Introduction: Periodontal disease affects more than half of the population in Colombia and is estimated to be one of the leading causes of oral morbidity. Diagnostic aids that allow the evaluation of its extension and severity are of importance since this will provide reliable tools to quantify the severity of the problem. Objective: To determine the inter-examiner agreement for the detection of radiographic findings in patients with localized chronic periodontitis using conventional periapical radiography. Methods: Study of diagnostic tests including patients with localized chronic periodontitis, the tooth with the worst clinical insertion level and a single conventional radiograph per dental organ using parallelism technique. The radiographic evaluations were performed by two independent and blinded evaluators for the findings: lamina dura, bone defects and type of defect. The agreement obtained was estimated through Cohen’s Kappa. Results: A total of 125 radiographs were taken. The mean age was 38.8 ± 9.9, and 61.6% were women. Concordance for lamina dura was 0.08 (95% CI: -0.04–0.21), bone defects 1.00 (95% CI: 1.00–1.00); type of defect present 0.31 (95% CI: 0.29–0.38). Conclusions: Concordance was evaluated as null, almost perfect and acceptable for the findings lamina dura, presence of bone defects and type of defect respectively. For some findings and given the importance of the diagnostic and therapeutic processes, more accurate evaluations are needed which would result in a higher degree of agreement.

The integration of medical images is the process of registering and fusing them to obtain a greater amount of diagnostic information. In this work an analysis is performed for the integration of images obtained through computed axial tomography and magnetic resonance imaging, for which a tool was developed in the Matlab program, where the registration is implemented through equivalent features; in addition, the pairs of images are compared by several fusion rules, with a view to identify the best algorithm in which the resulting fused image contains the most information from the original representations.

Magnetite magnetic nanoparticles (MNP) exhibit superparamagnetic behavior, which gives them important properties such as low coercive field, easy superficial modification and acceptable magnetization levels. This makes them useful in separation techniques. However, few studies have experimented with the interactions of MNP with magnetic fields. Therefore, the aim of this research was to study the influence of an oscillating magnetic field (OMF) on polymeric monolithic columns with vinylated magnetic nanoparticles (VMNP) for capillary liquid chromatography (cLC). For this purpose, MNP were synthesized by coprecipitation of iron salts. The preparation of polymeric monolithic columns was performed by copolymerization and aggregation of VMNP. Taking advantage of the magnetic properties of MNP, the influence of parameters such as resonance frequency, intensity and exposure time of a OMF applied to the synthesized columns was studied. As a result, a better separation of a sample according to the measured parameters was obtained, so that a column resolution (R_s) of 1.35 was achieved. The morphological properties of the columns were evaluated by scanning electron microscopy (SEM). The results of the chromatographic properties revealed that the best separation of the alkylbenzenes sample occurs under conditions of 5.5 kHz and 10 min of exposure in the OMF. This study constitutes a first application in chromatographic separation techniques for future research in nanotechnology.

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.

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.

One of the core problems in soil erosion research is the estimation of soil erosion. It is a feasible method and technical approach to estimate soil erosion in Loess Plateau region by using USLE model, GIS and RS technology and using DEM data, meteorological data and land-use type data. With the support of GIS and RS technology, the USLE factors and soil erosion in Loess Plateau region were estimated, and the soil erosion intensity was classified according to the Chinese soil erosion intensity classification standard. The results can provide reference for the development of soil erosion control measures in the Loess Plateau.