Studies related to the use of steel mill slag have become essential, because of the possibility of its use as a component of substrates in the production of seedlings and because this use minimizes the risk of environmental contamination, resulting from inadequate disposal. Thus, the objective of this work was to evaluate the effect of increasing levels of steel slag in substrates composed of soil with tanned bovine manure and sand, on the growth variables and the quality of “Dedo-de-moça” pepper (Capsicum baccatum L.) seedlings. A randomized block design was used with five slag concentrations (0%, 2.5%, 5%, 10% and 20%) and four repetitions. Evaluations occurred at 55 days after sowing, consisting of counting the number of leaves, measuring plant height and collar diameter, quantifying the dry mass of leaves and roots and determining the Dickson Quality Index. Regression models were fitted (P < 0.05) to treatments with increasing levels of steel slag. The addition around 10% of slag to the substrate provided the highest values of growth variables, in seedlings of Dedo-de-moça pepper.

Most airport development projects entail disputes due to the features that are distinctive and complicated. Disputes can be minimized through creative problem-solving by implementing knowledge management practices into the system. This study investigates the direct influence of knowledge management (KM) on dispute minimization (DM) along with the key factors for developing a strategy that can enhance KM success. A mixed method was adopted including statistical data analysis based on the PLS-SEM and descriptive analysis with the SECI (Socialization, Externalization, Combination, Internalization) model approach for strategy development. These findings show that KM has a positive and significant direct influence on DM, while the factors that are considered to have a significant influence on KM success are human resources management (HR) and learning & training (LT) on airport development projects in state-owned airport companies. This research supports the importance of a well-developed HR system accompanied by regular LT to all members of the organization to optimize and encourage the spread of knowledge in the organization.

Effective harvesting strategies are crucial for maximizing annual catch and ensuring the sustainability of lobster (Homarus americanus) farming. This paper presents a nonlinear objective programming model to optimize harvesting intensity based on lobster life cycle dynamics and harvesting characteristics. We model the population dynamics of 1-4 year-old lobsters using differential equations to account for natural mortality, spawning, and harvesting effects. Solving the model with LINGO 12.0, we determine that the optimal harvesting intensity coefficient is 17.36, which maximizes annual catch to 3.88 × 10¹⁰ grams. Results indicate that maintaining harvesting intensity around this optimal value balances economic benefits and population stability, ensuring sustainable farm operations.