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Psilocybin, a psychoactive substance, has recently garnered attention for its high therapeutic potential in psychiatry. In this study, we investigated the multifaceted aspects of psilocybin, highlighting its chemical properties, mechanisms of action, and burgeoning role in psychiatric treatment. Furthermore, we examined the clinical applications and potential therapeutic benefits of psilocybin in the treatment of various mental health disorders, supported by accumulating clinical evidence. This review aims to deepen our understanding of the clinical impact of psilocybin, elucidate its therapeutic value, and propose directions for future research, thereby paving the way for its integration into mainstream psychiatric treatments. Psilocybin has been shown to be safe in clinical trials with manageable side effects. However, additional safety measures are required after this discussion, including dosing protocols, patient monitoring, and distress management strategies.

Clouds and their shadows significantly affect satellite imagery, resulting in a loss of radiometric information in the shadowed areas. This loss reduces the accuracy of land cover classification and object detection. Among various cloud shadow detection methods, the geometric-based method relies on the geometry of the sun and sensor to provide consistent results across diverse environments, ensuring better interpretability and reliability. It is well known that the direction of shadows in raw satellite images depends on the sun’s illumination and sensor viewing direction. Orthoimages are typically corrected for relief displacements caused by oblique sensor viewing, aligning the shadow direction with the sun. However, previous studies lacked an explicit experimental verification of this alignment, particularly for cloud shadows. We observed that this implication may not be realized for cloud shadows, primarily due to the unknown height of clouds. To verify this, we used Rapideye orthoimages acquired in various viewing azimuth and zenith angles and conducted experiments under two different cases: the first where the cloud shadow direction was estimated based only on the sun’s illumination, and the second where both the sun’s illumination and the sensor’s viewing direction were considered. Building on this, we propose an automated approach for cloud shadow detection. Our experiments demonstrated that the second case, which incorporates the sensor’s geometry, calculates a more accurate cloud shadow direction compared to the true angle. Although the angles in nadir images were similar, the second case in high-oblique images showed a difference of less than 4.0° from the true angle, whereas the first case exhibited a much larger difference, up to 21.3°. The accuracy results revealed that shadow detection using the angle from the second case improved the average F1 score by 0.17 and increased the average detection rate by 7.7% compared to the first case. This result confirms that, even if the relief displacement of clouds is not corrected in the orthoimages, the proposed method allows for more accurate cloud shadow detection. Our main contributions are in providing quantitative evidence through experiments for the application of sensor geometry and establishing a solid foundation for handling complex scenarios. This approach has the potential to extend to the detection of shadows in high-resolution satellite imagery or UAV images, as well as objects like high-rise buildings. Future research will focus on this.

PURPOSE The purpose of this study was to analyze the effect size of the unified theory of acceptance and use of technology (UTAUT) in the sports field using a meta-analysis. METHODS After identifying related studies by using RISS, 22 articles were selected and used to analyze the relationship between UTAUT sub-factors (performance expectancy [PE], effort expectancy [EE], social influence [SI], and facilitating conditions [FC]) and intention to use via the comprehensive meta-analysis program. RESULTS The results are as follows: First, the effect size between PE and intention to use was 0.521. Second, the effect size between FC and intention to use was 0.514. Third, the effect size between EE and intention to use was 0.500. Finally, the effect size between SI and intention to use was 0.475. CONCLUSIONS Diverse strategies can be derived to increase consumers' intention to use in the sports field using the UTAUT model.

Recent advancements in satellite technology have significantly increased the availability of high-resolution imagery for Earth observation, enabling nearly all regions to be captured frequently throughout the year. These images have become a vast source of big data and hold immense potential for various applications, including environmental monitoring, urban planning, and disaster management. However, obtaining ground control points (GCPs) and performing geometric correction is a time-consuming and costly process, often limiting the efficient use of these images. To address this challenge, this study introduces a Rational Function Model (RFM)-based rigorous bundle adjustment method to enhance the relative geometric positioning accuracy of multiple KOMPSAT-3A images without the need for GCPs. The proposed method was tested using KOMPSAT-3A images. The results showed a significant improvement in geometric accuracy, with mean positional errors reduced from 30.02 pixels to 2.21 pixels. This enhancement ensured that the corrected images derived from the proposed method were reliable and accurate, making it highly valuable for various geospatial applications.

