The use of programming online judges (POJ) to support students acquiring programming skills is common nowadays because this type of software contains a large collection of programming exercises to be solved by students. A POJ not only provides exercises but also automates the code compilation and its evaluation process. A common problem that students face when using POJ is information overload, as choosing the right problem to solve can be quite frustrating due to the large number of problems offered. The integration of current POJs into e-learning systems such as Intelligent Tutoring Systems (ITSs) is hard because of the lack of necessary information in ITSs. Hence, the aim of this paper is to support students with the information overload problem by using a collaborative filtering recommendation approach that filters out programming problems suitable for students’ programming skills. It uses an enriched user-problem matrix that implies a better student role representation, facilitating the computation of closer neighborhoods and hence a more accurate recommendation. Additionally a novel data preprocessing step that manages anomalous users’ behaviors that could affect the recommendation generation is also integrated in the recommendation process. A case study is carried out on a POJ real dataset showing that the proposal outperforms other previous approaches.

A recommendation approach for programming online judges supported by data preprocessing techniques

Programming online judges (POJs) are autograders that have been increasingly used in introductory programming courses (also known as CS1) since these systems provide instantaneous and accurate feedback for learners’ codes solutions and reduce instructors’ workload in evaluating the assignments. Nonetheless, learners typically struggle to find problems in POJs that are adequate for their programming skills. A potential reason is that POJs present problems with varied categories and difficulty levels, which may cause a cognitive overload, due to the large amount of information (and choice) presented to the student. Thus, students can often feel less capable, which may result in undesirable affective states, such as frustration and demotivation, decreasing their performance and potentially leading to increasing dropout rates. Recently, new research emerged on systems to recommend problems in POJs; however, the data collection for these approaches was not fine-grained; importantly, they did not take into consideration the students’ previous effort and achievement. Thus, this study proposes for the first time a prescriptive analytics solution for students’ programming behaviour by constructing and evaluating an automatic recommender module based on students’ effort, to personalise the problems presented to the learner in POJs. The aim is to improve the learners achievement, whilst minimising negative affective states in CS1 courses. Results in a within-subject double-blind controlled experiment showed that our method significantly improved positive affective states, whilst minimising the negatives ones. Moreover, our recommender significantly increased students’ achievement (correct solutions) and reduced dropout and failure in problem-solving.

A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 Learning.

Emerging importance of bighead catfish (Clarias macrocephalus) and north African catfish (C. gariepinus) as a bioresource and their genomic perspective

Hong Kong catfish (Clarias fuscus) is an ecologically and economically important species that is widely distributed in freshwater regions of southern China. Hong Kong catfish has significant sexual growth dimorphism. The genome assembly of the Hong Kong catfish would facilitate study of the sex determination and evolution mechanism of the species.The first high-quality chromosome-level genome of the Hong Kong catfish was constructed. The total genome was 933.4 Mb, with 416 contigs and a contig N50 length of 8.52 Mb. Using high-throughput chromosome conformation capture (Hi-C) data, the genome assembly was divided into 28 chromosomes with a scaffold N50 length of 36.68 Mb. A total of 23,345 protein-coding genes were predicted in the genome, and 94.28% of the genes were functionally annotated in public databases. Phylogenetic analysis indicated that C. fuscus and Clarias magur diverged approximately 63.7 million years ago. The comparative genome results showed that a total of 60 unique, 353 expanded and 851 contracted gene families were identified in Hong Kong catfish. A sex-linked quantitative trait locus identified in a previous study was located in a sex-determining region of 30.26 Mb (0.02 to 30.28 Mb) on chromosome 13 (Chr13), the predicted Y chromosome. This QTL region contained 785 genes, of which 18 were identified as sex-related genes.This study is the first to report the chromosome-level genome assembly of Hong Kong catfish. The study provides an excellent genetic resource that will facilitate future studies of sex determination mechanisms and evolution in fish. 

/pdf/a-chromosome-level-genome-assembly-of-hong-kong-catfish-4dzpogz2.pdf

A chromosome-level genome assembly of Hong Kong catfish (Clarias fuscus) uncovers a sex-determining region

Simple Summary The Hong Kong catfish (Clarias fuscus) is a tropical and subtropical fish that is extensively cultured in southern China due to its adaptability and tolerance. While previous studies have investigated the impact of global-warming-induced increased water temperature on teleost fish, the response of C. fuscus to chronic high temperature and its underlying molecular mechanism remains unclear. This study conducted a 90-day heat-stress experiment on C. fuscus, revealing that continuous exposure to high temperatures stunted their growth, caused liver tissue damage, and increased apoptosis rates. Additionally, changes in antioxidant enzyme activity and an upregulation of heat shock protein (HSP) genes were observed, indicating a potential immune response mechanism. These results suggest that C. fuscus may counteract the negative effects of prolonged high-temperature stress by upregulating heat-shock-protein-related genes. This research enhances our comprehension of C. fuscus’ molecular responses to high-temperature stress and serves as a valuable model for studying similar responses in other fish species. Abstract Chronic heat stress can have detrimental effects on the survival of fish. This study aimed to investigate the impact of prolonged high temperatures on the growth, antioxidant capacity, apoptosis, and transcriptome analysis of Hong Kong catfish (Clarias fuscus). By analyzing the morphological statistics of C. fuscus subjected to chronic high-temperature stress for 30, 60, and 90 days, it was observed that the growth of C. fuscus was inhibited compared to the control group. The experimental group showed a significant decrease in body weight and body length compared to the control group after 60 and 90 days of high-temperature stress (p < 0.05, p < 0.01). A biochemical analysis revealed significant alterations in the activities of three antioxidant enzymes superoxide dismutase activity (SOD); catalase activity (CAT); glutathione peroxidase activity (GPx), the malondialdehyde content (MDA), and the concentrations of serum alkaline phosphatase (ALP); Aspartate aminotransferase (AST); and alanine transaminase (ALT) in the liver. TUNEL staining indicated stronger apoptotic signals in the high-temperature-stress group compared to the control group, suggesting that chronic high-temperature-induced oxidative stress, leading to liver tissue injury and apoptosis. Transcriptome analysis identified a total of 1330 DEGs, with 835 genes being upregulated and 495 genes being downregulated compared to the control group. These genes may be associated with oxidative stress, apoptosis, and immune response. The findings elucidate the growth changes in C. fuscus under chronic high temperature and provide insights into the underlying response mechanisms to a high-temperature environment.

Effects of Chronic Heat Stress on Growth, Apoptosis, Antioxidant Enzymes, Transcriptomic Profiles, and Immune-Related Genes of Hong Kong Catfish (Clarias fuscus)

A high-density genetic linkage map and QTL mapping for sex in Clarias fuscus

The Research of the Recommendation Algorithm in Online Learning

Integrative QTL Mapping and Transcriptomic Profiling to Identify Growth-Associated QTL and Candidate Genes in Hong Kong Catfish (Clarias fuscus)

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A high-density genetic linkage map and QTL mapping for sex in Clarias fuscus

The Research of the Recommendation Algorithm in Online Learning

Integrative QTL Mapping and Transcriptomic Profiling to Identify Growth-Associated QTL and Candidate Genes in Hong Kong Catfish (Clarias fuscus)