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Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs. Changes in FSIN physiology and cortical E–I balance underlying pHFO generation are not fully understood. Here authors show net synaptic drive at FSINs from excitation to inhibition represents the major epileptogenic mechanism of FCD I epilepsy.

Stretchable hybrid electronics (SHE) that combine high-performance rigid electronic devices with stretchable interconnects offer a facile route for accessing and processing bio-signals and human interactions. Incorporated with sensors and wireless communications, SHE achieves novel applications such as biomedical diagnosis, skin prosthetics, and robotic skin. The implementation of reliable SHE requires the comprehensive development of stretchable electrodes, bonding techniques, and strain-engineered integration schemes. This review covers the recent development of enabling technologies for SHE in terms of materials, structures, and system engineering. We introduce various strategies for stretchable interconnects based on novel materials and structural designs. In particular, we classify SHE into three groups based on strain-relief configurations: thin-film devices on rigid islands, rigid devices with stretchable bridges, and flexible circuits with stretchable bridges. Appropriate methods for substrates, stretchable interconnects, and bonding between rigid and soft components and their pros and cons are extensively discussed. We also explore state-of-the-art SHE in advanced human-machine interfaces and discuss the challenges and prospects for future directions.

Reliable long-range reservoir inflow forecast is essential to successfully manage water supply from reservoirs. This study aims to develop statistical reservoir inflow forecast models for a reservoir watershed, based on hydroclimatic teleconnection between monthly reservoir inflow and climatic variables. Predictability of such a direct relationship has not been assessed yet at the monthly time scale using the statistical ensemble approach that employs multiple data-driven models as an ensemble. For this purpose, three popular data-driven models, namely multiple linear regression (MLR), support vector machines (SVM) and artificial neural networks (ANN) were used to develop monthly reservoir inflow forecasting models. These models have been verified using leave-one-out cross-validation with expected error S as a measure of forecast skill. The S values of the MLR model ranged from 0.21 to 0.55, the ANN model ranged from 0.20 to 0.52 and the SVM from 0.21 to 0.56 for different months. When used as an ensemble, Bayesian model averaging was more accurate than simple model averaging and naïve forecast for four target years tested. These were considered to be decent prediction skills, indicating that teleconnection-based models have the potential to be used as a tool to make a decision for reservoir operation in preparing for droughts.

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R2 = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R2 = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R2 = 0.95) than that of the HYDRUS-1D’s own optimization module (R2 = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations.

Floods can have adverse health effects and impose a burden on healthcare systems. However, the potential consequences of floods on specific medical causes in densely populated metropolitan cities has not been characterized yet. Therefore, we evaluate the changes in healthcare utilization patterns after the 2022 Seoul flood using nationwide health insurance data. Based on the flood inundation map, districts within the flooded municipalities of Seoul were classified as severe‐(n = 12), mild‐(n = 22), or non‐(n = 38) flood‐affected districts. Capitalizing on the timing of the flood as a natural experiment, a generalized synthetic control method was applied to estimate changes in the number of disease‐specific hospital visits in flood‐affected districts during 2 weeks after the flood. We found excess hospital visits for external injuries (20.2 visits, 95% CI: −6.0, 45.2) and fewer visits for pregnancy and puerperium (−3.0 visits, 95% CI: −5.1, −0.5) in residents of flooded districts. When comparing severe‐ and non‐flood districts, the increase in hospital visits for external injuries (56.2 visits, 95% CI: 17.2, 93.2) and a decrease in hospital visits related to pregnancy and puerperium (−5.3 visits, 95% CI: −8.4, −1.6) were prominent in residents living in severe‐flood affected districts. Disease specific analysis showed an increase in hospital visits for injuries to the elbow and forearm, ankle and foot injuries, and chronic lower respiratory diseases in severe‐flood‐affected districts. However, these impacts were not observed when comparing the mild‐ and non‐flood‐affected districts. Our study suggests an immediate and substantial change in medical demand following flood exposure, highlighting the importance of public health responses after flood events. Plain Language Summary This study evaluated the acute medical demands after a 2022 Seoul Metropolitan City flooding event, highlighting the need for preparedness and response to future flood disasters. We observed an increase in hospital visits related to external injuries and chronic lower respiratory infection and a decrease in pregnancy and puerperium related hospital visits in residents of severely flood‐affected districts. However, such changes were not observed in residents of mildly flood‐affected districts. Future healthcare management plans following flood should include adjustments to changes in the demand for medical services during and after flood events. Key Points We evaluated the changes in healthcare utilization patterns after 2022 Seoul flood The universal health insurance data and a generalized synthetic control were used There was an increase in injuries and a decrease in pregnancy related hospital visits after flood

We can prevent climate change by reducing greenhouse gas (GHG) emissions caused by fossil fuel usage through introducing alternative fuels such as bio-oil. The fast pyrolysis process used for wood materials has recently gained substantial attention as an approach to produce bio-oil worldwide and in Korea as well. Bio-oil from fast pyrolysis contains highly oxygenated compounds and phenolics, thereby requiring upgrading processes, such as deoxygenation and condensation, for high-end use. To determine an efficient upgrading method for fast pyrolysis bio-oil (FPBO), one needs to elucidate its composition and classify it into chemical groups. We analyzed the composition of fractionized FPBO toward high-end use. FPBO was separated into two layers by adding distilled water: (a) the water-soluble phase, and (b) the oil phase, whereas liquid-liquid extraction and multi-step separation were applied for fractionization, respectively. The fractions were obtained, and their chemical groups were analyzed by gas chromatography time-of-flight mass spectrometry (GC×GC-TOF/MS). The water phase was separated into two fractions and classified into the main chemical groups of phenolics (9%) and heterocyclics (31%). The oil phase, which was separated into four fractions, was classified into the main chemical groups of phenolics (32%) and heterocyclics (23%). Our findings can help to upgrade products for high-end use.

