• Progress in Superconductivity and Cryogenics
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• v.12 no.1
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• pp.56-60
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• 2010

Recently, many researches have been carried out for a high temperature superconducting (HTS) magnet which is advantageous in high critical current density and critical temperature. In HTS magnet, however, critical current is decreased by perpendicular magnetic field and persistent current is hard to maintain due to a low index value and high joint resistance compared with low temperature superconducting (LTS) magnet. In this paper, the HTS magnet using BSCCO wire was simulated through finite element method (FEM) and manufactured. we experimentally investigated operating characteristics of the compensating mode of the HTS magnet for current decay and made a comparison between persistent current mode and compensating mode. A feedback control unit was used to sustain current within specified ranges with defined upper and lower limits.

• Steel and Composite Structures
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• v.42 no.1
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• pp.59-74
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• 2022

This study introduces a general reliability-based, performance-based design framework to design frames regarding their uncertainties and user-defined design goals. The Iterative-R method extracted from the main framework can designate a proper R (i.e., response modification factor) satisfying the design goal regarding target reliability index and pre-defined probability of collapse. The proposed methodology is based on FEMA P-695 and can be used for all systems that FEMA P-695 applies. To exemplify the method, multiple three-dimensional, four-story steel special moment-resisting frames are considered. Closed-form relationships are fitted between frames' responses and the modeling parameters. Those fits are used to construct limit state functions to apply reliability analysis methods for design safety assessment and the selection of proper R. The frameworks' unique feature is to consider arbitrarily defined probability density functions of frames' modeling parameters with an insignificant analysis burden. This characteristic enables the alteration in those parameters' distributions to meet the design goal. Furthermore, with sensitivity analysis, the most impactful parameters are identifiable for possible improvements to meet the design goal. In the studied examples, it is revealed that a proper R for frames with different levels of uncertainties could be significantly different from suggested values in design codes, alarming the importance of considering the stochastic behavior of elements' nonlinear behavior.

• Progress in Medical Physics
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• v.33 no.4
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• pp.88-100
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• 2022

Purpose: Cerebral microbleeds are more susceptible than surrounding tissues and have been associated with a variety of neurological and neurodegenerative disorders that are indicative of an underlying vascular pathology. We investigated relaxivity changes and microvascular indices in the presence of microbleeds in an imaging voxel by evaluating those before and after contrast agent injection. Methods: Monte Carlo simulations were run with a variety of conditions, including different magnetic field strengths (B₀), different echo times, and different contrast agents. ΔR2^* and ΔR2 and microvascular indices were calculated with varying microvascular vessel sizes and microbleed loads. Results: As B₀ and the concentration of microbleeds increased, 𝜟R2^* and 𝜟R2 increased. 𝜟R2^* increased, but 𝜟R2 decreased slightly as the vessel radius increased. When the vessel radius was increased, the vessel size index (VSI) and mean vessel diameter (mVD) increased, and all other microvascular indices except mean vessel density (Q) increased when the concentration of microbleeds was increased. Conclusions: Because patients with neurodegenerative diseases often have microbleeds in their brains and VSI and mVD increase with increasing microbleeds, microbleeds can be altered microvascular signals in a voxel in the brain of a neurodegenerative disease at 3T magnetic resonance imaging.

• Korean Journal of Exercise Nutrition
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• v.16 no.1
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• pp.11-17
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• 2012

The purposes of this study were to investigate the effects of acute exercise on blood vaspin, glucose level, and inflammatory cytokines in middle-aged women with pre-diabetes. Nineteen middle-aged women (normal women, n = 11) and women with pre-diabetes(n = 8), who were apparently healthy and not taking any medications affecting their blood pressure or blood glucose, participated. Body fatness parameters including body mass index, body fat percentage, and waist circumference were measured using a bio-impedance analyzer. Resting blood pressure was measured in duplicate, and mean values were used for the data analysis. Regardless of group assignments, all subjects participated in a 3-day consecutive walking exercise at an intensity of 65% VO_2max targeting an energy expenditure of 1200 kcal (400 kcal per day). The major outcome variables included total cholesterol, triglycerides, high-density lipoprotein cholesterol, glucose, vaspin, interleukin-6, and adiponectin levels. Unlike normal women, women with pre-diabetes had a significant improvement in the homeostatic model assessment of insulin resistance (p < 0.025) with no significant group difference in response to acute exercise. The findings suggest that acute exercise results in a significant improvement in insulin sensitivity without any change in serum vaspin levels in women with pre-diabetes.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Nutrition Research and Practice
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• v.18 no.2
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• pp.165-179
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• 2024

BACKGROUND/OBJECTIVES: Mushroom consumption, rich in diverse nutrients and bioactive compounds, is suggested as a potential significant contributor to preventing cardiometabolic diseases (CMDs). This systematic review aimed to explore the association between mushrooms and cardiometabolic health outcomes, utilizing data from prospective cohort studies and clinical trials focusing on the general population, with mushrooms themselves as a major exposure. SUBJECTS/METHODS: All original articles, published in English until July 2023, were identified through searches on PubMed, Ovid-Embase, and google scholar. Of 1,328 studies, we finally selected 5 prospective cohort studies and 4 clinical trials. RESULTS: Existing research is limited, typically consisting of 1 to 2 studies for each CMD and cardiometabolic condition. Examination of articles revealed suggestive associations in some cardiometabolic conditions including blood glucose (both fasting and postprandial), high-density lipoprotein cholesterol related indices, high-sensitivity C-reactive protein, and obesity indices (body weight, body mass index, and waist circumference). However, mushroom consumption showed no association with the mortality and morbidity of cardiovascular diseases, stroke, and type 2 diabetes, although there was a potentially beneficial connection with all cause-mortality, hyperuricemia, and metabolic syndrome. CONCLUSION: Due to the scarcity of available studies, drawing definitive conclusions is premature. Further comprehensive investigations are needed to clarify the precise nature and extent of this relationship before making conclusive recommendations for the general population.

