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Abstract Background Bacteriocins are peptides with antibacterial properties that are released by lactic acid bacteria and affect genetically closely related bacteria. Settled bacteriocin-producing probiotics in the GI tract may contribute to bacteriocin formation, which can lead to pathogen inhibition and immune system regulation. The purpose of this study is to evaluate the probiotic capabilities of bacteriocin-producing LAB isolated from malted barley, Pediococcus acidilactici HW01, and Leuconostoc citreum HW02. Results Both strains could survive in harsh GI conditions such as low pH, bile salt, pepsin, and lysozyme. Furthermore, exhibited non-haemolytic activity and tetracycline and erythromycin susceptibilities. In vitro adhesion of HW01 and HW02 strains to HT-29 cells was 76.28 and 75.99%, respectively. Auto-aggregation ability of HW01 and HW02 was about 14%, but their ability to aggregate with pathogens (Escherichia coli, Salmonella enterica ser. Typhimurium, Staphylococcus aureus and Listeria monocytogenes) ranged from 32.0% to 43.5%. Regarding the anti-inflammatory effect, heat-killed bacteriocin-producing strains suppressed the mRNA expression levels of cytokines and chemokines in RAW 264.7 macrophages induced by LPS (P

Category: Trauma; Ankle Introduction/Purpose: Ankle fracture is one of the most common fractures over the age of 50 years. However, there is a lack of research on osteoporotic ankle fractures compared to other osteoporotic fractures. Recently, some studies have been published that Hounsfield Unit(HU) measuring bone attenuation from CT scan is used for assessing the bone density of not only the hip and spine but also extremities such as the distal radius and proximal humerus. This study aims to evaluate the correlation between HU of distal tibia without ankle fracture and DEXA-BMD and determine the cut-off value of HU for osteoporosis diagnosis. Additionally, this study determines whether the HU of the distal tibia obtained from the preoperative CT scan of ankle fractures helps evaluate patients with osteoporotic ankle fractures. Methods: From June 2016 to August 2020, We retrospectively studied foot and ankle traumatic patients who are postmenopausal women or men over 50 years. They conducted a foot or ankle CT scan containing the axial images of the distal tibia and DEXA- BMD within three months. Patients with open fractures with severe displacement or arthritic change were excluded. The mean HU was obtained from two sequential axial images of the distal tibial metaphysis's largest region of interest (ROI), more than 1cm proximal to the tibial plafond. We divided the patients into Group A without ankle fractures and Group B with distal tibia or fibula fractures in the ankle. The correlation analysis was done between the distal tibial HU and DEXA-BMD. We obtained the cut-off value of the distal tibial HU for osteoporosis using receiver operating characteristic(ROC) curves and compared the results between the two groups. Results: Group A was 38 cases(mean age 69.9), and Group B was 59 (mean age 71.0). There were no statistical differences in patients' characteristics, the mean distal tibial HU, bone density, T-score, and rate of osteoporosis in BMD. All HU values in both groups showed excellent inter- and intra-observer reliability(All intraclass coefficients>0.9). Both groups had significant correlations between the distal tibial HU and DEXA-BMD, especially in the femur neck and L3 spine(r=0.706, 0.622, p< 0.001 in Group A, r=0.625,0.499, p< 0.001 in Group B). The cut-off value for osteoporosis of the distal tibial HU was 153.15(sensitivity 73.9%, specificity 86.7%; area under the curve(AUC) 0.841, 95% CI 0.716-0.965, p< 0.001) in Group A. The cut-off value of Group B was 167.35(sensitivity 66.7%, specificity 75.9%; AUC 0.737, 95% CI 0.610-0.865, p=0.002). Conclusion: The distal tibial HU values on the axial images on the CT showed a significant correlation with the central bone of DEXA-BMD. The distal tibial HU value showed excellent reliability with or without fracture. HU value can be easily obtained using a preoperative ankle CT scan without additional cost & radiation exposure to patients with ankle fractures. Therefore, it can help treat osteoporotic ankle fractures by screening for osteoporosis and deciding the fixation method of surgery.

This paper addresses the challenges of optimally placing a finite number of sensors to detect Poisson-distributed targets in a bounded domain. We seek to rigorously account for uncertainty in the target arrival model throughout the problem. Sensor locations are selected to maximize the probability that no targets are missed. While this objective function is well-suited to applications where failure to detect targets is highly undesirable, it does not lead to a computationally efficient optimization problem. We propose an approximation of the objective function that is non-negative, submodular, and monotone and for which greedy selection of sensor locations works well. We also characterize the gap between the desired objective function and our approximation. For numerical illustrations, we consider the case of the detection of ship traffic using sensors mounted on the seafloor.

