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This study explores the role of regional trade agreements (RTAs) in mitigating the negative effects of uncertainty on trade, focusing on their depth and differential impacts on global value chain (GVC) and traditional trade. By employing an augmented gravity model with data from 70 countries spanning 1995 to 2020, the analysis reveals that deep RTAs, incorporating WTO-plus and WTO-extra provisions beyond tariff reductions, significantly alleviate the negative effects of uncertainty on both GVC and traditional exports. In contrast, shallow RTAs do not provide such mitigation. This study further highlights the resilience of GVC trade to uncertainty, driven by relationship-specific investments and long-term partnerships, while also recognizing its vulnerability to cumulative trade costs. Deep RTAs demonstrate more pronounced and persistent uncertainty-mitigation effects for GVC trade compared to traditional trade. Furthermore, we also find that WTO-extra provisions exert a more pronounced impact on both GVC and traditional exports. These findings underscore the critical importance of deep RTAs in fostering economic resilience and sustaining global supply chains amidst increasing global uncertainties, offering valuable policy implications for the design of trade agreements.

The frequency and magnitude of natural hazards have been steadily increasing, largely due to extreme weather events driven by climate change. These hazards pose significant global challenges, underscoring the need for accurate prediction models and systematic preparedness. This study aimed to predict multiple natural hazards in South Korea using various machine learning algorithms. The study area, South Korea (100,210 km2), was divided into a grid system with a 0.01° resolution. Meteorological, climatic, topographical, and remotely sensed data were interpolated into each grid cell for analysis. The study focused on three major natural hazards: drought, flood, and wildfire. Predictive models were developed using two machine learning algorithms: Random Forest (RF) and Extreme Gradient Boosting (XGB). The analysis showed that XGB performed exceptionally well in predicting droughts and floods, achieving ROC scores of 0.9998 and 0.9999, respectively. For wildfire prediction, RF achieved a high ROC score of 0.9583. The results were integrated to generate a multi-hazard susceptibility map. This study provides foundational data for the development of hazard management and response strategies in the context of climate change. Furthermore, it offers a basis for future research exploring the interaction effects of multi-hazards.

Climate change has intensified natural hazards, including droughts, which have caused substantial damage in South Korea. Drought, characterized by prolonged moisture deficiency, is typically assessed using drought indices that reflect meteorological conditions. This study examined the influence of various meteorological and climate indices on drought variability in the Yeongsan and Seomjin River basins. The Standardized Precipitation Index (SPI) was used to represent drought conditions, and its monthly variations were predicted using the Long Short-Term Memory (LSTM) algorithm. To assess model performance, four statistical indicators—Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Nash–Sutcliffe Efficiency (NSE), and the Coefficient of Determination (R2)—were employed. The LSTM model that utilized both precipitation and drought indices as input data showed the best performance, achieving an MSE of 0.2, RMSE of 0.477, NSE of 0.77, and R2 of 0.78. Overall predictive performance ranged from 0.298 to 0.347 (MSE), 0.546 to 0.589 (RMSE), 0.578 to 0.628 (NSE), and 0.580 to 0.675 (R2). This study highlights the effectiveness of LSTM in predicting drought conditions and the value of incorporating meteorological and climatic indices. The results can support improved drought hazard assessment and management strategies in South Korea.

A low arousal threshold (LAT) is a pathophysiological trait of obstructive sleep apnea (OSA) that may be associated with brainstem ascending reticular activating system-cortical functional connectivity changes. We evaluated resting-state connectivity between the brainstem nuclei and 105 cortical/subcortical regions in OSA patients with or without a LAT and healthy controls. Twenty-five patients with moderate to severe OSA with an apnea–hypopnea index between 20 and 40/hr (15 with and 10 without a LAT) and 15 age- and sex-matched controls were evaluated. Participants underwent functional magnetic resonance imaging after overnight polysomnography. Three brainstem nuclei—the locus coeruleus (LC), laterodorsal tegmental nucleus (LDTg), and ventral tegmental area (VTA)—associated with OSA in our previous study were used as seeds. Functional connectivity values of the two brainstem nuclei (LC and LDTg) significantly differed among the three groups. The connectivity of the LC with the precuneus was stronger in OSA patients than in controls regardless of the concomitant LAT. The connectivity between the LDTg and the posterior cingulate cortex was also stronger in OSA patients regardless of the LAT. Moreover, OSA patients without a LAT showed stronger LDTg-posterior cingulate cortex connectivity than those with a LAT (post hoc p  = 0.013), and this connectivity strength was negatively correlated with the minimum oxygen saturation in OSA patients (r = − 0.463, p  = 0.023). The LAT in OSA patients was associated with altered LDTg-posterior cingulate cortex connectivity. This result may suggested that cholinergic activity may play a role in the LAT in OSA patients.

