• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.772-778
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• 2022

Objective : Endovascular treatment of large, wide-necked intracranial aneurysms by coil embolization is often complicated by low rates of complete occlusion and high rates of recurrence. A flow diverter device has been shown to be safe and effective for the treatment of not only large and giant unruptured aneurysms, but small and medium aneurysms. However, in Korea, its use has only recently been approved for aneurysms <10 mm. This study aims to compare the safety and efficacy of flow diversion and coil embolization for the treatment of unruptured aneurysms ≥7 mm. Methods : The participants will include patients aged between 19 and 75 years to be treated for unruptured cerebral aneurysms ≥7 mm for the first time or for recurrent aneurysms after initial endovascular coil embolization. Participants assigned to a flow diversion cohort will be treated using any of the following devices : Pipeline Flex Embolization Device with Shield Technology (Medtronic, Minneapolis, MN, USA), Surpass Evolve (Stryker Neurovascular, Fremont, CA, USA), and FRED or FRED Jr. (MicroVention, Tustin, CA, USA). Participants assigned to a coil embolization cohort will undergo traditional endovascular coiling. The primary endpoint will be complete occlusion confirmed by cerebral angiography at 12 months after treatment. Secondary safety outcomes will evaluate periprocedural and post-procedural complications for up to 12 months. Results : The trial will begin enrollment in 2022, and clinical data will be available after enrollment and follow-up. Conclusion : This article describes the aim and design of a multi-center, randomized, open-label trial to compare the safety and efficacy of flow diversion versus traditional endovascular treatment for unruptured cerebral aneurysms ≥7 mm.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3855-3863
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• 2022

An evaluation of the radiation shielding performance of high-Z-particle-loaded polylactic acid (PLA) composite materials was pursued. Specimens were produced via fused deposition modeling (FDM) using copper-PLA, steel-PLA, and BaSO₄-PLA composite filaments containing 82.7, 75.2, and 44.6 wt% particulate phase contents, respectively, and were tested under broad-band flash x-ray conditions at the Sandia National Laboratories HERMES III facility. The experimental results for the mass attenuation coefficients of the composites were found to be in good agreement with GEANT4 simulations carried out using the same exposure conditions and an atomistic mixture as a model for the composite materials. Further simulation studies, focusing on the Cu-PLA composite system, were used to explore a shield design parameter space (in this case, defined by Cu-particle loading and shield areal density) to assess performance under both high-energy photon and electron fluxes over an incident energy range of 0.5-15 MeV. Based on these results, a method is proposed that can assist in the visualization and isolation of shield parameter coordinate sets that optimize performance under targeted radiation characteristics (type, energy). For electron flux shielding, an empirical relationship was found between areal density (AD), electron energy (E), composition and performance. In cases where ${\frac{E}{AD}}{\geq}2MeV{\bullet}cm{\bullet}g^{-1}$, a shield composed of >85 wt% Cu results in optimal performance. In contrast, a shield composed of <10 wt% Cu is anticipated to perform best against electron irradiation when ${\frac{E}{AD}}<2MeV{\bullet}cm{\bullet}g^{-1}$.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.509-517
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• 2021

Background and objective: Problems currently occurred in the environment are caused by a lack of environmental awareness of the community. Biology students learn the environment in ecological learning. Students must explore environmental knowledge (EK) and are expected to have high environmental awareness (EA) and then apply their knowledge in daily life with pro-environmental behavior (PEB). There is a need for designing climate-change book serials for university students (CCBS-US) towards contextualized learning. This study aimed to determine the relationship between EK and EA and the PEB of biology students as a baseline for designing CCBS-US. Methods: The study used a quantitative descriptive method with a correlational design. Total 136 biology students from a state university in Jakarta, Indonesia served as samples of the study. Results: Research results revealed a positive relationship between EK and PEB of biology students. There was a positive relationship between EA and PEB of biology students and between EK and EA and PEB of Biology students. Moreover, 77% of students reported their EK is very high, 55% of students reported their EA is medium, and 46% of students reported their PEB is medium. Ecological learning has a vital role in shaping the EK, EA, and PEB, thus CCBS-US needs to be developed. Conclusion: The study concluded that there was a relationship between EK, EA, and PEB. The study recommends the development of CCBS-US based on the survey results.

• Journal of the Korean Wood Science and Technology
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• v.32 no.5
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• pp.59-65
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• 2004

The present study aims to optimise the process parameters of fish glue and adhesion property through room temperature in terms of curing time and opened assembly time for attaining best adhesion strength to wood (Yellow birch, B. alleghaniensis). The uncured and cured fish glue have been characterised by TGA, DSC, FT-JR. It is observed that with increasing curing time up to 48 H, tensile lap shear strength of adhesive joint of fish glue to wood increases and decreases after 48 H. At 15 min. opened assembly time, lap shear strength increases up to 4833 kgf/cm² and decreases after 15 min.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• Archives of Plastic Surgery
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• v.49 no.2
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• pp.166-173
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• 2022