PURPOSE This study aimed to investigate user perceptions regarding the mobile healthcare application of public health centers by using big data. METHODS The study data included 1,089 users’ reviews (from September 27, 2016 to December 23, 2021), which were analyzed using Python, Textom, KrKwic, UCINET 6, and the Net-draw program. RESULTS First, the evaluation of the application showed a higher number of “Good” responses (677 times) compared to “Bad” (329 times) and “Normal” responses (83 times). Second, network structures related to “Good” were “Like,” “Health care,” “Help,” “A sense of purpose,” “Grateful,” “Diet management,” “Exercise management,” “Easy,” “Recommendation,” “Satisfaction,” “Diet,” “Useful,” and so on. Third, network structures related to “Bad” were “Execution error,” “Request improvement,” “Question,” “Slow speed,” “Interlocking error,” “Lack of food type,” “Login error,” “Inconvenience,” “Delete and reinstall,” “Update error,” “Irritation,” “Connection error,” “Problem occurred,” “Direct input request,” “Not available,” “Waste of stars,” “Lack of function,” “Not enough,” “Stuffy,” “Lack of exercise,” and so on. Fourth, as a result of structural equivalence analysis, four clusters appeared: cluster 1 (negative function), cluster 2 (negative emotion), cluster 3 (positive function), and cluster 4 (positive emotion). CONCLUSIONS It is necessary to respond quickly in order to reflect on the users’ reviews, and active efforts are required to improve the program quality so that users can use it conveniently.

Abstract Recent studies on osteosarcoma regimens have mainly focused on modifying the combination of antineoplastic agents rather than enhancing the therapeutic efficacy of each component. Here, an albumin nanocluster (NC)‐assisted methotrexate (MTX), doxorubicin (DOX), and cisplatin (MAP) regimen with improved antitumor efficacy is presented. Human serum albumin (HSA) is decorated with thiamine pyrophosphate (TPP) to increase the affinity to the bone tumor microenvironment (TME). MTX or DOX (hydrophobic MAP components) is adsorbed to HSA‐TPP via hydrophobic interactions. MTX‐ or DOX‐adsorbed HSA‐TPP NCs exhibit 20.8‐ and 1.64‐fold higher binding affinity to hydroxyapatite, respectively, than corresponding HSA NCs, suggesting improved targeting ability to the bone TME via TPP decoration. A modified MAP regimen consisting of MTX‐ or DOX‐adsorbed HSA‐TPP NCs and free cisplatin displays a higher synergistic anticancer effect in HOS/MNNG human osteosarcoma cells than conventional MAP. TPP‐decorated NCs show 1.53‐fold higher tumor accumulation than unmodified NCs in an orthotopic osteosarcoma mouse model, indicating increased bone tumor distribution. As a result, the modified regimen more significantly suppresses tumor growth in vivo than solution‐based conventional MAP, suggesting that HSA‐TPP NC‐assisted MAP may be a promising strategy for osteosarcoma treatment.

UAV remote sensing is suitable for urgent image monitoring and periodic observation of an area of interest. To observe a target area using UAVs, many images must be acquired because of the narrow image coverage of UAVs. To increase the efficiency of UAV remote sensing, UAV mosaicking is used to create a single image from multiple UAV images. In order to maintain the strength of rapid UAV deployment, UAV mosaicked images have to be quickly generated through image-based mosaicking techniques. In addition, it is necessary to improve the mosaic errors of image-based techniques that often occur in contrast to terrain-based techniques. Relief displacement is a major source of mosaic error and can be detected by utilizing a terrain model. We have proposed an image-based mosaicking technique utilizing TIN, which is a model that can represent terrain with discontinuously acquired height information of ground points. Although the TIN is less accurate than DSM, it is simpler and faster to utilize for image mosaicking. In our previous work, we demonstrated fast processing speed of mosaicking using TIN-based image tiepoints. In this study, we improve the quality of image-based mosaicking techniques by optimizing seamline-based TIN geometry. Three datasets containing buildings with large relief displacement were used in this study. The experiment results showed that the TIN based on the proposed method improved the mosaic error caused by relief displacement significantly.

