ZheJiang Economic and Trade Polytechnic

Irrigation decision-making using Reinforcement Learning (RL) performs well in changing environment, but easily falls into sub-optimal solutions with high-dimensional data. Deep Reinforcement Learning (DRL) has fused RL with Deep Learning (DL) and excels at learning adaptive and long-term irrigation strategies directly from high-dimensional environment data. This paper systematically reviews the applications of DRL in irrigation optimization, covering both pre-trained environments based on crop growth simulators and dynamic environments driven by real-time sensors. We discussed the strengths of classic DRL algorithms, including their ability to handle dynamic and non-linear environments, and reviewed their performance in irrigation multi-objective optimization and decision-making. In addition, we identified constraints in applying DRL in irrigation decision making, which include data scarcity, poor model interpretability, and difficulties in field deployment. It shows DRL can provide a powerful framework for adaptive irrigation, but is constrained by the gap between simulation and real-world complexity. To address these limitations, we discussed approaches in future work, such as developing multi-objective DRL algorithms. These approaches will improve DRL modeling outcomes and provide a technological foundation for smart agriculture and sustainable resource management. • Review the application of Deep Reinforcement Learning (DRL) in agricultural irrigation. • Analyze the performance of DRL algorithms in irrigation decision-making. • Compare DRL models based on different environment in irrigation optimization. • Discuss the further work to improve DRL performance in irrigation optimization.

Social media's integration into education prompts exploration of its effects on mathematics learning outcomes. While Mathematics Learning with Social Media (MLSM) can create engaging environments, its impact on key factors such as mathematics self-efficacy (MathSE), mathematics interest (MathI), and self-regulation in mathematics learning (SR) remains underexplored. This study investigates the direct and indirect effects of MLSM on these variables to enhance mathematics education. A quantitative research design was employed, involving 398 university students who engaged in Mathematics Learning with Social Media (MLSM) activities. Participants were randomly selected from two universities in China, with a gender distribution of 43% male and 57% female. The sample included students from diverse academic programs, including science, technology, engineering and mathematics (STEM) (37.9%), economics and management (43.7%), and humanities and social sciences (17.3%). Data were collected through validated survey instruments that measured mathematics self-efficacy (MathSE), mathematics interest (MathI), and self-regulation in mathematics learning (SR). A two-step structural equation modeling (SEM) approach was used to analyze the relationships between MLSM and the three variables, examining both direct effects and mediation pathways. The findings revealed that MLSM had significant direct effects on both MathI (β = 0.343, p < 0.001) and SR (β = 0.578, p < 0.001) indicating that the use of social media in mathematics learning fosters students' interest in mathematics and enhances their ability to self-regulate their mathematics learning processes. Furthermore, while the direct influence of MLSM on MathSE was not substantial, its indirect effects through MathI (MLSM→MathI→MathSE, β = 0.092, p < 0.001), SR (MLSM→SR→MathSE, β = 0.418, p < 0.001) and both SR and MathI (MLSM→SR→MathI→MathSE, β = 0.115, p < 0.001) were found to be significant. These results highlight the mediating roles of interest and self-regulation in strengthening students' confidence in their mathematics abilities. This study underscores the transformative potential of social media as a valuable tool for mathematics education. By effectively integrating MLSM into instructional practices, educators can foster students' interest, enhance their self-regulation skills, and indirectly build their self-efficacy in mathematics. The findings provide actionable insights for designing innovative educational strategies and policies that leverage social media to create dynamic and learner-centered environments, particularly in mathematics. This research contributes to the broader understanding of social media's role in the digital age, emphasizing its capacity to support self-directed and effective learning in academic disciplines.

SmD1 isolated from seeds of common chickweed Stellaria media has strong inhibitory activity against phytopathogenic fungi and oomycetes in the micromolar range (IC50 ≤ 1 μM). However, the low production of plant defensins in natural strains limits their large-scale actual production. In this study, defensin gene SmD1 was successfully heterologously expressed in Escherichia coli BL21 (DE3) for efficient production of plant defensins. The defensin gene SmD1 fused with thioredoxin was cloned into pET22b (+) vector. Then, it was transformed into E. coli BL21 (DE3) and expressed solubly after induction of isopropyl-β-D-thiogalactopyranoside (IPTG). At 50 °C, active SmD1 was released by 50% (v/v) formic acid hydrolysis of the cleavage of Asp-Pro bond between fused proteins. The recombinant protein SmD1 was purified by Ni-IDA column and showed significant antifungal activities against fungi. The induction conditions was optimized, and the results showed that the antimicrobial activity reached its maximum when the IPTG had a concentration of 0.6 mmol/L, a temperature of 25 °C, an induction time of 12 h and an OD600 of 0.8.