In this paper, we propose a novel benchmark called the StarCraft Multi-Agent Exploration Challenges(SMAC-Exp), where agents learn to perform multi-stage tasks and to use environmental factors without precise reward functions. The previous challenges (SMAC) recognized as a standard benchmark of Multi-Agent Reinforcement Learning are mainly concerned with ensuring that all agents cooperatively eliminate approaching adversaries only through fine manipulation with obvious reward functions. SMAC-Exp, on the other hand, is interested in the exploration capability of MARL algorithms to efficiently learn implicit multi-stage tasks and environmental factors as well as micro-control. This study covers both offensive and defensive scenarios. In the offensive scenarios, agents must learn to first find opponents and then eliminate them. The defensive scenarios require agents to use topographic features. For example, agents need to position themselves behind protective structures to make it harder for enemies to attack. We investigate a total of twelve MARL algorithms under both sequential and parallel episode settings of SMAC-Exp and observe that recent approaches perform well in similar settings to the previous challenge, but we discover that current multi-agent approaches place relatively less emphasis on exploration perspectives. To a limited extent, we observe that an enhanced exploration method has a positive effect on SMAC-Exp, however, there is still a gap that state-of-the-art algorithms cannot resolve the most challenging scenarios of SMAC-Exp. Consequently, we propose a new axis for future research into Multi-Agent Reinforcement Learning studies.

Meta-learning aims to learn a model that can handle multiple tasks generated from an unknown but shared distribution. However, typical meta-learning algorithms have assumed the tasks to be similar such that a single meta-learner is sufficient to aggregate the variations in all aspects. In addition, there has been less consideration of uncertainty when limited information is given as context. In this paper, we devise a novel meta-learning framework, called Meta-learning Amidst Heterogeneity and Ambiguity (MAHA), that outperforms previous works in prediction based on its ability to task identification. By extensively conducting several experiments in regression and classification, we demonstrate the validity of our model, which turns out to generalize to both task heterogeneity and ambiguity.

ABSTRACT This paper was motivated to review and discuss the current issues and challenges for decarbonisation in the international shipping sector. It was mainly focused on international and local efforts to reduce greenhouse gas (GHG) emissions from shipping activities while introducing new strategies, agreements, and regulations to meet the target on GHG reduction levels. It firstly reviewed the impact of the Clydebank Declaration made at 26th UN Climate Change Conference in Glasgow, 2021. Then, the review was moved to UK and EU policies and activities. Findings from this research offer some insights into local governmental authorities and shipping companies in terms of how to respond to gradually stringent environmental regulations as well as their roles to make the shipping sector cleaner.

Abstract Realistic image synthesis based on deep learning is an invaluable technique for developing high-performance computer aided diagnosis systems while protecting patient privacy. However, training a generative adversarial network (GAN) for image synthesis remains challenging because of the large amounts of data required for training various kinds of image features. This study aims to synthesize retinal images indistinguishable from real images and evaluate the efficacy of the synthesized images having a specific disease for augmenting class imbalanced datasets. The synthesized images were validated via image Turing tests, qualitative analysis by retinal specialists, and quantitative analyses on amounts and signal-to-noise ratios of vessels. The efficacy of synthesized images was verified by deep learning-based classification performance. Turing test shows that accuracy, sensitivity, and specificity of 54.0 ± 12.3%, 71.1 ± 18.8%, and 36.9 ± 25.5%, respectively. Here, sensitivity represents correctness to find real images among real datasets. Vessel amounts and average SNR comparisons show 0.43% and 1.5% difference between real and synthesized images. The classification performance after augmenting synthesized images outperforms every ratio of imbalanced real datasets. Our study shows the realistic retina images were successfully generated with insignificant differences between the real and synthesized images and shows great potential for practical applications.

Gamma-hydroxybutyric acid (GHB), both a metabolic precursor and product of gamma-aminobutyric acid (GABA), is a central nervous system depressant used for the treatment of narcolepsy-associated cataplexy and alcohol withdrawal. However, administration of GHB with alcohol (ethanol) is a major cause of hospitalizations related to GHB intoxication. In this study, we investigated locomotor behavior as well as metabolic and pharmacokinetic interactions following co-administration of GHB and ethanol in rats. The locomotor behavior of rats was evaluated following the intraperitoneal administration of GHB (sodium salt, 500 mg/kg) and/or ethanol (2 g/kg). Further, time-course urinary metabolic profiling of GHB and its biomarker metabolites glutamic acid, GABA, succinic acid, 2,4-dihydroxybutyric acid (OH-BA), 3,4-OH-BA, and glycolic acid as well as pharmacokinetic analysis were performed. GHB/ethanol co-administration significantly reduced locomotor activity, compared to the individual administration of GHB or ethanol. The urinary and plasma concentrations of GHB and other target compounds, except for 2,4-OH-BA, were significantly higher in the GHB/ethanol co-administration group than the group administered only GHB. The pharmacokinetic analysis results showed that the co-administration of GHB and ethanol significantly increased the half-life of GHB while the total clearance decreased. Moreover, a comparison of the metabolite-to-parent drug area under the curve ratios demonstrated that the metabolic pathways of GHB, such α- and β-oxidation, were inhibited by ethanol. Consequently, the co-administration of GHB and ethanol aggravated the metabolism and elimination of GHB and enhanced its sedative effect. These findings will contribute to clinical interpretation of GHB intoxication.