To take full advantage of rapidly deployable unmanned aerial vehicles (UAVs), it is essential to effectively compose many UAV images into one observation image over a region of interest. In this paper, we propose fast image mosaicking using a triangulated irregular network (TIN) constructed from tiepoints. We conduct pairwise tiepoint extraction and rigorous bundle adjustment to generate rigorous tiepoints. We apply a bucketing algorithm to the tiepoints and generate evenly distributed tiepoints. We then construct a TIN from the bucketed tiepoints and extract seamlines for image stitching based on the TIN. Image mosaicking is completed by mapping UAV images along the seamlines onto a reference plane. The experimental results showed that the image mosaicking based on a TIN of bucketed tiepoints could produce image mosaics with stable and fast performance. We expect that our method could be used for rapid image mosaicking.

Summary Faecalibacterium prausnitzii (F. prausnitzii) is one of the most abundant bacteria in the human intestine, with its anti‐inflammatory effects establishing it as a major effector in human intestinal health. However, its extreme sensitivity to oxygen makes its cultivation and physiological study difficult. F. prausnitzii produces butyric acid, which is beneficial to human gut health. Butyric acid is a short‐chain fatty acid (SCFA) produced by the fermentation of carbohydrates, such as dietary fibre in the large bowel. The genes encoding butyryl‐CoA dehydrogenase (BCD) and butyryl‐CoA:acetate CoA transferase (BUT) in F. prausnitzii were cloned and expressed in E. coli to determine the effect of butyric acid production on intestinal health using DSS‐induced colitis model mice. The results from the E. coli Nissle 1917 strain, expressing BCD, BUT, or both, showed that BCD was essential, while BUT was dispensable for producing butyric acid. The effects of different carbon sources, such as glucose, N‐acetylglucosamine (NAG), N‐acetylgalactosamine (NAGA), and inulin, were compared with results showing that the optimal carbon sources for butyric acid production were NAG, a major component of mucin in the human intestine, and glucose. Furthermore, the anti‐inflammatory effects of butyric acid production were tested by administering these strains to DSS‐induced colitis model mice. The oral administration of the E. coli Nissle 1917 strain, carrying the expression vector for BCD and BUT (EcN‐BCD‐BUT), was found to prevent DSS‐induced damage. Introduction of the BCD expression vector into E. coli Nissle 1917 led to increased butyric acid production, which improved the strain’s health‐beneficial effects.

PURPOSE This study aims to analyze research trends on the social capital in sports. METHODS A total of 69 papers published until December 2020 were selected as research subjects. Further, Excel, KrKwic software, and NetDraw function of the UCINET 6 program were used for analysis. RESULTS First, social capital research on sports has shown quantitative growth since 2010. Second, the studies were conducted on sports participants such as general, elderly, college students, adolescents, foreigners, and the disabled, showing the highest frequency of research subjects. Third, quantitative research conducted based on the research method were several. Fourth, single-author studies were the highest. Fifth, as the result of the analysis on the publication journal, the Journal of the Korean Physical Education Association was shown the highest. Sixth, due to frequency analysis of the thesis keywords, “social capital,” “sports participation,” “action intention,” “social capital type,” “living sports participation,” and “youth” were shown the highest. Seventh, as a result of centrality analysis between keywords through the network analysis, “sports participation” in connection centrality, “health-promoting lifestyle” in proximity centrality, and “sports participation” in mediation centrality were found as the highest. CONCLUSIONS The significance of social capital in sports is more important than others because it is a fundamental element for creating a culture where more people can enjoy sports moderately in Korea, where capitalism and liberal democracy were adopted as the governing system. Therefore, this study can be a vital resource significantly contributing to the understanding and active use of social capital, a significant factor in developing sports in Korea.

