• Steel and Composite Structures
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• v.45 no.1
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• pp.133-145
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• 2022

Steel fiber composite bar (SFCB) is a novel type of reinforcement, which has good ductility and durability performance. Due to the unique pseudo strain hardening tensile behavior of SFCB, different flexural behavior is expected of SFCB reinforced concrete (SFCB-RC) beams from traditional steel bar reinforced concrete (S-RC) beams and FRP bar reinforced concrete (F-RC) beams. To investigate the flexural behavior of SFCB-RC beam, four points bending tests were carried out and different flexural behaviors between S/F/SFCB-RC beams were discussed. An flexural analytical model of SFCB-RC beams is proposed and proved by the current and existing experimental results. Based on the proposed model, the influence of the fiber volume ratio R of the SFCB on the flexural behavior of SFCB-RC beams is discussed. The results show that the proposed model is effective for all S/F/SFCB-RC flexural members. Fiber volume ratio R is a key parameter affecting the flexural behavior of SFCB-RC. By controlling the fiber volume ratio of SFCB reinforcements, the flexural behavior of the SFCB-RC flexural members such as bearing capacity, bending stiffness, ductility and repairability of SFCB-RC structures can be designed.

• Smart Structures and Systems
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• v.30 no.5
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• pp.479-500
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• 2022

In this study, a new type of isolation bearing is proposed by combining S-shaped steel plate dampers (SSDs) with a spherical steel bearing, and the seismic control effect of a five-span standard high-speed railway bridge is investigated. The advantages of the proposed S-shaped steel damping friction bearing (SSDFB) are that it cannot only lengthen the structural periods, dissipate the seismic energy, but also prevent bridge unseating due to the restraint effectiveness of SSDs in the large relative displacements between the girders and piers. This study first presents a detailed description and working principle of the SSDFB. Then, mechanical modeling of the SSDFB was derived to fundamentally define its cyclic behavior and obtain key mechanical parameters. The numerical model of the SSDFB's critical component SSD was verified by comparing it with the experimental results. After that, parameter studies of the dimensions and number of SSDs, the friction coefficient, and the gap length of the SSDFBs were conducted. Finally, the longitudinal seismic responses of the bridge with SSDFBs were compared with the bridge with spherical bearing and spherical bearing with strengthened shear keys. The results showed that the SSDFB can not only significantly mitigate the shear force responses and residual displacement in bridge substructures but also can effectively reduce girder displacement and prevent bridge unseating, at a cost of inelastic deformation of the SSDs, which is easy to replace. In conclusion, the SSDFB is expected to be a cost-effective option with both multi-stage energy dissipation and restraint capacity, making it particularly suitable for seismic isolation application to high-speed railway bridges.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.302-314
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• 2023

PURPOSE. The aim of this study was to classify the shapes of retromolar pads and assess their morphometric differences using a 3D model. MATERIALS AND METHODS. Two hundred fully edentulous or Kennedy Class I partially edentulous patients (400 retromolar pads) were enrolled. Scan data of the definitive mandibular casts produced through functional impressions were obtained using a 3D laser scanner. Seven parameters (transverse diameter, longitudinal diameter, transverse-contour length, longitudinal-contour length, longitudinal/transverse diameter ratio, longitudinal/transverse-contour length ratio, and angle of the retromolar pad line to the residual alveolar ridge line) were measured using image analysis software. Subsequently, the pads were classified according to the shape. Statistical analyses were performed using 95% confidence intervals. RESULTS. Classifying the retromolar pads into three shapes led to high intra-examiner reliability (Cronbach's alpha = 0.933). The pear shape was the most common (56.5%), followed by oval/round (27.7%) and triangular (15.8%) shapes. There were no significant differences between the left and right sides according to the shape and no significant differences in any parameter according to age. The transverse diameter and longitudinal/transverse diameter ratio differed between sexes (P < .05). The triangular shape had a significantly different transverse diameter, transverse-contour length, longitudinal/transverse diameter ratio, and longitudinal/transverse-contour length ratio compared with the pear and oval/round shapes (P < .05). CONCLUSION. From a clinical reliability standpoint, classifying retromolar pads into three shapes (oval/round, pear-shaped, and triangular) is effective. The differences in the sizes among the shapes were attributed to the transverse measurement values.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Journal of the Korean Society for Heat Treatment
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• v.36 no.6
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• pp.382-388
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• 2023

In this study, hydrogen embrittlement (HE) behavior of a SA-723 steel via controlling gaseous hydrogen pre-charging condition has been analyzed. The gaseous hydrogen charging of the SA-723 steel was performed under a constant pressure of 20 MPa of gaseous H₂ at 150℃ and 300℃ for 2 and 6h, and TDS, SSRT and Charpy tests were conducted to analyze the hydrogen embrittlement (HE) behavior of the SA-723 steel. Furthermore, prior to commencing the test, these specimens were coated with Zn to prevent hydrogen from diffusing out of a specimen during the tests. The TDS results showed that the 300℃-6h and 150℃-6h charged steels contain larger amounts of hydrogen than 300℃-2h and 150℃-2h charged steel. The SSRT and Charpy test results also showed the similar trends that the mechanical properties of the steels deteriorate as the amount of hydrogen charged in the steel increases. Therefore, this study suggests that, for SA-723 steel, the charging time parameter is more effective to charge more amount of hydrogen into SA-723 steel, rather than the charging temperature.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.759-769
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• 2021

Objective: To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. Materials and Methods: This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), return-to-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. Results: The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). Conclusion: MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.

