentiation (STP), and long-term potentiation (LTP), and demonstrates a good response to a low operating voltage of − 0.1 mV. The low power consumption experiment shows a very low energy consumption of 0.01375 fJ per spike. These findings suggest a way to improve the performance of future neuromorphic devices and artificial vision systems.

Natural purification of pollutants is highly recognized as regulating ecosystem services; however, the purification capacity of tidal flats remains largely unknown and/or unquantified. A 60-day mesocosm transplant experiment was conducted in situ to assess the purification capacity of natural tidal flats. We adopted the advanced sediment quality triad approach, monitoring 10 endpoints, including chemical reduction, toxicity changes, and community recoveries. The results indicated that contaminated sediments rapidly recovered over time, particularly > 50% within a day, then slowly recovered up to ∼ 70% in a given period (60 days). A significant early reduction of parent pollutants was evidenced across all treatments, primarily due to active bacterial decomposition. Notably, the presence of benthic fauna and vegetated halophytes in the treatments significantly enhanced the purification of pollutants in both efficacy and efficiency. A forecast linear modeling further suggested additive effects of biota on the natural purification of tidal flats, reducing a full recovery time from 500 to 300 days. Overall, the triad approach with machine learning practices successfully demonstrated quantitative insight into the integrated assessment of natural purification.

In the constrained computing environments such as mobile device or satellite on-board system, various computational factors of hardware resource can restrict the processing of deep learning (DL) services. Recent DL models such as satellite image analysis mainly require larger resource memory occupation for intermediate feature map footprint than the given memory specification of hardware resource and larger computational overhead (in FLOP) to meet service-level objective in the sense of hardware accelerator. As one of the solutions, we propose a new method of controlling the layer-wise channel pruning in a single-shot manner that can decide how much channels to prune in each layer by observing dataset once without full pretraining. To improve the robustness of the performance degradation, we also propose a layer-wise sensitivity and formulate the optimization problems for deciding layer-wise pruning ratio under target computational constraints. In the paper, the optimal conditions are theoretically derived, and the practical optimum searching schemes are proposed using the optimal conditions. On the empirical evaluation, the proposed methods show robustness on performance degradation, and present feasibility on DL serving under constrained computing environments by reducing memory occupation, providing acceleration effect and throughput improvement while keeping the accuracy performance.

In some DL applications such as remote sensing, it is hard to obtain the high task performance (e.g. accuracy) using the DL model on image analysis due to the low resolution characteristics of the imagery. Accordingly, several studies attempted to provide visual explanations or apply the attention mechanism to enhance the reliability on the image analysis. However, there still remains structural complexity on obtaining a sophisticated visual explanation with such existing methods: 1) which layer will the visual explanation be extracted from, and 2) which layers the attention modules will be applied to. 3) Subsequently, in order to observe the aspects of visual explanations on such diverse episodes of applying attention modules individually, training cost inefficiency inevitably arises as it requires training the multiple models one by one in the conventional methods. In order to solve the problems, we propose a new scheme of mediating the visual explanations in a pixel-level recursively. Specifically, we propose DropAtt that generates multiple episodes pool by training only a single network once as an amortized model, which also shows stability on task performance regardless of layer-wise attention policy. From the multiple episodes pool generated by DropAtt, by quantitatively evaluating the explainability of each visual explanation and expanding the parts of explanations with high explainability recursively, our visual explanations mediation scheme attempts to adjust how much to reflect each episodic layer-wise explanation for enforcing a dominant explainability of each candidate. On the empirical evaluation, our methods show their feasibility on enhancing the visual explainability by reducing average drop about 17% and enhancing the rate of increase in confidence 3%.

This study conducted laboratory tests and field surveys to understand the plasticizer contamination characteristics on the surface of PVC flooring materials used indoors, and discussed the risk of exposure of plasticizers to infants indoors. A lab experiment was conducted to measure the bleed-out of DEHP on PVC sheet surfaces. As a result of the bleed-out, the amount of DEHP on the specimen surfaces was 432 to 880 [ug/m2]. The present study showed that plasticizers such as DEHP contained in the PVC sheet accumulate a significant amount of DEHP on the surface of the PVC sheet even if a material such as house dust is not present on the surface of the PVC sheet. In addition, this study found that even if the dust accumulated on the PVC floor surface was vacuumed, it was difficult to completely remove the DEHP accumulated on the floor surface. The field surveys showed that the average concentration of DEHP on the floor surface in Korean and Japanese house were 356 and 608 ug/m2 respectively. Since infants have behavioral characteristics of crawling, sitting, and lying on the floor, they have more opportunities to directly contact the floor than adults.

In 1946, the U.S. Army established the 406th Medical General Laboratory as the central medical research institute for their new Asia-Pacific-occupied area. The primary mission of the 406th medical laboratory was to supplement the epidemiologic, sanitary, and diagnostic services available in other medical facilities and hospitals, and to investigate outbreaks of disease and conditions which affect or may affect the health of the people in the occupied area. At the time of its establishment, the 406th laboratory had considerable difficulties securing researchers, but it solved the related problems by actively cooperating with Japanese medical researchers and research institutes. According to the statistics in 1947, the 406th laboratory consisted of 46% of its total research personnel, Japanese researchers. The 406th medical laboratory’s professional research departments included the department of Pathology, Serology, Bacteriology, Medical Zoology, Chemistry, Virus and Ricketts, Entomology (established in 1949), and Epidemiology (established in 1951). All research departments played a central role in the Asia-Pacific region in their professional fields. For example, the department of Pathology functioned as the “histopathology center of all hospitals in Japan, Korea, and the Mariana-Bonin Command” under the provision of “Army Regulation 40-410,” and the department of Chemistry was called an “analytical chemistry laboratory for the Far East Command” because it performed various chemical experiments for many medical facilities in the area with insufficient research facilities.

