National Research Council of Science and Technology

The prognosis and incidence of colon cancer are linked to vitamin D3 serum levels. To evaluate the effects of D,L-buthionine-S,R-sulfoximine (BSO), 1,25(OH)2D3 and their combination on intestinal Caco-2 cell growth, to elucidate the possible cellular mechanisms involved in their antiproliferative action, and to determine whether BSO acts as a sensitizer to 1,25(OH)2D3 treatment, enabling minimization of the toxic effects caused by high doses of the steroid. Human colon cancer Caco-2 cells were treated with 1,25(OH)2D3, BSO, both, or vehicle. Cell proliferation was evaluated by crystal violet staining. Cell cycle and mitochondrial membrane potential were measured by flow cytometry. Total glutathione, catalase, superoxide dismutase, superoxide anion levels, and alkaline phosphatase activities were analyzed by spectrophotometry. DNA fragmentation was evaluated using the terminal dUTP nick end labeling assay. BSO and 1,25(OH)2D3 inhibited Caco-2 cell growth, an effect that was higher with the combined treatment. The antiproliferative effect produced by the combination could be protected by ascorbic acid. BSO plus 1,25(OH)2D3 induced cell cycle arrest and suppressed cell division. Total glutathione decreased and superoxide anion increased with BSO and BSO plus 1,25(OH)2D3. Catalase activity increased with the combined treatment. Mitochondrial membrane potential and alkaline phosphatase activity were altered by 1,25(OH)2D3 alone or plus BSO. The percentage of terminal dUTP nick end labeling-positive cells was increased. BSO increases the antiproliferative effect of 1,25(OH)2D3 on Caco-2 cells through induction of oxidative stress, which occurs simultaneously with DNA breakage. The antioxidant system can partially compensate the damage induced by BSO plus 1,25(OH)2D3. Cell differentiation induction is also involved in the response to the combined treatment.

In this paper, we examined the effect of deliberative democracy on the polarization of opinion. Through three case analyses, we find that deliberative democracy has two major components – provision of information and group discussion. Polarization of opinion can be explained by several theories: social identity theory, social comparison, and confirmation bias. We constructed a deliberative democracy model that reflected these mechanisms of polarization. We found that deliberative democracy actually decreased polarization of opinion when group discussion was a strong factor. Our study provides guidelines for an institutional design incorporating deliberative democracy, with emphasis on the composition of unbiased group discussions.

The Wii balance board (WBB) is a simplified force plate system used to evaluate the balancing ability of the elderly via a sensory interaction task to confirm a significant standing balance index. The accuracy of this system has been verified in previous studies. In this study, an instrumented and modified clinical test of sensory interaction on balance (i-mCTSIB) was performed on 84 elderly subjects, and the variables for center of pressure (CoP) were calculated using WBB for each task condition. The results indicate that the visual condition has a significant effect on the sway proprioceptive sensory variables with a foam condition as their complexity increases. In addition, the correlation between the variable and Berg Balance Scale was not confirmed since CTSIB is a sensory interaction on balance ability. Therefore, WBB can be used to evaluate balancing ability based on sensory interactions consisting of the surface condition.

Deep imitation learning requires many expert demonstrations, which can be hard to obtain, especially when many tasks are involved. However, different tasks often share similarities, so learning them jointly can greatly benefit them and alleviate the need for many demonstrations. But, joint multi-task learning often suffers from negative transfer, sharing information that should be task-specific. In this work, we introduce a method to perform multi-task imitation while allowing for task-specific features. This is done by using proto-policies as modules to divide the tasks into simple sub-behaviours that can be shared. The proto-policies operate in parallel and are adaptively chosen by a selector mechanism that is jointly trained with the modules. Experiments on different sets of tasks show that our method improves upon the accuracy of single agents, task-conditioned and multi-headed multi-task agents, as well as state-of-the-art meta learning agents. We also demonstrate its ability to autonomously divide the tasks into both shared and task-specific sub-behaviours.

