Towards Sensor-free Academic Emotion Prediction in Programming Environment

he transition from traditional learning to practice-oriented programming learning will bring learners discomfort.The discomfort quickly breeds negative emotions when encountering programming difficulties,which leads the learner to lose interest in programming or even give up.Emotion plays a crucial role in learning.Educational psychology research shows that positive emotion can promote learning performance,increase learning interest and cultivate creative thinking.Accurate recognition and interpretation of programming learners’emotions can give them feedback in time,and adjust teaching strategies accurately and individually,which is of considerable significance to improve effects of programming learning and education.The existing methods of sensor-free emotion prediction include emotion prediction based on keyboard dynamic,mouse interaction data and interaction logs,respectively.However,none of the three studies considered the temporal characteristics of emotion,resulting in low recognition accuracy.For the first time,this paper proposes an emotion prediction model based on time series and context information.Then,we establish a Bi-recurrent neural network,obtain the time sequence characteristics of data automatically,and explore the application of deep learning in the field of Academic Emotion prediction.The results show that the classification ability of this model is much better than that of the original LSTM(Long-Short Term Memory),GRU(Gate Recurrent Unit)and RNN(Re-current Neural Network),and this model has better generalization ability.

Two-dimensional correlation spectroscopic analysis on the interaction between humic acids and aluminum coagulant

In this study, two-dimensional correlation spectroscopy integrated with synchronous fluorescence and infrared absorption spectroscopy was employed to investigate the interaction between humic acids and aluminum coagulant at slightly acidic and neutral p H. Higher fluorescence quenching was produced for fulvic-like and humic-like fractions at p H 5. At p H 5, the humic-like fractions originating from the carboxylic acid, carboxyl and polysaccharide compounds were bound to aluminum first, followed by the fulvic-like fractions originating from the carboxyl and polysaccharide compounds. This finding also demonstrated that the activated functional groups of HA were involved in forming the Al-HA complex, which was accompanied by the removal of other groups by co-precipitation.Meanwhile, at p H 7, almost no fluorescence quenching occurred, and surface complexation was observed to occur, in which the activated functional groups were absorbed on the amorphous Al（OH）3. Two-dimensional FT-IR correlation spectroscopy indicated the sequence of HA structural change during coagulation with aluminum, with IR bands affected in the order of COOH〉 COO-〉NH deformation of amide Ⅱ〉 aliphatic hydroxyl C／OH at p H 5, and COO-〉aliphatic hydroxyl C／OH at p H 7. This study provides a promising pathway for analysis and insight into the priority of functional groups in the interaction between organic matters and metal coagulants.

Single-molecule investigation of human telomeric G-quadruplex interactions with Thioflavin T

G-quadruplex ligands have been accepted as potential therapeutic agents for anticancer treatment. Thioflavin T （ThT）, a highly selective G-quadruplex ligand, can bind G-quadruplex with a fluorescent light-up signal change and high specificity against DNA duplex. However, there are still different opinions that ThT induces/stabilizes G-quadruplex foldings/topologies in human telomere sequence. Here, a sensitive single-molecule nanopore technology was utilized to analyze the interactions between human telomeric DNA （Tel DNA） and ThT. Both translocation time and current blockade were measured to investigate the translocation behaviors. Furthermore, the effects of metal ion （K~ and Na~） and pH on the translocation behaviors were studied. Based on the single-molecule level analysis, there are some conclusions： （1） In the electrolyte solution containing 50 mmol/L I（Cl and 450 mmol/L NaCl, ThT can bind strongly with Tel DNA but nearly does not change the G-quadruplex form; （2） in the presence of high concentration K~, the ThT binding induces the structural change of hybrid G-quadruplex into antiparallel topology with an enhanced structural stability; （3） In either alkaline or acidic buffer, G-quadruplex form will change in certain degree. All above conclusions are helpful to deeply understand the interaction behaviors between Tel DNA and ThT. This nanopore platform, investigating G-quadruplex ligands at the single-molecule level, has great potential for the design of new drugs and sensors.

Assessing protein-DNA interactions: Pros and cons of classic and emerging techniques

Investigation of protein-DNA interactions provides important information for understanding gene function and regulation, but identification and validation of specific interactions remain major challenges in the post-genomics era. Therefore, effective and economical methods to assess protein-DNA interactions are highly sought-after by molec- ular biologists.