Currently there is a great acceptance in medicine and dentistry that clinical practice should be “evidence-based” as much as possible. That is why multiple works have been published aimed at decreasing radiation doses in the different types of imaging modalities used in dentistry, since the greater effect of radiation, especially in children, forces us to take necessary measures to rationalize its use, especially with Cone Beam computed tomography (CBCT), the method that provides the highest doses in dentistry. This review was written using such an approach with the purpose of rationalizing the radiation dose in our patients. In order to formulate recommendations that contribute to the optimization of the use of ionizing radiation in dentistry, the SEDENTEXCT project team compiled and analyzed relevant publications in the literature, guidelines that have demonstrated their efficiency in the past, thus helping to see with different perspectives the dose received by patients, and with this, it is recommended taking into account this document so as to prescribe more adequately the complementary examinations that we use on a daily basis.

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.

Spectrum map is the foundation of spectrum resource management, security governance and spectrum warfare. Aiming at the problem that the traditional spectrum mapping is limited to two-dimensional space, a three-dimensional spectrum data acquisition and mapping system architecture for the integration of space, sky and earth is presented, and a spectrum map reconstruction scheme driven by propagation model is proposed, which can achieve high-precision three-dimensional spectrum map rendering under the condition of sparse sampling. The spectrum map reconstructed by this method in the case of single radiation source and multiple radiation sources is in good agreement with the theoretical results based on ray tracing method. In addition, the measured results of typical scenes further verify the feasibility of this method.

Context: Noise in the work environment, in all types of productive activities, represents a hazard and has not really been valued in its real dimension. Little has been seen that stakeholders have determined the urgency of managing noise control programs. Therefore, losses resulting from medical treatment and absenteeism, represented in health care and social services, result in hidden work-related costs that directly affect the gross domestic product in any country.

Method: This article compiles different case studies from around the world. The studies were divided for review into general studies on the effects of workforce noise and then particularized according to the effects of industrial noise on workers’ health. At a control level, the assessment and measurement of noise is defined through the use of tools such as noise maps and their respective derivations, in addition to spatial databases.

Results: According to the collection of information and its analysis, we observe that in the medium term, the economies will be diminished in an important percentage due to the consequences generated by the exposure to noise. Specific information can be found in the development of the article.

Conclusions: The data provided by the case studies point to the need for Colombia, a country that is no stranger to this phenomenon, and which additionally has the great disadvantage of not having significant studies in the field of noise analysis, should strengthen studies based on spatial data as a mechanism for measurement and control.

Financing: Fundación universitaria Los Libertadores.

The wave effect and the shyness phenomenon in Alnus acuminata (Kunth) are crown parameters rarely studied, but important in the quality of the wood of standing trees, therefore, a morphometric modeling of the crowns of Alnus acuminata in homogeneous forests in the Sierra Norte de Puebla was carried out. In 20 rectangular sites of 1,000 m², the following were evaluated: total height (TA), normal diameter (ND), crown diameter (CD) and crown cover (CC). The Kruskal Wallis test was applied to data that did not meet the assumption of normality; for those that did, analysis of variance (ANOVA) was used, with Tukey mean comparison tests (α ≤ 0.05). The forest value index was 14.99, so its two-dimensional structure is normal based on DN, AT and CC. Its average slenderness index was 93.52, which makes the tree not very stable to mechanical damage. The life-space index was 38.92, which is high indicating that trees with low intraspecific competition developed better. At the canopy level, a pattern following an upward, oscillatory and constant wave effect was observed in groups of 10 trees. The shyness phenomenon showed an average crack opening of 27.39 cm between canopies, so this phenomenon is well defined for the species. It is concluded that in the crowns of Alnus acuminata, the wave effect is observed as a consequence of inequality in the acquisition of resources, and one way to minimize this inequality is through the phenomenon of botanical shyness.

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.