Repeated arousals during sleep in obstructive sleep apnea (OSA) may lead to altered functional connectivity (FC) of the ascending reticular activating system (ARAS). We evaluated resting-state FC between eight ARAS nuclei and 105 cortical/subcortical regions in OSA patients and healthy controls. Fifty patients with moderate to severe OSA and 20 controls underwent overnight polysomnography and resting-state functional magnetic resonance imaging. Seed-to-voxel analysis of ARAS–cortex FC was compared between OSA patients and controls. The ARAS nuclei included the locus coeruleus (LC), laterodorsal tegmental nucleus (LDTg), and ventral tegmental area (VTA). FC values of three ARAS nuclei (the LC, LDTg, and VTA) significantly differed between the groups. FC of the LC with the precuneus, posterior cingulate gyrus, and right lateral occipital cortex (LOC) was stronger in OSA patients than controls. FC between the LDTg and right LOC was stronger in OSA patients than controls, but FC between the VTA and right LOC was weaker. Average LC–cortex FC values positively correlated with the arousal, apnea, and apnea–hypopnea index in OSA patients. Alterations in ARAS–cortex FC were observed in OSA patients. The strength of LC–cortex noradrenergic FC was related to arousal or OSA severity in patients.

Alzheimer's disease (AD) presents typically gray matter atrophy and white matter abnormalities in neuroimaging, suggesting that the gray-white matter boundary could be altered in individuals with AD. The purpose of this study was to explore differences of gray-white matter boundary Z-score (gwBZ) and its tissue volume (gwBTV) between patients with AD, amnestic mild cognitive impairment (MCI), and cognitively normal (CN) elderly participants. Three-dimensional T1-weight images of a total of 227 participants were prospectively obtained from our institute from 2006 to 2022 to map gwBZ and gwBTV on images. Statistical analyses of gwBZ and gwBTV were performed to compare the three groups (AD, MCI, CN), to assess their correlations with age and Korean version of the Mini-Mental State Examination (K-MMSE), and to evaluate their effects on AD classification in the hippocampus. This study included 62 CN participants (71.8 ± 4.8 years, 20 males, 42 females), 72 MCI participants (72.6 ± 5.1 years, 23 males, 49 females), and 93 AD participants (73.6 ± 7.7 years, 22 males, 71 females). The AD group had lower gwBZ and gwBTV than CN and MCI groups. K-MMSE showed positive correlations with gwBZ and gwBTV whereas age showed negative correlations with gwBZ and gwBTV. The combination of gwBZ or gwBTV with K-MMSE had a high accuracy in classifying AD from CN in the hippocampus with an area under curve (AUC) value of 0.972 for both. gwBZ and gwBTV were reduced in AD. They were correlated with cognitive function and age. Moreover, gwBZ or gwBTV combined with K-MMSE had a high accuracy in differentiating AD from CN in the hippocampus. These findings suggest that evaluating gwBZ and gwBTV in AD brain could be a useful tool for monitoring AD progression and diagnosis.

Blood inflammatory biomarkers have emerged as important tools for diagnosing, assessing treatment responses, and predicting neurodegenerative diseases. This study evaluated the associations between blood inflammatory biomarkers and brain tissue volume loss in elderly people. This study included 111 participants (age 67.86 ± 8.29 years; 32 men and 79 women). A battery of the following blood inflammatory biomarkers was measured, including interleukin 1-beta (IL1β), NACHT, LRR, and PYD domains-containing protein 3 (NLRP3), monomer Aβ42 (mAβ), oligomeric Aβ42 (oAβ), miR155, neurite outgrowth inhibitor A (nogo-A), phosphorylated tau (P-tau), and total tau (T-tau). Three-dimensional T1-weight images (3D T1WI) of all participants were prospectively obtained and segmented into gray matter and white matter to measure the gray matter volume (GMV), white matter volume (WMV), and gray-white matter boundary tissue volume (gwBTV). The association between blood biomarkers and tissue volumes was assessed using voxel-based and region-of-interest analyses. GMV and gwBTV significantly decreased as the levels of IL1β and T-tau increased, while no significant association was found between the level of P-tau and the three brain tissue volumes. Three brain tissue volumes were negatively correlated with the levels of IL1β, P-tau, and T-tau in the hippocampus. Specifically, IL1β and T-tau levels showed a distinct negative association with the three brain tissue volume losses in the hippocampus. In addition, gwBTV was negatively associated with the level of NLRP3. The observed association between brain tissue volume loss and elevated levels of IL1β and T-tau suggests that these biomarkers in the blood may serve as potential biomarkers of cognitive impairment in elderly people. Thus, IL1β and T-tau could be used to assess disease severity and monitor treatment response after diagnosis in elderly people who are at risk of cognitive decline.