• Steel and Composite Structures
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• v.51 no.1
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• pp.73-91
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• 2024

This paper has focused on presenting vibration analysis of trapezoidal sandwich plates with a damaged core and FG wavy CNT-reinforced face sheets. A damage model is introduced to provide an analytical description of an irreversible rheological process that causes the decay of the mechanical properties, in terms of engineering constants. An isotropic damage is considered for the core of the sandwich structure. The classical theory concerning the mechanical efficiency of a matrix embedding finite length fibers has been modified by introducing the tube-to-tube random contact, which explicitly accounts for the progressive reduction of the tubes' effective aspect ratio as the filler content increases. The First-order shear deformation theory of plate is utilized to establish governing partial differential equations and boundary conditions for the trapezoidal plate. The governing equations together with related boundary conditions are discretized using a mapping-generalized differential quadrature (GDQ) method in spatial domain. Then natural frequencies of the trapezoidal sandwich plates are obtained using GDQ method. Validity of the current study is evaluated by comparing its numerical results with those available in the literature. After demonstrating the convergence and accuracy of the method, different parametric studies for laminated trapezoidal structure including carbon nanotubes waviness (0≤w≤1), CNT aspect ratio (0≤AR≤4000), face sheet to core thickness ratio (0.1 ≤ ${\frac{h_f}{h_c}}$ ≤ 0.5), trapezoidal side angles (30° ≤ α, β ≤ 90°) and damaged parameter (0 ≤ D < 1) are carried out. It is explicated that the damaged core and weight fraction, carbon nanotubes (CNTs) waviness and CNT aspect ratio can significantly affect the vibrational behavior of the sandwich structure. Results show that by increasing the values of waviness index (w), normalized natural frequency of the structure decreases, and the straight CNT (w=0) gives the highest frequency. For an overall comprehension on vibration of laminated trapezoidal plates, some selected vibration mode shapes were graphically represented in this study.

• Journal of Veterinary Science
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• v.25 no.4
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• pp.58.1-58.8
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• 2024

Importance: Over the past decade, catfish farming has increased in Southeast Asia. However, there has been no existing for pharmacokinetic data in the hybrid catfish (Clarias macrocephalus x C. gariepinus). Objective: This study was designed to evaluate the pharmacokinetic characteristics of oxytetracycline (OTC) in the hybrid catfish, following single intravascular (IV) or oral (PO) administration at a single dosage of 50 mg/kg body weight (BW). Methods: In total, 140 catfish (each about 100-120 g BW) were divided into two groups (n = 70). Blood samples (0.6-0.8 mL) were collected from ventral caudal vein at pre-assigned times up to 144 h (sparse samples design). OTC plasma concentrations were analyzed using high-performance liquid chromatography-photodiode array detector. Results: The pharmacokinetic parameter of OTC was evaluated using a non-compartment model. OTC plasma concentrations were detectable for up to 144 and 120 h after IV and PO, respectively. The elimination half-life value of OTC was long with slow clearance after IV administration in hybrid catfish. The average maximum concentration value of OTC was 2.72 ㎍/mL with a time at the maximum concentration of 8 h. The absolute PO bioavailability was low (2.47%). Conclusions and Relevance: These results showed that PO administration of OTC at a dosage of 50 mg/kg BW was unlikely to be effective for clinical use in catfish. The pharmacodynamic properties and clinical efficacy of OTC after multiple medicated feed are warranted.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.4
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• pp.1-14
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• 2024

Otters, designated as Class I endangered wildlife due to population declines resulting from urban development and stream burial, have seen increased appearances in freshwater environments since the nationwide ban on stream filling in 2020 and the implementation of urban stream restoration projects. There is a pressing need for scientific and strategic conservation measures for otters, an umbrella and vulnerable species in aquatic ecosystems. Therefore, this study predicts potential otter habitats using the species distribution model MaxEnt, focusing on Hwangguji Stream in Suwon, and proposes conservation strategies. Otter signs were surveyed over three years from 2019 to 2021 with citizen scientists, serving as presence data for the model. The model's outcomes were enhanced by analyzing 'river nature map' as a boundary. MaxEnt compared the performance of 60 combinations of feature classes and regularization multipliers to prevent model complexity and overfitting. Additionally, unmanned sensor cameras observed otter density for model validation, confirming correlations with the species distribution model results. The 'LQ-5.0' parameter combination showed the highest explanatory power with an AUC of 0.853. The model indicated that the 'adjacent land use' variable accounted for 31.5% of the explanation, with a preference for areas around cultivated lands. Otters were found to prefer shelter rates of 10-30% in riparian forests within 2 km of bridges. Higher otter densities observed by unmanned sensors correlated with increasing model values. Based on these results, the study suggests three conservation strategies: establishing stable buffer zones to enhance ecological connectivity, improving water quality against non-point source pollution, and raising public awareness. The study provides a scientific basis for potential otter habitat management, effective conservation through governance linking local governments, sustainable biodiversity goals, and civil organizations.