The purpose of this article is to determine the equitability of airport and university allocations throughout Ethiopian regional states based on the number of airports and institutions per 1 million people. According to the sample, the majority of respondents believed that university allocation in Ethiopia is equitable. In contrast, the majority of respondents who were asked about airports stated that there is an uneven distribution of airports across Ethiopia’s regional states. Hence, both interviewees and focus group discussants stated that there is a lack of equitable distribution of universities and airports across Ethiopia’s regional states. This paper contributes a lesson on how to create a comprehensive set of determining factors for equitable infrastructure allocation. It also provides a methodological improvement for assessing infrastructure equity and other broader implications across Ethiopian regional states.

Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.

Species of the Moraceae family are of great economic, medicinal and ecological importance in Amazonia. However, there are few studies on their diversity and population dynamics in residual forests. The objective was to determine the composition, structure and ecological importance of Moraceae in a residual forest. The applied method was descriptive and consisted of establishing 16 plots of 20 m × 50 m (0.10 ha), in a residual forest of the Alexánder von Humboldt substation of the National Institute of Agrarian Innovation-INIA, Pucallpa, department of Ucayali, where individuals of arboreal or hemi-epiphytic habit, with DBH ≥ 2.50 cm, were evaluated. The floristic composition was represented by 33 species, distributed in 12 genera; five species not recorded for Ucayali were found. Structurally, the family was represented by 138 individuals/ha with a horizontal distribution similar to an irregular inverted “J”. However, there were different horizontal structures among species. It was determined that 85% of the species were in diameter class I (2.50 to 9.99 cm), being the most abundant Pseudolmedia laevis (Ruiz & Pav.) J.F. Macbr. (41.88 individuals/ha); and the most dominant were Brosimum utile (Kunth) Oken (1.71 m²∕ha) and Brosimum alicastrum subsp. bolivarense (Pittier) C.C.Berg (0.90 m²/ha). Likewise, P. laevis and B. utile were the most ecologically important. The information from the present research will allow the establishment of a baseline, which can be used to propose the management of Moraceae in residual forests in the same study area.

Lettuce (Lactuca sativa L.) is the main leafy vegetable grown in Brazil. Its productivity and quality are limited by the growing season, the nearby environment and the type of cultivar adopted. The objective of this work was to verify at different times of the year the best planting environment for lettuce cultivation in a semi-humid tropical climate. For this purpose, an experiment was set up in three different seasons (October–November 2014, January–March, May–July 2015). The experimental design was randomized blocks, in a 3 × 3 × 2 factorial arrangement, consisting of three seasons, three cultivars (cvs. Vera^®, Tainá^® and Rafaela^®) and two growing environments (low tunnel with beds protected with mulching consisting of soil protection with plastic fabric covering, and beds without protection or conventional cultivation) and four replicates per treatment. Plant biomass, stem length, head diameter, number of leaves per head and crop productivity were evaluated as response parameters. The results showed that the May–July period favored biomass production, head diameter and productivity. Despite the similarity between varieties, the variety Vera^® is more productive in biomass, number of leaves per head, stem length and productivity. The low tunnel planting system with mulching is adequate under the conditions evaluated for lettuce cultivation. This system in the May–July period favors a superior development in the characteristics biomass, head diameter and productivity, if compared to conventional cultivation during the October–November period.

Lattice Boltzmann models for diffusion equation are generally in Cartesian coordinate system. Very few researchers have attempted to solve diffusion equation in spherical coordinate system. In the lattice Boltzmann based diffusion model in spherical coordinate system extra term, which is due to variation of surface area along radial direction, is modeled as source term. In this study diffusion equation in spherical coordinate system is first converted to diffusion equation which is similar to that in Cartesian coordinate system by using proper variable. The diffusion equation is then solved using standard lattice Boltzmann method. The results obtained for the new variable are again converted to the actual variable. The numerical scheme is verified by comparing the results of the simulation study with analytical solution. A good agreement between the two results is established.