ERBB3, a key member of the receptor tyrosine kinase family, is implicated in the progression and development of various human cancers, affecting cellular proliferation and survival. This study investigated the expression of ERBB3 isoforms in renal clear cell carcinoma (RCC), utilizing data from 538 patients from The Cancer Genome Atlas (TCGA) Firehose Legacy dataset. Employing the SUPPA2 tool, the activity of 10 ERBB3 isoforms was examined, revealing distinct expression patterns in RCC. Isoforms uc001sjg.3 and uc001sjh.3 were found to have reduced activity in tumor tissues, while uc010sqb.2 and uc001sjl.3 demonstrated increased activity. These variations in isoform expression correlate with patient survival and tumor aggressiveness, indicating their complex role in RCC. The study, further, utilizes CIBERSORTx to analyze the association between ERBB3 isoforms and immune cell profiles in the tumor microenvironment. Concurrently, Gene Set Enrichment Analysis (GSEA) was applied, establishing a strong link between elevated levels of ERBB3 isoforms and critical oncogenic pathways, including DNA repair and androgen response. RT-PCR analysis targeting the exon 21–23 and exon 23 regions of ERBB3 confirmed its heightened expression in tumor tissues, underscoring the significance of alternative splicing and exon utilization in cancer development. These findings elucidate the diverse impacts of ERBB3 isoforms on RCC, suggesting their potential as diagnostic markers and therapeutic targets. This study emphasizes the need for further exploration into the specific roles of these isoforms, which could inform more personalized and effective treatment modalities for renal clear cell carcinoma.

BackgroundHemispatial neglect (HSN) was diagnosed using a virtual reality-based test (FOPR test) that explores the field of perception (FOP) and field of regard (FOR). Here, we developed virtual reality-visual exploration therapy (VR-VET) combining elements from the FOPR test and visual exploration therapy (VET) and examined its efficacy for HSN rehabilitation following stroke.MethodsEleven participants were randomly assigned to different groups, training with VR-VET first then waiting without VR-VET training (TW), or vice versa (WT). The TW group completed 20 sessions of a VR-VET program using a head-mounted display followed by 4 weeks of waiting, while the WT group completed the opposite regimen. Clinical HSN measurements [line bisection test (LBT), star cancellation test (SCT), Catherine Bergego Scale (CBS), CBS perceptual-attentional (CBS-PA), and CBS motor-explanatory (CBS-ME)] and FOPR tests [response time (RT), success rate (SR), and head movement (HM) for both FOP and FOR] were assessed by blinded face-to-face assessments.ResultsFive and six participants were allocated to the TW and WT groups, respectively, and no dropout occurred throughout the study. VR-VET considerably improved LBT scores, FOR variables (FOR-RT, FOR-SR), FOP-LEFT variables (FOP-LEFT-RT, FOP-LEFT-SR), and FOR-LEFT variables (FOR-LEFT-RT, FOR-LEFT-SR) compared to waiting without VR-VET. Additionally, VR-VET extensively improved FOP-SR, CBS, and CBS-PA, where waiting failed to make a significant change. The VR-VET made more improvements in the left hemispace than in the right hemispace in FOP-RT, FOP-SR, FOR-RT, and FOR-SR.ConclusionThe observed improvements in clinical assessments and FOPR tests represent the translatability of these improvements to real-world function and the multi-dimensional effects of VR-VET training.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03463122, identifier NCT03463122.

Abstract Dietary antigens affect the adaptive immunity of the host by inducing regulatory T cells and IgE-producing B cells. However, their roles in innate immune compartments such as innate lymphoid cells (ILCs) and intestinal epithelial cells (IECs) are unclear. Here, using antigen-free (AF) mice, which are germ-free (GF) mice fed with amino-acid-based diet, we found dietary proteins suppress the development of GATA-3-expressing ILC2s independent of the adaptive immune cells. These cells produce more type 2 cytokines and upregulated proliferation and activation markers such as Ki-67, CD69, and CD25. With this, AF mice had increased expressions of tuft cell-specific transcripts such as Il25, Il33, Dclk1, Trpm5, and Pou2f3 in IECs. Accordingly, expanded ILC2s upregulated IL-17RB, a receptor of IL-25, and their proliferation was blocked by IL-25 neutralizing or IL-17RB blocking antibodies. These results suggest a new dialogue between dietary antigens, IECs, and ILCs in which dietary antigens suppress ILC2 activation and proliferation by restraining homeostatic IL-25 production, potentially limiting type 2 immunity by food antigens.