The quest to find extraterrestrial life is a critical scientific endeavor with civilization-level implications. Icy moons in our solar system are promising targets for exploration because their liquid oceans make them potential habitats for microscopic life. However, the lack of a precise definition of life poses a fundamental challenge to formulating detection strategies. To increase the chances of unambiguous detection, a suite of complementary instruments must sample multiple independent biosignatures (e.g., composition, motility/behavior, and visible structure). Such an instrument suite could generate 10,000× more raw data than is possible to transmit from distant ocean worlds like Enceladus or Europa. To address this bandwidth limitation, Onboard Science Instrument Autonomy (OSIA) is an emerging discipline of flight systems capable of evaluating, summarizing, and prioritizing observational instrument data to maximize science return. We describe two OSIA implementations developed as part of the Ocean World Life Surveyor (OWLS) prototype instrument suite at the Jet Propulsion Laboratory. The first identifies life-like motion in digital holographic microscopy videos, and the second identifies cellular structure and composition via innate and dye-induced fluorescence. Flight-like requirements and computational constraints were used to lower barriers to infusion, similar to those available on the Mars helicopter, “Ingenuity.” We evaluated the OSIA's performance using simulated and laboratory data and conducted a live field test at the hypersaline Mono Lake planetary analog site. Our study demonstrates the potential of OSIA for enabling biosignature detection and provides insights and lessons learned for future mission concepts aimed at exploring the outer solar system.

We doped carbon into a TiZrN coating to reduce hydrogen permeability, and investigated the phase formation, bonding state, microstructure, and surface roughness of the carbon-doped TiZrN. The laser output for laser carburization was limited to a range of 20–50%. The grain size of the TiZrN coatings decreased from 26.49 nm before carburization to 18.31 nm after carburization. For XPS analysis, the sp2/sp3 ratio was 1.23 at 20% laser output, but it showed 2.64 at 40% laser output, which means that amorphous carbon was formed. As the grain size decreased with the formation of amorphous carbon, the surface microstructure of the carbon-doped TiZrN coatings transitioned to an intergranular structure, indicating the creation of amorphous carbon-embedded (Ti, Zr)(C, N) in the coating. The surface roughness (Ra) of the carbon-doped TiZrN coating was decreased to a maximum of 7.12 nm, and the hydrogen permeability correspondingly decreased by 78% at 573 K.

The Chinese burrowing-cricket Velarifictorus beybienkoi is newly found in Korea. Previously, it was only known on the east coast of China but is now confirmed on the midwest of Korea. Compared with other Velarifictorus species in Korea, V. beybienkoi can be distinguished by shortest tegmina of both sexes and male genitalia. Redescription, figures of the species are provided to aid in identification, and the male calling songs are analyzed for the first time.

Deep brain stimulation (DBS) therapies have shown clinical success in the treatment of a number of neurological illnesses, including obsessive-compulsive disorder, epilepsy, and Parkinson’s disease. An emerging strategy for increasing the efficacy of DBS therapies is to develop closed-loop, adaptive DBS systems that can sense biomarkers associated with particular symptoms and in response, adjust DBS parameters in real-time. The development of such systems requires extensive analysis of the underlying neural signals while DBS is on, so that candidate biomarkers can be identified and the effects of varying the DBS parameters can be better understood. However, DBS creates high amplitude, high frequency stimulation artifacts that prevent the underlying neural signals and thus the biological mechanisms underlying DBS from being analyzed. Additionally, DBS devices often require low sampling rates, which alias the artifact frequency, and rely on wireless data transmission methods that can create signal recordings with missing data of unknown length. Thus, traditional artifact removal methods cannot be applied to this setting. We present a novel periodic artifact removal algorithm for DBS applications that can accurately remove stimulation artifacts in the presence of missing data and in some cases where the stimulation frequency exceeds the Nyquist frequency. The numerical examples suggest that, if implemented on dedicated hardware, this algorithm has the potential to be used in embedded closed-loop DBS therapies to remove DBS stimulation artifacts and hence, to aid in the discovery of candidate biomarkers in real-time. Code for our proposed algorithm is publicly available on Github.

With advances in NanoSat (CubeSat) and high-resolution sensors, the amount of raw data to be analyzed by human supervisors has been explosively increasing for satellite image analysis. To reduce the raw data, the satellite onboard AI processing with low-power COTS (Commercial, Off-The-Shelf) HW has emerged from a real satellite mission. It filters the useless data (e.g. cloudy images) that is worthless to supervisors, achieving efficient satellite-ground station communication. In the application for complex object recognition, however, additional explanation is required for the reliability of the AI prediction due to its low performance. Although various explainable AI (XAI) methods for providing human-interpretable explanation have been studied, the pyramid architecture in a deep network leads to the background bias problem which visual explanation only focuses on the background context around the object. Missing the small objects in a tiny region leads to poor explainability although the AI model corrects the object class. To resolve the problems, we propose a novel federated onboard-ground station (FOGS) computing with Cascading Pyramid Attention Network (CPANet) for reliable onboard XAI in object recognition. We present an XAI architecture with a cascading attention mechanism for mitigating the background bias for the onboard processing. By exploiting the localization ability in pyramid feature blocks, we can extract high-quality visual explanation covering the both semantic and small contexts of an object. For enhancing visual explainability of complex satellite images, we also describe a novel computing federation with the ground station and supervisors. In the ground station, active learning-based sample selection and attention refinement scheme with a simple feedback method are conducted to achieve the robustness of explanation and efficient supervisor’s annotation cost, simultaneously. Experiments on various datasets show that the proposed system improves task accuracy in object recognition and accurate visual explanation detecting small contexts of objects even in a peripheral region. Then, our attention refinement mechanism demonstrates that the inconsistent explanation can be efficiently resolved only with very simple selection-based feedback.

