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2023 China Arbitration Summit and the 3rd Belt and Road Arbitration Institutions Forum Successfully Held in Beijing

On 6 September 2023, 2023 China Arbitration Summit and the 3rd Belt and Road Arbitration Institutions Forum (“Summit”) was successfully held in Beijing. The Summit was co-hosted by China International Economic and Trade Arbitration Commission (“CIETAC”) and United Nations Commission on International Trade Law (“UNCITRAL”). Yu Jianlong, Vice Chairman of China Council for the Promotion of International Trade (“CCPIT”) and Vice Chairman of China Chamber of International Commerce (“CCOIC”), Anna Joubin-Bret, Secretary of UNCITRAL, Liu Guixiang, Permanent Member of the Supreme People’s Court (“SPC”)’s Judicial Committee (Vice-Minister Level) and Grand Justice of the Second Rank, attended the opening ceremony and delivered opening remarks. Wang Zhenjiang, Vice Minister of the Ministry of Justice (“MOJ”), delivered a speech via video. Zhang Shuming, Deputy Chief Judge of the Fourth Civil Division of the SPC, gave a keynote speech. Sun Chunying, First-Level Insp

Two Supermassive Black Holes Circling Each Other in a Distant Galaxy Confirmed in New Observations of Bright Flares

Two Supermassive Black Holes Circling Each Other in a Distant Galaxy Confirmed in New Observations of Bright Flares
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As Plundered Items Return to Wounded Knee, Decisions Await

The Oglala Sioux Tribe recently secured the return of cultural objects kept for over a century in a tiny Massachusetts museum. Now it is seeking consensus on their final resting place.

Improved Organic LED Luminous Efficiency from New Observations

Frontiers | Mapping of Pollution Distribution for Electric Power System Based on Satellite Remote Sensing

In recent years, the frequent fouling accidents has posed a serious threat to people's life and property safety. Due to the wide distribution of pollution sources and variable meteorological factors, it is a very time-consuming and labour-intensive task to map the pollution distribution by traditional methods. In this work, a study on the mapping of pollution distribution based on satellite remote sensing is carried out in Yunnan Province, China, as an example. Several machine learning methods (e.g. KNN, SVM, etc.) are used to analyze the effects of conditions such as multiple air pollution data and meteorological data on pollution distribution map levels. The results indicate that the ensemble learning model has the highest accuracy of 71.2\% in this application. The new pollution distribution map using this classifier has 5,506 more pixels in the most severe pollution level than the traditional. Lastly, The remote sensing-based map and the manual measurement-based map were combin

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