LINKAGE BETWEEN INDIAN OCEAN DIPOLE AND TWO TYPES OF El NI?O AND ITS POSSIBLE MECHANISMS

After compositing three representative ENSO indices,El Nio events have been divided into an eastern pattern(EP) and a central pattern(CP).By using EOF,correlation and composite analysis,the relationship and possible mechanisms between Indian Ocean Dipole(IOD) and two types of El Nio were investigated.IOD events,originating from Indo-Pacific scale air-sea interaction,are composed of two modes,which are associated with EP and CP El Ni o respectively.The IOD mode related to EP El Nio events(named as IOD1) is strongest at the depth of 50 to 150 m along the equatorial Indian Ocean.Besides,it shows a quasi-symmetric distribution,stronger in the south of the Equator.The IOD mode associated with CP El Nio(named as IOD2) has strongest signal in tropical southern Indian Ocean surface.In terms of mechanisms,before EP El Nio peaks,anomalous Walker circulation produces strong anomalous easterlies in equatorial Indian Ocean,resulting in upwelling in the east,decreasing sea temperature there;a couple of anomalous anticyclones(stronger in the south) form off the Equator where warm water accumulates,and thus the IOD1 occurs.When CP El Nio develops,anomalous Walker circulation is weaker and shifts its center to the west,therefore anomalous easterlies in equatorial Indian Ocean is less strong.Besides,the anticyclone south of Sumatra strengthens,and the southerlies east of it bring cold water from higher latitudes and northerlies west of it bring warm water from lower latitudes to the 15° to 25°S zone.Meanwhile,there exists strong divergence in the east and convergence in the west part of tropical southern Indian Ocean,making sea temperature fall and rise separately.Therefore,IOD2 lies farther south.

Prediction of Academic Performance of Students in Online Live Classroom Interactions-An Analysis Using Natural Language Processing and Deep Learning Methods

Prior studies have shown the importance of classroom dialogue in academic performance,through which knowledge construction and social interaction among students take place.However,most of them were based on small scale or qualitative data,and few has explored the availability and potential of big data collected from online classrooms.To address this issue,this paper analyzes dialogues in live classrooms of a large online learning platform in China based on natural language processing techniques.The features of interactive types and emotional expression are extracted from classroom dialogues.We then develop neural network models based on these features to predict high-and low-academic performing students,and employ interpretable AI(artificial intelligence)techniques to determine the most important predictors in the prediction models.In both STEM(science,technology,engineering,mathematics)and non-STEM courses,it is found that high-performing students consistently exhibit more positive emotion,cognition and off-topic dialogues in all stages of the lesson than low-performing students.However,while the metacognitive dialogue illustrates its importance in non-STEM courses,this effect cannot be found in STEM courses.While high-performing students in non-STEM courses show negative emotion in the last stage of lessons,STEM students show positive emotion.

Vibration induced transparency:Simulating an optomechanical system via the cavity QED setup with a movable atom

We simulate an optomechanical system via a cavity QED scenario with a movable atom and investigate its application in the tiny mass sensing.We find that the steady-state solution of the system exhibits a multiple stability behavior,which is similar to that in the optomechanical system.We explain this phenomenon by the opto-mechanical interaction term in the effective Hamiltonian.Due to the dressed states formed by the effective coupling between the vibration degree of the atom and the optical mode in the cavity,we observe a narrow transparent window in the output field.We utilize this vibration induced transparency phenomenon to perform the tiny mass sensing.We hope our study will broaden the application of the cavity QED system to quantum technologies.