Elevated levels of IgE is associated with a range of allergic pathology but the source of such IgE producing B cells during the steady state is poorly understood. Here, Kwon et al. show that homeostatic IgE is secreted by plasma cells in the thymus and link this to mast cell survival.

A space-based augmentation system (SBAS) provides real-time GNSS correction signals via geostationary satellites for near-ground GNSS users. To use the SBAS correction for low Earth orbit (LEO) satellites, the correction, especially the ionosphere correction, must be adjusted for the LEO altitude. We apply modified SBAS data to LEO satellite onboard navigator to improve the positioning accuracy of a LEO satellite for possible real-time use. The onboard navigator requires high positioning reliability, and code pseudoranges, rather than phase pseudoranges, are used for the primary measurements. The Galileo NeQuick G model is used to determine the real-time conversion factor of the SBAS ionosphere correction for a LEO satellite. The GPS L1 data from GRACE satellite are combined with the SBAS data from the ground receiver. The onboard navigator combines the precise satellite dynamic model with an extended Kalman filter to improve positioning accuracy and stability. The kinematic positioning method, which uses the weighted least square method without the dynamic model, is also performed for comparison. The SBAS correction reduces the positioning error in both the kinematic positioning and the dynamic positioning. The positioning error reduction of the GPS and WAAS case over the GPS-only case is 25.2% for the kinematic method and 30.6% for the dynamic method. In the case of the dynamic method with the SBAS corrections, the positioning error remains smaller than that of the GPS-only dynamic method even after the satellite has left the SBAS service area.

Abstract Realistic image generation is valuable in dental medicine, but still challenging for generative adversarial networks (GANs), which require large amounts of data to overcome the training instability. Thus, we generated lateral cephalogram X-ray images using a deep-learning-based progressive growing GAN (PGGAN). The quality of generated images was evaluated by three methods. First, signal-to-noise ratios of real/synthesized images, evaluated at the posterior arch region of the first cervical vertebra, showed no statistically significant difference (t-test, p = 0.211). Second, the results of an image Turing test, conducted by non-orthodontists and orthodontists for 100 randomly chosen images, indicated that they had difficulty in distinguishing whether the image was real or synthesized. Third, cephalometric tracing with 42 landmark points detection, performed on real and synthesized images by two expert orthodontists, showed consistency with mean difference of 2.08 ± 1.02 mm. Furthermore, convolutional neural network-based classification tasks were used to classify skeletal patterns using a real dataset with class imbalance and a dataset balanced with synthesized images. The classification accuracy for the latter case was increased by 1.5%/3.3% at internal/external test sets, respectively. Thus, the cephalometric images generated by PGGAN are sufficiently realistic and have potential to application in various fields of dental medicine.

Alopecia areata (AA) is an autoimmune disease mediated by NKG2D-expressing cytotoxic T lymphocytes destroying hair follicles in the skin. It is one of the most common autoimmune diseases, but there is no effective treatment modality approved by the FDA. Regulatory T cells (Tregs) are crucial for suppressing autoreactive T cells, and in the skin, they promote hair growth by inducing anagen. Based on this, we tested the therapeutic potential of expanded Tregs in AA using the C3H/HeJ mouse model. In mice with AA, NKG2D-expressing CD8 T cells widely infiltrate both haired and hairless skin areas, which have tissue-resident memory T-cell phenotypes. Tregs in the skin express CD25, CTLA-4, GATA-3, and Jagged1 and efficiently proliferate with IL-2 cytokine antibody complex. However, expanding Tregs in the skin did not induce anagen in normal mice, indicating that they are necessary but not sufficient for anagen induction. Also, they fail to suppress autoreactive CD8 T cells in the skin to reverse established AA in C3H/HeJ mice. These results suggest that Treg expansion alone is not sufficient for AA treatment, and combined immunotherapy is required.

The manufacture of complicated automobile components that are joined by resistance spot welding requires considerable cost and time. The use of additive manufacturing technology to manufacture automobile components helps reduce the overall time consumption and yields high accuracy. In this study, the weldability of conventional (C) 316L stainless steel and additive manufactured (AM) 316L stainless steel was evaluated and analyzed. After deriving the lobe diagram for both the materials, the monitoring data, nugget diameter, tensile shear strength, and hardness were analyzed. The findings of the study have opened up a massive potential for use in resistance spot welding technology for additive manufactured materials’ industries in the forthcoming years. When AM 316L stainless steel was welded in the constant current control mode, a nugget diameter of up to 4.7 mm, which is below the international standard, could be secured. Through the constant power control mode, however, the nugget diameter could be improved to a sufficient level of 5.8 mm.

