• Journal of the Korean Magnetics Society
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• v.5 no.5
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• pp.366-371
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• 1995

High performance magnetic materials are characterized by the combination of outstanding magnetic properties and optimized microstructures, e.g., nanocrystalline composites of multilayers and small particle systems. The characteristic parameters of the hysteresis loops of these materials vary over more than a factor of $10^{6}$ with optimum values for the coercive field of several Tesla and permeabilities of $10^{6}$. Within the framework of the computational micromagnetism (nanomagnetism) using the finite element method the upper and lower bounds of the coercive field of different types of grain ensembles and multilayers have been determined. For the case of nanocrystalline composites the role of grain size, exchange and dipolar coupling between grains and the degree of grain alignment will be discusses in detail. It is shown that the largest coercivities are obtained for exchange decoupled grains, whereas remanence enhancing requires exchange coupled grains below 20 nm. For composite permanent magnets based on $Nd_{2}Fe_{14}B$ with an amount of ~ 50% soft $\alpha$-Fe-phase coercivities of ${\mu}_{0}H_{c}=0.75\;T$, a remanence of 1.5 T and an energy product of $400\;kJ/m^{3}$ is expected. In nanocrystalline systems the temperature dependence of the coercivity is well described by the relation ${\mu}_{0}H_{c}=(2\;K_{1}/M_{s}){\alpha}-N_{eff}{\mu}_{0}M_{s}$, where the microstructural parameters $\alpha$ and $N_{eff}$ take care of the short-range perturbations of the anisotropy and $N_{eff}$ is related to the long-range dipolar interactions. $N_{eff}$ is found to follow a logarithmic grain size size dependence ${\mu}_{0}H_{c}=(2\;K_{1}/M_{s}){\alpha}-N_{eff}(\beta1nD){\mu}_{0}M_{s}$. Several trends how to achieve the ideal situation $\alpha$->1 and $N_{eff}$->1->0 will be discussed.

• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.31-44
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• 2014

In the present study, a few of recently developed geostatistical models are comparatively studied. The models are two-point statistics based sequential indicator simulation (SISIM) and generalized coupled Markov chain (GCMC), multi-point statistics single normal equation simulation (SNESIM), and object based model of FLUVSIM (fluvial simulation) that predicts structures of target object from the provided geometric information. Out of the models, SNESIM and FLUVSIM require additional information other than conditioning data such as training map and geometry, respectively, which generally claim demanding additional resources. For the comparative studies, three-dimensional fluvial reservoir model is developed considering the genetic information and the samples, as input data for the models, are acquired by mimicking realistic sampling (i.e. random sampling). For SNESIM and FLUVSIM, additional training map and the geometry data are synthesized based on the same information used for the objective model. For the comparisons of the predictabilities of the models, two different measures are employed. In the first measure, the ensemble probability maps of the models are developed from multiple realizations, which are compared in depth to the objective model. In the second measure, the developed realizations are converted to hydrogeologic properties and the groundwater flow simulation results are compared to that of the objective model. From the comparisons, it is found that the predictability of GCMC outperforms the other models in terms of the first measure. On the other hand, in terms of the second measure, the both predictabilities of GCMC and SNESIM are outstanding out of the considered models. The excellences of GCMC model in the comparisons may attribute to the incorporations of directional non-stationarity and the non-linear prediction structure. From the results, it is concluded that the various geostatistical models need to be comprehensively considered and comparatively analyzed for appropriate characterizations.

• Molecules and Cells
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• v.44 no.9
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• pp.627-636
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• 2021

The three-dimensional organization of chromatin and its time-dependent changes greatly affect virtually every cellular function, especially DNA replication, genome maintenance, transcription regulation, and cell differentiation. Sequencing-based techniques such as ChIP-seq, ATAC-seq, and Hi-C provide abundant information on how genomic elements are coupled with regulatory proteins and functionally organized into hierarchical domains through their interactions. However, visualizing the time-dependent changes of such organization in individual cells remains challenging. Recent developments of CRISPR systems for site-specific fluorescent labeling of genomic loci have provided promising strategies for visualizing chromatin dynamics in live cells. However, there are several limiting factors, including background signals, off-target binding of CRISPR, and rapid photobleaching of the fluorophores, requiring a large number of target-bound CRISPR complexes to reliably distinguish the target-specific foci from the background. Various modifications have been engineered into the CRISPR system to enhance the signal-to-background ratio and signal longevity to detect target foci more reliably and efficiently, and to reduce the required target size. In this review, we comprehensively compare the performances of recently developed CRISPR designs for improved visualization of genomic loci in terms of the reliability of target detection, the ability to detect small repeat loci, and the allowed time of live tracking. Longer observation of genomic loci allows the detailed identification of the dynamic characteristics of chromatin. The diffusion properties of chromatin found in recent studies are reviewed, which provide suggestions for the underlying biological processes.

