The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater numb...The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater number of pro-gramming problems in their repository,learners experience information overload.Recommender systems are a common solution to information overload.Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners’current context,like learning goals and current skill level(topic knowledge and difficulty level).To overcome the issue,we propose a context-aware practice problem recommender system based on learners’skill level navigation patterns.Our system initially performs skill level navigation pattern mining to discover frequent skill level navigations in the POJ and tofind learners’learning goals.Collaborativefiltering(CF)and con-tent-basedfiltering approaches are employed to recommend problems in the cur-rent and next skill levels based on frequent skill level navigation patterns.The sequence similarity measure is used tofind the top k neighbors based on the sequence of problems solved by the learners.The experiment results based on the real-world POJ dataset show that our approach considering the learners’cur-rent skill level and learning goals outperforms the other approaches in practice problem recommender systems.展开更多
Birds exhibit extraordinary mobility and remarkable navigational skills,obtaining guidance cues from the Earth’s magnetic field for orientation and long-distance movement.Bird species also show tremendous diversity i...Birds exhibit extraordinary mobility and remarkable navigational skills,obtaining guidance cues from the Earth’s magnetic field for orientation and long-distance movement.Bird species also show tremendous diversity in navigation strategies,with considerable differences even within the same taxa and among individuals from the same population.The highly conserved iron and iron-sulfur cluster binding magnetoreceptor(MagR)protein is suggested to enable animals,including birds,to detect the geomagnetic field and navigate accordingly.Notably,MagR is also implicated in other functions,such as electron transfer and biogenesis of iron-sulfur clusters,raising the question of whether variability exists in its biochemical and biophysical features among species,particularly birds.In the current study,we conducted a comparative analysis of MagR from two different bird species,including the migratory European robin(Erithacus rubecula)and the homing pigeon(Columba livia).Sequence alignment revealed an extremely high degree of similarity between the MagRs of these species,with only three sequence variations.Nevertheless,two of these variations underpinned significant differences in metal binding capacity,oligomeric state,and magnetic properties.These findings offer compelling evidence for the marked differences in MagR between the two avian species,potentially explaining how a highly conserved protein can mediate such diverse functions.展开更多
文摘The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater number of pro-gramming problems in their repository,learners experience information overload.Recommender systems are a common solution to information overload.Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners’current context,like learning goals and current skill level(topic knowledge and difficulty level).To overcome the issue,we propose a context-aware practice problem recommender system based on learners’skill level navigation patterns.Our system initially performs skill level navigation pattern mining to discover frequent skill level navigations in the POJ and tofind learners’learning goals.Collaborativefiltering(CF)and con-tent-basedfiltering approaches are employed to recommend problems in the cur-rent and next skill levels based on frequent skill level navigation patterns.The sequence similarity measure is used tofind the top k neighbors based on the sequence of problems solved by the learners.The experiment results based on the real-world POJ dataset show that our approach considering the learners’cur-rent skill level and learning goals outperforms the other approaches in practice problem recommender systems.
基金supported by the National Natural Science Foundation of China(31640001 and T2350005 to C.X.,U21A20148 to X.Z.and C.X.)Ministry of Science and Technology of China(2021ZD0140300 to C.X.)Presidential Foundation of Hefei Institutes of Physical Science,Chinese Academy of Sciences(Y96XC11131,E26CCG27,and E26CCD15 to C.X.,E36CWGBR24B and E36CZG14132 to T.C.)。
文摘Birds exhibit extraordinary mobility and remarkable navigational skills,obtaining guidance cues from the Earth’s magnetic field for orientation and long-distance movement.Bird species also show tremendous diversity in navigation strategies,with considerable differences even within the same taxa and among individuals from the same population.The highly conserved iron and iron-sulfur cluster binding magnetoreceptor(MagR)protein is suggested to enable animals,including birds,to detect the geomagnetic field and navigate accordingly.Notably,MagR is also implicated in other functions,such as electron transfer and biogenesis of iron-sulfur clusters,raising the question of whether variability exists in its biochemical and biophysical features among species,particularly birds.In the current study,we conducted a comparative analysis of MagR from two different bird species,including the migratory European robin(Erithacus rubecula)and the homing pigeon(Columba livia).Sequence alignment revealed an extremely high degree of similarity between the MagRs of these species,with only three sequence variations.Nevertheless,two of these variations underpinned significant differences in metal binding capacity,oligomeric state,and magnetic properties.These findings offer compelling evidence for the marked differences in MagR between the two avian species,potentially explaining how a highly conserved protein can mediate such diverse functions.