Chungnam National University

Considerable levels of methylmercury (MeHg) have been found rice-based infant cereals as a result of MeHg transfer from the rice as a raw material to the products, hence consumption of rice products may pose a potential health risk to infants who may receive cereals as the major diets and are susceptible to toxicity of MeHg. Determination of bioaccessibility of MeHg would provide a more accurate assessment of MeHg exposure through consumption of rice-based cereals, yet this information remains lacking. Further, the re-adsorption of methylmercury on the residual food will affect the accurate assessment of its bioaccessibility. Our goals in this work were 1) to determine the bioaccessibility of MeHg in infant rice cereals commonly available on the market by using a typical in vitro artificial gastrointestinal digestion model and 2) to evaluate the effects of MeHg re-adsorption on the in vitro assessment of MeHg bioaccessibility. The determined bioaccessibility of MeHg in the studied rice cereals after the standard dual-step (using gastric followed by intestinal juice) protocol ranged from 25% to 74%, a wide range comparable to that of fish samples observed here and in previous studies. The surprisingly higher bioaccessibility of MeHg in fish and rice cereals after the gastric step only, in comparison to after the complete two-step gastrointestinal digestion, suggests the re-adsorption of MeHg on the residual food. Separate experiments with spiked MeHg standards confirmed that the MeHg released by the acetic gastric juice was re-adsorbed on the residues during the intestinal step at neutral pH. This study provided first-hand data on the bioaccessibility of MeHg in infant rice cereals and methodological implications on using in vitro digestion to evaluate the bioaccessibility of MeHg and metal contaminants in general.

Evaluating the pressure of atmospheric pollutant emissions on the atmospheric environment is crucial for effective pollution control and emission reduction policies. This study introduces a novel Atmospheric Environmental Pressure Index (AEPI) and employs a dynamic comprehensive method to evaluate China's Atmospheric Environmental Pressure (AEP) across 31 provinces from 2008 to 2017. The drivers of AEP were analyzed using a spatial panel data model, uncovering the integral role of pollution reduction policies, particularly the Air Pollution Prevention and Control Action Plan, which led to a 25% reduction in AEP during its enforcement. Our findings reveal significant spatial disparities in AEP, with higher levels in the Beijing-Tianjin-Hebei and Yangtze River Delta regions. The regression analysis identifies economic development, industrial structure, energy efficiency, environmental regulations, and urbanization as key influencing factors, though their impacts vary across different regions, suggesting the need for region-specific pollution control policies. Furthermore, the shift in the AEP gravity center from 2008 to 2017 indicated a southeastward movement, suggesting the necessity to focus air pollution control efforts on the southeast provinces. In conclusion, the AEPI developed in this study enables comparative analysis of AEP across different regions and facilitates the monitoring of long-term trends, which is valuable in guiding regional air pollution control in China.

The formation of the modern east-flowing Yangtze River is marked by the incision of the Three Gorges (TG) between the Sichuan and Jianghan basins. However, it is still controversial on the timing of the TG incision, due to diverse tectonic, sedimentological and geochemical records. These records, together with other geological data, i.e. curves of paleo-climate and sea level fluctuation, are critical parameters in the software Badlands , a tool to simulate large-scale and long-term geomorphic evolution. Using Badlands , we modeled the geomorphology and drainage evolutionary process of the Yangtze River since the Late Cretaceous (80 Ma). It revealed that the drainage system in the Sichuan Basin was gradually reversed from southward flowing to northward flowing during the Late Eocene and the Oligocene, due to the periodic uplift of the eastern Tibet Plateau and the southwestern Yangtze Block. Coevally, the Jianghan Basin experienced a base level drop, controlled by the collapse of a paleo-coastal mountain range and the subsequent continental rifting along the Southeast China continental margin. The tectono-geomorphic interplay eventually led to the incision of the TG at the Late Oligocene (about 24Ma), when the drainage system of the Upper Yangtze River was captured by the Middle-Lower Yangtze River.

Perforation is essential for the development of unconventional oil and gas, hydrogen, geothermal energy, and deep subsurface exploration, yet an effective evaluation method has remained elusive. The multiscale tomography (MST) method is applied to analyze downhole perforation, improving inversion accuracy through the multiscale discretization of velocity model grids. Numerical experiments demonstrate the method’s reliability in determining perforation depth intervals, radial penetration depths, and velocity variations outside the well. Simulations before and after perforation reveal significant traveltime changes, supported by logging data showing delays and velocity shifts. A comparison of imaging results with various receiver configurations highlights the critical role of receiver arrangement in achieving accurate subsurface imaging. These findings validate MST as an effective tool for perforation assessment and velocity imaging around wells, with an emphasis on optimal receiver configuration.

