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Abstract Few studies have discussed the disease nature and treatment outcomes for bilateral cavernous sinus dural arteriovenous fistula (CSDAVF). This study aimed to investigate the clinical features and treatment outcomes of bilateral CSDAVF. Embase, Medline, and Cochrane library were searched for studies that specified the outcomes of bilateral CSDAVF from inception to April 2022. The classification, clinical presentation, angiographic feature, surgical approach, and treatment outcomes were collected. Meta-analysis was performed using the random effects model. Eight studies reporting 97 patients were included. The clinical presentation was mainly orbital (n = 80), cavernous (n = 52) and cerebral (n = 5) symptoms. The most approached surgical route was inferior petrosal sinus (n = 80), followed by superior orbital vein (n = 10), and alternative approach (n = 7). Clinical symptoms of 88% of the patients (95% CI 80–93%, I2 = 0%) were cured, and 82% (95% CI 70–90%, I2 = 7%) had angiographic complete obliteration of fistulas during follow up. The overall complication rate was 18% (95% CI 11–27%, I2 = 0%). Therefore, endovascular treatment is an effective treatment for bilateral CSDAVF regarding clinical or angiographic outcomes. However, detailed evaluation of preoperative images and comprehensive surgical planning of the approach route are mandatory owing to complexity of the lesions.

According to the problem that a large number of residual coal left in the goaf of the resources integration mine because of the early extensive mining, which was easy to cause spontaneous combustion of coal. Taking No. 4+9 coal seam of Beizu Coal Mine as a study subject, the combustion situation of fire area was researched through indicator gas experiment, and the high-temperature area of the roadway roof face was divided through infrared detection technique. The result showed that, CO C2H4 and C2H6 could be taken as the indicator gas for spontaneous combustion in No. 4+9 coal seam of Beizu Coal Mine, the temperature in fire area was 80~110 ⋅C, and there was a tendency that the fire area enlarged from north to south. The research result provided reference for drilling detection and plugging and so on. [ABSTRACT FROM AUTHOR]

With the widespread use of digital technologies such as big data, cloud computing and artificial intelligence in higher education, how to establish a scientific and systematic evaluation system to turn the traditional classroom with the one-way transmission of knowledge into an interactive space for exchanging ideas and inspiring wisdom has become an essential task for human resource management in universities, and a key to improving teaching quality. However, due to the debate between scientism and humanism in teaching evaluation, studies related to teaching performance have been isolated from human resource management, resulting in the lack of a systematic vision and framework for such studies. Relevant studies are still limited to the evaluation contents of different evaluation subjects. Evaluations also tend to focus only on the teaching process, ignoring the objectives of talent training, making it difficult for evaluations to play a goal-oriented role and hindering the further development of relevant studies. Therefore, this paper draws on human resource management methodologies and analyzes knowledge teaching evaluation system characteristics in colleges and universities in a big data context to construct a “multiple evaluations, trinity and four-step closed-loop” big data-based knowledge teaching evaluation system. “Trinity” represents evaluation from three performance dimensions: teaching effect, teaching behavior and teaching ability. “Multiple evaluations” represents the design of teaching performance indicators based on teaching data, breaking the barriers between different evaluation subjects. “Four-step closed-loop” draws on performance management theory to standardize the teaching performance management process from four aspects: planning, implementation, evaluation, and feedback. This evaluation system provides a systematic methodology for unifying the theory and practice of innovative knowledge teaching evaluation system in universities in a big data context.