Deformable Graph Transformer

Transformer-based models have recently shown success in representation learning on graph-structured data beyond natural language processing and computer vision. However, the success is limited to small-scale graphs due to the drawbacks of full dot-product attention on graphs such as the quadratic complexity with respect to the number of nodes and message aggregation from enormous irrelevant nodes. To address these issues, we propose Deformable Graph Transformer (DGT) that performs sparse attention via dynamically sampled relevant nodes for efficiently handling large-scale graphs with a linear complexity in the number of nodes. Specifically, our framework first constructs multiple node sequences with various criteria to consider both structural and semantic proximity. Then, combining with our learnable Katz Positional Encodings, the sparse attention is applied to the node sequences for learning node representations with a significantly reduced computational cost. Extensive experiments demonstrate that our DGT achieves state-of-the-art performance on 7 graph benchmark datasets with 2.5 - 449 times less computational cost compared to transformer-based graph models with full attention.Comment: 16 pages, 3 figure

Contributing to sustainability education of east asian university students through a field trip experience: A social-ecological perspective

This study reports the effects of a field trip environmental education program with a social-ecological perspective on the experience and learning of university students from China, Japan, South Korea and Vietnam. The students visited Jeju Island, the SaemangeumSeaDike, theDemilitarized Zone and Seoul, South Korea. Their experiences and learning about social-ecological interactions were analyzed using the new environmental paradigmtest, an evaluation questionnaire, group presentations and individual reports. Across demographic characteristics, the participants believed the program fairly presented the concept of social-ecological systems. Some developed new ideas of social-ecological systems through interpreting, transforming and contextualizing their field trip experience based on prior knowledge bases; others compared the sites to case studies. They preferred the sites where social-ecological issues were clearly presented by well-preserved landscapes, successful environmental management or environmental conflict. The results show the need for an advanced multi-dimensional methodology to evaluate students' learning through constructive processes. The program design of this study from planning to field trip and evaluation, the field site design in which regional site resources were organized in a social-ecological context and the analysis of participants' learning and experiences could contribute to attempts to couple the social-ecological perspective with the practice of sustainability and environmental education in field trip design.We appreciate the anonymous private environmental foundation that organized and supported the field trip program. We also appreciate the passionate NGO directors and activists who devoted themselves to helping and guiding the field trip in Jeju, Saemangeum and the DMZ. This study was supported by research grants from the National Research Foundation of Korea (2015R1A6A3A01058445) and the Korea Forest Service (S211216L030120).Scopu

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts

Willingness to Pay for Public Benefit Functions of Daecheong Dam Operation: Moderating Effects of Climate Change Perceptions

This study estimates the economic value of the Daecheong Dam for the public function of responding to climate change. It examines the moderating effect of climate change perceptions on value estimates by applying choice experiments (CE). The study specifies three dam function attributes—drought management (DM), flood control (FC), and water quality monitoring (WM)—subdivided into three levels to improve the existing conditions. Survey data from 603 households living in Daejeon, Chungbuk, and Chungnam have been collected to perform the CE. Subsequently, two clusters—high-involvement and low-involvement groups—have been extracted, based on the climate change perception index. The main results of comparing the marginal willingness-to-pay between the two clusters are as follows. The attributes and price variable significantly affected the choice probability to benefit from improvements in the rational signs of the coefficients. This does not violate the independence of the irrelevant alternatives assumption. The improvement values of high-involvement and low-involvement groups are estimated as KRW 21,570 and KRW 14,572 a year per household, respectively. Both show the same value intensities in the order of WM, DM, and FC

Willingness to Pay for Public Benefit Functions of Daecheong Dam Operation: Moderating Effects of Climate Change Perceptions