Gamma-hydroxybutyric acid (GHB), used as a therapeutic and an illegal anesthetic, is a human neurotransmitter produced during gamma-aminobutyric acid (GABA) biosynthesis and metabolism. Potential biomarker metabolites of GHB intoxication have been identified previously; however, reference concentrations have not been set due to the lack of clinical study data. Urinary profiling of endogenous GHB and its biomarker metabolites in urine samples (n = 472) of 206 healthy females was performed based on differences in age and time of sample collection using liquid chromatography-tandem mass spectrometry following validation studies. The unadjusted and creatinine-adjusted urinary concentrations ranges were obtained after urinary profiling. The creatinine-adjusted concentrations of glutamic and succinic acids and succinylcarnitine significantly increased, whereas that of glycolic acid significantly decreased with advancing age. Significant inter-day variation of GABA concentration and intra-day variation of 3,4-dihydroxybutyric acid and succinylcarnitine concentrations were observed. The urinary concentrations of 2,4-dihydroxybutyric acid, succinic acid, and 3,4-dihydroxybutyric acid showed the highest correlation with that of GHB. Data from this study suggest population reference limits to facilitate clinical and forensic decisions related to GHB intoxication and could be useful for identification of biomarkers following comparison with urinary profiles of GHB-administered populations.

Medical image analyses have been widely used to differentiate normal and abnormal cases, detect lesions, segment organs, etc. Recently, owing to many breakthroughs in artificial intelligence techniques, medical image analyses based on deep learning have been actively studied. However, sufficient medical data are difficult to obtain, and data imbalance between classes hinder the improvement of deep learning performance. To resolve these issues, various studies have been performed, and data augmentation has been found to be a solution. In this review, we introduce data augmentation techniques, including image processing, such as rotation, shift, and intensity variation methods, generative adversarial network-based method, and image property mixing methods. Subsequently, we examine various deep learning studies based on data augmentation techniques. Finally, we discuss the necessity and future directions of data augmentation.

Abstract Background There is a paucity of reports clarifying the implication of knee osteoarthritis (OA) on spinal sagittal alignment of patients undergone surgery for lumbar spine. This study aimed to analyze how osteoarthritic knee affects radiographic and clinical results of degenerative lumbar disease patients undergone lumbar fusion. Methods We retrospectively reviewed the medical records and radiographs of 74 consecutive degenerative lumbar disease patients who underwent posterior instrumentation and fusion surgery between May 2016 and June 2017 and were followed up for minimum 3 years postoperatively. The patients were divided into 2 groups according to the severity of knee OA by Kellgren-Lawrence grading (KLG) scale (group I, KLG 1 or 2 [n = 39]; group II, KLG 3 or 4 [n = 35]). Patient demographic data, comorbidities, spinal sagittal parameters and clinical scores were extracted and compared at preoperative, postoperative 1 month and the ultimate follow-up between the groups. In radiographic assessment, sagittal alignment parameters and sagittal balance were used. In clinical assessment, the scores of Oswestry disability index (ODI) and Scoliosis Research Society questionnaire (SRS-22) were used. For the frequency analysis of categorical variables across the groups, chi-square test was used and student t tests was used to compare the differences of continuous variables. Results In radiographic assessment, TLK (thoracolumbar kyphosis), LL (lumbar lordosis), PT (pelvic tilt), C7 SVA (sagittal vertical axis) in both groups improved significantly after surgery (p 0.05). There were significant differences between the groups at the ultimate follow-up in ODI (− 25.6 vs − 12.1, p

Gamma-hydroxybutyric acid (GHB) is a potent, short-acting central nervous system depressant as well as an inhibitory neurotransmitter or neuromodulator derived from gamma-aminobutyric acid (GABA), a major inhibitory neurotransmitter. The sodium salt of GHB, sodium oxybate, has been used for the treatment of narcolepsy and cataplexy, whereas GHB was termed as a date rape drug or a club drug in the 1990s. Ethanol is the most co-ingested drug in acute GHB intoxication. In this review, the latest findings on the combined effects of GHB and ethanol are summarized from toxicokinetic and toxicodynamic perspectives. For this purpose, we mainly discussed the pharmacology and toxicology of GHB, GHB intoxication under alcohol consumption, clinical cases of the combined intoxication of GHB and ethanol, and previous studies on the toxicokinetic and toxicodynamic interactions between GHB and ethanol in humans, animals, and an in vitro model. The combined administration of GHB and ethanol enhanced sedation and cardiovascular dysfunction, probably by the additive action of GABA receptors, while toxicokinetic changes of GHB were not significant. The findings of this review will contribute to clinical and forensic interpretation related to GHB intoxication. Furthermore, this review highlights the significance of studies aiming to further understand the enhanced inhibitory effects of GHB induced by the co-ingestion of ethanol.