Background: Lung cancer has a high incidence worldwide, and most lung cancer-associated deaths are attributable to cancer metastasis. Although several medicinal properties of Panax ginseng Meyer have been reported, the effect of ginsenosides Rk1 and Rg5 on epithelial-mesenchymal transition (EMT) stimulated by transforming growth factor beta 1 (TGF- β1) and self-renewal in A549 cells is relatively unknown. Methods: We treated TGF-β1 or alternatively Rk1 and Rg5 in A549 cells. We used western blot analysis, real-time polymerase chain reaction (qPCR), wound healing assay, Matrigel invasion assay, and anoikis assays to determine the effect of Rk1 and Rg5 on TGF-mediated EMT in lung cancer cell. In addition, we performed tumorsphere formation assays and real-time PCR to evaluate the stem-like properties. Results: EMT is induced by TGF-β1 in A549 cells causing the development of cancer stem-like features. Expression of E-cadherin, an epithelial marker, decreased and an increase in vimentin expression was noted. Cell mobility, invasiveness, and anoikis resistance were enhanced with TGF-β1 treatment. In addition, the expression of stem cell markers, CD44, and CD133, was also increased. Treatment with Rk1 and Rg5 suppressed EMT by TGF-β1 and the development of stemness in a dose-dependent manner. Additionally, Rk1 and Rg5 markedly suppressed TGF-β1-induced metalloproteinase-2/9 (MMP2/9) activity, and activation of Smad2/3 and nuclear factor kappa B/extra-cellular signal regulated kinases (NF-kB/ERK) pathways in lung cancer cells. Conclusions: Rk1 and Rg5 regulate the EMT inducing TGF-β1 by suppressing the Smad and NF-κB/ERK pathways (non-Smad pathway).

This paper proposes a new approach to small-object change detection from high-resolution satellite images. We propose using feature points that can be quickly extracted from satellite images as a suitable unit of change for small objects and to reduce false alarms. We can perform feature-based change detection by extracting features from previous and recent images and by estimating change based on change magnitude of the features. We estimate the magnitude by calculating pixel-based change magnitude, and counting the ratio of changed pixels around the extracted features. We apply feature matching and determine matched features as unchanged ones. The remaining feature points are judged as changed or unchanged based on their change magnitude. We tested our approach with three Kompsat-3A image sets with a ground sampling distance of 50 cm. We showed that our approach outperformed the pixel-based approach by producing a higher precision of 88.7% and an accuracy of 86.1% at a fixed false alarm rate of 10%. Our approach is unique in the sense that the feature-based approach applying computer vision methods is newly proposed for change detection. We showed that our feature-based approach was less noisy than pixel-based approaches. We also showed that our approach could compensate for the disadvantages of supervised object-based approaches by successfully reducing the number of change candidates. Our approach, however, could not handle featureless objects, and may increase the number of undetected objects. Future studies will handle this issue by devising more intelligent schemes for merging pixel-based and feature-based change detection results.

In the present study, a nozzle was used to improve the flow performance of an intake manifold, and its effects on the automobile engine output and the exhaust gas were experimentally studied. It was found that the engine output of a vehicle with a mileage of 30,000 km increased by 4.7% and 6.5% when nozzles with diameters of 5 and 2.5 mm were used. In addition, the engine output of a vehicle with a mileage of 180,000 km increased by 3.3% and 13.3% when nozzles with diameters of 5 and 2.5 mm were used compared to those of the same vehicle when no nozzle was used. Thus, using a nozzle for the inflow of outside air created a uniform combustion environment to improve the engine output and reduce harmful exhaust gases, such as hydrocarbon, carbon monoxide, and nitrogen oxides, by generating vortexes inside the intake manifold and increasing the degree of mixing. Furthermore, the smaller nozzle with a diameter of 2.5 mm had greater effects.