We propose a new low-diameter interconnection network called FleX, which offers high flexibility when installing interconnections in a HPC system. FleX consists of multiple layers with only connections between neighboring layers and not within each layer. These structural properties make it easy to achieve a low diameter with regardless of the scale. The cross-like connections between the adjacent layers in FleX impart various alternative minimal paths, allowing FleX to have high resiliency and a wide bisection width. We also discuss the minimal routing scheme and a stochastic load balancing scheme (LBR) for the proposed interconnection network. Through cycle-based simulations, the performance of FleX is evaluated, and the cost and power consumption analyses in comparison with other interconnection networks are also conducted. We verify that FleX has high configuration flexibility with regard to cost and performance, and also provides low latency and high saturation throughput with the same cost over the legacy interconnection networks for the HPC system. Moreover, being synergied with the proposing LBR, we also verify that FleX can expand its saturation throughput further while only sacrificing the latency slightly.

Thermal effects on fatigue life were investigated by analyzing the thermomechanical behavior of double-row tapered roller bearings (DTRBs) and a fatigue life prediction model was developed. A bearing’s mechanical behavior was analyzed using a quasi-static model and its thermal behavior was analyzed using a thermal network method. Viscous drag and sliding friction at the contact area were considered as heat generation factors for DTRBs. The bearing lubrication characteristics and shape dimensions interacted with the temperature and the analysis was repeated until the entire DTRB system’s temperature converged. DTRB fatigue life was estimated using a fatigue life formula based on Gupta and Zaretsky’s statistical model. Results confirmed that the fatigue life decreased rapidly because of an interference fit that occurred at very high rotation speeds or at very low supply oil flow rates. This interference fit phenomenon is caused by thermal expansion of the bearing element. The interference fit can be prevented by designing with a large initial clearance value, but an initial clearance that is too large affects fatigue life negatively because of load distribution imbalance. Optimal design of the roller end sphere radius to minimize sliding friction for the flange part can provide additional help in preventing interference fit.

The improved mechanical properties of carbon-doped TiZrN coatings were investigated in terms of the microstructure and bonding state. The carbon incorporation and structural change were confirmed as a shift to lower degree of the diffraction pattern and the decreased grain size from 24.64 to 22.19 nm. The clear grain boundaries (GBs) were observed in the carbon-doped coating, and its fast Fourier transform (FFT) exhibited a diffused ring pattern. Edge dislocations were also observed in the inverse FFT image, indicating the formation of an amorphous phase due to laser carburization. From the X-ray photoelectron spectroscopy depth profile analysis, the carbon concentration decreased to 37.26 at.% after carburization, which is non-stoichiometric behavior that suggests the formation of the amorphous carbon (a-C) rather than carbides. Both sp2- and sp3-hybridized bonds were detected in the C 1s spectrum of the carbon-doped coating, indicating that the diffused carbon atoms were trapped in the GBs as a-C. The change in the GB structure increased the compressive residual stress from 3.97 to 4.63 GPa. In addition, the hardness, elastic strain to failure (H/E), and plastic deformation resistance (H3/E2) of the carbon-doped TiZrN increased by 19.22%, 12.64%, and 49.59%, respectively, demonstrating the effect of GB strengthening.

Summary: With the continuous emergence of highly transmissible SARS-CoV-2 variants, the comparison of their infectivity has become a critical issue for public health. However, a direct assessment of the viral characteristic has been challenging because of the lack of appropriate experimental models and efficient methods. Here, we integrated human alveolar organoids and single-cell transcriptome sequencing to facilitate the evaluation. In a proof-of-concept study with four highly transmissible SARS-CoV-2 variants, including GR (B.1.1.119), Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (BA.1), a rapid evaluation of the relative infectivity was possible. Our system demonstrates that the Omicron variant is 5- to 7-fold more infectious to human alveolar cells than the other SARS-CoV-2 variants at the initial stage of infection. To our knowledge, for the first time, this study measures the relative infectivity of the Omicron variant under multiple virus co-infection and provides new experimental procedures that can be applied to monitor emerging viral variants.

[This corrects the article DOI: 10.1371/journal.ppat.1010092.].

Abstract Understanding the precise molecular arrangement of chiral supramolecular polymers is essential not only to comprehend complex superstructures like proteins and DNA but also for the development of next‐generation optoelectronic materials, including materials displaying high‐performance circularly polarized luminescence (CPL). Herein, we report the first chiral supramolecular polymer systems based on hydrazone–pyridinium conjugates comprising alkyl chains of different lengths, which afforded control of the apparent supramolecular chirality. Although supramolecular chirality is governed basically by the remote chiral centers of alkyl chains, helicity inversion was achieved by controlling the conditions under which the hydrazone building blocks underwent aggregation (i.e., solvent compositions or temperature). More importantly, the addition of water to the system led to aggregation‐induced hydrazone deprotonation, which resulted in a completely different self‐assembly behavior. Structural water molecules played an essential role, forming the assembly's channel‐like backbone, around which hydrazone molecules gathered as a result of hydrogen bonding interactions. Further co‐assembly of an achiral hydrazone luminophore with the given supramolecular polymer system allowed the fabrication of a novel CPL‐active hydrazone‐based material exhibiting a high maximum value for the photoluminescence dissymmetry factor of −2.6 × 10−2.

