• Current Applied Physics
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• v.18 no.11
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• pp.1174-1181
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• 2018

In nanomagnetism, one of the crucial scientific questions is whether magnetic behaviors are deterministic or stochastic on a nanoscale. Apart from the exciting physical issue, this question is also of paramount highest relevance for using magnetic materials in a wealth of technological applications such as magnetic storage and sensor devices. In the past, the research on the stochasticity of a magnetic process has been mainly done by macroscopic measurements, which only offer ensemble-averaged information. To give more accurate answer for the question and to fully understand related underlying physics, the direct observation of statistical behaviors in magnetic structures and magnetic phenomena utilizing advanced characterization techniques is highly required. One of the ideal tools for such study is a full-field soft X-ray microscope since it enables imaging of magnetic structures on the large field of view within a few seconds. Here we review the stochastic behaviors of various magnetic processes including magnetization reversal process in thin films, magnetic domain wall motions in nanowires, and magnetic vortex formations in nanodisks studied by full-field soft X-ray microscopy. The origin triggering the stochastic nature witnessed in each magnetic process and the way to control the intrinsic nature are also discussed.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.537-549
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• 2022

In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

• Steel and Composite Structures
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• v.44 no.5
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• pp.651-676
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• 2022

Most of the experimental, theoretical, and numerical studies on the stability of functionally graded composites are deterministic, while there are full of complex interactions of variables with an inherently probabilistic nature, this paper presents a non-intrusive framework to investigate the stochastic nonlinear buckling behaviors of porous functionally graded cylindrical shells exposed to inevitable source-uncertainties. Euler-Lagrange equations are theoretically derived based on the three variable refined shear deformation theory. Closed-form solutions for the shell buckling loads are achieved by solving the deterministic eigenvalue problems. The analytical results are verified with numerical results obtained from finite element analyses that are conducted in the commercial software ABAQUS. The non-intrusive framework is completed by integrating the Monte Carlo simulation with the verified closed-form solutions. The convergence studies are performed to determine the effective pseudorandom draws of the simulation. The accuracy and efficiency of the framework are verified with statistical results that are obtained from the first and second-order perturbation techniques. Eleven cases of individual and compound uncertainties are investigated. Sensitivity analyses are conducted to figure out the five cases that have profound perturbative effects on the shell buckling loads. Complete probability distributions of the first three critical buckling loads are completely presented for each profound uncertainty case. The effects of the shell thickness, volume fraction index, and stochasticity degree on the shell buckling load under compound uncertainties are studied. There is a high probability that the shell has non-unique buckling modes in stochastic environments, which should be known for reliable analysis and design of engineering structures.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.13-22
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• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• Journal of Ecology and Environment
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• v.43 no.3
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• pp.320-331
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• 2019

Background: Dioecious plant species having both male and female plants have been investigated regarding sex-related characteristics such as sex ratio, sex-differential resource requirements, and spatial segregation of the sexes. Habitat loss and fragmentation are major threats to the survival of plant populations, but dioecious species are particularly more prone to such habitat degradation than non-dioecious species because of their dimorphic sexual system. We examined the sex-related demographics of two Ilex cornuta populations being different regarding land use history. Methods: During 2016-2017, we examined I. cornuta trees with a basal diameter ${\geq}1.5cm$ in the Yongsu-ri population (YS population) and the Gotjawal Provincial Park population (GP population). Plant sex (male, female, or unsexed) was identified. The tree size (basal diameter and height of the main stem), clonal production (the ramet numbers per genet), and vitality for each clone were measured. The associations between population, sex, tree size, clonal production, and vitality were examined using ANOVAs and contingency table analyses. Finally, point pattern analyses using O-ring statistics were conducted to assess spatial patterns. Results: Upon excluding unsexed trees, the YS population with 74 trees was significantly male-biased (0.66), while the GP population with only 26 trees had a 1:1 sex ratio. In both populations, males and females did not differ in tree size. Although the mean number of ramets differed significantly between populations, females tended to produce more ramets than males. The proportion of weak trees was significantly higher in the YS than in the GP population. Neither population showed evidence of spatial segregation of the sexes. Conclusions: The two populations of dioecious I. cornuta are characterized by the small number of trees and relatively high frequencies of non-reproductive trees. Both indicate that these populations are quite susceptible to environmental and genetic stochasticity. On the other hand, the differences between populations in sex ratio, clonal production, and vitality suggest that conservation efforts for I. cornuta need to be population-specific. In order to help recover and enable this vulnerable species to persist, it is necessary to find ways to enhance their sexual reproduction and simultaneously reduce habitat disturbances due to anthropogenic activities.

• BMB Reports
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• v.54 no.2
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• pp.98-105
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• 2021

The clustered regularly interspaced short palindromic repeats (CRISPR) system is a family of DNA sequences originally discovered as a type of acquired immunity in prokaryotes such as bacteria and archaea. In many CRISPR systems, the functional ribonucleoproteins (RNPs) are composed of CRISPR protein and guide RNAs. They selectively bind and cleave specific target DNAs or RNAs, based on sequences complementary to the guide RNA. The specific targeted cleavage of the nucleic acids by CRISPR has been broadly utilized in genome editing methods. In the process of genome editing of eukaryotic cells, CRISPR-mediated DNA double-strand breaks (DSB) at specific genomic loci activate the endogenous DNA repair systems and induce mutations at the target sites with high efficiencies. Two of the major endogenous DNA repair machineries are non-homologous end joining (NHEJ) and homology-directed repair (HDR). In case of DSB, the two repair pathways operate in competition, resulting in several possible outcomes including deletions, insertions, and substitutions. Due to the inherent stochasticity of DSB-based genome editing methods, it was difficult to achieve defined single-base changes without unanticipated random mutation patterns. In order to overcome the heterogeneity in DSB-mediated genome editing, novel methods have been developed to incorporate precise single-base level changes without inducing DSB. The approaches utilized catalytically compromised CRISPR in conjunction with base-modifying enzymes and DNA polymerases, to accomplish highly efficient and precise genome editing of single and multiple bases. In this review, we introduce some of the advances in single-base level CRISPR genome editing methods and their applications.