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The accurate segmentation of cracks in structural materials is crucial for assessing the safety and durability of infrastructure. Although conventional segmentation models based on deep learning techniques have shown impressive detection capabilities in these tasks, their performance can be restricted by small amounts of training data. Data augmentation techniques have been proposed to mitigate the data availability issue; however, these systems often have limitations in texture diversity, scalability over multiple physical structures, and the need for manual annotation. In this paper, a novel generative artificial intelligence (GAI)-driven data augmentation framework is proposed to overcome these limitations by integrating a projected generative adversarial network (ProjectedGAN) and a multi-crack texture transfer generative adversarial network (MCT2GAN). Additionally, a novel metric is proposed to evaluate the quality of the generated data. The proposed method is evaluated using three datasets: the bridge crack library (BCL), DeepCrack, and Volker. From the simulation results, it is confirmed that the segmentation performance can be improved by the proposed method in terms of intersection over union (IoU) and Dice scores across three datasets. [ABSTRACT FROM AUTHOR]

This study investigated whether economic motivations are a key factor in international migration decisions. Applying the selectivity-corrected expected income for migrants and stayers, the difference in expected income for an individual in origin and destination countries was analyzed. This study used data from the U.S. and Canada to empirically test the role of income gaps in migration decisions. The main difficulty in analyzing the role of the gaps lies in collecting both income streams for the same individual, since once an individual migrates to a different country, their potential income in the origin country cannot be observed; and vice versa for stayers. Therefore, directly applying the average income of migrants (conditionally relying on their observed characteristics) to estimate the income of stayers if they had migrated results in a biased estimate of stayers' income. Hence, there is a need to account for selectivity in the migration decision and calculate selectivity-corrected income. The key finding in this study is that the expected income gap is positively associated with, and statistically significant for, international migration decisions for the U.S. and Canada. One of the main reasons may be the easy transfer of labor skills between countries that have similar labor environments and cultural backgrounds. [ABSTRACT FROM AUTHOR]

The transition to smart grids has served to transform traditional power systems into data-driven power systems. The purpose of this transition is to enable effective energy management and system reliability through an analysis that is centered on energy information. However, energy theft caused by vulnerabilities in the data collected from smart meters is emerging as a primary threat to the stability and profitability of power systems. Therefore, various methodologies have been proposed for energy theft detection (ETD), but many of them are challenging to use effectively due to the limitations of energy theft datasets. This paper provides a comprehensive review of ETD methods, highlighting the limitations of current datasets and technical approaches to improve training datasets and the ETD in smart grids. Furthermore, future research directions and open issues from the perspective of generative AI-based ETD are discussed, and the potential of generative AI in addressing dataset limitations and enhancing ETD robustness is emphasized. [ABSTRACT FROM AUTHOR]

In a filtration system, a chemical cartridge packed with porous adsorbents needs to be replaced when its maximum adsorption capacity is exceeded. An end of service life indicator (ESLI) informs when to replace the cartridge. However, ESLI technology for filtration of toxic gases is overlooked despite high toxicity of the gases even at low concentrations. In this study, a real‐time ESLI is demonstrated for filtration of chemical warfare agents by inserting four chemiresistors made of carbon nanotubes into the adsorbent layer of a canister for gas masks. The sensors are installed on a flexible printed circuit board with a 3D structure to minimize the channeling effect in the canister. As the breakthrough of dimethyl methylphosphonate, a nerve agent simulant, progresses in the canister, the resistance of the sensors increases sequentially with time. The inflection points in the responses from sensors designated #1–#4 indicate that the percentage of remaining service life is 75%, 50%, 25%, and 0%, respectively. The ESLI potentially applies to a wide range of toxic gases and cartridge designs, regardless of the sensitivity and selectivity of the sensors, as supported by the breakthrough of ammonia as well as the results from a smaller canister. [ABSTRACT FROM AUTHOR]

Background: Skin pores are structural features of the skin, which tend to change as the skin ages. Since previous studies measured pores two‐dimensionally, precise measurements using three‐dimensional imaging were needed to comprehensively understand skin pores. This study aimed to determine the patterns behind the changes in skin pores during one's lifetime and to identify new characteristics of the pores in aged. Materials and Methods: Skin surface profiles were measured three‐dimensionally from the cheeks of 101 Korean women from February to March 2020 to analyze the exact state of their pores. The researchers performed K‐means clustering to classify the skin pores, and topographical features of pores were analyzed as well. Statistical analyses were performed to verify the differences in the skin pore characteristics among clusters and the correlation between clusters and ages. Results: Skin pores were classified into five groups based on size, density, and elongation. The skin conditions of the cluster groups were well correlated with aging, despite excluding age as a factor in pore classification. Adjacent skin pores tend to connect in the elderly. Conclusion: Skin pores become larger and longer over time. Skin pores connect together in the elderly, which might be related to wrinkle formation. This phenomenon strongly suggests skin pores as a characteristic of aging skin and as a potential target for anti‐aging treatment. [ABSTRACT FROM AUTHOR]