The practical use of the Transformer-based methods for processing videos is constrained by the high computing complexity. Although previous approaches adopt the spatiotemporal decomposition of 3D attention to mitigate the issue, they suffer from the drawback of neglecting the majority of visual tokens. This article presents a novel mixed attention operation that subtly fuses the random, spatial, and temporal attention mechanisms. The proposed random attention stochastically samples video tokens in a simple yet effective way, complementing other attention methods. Furthermore, since the attention operation concentrates on learning long-distance relationships, we employ the channel shift operation to encode short-term temporal characteristics. Our model can provide more comprehensive motion representations thanks to the amalgamation of these techniques. Experimental results show that the proposed method produces competitive action recognition results with low computational overhead on both large-scale and small-scale public video datasets.

Visual question answering (VQA) is a challenging task that requires models to understand both visual and linguistic inputs and produce accurate answers. However, VQA models often exploit biases in datasets to make predictions rather than reasoning based on the inputs. Prior approaches to debiasing have suggested the implementation of a supplementary model, deliberately designed to exhibit bias, which subsequently informs the training of a resilient target model. Nevertheless, such techniques merely quantify the model’s divergence based on the statistical distribution of labels within the training dataset or in relation to unimodal branches. In this work, we propose a novel method of generating bias from the target model itself, called LEGO, which aims to combat the language guidance bias. Specifically, LEGO framework employs a generative network that assimilates the biases inherent in the target model by integrating adversarial goals with the principles of knowledge distillation. Then, we use a debiased contrastive learning strategy to model the language guidance bias of caption and question. In the process of modelling, in order to obtain robust semantic coreference, the multi-modal representations of two semantic granularity are modelled by mutual information fusion and contrast learning difference modelling. We evaluate our method on various VQA-biased datasets, including VQA-CP2, GQA-OOD, and RSICD, and show that it outperforms similar methods.

AbstractClimate warming has led to the translocation of a large amount of terrestrial organic carbon (TerrOC) into the Arctic Ocean. The fate of TerrOC varies dramatically in the Arctic shelves, thus introducing uncertainty into the climate‐carbon feedback. In this study, we analyzed total organic carbon (TOC), stable organic carbon isotopes (δ13C) and lignin to investigate the spatial heterogeneity of sources and degradation of sedimentary OC on the East Siberian Arctic Shelf (ESAS). Furthermore, we also compared the cross‐shelf degradation of TerrOC between the ESAS and Beaufort Shelf. High lignin content (0.51–2.25 mg/100 mg OC) and relatively depleted δ13C (−27.47‰ to −25.72‰) indicate that sedimentary OC in the nearshore areas of Laptev Sea and East Siberian Sea is predominantly of terrestrial origin, while in the rest area of the ESAS, the contribution of marine OC plays a dominant role in the OC burial. The distribution results of OC loadings and degradation proxy (3,5‐Bd/V) suggest that OC supply is the main factor controlling the nearshore distribution of OC loadings. The simultaneous decrease of OC loadings (from 1.44 to 0.15 mg/m2) and increase of 3,5‐Bd/V (from 0.04 to 0.73) indicate that TerrOC degradation could be an important mechanism controlling the offshore decrease of OC. Compared to the broad ESAS, although the inherent characteristics of the TerrOC sources could not be ignored, the inconspicuous variations in lignin content and degradation proxy in the narrow Beaufort Shelf may indicate that the shelf width could be an important factor influencing the offshore degradation of TerrOC.

Recent advancements in tissue engineering and stem cell science have positioned bone disease treatment as a promising frontier in regenerative medicine. This review explores the hormonal and signaling pathways critical to bone regeneration, with a focus on their clinical relevance. Key endocrine factors, including thyroid hormones (T3 and T4), insulin-like growth factor 1 (IGF-1), bone morphogenetic proteins (BMPs), parathyroid hormone (PTH), calcitonin, and fibroblast growth factor 23 (FGF23), play pivotal roles in bone remodeling by regulating osteoblast activity, bone resorption, and mineralization. These factors primarily act through the Wnt/β-catenin, BMP, and FGF signaling pathways, which govern bone repair and regeneration. While animal models, such as axolotls, zebrafish, and Xenopus laevis, provide valuable findings about these mechanisms, translating these findings into human applications presents challenges. This review underscores the therapeutic potential of modulating these hormonal networks to enhance bone regeneration while cautioning against possible adverse effects, such as uncontrolled tissue proliferation or metabolic imbalances. By integrating knowledge from regenerative models, this work provides a foundation for optimizing hormone-based therapies for clinical applications in bone repair and disease treatment.

We accomplish for the first time the next-to-leading-order computation of the weak annihilation contribution to the electroweak penguin decays B→{K,π}ℓ+ℓ−, which is an essential missing piece of the complete QCD correction to the matrix elements of hadronic operators in the weak effective Hamiltonian. Both the hard functions and the jet functions in the perturbative factorization formulas from the short-distance fluctuations at the two distinct scales mb and mbΛ are determined at O(αs). We then demonstrate that the one-loop weak annihilation correction can bring about the noticeable impacts on theory predictions for the CP asymmetries and the isospin asymmetry in the B→πℓ+ℓ− decays. Published by the American Physical Society 2025