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SUMMARY The imaging of subsurface structures is an essential task in subsurface engineering projects; it provides information regarding the locations of active faults and layer boundaries. Among the methods available for imaging of subsurface structures, the body wave imaging method using urban traffic noise has recently attracted attention because it permits continuous measurement at low cost in urban areas. However, because the urban traffic noise signal used for imaging on the engineering scale has characteristics that differ from the ambient noise used on the crustal scale, the conventional crustal-scale data processing workflow should be modified through systematic data analysis. In this study, traffic noise sources were systematically analysed using field data obtained over the Xiadian fault in Hebei province, China. The traffic noise signals were recorded in various patterns because of diverse incoming directions and show marked amplitude changes depending on time of recording. The overlapping signals originating from opposite directions generate spurious events and noise in the seismic interferometry images; constant processing parameters cannot respond to the large amplitude changes. In this study, to remove surface waves with markedly changing amplitude, we applied actively varying threshold values to each set of traces using the moving average of amplitude changes within the trace. In addition, the signals originating from diverse directions were separated into negative and positive slopes through the f–k filter; the interference generated by overlapping signals was minimized by applying data processing (e.g. median filtering and high amplitude removal) separately to the negative and positive slopes of each simultaneously acquired trace gather. Due to the modified data processing workflow, most spurious events were successfully suppressed in the final stacked image compared with those produced using the conventional data processing workflow, and reflections were imaged more clearly. Fault spatial locations and layer boundary depth variation in the final image obtained by the modified processing workflow were similar to those reported in previous studies.

Various disasters have recently occurred in Korea because of weather changes caused by climate change, and the scale of the damage is also increasing. In terms of the weather phenomena and their socioeconomic impacts, weather-related disasters cause the most damage. Therefore, this study suggests a method of calculating rainfall thresholds to predict the impact of heavy rains. To calculate rainfall thresholds on the basis of a multimethod approach, this study divided Korea into a 1 km × 1 km grid and further split it into four categories: standard watershed, urban, river, and inundation trace maps. This study verified the results of the rainfall thresholds in the standard basin and city center by referring to the relevant data on the rainy season in summer 2020 and the Typhoon Haishen in September. Verification results showed that the flooding that occurred in the grid actually caused the urban flooding in Busan in July 2020. Moreover, the calculation on the grid that caused flooding in Gangneung, which was hit by Typhoon Haishen in September, reflected the actual damage. When used in impact forecasting, the proposed method of calculating rainfall thresholds and predicting rainfall information is expected to be able to provide data on the impact of heavy rains and facilitate rainfall forecasting.

In this study, water utilization status and water saving awareness investigation were analyzed through a survey in Gwangju Metropolitan City. Consequently, it was observed that most water is wasted when showering and doing laundry. Therefore, it is necessary to supply water-saving washing machines and dishwashers along with water-saving devices. A total of 64% of the respondents conserve water in their daily lives, and the reasons are worries about the future and economic reasons. Water saving is not practiced because it is unfamiliar or uncomfortable. Therefore, methods are necessary to save water without inconvenience in daily lives. It is judged that the results of this study can be used to establish strategies for water demand management.

