In Nigeria, deforestation has led to an unimaginable loss of genetic variation within tree populations. Regrettably, little is known about the genetic variation of many important indigenous timber species in Nigeria. More so, the specific tools to evaluate the genetic diversity of these timber species are scarce. Therefore, this study developed species-specific markers for Pterygota macrocarpa using state-of-the-art equipment. Leaf samples were collected from Akure Forest Reserve, Ondo State, Nigeria. DNA isolation, quantification, PCR amplification, gel electrophoresis, post-PCR purification, and sequencing were done following a standardized protocol. The melting temperatures (TM) of the DNA fragments range from 57.5 ℃to 60.1 ℃ for primers developed from the MatK gene and 58.7 ℃ to 60.5 ℃ for primers developed from the RuBisCo gene. The characteristics of the ten primers developed are within the range appropriate for genetic diversity assessment. These species-specific primers are therefore recommended for population evaluation of Pterygota macrocarpa in Nigeria.

Taking the west slope of Cangshan Mountain in Yangbi County, Dali as the research site, on the basis of investigating the local natural geographical conditions, topography and biodiversity status of Cangshan Mountain, the CAP protection action planning method was adopted, and the priority protection objects were determined to be native forest vegetation, rare and endangered flora and fauna, alpine vertical ecosystems, hard-leaf evergreen broad-leaved forests and cold-tempered coniferous forests; The main threat factors were commercial collection, tourism development and overgrazing. Biodiversity conservation on the western slope of Cangshan Mountain should take species as “point”, regional boundary as “line”, ecosystem and landscape system as “plane”, so as to realize the overall planning structure system combining “point—line—plane”, which can be divided into conservation core area, buffer zone and experimental area. The results can provide a reference for biodiversity conservation on the western slope of Cangshan Mountain.

Telecommunications markets have a giant impact on countries’ economies. An example of this is the great potential offered by the internet service, which allows growth in various aspects such as productivity, education, health, and connectivity. A few companies dominate telecommunications markets, so there is a high market concentrations risk. In that sense, the state has to generate strong regulation in the sector. Models for measuring competition in telecommunications markets allow the state to monitor the concentration performance in these markets. The prediction of competition in the telecommunications market based on artificial intelligence techniques would allow the state to anticipate the necessary controls to regulate the market and avoid monopolies and oligopolies. This work’s added value and the main objective is to measure the current concentration level in the Colombian telecommunications market, this allows for competitive analysis in order to propose effective strategies and methodologies to improve competition in the future of Colombian telecommunications services operators. The main result obtained in the research is the existence of concentration in the Colombian telecommunications market.

Twenty-two tomato (Solanum lycopersicum L.) genotypes were examined for correlation and path analysis in the randomized block design under open field conditions. Total fruit yield showed a significant positive correlation with the number of fruits per plant, average fruit weight, lycopene content, and percent seedling survival in the field at both the genotypic and phenotypic levels. A strong correlation between these characters revealed that selection based on these characters would consequently improve the total fruit yield. Path analysis showed that the number of fruits per plant, average fruit weight, percent seedling survival in the nursery, and number of locules per fruit exhibited high positive direct phenotypic effects on total fruit yield, whereas the number of fruits per plant, average fruit weight, percent seedling survival in the field, and pollen viability had very high positive direct genotypic effects. Therefore, to increase the yield, it would be profitable to prioritize these traits in the selection program.

Over several centuries, the native vegetation of the flat part of the Bogotá Savanna has been almost completely replaced by crops, pastures and urbanization. The last remnant of this vegetation is a small forest (10 hm²), located at Hacienda Las Mercedes on the northern edge of the city of Bogotá. The reduced size and isolation of the forest, aggravated by the uncontrolled growth of invasive vegetation (lianas and wild blackberry) has resulted in the loss of many species. However, in recent years the forest has been subject to rehabilitation actions and currently the area is immersed in a reserve where more extensive restoration programs are planned. In order to evaluate changes in the bird community to estimate the effects of restoration actions, the avifauna present in 2001–2002 and in 2014 was recorded by visual and auditory records at fixed points in the forest. Twenty-seven forest species were found in the first census and 30 in the second, and the relative abundances of at least a third of them also increased over the 13 years, indicating a positive result in the recovery of the forest. The results highlight the recovery capacity of the degraded ecosystems and the importance of continuing with restoration actions in the reserve area.

This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.