Regular physical activity and balanced nutrition are important in maintaining a healthy weight. Nonetheless, minority populations, like Hispanics, face challenges (e.g., language barriers and transportation unavailability) that limit their participation in intervention programs to receive benefits. Furthermore, dog companionship has been shown to relate to adolescents' behavioral and socio-emotional development positively, and it has been shown to have the potential to increase physical activity in adolescence. Therefore, this study aimed to examine the feasibility, i.e., program adaptation, limited efficacy, and acceptability, of the two exercise and nutrition education interventions to improve body composition, motivation, and well-being in overweight and obese Hispanic adolescents. This pilot study was a quasi-experimental trial with eight pediatrician-referred participants (M[subscript age] =11.75±1.48) assigned to two parallel arms: (1) BRAVO! and (2) BRAVO!+. Both share identical exercise (24 hours) and nutrition (12 hours) programs centered on the self-determination theory for 12 weeks. The results suggested, first, acceptable attendance (BRAVO! = 56.25%; BRAVO!+ = 64.58%) but poor retention (BRAVO! = 33.33%; BRAVO!+ = 63.63%). Second, the findings suggested promising limited efficacy in BRAVO!+ group, with small but statistically non-significant reductions in participants' BMI (M[subscript baseline] = 33.08±6.13; M[subscript post] = 32.23±6.88; t[3] = 1.633, p = 0.201) and weight (M[subscript baseline] = 78.13±16.22; M[subscript post] = 77.62±17.64; t[3] = 0.485, p = 0.661). In addition, the results suggested high satisfaction and acceptable suitability for both programs and providing important suggestions for the future. In conclusion, our pilot study findings only partially supported the feasibility of the pet-dog-enhanced lifestyle intervention. Although this study found evidence that pet-dog companionship can improve program satisfaction and acceptability of pediatric lifestyle interventions, including a pet-dog in the intervention may contribute to high dropout evidenced in this study.

In the study of microbial life, microscopy plays a unique role due to its ability to detect ordered structure, motility, and fluorescence signals. As such it has also recently gained attention in the context of searching for extant life on distant Solar System bodies bearing liquid water. In this paper we introduce a multi-modal volumetric microscopy system for potential future spaceflight missions that combines digital holographic microscopy (DHM) and volume fluorescence imager (VFI), which are volumetric imaging methods that provide high-resolution, high-throughput examination of liquid samples. DHM provides information on the absorption, morphology, and motility of imaged objects without requiring the use of contrast agents. On the other hand, VFI based on light field microscopy focuses on the fluorescence signals from the sample to observe specific structures dyed with targeted contrast agents or providing unique autofluorescence signals. We also present an autonomous sample handling and data acquisition system to allow for an autonomous mission to distant planets or moons, or for autonomous use in bodies of water on Earth. The full system, named ELVIS, or Extant Life Volumetric Imaging System, is capable of autonomously surveying a liquid sample to extract morphology, motility, and fluorescence signals of extant microbial life.

Abstract The hurdle of fabricating asymmetric supercapacitor (ASC) devices using a faradic cathode and a double layer anode is challenging due to the required large amount of active mass of anodic material compared to that of the cathodic material during mass balancing due to the large difference in capacitance values of the two electrodes. Here, the problem is addressed by engineering a negative electrode that furnishes an ultrahigh capacitance. An in situ developed metal–organic framework (MOF)‐based thermal treatment is adopted to grow highly porous N‐doped carbon nanotubes (CNTs) containing submerged Co nanoparticles over nano‐fibrillated electrospun hollow carbon nanofibers (HCNFs). The optimized CNT@HCNF‐1.5 furnishes an ultrahigh capacitance approaching 712 F g–1 with excellent rate capability. The capacitance reported from this work is the highest for any carbonaceous material reported to date. The CNT@HCNF‐1.5 is further used to fabricate symmetric supercapacitors (SSCs), as well as ASC devices. Remarkably, both the SSC and ASC devices furnish incredible performances in all aspects of SCs, such as a high energy density, long cycle life, and high rate capability, displaying decent practical applicability. The energy density of the SSC device reaches as high as 20.13 W h kg–1, whereas that of ASC approaches 87.5 W h kg–1.

A novel actuator disk model (ADM) coupled with lifting-line theory is proposed in this paper. Several virtual planform blades are placed on a disk plane with a constant azimuthal interval, and the lifting-line theory is applied to each blade to predict the effective angle of attack. The proposed model considers the local lift and drag forces acting on disk surface cells by interpolating the predicted effective angle of attack with various azimuth angles to the actuator disk plane; therefore, the proposed model considers individual blade tip vortices without tip loss functions. Experimental data for hover and forward flight rotors are used to validate the proposed model. For hovering flight, sectional thrust based on collective pitch angles predicted by the modified ADM was similar to that obtained in the experiments. For forward flight, the inflow above the rotor estimated by the proposed ADM was similar to that obtained in the experiments and by using other numerical methods. Thus, the developed ADM can be used for rotor performance analysis under the main flight conditions of V/STOL.

This study aimed to elucidate the structural congeners of natural izenamides A, B, and C (1–3) responsible for cathepsin D (CTSD) inhibition. Structurally modified izenamides were synthesized and biologically evaluated, and their biologically important core structures were identified. We confirmed that the natural statine (Sta) unit (3S,4S)-γ-amino-β-hydroxy acid is a requisite core structure of izenamides for inhibition of CTSD, which is closely related to the pathophysiological roles in numerous human diseases. Interestingly, the statine-incorporated izenamide C variant (7) and 18-epi-izenamide B variant (8) exhibited more potent CTSD-inhibitory activities than natural izenamides.

The ever-increasing energy demand and global warming caused by fossil fuels push for the exploration of sustainable and eco-friendly energy sources. Waste thermal energy has been considered as one of the promising candidates for sustainable power generation as it is abundantly available everywhere in our daily lives. Recently, thermo-electrochemical cells based on the temperature-dependent redox potential have been intensely studied for efficiently harnessing low-grade waste heat. Despite considerable progress in improving thermocell performance, no attempt was made to develop electrode materials from renewable precursors. In this work, we report the synthesis of a porous carbon electrode from mandarin peel waste through carbonization and activation processes. The influence of carbonization temperature and activating agent/carbon precursor ratio on the performance of thermocell was studied to optimize the microstructure and elemental composition of electrode materials. Due to its well-developed pore structure and nitrogen doping, the mandarin peel-derived electrodes carbonized at 800 °C delivered the maximum power density. The areal power density (P) of 193.4 mW m−2 and P/(ΔT)2 of 0.236 mW m−2 K−2 were achieved at ΔT of 28.6 K. However, KOH-activated electrodes showed no performance enhancement regardless of activating agent/carbon precursor ratio. The electrode material developed here worked well under different temperature differences, proving its feasibility in harvesting electrical energy from various types of waste heat sources.