Purpose To describe the distribution and determinants of choroidal thickness (CT) in participants in a population study based on spectral-domain (SD)-OCT measurements. Design Population-based, cross-sectional study. Participants Ethnic Chinese, Indian, and Malay adults aged more than 50 years without any retinal diseases (e.g., diabetic retinopathy, macular edema, age-related macular degeneration, central serous chorioretinopathy) that might affect the CT were recruited from the Singapore Epidemiology of Eye Diseases Study. Methods Choroidal imaging was performed by SD-OCT (Spectralis, Heidelberg Engineering, Heidelberg, Germany) in enhanced depth imaging (EDI) mode. Subfoveal choroidal thickness (SFCT) was measured on the foveal line scan by 2 retinal experts independently (YS and KT), and the average was used in the analyses. In Chinese and Indian cohorts in whom macular raster scans were captured, the manufacturer-supplied research software (Heyex SP-X version 6.4.8.116; Heidelberg Engineering) was used to obtain automated segmentation yielding mean choroidal thickness in each of the 9 ETDRS grid sectors. Main Outcome Measures Subfoveal choroidal thickness and regional CT in the 9 ETDRS grid sectors. Results For the SFCT analysis, 2794 eyes of 1619 participants (Chinese, Indian, and Malay ) were included. The mean age was 60.9 years (standard deviation, 7.7), and 797 (49.2%) were male. Mean SFCT was 255.2 μm (standard deviation, 102.6). The normal range of SFCT was 106 to 447 μm (corresponding to 5th and 95th percentile limits of SFCT, respectively). In multivariable models, thinner SFCT was associated with older age, female gender, longer axial length, and Malay (vs. Chinese) ethnicity. In the subset of Chinese and Indian eyes (n = 1842) in whom regional variation was evaluated, the choroid was thickest at the superior and temporal sectors and thinner at the inferior and nasal sectors. Conclusions Subfoveal choroidal thickness is influenced by age, gender, and ethnicity along with regional differences even within individual eyes. Subfoveal choroidal thickness also shows a wide range in physiologic limits. These data may be used as a reference in future studies.

In this study, the camera angle of a UAV (Unmanned Aerial Vehicle) was adjusted to take aerial photographs, and 2D and 3D models were constructed to evaluate the quantitative impact. The study area was Waryong Bridge, located in Dalseong-gun, Daegu Metropolitan City. The camera angles of the UAV were 90°, 75°, and 60°; DSM, orthophoto, and the 3D model were analyzed. As a result of the analysis of DSM and orthophoto, images were 1.05 times in 75° and 1.10 times in 60° compared to 90°, and matching was 1.09 times in 75° and 1.60 times in 60° compared to 90°. The point cloud for building 3D models increased analysis points to 1.17 times for 75° and 1.47 times for 60° compared to 90°. However, the area of an orthophoto of 1 pixel increased by 1.10 times for 75° and 1.34 times for 60° compared to 90°, resulting in a decrease in resolution. As the camera angle of the UAV decreases, the overlapping ratio of aerial photographs increases and the structure of wide areas can be implemented. However, since a large difference occurs in the precision of the 3D model, a shooting plan according to the purpose should be established.

Atropine eye drops prevent the progression of myopia, but their use has not been tested in the Japanese schoolchildren population. Here, we evaluate the efficacy and safety of 0.01% atropine eye drops for myopia control in Japanese children. Multicenter (7 university hospitals), randomized, double-masked, placebo-controlled trial. Participants were 171 Japanese schoolchildren aged 6 to 12 years, with progressive myopia, spherical equivalence (SE) of −1.00 to −6.00 diopters (D), and astigmatism of ≤1.5 D. They were randomized to receive either 0.01% atropine (n=85) or placebo (n=86) eye drops once nightly OU for 24 months. Primary and secondary efficacy endpoints were changes in SE and axial length (AL), respectively, from baseline to month 24. Data from 168 subjects were analyzed. At month 24, compliance was similar in both groups (atropine: 83.3%; placebo: 85.7%). The least squares mean change in SE and AL from baseline were, respectively, −1.26 D (95% confidence interval [CI]: −1.35, −1.17) and 0.63 mm (0.59, 0.67) for atropine and −1.48 D (− 1.57, −1.39) and 0.77 mm (0.73, 0.81) for placebo. Inter-group differences were 0.22 D (95% CI: 0.09, 0.35; P

Recently, unmanned aerial vehicles (UAVs) have been used in various fields, such as military, logistics, transportation, construction, and agriculture, making it possible to apply the limited activities of humans to various and wide ranges. In addition, UAVs have been utilized to construct topographic data that are more precise than existing satellite images or cadastral maps. In this study, a monitoring point for preventing flood damage in an urban area was selected using a UAV. In addition, the topographic data were constructed using a UAV, and the flow of rainwater was examined using the watershed analysis in an urban area. An orthomosaic, a digital surface model (DSM), and a three-dimensional (3D) model were constructed for the topographic data, and a precision of 0.051 m based on the root mean square error (RMSE) was achieved through the observation of ground control points (GCPs). On the other hand, for the watershed analysis in the urban area, the point in which the flow of rainwater converged was analyzed by adjusting the thresholds. A monitoring point for preventing flood damage was proposed by examining the topographic characteristics of the target area related to the inflow of rainwater.

