미국에서는 재난으로 인한 기반시설물의 피해를 줄이기 위해 국가기반시설 리질리언스 확보가 국가기반시설보호계
획에 활용되고 있다. 여기서 “리질리언스”는 재난으로 인한 시스템의 영향을 효율적으로 줄일 수 있는 기반시설 시
스템의 능력으로, 리질리언스 비용으로 정량화가 시도되었다. 리질리언스 비용은 시스템 영향과 복구노력을 합한 것
으로, 리질리언스 평가 사례는 리질리언스 평가시 복구노력을 고려할 필요가 있음을 보여주고 있다. 본 논문은 리질
리언스 비용을 설명하고, 연구 사례를 통해 리질리언스 비용의 평가 방법을 보여주고자 한다.

Critical infrastructure resilience has been integrated in critical infrastructure protection in US after Department of
Homeland Security recognized that protection, in isolation, is a brittle strategy. Here “resilience” is the system’s
ability to efficiently reduce both the magnitude and the duration of systemic impacts after hazards, and quantitatively
assessed as a resilience cost. The resilience cost is the sum of systemic impacts and recovery efforts, and
many case studies on resilience costs show that the recovery effort should be included in resilience assessment.
This paper explains how the resilience cost is defined and quantified with a case study.

Canopy turbulence plays an important role in mass and energy exchanges at the canopy-atmosphere interface. Despite extensive studies on canopy turbulence over a flat terrain, less attention has been given to canopy turbulence in a complex terrain. The purpose of this study is to scrutinize characteristics of canopy turbulence in roughness sublayer over a hilly forest terrain. We investigated basic turbulence statistics, conditionally sampled statistics, and turbulence spectrum in terms of different atmospheric stabilities, wind direction and vertical structures of momentum fluxes. Similarly to canopy turbulence over a homogeneous terrain, turbulence statistics showed coherent structure. Both quadrant and spectrum analysis corroborated the role of intermittent and energetic eddies with length scale of the order of canopy height, regardless of wind direction except for shift of peak in vertical wind spectrum to relatively high frequency in the down-valley wind. However, the magnitude of the momentum correlation coefficient in a neutral condition was smaller than typical value over a flat terrain. Further scrutiny manifested that, in the up-valley flow, temperature skewness was larger and the contribution of ejection to both momentum and heat fluxes was larger compared to the downvalley flow, indicating that thermal instability and weaker wind shear in up-valley flow asymmetrically affect turbulent transport within the canopy.

The core of neutron-star matter is supposed to be at a much higher density than the normal nuclear-matter density, for which various possibilities have been suggested, such as, for example, meson or hyperon condensation and/or deconfined quark or color-superconducting matter. In this work, we explore the implication on hadron physics of a dense compact object that has three “phases”: nuclear matter at the outer layer, kaon condensed nuclear matter in the middle, and strange quark matter at the core. Using a drastically simplified but not unreasonable model, we develop the scenario where the different phases are smoothly connected with the kaon condensed matter playing a role of a “doorway” to a quark core, the equation of state of which with parameters restricted within the range allowed by nature could be made compatible with the mass vs radius constraint given by the 1.97-solar-mass object PSR J1614-2230 recently observed.

The goal of magnetic resonance electrical impedance tomography (MREIT) is to produce a tomographic image of a conductivity distribution inside an electrically conducting object. Injecting current into the object, we measure a z-component B_z of an induced magnetic flux density using an MRI scanner. Based on the relation between the conductivity and measured B_z data, we may reconstruct cross-sectional images of the conductivity distribution. In a two-dimensional imaging slice, we can see that conductivity changes along equipotential lines are determined by the measured B_z data. Since the equipotential lines themselves depend nonlinearly on the unknown conductivity distribution, it is not possible to recover the conductivity distribution directly from measured B_z data. Conductivity image reconstruction algorithms such as the harmonic B_z algorithm utilize an iterative procedure to update conductivity values and in each iteration we need to solve an elliptic boundary value problem with a presumed conductivity distribution. This iteration is often troublesome in practice due to excessive amounts of noise in some local regions where weak MR signals are produced. This motivated us to develop a non-iterative reconstruction algorithm which does not depend on a global structure of the conductivity distribution. In this paper, we propose a new MREIT conductivity image reconstruction algorithm, called the non-iterative harmonic B_z algorithm, which provides a conductivity image directly from measured B_z data. From numerical simulations, we found that the new method produces absolute images of a conductivity distribution with a high accuracy by maximizing the use of reliable B_z data. It effectively reduces adverse effects of excessive noise in some local regions of weak MR signals by restricting the influences within them.

In magnetic resonance electrical impedance tomography, among several conductivity image reconstruction algorithms, the harmonic B_z algorithm has been successfully applied to B_z data from phantoms and animals. The algorithm is, however, sensitive to measurement noise in B_z data. Especially, in in vivo animal and human experiments where injection current amplitudes are limited within a few milliampere at most, measured B_z data tend to have a low SNR. In addition, magnetic resonance (MR) signal void in outer layers of bones and gas-filled organs, for example, produces salt-pepper noise in the MR phase and, consequently, B_z images. The B_z images typically present areas of sloped transitions, which can be assimilated to ramps. Conductivity contrasts change ramp slopes in B_z images and it is critical to preserve positions of those ramps to correctly recover edges in conductivity images. In this paper, we propose a ramp-preserving denoising method utilizing a structure tensor. Using an eigenvalue analysis, we identified local regions of salt-pepper noise. Outside the identified local regions, we applied an anisotropic smoothing to reduce noise while preserving their ramp structures. Inside the local regions of salt-pepper noise, we used an isotropic smoothing. After validating the proposed denoising method through numerical simulations, we applied it to in vivo animal imaging experiments. Both numerical simulation and experimental results show significant improvements in the quality of reconstructed conductivity images.

The monsoon system is an important natural driver of ecosystem carbon and water exchanges in Asia and is being altered by anthropogenic forcings. This system is accompanied by heavy rainfall and typhoons in the main growing season, thus causing alterations of environmental conditions such as rainfall, wind, and temperature; therefore, it acts as a natural disturbance to forests in Asia. Therefore, degradation of ecosystem service by monsoon activity reinforced by anthropogenic factors in a changing climate is of great concern. In this study, we presented observational evidences for the interplay of terrestrial carbon and water dynamics with the Asian monsoon and their implication in ecosystem modeling. We analyzed 3­year eddy­covariance data at a temperate deciduous forest in Korea. We used wavelet power and coherence spectra to investigate the Asian monsoon system and to determine its impact on the ecosystem. During the study period, our analysis showed strong coupling between ecosystem functioning and temporal variations of monsoon climate. Further scrutiny on the model outputs showed that the model did not accurately reproduce the observed plant phenology and thus ecosystem carbon and water exchanges disturbed by monsoon activities. Our findings suggest that under projected climate scenarios, terrestrial carbon sinks in monsoon Asia will decline if the monsoon disturbance will exceed its natural range of variation and if there is no enhancement in the robustness of the ecosystem in this region.

We discuss the nonlinear instability of some class of stationary solutions to the one-dimensional Vlasov–Yukawa system with a mass parameter m. The Vlasov–Yukawa system corresponds to the short-range correction of the repulsive Vlasov–Poisson system arising from plasma physics. We show that the stationary solutions satisfying the Penrose condition are nonlinearly unstable in small mass regime. In a large mass regime, the massiveness of force carrier particles acts as stabilizer in a finite time interval. We present several numerical results to confirm our analytical results.