The purpose of this study was to evaluate disease patterns among military working dogs (MWDs) at the Armed Forces Medical Research Institute (AFMRI) to provide basic medical data on Korean MWDs. The medical records of procedures performed at AFMRI between November 2017 and March 2021 were reviewed. Physical examination, diagnostic imaging, and laboratory tests were performed according to the status of each dog. A total of 353 MWDs (215 males and 138 females; mean age, 6 ± 3 years) were analyzed in this study. Among Korean MWDs, gastrointestinal (GI) disorders are the most frequently diagnosed, followed by dental and musculoskeletal disorders. Foreign body (FB) ingestion had the highest prevalence of GI disorders, with the most common FB being a leather collar or leash. General and dental surgeries, including removal of gastric FB and tooth extraction, were routinely performed at the AFMRI. Preventative care focusing on dental disease and FB ingestion may be helpful for effective performance and good quality of life in MWDs, with the regular assessment and prevention of environmental factors that may contribute to behavioral problems such as FB ingestion, coprophagy, and anorexia.

Training an object instance detector where only a few training object images are available is a challenging task. One solution is a cut-and-paste method that generates a training dataset by cutting object areas out of training images and pasting them onto other background images. A detector trained on a dataset generated with a cut-and-paste method suffers from the conventional domain shift problem, which stems from a discrepancy between the source domain (generated training dataset) and the target domain (real test dataset). Though state-of-the-art domain adaptation methods are able to reduce this gap, it is limited because they do not consider the difference of domain gaps of foreground and background. In this study, we present that the conventional domain gap can be divided into two sub-domain gaps for foreground and background. Then, we show that the original cut-and-paste approach suffers from a new domain gap problem, an unbalanced domain gaps, because it has two separate source domains for foreground and background, unlike the conventional domain shift problem. Then, we introduce an advanced cut-and-paste method to balance the unbalanced domain gaps by diversifying the foreground with GAN (generative adversarial network)-generated seed images and simplifying the background using image processing techniques. Experimental results show that our method is effective for balancing domain gaps and improving the accuracy of object instance detection in a cluttered indoor environment using only a few seed images. Furthermore, we show that balancing domain gaps can improve the detection accuracy of state-of-the-art domain adaptation methods.

Treatments for epilepsy include pharmacotherapy or surgery. Recently, focused ultrasound stimulation has been investigated as a promising non-invasive neuromodulation tool for neurological disorders, including epilepsy. To investigate the neuronal dynamics in epilepsy, we acutely stimulated 29 Sprague–Dawley rats to low-intensity focused ultrasound stimulation (LIFUS) three times for 3 minutes. Pentylenetetrazol (PTZ) was injected into the abdominal cavity of the anesthetized rats to induce epilepsy. During the anesthesia, the electroencephalography (EEG) signal was measured and analyzed for 1 h in groups of animals untreated (sham) and treated with LIFUS. The EEG signal was quantitatively processed to show the different characteristics of the frequency change over time and of the band power between sham and treated groups. Histological analyses (Nissl, Iba1, c-Fos, and GAD65) measured the degree of staining of expression factors to confirm the effect of the stimulation on seizure suppression. These results suggest that repetitive LIFUS can effectively reduce epileptic seizure activity by attenuating theta and beta-band oscillation in a PTZ-induced rat model. LIFUS can potentially facilitate hippocampal and cortical cellular recovery by augmenting GABAergic inhibitory neurons via its anti-seizure effect.

Abstract Chronic obstructive pulmonary disease (COPD) is a respiratory disorder involving abnormalities of lung parenchymal morphology with different severities. COPD is assessed by pulmonary-function tests and computed tomography-based approaches. We introduce a new classification method for COPD grouping based on deep learning and a parametric-response mapping (PRM) method. We extracted parenchymal functional variables of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%) with an image registration technique, being provided as input parameters of 3D convolutional neural network (CNN). The integrated 3D-CNN and PRM (3D-cPRM) achieved a classification accuracy of 89.3% and a sensitivity of 88.3% in five-fold cross-validation. The prediction accuracy of the proposed 3D-cPRM exceeded those of the 2D model and traditional 3D CNNs with the same neural network, and was comparable to that of 2D pretrained PRM models. We then applied a gradient-weighted class activation mapping (Grad-CAM) that highlights the key features in the CNN learning process. Most of the class-discriminative regions appeared in the upper and middle lobes of the lung, consistent with the regions of elevated fSAD% and Emph% in COPD subjects. The 3D-cPRM successfully represented the parenchymal abnormalities in COPD and matched the CT-based diagnosis of COPD.

This study explores the history of research in Medical Anthropology by examining key concepts in the field with a focus on their relevance with findings from the field of History of Medicine. The concepts discussed in this paper are Medical Pluralism, Social Suffering, Biopolitics, and Care. Since concepts internalize the ethnographic gaze, what this paper aims is to trace the development of the gaze on a historical axis. Although concepts come from a specific historical period, they are by no means exclusive to it, as they are revisited again and again through various discourses. In other words, the insight that the previous meaning of a concept has grasped is instilled into the revisited concept. In this way, concepts engage in historical communication, create intersections with the interests of History of Medicine. By discussing these intersections with each concept, this paper suggests the complementary roles of the two fields and their approach to historical events and phenomena.