The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learnable data, ANN has suffered from overfitting and vanishing gradient problems for training deep networks. The advancement of computing power with graphics processing units and the availability of large data acquisition, deep neural network outperforms human or other ML capabilities in computer vision and speech recognition tasks. These potentials are recently applied to healthcare problems, including computer-aided detection/diagnosis, disease prediction, image segmentation, image generation, etc. In this review article, we will explain the history, development, and applications in medical imaging

In this study, numerical simulations for the prediction of added resistance for KVLCC2 with varying wave steepness are performed using a Computational Fluid Dynamics (CFD) method and a 3-D linear potential method, and then the non-linearities of added resistance and ship motions are investigated in regular short and long waves. Firstly, grid convergence tests in short and long waves are carried out to establish an optimal mesh system for CFD simulations. Secondly, numerical simulations are performed to predict ship added resistance and vertical motion responses in short and long waves and the results are verified using the available experimental data. Finally, the non-linearities of added resistance and ship motions with unsteady wave patterns in the time domain are investigated with the increase in wave steepness in both short and long waves. The present systematic study demonstrates that the numerical results have a reasonable agreement with the experimental data and emphasizes the non-linearity in the prediction of the added resistance and the ship motions with the increasing wave steepness in short and long waves. Keywords: Added resistance, Wave steepness, Short waves, Potential flow, CFD, KVLCC2

Protopine is a substance used for hemostasis with an anti-inflammatory action and is one of the substances that are actively undergoing experiments to confirm their utility as anticancer agents. This study examined the molecular changes in the cellular signaling pathways associated with inflammatory responses in phorbol 12-myristate 13 acetate (PMA)-induced human hepatocellular carcinoma cell line (Hep G2). The inhibition of PMA-induced phosphorylation of I-κB in HepG2, the effect of protopine on the MAPK signals, the inhibition of COX-2 activity, and the inhibition of MMP-9 as a medium of inflammatory response were evaluated by Western blot and qPCR. The effect of protopine on the survival rates in HepG2 cells was evaluated and found to be stable to a processing concentration of up to 40μM. Subsequent Western blot analyses showed that protopine blocks the transfer of the MAPKs cell signals induced by PMA and the transfer of the subunit of the nuclear factor-kappa B (NF-κB) to the nucleolus. Protopine inhibited the kappa alpha (I-κBα) phosphorylation in the cytosol and blocked PMA-induced inflammation via COX-2 activity inhibition. The expression of MMP-9 at the gene and protein levels, which is associated with cell migration and metastasis, was reduced by protopine.

Particulate matter (PM) induces neutrophilic inflammation and deteriorates the prognosis of diseases such as cardiovascular diseases, cancers, and infections, including COVID-19. Here, we addressed the role of γδ T cells and intestinal microbiome in PM-induced acute neutrophilia. γδ T cells are a heterogeneous population composed of Tγδ1, Tγδ2, Tγδ17, and naïve γδ T cells (TγδN) and commensal bacteria promote local expansion of Tγδ17 cells, particularly in the lung and gut without affecting their Vγ repertoire. Tγδ17 cells are more tissue resident than Tγδ1 cells, while TγδN cells are circulating cells. IL-1R expression in Tγδ17 cells is highest in the lung and they outnumber all the other type 17 cells such as Th17, ILC3, NKT17, and MAIT17 cells. Upon PM exposure, IL-1β-secreting neutrophils and IL-17-producing Tγδ17 cells attract each other around the airways. Accordingly, PM-induced neutrophilia was significantly relieved in γδ T- or IL-17-deficient and germ-free mice. Collectively, these findings show that the commensal microbiome promotes PM-induced neutrophilia in the lung via Tγδ17 cells.

Space-based augmentation system (SBAS) provides correction information for improving the global navigation satellite system (GNSS) positioning accuracy in real-time, which includes satellite orbit/clock and ionospheric delay corrections. At SBAS service area boundaries, the correction is not fully available to GNSS users and only a partial correction is available, mostly satellite orbit/clock information. By using the geospatial correlation property of the ionosphere delay information, the ionosphere correction coverage can be extended by a spatial extrapolation algorithm. This paper proposes extending SBAS ionosphere correction coverage by using a biharmonic spline extrapolation algorithm. The wide area augmentation system (WAAS) ionosphere map is extended and its ionospheric delay error is compared with the GPS Klobuchar model. The mean ionosphere error reduction at low latitude is 52.3%. The positioning accuracy of the extended ionosphere correction method is compared with the accuracy of the conventional SBAS positioning method when only a partial set of SBAS corrections are available. The mean positioning error reduction is 44.8%, and the positioning accuracy improvement is significant at low latitude.