When estimating human pose with a partial image of a person, we, humans, do not confine the spatial range of our estimation to the given image and can readily localize keypoints outside of the image by referring to visual clues such as the body size. However, computational methods for human pose estimation do not consider those keypoints outside and focus only on the bounded area of a given image. In this paper, we propose a neural network and a data augmentation method to extend the range of human pose estimation beyond the bounding box. While our Position Puzzle Network expands the spatial range of keypoint localization by refining the position and the size of the target’s bounding box, Position Puzzle Augmentation enables the keypoint detector to estimate keypoints not only within, but also beyond the input image. We show that the proposed method enhances the baseline keypoint detectors by 39.5% and 30.5% on average in mAP and mAR, respectively, by enabling the localization of keypoints out of the bounding box using a cropped image dataset prepared for proper evaluation. Additionally, we verify that the proposed method does not degrade the performance under the original benchmarks and instead, improves the performance by alleviating false-positive errors.

Background Apolipoprotein E (ApoE) ε4 carriers have a higher risk of developing Alzheimer's disease (AD) and show brain atrophy and cognitive decline even before diagnosis. Objective To predict ApoE ε4 status using gray matter volume (GMV) obtained from magnetic resonance imaging images and demographic data with machine learning (ML) methods. Methods We recruited 74 participants (25 probable AD, 24 amnestic mild cognitive impairment, and 25 cognitively normal older people) with known ApoE genotype (22 ApoE ε4 carriers and 52 noncarriers) and scanned them with three‐dimensional (3D) T1‐weighted (T1W) and 3D double inversion recovery (DIR) sequences. We extracted GMV from regions of interest related to AD pathology and used them as features along with age and mini–mental state examination (MMSE) scores to train different ML models. We performed both receiver operating characteristic curve analysis and the prediction analysis of the ApoE ε4 carrier with different ML models. Results The best model of ML analyses was a cubic support vector machine (SVM3) that used age, the MMSE score, and DIR GMVs at the amygdala, hippocampus, and precuneus as features (AUC = .88). This model outperformed models using T1W GMV or demographic data alone. Conclusion Our results suggest that brain atrophy with DIR GMV and cognitive decline with aging can be useful biomarkers for predicting ApoE ε4 status and identifying individuals at risk of AD progression. The ApoE ε4 genotype might be carried by an elderly participant with a low MMSE score and GMV reduction in the amygdala and hippocampus. This result is important to identify individuals who have a high risk for AD progression in the future.

BackgroundThis meta-analysis aimed to evaluate the association between antiplatelet resistance and the risk of procedure-related complications in neurovascular interventions.MethodsWe identified relevant articles by searching electronic databases and reviewed the reference lists of selected papers. The risk of adverse events between antiplatelet responders and hyporesponders during neurointervention was compared in eligible clinical studies. Risk ratios (RRs) and 95% CIs were pooled using a random-effects meta-analysis.ResultsOf 2134 potentially relevant studies, our search identified 15 studies enrolling a total of 2365 patients. Pooled RRs showed thromboembolic events (TEE) were more frequent in hyporesponders (RR 2.634, 95% CI 1.465 to 4.734). However, hemorrhagic complications did not differ between the two groups (RR 1.236, 95% CI 0.642 to 2.380). In subgroup analysis, hyporesponders showed a higher prevalence of TEE with standard antiplatelet medication, but there was no obvious difference in TEE between the two arms when using a modified antiplatelet medication (RR 3.645, 95% CI 1.537 to 8.646; and RR 1.877, 95% CI 0.749 to 4.751). Studies using stent placement for aneurysms showed a higher TEE rate in hyporesponders (RR 3.221, 95% CI 1.899 to 5.464).ConclusionAntiplatelet resistance was significantly associated with TEE in neurointervention, and this adverse event was associated with individually-intensified antiplatelet medication as well as the type of neurointerventional procedure. Our findings support the use of antiplatelet resistance assays and tailored antiplatelet medications in neurovascular stent placement as a management strategy to reduce thromboembolic risk.