• Journal of Ecology and Environment
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• v.48 no.1
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• pp.49-59
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• 2024

Background: The present study aims to identify the pattern and size of Juniperus species (Juniperus phoenicea and J. procera) in the natural forests in terms of tree dimension, size structure and density, discussing the existing both species in Sarrawat Mountains for suggesting the preservation, conservation, and sustainable development. For achieving this, the height and mean crown diameter of each individual was measured based on 2-4 diameter measurements per ind. (506 ind. for J. phoenicea and 322 ind. for J. procera). Results: The size index of both species was classified into 7 classes: the first (< 100 cm) and the second (100-200 cm) classes were chosen to represent the juvenile stage. The total mean of the J. phoenicea population increased with the increase of altitude, while the whole population decreased after altitude of 2,000 m. The total mean of the J. procera population increased with the increase of altitude till altitude of 2,000-2,100 m. Conclusions: The present study indicated that both of species grow at low altitudes, they only grow at altitude above 1,700 m above sea level. The present study indicated that the study area has the two Juniperus spp. (J. phoenicea and J. procera) associated together all over the area. The results were discussed and compared with other related studies.

• Geomechanics and Engineering
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• v.38 no.1
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• pp.93-106
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• 2024

The present paper investigates the spatial variability effect of soil property on the three-dimensional probabilistic characteristics of the bearing capacity factor (i.e., mean and coefficient of variation) of a circular footing resting on clayey soil where both mean and standard deviation of undrained shear strength increases with depth, keeping the coefficient of variation constant. The mean trend of undrained shear strength is defined by introducing the dimensionless strength gradient parameter. The finite difference method along with the random field and Monte Carlo simulation technique, is used to execute the numerical analyses. The lognormal distribution is chosen to generate random fields of the undrained shear strength. In the study, the potential failure of the structure is represented through the failure probability. The influences of different vertical scales of fluctuation, dimensionless strength gradient parameters, and coefficient of variation of undrained shear strength on the probabilistic characteristics of the bearing capacity factor and failure probability of the footing, along with the probability and cumulative density functions, are explored in this study. The variations of failure probability for different factors of safety corresponding to different parameters are also illustrated. The results are presented in non-dimensional form as they might be helpful to the practicing engineers dealing with this type of problem.

• Geomechanics and Engineering
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• v.39 no.2
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• pp.129-142
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• 2024

The most significant soil parameters that are utilized in geotechnical engineering projects' design and implementations are soil strength parameters including friction (ϕ), cohesion (c), and uniaxial compressive strength (UCS). Understanding soil shear strength parameters can be guaranteed the design success and stability of structures. In this regard, professionals always looking for ways to get more accurate estimations. The presented study attempted to investigate soil shear strength parameters by using multivariate regression and multilayer perceptron predictive models which were implemented on 100 specimens' data collected from the Tabriz region (NW of Iran). The uniaxial (UCS), liquid limit (LL), plasticity index (PI), density (γ), percentage of fine-grains (pass #200), and sand (pass #4) which are used as input parameters of analysis and shear strength parameters predictions. A confusion matrix was used to validate the testing and training data which is controlled by the coefficient of determination (R²), mean absolute (MAE), mean squared (MSE), and root mean square (RMSE) errors. The results of this study indicated that MLP is able to predict the soil shear strength parameters with an accuracy of about 93.00% and precision of about 93.5%. In the meantime, the estimated error rate is MAE = 2.0231, MSE = 2.0131, and RMSE = 2.2030. Additionally, R² is evaluated for predicted and measured values correlation for friction angle, cohesion, and UCS are 0.914, 0.975, and 0.964 in the training dataset which is considerable.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.6
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• pp.751-758
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• 2017

The objective of this study was to determine the effects of moisture content and screw speed on the physical properties of extruded soy protein isolate (SPI). Expansion index, water absorption index, texture, integrity index, color, and nitrogen solubility index of extruded SPI were analyzed to determine the relationship with extrusion conditions. Extrusion conditions were moisture content (40, 50, and 60%) at a fixed die temperature ($140^{\circ}C$) and screw speed (250 rpm). The other extrusion conditions were screw speed (150, 250, and 330 rpm) at a fixed moisture content (55%) and die temperature ($140^{\circ}C$). Specific mechanical energy (SME) input decreased as moisture content increased from 40 to 60%. However, SME input increased as screw speed increased from 150 to 330 rpm. Expansion ratio and piece density decreased as moisture content and screw speed increased, and specific length increased as moisture content and screw speed increased. The extruded SPI at 40% moisture content had higher water absorption index, texture, and color differences than those of the extruded SPI at other moisture contents (50 and 60%). however, the extruded SPI at 40% moisture content had lower integrity index and cutting strength than those of the extruded SPI at other moisture contents (50 and 60%). In conclusion, the physical properties of extruded SPI were more affected by moisture content than screw speed.