This study estimates the economic value of the Daecheong Dam for the public function of responding to climate change. It examines the moderating effect of climate change perceptions on value estimates by applying choice experiments (CE). The study specifies three dam function attributes—drought management (DM), flood control (FC), and water quality monitoring (WM)—subdivided into three levels to improve the existing conditions. Survey data from 603 households living in Daejeon, Chungbuk, and Chungnam have been collected to perform the CE. Subsequently, two clusters—high-involvement and low-involvement groups—have been extracted, based on the climate change perception index. The main results of comparing the marginal willingness-to-pay between the two clusters are as follows. The attributes and price variable significantly affected the choice probability to benefit from improvements in the rational signs of the coefficients. This does not violate the independence of the irrelevant alternatives assumption. The improvement values of high-involvement and low-involvement groups are estimated as KRW 21,570 and KRW 14,572 a year per household, respectively. Both show the same value intensities in the order of WM, DM, and FC

Estimating the production and mortality of fine roots using minirhizotrons in a Pinus densiflora forest in Gwangneung, Korea

The aim of this study was to estimate fine root production (FP) and fine root mortality (FM) at 0–10, 10–20, and 20–30 cm soil depths using minirhizotrons in a 75-year-old Pinus densiflora Sieb. et Zucc. forest located in Gwangneung, Korea. We developed the conversion factors (frame cm−2) of three soil depths (0.158 for 0–10 cm, 0.120 for 10–20 cm, and 0.131 for 20–30 cm) based on soil coring and minirhizotron data. FP and FM were estimated using conversion factors from March 26, 2013 to March 2, 2014. The annual FP and FM values at the 0–30 cm soil depth were 3200.2 and 2271.5 kg ha−1 yr −1, respectively. The FP estimate accounted for approximately 17 % of the total net primary production at the study site. FP was highest in summer (July 31–September 26), and FM was highest in autumn (September 27–November 29). FP was positively correlated with seasonal change in soil temperature, while FM was not related to that change. The seasonality of FP and FM might be linked to above-ground photosynthetic activity. Both FP and FM at the 0–10 cm depth were significantly higher than at 10–20 and 20–30 cm depths, and this resulted from the decrease in nutrient availability with increasing soil depth. The minirhizotron approach and conversion factors developed in this study will enable fast and accurate estimation of the fine root dynamics in P. densiflora forest ecosystems.Scopu

Short-term effects of warming treatment and precipitation manipulation on the ecophysiological responses of pinus densiflora seedlings

The aim of this study was to investigate the short-term effects of warming treatment and precipitation manipulation on the growth, photosynthetic rate, and chlorophyll content of Pinus densiflora seedlings based on a climate change scenario in Korea. Two year old P. densiflora seedlings were planted in a nursery in April 2013. The air temperature of warmed plots (W) was set to increase by 3 °C compared to control plots (C) using an infrared heater in May 2013. The three precipitation manipulations consisted of decreased precipitation using transparent panels (–30%; P–), increased precipitation using pumps and drip irrigation (+30%; P+), and a control (0%; P0). Root collar diameter and seedling height of P. densiflora were measured in April and October 2013. Net photosynthetic rate and total chlorophyll contents were measured from June to October 2013. Warming treatment increased the growth of root collar diameter, and the interaction effect of the warming treatment and precipitation manipulation on it was also significant. In contrast, no significant effects were found for the growth of seedling height. These results demonstrate that warming treatment might affect the growth of root collar diameter and seedling height differently. It was also found that WP– treatment decreased net photosynthetic rates. This pattern might be due to the soil moisture availability, as soil moisture content was lowest in the WP– treatment and net photosynthetic rate was elevated with increasing soil moisture content. Meanwhile, warming treatment increased the total chlorophyll content. The results suggest that chlorophyll synthesis was promoted by a temperature increase in the leaves. The current study, which simulated a climate change environment in an open field, provides important information for the prediction of the ecophysiological effects of changes in temperature and precipitation on P. densiflora seedlings in Korea.This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) that is funded by the Ministry of Education (2013R1A1A2012242) and by the Korea Forest Service (S111115L030100).Scopu