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The current ideological education in colleges and universities is undergoing a series of changes, and the return of Chinese traditional culture to the system of ideological education in colleges and universities has become the development trend of the current ideological education. The study constructs the ARCS model of college civic education, integrating traditional culture according to the ARCS model, and improves the traditional hierarchical analysis method by introducing triangular fuzzy numbers so as to construct the evaluation index system of college civic education. The evaluation results of the ARCS model of Civic Education in Colleges and Universities, which integrates traditional culture, and its application effects on students’ civic performance and civic literacy are explored. In the three initial indexes of Teaching Content, Teaching Methods, and Teaching Effect, ARCS Civic Teaching in Colleges and Universities has a score of 0.826, 0.809, and 0.854, respectively. The scores of most of the second-level indexes are more than 0.8, and Civic Teaching in Colleges and Universities under ARCS has achieved a better evaluation result. The Civics scores of the experimental group and the control group do not have significant differences at the beginning of the experiment, and the significant p-value is 0.004 after the experiment, which is a significant difference. At the beginning of the experiment, the p-value of each Civic and Political Literacy of the two groups was greater than 0.05, and after the experiment, the p-value of each Civic and Political Literacy of the two groups was less than 0.05. The ARCS model of Civic and Political Education in Colleges and Universities, which integrates traditional culture, significantly improves the civic and political achievements and civic and political literacy of students.

Network ideological and political education is a great extension of school education, but the complex and confusing network information is also easy to give students bad emotional guidance. In this paper, microblogging data and topic clustering technology are used to obtain the emotional text data of network ideological and political education, based on the LDA model for topic feature extraction, to remove the data that has a lower degree of relevance to ideological and political education emotion in the data. Then, combined with the Jieba segmentation tool, based on the TF-IDF algorithm, for keyword extraction of the data that has been segmented. The text semantic features extracted based on the Word2Vec word vector model are used as the input information of this model, and the unique memory unit and gating structure of LSTM are utilized to solve the problem of storing memory of a priori knowledge and the problem of gradient dissipation caused by too long time threshold in long text classification. The Word2Vec-LSTM text sentiment classification model is developed and trained using Python and related machine learning libraries, and comparative experiments are carried out to validate the algorithm’s effectiveness and feasibility. The performance of Word2Vec-LSTM sentiment analysis on the dataset is higher than Word2Vec and LSTM algorithms. In addition, the value of sentiment perplexity is the smallest when the number of topics is set to be about 8, and its value is 0.542, and the positive sentiment density reaches the maximum value (0.648) as the sentiment score grows to 0.48. This paper explores the application of emotion analysis results in network ideological and political education to further improve the construction of a network ideological and political education system.

This paper firstly builds a diversified content system of ideological and political courses based on knowledge graph, extracts course knowledge, proposes a LEBERT-CRF entity recognition method that dynamically fuses words and word-level word vectors for the problems that arise in ideological and political courses, and uses dictionary adapters to integrate the features of ideological and political dictionaries into the BERT model, and then combines the resources of ideological and political courses to expand the data sources of knowledge graphs. Finally, taking the teaching and classroom of ideological and political courses in a university as an empirical study, the results show that the test results of the teaching objects on the feedback of ideological and political course content have very significant differences. The teaching observers give 8 “good” evaluations, 6 “average,” 5 “excellent” evaluations, and 2 “need for improvement” evaluations, indicating that the ideological and political elements are well integrated with the course content. The mean values of value orientation, ideological and political integration, ideological and political resources, discussion and interaction, reflection and evaluation, activity organization, technical support, resource push, and dual-line teaching were 3.776, 4.098, 3.874, 4.191, 4.075, 3.885, 4.265, 3.945, and 4.245, respectively. Students recognize the content system of ideological and political courses constructed in this paper. Therefore, the content system of ideological and political courses built in this paper can effectively solve the current situation of redundant and difficult-to-grasp ideological and political knowledge systematically.

Evaluating innovation and entrepreneurship ability measurement of college students is one of the critical areas of research on innovation ability cultivation in colleges and universities. In this study, based on the existing Bayesian knowledge tracking model, the parameter matrix of innovation and entrepreneurship knowledge point relationship is added to improve the standard knowledge tracking model. The CS-BKT model is proposed to provide college teachers with detailed mastery of students’ innovation and entrepreneurship knowledge. Then the corresponding state space is delineated according to the mastery situation, and the evaluation model of innovation and entrepreneurship ability measurement for college students based on polymorphic rewarded Markov chain is constructed. Combined with different transfer probabilities, the model operates on student data to measure students’ innovation and entrepreneurship ability. The results of the study showed that there was a significant difference between the acceptance and non-acceptance of innovation and entrepreneurship education in students’ innovation and entrepreneurship competence, and the level of innovation and entrepreneurship competence of students who had accepted it was 3.71, which was higher than that of students who had not taken it (3.53). There is a significant positive correlation between the social level of the place of origin, the individual level of entrepreneurial experience, and the rank of professional achievement and innovation and entrepreneurship ability, with p-values of 0.008, 0.003, and 0.001 respectively are less than 0.01. This study concludes the factors influencing the innovation and entrepreneurship ability of college students, which provides a reference value to the formation and development of the innovation and entrepreneurship ability of the students.

