Taking six typical forest communities in Taizhou Green Heart (ⅰ: Liquidambar formosana + Ulmus pumila + Celtis sinensis; ⅱ: Celtis sinensis + Pterocarya stenoptera + Pinus massoniana; ⅲ: Sapindus mukorossi + Sapium sebiferum + Cupressus funebris; ⅳ: Liquidambar formosana + Acer buergerianum + Cupressus funebris); ⅴ: Celtis sinensis + Ligustrum compactum + Pinus massoniana; ⅵ: Machilus ichangensis + Sapindus mukorossi + Acer buergerianum) as the research objects, 5 indicators: Shannon-Wiener (H), Patrick richness (R1), Margalef species richness (R2), Pielou evenness (J) and ecological dominance (D) were used to analyze species diversity in forest communities. The results showed that: (1) the community was rich in plant resources, with a total of 50 species belonging to 40 genus and 31 families, including 19 species in tree layer, 22 species in shrub layer and only 9 species in herb layer, few plant species; (2) the species richness and diversity index of tree layer and shrub layer were significantly higher than that of herb layer, but there were differences among different communities in the same layer, and no significant difference was reached; (3) the species richness and community diversity of the six communities showed as follows: community VI > community I > community II > community IV > community V > community III.

In the current work, it was investigated to the K X-ray fluorescence efficiency and chemical effect on vacancy transfer probability for some tin compounds. We used Br₂Tin, TinI₂, SeTin, TinF₂, TinSO₄, TinCl₂, TinO and TinS compounds for experimental study. The target samples were irradiated with ²⁴¹Am annular radioactive source at the intensity of 5 Ci which emits gamma rays at wavelength of 0.2028 nm. The characteristic x-rays emitted because of the excitation are collected by a high-resolution HPGe semiconductor detector. It has been determined that the experimental calculations of the tin (Sn) element are compatible with the theoretical calculation. In addition, we have calculated the experimental intensity ratios, fluorescence yields and total vacancy transfer probabilitiesfor other Sn compounds. 

The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.

Despite Cameroon’s immense sand reserves, several enterprises continue to import standardized sands to investigate the properties of concretes and mortars and to guarantee the durability of built structures. The present work not only falls within the scope of import substitution but also aims to characterize and improve the properties of local sand (Sanaga) and compare them with those of imported standardized sand widely used in laboratories. Sanaga sand was treated with HCl and then characterized in the laboratory. The constituent minerals of Sanaga sand are quartz, albite, biotite, and kaolinite. The silica content (SiO₂) of this untreated sand is 93.48 wt.%. After treatment, it rose 97.5 wt.% for 0.5 M and 97.3 wt.% for 1 M HCl concentration. The sand is clean (ES, 97.67%–98.87%), with fineness moduli of 2.45, 2.48, and 2.63 for untreated sand and sand treated with HCl concentrations of 0.5 and 1 M respectively. The mechanical strengths (39.59–42.4 MPa) obtained on mortars made with untreated Sanaga sand are unsatisfactory compared with those obtained on mortars made with standardized sand and with the expected strengths. The HCl treatment used in this study significantly improved these strengths (41.12–52.36 MPa), resulting in strength deficiencies of less than 10% after 28 curing days compared with expected values. Thus, the treatment of Sanaga sand with a 0.5 M HCl concentration offers better results for use as standardized sand.

The technological development and growth of the telecommunications industry have had a great positive impact on the education, health, and economic sectors, among others. However, they have also increased rivalry between companies in the market to keep and acquire new customers. A lower level of market concentration is related to a higher level of competitiveness among companies in the sector that drives a country’s socioeconomic development. To guarantee and improve the level of competition, it is necessary to monitor the concentration level in the telecommunications market to plan and develop appropriate strategies by governments. With this in mind, the present work aims to analyze the concentration prediction in the telecommunications market through recurrent neural networks and the Herfindahl-Hirschman index. The results show a slight gradual increase in competition in terms of traffic and access, while a more stable concentration level is observed in revenues.