We propose a low-asymmetry interface to improve the presence of non-head-mounted-display (non-HMD) users in shared virtual reality (VR) experiences with HMD users. The low-asymmetry interface ensures that the HMD and non-HMD users’ perception of the VR environment is almost similar. That is, the point-of-view asymmetry and behavior asymmetry between HMD and non-HMD users are reduced. Our system comprises a portable mobile device as a visual display to provide a changing PoV for the non-HMD user and a walking simulator as an in-place walking detection sensor to enable the same level of realistic and unrestricted physical-walking-based locomotion for all users. Because this allows non-HMD users to experience the same level of visualization and free movement as HMD users, both of them can engage as the main actors in movement scenarios. Our user study revealed that the low-asymmetry interface enables non-HMD users to feel a presence similar to that of the HMD users when performing equivalent locomotion tasks in a virtual environment. Furthermore, our system can enable one HMD user and multiple non-HMD users to participate together in a virtual world; moreover, our experiments show that the non-HMD user satisfaction increases with the number of non-HMD participants owing to increased presence and enjoyment.

The introduction of the maritime autonomous surface ship (MASS) to the maritime industry will open up a new era and bring about a new paradigm shift in terms of cost efficiency, maritime accidents, and human resources. Various studies are currently being conducted to realize the MASS. Understanding the scope and direction of these studies will be of great help for future MASS research. In this study, the current development status of technologies for autonomous ships is identified, and considerations and directions of improvement are suggested for six major research fields that cover all technological issues of MASS. Firstly, the results of the regulatory scoping exercise (RSE) on the International Maritime Organization (IMO) conventions to accept MASSs are identified; in particular, human elements are identified as vital issues to be considered for the design and operation of MASSs. Secondly, various studies on the decision-making system are identified, and the future direction is suggested. Thirdly, in terms of ship design and propulsion system, design changes for autonomous cargo ships are investigated, with their potential impacts to be considered. Fourthly, the communication system will need to be robust and supported by multiple systems to minimize potential risk with third-party infrastructures, and suitable protection of systems, networks, and data will be required as an integral part of the safety system for cybersecurity. Fifthly, issues of maintenance and repair are identified, with a maintenance strategy to be considered. Lastly, hazard analysis of the autonomous ship is explored, and system-theoretic process analysis (STPA) and the functional resonance analysis method (FRAM) are identified as the most representative new methods that can be used for hazard analysis of autonomous ships.

This study proposes an asymmetric interface that can provide head-mounted display (HMD) and non-HMD users with improved presence and an experience consistent with the user’s environment in an asymmetric virtual reality. For the proposed asymmetric interface, a controller-based hand interface is designed for portability, easy and convenient use, and high immersion. Subsequently, a three-step decision-making structure that supports accurate and efficient decision-making is defined based on the asymmetric experience structure of each user (HMD and non-HMD). Based on this process, an optimal interface that distinguishes between HMD (direct interaction) and non-HMD users (multi-viewpoint interaction) is implemented. With the objective of surveying and analyzing each user’s experience along with the presence provided by the proposed interface, an asymmetric virtual reality application is developed directly, and an experiment is conducted with the participants. Finally, it is statistically analyzed and verified that the use of the proposed asymmetric interface can provide optimal presence and user-optimized experience to both HMD and non-HMD users.

This paper presents the simplified welding distortion analysis method to predict the welding deformation of both plate and stiffener in fillet welds. Currently, the methods based on equivalent thermal strain like Strain as Direct Boundary (SDB) has been widely used due to effective prediction of welding deformation. Regarding the fillet welding, however, those methods cannot represent deformation of both members at once since the temperature degree of freedom is shared at the intersection nodes in both members. In this paper, we propose new approach to simulate deformation of both members. The method can simulate fillet weld deformations by employing composite shell element and using different thermal expansion coefficients according to thickness direction with fixed temperature at intersection nodes. For verification purpose, we compare of result from experiments, 3D thermo elastic plastic analysis, SDB method and proposed method. Compared of experiments results, the proposed method can effectively predict welding deformation for fillet welds.

The global navigation satellite system (GNSS) is widely used to estimate user positions. For precise positioning, users should correct for GNSS error components such as satellite orbit and clock errors as well as ionospheric delay. The international GNSS service (IGS) real-time service (RTS) can be used to correct orbit and clock errors in real-time. Since the IGS RTS provides real-time corrections via the Internet, intermittent data loss can occur due to software or hardware failures. We propose applying a genetic algorithm autoregressive moving average (GA-ARMA) model to predict the IGS RTS corrections during data loss periods. The RTS orbit and clock corrections are predicted up to 900 s via the GA-ARMA model, and the prediction accuracies are compared with the results from a generic ARMA model. The orbit prediction performance of the GA-ARMA is nearly equivalent to that of ARMA, but GA-ARMA’s clock prediction performance is clearly better than that of ARMA, achieving a 32% error reduction. Predicted RTS corrections are applied to the broadcast ephemeris, and precise point positioning accuracies are compared. GA-ARMA shows a significant accuracy improvement over ARMA, particularly in terms of vertical positioning.

