The cultivation of vegetables serves as a vital pillar in horticulture, offering an alternative avenue towards achieving economic sustainability. Unfortunately, farmers often lack adequate knowledge on optimizing resource utilization, which subsequently results in low productivity. Furthermore, there has been insufficient research conducted on the comparative profitability and efficient use of resources for pea cultivation. So, the present study was conducted to examine the profitability and resource use efficiency of conventional and organic pea production in Northwestern Himalayan state. Using the technique of purposive sampling, the districts and villages were selected based on the highest area. By using simple random sampling, a sample of 100 farmers was selected, out of which 50 were organic growers and 50 were inorganic growers, who were further categorized as marginal and small. The cost incurred was higher for the cultivation of inorganic vegetable crops, whereas returns and output-input ratio was higher in organic cultivation. The cultivation of peas revealed that the majority of inputs were being underutilized, and there was a need for proper reallocation of the resources, which would result in enhanced production. Further, major problems in the cultivation of vegetable crops were a high wage rate, a lack of organic certification, a shortage of skilled labour and a lack of technical knowledge.

The purpose of this work is to present the model of a Parabolic Trough Solar Collector (PTC) using the Finite Element Method to predict the thermal behavior of the working fluid along the collector receiver tube. The thermal efficiency is estimated based on the governing equations involved in the heat transfer processes. To validate the model results, a thermal simulation of the fluid was performed using Solidworks software. The maximum error obtained from the comparison of the modeling with the simulation was 7.6% at a flow rate of 1 L/min. According to the results obtained from the statistical errors, the method can effectively predict the fluid temperature at high flow rates. The developed model can be useful as a design tool, in the optimization of the time spent in the simulations generated by the software and in the minimization of the manufacturing costs related to Parabolic Trough Solar Collectors.

The Ecuadorian electricity sector encompasses generation, transmission, distribution and sales. Since the change of the Constitution in Ecuador in 2008, the sector has opted to employ a centralized model. The present research aims to measure the efficiency level of the Ecuadorian electricity sector during the period 2012–2021, using a DEA-NETWORK methodology, which allows examining and integrating each of the phases defined above through intermediate inputs, which are inputs in subsequent phases and outputs of some other phases. These intermediate inputs are essential for analyzing efficiency from a global view of the system. For research purposes, the Ecuadorian electricity sector was divided into 9 planning zones. The results revealed that the efficiency of zones 6 and 8 had the greatest impact on the overall efficiency of the Ecuadorian electricity sector during the period 2012–2015. On the other hand, the distribution phase is the most efficient with an index of 0.9605, followed by sales with an index of 0.6251. It is also concluded that the most inefficient phases are generation and transmission, thus verifying the problems caused by the use of a centralized model.

The pursuit of good governance by companies confronts a fundamental challenge: defining what constitutes “good governance”. Existing corporate governance codes and their implementation documents fall short of offering a clear answer to this crucial question. Despite the establishment of a reference framework years ago, the focus has shifted from defining the objectives of good governance to a consensus on the means of achieving these objectives. Unfortunately, this consensus often absolves stakeholders from providing detailed explanations. Achieving effective good governance necessitates a shift in focus towards the underlying goals of governance structures. Two potential approaches emerge in this context. While many companies rely on codes without explicitly outlining their objectives, there is a compelling case for urging or mandating them to articulate the purposes of the governance methods they employ in their reports. This level of specificity has the potential to enhance the reflective qualities of the transparency process, fostering a more comprehensive understanding of the governance landscape. Beyond merely discussing the objectives of corporate governance, the pursuit of good governance necessitates the implementation of instruments whose efficacy transcends reliance solely on market discipline. The aim is not to undermine the imperatives of transparency and justification. Instead, the intention is to recognize that these elements, while essential, do not independently ensure the effectiveness of soft law instruments, such as governance codes. Nowadays, it is crucial to assess the extent to which traditional corporate governance codes respond to the needs of companies in the era of digitalization and sustainability. Therefore, conducting a critical analysis of the existing corporate governance codes will contribute in shedding light on the gaps of these instruments to come up with recommendations for improvements. Aims and objectives: This article will focus on the following areas: Defining the role and purpose of corporate governance codes in enhancing corporate performance and accountability and discussing the challenges and limitations of corporate governance codes, including compliance issues and enforcement challenges. Presenting empirical evidence on the impact of corporate governance codes on corporate behavior and analyzing, through the principle of comply or explain, whether code adherence leads to improved corporate governance practices and financial performance. Discussing emerging trends in corporate governance and offering recommendations for improving the effectiveness of corporate governance codes.

An alternative for sustainable management in the cultivation of Capsicum annuum L. has focused on the use of plant growth promoting rhizobacteria (PGPR) and arbuscular mycorrhizal fungi (AMF). This research selected PGPRPGPR and AMF based on their effect on Bell Pepper and Jalapeño bell pepper plants. Five bacterial strains isolated from different localities in the state of Mexico (P61 [Pseudomonas tolaasii], A46 [P. tolaasii], R44 [Bacillus pumilus], BSP1.1 [Paenibacillus sp.] and OLs-Sf5 [Pseudomonas sp.]) and 3 AMF treatments (H1 [consortium isolated from Chile rhizosphere in the state of Puebla], H2 [Rhizophagus intraradices] and H3 [consortium isolated from lemon rhizosphere from the state of Tabasco]). In addition, a fertilized treatment (Steiner solution 25%) and an absolute control were included. Jalapeño bell pepper “Caloro” and Bell Pepper “California Wonder” seedlings were inoculated with AMF at sowing and with CPB 15 days after emergence, and grown under controlled environment chamber conditions. In Jalapeño bell pepper, the best bacterial strain was P61 and the best AMF treatment was H1; in Bell Pepper the best strain was R44 and the best AMF were H3 and H1. These microorganisms increased the growth of jalapeño bell pepper and Bell Pepper seedlings compared to the unfertilized control. Likewise, P61 and R44 positively benefited the photosynthetic capacity of PSII.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.