Junction networks made of longitudinally connected metal oxide nanowires (MOx NWs) have been widely utilized in resistive-type gas sensors because the potential barrier at the NW junctions leads to improved gas sensing performances. However, conventional MOx–NW-based gas sensors exhibit limited gas access to the sensing sites and reduced utilization of the entire NW surfaces because the NW networks are grown on the substrate. This study presents a novel gas sensor platform facilitating the formation of ZnO NW junction networks in a suspended architecture by growing ZnO NWs radially on a suspended carbon mesh backbone consisting of sub-micrometer-sized wires. NW networks were densely formed in the lateral and longitudinal directions of the ZnO NWs, forming additional longitudinally connected junctions in the voids of the carbon mesh. Therefore, target gases could efficiently access the sensing sites, including the junctions and the entire surface of the ZnO NWs. Thus, the present sensor, based on a suspended network of longitudinally connected NW junctions, exhibited enhanced gas response, sensitivity, and lower limit of detection compared to sensors consisting of only laterally connected NWs. In addition, complete sensor structures consisting of a suspended carbon mesh backbone and ZnO NWs could be prepared using only batch fabrication processes such as carbon microelectromechanical systems and hydrothermal synthesis, allowing cost-effective sensor fabrication.

Recently, the mapping industry has been focusing on the possibility of large-scale mapping from unmanned aerial vehicles (UAVs) owing to advantages such as easy operation and cost reduction. In order to produce large-scale maps from UAV images, it is important to obtain precise orientation parameters as well as analyzing the sharpness of they themselves measured through image analysis. For this, various techniques have been developed and are included in most of the commercial UAV image processing software. For mapping, it is equally important to select images that can cover a region of interest (ROI) with the fewest possible images. Otherwise, to map the ROI, one may have to handle too many images, and commercial software does not provide information needed to select images, nor does it explicitly explain how to select images for mapping. For these reasons, stereo mapping of UAV images in particular is time consuming and costly. In order to solve these problems, this study proposes a method to select images intelligently. We can select a minimum number of image pairs to cover the ROI with the fewest possible images. We can also select optimal image pairs to cover the ROI with the most accurate stereo pairs. We group images by strips and generate the initial image pairs. We then apply an intelligent scheme to iteratively select optimal image pairs from the start to the end of an image strip. According to the results of the experiment, the number of images selected is greatly reduced by applying the proposed optimal image–composition algorithm. The selected image pairs produce a dense 3D point cloud over the ROI without any holes. For stereoscopic plotting, the selected image pairs were map the ROI successfully on a digital photogrammetric workstation (DPW) and a digital map covering the ROI is generated. The proposed method should contribute to time and cost reductions in UAV mapping.

The combustion performance of a conventional rail diesel engine was investigated by measuring the exhaust gas with the respect to the number of injector holes, fuel type, and the use of exhaust gas recirculation (EGR), to provide a detailed reduction of environmental pollutants. It was found that a six- or seven-hole injector was more effective than a five-hole injector for reducing the exhaust gas. In addition, the mixing of 20% biodiesel oil with diesel most effectively reduced the HC and NOx contents. The technology generally reduced the NOx and CO contents of the exhaust, but had no significant effect on the HC and CO2 contents.

As the use of unmanned aerial vehicle (UAV) images rapidly increases so does the need for precise radiometric calibration. For UAV images, relative radiometric calibration is required in addition to the traditional vicarious radiometric calibration due to the small field of view. For relative radiometric calibration, some UAVs install irradiance sensors, but most do not. For UAVs without them, an intelligent scheme for relative radiometric calibration must be applied. In this study, a relative radiometric calibration method is proposed to improve the quality of a reflectance map without irradiance measurements. The proposed method, termed relative calibration by the optimal path (RCOP), uses tie points acquired during geometric calibration to define the optimal paths. A calibrated image from RCOP was compared to validation data calibrated with irradiance measurements. As a result, the RCOP method produces seamless mosaicked images with uniform brightness and reflectance patterns. Therefore, the proposed method can be used as a precise relative radiometric calibration method for UAV images.