In recent years, machine learning techniques have been widely applied in seismological data processing such as seismic event detection, phase picking, location, magnitude estimation, and further data analysis for determining source mechanisms. Especially in earthquake location, deep learning methods are used to reduce location errors compared to conventional algorithms.In this study, we present a deep learning based epicentral distance estimation with two separate models using seismic data from two stations as input data. The first model is the P- and S-wave arrival time picking model and the second is the epicentral distance estimation model. Since the traditional epicentral distance estimation methods uses the difference in arrival times between P- and S-waves, the P- and S-wave arrival times were first predicted from three-component seismic data so that this information could be directly used as the next input data. This picking information is used as input data along with the station location in the epicentral distance estimation model to output the final epicentral distance. Since this method uses data from two stations, it has higher accuracy than epicentral distance estimation using data from a single station.The P- and S-wave arrival time picking model was modified by referring to the ResUNet (Diakogiannis et al., 2020) structure to improve performance based on the seismic detection and phase picking model from the three-component acceleration data developed by Mousavi et al. (2020). This modified model performs feature extraction for P- and S-phase picking and includes a residual block and skip connection. The model for estimating the distance from the epicenter was constructed using a basic artificial neural network (ANN) architecture. As input data, a total of eight features were used by adding six combinations of the difference in arrival times of P-wave and S-wave in each component of the two stations and two values of the latitude and longitude difference between two stations. The ANN architecture consists of four hidden layers and the epicentral distances of the two stations are final output.The STEAD data were used as training data and test data. The STEAD is a seismogram dataset recorded from about 450,000 global earthquakes, and among them, data with magnitudes greater than 2.5 and epicentral distances less than 400 km were selected and used. As a result of applying the trained model to the test data, the mean absolute error of the predicted epicentral distance was 6.5 km, which showed improved performance compared to the previous results. Also, since this method uses six time-differences as input data, it can provide more robust results even in the presence of random noise at the picked times.

Seismic reflection images derived by ambient-noise seismic interferometry (SI) can show subsurface structures without active sources. To image and interpret the upper mantle structures and tectonic boundaries beneath the southern part of Korean Peninsula, we applied SI method to seismic ambient noise data recorded at 119 seismic stations on the Korean Peninsula in 2014 (from the seismic network of the Korean Meteorological Administration). The factor that makes interpretation difficult is the steeply dipping events in reflection images. Most of these events of apparent steeply dips show as true reflection events from steep geologic boundaries. Therefore, we need to attenuate these events to interpret true reflection events. These events overlap many times. Also, the value of the slope has several values close to half of the Rayleigh waves or P waves. To attenuate these events with these complex features, we used machine learning techniques. We attenuated our steeply dipping events by applying the Extraction of diffractions method. As the steeply dipping events are attenuated, horizontal events were strengthened, and noises were attenuated. We can more clearly identify the reflection events of the Moho discontinuity and the lithosphere/asthenosphere (LAB) boundary near the two-way reflection times of 7-11 s and 17-22 s respectively.

