In this paper, the dynamic response of a simply-supported composite sandwich plate with a viscoelastic core based on the Golla-Hughes-McTavish (GHM) viscoelastic model is investigated analytically. The formulation is developed using the three-layered sandwich panel theory. Hamilton's principle has been employed to derive the equations of motion. Since classical models, like kelvin-voigt and Maxwell models, cannot express a comprehensive description of the dynamic behavior of viscoelastic material, the GHM method is used to model the viscoelastic core of the plate in this research. The main advantage of the GHM model in comparison with classical models is the consideration of the frequency-dependent characteristic of viscoelastic material. Identification of the material parameters of GHM mini-oscillator terms is an essential procedure in applying the GHM model. In this study, the focus of viscoelastic modeling is on the development of GHM parameters identification. For this purpose, a new method is proposed to find these constants which express frequency-dependent behavior characterization of viscoelastic material. Natural frequencies and loss factors of the sandwich panel based on ESL and three-layered theories in different geometrics are described at 30℃ and 90℃; also, the comparisons show that obtained natural frequencies are grossly overestimated by ESL theory. The argumentations of differences in natural frequencies are also illustrated in detail. The obtained results show that the GHM model presents a more accurate description of the plate's dynamic response by considering the frequency dependency behavior of the viscoelastic core.
Ye Ra Choi;Soon Ho Yoon;Jihang Kim;Jin Young Yoo;Hwiyoung Kim;Kwang Nam Jin
Tuberculosis and Respiratory Diseases
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v.86
no.3
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pp.226-233
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2023
Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.
Xiongjie Zhang;Bin Tang ;Geng Nian;Haitao Wang ;Lijiao Zhang ;Yan Zhang ;Rui Chen ;Zhifeng Liu ;Jinhui Qu
Nuclear Engineering and Technology
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v.55
no.7
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pp.2572-2577
/
2023
A field determination method for small D-T neutron source yield based on the oxygen prompt gamma rays was established. A neutron-gamma transport equation of the determination device was developed. Two yield field determination devices with a thickness of 20 mm and 50 mm were made. The count rates of the oxygen prompt gamma rays were calculated using three energy spectra processing approaches, which were the characteristic peak of 6.13 MeV, the overlapping peak of 6.92 MeV and 7.12 MeV, and the total energy area. The R-square of the calibration curve is better than 94% and the maximum error of the yield test is 5.21%, demonstrating that it is feasible to measure the yield of D-T neutron source by oxygen prompt gamma rays. Additionally, the results meet the requirements for field determination of the conventional D-T neutron source yield.
Background: The neutrophil-to-lymphocyte ratio (NLR) has been suggested as a novel predictive marker of cardiovascular disease. However, its prognostic role in patients under-going coronary artery bypass grafting (CABG) is unclear. This study aimed to determine the association between the preoperative NLR and early mortality in patients undergoing CABG. Methods: Cardiac surgery was performed in 2,504 patients at Seoul St. Mary's Hospital from January 2010 to December 2021. This study retrospectively reviewed 920 patients who underwent isolated CABG, excluding those for whom the preoperative NLR was unavailable. The primary endpoints were the 30- and 90-day mortality after isolated CABG. Risk factor analysis was performed using logistic regression analysis. Based on the optimal cut-off value of preoperative NLR on the receiver operating characteristic curve, high and low NLR groups were compared. Results: The 30- and 90-day mortality rates were 3.8% (n=35) and 7.0% (n=64), respectively. In the multivariable analysis, preoperative NLR was significantly associated with 30-day mortality (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.17-1.39; p<0.001) and 90-day mortality (OR, 1.17; 95% CI, 1.07-1.28; p<0.001). The optimal cut-off value of the preoperative NLR was 3.4. Compared to the low NLR group (<3.4), the high NLR group (≥3.4) showed higher 30- and 90-day mortality rates (1.4% vs. 12.1%, p<0.001; 2.8% vs. 21.3%, p<0.001, respectively). Conclusion: Preoperative NLR was strongly associated with early mortality after isolated CABG, especially in patients with a high preoperative NLR (≥3.4). Further studies with larger cohorts are necessary to validate these results.
Vahed Ghiasi;Nur Irfah Mohd Pauzi;Shahab Karimi;Mahyar Yousefi
Geomechanics and Engineering
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v.34
no.3
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pp.267-284
/
2023
Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.