This paper proposes a robust feature-based mosaicking method that can handle images obtained by lightweight unmanned aerial vehicles (UAVs). The imaging geometry of small UAVs can be characterized by unstable flight attitudes and low flight altitudes. These can reduce mosaicking performance by causing insufficient overlaps, tilted images, and biased tiepoint distributions. To solve these problems in the mosaicking process, we introduce the tiepoint area ratio (TAR) as a geometric stability indicator and orthogonality as an image deformation indicator. The proposed method estimates pairwise transformations with optimal transformation models derived by geometric stability analysis between adjacent images. It then estimates global transformations from optimal pairwise transformations that maximize geometric stability between adjacent images and minimize mosaic deformation. The valid criterion for the TAR in selecting an optimal transformation model was found to be about 0.3 from experiments with two independent image datasets. The results of a performance evaluation showed that the problems caused by the imaging geometry characteristics of small UAVs could actually occur in image datasets and showed that the proposed method could reliably produce image mosaics for image datasets obtained in both general and extreme imaging environments.

This paper investigates the positioning accuracy of image pairs achieved by integrating images from multiple satellites. High-resolution satellite images from IKONOS, QuickBird, and KOMPSAT-2 for Daejeon, Korea were combined to produce pairs of stereo images. From single-satellite stereo pairs to multiple-satellite image pairs, all available combinations were analyzed via a rational function model (RFM). The positioning accuracy of multiple-satellite pairs was compared to a typical single-satellite stereo pair. The results show that dual-satellite integration can be an effective alternative to single-satellite stereo imagery for horizontal position mapping, but is less accurate for vertical mapping. The integration of additional higher-resolution images can improve the overall accuracy of the existing two images, but, conversely, may result in lower accuracy when very weak convergence or bisector elevation (BIE) angles occur. This highlights that the use of higher resolution images may not ensure improved accuracy, as it can result in very weak geometry. The findings confirm that multiple-satellite images can replace or enhance typical stereo pairs, but also suggest the need for careful verification, including consideration of various geometric elements and image resolution. This paper reveals the potential, limitations, and important considerations for mapping applications using images from multiple satellites.

In this study, we demonstrated the efficient structural conversion of ginsenosides, which enhances the anticancer activity of ginseng by microwave irradiation. The microwave-irradiated product of ginseng (MG) had a higher content of ginsenosides, Rg3+Rg5+Rk1, particularly Rg5 and Rk1, and, thus, has an increased medicinal effect. To confirm the anticancer effect of MG, it was tested in 5 human cancer cell lines (cervical cancer HeLa, gastric cancer AGS, colon cancer HCT-116, lung cancer A549, and liver cancer HepG2 cells). Anti-proliferation results for 5 human cancer cell lines treated with ginseng extracts indicate that HeLa cells treated with MG showed the highest activity with an IC50 value of 130.1 µg/mL. MG also suppressed the growth of human cervical cancer cell xenografts in athymic nude mice as an in vivo model. This growth suppression by MG is associated with the induction of cell death and autophagy. Moreover, there were no toxic sign or decrease in renal and hepatic function in mice administered with MG. Therefore, heat processing by microwave irradiation is a useful method to enhance the anticancer effect of ginseng as it increases the content of ginsenosides, Rg3, Rg5, and Rk1.

Insulin plays a key role in glucose homeostasis and is hence used to treat hyperglycemia, the main characteristic of diabetes mellitus. Annulohypoxylon annulatum is an inedible ball-shaped wood-rotting fungus, and hypoxylon F is one of the major compounds of A. annulatum. The aim of this study is to evaluate the effects of hypoxylonol F isolated from A. annulatum on insulin secretion in INS-1 pancreatic β-cells and demonstrate the molecular mechanisms involved. Glucose-stimulated insulin secretion (GSIS) values were evaluated using a rat insulin ELISA kit. Moreover, the expression of proteins related to pancreatic β-cell metabolism and insulin secretion was evaluated using Western blotting. Hypoxylonol F isolated from A. annulatum was found to significantly enhance glucose-stimulated insulin secretion without inducing cytotoxicity. Additionally, hypoxylonol F enhanced insulin receptor substrate-2 (IRS-2) levels and activated the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway. Interestingly, it also modulated the expression of peroxisome proliferator-activated receptor γ (PPARγ) and pancreatic and duodenal homeobox 1 (PDX-1). Our findings showed that A. annulatum and its bioactive compounds are capable of improving insulin secretion by pancreatic β-cells. This suggests that A. annulatum can be used as a therapeutic agent to treat diabetes.