The introduction of acellular dermal matrix (ADM) to breast reconstruction has allowed surgeons to reexplore the prepectoral implant placement technique in postmastectomy breast reconstruction. Our institution adopted a novel approach using meshed ADM to lessen the financial burden of increased ADM utilization with the prepectoral breast reconstruction. This is a retrospective, single-center review of two-stage prepectoral breast reconstruction using meshed human-derived ADM for anterior prosthesis coverage. Patient demographics, oncologic data, perioperative characteristics, and complications were examined and reported as means with standard deviations. Cost-saving with the meshed technique was evaluated. Forty-eight patients (72 breasts) with a mean age of 48.5 ± 15.0 years (range 26-70 years) were included in the study. The mean follow-up time was 13.2 ± 4.4 months (range 4.1-25.8 months). Nineteen breasts (24.6%) experienced complications, with seromas being the most common complication (12.5%, n = 9). Expander removal and reoperation occurred at a rate of 8.3 and 9.7%, respectively. The average time to drain removal was 18.8 ± 6.6 days (range 8-32 days). Meshed ADM provided an average cost savings of $6,601 for unilateral and $13,202 for bilateral reconstructions. Our study found that human-derived meshed ADM can be safely used in two-staged prepectoral tissue expander-based breast reconstruction and can result in significant cost savings.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.170-178
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• 2022

A high-performing Earned Value Management System (EVMS) can influence project success and help stakeholders meet project objectives. Although EVMS processes are well-supported by technical guidelines and standards, project managers often face challenges related to the project culture, team, resources, and business practices that make up the project environment within which an EVMS is being used. A comprehensive literature review revealed a lack of a data-driven and consistent assessment frameworks that can gauge the environment surrounding EVMS implementation. This paper will discuss the EVMS environment of construction and environmental projects, and examine its impact on cost performance. The authors used a multi-method approach to identify 27 environment factors that make up the EVMS environment, assessing them on 18 construction and environmental projects worth over $2 billion of total cost. Research methods employed include: (1) a literature review of more than 300 references; (2) a survey of 294 respondents; and (3) remote research charrettes with more than 60 participating expert practitioners. Culture (one of the identified environment categories) was found to be relatively more important in terms of its impact on the EVMS environment, followed by people, practices, and resources. These exploratory results show statistically significant differences in cost performance between completed projects with either a good or poor environment, for the sample projects. Key environment factors are outlined, and guidance is provided to practitioners around how to set up an effective EVMS environment in a construction or environmental project to inform decision-making and support achieving the project cost objectives successfully.

• ALGAE
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• v.37 no.4
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• pp.249-264
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• 2022

Two genera of the Rhodymeniales, Halopeltis and Leptofauchea, are here reported for the first time from the Hawaiian Islands and represent the deepest records for both genera. Molecular phylogenetic analyses of cytochrome oxidase subunit I (COI), rbcL, and large subunit ribosomal DNA (LSU) sequences for Hawaiian specimens of Leptofauchea revealed one well-supported clade of Hawaiian specimens and three additional lineages. One of these clades is described here as Leptofauchea huawelau sp. nov., and is thus far known only from mesophotic depths at Penguin Bank in the Main Hawaiian Islands. L. huawelau sp. nov. is up to 21 cm, and is the largest known species. An additional lineage identified in the LSU and rbcL analyses corresponds to the recently described L. lucida from Western Australia, and is a new record for Hawai'i. Hawaiian Halopeltis formed a well-supported clade along with H. adnata from Korea, the recently described H. tanakae from mesophotic depths in Japan, and H. willisii from North Carolina, and is here described as Halopeltis nuahilihilia sp. nov. H. nuahilihilia sp. nov. has a distinctive morphology of narrow vegetative axes that harbor constrictions along their length. The current distribution of H. nuahilihilia includes mesophotic depths around W. Maui, W. Moloka'i, and the island of Hawai'i in the Main Hawaiian Islands. Few reproductive characters were observed because of the small number of specimens available; however, both species are distinct based on phylogeny and morphology. These descriptions further emphasize the Hawaiian mesophotic zone as a location harboring many undescribed species of marine macroalgae.

• Genomics & Informatics
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• v.21 no.1
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• pp.4.1-4.18
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• 2023

Coronavirus disease 2019 (COVID-19) is an inflammatory and infectious disease caused by severe acute respiratory syndrome coronavirus 2 virus with a complex pathophysiology. While COVID-19 vaccines and boosters are available, treatment of the disease is primarily supportive and symptomatic. Several research have suggested the potential of herbal medicines as an adjunctive treatment for the disease. A popular herbal medicine approved in the Philippines for the treatment of acute respiratory disease is Vitex negundo L. In fact, the Department of Science and Technology of the Philippines has funded a clinical trial to establish its potential as an adjunctive treatment for COVID-19. Here, we utilized network pharmacology and molecular docking in determining pivotal targets of Vitex negundo compounds against COVID-19. The results showed that significant targets of Vitex negundo compounds in COVID-19 are CSB, SERPINE1, and PLG which code for cathepsin B, plasminogen activator inhibitor-1, and plasminogen, respectively. Molecular docking revealed that α-terpinyl acetate and geranyl acetate have good binding affinity in cathepsin B; 6,7,4-trimethoxyflavanone, 5,6,7,8,3',4',5'-heptamethoxyflavone, artemetin, demethylnobiletin, gardenin A, geranyl acetate in plasminogen; and 7,8,4-trimethoxyflavanone in plasminogen activator inhibitor-1. While the results are promising, these are bound to the limitations of computational methods and further experimentation are needed to completely establish the molecular mechanisms of Vitex negundo against COVID-19.