Regularity of rural settlement changes driven by rapid urbanization in North China over the three decades.

The systematic decline of rural areas in the process of rapid urbanization has become a global trend, creating greater challenges for sustainable rural development. As the spatial projection of socio-economic development and living environment in rural areas, the continuous tracking of rural settlements (RUS) is crucial to quantify the imbalance of rural development. However, consistent information on RUS is highly needed but is quite deficient in current research. In this study, a cost-effective mapping model was proposed to produce an annual RUS dataset in the rapid urbanization region of Beijing-Tianjin-Hebei (BTH) in North China during 1990-2020, and the temporal-spatial regularity of RUS changes was further analyzed. The location-based and the area-based comparison verified the effectiveness of our model, with a mean overall accuracy of 85% and a mean correlation value of 0.88, respectively. The total area of RUS in the BTH region increased by 2561 km2 from 1990 to 2020, while the average size of RUS remained stable after 2005. The annual change trends in RUS appeared with increasing and decreasing accounting for 76.33% and 23.67%, respectively. The centroids of RUS in Tianjin and Hebei have moved closer to Beijing, while those in Beijing have moved away from the former. Notably, we have identified 56.3% counties in the BTH region belong to the "Convex-I" change type in RUS. In general, our work can help to consistently quantify the spatiotemporal patterns of RUS in a cost-effective way, providing more explicit spatial information and continuous temporal information for rural residential land management.

Dynamic Heterogeneous User Generated Contents-Driven Relation Assessment via Graph Representation Learning.

Cross-domain decision-making systems are suffering a huge challenge with the rapidly emerging uneven quality of user-generated data, which poses a heavy responsibility to online platforms. Current content analysis methods primarily concentrate on non-textual contents, such as images and videos themselves, while ignoring the interrelationship between each user post's contents. In this paper, we propose a novel framework named community-aware dynamic heterogeneous graph embedding (CDHNE) for relationship assessment, capable of mining heterogeneous information, latent community structure and dynamic characteristics from user-generated contents (UGC), which aims to solve complex non-euclidean structured problems. Specifically, we introduce the Markov-chain-based metapath to extract heterogeneous contents and semantics in UGC. A edge-centric attention mechanism is elaborated for localized feature aggregation. Thereafter, we obtain the node representations from micro perspective and apply it to the discovery of global structure by a clustering technique. In order to uncover the temporal evolutionary patterns, we devise an encoder-decoder structure, containing multiple recurrent memory units, which helps to capture the dynamics for relation assessment efficiently and effectively. Extensive experiments on four real-world datasets are conducted in this work, which demonstrate that CDHNE outperforms other baselines due to the comprehensive node representation, while also exhibiting the superiority of CDHNE in relation assessment. The proposed model is presented as a method of breaking down the barriers between traditional UGC analysis and their abstract network analysis.

Investigating the biophysical and socioeconomic determinants of China tropospheric O3 pollution based on a multilevel analysis approach.

Severe tropospheric O3 pollution has swept across China in recent years. Consequently, investigation of tropospheric O3 concentration influencing mechanism is of significance for O3 pollution control in China. Previous studies have rarely detected combined impacts of natural factors and anthropogenic activities behind tropospheric O3 concentration in China at a national scale. Moreover, there is significant spatiotemporal heterogeneity of O3 pollution distribution in China due to the temporal and regional differences of socioeconomic and natural environmental condition in the vast territory. The targeted O3 control recommendations for different regions and seasons should be put forward in terms of the spatiotemporal heterogeneity of O3 concentration determinants. In this context, a three-level regression model integrating multi-scale biophysical and socioeconomic variables was proposed to explore the determinants of O3 pollution in China. The results showed that the tropospheric O3 concentration in the eastern and southeastern regions of China was strongly affected by meteorological conditions. In contrast, tropospheric O3 pollution concentrated in inland areas mainly depended on the emission intensity from anthropogenic sources.

Reliability and validity of the international dementia alliance schedule for the assessment and staging of care in China.

BACKGROUND: Clinical and social services both are important for dementia care. The International Dementia Alliance (IDEAL) Schedule for the Assessment and Staging of Care was developed to guide clinical and social care for dementia. Our study aimed to assess the validity and reliability of the IDEAL schedule in China. METHODS: Two hundred eighty-two dementia patients and their caregivers were recruited from 15 hospitals in China. Each patient-caregiver dyad was assessed with the IDEAL schedule by a rater and an observer simultaneously. The Clinical Dementia Rating (CDR), Mini-Mental Status Examination (MMSE), and Caregiver Burden Inventory (CBI) were assessed for criterion validity. IDEAL repeated assessment was conducted 7-10 days after the initial interview for 62 dyads. RESULTS: Two hundred seventy-seven patient-caregiver dyads completed the IDEAL assessment. Inter-rater reliability for the total score of the IDEAL schedule was 0.93 (95%CI = 0.92-0.95). The inter-class coefficient for the total score of IDEAL was 0.95 for the interviewers and 0.93 for the silent raters. The IDEAL total score correlated with the global CDR score (ρ = 0.72, p < 0.001), the CDR-sum of box (CDR-SOB, ρ = 0.74, p < 0.001), the total score of MMSE (ρ = -0.65, p < 0.001) and CBI (ρ = 0.70, p < 0.001). All item scores of the IDEAL schedule were associated with the CDR-SOB (ρ = 0.17 ~ 0.79, all p < 0.05). CONCLUSION: The IDEAL schedule is a valid and reliable tool for the staging of care for dementia in the Chinese population.

Distribution and risk assessment of radionuclides released by Fukushima nuclear accident at the northwest Pacific.

In order to understand the impact of Fukushima Nuclear Accident (FNA) on the marine environment, seawater and a composite squid (Ommastrephe bartrami) sample were collected on the monitoring cruise XT01 during June 16-July 4, 2011. The concentration levels of Cesium-134, Cesium-137, Strontium-90, Silver-110 m, Cobalt-58 and Cobalt-60 were measured both for the seawater and squid samples. The elevated activity levels of Cesium-134 and Cesium-137 were found in the sampling area. Cesium-134 and Silver-110 m, which were usually undetectable before FNA, were also found in the squid sample, with the activity levels of 1.65 ± 0.13 Bq/kg-wet and 0.07 ± 0.01 Bq/kg-wet, respectively. The radiological assessment result showed that the radioactive release from the FNA would not have a significant adverse effect on marine biota at the population level.