• Applied Chemistry for Engineering
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• v.32 no.2
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• pp.205-213
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• 2021

The present study aimed to determine the effect of co-pyrolysis of sawdust biomass and scrap tyre waste employing different blending ratios of sawdust to waste tyre such as 100:0, 75:25, 50:50, 25:75, and 0:100. The thermochemical characterization of feedstocks was carried out by employing the proximate, ultimate analysis, and thermogravimetric (TGA) analyses, calorific values, and scanning electron microscope coupled with energy dispersive x-ray analysis (SEM-EDX) to select the blending ratio having better bioenergy potential amongst the studied ratios. The blending ratio of 25:75 (sawdust to waste tyre) was selected for the co-pyrolysis study in a fixed-bed pyrolysis reactor system based on its solid biofuels properties such as heating value (30.18 MJ/kg), and carbon (71.81 wt%) and volatile matter (63.82 wt%) contents. The pyrolysis temperatures were varied as 500, 600 and 700 ℃ while the other parameters such as heating rate and nitrogen flowrate were maintained at 30 ℃/min and 0.5 L/min respectively. The bio-oil yields as 31.9, 47.1 and 61.2 wt%, bio-char yields as 34.5, 34.2 and 31.4 wt% and gaseous product yields as 33.6, 18.60 and 7.3 wt% at the pyrolysis temperatures of 500, 600 and 700 ℃ respectively were obtained. The blends of sawdust and waste tyres showed the improved energy characteristics which could provide the solution for the beneficial management of sawdust and scrape tyre wastes via co-pyrolysis processing.

• Molecules and Cells
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• v.42 no.2
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• pp.123-134
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• 2019

Lysophosphatidic acid (LPA) is an endogenous lysophospholipid with signaling properties outside of the cell and it signals through specific G protein-coupled receptors, known as $LPA_{1-6}$. For one of its receptors, $LPA_1$ (gene name Lpar1), details on the cis-acting elements for transcriptional control have not been defined. Using 5'RACE analysis, we report the identification of an alternative transcription start site of mouse Lpar1 and characterize approximately 3,500 bp of non-coding flanking sequence 5' of mouse Lpar1 gene for promoter activity. Transient transfection of cells derived from mouse neocortical neuroblasts with constructs from the 5' regions of mouse Lpar1 gene revealed the region between -248 to +225 serving as the basal promoter for Lpar1. This region also lacks a TATA box. For the region between -761 to -248, a negative regulatory element affected the basal expression of Lpar1. This region has three E-box sequences and mutagenesis of these E-boxes, followed by transient expression, demonstrated that two of the E-boxes act as negative modulators of Lpar1. One of these E-box sequences bound the HeLa E-box binding protein (HEB), and modulation of HEB levels in the transfected cells regulated the transcription of the reporter gene. Based on our data, we propose that HEB may be required for a proper regulation of Lpar1 expression in the embryonic neocortical neuroblast cells and to affect its function in both normal brain development and disease settings.

• Steel and Composite Structures
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• v.30 no.3
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• pp.281-292
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• 2019

In this paper, analysis of critical fluid velocity and heat transfer in the nanocomposite pipes conveying nanofluid is presented. The pipe is reinforced by carbon nanotubes (CNTs) and the fluid is mixed by $AL_2O_3$ nanoparticles. The material properties of the nanocomposite pipe and nanofluid are considered temperature-dependent and the structure is subjected to magnetic field. The forces of fluid viscosity and turbulent pressure are obtained using momentum equations of fluid. Based on energy balance, the convection of inner and outer fluids, conduction of pipe and heat generation are considered. For mathematical modeling of the nanocomposite pipes, the first order shear deformation theory (FSDT) and energy method are used. Utilizing the Lagrange method, the coupled pipe-nanofluid motion equations are derived. Applying a semi-analytical method, the motion equations are solved for obtaining the critical fluid velocity and critical Reynolds and Nusselt numbers. The effects of CNTs volume percent, $AL_2O_3$ nanoparticles volume percent, length to radius ratio of the pipe and shell surface roughness were shown on the critical fluid velocity, critical Reynolds and Nusselt numbers. The results are validated with other published work which shows the accuracy of obtained results of this work. Numerical results indicate that for heat generation of $Q=10MW/m^3$, adding 6% $AL_2O_3$ nanoparticles to the fluid increases 20% the critical fluid velocity and 15% the Nusselt number which can be useful for heat exchangers.