Abstract Background Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs. This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure. Methods To reduce confounding factors, subjects with normal spirometry without fibrosis, asthma and pneumonia histories were only selected, and a propensity score matching was applied to match age, sex, height, smoking status, and pack-years. Thus, from a larger data set (N = 609), only 41 cement dust-exposed subjects were compared with 164 non-cement dust-exposed subjects. QCT imaging metrics of airway hydraulic diameter (D h), wall thickness (WT), and bifurcation angle (θ) were extracted at total lung capacity (TLC) and functional residual capacity (FRC), along with their deformation ratios between TLC and FRC. Results In TLC scan, dust-exposed subjects showed a decrease of D h (airway narrowing) especially at lower-lobes (p

Recent advancements in robots and deep learning have led to active research in human-robot interaction. However, non-physical interaction using visual devices such as laser pointers has gained less attention than physical interaction using complex robots such as humanoids. Such vision-based interaction has high potential for use in recent human-robot collaboration environments such as assembly guidance, even with a minimum amount of configuration. In this paper, we introduce a simple robotic laser pointer device that follows an arbitrary planar path and is designed to be a visual instructional aid. We also propose an image-based automatic path generation method using reinforcement learning and a sequential pattern reduction technique. However, such vision-based human-robot interaction is generally performed in a dynamic environment, and it can frequently be necessary to calibrate the devices more than once. In this paper, we avoid the need for this re-calibration process through episodic randomization learning and improved learning efficiency. In particular, contrary to previous approaches, the agent controls the curriculum difficulty in a self-directed manner to determine the optimal curriculum. To our knowledge, this is the first study of curriculum learning that incorporates an explicit learning environment control signal initiated by the agent itself. Through quantitative and qualitative analyses, we show that the proposed self-directed curriculum learning method outperforms ordinary episodic randomization and curriculum learning. We hope that the proposed method can be extended to a general reinforcement learning framework.

Background: Asthma is a heterogeneous inflammatory airway disorder with various phenotypes. Quantitative computed tomography (QCT) methods can differentiate among lung diseases through accurate assessment of the location, extent, and severity of the disease. The purpose of this study was to identify asthma clusters using QCT metrics of airway and parenchymal structure, and to identify associations with visual analyses conducted by radiologists. Methods: This prospective study used input from QCT-based metrics including hydraulic diameter (Dh), luminal wall thickness (WT), functional small airway disease (fSAD), and emphysematous lung (Emph) to perform a cluster analysis and made comparisons with the visual grouping analysis conducted by radiologists based on site of airway involvement and remodeling evaluated. Results: A total of 61 asthmatics of varying severities were grouped into 4 clusters. From C1 to C4, more severe lung function deterioration, higher fixed obstruction rate, and more frequent asthma exacerbations were observed in the 5-year follow-up period. C1 presented non-severe asthma with increased WT, Dh of proximal airways, and fSAD. C2 was mixed with non-severe and severe asthmatics, and showed bronchodilator responses limited to the proximal airways. C3 and C4 included severe asthmatics that showed a reduced Dh of the proximal airway and diminished bronchodilator responses. While C3 was characterized by severe allergic asthma without fSAD, C4 included ex-smokers with high fSAD% and Emph%. These clusters correlated well with the grouping done by radiologists and clinical outcomes. Conclusions: Four QCT imaging-based clusters with distinct structural and functional changes in proximal and small airways can stratify heterogeneous asthmatics and can be a complementary tool to predict clinical outcomes.

Europa's subsurface ocean is postulated to contain appreciable amounts of Mg ^2+ and ${{\mathrm{SO}}_{4}}^{2-}$ ions, among other species. Recent laboratory experiments have shown that when solutions containing these species freeze to Europa-relevant temperatures, they can form vitreous MgSO _4 hydrate, which can remain stable at these temperatures. Since vitreous phases can protect cells from physical damage that can occur during crystallization, their presence on Europa could potentially preserve entrained microorganisms from the ocean below. However, to date, it remains unclear whether such materials actually impact microbial survival. In this work, experiments were performed in which the motile nonspore-forming Antarctic isolate Pseudoalteromonas haloplanktis in solutions of 0.1 M MgSO _4 were frozen to Europa surface temperatures (100 K) under conditions that resulted in the formation of either vitreous or crystalline salt hydrates. We found that cells survived in both cases, exhibiting a 3-log reduction in viable cells in the crystalline salt hydrate case while only a 1.5-log reduction in the vitreous salt hydrate case. Scanning electron microscopy accordingly showed much higher degrees of membrane lysis and cellular damage in the crystalline salt hydrate than the vitreous case. Our results demonstrate the ability of a terrestrial oceanic microorganism to survive in MgSO _4 solutions frozen to Europa surface temperatures, with enhanced viability in vitreous salt-hydrate-producing conditions versus crystalline. These findings suggest that future missions should target vitrified salt-rich environments for life detection due to this potential for preserving viable microorganisms that may be present and trapped in ocean world ices.

The broad-line region (BLR) size–luminosity relation has paramount importance for estimating the mass of black holes in active galactic nuclei (AGNs). Traditionally, the size of the H β BLR is often estimated from the optical continuum luminosity at 5100 Å, while the size of the H α BLR and its correlation with the luminosity is much less constrained. As a part of the Seoul National University AGN Monitoring Project, which provides 6 yr photometric and spectroscopic monitoring data, we present our measurements of the H α lags of high-luminosity AGNs. Combined with the measurements for 42 AGNs from the literature, we derive the size–luminosity relations of the H α BLR against the broad H α and 5100 Å continuum luminosities. We find the slope of the relations to be 0.61 ± 0.04 and 0.59 ± 0.04, respectively, which are consistent with the H β size–luminosity relation. Moreover, we find a linear relation between the 5100 Å continuum luminosity and the broad H α luminosity across 7 orders of magnitude. Using these results, we propose a new virial mass estimator based on the H α broad emission line, finding that the previous mass estimates based on scaling relations in the literature are overestimated by up to 0.7 dex at masses lower than 10 ^7 M _⊙ .