Adaptive and extreme changes in shape and configuration are the functional and morphological uniqueness of soft robots, but existing design approaches still rely on the predefined coordination of their “muscle” and “nerve” functions to produce such behaviors. Herein, a strategy is introduced for building modular soft machines that can be innervated in ways that conform to their body extension or shape changes, based on modular soft electronics. The development of soft electronic adhesive interlocking (SEAL) technology allows for instant, robust, and repeatable integration of soft electronic modules that can “innervate” and activate modular soft actuators and machines in a reconfigurable manner. Demonstrations of soft robotic tentacles and their grasping capability show that the robot function can be adapted to or reconfigured within the body with a length extended more than 10 times. The modular strategy presented herein can offer a unique promise to build up future robots with dynamic, reconfigurable functions. Soft electronic adhesive interlocking facilitates reconfigurable electronic innervation of modular soft machines by providing robust Van der Waals adhesion, mechanical interlocking, and high conductivity. This mechanism allows instant, repeatable integration of soft electronic modules demonstrated through modularized soft robots that adaptively and selectively innervate electronic modules for effective body shape changes.

Extreme precipitation events have been extensively applied to the design of social infra structures. Thus, a method to more scientifically estimate the extreme event is required. This paper suggests a method to estimate the extreme precipitation in Korea using a regional climate model. First, several historical extreme events are identified and the most extreme event of Typhoon Rusa (2002) is selected. Second, the selected event is reconstructed through the Weather Research and Forecasting (WRF) model, one of the Regional Climate Models (RCMs). Third, the reconstructed event is maximized by adjusting initial and boundary conditions. Finally, the Probable Maximum Precipitation (PMP) is obtained. The WRF could successfully simulate the observed precipitation in terms of spatial and temporal distribution (R2 = 0.81). The combination of the WRF Single-Moment (WSM 6-class graupel scheme (of microphysics), the Betts-Miller-Janjic scheme (of cumulus parameterization) and the Mellor-Yamada-Janjic Turbulent Kinetic Energy (TKE) scheme (of planetary boundary layer) was determined to be the best combination to reconstruct Typhoon Rusa. The estimated PMP (RCM_PMP) was compared with the existing PMP. The RCM_PMP was generally in good agreement with the PMP. The suggested methodology is expected to provide assessments of the existing PMP and to provide a new alternative for estimating PMP.

A major industrial fire accident occurred in a tire manufacturing factory in Daejeon, Korea, on 12 March 2023 and lasted for 3 d, generating air pollutant emissions. Although evidence regarding the health effects of urban fires is limited, residents near tire factory may have experienced health hazards due to smoke exposure from fire plumes. Capitalizing on the timing of this fire incident as a natural experiment, we estimated the attributable excess air pollution exposure and associated disease development among residents living near the tire factory. We used the generalized synthetic control method to estimate air pollution exposure and health burden attributable to the accident among residents living in smoke-exposed districts. Based on satellite images and air pollution monitoring results, three administrative districts (within from the factory) were defined as smoke-exposed, and the other 79 districts of Daejeon were defined as controls. Among the 11 monitoring stations in Daejeon, the station located from the factory was used to estimate excess air pollution exposure ( , , , , , and CO) for residents in the exposed districts. The number of daily district-level disease-specific incidence cases were acquired from the National Health Insurance Database and used to estimate excess health burden resulting from the fire. During the first week following the factory fire, residents of exposed districts had an estimated excess exposure to 125.2 [95% confidence interval (CI): 44.9, 156.7] of , 50.4 (95% CI: 12.7, 99.8) ppb of , and 32.0 (95% CI: 21.0, 35.9) ppb of . We also found an average increase in the incidence cases of other diseases of upper respiratory tract [20.6 persons (95% CI: 6.2, 37.4)], lung disease due to external agents [2.5 persons (95% CI: 2.1, 3.3)], urticaria and erythema [5.9 persons (95% CI: , 11.2)], and episodic and paroxysmal disorders [8.5 persons (95% CI: 3.7, 13.4)] in exposed districts. Excessive air pollution exposure and disease incidence were identified among residents living close to the tire factory. Preventive measures, such as a warning system, to avoid health impacts to people breathing fire-related pollution may be beneficial for communities impacted by such events. https://doi.org/10.1289/EHP14115.

We propose a novel real-time video stitching method using camera path estimation and homography refinement. The method can stably stitch multiple frames acquired from moving cameras in real time. In the proposed method, one initial between-camera (BC) homography and each camera path (CP) homography are used to estimate the BC homography at every frame. The BC homography is refined by using block matching to adjust the errors of estimated CPs (homography refinement). For fast processing, we extract features using the difference of intensities and use the optical flow to estimate camera motion (CM) homographies, which are multiplied with the previous CMs to calculate CPs (camera path estimations). In experiments, we demonstrated the performance of the CP estimation and homography refinement approach by comparing it with other methods. The experimental results show that the proposed method can stably stitch two image sequences at a rate exceeding 13 fps (frames per second).