Earthquake Early Warning System (EEW) is a technology that calculates earthquake parameter using P-wave that arrives earlier and warns the expected damage area before the arrival of destructive S wave. Therefore, many countries are operating EEW to mitigate damage from earthquake shaking. Especially an on-site EEW is drawn attention as it can reduce blind zones due to using only a single or minimum station. In the on-site EEW, it is important to quickly predict the seismic intensity, which indicates the degree of ground damage, response of structures and ground shaking felt by people at a given location, rather than information on the magnitude or distance of the earthquake.In this study, we suggest a machine learning (ML) model that can directly estimate the seismic intensity scale from initial P-waveforms of three-component acceleration data measured at a single station. We used 1D-Convolutional Neural Networks (1D-CNN), which have been shown good performance in signal processing of speech and medical data which are similar to earthquake signals. K-Net and KiK-net datasets, recorded at stations in Japan, were used for training the ML model. Since the amount of data is enough and all of data are labeled with Japan Meteorological Agency Seismic Intensity Scale (IJMA), the datasets were used as training data in this study. The developed model produced fast and accurate results using only the three-component acceleration field data at a single station.In order to test applicability of the trained model to the new dataset acquired from other regions, the trained model was applied to the STEAD data which were recorded at stations distributed globally. When the trained model was applied to STEAD data directly, the prediction results were worse than those of K-Net and KiK-net data. The reason is that the characteristics of the ground and waveforms are different depending on the region. Therefore, to solve this problem, transfer learning was applied, and only the parameters of a fully connected layer of pretrained ML model were fine-tuned using small number of both labeled target dataset and training dataset used for pretraining. Moreover, by considering the imbalance problem of the training data for transfer learning, it was able to obtain better prediction results. Ultimately, this study shows the pretrained model with a specific region dataset can provide reasonable prediction of seismic intensity to new dataset acquired from other regions using transfer learning.

Purpose We aimed to explore the velocity waveform characteristics of the retinal artery associated with age and the cardio-ankle vascular index (CAVI) as a conventional arterial stiffness marker by applying the Doppler optical coherence tomography (DOCT) flowmeter. Methods In this cross-sectional study, DOCT flowmeter imaging was performed in 66 participants aged 21 to 83 years (17 men, 49 women) with no history of eye diseases and no systemic diseases, except for hypertension. Retinal blood velocity waveform was analyzed where several parameters in time (upstroke time, T1, T2, T3, and T4) and area under the waveform (area elevation, area declination, A1, A2, A3, and A4) were extracted. Systolic blood pressure-adjusted Pearson's coefficients were calculated to determine the correlations of each parameter with age or CAVI. Results Corrected upstroke time (UTc) was the waveform parameter most positively correlated with age (r = 0.497, P < 0.001). Area declination was the waveform parameter most negatively correlated with age (r = -0.682, P < 0.001) and CAVI (r = -0.601, P < 0.001). Conclusions We extracted the waveform parameters associated with the risks of arterial stiffening. The velocity waveform analysis of the retinal artery with DOCT flowmeter potentially could become a new method for arterial stiffness identification. Translational Relevance DOCT flowmeter could evaluate arterial stiffening in a different way from the conventional method of measuring arterial stiffening using pressure waveform. Because the DOCT flowmeter can easily, quickly, and noninvasively provide a retinal blood velocity waveform, this system could be useful as a routine medical examination for arterial stiffening.

To evaluate choroidal volume and thickness changes after photodynamic therapy (PDT) for chronic central serous chorioretinopathy (CSC). Chronic CSC eyes with a history of PDT were selected. Average choroidal volume, average choroidal thickness, the maximum and minimum choroidal thickness of the macula irradiated area and peripheral non-irradiated areas before and after one and three months of treatment were examined. A total of 14 patients with chronic CSC and 9 controls without any eye pathology were enrolled. The mean choroidal volume in CSC before and, and after one and three months of treatment were 2.36 (standard deviation: 0.70), 1.90 (0.69), 1.86 (0.66) mm3 for the central area, 1.25 (0.38), 1.14 (0.35), 1.13 (0.34) mm3 for superior nasal area, 1.47 (0.41), 1.28 (0.43), 1.26 (0.43) mm3 for superior temporal area, 1.07 (0.49), 0.95 (0.38), 0.93 (0.35) mm3 for inferior nasal area, 1.17 (0.38), 1.04 (0.32), 1.03 (0.33) mm3 for inferior temporal area. This study revealed the choroidal volume changes in a short period after PDT and a decrease in unirradiated choroidal volume was also shown after the treatment. The algorithm provided on the ARI Network enables to evaluate the choroidal changes quantitatively and qualitatively.