This research was focused on a comparative analysis of using LNG as a marine fuel with a conventional marine gas oil (MGO) from an environmental point of view. A case study was performed using a 50K bulk carrier engaged in domestic services in South Korea. Considering the energy exporting market for South Korea, the fuel supply chain was designed with the two largest suppliers: Middle East (LNG-Qatar/MGO-Saudi Arabia) and U.S. The life cycle of each fuel type was categorized into three stages: Well-to-Tank (WtT), Tank-to-Wake (TtW), and Well-to-Wake (WtW). With the process modelling, the environmental impact of each stage was analyzed based on the five environmental impact categorizes: Global Warming Potential (GWP), Acidification Potential (AP), Photochemical Potential (POCP), Eutrophication Potential (EP) and Particulate Matter (PM). Analysis results reveal that emission levels for the LNG cases are significantly lower than the MGO cases in all potential impact categories. Particularly, Case 1 (LNG import to Korea from Qatar) is identified as the best option as producing the lowest emission levels per 1.0 × 107 MJ of fuel consumption: 977 tonnages of CO2 equivalent (for GWP), 1.76 tonnages of SO2 equivalent (for AP), 1.18 tonnages of N equivalent (for EP), 4.28 tonnages of NMVOC equivalent (for POCP) and 26 kg of PM 2.5 equivalent (for PM). On the other hand, the results also point out that the selection of the fuel supply routes could be an important factor contributing to emission levels since longer distances for freight transportation result in more emissions. It is worth noting that the life cycle assessment can offer us better understanding of holistic emission levels contributed by marine fuels from the cradle to the grave, which are highly believed to remedy the shortcomings of current marine emission indicators.

This study proposes the interaction of third-person virtual reality (TPVR) to provide users with a new presence and experience during immersive virtual reality (VR). The proposed TPVR interaction consists of the ability to directly control the virtual environment and objects by utilizing the hands. For this purpose, this study defines the interaction of TPVR from three types: moving inside the virtual environment, selecting virtual objects and using a menu interface that includes a variety of functions and behaviors. Then, it designs its own experimental application that is able to systematically compare and analyze the proposed interaction against traditional first-person perspective VR. Finally, it examines whether the proposed interaction provides new presence and experience to users by conducting survey experiments. Through this process, this study was able to confirm not only that TPVR interaction can provide a sufficient presence, even in comparison with the first-person viewpoint, but also that it causes less VR sickness and offers a differentiated VR experience, suggesting that the proposed interaction can provide an alternative method for utilizing VR technology in a greater variety of fields.

For low earth orbit (LEO) satellite GPS receivers, space-based augmentation system (SBAS) ephemeris/clock corrections can be applied to improve positioning accuracy in real time. The SBAS correction is only available within its service area, and the prediction of the SBAS corrections during the outage period can extend the coverage area. Two time series forecasting models, autoregressive moving average (ARMA) and autoregressive (AR), are proposed to predict the corrections outside the service area. A simulated GPS satellite visibility condition is applied to the WAAS correction data, and the prediction accuracy degradation, along with the time, is investigated. Prediction results using the SBAS rate of change information are compared, and the ARMA method yields a better accuracy than the rate method. The error reductions of the ephemeris and clock by the ARMA method over the rate method are 37.8% and 38.5%, respectively. The AR method shows a slightly better orbit accuracy than the rate method, but its clock accuracy is even worse than the rate method. If the SBAS correction is sufficiently accurate comparing with the required ephemeris accuracy of a real-time navigation filter, then the predicted SBAS correction may improve orbit determination accuracy.

This research proposes a gaze pointer-based user interface to provide user-oriented interaction suitable for the virtual reality environment on mobile platforms. For this purpose, a mobile platform-based three-dimensional interactive content is produced to test whether the proposed gaze pointer-based interface increases user satisfaction through the interactions in a virtual reality environment based on mobile platforms. The gaze pointer-based interface—the most common input method for mobile virtual reality content—is designed by considering four types: the visual field range, the feedback system, multi-dimensional information transfer, and background colors. The performance of the proposed gaze pointer-based interface is analyzed by conducting experiments on whether or not it offers motives for user interest, effects of enhanced immersion, provision of new experience, and convenience in operating content. In addition, it is verified whether any negative psychological factors, such as VR sickness, fatigue, difficulty of control, and discomfort in using contents are caused. Finally, through the survey experiment, this study confirmed that it is possible to design different ideal gaze pointer-based interface in mobile VR environment according to presence and convenience.