BACKGROUND: In response to growing concerns regarding heavy metal contamination in food, particularly chromium (Cr)(VI) contamination, this study presented a simple, sensitive and practical method for Cr(VI) detection. RESULTS: A magnetic separation‐based capture–exponential enrichment ligand system evolution (SELEX) method was used to identify and characterize DNA aptamers with a high affinity for Cr(VI). An aptamer, Cr‐15, with a dissociation constant (Kd) of 4.42 ± 0.44 μmol L−1 was obtained after only eight rounds of selection. Further innovative methods combining molecular docking, dynamic simulation and thermodynamic analysis revealed that CrO42− could bind to the 19th and 20th guanine bases of Cr‐15 via hydrogen bonds. Crucially, a label‐free fluorometric aptasensor based on SYBR Green I was successfully constructed to detect CrO42−, achieving a linear detection range of 60–300 nmol L−1 with a lower limit of detection of 44.31 nmol L−1. Additionally, this aptasensor was able to quantitatively detect CrO42− in grapes and broccoli within 40 min, with spike recovery rates ranging from 89.22% to 108.05%. The designed fluorometric aptasensor exhibited high selectivity and could detect CrO42− in real samples without sample processing or target pre‐enrichment. CONCLUSION: The aptasensor demonstrated its potential as a reliable tool for monitoring Cr(VI) contamination in fruit and vegetable products. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The development of education should serve the needs of economic and social development by providing high‐quality and appropriate professionals for economic development. Recently, the implementation of Double High Plan has provided many opportunities for the cultivation of high‐level professional groups. In the process of professional group construction, the extent of coupling between the level of professional group construction and the level of regional economic clusters is an important evaluation. This work is based on the list of proposed projects for the construction of high‐level professional clusters in Guangdong Province between 2019 and 2021. This list is issued by the department of education of Guangdong Province. The quantitative indicators and coupling models are established to estimate the degree of coupling between the construction of professional clusters in 9 prefecture‐level cities located in the Pearl River Delta region and the level of regional industrial clusters. The results presented in this work show that the professional cluster construction and industrial construction level of four prefecture‐level cities, including Guangzhou, Shenzhen, Foshan, and Dongguan, achieve coordinated development, while the remaining areas are mostly in transformation and integration stages. This is because the development level of industrial clusters has surpassed the construction of professional clusters in universities, resulting in a mismatch between talent cultivation and the requirements of economic development. This mismatch is manifested in three aspects. First, the supply and demand do not align in terms of the scale of professional groups and industrial clusters. Second, insufficient integration of professional clusters and industrial clusters. Finally, this mismatch is evident in imbalanced resource allocation. The fit between the setting of professional clusters and the structure of industrial clusters is not high. Based on the aforementioned analysis, this work presents suggestions for promoting the integration of industry and education and school‐enterprise cooperation among universities in the Pearl River Delta region. This will eventually enhance the construction of high‐level professional groups in the Pearl River Delta region and result in coordinated economic and social development. [ABSTRACT FROM AUTHOR]

Sensing the lowering of endoplasmic reticulum (ER) calcium (Ca2+), STIM1 mediates a ubiquitous Ca2+ influx process called the store-operated Ca2+ entry (SOCE). Dysregulated STIM1 function or abnormal SOCE is strongly associated with autoimmune disorders, atherosclerosis, and various forms of cancers. Therefore, uncovering the molecular intricacies of post-translational modifications, such as oxidation, on STIM1 function is of paramount importance. In a recent proteomic screening, we identified three protein disulfide isomerases (PDIs)—Prolyl 4-hydroxylase subunit beta (P4HB), protein disulfide-isomerase A3 (PDIA3), and thioredoxin domain-containing protein 5 (TXNDC5)—as the ER-luminal interactors of STIM1. Here, we demonstrated that these PDIs dynamically associate with STIM1 and STIM2. The mutation of the two conserved cysteine residues of STIM1 (STIM1-2CA) decreased its Ca2+ affinity both in cellulo and in situ. Knockdown of PDIA3 or P4HB increased the Ca2+ affinity of wild-type STIM1 while showing no impact on the STIM1-2CA mutant, indicating that PDIA3 and P4HB regulate STIM1's Ca2+ affinity by acting on ER-luminal cysteine residues. This modulation of STIM1's Ca2+ sensitivity was further confirmed by Ca2+ imaging experiments, which showed that knockdown of these two PDIs does not affect STIM1-mediated SOCE upon full store depletion but leads to enhanced SOCE amplitudes upon partial store depletion. Thus, P4HB and PDIA3 dynamically modulate STIM1 activation by fine-tuning its Ca2+ binding affinity, adjusting the level of activated STIM1 in response to physiological cues. The coordination between STIM1-mediated Ca2+ signaling and redox responses reported herein may have implications for cell physiology and pathology. [ABSTRACT FROM AUTHOR]

