雜志原文:Grand Harvest for Seawater Rice

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Grand Harvest for Seawater Rice

In mid October， the seawater rice planted by the research team of Yuan Longping， a renowned agronomist dubbed Chinas “father of hybrid rice，” was harvested in test fields in Qingdong， Weifang， and Wenzhou. Their yields vary from 4，811.7 kilograms （a saline-alkali tolerant rice coded yc-2002 in the Ruian base in Wenzhou） to 8，137.5 kilograms per hectare（a saline-alkali tolerant rice coded yc-2003 in the Qingdao base）.

This year seawater rice was planted over 6，666 hectares in 10 regions across China under a pilot program. In Xinjiang， Ningxia， Heilongjiang， and Shandong， per hectare output exceeded 7，500 kilograms. After years of trials and improvements， the average yield of seawater rice has now surpassed 7，500 kilograms per hectare， and the maximum yield is more than 12，000 kilograms. Yuans team is moving on to grow this crop on another 66，666 hectares of saline-alkali land， and plans to expand the plantation a hundred fold over the next eight to 10 years.

All Pollution Control Targets to be Met for 2016-20 Period

China will be able to meet all of its nine pollution control targets during the 13th Five-Year Plan period（2016-20） as scheduled， announced Zhao Yingmin， vice minister of ecology and environment， at a recent news conference.

Eight of the goals， including reductions in the discharge of sulfur dioxide， oxynitride， and ammonia nitrogen， had been achieved as of 2019. The country is also expected to meet its ninth goal — ensuring fairly good air quality， considered to be below 100 on the 0-500 air quality index scale， on at least 84.5 percent of days in the 337 monitored cities by years end.

From January to September， the proportion of days with fairly good air quality in those cities reached 87.2 percent， 5.7 percentage points higher than that of the same period in 2019. Zhao said the marked improvement in air quality can be attributed to consistent efforts in optimizing the industrial structure and decarbonizing energy consumption.

About 200 million metric tons of excess steel capacity has been eliminated across the country. By the end of 2019， extra-low emissions had been realized in the generation of 890 million kilowatts of coal-fired power generation capacity.

Great achievements have also been recorded in water pollution control with the reduction of pollutant discharges， according to the ministry.

Absolute Poverty Eradicated in Tibet

At a recent press conference， the Information Office of the State Council elaborated on the progress Tibet has made in reducing poverty.

By the end of 2019， the poverty head count ratio in the autonomous region had fallen to zero， with per capita net income of its poor population rising from RMB 1，499 in 2015 to RMB 9，328. Due to natural and historical factors， Tibet had the highest poverty rate — 25.32 percent — at the end of 2015， and all the 74 county-level areas in the region were classified as poor by the national standard.

Over recent years， central and local governments have ratcheted up efforts to tackle absolute poverty， rolling out 70-odd policies， improving the accountability system for officials， and ensuring that rural poor people have enough food and clothing， access to compulsory education， basic medical services， and safe housing.

Since 2016， RMB 39.89 billion has been invested in 2，984 poverty alleviation projects in Tibet， which helped lift more than 238，000 impoverished people out of poverty and benefited more than 840，000 people. The construction of 965 relocation sites has been completed， and 266，000 people have moved into new houses. The employment rate for college graduates has stayed above 90 percent.

AI Model Used in Identifying COVID-19

Chinese researchers published a paper in the journal Nature Communications proposing an artificial intelligence model that can help doctors quickly differentiate between COVID-19， influenza， and pneumonia with high accuracy.

Researchers from Tsinghua University and Union Hospital in Wuhan， Hubei Province， have developed and evaluated an AI system using a large data set with more than 11，000 CT volumes from cases of COVID-19， influenza， non-viral community-acquired pneumonia， and non-pneumonia. The AI model， known as a deep convolutional neural network-based system， turned detection experiences accumulated by experts into algorithms. Test results showed it can differentiate between four respiratory diseases with a high degree of accuracy.

In further studies， the research team compared the diagnostic performance of the CT-based AI system with that of five radiologists， and results showed the system performed better than its human counterparts. The AI model will help lessen the workload of doctors.

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