Techniques for measuring the position and orientation of an object from corresponding images are based on the principles of epipolar geometry in the computer vision and photogrammetric fields. Contributing to their importance, many different approaches have been developed in computer vision, increasing the automation of the pure photogrammetric processes. The aim of this paper is to evaluate the main differences between photogrammetric and computer vision approaches for the pose estimation of an object from image sequences, and how these have to be considered in the choice of processing technique when using a single camera. The use of a single camera in consumer electronics has enormously increased, even though most 3D user interfaces require additional devices to sense 3D motion for their input. In this regard, using a monocular camera to determine 3D motion is unique. However, we argue that relative pose estimations from monocular image sequences have not been studied thoroughly by comparing both photogrammetry and computer vision methods. To estimate motion parameters characterized by 3D rotation and 3D translations, estimation methods developed in the computer vision and photogrammetric fields are implemented. This paper describes a mathematical motion model for the proposed approaches, by differentiating their geometric properties and estimations of the motion parameters. A precision analysis is conducted to investigate the main characteristics of the methods in both fields. The results of the comparison indicate the differences between the estimations in both fields, in terms of accuracy and the test dataset. We show that homography-based approaches are more accurate than essential-matrix or relative orientation–based approaches under noisy conditions.

An extract of the red alga, Neorhodomela aculeata, exhibited antiviral activity against human rhinoviruses. Bioassay-guided purification was performed to yield six compounds, which were subsequently identified as lanosol (1) and five polybromocatechols (2–6) by spectroscopic methods, including 1D and 2D NMR and mass spectrometric analyses. Structurally, all of these compounds, except compound 5, contain one or two 2,3-dibromo-4,5-dihydroxyphenyl moieties. In a biological activity assay, compound 1 was found to possess antiviral activity with a 50% inhibitory concentration (IC50) of 2.50 μg/mL against HRV2. Compound 3 showed anti-HRV2 activity, with an IC50 of 7.11 μg/mL, and anti-HRV3 activity, with an IC50 of 4.69 μg/mL, without demonstrable cytotoxicity at a concentration of 20 μg/mL. Collectively, the results suggest that compounds 1 and 3 are candidates for novel therapeutics against two different groups of human rhinovirus.

One of the important image processing technologies is visual odometry (VO) technology. VO estimates platform motion through a sequence of images. VO is of interest in the virtual reality (VR) industry as well as the automobile industry because the construction cost is low. In this study, we developed stereo visual odometry (SVO) based on photogrammetric geometric interpretation. The proposed method performed feature optimization and pose estimation through photogrammetric bundle adjustment. After corresponding the point extraction step, the feature optimization was carried out with photogrammetry-based and vision-based optimization. Then, absolute orientation was performed for pose estimation through bundle adjustment. We used ten sequences provided by the Karlsruhe institute of technology and Toyota technological institute (KITTI) community. Through a two-step optimization process, we confirmed that the outliers, which were not removed by conventional outlier filters, were removed. We also were able to confirm the applicability of photogrammetric techniques to stereo visual odometry technology.

