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A three-dimensional MOOC analysis framework was developed, focusing on platform design, organizational mechanisms, and course construction. This framework aims to investigate the current situation of big data MOOCs in the intelligent era, particularly from the perspective of improving the mental health of college students; moreover, the framework summarizes the construction experience and areas for improvement. The construction of 525 big data courses on 16 MOOC platforms is compared and analyzed from three aspects: the platform (including platform construction, resource quantity, and resource quality), organizational mechanism (including the course opening unit, teacher team, and learning norms), and course construction (including course objectives, teaching design, course content, teaching organization, implementation, teaching management, and evaluation). Drawing from the successful practices of international big data MOOCs and excellent Chinese big data MOOCs, and considering the requirements of authoritative government documents, such as the no. 8 document (J.G. [2019]), no. 3 document (J.G. [2015]), no. 1 document (J.G. [2022]), as well as the "Educational Information Technology Standard CELTS-22—Online Course Evaluation Standard", recommendations about the platform, organizational mechanism, and course construction are provided for the future development of big data MOOCs in China. [ABSTRACT FROM AUTHOR]

Alternaria mycotoxins are a class of important, agriculture-related hazardous materials, and their contamination in ruminant feeds and products might bring severe toxic effects to animals and even human beings. To control these hazardous compounds, a reliable and sensitive LC-MS/MS (liquid chromatography–tandem mass spectrometry) method was established for simultaneous determination of six target Alternaria mycotoxins in ruminant feeds, including ALT (Altenuene), AME (Alternariol Monomethyl Ether), AOH (Alternariol), ATX-Ι (Altertoxins I), TeA (Tenuazonic Acid), and TEN (Tentoxin). This developed analytical method was used for the determination of the presence of these substances in cattle and sheep feeds in Xinjiang Province, China. The results revealed that Alternaria mycotoxins are ubiquitously detected in feed samples. Especially, AME, AOH, TeA, and TEN are the most frequently found mycotoxins with a positive rate over 40% and a concentration range of 4~551 µg/kg. The proposed method could be applied for exposure investigation of Alternaria mycotoxins in ruminant feeds and for the reduction in the health risk to animals and even consumers. [ABSTRACT FROM AUTHOR]

China faces a difficult choice of maintaining socioeconomic development and carbon emissions mitigation. Analyzing the decoupling relationship between economic development and carbon emissions and its driving factors from a regional perspective is the key for the Chinese government to achieve the 2030 emission reduction target. This study adopted the logarithmic mean Divisia index (LMDI) method and Tapio index, decomposed the driving forces of the decoupling, and measured the sector's decoupling states from carbon emissions in Xinjiang province, China. The results found that: (1) Xinjiang's carbon emissions increased from 93.34 Mt in 2000 to 468.12 Mt in 2017. Energy-intensive industries were the key body of carbon emissions in Xinjiang. (2) The economic activity effect played the decisive factor to carbon emissions increase, which account for 93.58%, 81.51%, and 58.62% in Xinjiang during 2000–2005, 2005–2010, and 2010–2017, respectively. The energy intensity effect proved the dominant influence for carbon emissions mitigation, which accounted for −22.39% of carbon emissions increase during 2000–2010. (3) Weak decoupling (WD), expansive coupling (EC), expansive negative decoupling (END) and strong negative decoupling (SND) were identified in Xinjiang during 2001 to 2017. Gross domestic product (GDP) per capita elasticity has a major inhibitory effect on the carbon emissions decoupling. Energy intensity elasticity played a major driver to the decoupling in Xinjiang. Most industries have not reached the decoupling state in Xinjiang. Fuel processing, power generation, chemicals, non-ferrous, iron and steel industries mainly shown states of END and EC. On this basis, it is suggested that local governments should adjust the industrial structure, optimize energy consumption structure, and promote energy conservation and emission reduction to tap the potential of carbon emissions mitigation in key sectors. [ABSTRACT FROM AUTHOR]