The purpose of this study was to evaluate the diagnostic performance of retinal blood flow (RBF) measured with the Doppler optical coherence tomography (OCT) segmental scanning method to distinguish between healthy and glaucoma eyes.Fifty-eight patients with normal tension glaucoma (NTG) who had a single-hemifield visual field defect and 44 age-matched healthy subjects were enrolled. Retinal nerve fiber layer thickness (RNFLT) was measured with swept-source OCT. Superior and inferior temporal arteries (TAs) and temporal veins (TVs) RBF were measured with Doppler OCT. The area under the curve (AUC) of the receiver operating characteristic (ROC) was used to compare the diagnostic performances in the damaged and normal hemispheres.Multivariate regression analysis showed TA RBF and TV RBF were significantly reduced in the damaged and normal hemispheres. The ROC analysis showed that the AUC for quadrant RNFLT, TA RBF, and TV RBF were 0.973, 0.909, and 0.872 in the damaged hemisphere, respectively. The AUC values in the normal hemisphere were 0.783, 0.744, and 0.697, respectively. The combination of quadrant RNFLT and TA/TV RBF had a greater AUC than quadrant RNFLT alone in both damaged (AUC = 0.987) and normal (AUC = 0.825) hemispheres.In NTG eyes with single-hemifield damage, the RBF was found to be significantly reduced in the damaged and normal hemispheres independent from structural changes. The combination of RNFLT and RBF could improve diagnostic performances for glaucoma.Combining morphological and blood flow measurements with Doppler OCT may be useful in glaucoma diagnosis.

This study aimed to investigate the influence of educational pressure on myopia. A less-intense school curriculum was introduced nationally in Japan beginning in 2012 based on a pressure-free education policy. In this retrospective observational study, a total of 1025 Japanese medical students of Asahikawa Medical University underwent measurements of the cycloplegic refractive error and axial length (AL), from 2011 to 2020. The spherical equivalent (SE) and AL were correlated significantly with the fiscal year of births (p = 0.004 and p = 0.034, respectively) only during enforcement of the system of high-pressure education. The SE and AL regression rates during the two educational approaches differed significantly (p = 0.004 and p = 0.037, respectively). The prevalence of high myopia was correlated significantly (p &lt, 0.001) only during the system of high-pressure education. The regression of the prevalence rate of high myopia during the two education approaches differed significantly (p = 0.010). The progression rates of myopia and increased prevalence of high myopia were observed only during high-pressure education, suggesting that not only ophthalmologists but also educators and the government should work on together to control the progression of myopia.

The current study aimed to address whether ripasudil, a Rho-associated coiled-coil containing protein kinase (ROCK) inhibitor developed to treat glaucoma and ocular hypertension (OH), improves diabetic macular edema (DME) since it is known that ROCK upregulates vascular endothelial growth factor. We retrospectively investigated the foveal thickness (FT) measured by spectral-domain optical coherence tomography, visual acuity (VA), and intraocular pressure (IOP) in 12 eyes with DME that received ripasudil treatment for primary open-angle glaucoma or OH and compared them with 14 eyes that received no treatment. One month after ripasudil therapy, the mean FT decreased significantly from 439 ± 72 µm to 395 ± 62 µm (P = 0.003); this change was significantly different from that in the controls, in which the mean FT increased by 1 ± 39 µm (P = 0.01). Ripasudil also caused a significant decrease in IOP from 17.3 ± 5.2 mmHg to 14.6 ± 4.0 mmHg (P = 0.02); this change was significantly greater than that in the controls, in which IOP changed by 0.0 ± 1.6 mmHg (P

Cu nanofoams are promising materials for a variety of applications, including anodes in high-performance lithium-ion batteries. The high specific surface area of these materials supports a high capacity and porous structure that helps accommodate volume expansion which occurs as batteries are charged. One of the most efficient methods to produce Cu nanofoams is the dealloying of Cu alloy precursors. This process often yields nanofoams that have low strength, thus requiring additional heat treatment to improve the mechanical properties of Cu foams. This paper provides the effects of heat treatment on the microstructures, mechanical properties, and electrochemical performance of Cu nanofoams. Annealing was conducted under both inert and oxidizing atmospheres. These studies ultimately reveal the underlying mechanisms of ligament coarsening during heat treatment.