A force plate is mainly used in biomechanics; it aims to measure the ground reaction force in a person's walking or standing position. In this study, a large-area force mat of the piezoresistance sensing type was developed, and a deep-learning-based weight measurement calibration method was applied to solve the problem in which measurements are not normalized because of physical limitations in hardware and signal processing. The test set was composed of the values measured at each point by weight and the value of the center of the pressure variable, and the measured value was predicted using a deep neural network (DNN) regression model. The calibration verification results show that the average weight errors range from a minimum of 0.06% to a maximum of 3.334%. This is simpler than the previous method, which directly measures the ratio of the resistance value to the measured weight of each sensor and derives an equation.

Digital services trade is often viewed as a pathway to lower carbon intensity by reducing reliance on carbon-intensive physical trade. However, its environmental benefits may depend critically on the regulatory environments governing cross-border digital interactions. Integrating institutional distance theory with environmental economics, this study examines how regulatory divergence in digital services trade shapes the carbon intensity of international trade. Using bilateral trade data and country-level measures of digital services trade regulations, renewable energy capacity, and environmental policy rigor, we analyze the effects of digital regulatory gaps on carbon emissions embodied in exports. The results show that greater regulatory divergence significantly increases both total carbon emissions and export carbon intensity. The analysis further reveals that the scale effect associated with increased trade volume dominates the technique effect, such that the potential environmental benefits of digitalization are frequently offset by structural inefficiencies and compliance costs induced by regulatory fragmentation. Moreover, exporters’ renewable energy capability amplifies—rather than mitigates—the carbon-intensity-increasing effect of digital regulatory gaps, indicating that institutional misalignment imposes higher environmental opportunity costs on countries with greater low-carbon potential. By contrast, environmental policy rigor in importing countries does not significantly attenuate these effects. Overall, the findings highlight regulatory alignment as a critical condition for realizing the environmental benefits of digital trade.

ABSTRACT This study explores how digital dynamic capabilities (DDC)—specifically digital absorptive capacity (DAC) and digital transformation capacity (DTC)—contribute to environmental sustainability (ES), both directly and through circular supply chain practices (CSCP). Utilizing dynamic capabilities and resource‐orchestration theories, we collected survey data from 252 Chinese manufacturing firms using a two‐wave design and employed partial least squares structural equation modeling (PLS‐SEM) for hypothesis testing. The results indicate that both DAC and DTC significantly enhance ES, underscoring the strategic importance of digital capabilities in promoting environmentally responsible operations. Open‐loop circular initiatives, such as material efficiency and product redesign, partially mediate these effects, suggesting that digitally enabled circular practices bolster sustainability performance. In contrast, closed‐loop initiatives—such as recovery and remanufacturing—did not significantly mediate the relationship between DDC and ES. These findings deepen our understanding of how digitalization fosters circularity and provide practical insights for firms aiming to integrate digital capabilities with circular economy strategies for long‐term environmental benefits.

In this study, we developed a quantitative assessment model that measures the digital maturity of South Korea’s government-funded research institutes (GRIs) and provide practical guidance for advancing digital transformation in the public sector. We proposed a digital maturity assessment (DMA) model tailored for GRIs and demonstrated its enhancement through implementation in real-world public sector cases. We employed a Design Science Research (DSR) approach to develop and validate a DMA model for GRIs, which was initially derived from an interview-based qualitative study. The resulting GRI-specific model incorporates six core dimensions: strategy, organization, operations, users, technology, and data. The proposed model was applied to 122 respondents from 21 institutes. To justify the aggregation of individual responses to the institutional level, we validated the consensus among respondents using the within-group agreement index <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_WG(J)</i>, which yielded a high average value of 0.85. The results indicate that the overall digital maturity of the GRIs remains at the “Emerging” level, with notable strengths in user engagement and data usage. However, there are critical gaps in strategy, organization, and technology. The proposed DMA model serves as a robust tool for benchmarking digital capabilities and provides a foundation for customized roadmaps, governance, and policy alignment to advance transformation.