Illegal, unreported, and unregulated fishing (IUU fishing) crimes by rogue fisheries companies are rife in the sea waters of Riau Province. However, this issue is rarely reported by those provincial journalists in the online media where they work. In fact, in Riau, there are 163 online media companies and 600 competent journalists; 200 of them live in capture fisheries center areas. Apart from the journalist competency factor, the decision to make IUU fishing news can also be influenced by the fisheries company intervention that committed the crime. Besides, the policy role of media leaders—editors, editors-in-chief, and media owners—also determines journalists’ decisions to make those news stories. This research aims to analyze the influence of journalist competence and fishing company intervention on the decision to make IUU fishing news, as well as the role of media leader policy as mediators in these influences. This survey involved 100 competent journalists as respondents. Data collection was carried out through a questionnaire containing a number of closed statements measured on a 5-point Likert scale, which was distributed to respondents. The data were analyzed using the Structural Equation Modeling (SEM) method. The research results show that the fishing company intervention has a negative and significant influence on the decision to make IUU fishing news in Riau, while journalist competence does not. Additionally, media leader policy was found to play a significant role in mediating the influence of fisheries company intervention and journalist competence on the decision to make IUU fishing news. The leader policy could prevent journalists from making IUU fishing news if fisheries companies, who are responsible for those crimes, intervene and request it. Those actions of media leaders need to be questioned because they can hamper the media’s function as a means of disseminating information, educating the public, and implementing social control, especially those related to combating IUU fishing crimes.

In the wake of the COVID-19 pandemic, the prevalence of online education in primary education has exhibited an upward trajectory. Relative to traditional learning environments, online instruction has evolved into a pivotal pedagogical modality for contemporary students. Thus, to comprehensively comprehend the repercussions of environmental changes on students’ psychological well-being in the backdrop of prolonged online education, this study employs an innovative methodology. Founded upon three elemental feature sequences—images, acoustics, and text extracted from online learning data—the model ingeniously amalgamates these facets. The fusion methodology aims to synergistically harness information from diverse perceptual channels to capture the students’ psychological states more comprehensively and accurately. To discern emotional features, the model leverages support vector machines (SVM), exhibiting commendable proficiency in handling emotional information. Moreover, to enhance the efficacy of psychological well-being prediction, this study incorporates an attention mechanism into the traditional Convolutional Neural Network (CNN) architecture. By innovatively introducing this attention mechanism in CNN, the study observes a significant improvement in accuracy in identifying six psychological features, demonstrating the effectiveness of attention mechanisms in deep learning models. Finally, beyond model performance validation, this study delves into a profound analysis of the impact of environmental changes on students’ psychological well-being. This analysis furnishes valuable insights for formulating pertinent instructional strategies in the protracted context of online education, aiding educational institutions in better addressing the challenges posed to students’ psychological well-being in novel learning environments.

Adopting electric vehicles (E.V.) is crucial for promoting sustainable mobility in metropolitan areas such as Medan, Indonesia. To achieve this, it is essential to comprehend the factors that influence E.V. adoption, with a particular focus on the impact of media. This study examines the adoption of electric vehicles in Medan and evaluates the influence of the media on the public’s perception and policy decisions. Opinions, concerns, and recommendations surrounding electric vehicles were examined through surveys and interviews with 35 stakeholders, including students, lawmakers, industry experts, business owners, and media professionals. The findings indicate a strong knowledge and favorable perception of electric vehicles in Medan. However, there are worries regarding the expenses associated with E.V.s and the availability of charging infrastructure. Notably, 60% of the respondents identified media as their primary source of information, highlighting its significant influence. Encouraging cooperation between media, professionals, and stakeholders is advisable to achieve accurate and balanced reporting. This can be done by employing techniques like showcasing success stories and emphasizing the environmental advantages to encourage acceptance and implementation. This study provides valuable insights into improving the adoption of electric vehicles in Medan. It emphasizes the significance of implementing effective media strategies and supportive policies to achieve sustainable transportation solutions.

This study aims to determine the effects of monosodium glutamate (MSG) dosage on the yield of long beans (Vigna sinensis L.) of the Peleton variety. The use of MSG as a food ingredient has been a topic of debate, but research on its impact on plant growth is still limited, especially regarding long beans. Therefore, this research is important for providing further understanding of the influence of MSG on long beans plants. The study was conducted from July to October 2023 in Mata Air Village, Central Kupang District, Kupang Regency, East Nusa Tenggara Province. The research method used was a Randomized Complete Block Design (RCBD) with 9 treatments and 3 replications. The treatments included: No MSG, MSG at doses of 2.5 g/plant, 5 g/plant, 7.5 g/plant, 10 g/plant, 12.5 g/plant, 15 g/plant, 17.5 g/plant, and 20 g/plant. Parameters observed included flowering age (days), number of pods (pieces), pod length (cm), and pod weight (g). Based on the results and discussion, it can be concluded that MSG application had a significant effect on the number, length, and weight of pods, but had a non-significant effect on flowering age. The treatment of 15 g/plant was identified as the optimal MSG dosage for the plants, resulting in the highest number of pods (16.2), longest pod length (60.4 cm), and highest pod weight (256.4 g/plant). This research is innovative in exploring the potential use of monosodium glutamate (MSG) on long beans plants, particularly the Peleton variety. The focus on MSG application as a growth stimulant is an innovative step that has been less studied previously. The discovery of the optimal MSG dosage (15 g/plant) for achieving the best results provides valuable information for farmers to enhance productivity efficiently, sustainably, and environmentally friendly. Information about MSG’s potential as a plant stimulant can serve as a starting point for more sustainable agricultural strategies aimed at optimizing available resources.

The effect of foliar treatment with brassinosteroid (BR) on gender distribution in flowers of walnut (Juglans regia L. cv. Chandler) was investigated. Grafted walnut saplings (‘Chandler’) on the wild walnut (Juglans regia L.) rootstock were planted into 70-liter pots with a soil: peat: perlite medium and grown in pots between 2016–2020. BRs (24-epibrassinolide; EBR and 22(S), 23(S)-homobrassinolide; HBR) were applied at a concentration of 1 mg L^–1 for four consecutive years at the time of flower differentiation. The experimental design was completely randomized with three replicates. The results show that BR applications could alter the sexual distribution of the walnut’s flower. BRs application significantly increased the number of total flowers and female flowers per tree. The number of female flowers was also increased by the season. The highest number of female flowers (20.9) was observed in the trees in 2020 and the application of 1 mg L^–1 of HBR. It was determined that the annual growth of the plant and the increase in the number of females and total flowers were positively related. The effect of BRs indicated that the response was BR-type specific.