The progenitor system of Type Ia supernovae (SNe Ia) is expected to be a close binary system consisting of a carbon/oxygen white dwarf (WD) and a nondegenerate star or another WD. Here, we present results from high-cadence monitoring observations of SN 2021hpr in a spiral galaxy, NGC 3147, and constraints on the progenitor system based on its early multicolor light-curve data. First, we classify SN 2021hpr as a normal SN Ia from its long-term photometric and spectroscopic data. More interestingly, we found a significant “early excess” in the light curve over a simple power-law ∼ t ^2 evolution. The early light curve evolves from blue to red to blue during the first week. To explain this, we fitted the early part of the BVRI -band light curves with a two-component model consisting of ejecta–companion interaction and a simple power-law model. The early excess and its color can be explained by shock-cooling emission due to a companion star having a radius of 8.84 ± 0.58 R _⊙ . We also examined Hubble Space Telescope preexplosion images, finding no detection of a progenitor candidate, consistent with the above result. However, we could not detect signs of a significant amount of stripped mass from a nondegenerate companion star (≲0.003 M _⊙ for H α emission). The early excess light in the multiband light curve supports a nondegenerate companion in the progenitor system of SN 2021hpr. At the same time, the nondetection of emission lines opens the door for other methods to explain this event.

The development of safe and effective vaccines to prevent SARS-CoV-2 infections remains an urgent priority worldwide. We have used a recombinant vesicular stomatitis virus (rVSV)-based prime-boost immunization strategy to develop an effective COVID-19 vaccine candidate. We have constructed VSV genomes carrying exogenous genes resulting in the production of avirulent rVSV carrying the full-length spike protein (SF), the S1 subunit, or the receptor-binding domain (RBD) plus envelope (E) protein of SARS-CoV-2. Adding the honeybee melittin signal peptide (msp) to the N-terminus enhanced the protein expression, and adding the VSV G protein transmembrane domain and the cytoplasmic tail (Gtc) enhanced protein incorporation into pseudotype VSV. All rVSVs expressed three different forms of SARS-CoV-2 spike proteins, but chimeras with VSV-Gtc demonstrated the highest rVSV-associated expression. In immunized mice, rVSV with chimeric S protein-Gtc derivatives induced the highest level of potent neutralizing antibodies and T cell responses, and rVSV harboring the full-length msp-SF-Gtc proved to be the superior immunogen. More importantly, rVSV-msp-SF-Gtc vaccinated animals were completely protected from a subsequent SARS-CoV-2 challenge. Overall, we have developed an efficient strategy to induce a protective response in SARS-CoV-2 challenged immunized mice. Vaccination with our rVSV-based vector may be an effective solution in the global fight against COVID-19.

BackgroundFat fraction values obtained from magnetic resonance imaging (MRI) can be used to obtain an accurate diagnosis of fatty liver diseases. However, MRI is expensive and cannot be performed for everyone. ObjectiveIn this study, we aim to develop multi-view ultrasound image–based convolutional deep learning models to detect fatty liver disease and yield fat fraction values. MethodsWe extracted 90 ultrasound images of the right intercostal view and 90 ultrasound images of the right intercostal view containing the right renal cortex from 39 cases of fatty liver (MRI–proton density fat fraction [MRI–PDFF] ≥ 5%) and 51 normal subjects (MRI–PDFF < 5%), with MRI–PDFF values obtained from Good Gang-An Hospital. We obtained combined liver and kidney-liver (CLKL) images to train the deep learning models and developed classification and regression models based on the VGG19 model to classify fatty liver disease and yield fat fraction values. We employed the data augmentation techniques such as flip and rotation to prevent the deep learning model from overfitting. We determined the deep learning model with performance metrics such as accuracy, sensitivity, specificity, and coefficient of determination (R2). ResultsIn demographic information, all metrics such as age and sex were similar between the two groups—fatty liver disease and normal subjects. In classification, the model trained on CLKL images achieved 80.1% accuracy, 86.2% precision, and 80.5% specificity to detect fatty liver disease. In regression, the predicted fat fraction values of the regression model trained on CLKL images correlated with MRI–PDFF values (R2=0.633), indicating that the predicted fat fraction values were moderately estimated. ConclusionsWith deep learning techniques and multi-view ultrasound images, it is potentially possible to replace MRI–PDFF values with deep learning predictions for detecting fatty liver disease and estimating fat fraction values.

Chikungunya virus (CHIKV) causes outbreaks of rash, arthritis, and fever associated with neurologic complications, where astrocytes are preferentially infected. A determinant of virulence is the macrodomain (MD) of nonstructural protein 3 (nsP3), which binds and removes ADP-ribose (ADPr) from ADP-ribosylated substrates and regulates stress-granule disruption. We compared the replication of CHIKV 181/25 (WT) and MD mutants with decreased ADPr binding and hydrolase (G32S) or increased ADPr binding and decreased hydrolase (Y114A) activities in C8-D1A astrocytic cells and NSC-34 neuronal cells. WT CHIKV replication was initiated more rapidly with earlier nsP synthesis in C8-D1A than in NSC-34 cells. G32S established infection, amplified replication complexes, and induced host-protein synthesis shut-off less efficiently than WT and produced less infectious virus, while Y114A replication was close to WT. However, G32S mutation effects on structural protein synthesis were cell-type-dependent. In NSC-34 cells, E2 synthesis was decreased compared to WT, while in C8-D1A cells synthesis was increased. Excess E2 produced by G32S-infected C8-D1A cells was assembled into virus particles that were less infectious than those from WT or Y114A-infected cells. Because nsP3 recruits ADP-ribosylated RNA-binding proteins in stress granules away from translation-initiation factors into nsP3 granules where the MD hydrolase can remove ADPr, we postulate that suboptimal translation-factor release decreased structural protein synthesis in NSC-34 cells while failure to de-ADP-ribosylate regulatory RNA-binding proteins increased synthesis in C8-D1A cells.