How underlying mechanisms bias evolution toward predictable outcomes remains an area of active debate. In this study, we leveraged phenotypic plasticity and parallel adaptation across independent lineages of Trinidadian guppies (Poecilia reticulata) to assess the predictability of gene expression evolution during parallel adaptation. Trinidadian guppies have repeatedly and independently adapted to high- and low-predation environments in the wild. We combined this natural experiment with a laboratory breeding design to attribute transcriptional variation to the genetic influences of population of origin and developmental plasticity in response to rearing with or without predators. We observed substantial gene expression plasticity, as well as the evolution of expression plasticity itself, across populations. Genes exhibiting expression plasticity within populations were more likely to also differ in expression between populations, with the direction of population differences more likely to be opposite those of plasticity. While we found more overlap than expected by chance in genes differentially expressed between high- and low-predation populations from distinct evolutionary lineages, the majority of differentially expressed genes were not shared between lineages. Our data suggest alternative transcriptional configurations associated with shared phenotypes, highlighting a role for transcriptional flexibility in the parallel phenotypic evolution of a species known for rapid adaptation.

Purpose It has been reported that peripapillary loops develop after central retinal artery occlusion (CRAO). Although cilioretinal anastomoses have been shown by fluorescein angiography (FA) and indocyanine green angiography, these examinations cannot confirm the structural continuity between the retinal arteries and the posterior ciliary arteries. In the current report, we followed a patient with iatrogenic CRAO in which circumpapillary collaterals formed and assessed the connection between these two vascular systems using optical coherence tomography angiography (OCTA). Observation Iatrogenic CRAO developed in the left eye of a 30-year-old woman during preoperative embolization of a convexity meningioma. FA and OCTA showed complete impairment of the retinal circulation. Two weeks after this event, OCTA images showed flow in the retinal vessels and the beginning of collateral vessel development on the optic disc margin. Six months later, OCTA images showed that these circumpapillary collaterals connected branches of the retinal arteries with the vessels supplying the optic disc, which originate from the posterior ciliary arteries. Conclusion and importance OCTA aided our understanding of the three-dimensional configuration of the circumpapillary collaterals that developed after iatrogenic CRAO, which included anastomosis of the retinal and posterior ciliary artery systems. OCTA is useful for noninvasively monitoring the status of retinal circulatory dynamics after iatrogenic CRAO.

Background: Doppler optical coherence tomography (DOCT) flowmeter can be used to measure retinal blood flow (RBF) parameters, including vessel diameter, blood velocity, and the absolute value of RBF within 2.0 s. We investigated the RBF parameters in eyes with branch retinal vein occlusion (BRVO) using a DOCT flowmeter. Methods: Seventeen patients with unilateral BRVO were enrolled. All subjects underwent comprehensive ophthalmologic examinations. The RBF parameters were assessed from three veins, i.e., (1) an occluded vein, (2) a non-occluded vein in the BRVO eyes, and (3) an equivalent (superior or inferior) vein in the fellow eye (non-affected vein), using prototype DOCT flowmeter (Topcon, Tokyo, Japan). Moreover, the correlation between RBF parameters and the best corrected visual acuity (BCVA) was examined. We investigated the correlation between (1) the RBF parameters and the time from the initial visit, (2) the RBF parameters and the time from the last injection, and (3) the RBF parameters and the number of anti-vascular endothelial growth factor injections (VEGF). Results: The diameter of the occluded vein (95.9 &plusmn, 24.7 &micro, m) was smaller than that of the non-occluded vein (127.9 &plusmn, 23.7 &micro, m) and that of the healthy veins (116.4 &plusmn, 13.9 &micro, m). The RBF was lower in the occluded veins (4.7 &plusmn, 3.7 &micro, L/min) than that in the non-occluded veins (10.3 &plusmn, 5.1 &micro, L/min, p &lt, 0.01) and in the fellow eyes (8.6 &plusmn, 4.0 &micro, p = 0.013). In contrast, the blood velocity was not significantly different among the three types of veins. BCVA was correlated with the diameter of the occluded vein (&rho, = 0.711, p = 0.001) but not with the RBF and blood velocity. The time from the initial visit, the time from the last injection, and the total number of anti-VEGF injections were not associated with any RBF parameters on the occluded vein. Conclusions: The RBF was significantly lower in the occluded veins than that in the other veins, and the diameter of the occluded vein was significantly smaller than that of the other veins in patients with BRVO. However, neither the time from the initial visit, nor the time from the last injection, nor the number of anti-VEGF injections were correlated with the RBF parameters on the occluded vein.

