To investigate the possible role of arbuscular mycrrhizal fungi (AMF) in alleviating the negative effects of salinity on Stevia rebaudiana (Bert.), the regenerated plantlets in tissue culture was transferred to pots in greenhouse and inoculated with Glomus intraradices. Salinity caused a significant decrease in chlorophyll content, photosynthesis efficiency and enhanced the electrolyte leakage. The use of AMF in salt –affected plants resulted in improved all above mentioned characteristics. Hydrogen peroxide and malondialdehyde (MDA) contents increased in salt stressed plants while a reduction was observed due to AMF inoculation. CAT activity showed a significant increase up to 2 g/l and then followed by decline at 5 g/l NaCl in both AMF and non-AMF treated stevia, however, AMF inoculated plants maintained lower CAT activity at all salinity levels (2 and 5 g/l). Enhanced POX activities in salt- treated stevia plants were decreased by inoculation of plants with AMF. The addition of NaCl to stevia plants also resulted in an enhanced activity of SOD whilst, AMF plants maintained higher SOD activity at all salinity levels than those of non-AMF inoculated plants. AMF inoculation was capable of alleviating the damage caused by salinity on stevia plants by reducing oxidative stress and improving photosynthesis efficiency. 

Rambutan (Nephelium lappaceum L.) was introduced to Mexico in 1959. Currently there is an estimated planted area of 835.96 ha and a production of 8,730.27 tons. The fruit is mainly consumed fresh, but quickly loses its external appearance due to dehydration and browning, which limits its commercialization, an alternative may be minimal processing and adjuvant treatments that extend the shelf life. The objective of this work was to evaluate the effect of coating with cactus mucilage (Opuntia ficus-indica), in the preservation of minimally processed rambutan stored at 5 °C, in two types of packaging. The rambutan was sanitized with chlorinated water (80 ppm), the epicarp was removed and batches were formed for each treatment. The factors were type of container (polyethylene bag and polystyrene container), coating (with and without coating) and time (0, 3, 6, 6, 10 and 12 d). The coating consisted of mucilage obtained from developing cladodes (15–21 cm), applied by dipping. All treatments were stored at 5 ℃. Total soluble solids (TSS), firmness (N) and color (L*, a*, b*, chroma and hue angle) were evaluated at each storage period. Also, 40 untrained judges (47% male and 53% female) evaluated sensory acceptability, consumption intention and acceptance/rejection. The results showed significant effect (p ≤ 0.05) of package type on firmness, chroma and hue angle. Coating had an effect on L* value and product acceptability. Consumption intention was higher, and was maintained for 10 days, in fruits with coating and packaged in polyethylene bags, stored at 5 ℃.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

In green construction, sustainable resources are essential. One such material is copper, which is widely utilized in electronics, transportation, manufacturing, and residential buildings. As a very useful material, it has many beneficial impacts on human life. Observed from the recent demand spike is in line with the overall trend and the current growing smelter construction in Indonesia. Researchers intend to adapt the existing Copper Smelting Plant Building into an environmentally friendly building as a part of the production chain, in addition to reducing public and environmental concerns about the consequences of this development. We have identified a disparity in cost, where the high cost of green buildings is an obstacle to its implementation to enhance the cost performance with increased renewable energy of the Smelter Construction Building, this study investigates the application of LEED parameters to evaluate green retrofit approaches through system dynamics. The most relevant features of the participant assessments were identified using the SEM-PLS approach, which is used to build and test statistical models of causal models. We have results for this Green Retrofitting study following significant variables according to the following guidelines: innovation, low-emission materials, renewable energy, daylighting, reducing indoor water usage, rainwater management, and access to quality transit.

This study aims to develop and validate a strategic model tailored to the unique challenges and contexts faced by micro, small, and medium-sized enterprises (MSMEs) in Ecuador, enhancing their operational efficiency and access to financing. Employing a quantitative approach, the research utilized a non-experimental, cross-sectional design to gather data from a sample of 358 companies. The study revealed that MSMEs are significantly hindered by limited access to financing, lack of managerial skills, and technological gaps. Despite these challenges, MSMEs demonstrated considerable adaptability and resilience, underscoring their critical role in the local economy. The strategic model proposed leverages Porter’s Diamond Model to identify and address the specific competitive and operational challenges encountered by these enterprises. Key findings include the necessity for enhanced financial literacy, simplified regulatory frameworks, and the integration of digital technologies to improve competitiveness. The proposed model focuses on strategic training, fostering innovation, and creating a more supportive financing environment. The implications of this study are profound, suggesting that policymakers and practitioners should streamline regulatory processes, enhance financial and technological support frameworks, and provide tailored training programs. These strategies are intended to bolster the sustainability and growth of MSMEs, contributing to broader economic development. This research contributes to the academic literature by providing empirical evidence on the challenges faced by MSMEs in developing economies and proposing a contextually adapted strategic model to mitigate these challenges, thereby enhancing their economic impact and sustainability.