This paper reports a concise and scalable method for the synthesis of the phytoestrogen 7,2′-dihydroxy-4′,5′-dimethoxyisoflavanone 1 via an optimized synthetic route. Compound 1 was readily obtained in 11 steps and 11% overall yield on a gram scale from commercially available 3,4-dimethoxyphenol. The key features of the synthesis include the construction of the deoxybenzoin unit through a sequence of Claisen rearrangement, oxidative cleavage, and aryllithium addition and the efficient synthesis of the isoflavanone architecture from highly functionalized 2-hydroxyketone.

Recently, Korea has upgraded the luminance standard of classrooms and started to introduce the air-conditioning system in order to enhance pleasantness of the learning environment. In addition, as use of auxiliary equipment, such as TV, VTR and computer, is increasing and due to school meals, energy consumption is increasing in school facilities. Despite the increase of energy consumption of school facilities, however, it is difficult to find actual data on energy consumption. Therefore, in this study, the actual conditions of energy consumption are researched, and the relation between the facility area, the number of classes and students, and the cooling and heating facilities is analyzed. And then, the basic data required for energy-saving strategies at school facilities are prepared. In conclusion, the energy consumption of the surveyed schools is increasing. The total annual energy consumption of each school is estimated to be 400–1750[MWh/yr], which varies between schools depending on the scale. The electric power consumption accounted for approx. 82% of the total energy consumption of the surveyed schools, and LNG and kerosene accounted for 14% and 4%, respectively. The schools using fans for cooling had significantly lower energy consumption than the schools with Electric Heat Pump(EHP). The annual energy consumption per unit area of the surveyed schools is approx. 67–240[kWh/m2/yr], and the annual average energy consumption per unit area is 133[kWh/m2/yr]. However, there is no significant difference in energy consumption per student. These results can be caused by various reasons, but are especially related with the size of school and the number of classes. Keywords: Middle schools, Buildings, Energy, Educational facilities, Energy consumption

How do classical texts, such as Hwangdi Neijing and Shanghanlun, continuously play significant roles in medical practices in the history of East Asian medicine? Although this is a significant question in interpreting the position of written texts in the medical history and even for understanding the structure of East Asian medical knowledge, it has been conspicuously underexamined in the studies of East Asian medicine. In order to explore this underrepresented question, this study focuses on currents of tradition in contemporary South Korea. Drawing on anthropological fieldwork at three Donguibogam (Treasured Mirror of Eastern Medicine) currents, it delves into the interaction of text and practice in East Asian medicine. Even though all three currents (Hyun-dong, Byeong-in, Hyung-sang) are based on Donguibogam, their ways of reading the text and organizing clinical practices are diverse. Each current sets up a keyword, such as pulse diagnosis, cause of disease, and appearance-image, and attempts to penetrate the entire Donguibogam through the keyword. This means that the classical medical text is open to plural approaches. This study found that there is a visible gap between a medical text and the reader of the text in East Asia. Masters and currents of tradition are the actors who fill up the gap, continuously interpreting and reinterpreting classical texts, and guiding medical practices of new readers. Adding the history of practice to the body of literature that have focused on the history of written texts, this study will contribute to the history of East Asian medicine.

The Yellow and Bohai seas comprise one of the most rapidly developing regions in the world, but efforts to assess coastal pollution by persistent toxic substances (PTSs) on wide spatial scale are lacking. The present study aimed to (1) measure the concentrations of PTSs, such as polycyclic aromatic hydrocarbons (PAHs), alkylphenols (APs), and styrene oligomers (SOs) via large-scale sediment monitoring (total of 125 locations), (2) assess potential ecological risk of PTSs in sediments to coastal ecosystems, (3) estimate various sources and fresh inputs of PTSs, (4) determine distribution patterns of PTSs by human activities and land-use type, and (5) address decadal (2008–2018) changes in distributions of PTSs. The high concentrations of PAHs [> 7000 ng g−1 dry weight (dw)] in sediments were detected in Nantong in the Yellow Sea of China (YSC) and Huludao and Qinhuangdao in the Bohai Sea (BS), whereas lesser concentrations (< 200 ng g−1 dw) were detected in the Yellow Sea of Korea (YSK). We found relatively high concentrations of sedimentary APs and SOs in Nantong, Huludao, and Qinhuangdao from the YSC and BS regions, but corresponding concentrations were generally below < 100 ng g−1 dw in other locations. Concentrations of PAHs at 38 locations (30% of YSC and BS) posed a potential risk to aquatic ecosystems, whereas relatively low risk concentrations occurred in all locations of YSK. The main source of PAHs (concentrated in YSC and BS) were by-products of diesel and gasoline combustion (42% of total concentration), whereas biomass combustion (24%) dominated in YSK. Fresh inputs of PTSs indicated that the generation and use of PTSs continue across all regions and locations. Among PTSs, concentrations of PAHs were significantly associated with location (p 0.05) among or within regions. Over time, concentrations of PAHs have generally declined, but sediment contamination has increased at some locations in China, with sources shifting from a mixture of PAHs types to those linked to diesel and gasoline combustion. Additional studies are needed on the fate and potential ecological risk posed by certain PTSs in hotspots. This is one of the first efforts providing backgrounds on PTS pollution in the large marine ecosystem of the Yellow and Bohai seas. Keywords: Coastal pollution, PAHs, Alkylphenols, Styrene oligomers, Ecological risk assessment, East Asia