Aims: Adenosine and salidroside exert both preventive and therapeutic effects on neurodegenerative diseases, including Alzheimer's and Parkinson's diseases. However, the mechanism is unclear. Methodology: N2 wild-type and EG6890 (Ador-1 gene knockout) Caenorhabditis elegans were used as models, and 0.03, 0.3, and 3 mM adenosine and salidroside were applied to systematically evaluate their effects on the nematodes' physiological indicators (including pharyngeal pumping, bending, head swinging, and swimming). The interaction between salidroside and Ador-1 adenosine receptors was further investigated using molecular docking. Results: The results revealed that N2 wild-type treatment with different concentrations of salidroside and adenosine significantly downregulated pharyngeal pumping, bending, head swinging, and swimming. Comparison of the relative motor ability indices of the N2 and EG6890 strains indicated that adenosine modulated the nematodes' motor abilities via adenosine receptors. In addition to regulating motor behavior through adenosine receptors, salidroside may involve other receptors or demonstrate concentration-dependent effects. Molecular docking results revealed that salidroside exhibits a stronger affinity for the Ador-1 receptor compared to adenosine, suggesting that both compounds regulate motor function through this receptor pathway. Conclusion: This study provides a novel experimental foundation for elucidating the neuroprotective mechanisms of salidroside and adenosine as adenosine receptor agonists, as well as for related drug screening.

The cAMP response element binding protein (CREB)-binding protein (CBP) is a histone acetyltransferase that plays an indispensable role in regulating the acetylation of histone and non-histone proteins. Recently, it has been discovered that chemical inhibitors A485 and C646 can bind to Bombyx mori's CBP (BmCBP) and inhibit its acetyltransferase activity. Notably, the binding ability of A485 with BmCBP showed a very low Kd value of 48 nM by surface plasmon resonance (SPR) test. Further identification showed that both A485 and C646 can decrease the acetylation level of known substrate H3K27 and only 1 μM of A485 can almost completely inhibit the acetylation of H3K27, suggesting that A485 is an effective inhibitor of BmCBP's acetyltransferase activity. Moreover, it was confirmed that A485 could downregulate the expression of acetylated Bm30K-24 protein at a post-translational level through acetylation modification by BmCBP. Additionally, it was found that A485 can downregulate the stability of Bm30K-24 and improve its ubiquitination level, suggesting that the acetylation modification by BmCBP could compete with ubiquitination modification at the same lysine site on Bm30K-24, thereby affecting its protein stability. Here, we predict that A485 may be a potent CBP acetyltransferase inhibitor which could be utilized to inhibit acetyltransferase activity in insects, including silkworms.

n the context of high-level opening-up, the digital economy has become a key driver of economic growth and industrial upgrading, emerging as a central issue in China's modern economic development. This study explores the significance of digital economy innovation in this context and addresses the challenges it faces, such as the need for technological advancement, incomplete legal frameworks, and a shortage of relevant talent. Strategies to enhance technological innovation, improve legal systems, and streng1hen the cultivation and attraction of digital economy talent are proposed. The feasibility of these strategies is validated through a case study of Wenzhou, Zhejiang, providing insights for the development of China's digital economy in the new era.

Maize chlorotic mottle virus (MCMV) is the only species in the Mahromovirus genus and is often co-infected with one or several viruses of the Potyvirus genus, posing a great threat to the global maize industry. Effective viral integrated management measures are dependent on the timely and proper detection of the causal agent of the disease. In this work, six super-sensitive and specific monoclonal antibodies (mAbs) against MCMV were first prepared using purified MCMV virions as the immunogen. Then, the Dot enzyme-linked immunosorbent assay (Dot-ELISA) was established based on the obtained mAbs, and it can detect MCMV in infected maize leaf crude extracts diluted up to 1:10,240-fold (w/v, g/mL). Furthermore, a rapid and user-friendly Au nanoparticle-based immunochromatographic test strip (AuNP-ICTS) based on paired mAbs 7B12 and 17C4 was created for monitoring MCMV in point-of-care tests, and it can detect the virus in a 25,600-fold dilution (w/v, g/mL) of MCMV-infected maize leaf crude extracts. The whole test process for ICTS was completed in 10 min. Compared with conventional reverse transcription-polymerase chain reaction (RT-PCR), the detection endpoint of both serological methods is higher than that of RT-PCR, especially the Dot-ELISA, which is 12.1 times more sensitive than that of RT-PCR. In addition, the detection results of 20 blinded maize samples by the two serological assays were consistent with those of RT-PCR. Therefore, the newly created Dot-ELISA and AuNP-ICTS exhibit favorable application potential for the detection of MCMV in plant samples.