Abstract
Over the years, methods and algorithms have been extensively studied to solve variations of the rectangular twodimensional strip packing problem (2D-SPP), in which small rectangles must be packed inside a larger object denominated as a strip, while minimizing the space necessary to pack all rectangles. In the rectangular 2D-SPP, constraints are used to restrict the packing process, satisfying physical and real-life practical conditions that can impact the material cutting. The objective of this paper is to present an extensive literature review covering scientific publications about the rectangular 2D-SPP constraints in order to provide a useful foundation to support new research works. A systematic literature review was conducted, and 223 articles were selected and analyzed. Real-life practical constraints concerning the rectangular 2D-SPP were classified into seven different groups. In addition, a bibliometric analysis of the rectangular 2D-SPP academic literature was developed. The most relevant authors, articles, and journals were discussed, and an analysis made concerning the basic constraints (orientation and guillotine cutting) and the main solving methods for the rectangular 2D-SPP. Overall, the present paper indicates opportunities to address real-life practical constraints.

Abstract
In the field of immersive learning, instructors often find it challenging to match their pedagogical approaches and content knowledge with specific technologies. Unfortunately, this usually results in either a lack of technology use or inappropriate use of some technologies. Teachers and trainers wishing to use immersive learning environments face a diversity of technological and pedagogical alternatives. To scaffold educators in their planning of immersive learning educational activities, we devised a recommendation tool, which maps educational context variables to the dimensions of immersion and uses educators' contexts to identify the closest educational uses. Sample educational activities for those uses are then presented, for various types of educational methodologies. Educators can use these samples to plan their educational activities in line with their current resources or to innovate by pursuing entirely different approaches.

Abstract
A smart grid is the future vision of power systems that will be enabled by artificial intelligence (AI), big data, and the Internet of things (IoT), where digitalization is at the core of the energy sector transformation. However, smart grids require that energy managers become more concerned about the reliability and security of power systems. Therefore, energy planners use various methods and technologies to support the sustainable expansion of power systems, such as electricity demand forecasting models, stochastic optimization, robust optimization, and simulation. Electricity forecasting plays a vital role in supporting the reliable transitioning of power systems. This paper deals with short-term load forecasting (STLF), which has become an active area of research over the last few years, with a handful of studies. STLF deals with predicting demand one hour to 24 h in advance. We extensively experimented with several methodologies from machine learning and a complex case study in Panama. Deep learning is a more advanced learning paradigm in the machine learning field that continues to have significant breakthroughs in domain areas such as electricity forecasting, object detection, speech recognition, etc. We identified that the main predictors of electricity demand in the short term: the previous week's load, the previous day's load, and temperature. We found that the deep learning regression model achieved the best performance, which yielded an R squared (R-2) of 0.93 and a mean absolute percentage error (MAPE) of 2.9%, while the AdaBoost model obtained the worst performance with an R-2 of 0.75 and MAPE of 5.70%.

Abstract
Guided by a real case, this paper efficiently proposes a new metaheuristic algorithm based on Simulated Annealing to solve the Heterogeneous Vehicle Routing Problem with Time Windows to deliver fresh meat in urban environments. Our proposal generates an initial feasible solution using a hybrid heuristic based on the well-known Travelling Salesman Problem (TSP) solution and, subsequently, refining it through a Simulated Annealing (SA). We have tested the efficiency of the proposed approach in a company case study related to the planning of the transportation of a regional distribution center meat company to customers within the urban and rural perimeter of Bogota, Colombia. The main goal is to reach a service level of 97% while reducing operational costs and several routes (used vehicles). The results show that the proposed approach finds better routes than the current ones regarding costs and service level within short computing times. The proposed scheme promises to solve the refrigerated vehicle routing problem. (c) 2022 by the authors; licensee Growing Science, Canada

Abstract
Objective: This study aimed to identify health behaviours that determine adolescent's adherence to the Mediterranean diet (MD) through a decision tree statistical approach. Design: Cross-sectional study, with data collected through a self-fulfilment questionnaire with five sections: (1) eating habits; (2) adherence to the MD (KIDMED index); (3) physical activity; (4) health habits and (5) socio-demographic characteristics. Anthropometric and blood pressure data were collected by a trained research team. The Automatic Chi-square Interaction Detection (CHAID) method was used to identify health behaviours that contribute to a better adherence to the MD. Setting: Eight public secondary schools, in Algarve, Portugal. Participants: Adolescents with ages between 15 and 19 years (n 325). Results: According to the KIDMED index, we found a low adherence to MD in 9 center dot 0 % of the participants, an intermediate adherence in 45 center dot 5 % and a high adherence in 45 center dot 5 %. Participants that regularly have breakfast, eat vegetable soup, have a second piece of fruit/d, eat fresh or cooked vegetables 1 or more times a day, eat oleaginous fruits at least 2 to 3 times a week, and practice sports and leisure physical activities outside school show higher adherence to the MD (P < 0 center dot 001). Conclusions: The daily intake of two pieces of fruit and vegetables proved to be a determinant health behaviour for high adherence to MD. Strategies to promote the intake of these foods among adolescents must be developed and implemented.

Abstract
Production scheduling generates a direct impact on several aspects of manufacture, such as the number of delays in delivery to customers, total flow time, as well as the percentage of equipment used. It must, therefore, constitute a priority in production management, which should seek to implement scheduling techniques that will lead to positive results from the perspective of the quality of the solution. However, the methodology cannot overlook the functional aspect of the time which has elapsed until the solution is reached. This study is based on a real and specific module software improvement into a company devoted to the development of ERP software systems (Enterprise Resource Planning). It presents a solution for the production scheduling module focused on flow-shop operations, comprising a total of nine dispatching rules. An additional solution for scheduling is also proposed, which resorts to metaheuristic simulated annealing. Both solutions are compared to each other by using the quality-functionality binomial approach. These two environments are further contrasted with a third, where no effective solution for production scheduling exists. The environment which includes scheduling through dispatching rules was compared to the environment where no production scheduling was implemented. The results obtained from this analysis show an improvement of 13%. The simulated annealing solution presents an improvement of 3,6% when compared to a solution which uses dispatching rules. This improvement implies one extra minute in the calculation of the final solution.