• Coupled systems mechanics
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• v.8 no.2
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• pp.169-184
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• 2019

This research work presents a study that aims to assess the dynamic structural behaviour and also investigate the human comfort levels of a reinforced concrete building, when subjected to nondeterministic wind dynamic loadings, considering the effect of masonry infills on the global stiffness of the structural model. In general, the masonry fills most of the empty areas within the structural frames of the buildings. Although these masonry infills present structural stiffness, the common practice of engineers is to adopt them as static loads, disregarding the effect of the masonry infills on the global stiffness of the structural system. This way, in this study a numerical model based on sixteen-storey reinforced concrete building with 48 m high and dimensions of $14.20m{\times}15m$ was analysed. This way, static, modal and dynamic analyses were carried out in order to simulate the structural model based on two different strategies: no masonry infills and masonry infills simulated by shell finite elements. In this investigation, the wind action is considered as a nondeterministic process with unstable properties and also random characteristics. The fluctuating parcel of the wind is decomposed into a finite number of harmonic functions proportional to the structure resonant frequency with phase angles randomly determined. The nondeterministic dynamic analysis clearly demonstrates the relevance of a more realistic numerical modelling of the masonry infills, due to the modifications on the global structural stiffness of the building. The maximum displacements and peak accelerations values were reduced when the effect of the masonry infills (structural stiffness) were considered in the dynamic analysis. Finally, it can be concluded that the human comfort evaluation of the sixteen-storey reinforced concrete building can be altered in a favourable way to design.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.426-439
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• 2018

Purpose: To continuously monitor soil and climatic properties, a data acquisition system (DAQ) was developed and tested in plum farms (Gyewol-ri and Haechang-ri, Suncheon, Korea). Methods: The DAQ consisted of a Raspberry-Pi processor, a modem, and an ADC board with multiple sensors (soil moisture content (SEN0193), soil temperature (DS18B20), climatic temperature and humidity (DHT22), and rainfall gauge (TR-525M)). In the laboratory, various tests were conducted to calibrate SEN0193 at different soil moistures, soil temperatures, depths, and bulk densities. For performance comparison of the SEN0193 sensor, two commercial moisture sensors (SMS-BTA and WT-1000B) were tested in the field. The collected field data in Raspberry-Pi were transmitted and stored on a web server database through a commercial communications wireless network. Results: In laboratory tests, it was found that the SEN0193 sensor voltage reading increased significantly with an increase in soil bulk density. A linear calibration equation was developed between voltage and soil moisture content depending on the farm soil bulk density. In field tests, the SEN0193 sensor showed linearity (R = 0.76 and 0.73) between output voltage and moisture content; however, the other two sensors showed no linearity, indicating that site-specific calibration is important for accurate sensing. In the long-term monitoring results, it was observed that the measured climate temperature was almost the same as website information. Soil temperature information was higher than the values measured by DS18B20 during spring and summer. However, the local rainfall measured using TR 525M was significantly different from the values on the website. Conclusion: Based on the test results obtained using the developed monitoring system, it is thought that the measurement of various parameters using one device would be helpful in monitoring plum growth. Field data from the local farm monitoring system can be coupled with website information from the weather station and used more efficiently.

• Coupled systems mechanics
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• v.8 no.5
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• pp.439-457
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• 2019

In this paper, a new application of a four variable refined plate theory to analyze the nonlinear bending of functionally graded plates exposed to thermo-mechanical loadings, is presented. This recent theory is based on the assumption that the transverse displacements consist of bending and shear components in which the bending components do not contribute toward shear forces, and similarly, the shear components do not contribute toward bending moments. The derived transverse shear strains has a quadratic variation across the thickness that satisfies the zero traction boundary conditions on the top and bottom surfaces of the plate without using shear correction factors. The material properties are assumed to vary continuously through the thickness of the plate according to a power-law distribution of the volume fraction of the constituents. The solutions are achieved by minimizing the total potential energy. The non-linear strain-displacement relations in the von Karman sense are used to derive the effect of geometric non-linearity. It is concluded that the proposed theory is accurate and simple in solving the nonlinear bending behavior of functionally graded plates.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.289-296
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• 2021

The Korean construction industry has been implementing G-SEED, a certification system that evaluates the environmental properties of buildings for the purpose of reducing environmental burdens such as energy and resource consumption and pollutant emissions. Also, creating a pleasant environment in general is one more purpose of G-SEED certification system. However, G-SEED certification in practice is difficult and time consuming due to the complexity of the certification acquisition process coupled with little economic consideration for the materials of each certification item. Therefore, in this study, we present a model for the optimal selection of materials and economic assessment using a genetic algorithm. The development of the model involves building a material database based on life-cycle costing (LCC) targeted at "Application of Indoor Air Pollutant Low Emission Material" from G-SEED. Next, the model was validated using a real non-residential building case study. The result shows an average cost reduction rate of 74.5 % compared with the existing cost. This model is expected to be used as an economically efficient tool in G-SEED.