Among natural disasters, droughts can affect a large area for a prolonged period of time. If a drought happens, an appropriate response requires a lot of time and manpower from beginning to end, and continuous management is necessary for further prevention. Using data on drought damages from 1900 to 2018 in 148 countries in six continents around the world, this study was able to set quantitative standards for mega-droughts. According to data on the status of annual drought damages, the frequency of drought damages (1900&ndash, 2018) and the subsequent damage costs (1965&ndash, 2018) are increasing, while human losses (1900&ndash, 2018) are decreasing. Additionally, Africa had the highest frequency of drought damages, while Africa and Asia were ranked at the top of the list in terms of human losses and damage costs, respectively. Droughts persisted for continuous periods ranging from 1 to 17 years, and the total number of cases involving drought damage was estimated to be 600 in total, with total human losses of 11,731,294 people and total accumulated damage costs of $17,367,007,000. This study provided quantitative standards for the frequency of drought damages, human losses, and damage costs for mega-droughts in consideration of continuous drought periods. This study set the quantitative standards for a mega-drought as follows: (1) if drought damages continue to occur in a country for more than seven years, (2) if human losses continue to occur in a country for more than seven years, and (3) if mean annual damage costs of $17,000,000 continue to occur in a country for more than seven years.

Inundation damage occurs in urban regions due to short flood reach time and increased surface runoff caused by urbanized impervious areas. Furthermore, heavy rainfall frequency has increased because of climate change, thus exceeding the design frequency and resulting in sewer pipes&rsquo, lack of flood control capacity, with damage expanding from low-lying areas. Despite many urban disaster-mitigation policies, complex causes and uncertainties make reducing urban inundation damage difficult. This study established a rainfall-related disaster-prevention standard by time duration considering rainfall characteristics targeting urban disaster-induced inundation damage. Based on the South Korean urbanization rate and population, seven target regions were selected. Rainfall by time duration was analyzed with respect to disaster length (number of days) from 2010&ndash, 2017. The average rainfall for durations from 1&ndash, 24 hours were analyzed according to disaster length (1&ndash, 13 days). Using the results, an equation was proposed for rainfall estimation by length of disaster resulting in urban inundation damage, through multiple regression analysis. An equation was developed for rainfall-related disaster-prevention in urban areas considering the length of disaster and rainfall duration. This was accomplished by selecting a duration whereby the average rainfall of duration corresponded to 50% of total rainfall during the disaster period.

Purpose We aimed to observe longitudinal changes in retinal blood flow (RBF) and structural transformations in capillaries using Doppler optical coherence tomography (DOCT) and optical coherence tomography angiography (OCTA) in a feline retinal blood occlusion (RVO) model. Methods RVO was induced by argon green laser photocoagulation (PC) in six eyes of six cats. RBF was measured at a first-order retinal artery and vein by a DOCT flowmeter, and structural changes in the capillaries around the occluded vessels (12 × 12 and 3 × 3 mm) were assessed by OCTA before (at baseline); immediately after PC; and on days 1, 4, 7, and 14 thereafter. Systemic and ocular parameters were monitored during the observation period. Results There were no significant differences in any systemic or ocular parameters before and after PC. Arterial RBF increased significantly on day 1 (160.6 ± 8.6% vs. baseline, P < 0.001) and decreased below baseline after day 1 through 14. Venous RBF decreased immediately after PC (17.4 ± 9.6% vs. baseline, P = 0.001) and then gradually increased afterwards, but did not return to baseline. OCTA showed dilatation of retinal venules immediately after PC to day 1. Collateral vessels began to form on day 4, had matured by day 7, and were pruned on day 14, which formed as mature as normal retinal venule diameters. Conclusions With increasing arterial RBF within 1 day after inducing RVO, venules gradually expanded to form collateral vessels, suggesting that collateral vessels originate from existing capillary networks, not neovascularization.