As the most widely distributed scavenger birds on the Qinghai-Tibetan Plateau, Himalayan vultures (Gyps himalayensis) feed on the carcasses of various wild and domestic animals, facing the dual selection pressure of pathogens and antibiotics and are suitable biological sentinel species for monitoring antibiotic resistance genes (ARGs). This study used metagenomic sequencing to comparatively investigate the ARGs and mobile genetic elements (MGEs) of wild and captive Himalayan vultures. Overall, the resistome of Himalayan vultures contained 414 ARG subtypes resistant to 20 ARG types, with abundances ranging from 0.01 to 1,493.60 ppm. The most abundant resistance type was beta-lactam (175 subtypes), followed by multidrug resistance genes with 68 subtypes. Decreases in the abundance of macrolide-lincosamide-streptogramin (MLS) resistance genes were observed in the wild group compared with the zoo group. A total of 75 genera (five phyla) of bacteria were predicted to be the hosts of ARGs in Himalayan vultures, and the clinical (102 ARGs) and high-risk ARGs (35 Rank I and 56 Rank II ARGs) were also analyzed. Among these ARGs, twenty-two clinical ARGs, nine Rank I ARG subtypes, sixteen Rank II ARG subtypes were found to differ significantly between the two groups. Five types of MGEs (128 subtypes) were found in Himalayan vultures. Plasmids (62 subtypes) and transposases (44 subtypes) were found to be the main MGE types. Efflux pump and antibiotic deactivation were the main resistance mechanisms of ARGs in Himalayan vultures. Decreases in the abundance of cellular protection were identified in wild Himalayan vultures compared with the captive Himalayan vultures. Procrustes analysis and the co-occurrence networks analysis revealed different patterns of correlations among gut microbes, ARGs, and MGEs in wild and captive Himalayan vultures. This study is the first step in describing the characterization of the ARGs in the gut of Himalayan vultures and highlights the need to pay more attention to scavenging birds. [ABSTRACT FROM AUTHOR]

Background: Lots of patients with bipolar disorder (BD) continue to have residual symptoms after treatment in their remission, BD exhibits intricate characteristics and transformation patterns in its residual symptoms, residual symptoms of different polarities and degrees can mix with and transform to each other. There is a need for further investigation of BD as a comprehensive multivariate disease system. The current research lacks network analyses focusing on BD's residual and subsyndromal symptoms. Methods: 242 patients were included with bipolar disorder in remission. We compared demographic data and differences in symptoms between populations with and without residual symptoms using t-tests and chi-square tests, with FDR applied for multiple comparison correction. Logistic regression was used to identify influencing factors for residual symptoms. Symptom networks were compared by network analysis to analyze the relationships between different types of residual symptoms. Results: Depressive residual symptoms (N=111) were more common than manic residual symptoms (n=29) in the patients included. The comparison between two groups with and without residual symptoms shows no difference in demographic data and medical history information. The main influencing factors related to residual symptoms were time from diagnosis to first treatment (OR=0.88), the first(OR=1.51) and second (OR=17.1)factors of the Mood Disorder Questionnaire (MDQ), the Quick Inventory of Depressive Symptomatology Self-Report (QIDS)(OR=5.28), the psychological(OR=0.68) and environment (OR=1.53) subscale of the World Health Organization Quality of Life Short Form (WHOQOL-BREF). There was a significant difference in network structure between the groups with and without residual symptoms (network invariance difference=0.4, p =0.025). At the same time, there was no significant difference between the groups with and without depressive residual symptoms. However, the symptom network in patients with depressive residual symptoms is more loosely structured than in those without, with symptoms exhibiting weaker interconnections. When there is no depressive or manic residual symptom, it can still form a symptom network and cause an impact on social function. Conclusion: This study underscores the complexity of bipolar disorder's residual symptoms. Although it primarily manifests as loosely structured depressive residual symptoms, manic residual symptoms should not be ignored. Future research should explore network-based interventions targeting specific symptom clusters or connections to improve residual symptom management and patient outcomes. [ABSTRACT FROM AUTHOR]