Inactive Interaction Research Articles

A Research on Online Teaching Behavior of Chinese Local University Teachers Based on Cluster Analysis

COVID-19 boosted online teaching and yielded a significant amount of valuable data, yet utilizing it for education is a challenge. This study employed the K-means clustering method to analyze the online teaching behavior data of 1147 courses from a local university in East China. As a result, five types of courses with distinct teaching behaviors were identified: resource preparation (4.1%), online classroom interaction (3.6%), task evaluation (9.2%), active interaction (15.5%), and inactive interaction (67.6%). By examining the relationship between these course types and academic performance, the authors discovered no significant difference in the academic performance of students in the three course groups (i.e., resource preparation, online classroom interaction, and task evaluation) and students in the inactive interaction course group. However, there was a significant disparity in academic performance between students in active interaction courses and students in inactive interaction courses. These findings can assist teachers in planning online teaching activities more effectively and improving teaching outcomes.

Nano Filling Effect of Nonmeat Protein Emulsion on the Rheological Property of Myofibrillar Protein Gel.

Incorporation of vegetable oils through pre-emulsification has received notable attention for delivering polyunsaturated fatty acids to emulsified-type meat products. The two important influencing factors of the rheological property of composite myofibrillar protein (MP) gel are emulsion droplet size and active or inactive interaction between interface and meat proteins. Incorporation of nonmeat protein emulsion (2% protein (w/w), egg-white protein isolate (EPI), porcine plasma protein (PPP), or sodium caseinate (SC)) with different droplet sizes (nano or macro) to a model of 2% MP gel was investigated in this research. The results of drop size measurement showed that 15,000 psi homogenizing could decrease the diameter of emulsion drop from macro- to nanoscale in the range of 324.4–734.5 nm. Active fillers (PPP and EPI emulsions) with nanodroplet size did not influence the viscosity of emulsion-filled composite cold sols but caused positive filling effects on the MP gel matrix after heating, as evidenced by the density microstructure. PPP and EPI nano-emulsion-filled composite MP had a significant high storage modulus enforcement effect, which reached nearly eight times those of other treatments (p < 0.05). Similarly, the results of thermal scanning rheology and a large-deformation mechanical test showed that PPP and EPI emulsions with nanoscale droplets, other than macroscale, had the highest gel strength of heat-induced emulsion-filled composite MP gel (p < 0.05). Overall, these findings will be helpful for selecting the correct pre-emulsified protein and designing the textural properties of foods.

Atom pair partitioning of the correlation energy

Using our atomic orbital formulation of the electronic structure problem, contributions to the correlation energy are condensed over pairs of atomic centers. We show that the resulting pair energies can be used to understand how correlation energy is distributed throughout a molecule. These pair energies reflect the near-sightedness of the correlation energy while offering a simple way to represent and quantify intramolecular interactions. In particular, the dependence of these interactions with basis set is explored. We propose that strong or active interactions be treated using large basis sets while weak or inactive interactions are treated using a smaller basis set.