Arteriovenous fistula flow dysfunction is the leading cause of vascular access thrombosis and loss in patients undergoing hemodialysis. However, data regarding the influence of access flow rate measurements on the long-term outcomes of access are limited. This study aims to identify accesses at a high risk of thrombosis and loss among patients undergoing hemodialysis by measuring the access flow rate and exploring an optimal threshold value for predicting future access thrombosis. We enrolled 220 patients with arteriovenous fistula undergoing hemodialysis. The primary outcome was the occurrence of access thrombosis. Access flow rates were measured monthly using the ultrasound dilution method and were averaged using all measurements from patients with patent access. In patients experienced access thrombosis, those immediately before the thrombosis were selected. Using these data, we calculated the access flow rate threshold for thrombosis occurrence by analyzing the receiver operating characteristic curve, and the patients were divided into two groups according to whether access flow rates were higher or lower than 400 mL/min. During a median follow-up period of 3.1 years, 4,510 access flows were measured (median measurements per patient, 33 times; interquartile range, 11-54). A total of 65 access thromboses and 19 abandonments were observed. Access thrombosis and loss were higher in the lowflow group than in the high-flow group. This study revealed that low access flow rates are strongly associated with access thrombosis occurrence and subsequent loss of arteriovenous fistulas in patients undergoing hemodialysis.
The improper management of radioactive waste or accidents caused by natural disasters can result in the release of radioactive materials into the surrounding environment, potentially leading to soil and groundwater contamination by radionuclides. In this study, adsorption-desorption behaviors of the radionuclides (cobalt and strontium) in natural soil, montmorillonite, Mn-PILC, Fe-PILC, and fishbone were investigated. Several models were used to predict adsorption isotherms of radionuclides on various absorbents. Adsorption isotherms of cobalt and strontium in several adsorbents were examined at pH 5.5. The amount of sorbed cobalt and strontium were represented fishbone > natural soil > Mn-PILC > Fe-PILC > montmorillonite and natural soil > Mn-PILC > fishbone > Fe-PILC > montmorillonite, respectively. Adsorption datas were fitted with several models such as Freundlich, Langmuir, Sips, Redlich-Peterson, Khan, and Generalized model. The results of curve fitting showed R2> 0.98 in all of adsorption models, except Sr2+ adsorption onto montmorillonite. For modified clays (Mn-PILC, Fe-PILC), it is suggested that, unlike natural soils and fish bones, there are not only single adsorption mechanisms but also adsorption mechanisms based on chemical adsorption and surface charge. In the case of fish bones, due to the relatively higher adsorption capacity than modified clays and its characteristic of significant desorption, it is expected more suitable for the removal of radionuclides in aquatic environments than for the immobilization of radionuclides in soil.
Proceedings of the National Institute of Ecology of the Republic of Korea
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v.4
no.4
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pp.159-176
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2023
The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.
Objective : The optic nerve sheath diameter (ONSD)/eyeball transverse diameter (ETD) ratio is a more reliable marker of intracranial pressure than the ONSD alone. We aimed to investigate the predictive value of the ONSD/ETD ratio (OER) for neurological outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods : Adult patients with aSAH who visited the emergency department of a tertiary hospital connected to a South Korean university between January 2015 and December 2021 were included. Data on patient characteristics and brain computed tomography scan findings, including the ONSD and ETD, were collected using a predefined protocol. According to the neurological outcome at hospital discharge, the patients were divided into the unfavorable neurological outcome (UNO; cerebral performance category [CPC] score 3-5) and the favorable neurological outcome (FNO; CPC score 1-2) groups. The primary outcome was the association between the OER and neurological outcomes in patients with aSAH. Results : A total of 171 patients were included in the study, of whom 118 patients (69%) had UNO. Neither the ONSD (p=0.075) nor ETD (p=0.403) showed significant differences between the two groups. However, the OER was significantly higher in the UNO group in the univariate analysis (p=0.045). The area under the receiver operating characteristic curve of the OER for predicting UNO was 0.603 (p=0.031). There was no independent relationship between the OER and UNO in the multivariate logistic regression analysis (adjusted odds ratio, 0.010; p=0.576). Conclusion : The OER was significantly higher in patients with UNO than in those with FNO, and the OER was more reliable than the ONSD alone. However, the OER had limited utility in predicting UNO in patients with aSAH.
This study analyzes the operational characteristics of 311 aged and non-aged residual current circuit breakers (RCCBs) in low-voltage consumer contexts. It investigates the influence of external temperature and harmonics based on the rated current multiples. To simulate temperature variations, a convectional oven was used around the circuit breakers. Additionally, the generation of harmonic reference signals and data measurement for overcurrent experiments were conducted using NI SCXI, myDAQ, and LabVIEW. An observation revealed that as the ambient temperature increased, the operating time of RCCBs decreased in the time delay region. This was attributed to the faster response or bending of the bimetal, which is the tripping element. However, aged RCCBs encountered challenges with tripping outside the protective curve. The operating time of the circuit breakers exhibited an acceleration influenced by the order and content of harmonic currents, potentially leading to malfunctions. Aged RCCBs demonstrated faster operating times than their non-aged counterparts. However, the difference in operating time varied based on the manufacturer's and operating environment of the RCCBs. Frequent malfunctions of RCCBs can result in power outages. In cases where these circuit breakers fail to operate, they can lead to secondary damages, including electrical fires and shocks. Consequently, it is imperative to consider the operating environment of RCCBs and provide appropriate replacement cycles to mitigate these risks.
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