A digital surface model (DSM) is an important geospatial infrastructure used in various fields. In this paper, we deal with how to improve the quality of DSMs generated from stereo image matching. During stereo image matching, there are outliers due to mismatches, and non-matching regions due to match failure. Such outliers and non-matching regions have to be corrected accurately and efficiently for high-quality DSM generation. This process has been performed by applying a local distribution model, such as inverse distance weight (IDW), or by forming a triangulated irregular network (TIN). However, if the area of non-matching regions is large, it is not trivial to interpolate elevation values using neighboring cells. In this study, we proposed a new DSM interpolation method using a 3D mesh model, which is more robust to outliers and large holes. We compared mesh-based DSM with IDW-based DSM and analyzed the characteristics of each. The accuracy of the mesh-based DSM was a 2.80 m root mean square error (RMSE), while that for the IDW-based DSM was 3.22 m. While the mesh-based DSM successfully removed empty grid cells and outliers, the IDW-based DSM had sharper object boundaries. Because of the nature of surface reconstruction, object boundaries appeared smoother on the mesh-based DSM. We further propose a method of integrating the two DSMs. The integrated DSM maintains the sharpness of object boundaries without significant accuracy degradation. The contribution of this paper is the use of 3D mesh models (which have mainly been used for 3D visualization) for efficient removal of outliers and non-matching regions without a priori knowledge of surface types.

Geometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when the shoreline is absent. In this study, we develop a hybrid geometric correction method, which applies shoreline matching and frequency matching on slots with shorelines and without shorelines, respectively. Frequency matching has been proposed to estimate the relative orientation between GOCI slots without a shoreline. In this paper, we extend our earlier research for absolute orientation and geometric correction by combining frequency matching results with shoreline matching ones. The proposed method consists of four parts: Initial sensor modeling of slots without shorelines, precise sensor modeling through shoreline matching, relative orientation modeling by frequency matching, and generation of geometric correction results using a combination of the two matching procedures. Initial sensor modeling uses the sensor model equation for GOCI and metadata in order to remove geometric distortion due to the Earth’s rotation and curvature in the slots without shorelines. Precise sensor modeling is performed with shoreline matching and random sample consensus (RANSAC) in the slots with shorelines. Frequency matching computes position shifts for slots without shorelines with respect to the precisely corrected slots with shorelines. GOCI Level 1B scenes are generated by combining the results from shoreline matching and frequency matching. We analyzed the accuracy of shoreline matching alone against that of the combination of shoreline matching and frequency matching. Both methods yielded a similar accuracy of 1.2 km, which supports the idea that frequency matching can replace traditional shoreline matching for slots without visible shorelines.

Thc CCD earth image experiment(CEIE) is one of the main payload of the KITSAT-1. Since it was launched on Age. 11, 1992, the CEIE has taken more than 500 images on the earth surface world-wide so far. An image from the space is very different from a feature on the real Earth surface due to various radiometric and geometric distortions. Preprocessing to remove those distortions has to take place before the image data are processed and analyzed further for various applications. This paper summarizes the result of the operation of the CEIE and describes the procedure to perform preprocessing including radiometric and geometric correction.

Epipolar resampling is the procedure of eliminating vertical disparity between stereo images. Due to its importance, many methods have been developed in the computer vision and photogrammetry field. However, we argue that epipolar resampling of image sequences, instead of a single pair, has not been studied thoroughly. In this paper, we compare epipolar resampling methods developed in both fields for handling image sequences. Firstly we briefly review the uncalibrated and calibrated epipolar resampling methods developed in computer vision and photogrammetric epipolar resampling methods. While it is well known that epipolar resampling methods developed in computer vision and in photogrammetry are mathematically identical, we also point out differences in parameter estimation between them. Secondly, we tested representative resampling methods in both fields and performed an analysis. We showed that for epipolar resampling of a single image pair all uncalibrated and photogrammetric methods tested could be used. More importantly, we also showed that, for image sequences, all methods tested, except the photogrammetric Bayesian method, showed significant variations in epipolar resampling performance. Our results indicate that the Bayesian method is favorable for epipolar resampling of image sequences.

We establish the non-commutative analogue of Grothendieck's standard conjecture D for the differential graded category of G-equivariant matrix factorizations associated to an isolated hypersurface singularity where G is a finite group. [ABSTRACT FROM AUTHOR]