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Mining slopes, electrical power generation dams and several big construction enterprises demands continuous inspections. The size and diversity of these structures demands high precision and portable approach. In such environments, 3D reconstruction methodologies are able to capture and analyze the real world in detail. However, the accuracy and precision can affect the ability to process and interpret the acquired data. For instance, laser scanning is a very accurate method and can deliver a higher quality result. Meanwhile, 3D photogrammetry using a single camera and Structure From Motion (SFM) have their performance correlated with the image quality. In a typical application, 3D data from reconstruction is pre-processed by a specialist. Then, it is stored for comparison and analyzed over time. The posterior analysis has several challenges associated with the reconstruction process characteristics. Several techniques have been developed to allow the comparison of point cloud captured at different epochs. Therefore, this research work presents a new methodology to perform alignment and comparison of point clouds, namely 3D-CP2, an acronym for 3D Correspondence and Point Projection. This method intends to analyze the point cloud motion to be applied in terrestrial 3D SFM reconstructions. Besides, the technique can also be used in many other related applications. The methodology developed in this work is applied in controlled experiments and real use cases to show its potential for point cloud displacements analysis. The results showed that the proposed method is efficient and can produce results more accurately than the referenced literature.

The interest in 3,4-dihydropyrimidine-2(1H)-(thio)ones is increasing every day, mainly due to their paramount biological relevance. The Biginelli reaction is the classical approach to reaching these scaffolds, although the product diversity suffers from some limitations. In order to overcome these restrictions, two main approaches have been devised. The first one involves the modification of the conventional components of the Biginelli reaction and the second one refers to the postmodification of the Biginelli products. Both strategies have been extensively revised in this manuscript. Regarding the first one, initially, the modification of one of the components was covered. Although examples of modifications of the three of them were described, by far the modification of the keto ester counterpart was the most popular approach, and a wide variety of different enolizable carbonylic compounds were used; moreover, changes in two or the three components were also described, broadening the substitution of the final dihydropyrimidines. Together with these modifications, the use of Biginelli adducts as a starting point for further modification was also a very useful strategy to decorate the final heterocyclic structure.

Unmanned aerial vehicle (UAV) applications have evolved to a wide range of fields in the last decade. One of the main challenges in autonomous tasks is the UAV stability during maneuvers. Thus, attitude and position control play a crucial role in stabilizing the vehicle in the desired orientation and path. Many control techniques have been developed for this. However, proportional integral derivative (PID) controllers are often used due their structure and efficiency. Despite PID’s good performance, different requirements may be present at different mission stages. The main contribution of this research work is the development of a novel strategy based on a fuzzy-gain scheduling mechanism to adjust the PID controller to stabilize both position and altitude. This control strategy must be effective, simple, and robust to uncertainties and external disturbances. The Robot Operating System (ROS) integrates the proposed system and the flight control unit. The obtained results showed that the proposed approach was successfully applied to the trajectory tracking and revealed a good performance compared to conventional PID and in the presence of noises. In the tests, the position controller was only affected when the altitude error was higher, with an error of 2% lower.

Path planning is one of the most important issues in the robotics field, being applied in many domains ranging from aerospace technology and military tasks to manufacturing and agriculture. Path planning is a branch of autonomous navigation. In autonomous navigation, dynamic decisions about the path have to be taken while the robot moves towards its goal. Among the navigation area, an important class of problems is Coverage Path Planning (CPP). The CPP technique is associated with determining a collision-free path that passes through all viewpoints in a specific area. This paper presents a method to perform CPP in 3D environment for Unmanned Aerial Vehicles (UAVs) applications, namely 3D dynamic for CPP applications (3DD-CPP). The proposed method can be deployed in an unknown environment through a combination of linear optimization and heuristics. A model to estimate cost matrices accounting for UAV power usage is proposed and evaluated for a few different flight speeds. As linear optimization methods can be computationally demanding to be used on-board a UAV, this work also proposes a distributed execution of the algorithm through fog-edge computing. Results showed that 3DD-CPP had a good performance in both local execution and fog-edge for different simulated scenarios. The proposed heuristic is capable of re-optimization, enabling execution in environments with local knowledge of the environments.

Different practical applications have emerged in the last few years, requiring periodic and detailed inspections to verify possible structural changes. Inspections using Unmanned Aerial Vehicles (UAVs) should minimize flight time due to battery time restrictions and identify the terrain’s topographic features. In this sense, Coverage Path Planning (CPP) aims at finding the best path to coverage of a determined area respecting the operation’s restrictions. Photometric information from the terrain is used to create routes or even refine paths already created. Therefore, this research’s main contribution is developing a methodology that uses a metaheuristic algorithm based on point cloud data to inspect slope and dams structures. The technique was applied in a simulated and real scenario to verify its effectiveness. The results showed an increasing 3D reconstructions’ quality observing optimizing photometric and mission time criteria.

When performing structural inspection, the generation of three-dimensional (3D) point clouds is a common resource. Those are usually generated from photogrammetry or through laser scan techniques. However, a significant drawback for complete inspection is the presence of covering vegetation, hiding possible structural problems, and making difficult the acquisition of proper object surfaces in order to provide a reliable diagnostic. Therefore, this research’s main contribution is developing an effective vegetation removal methodology through the use of a deep learning structure that is capable of identifying and extracting covering vegetation in 3D point clouds. The proposed approach uses pre and post-processing filtering stages that take advantage of colored point clouds, if they are available, or operate independently. The results showed high classification accuracy and good effectiveness when compared with similar methods in the literature. After this step, if color is available, then a color filter is applied, enhancing the results obtained. Besides, the results are analyzed in light of real Structure From Motion (SFM) reconstruction data, which further validates the proposed method. This research also presented a colored point cloud library of bushes built for the work used by other studies in the field.

The mixed zinc-ferrite spinel magnetic nanoparticles (MNPs) with the general formula ZnxFe3−xO4 are among the most extensively studied families of Fe oxides due to their interesting and diverse chemical, electronic, and magnetic properties. These systems offer the possibility of surface functionalization and possess high biocompatibility, making them highly attractive for applications in biomedicine, such as magnetic fluid hyperthermia (MFH). The efficiency of the MFH process relies on the magnetic, structural and morphological properties of the MNPs. The substitution with the Zn ion and the cationic distribution, as well as the synthesis process employed, have a direct impact on the final properties of these oxides. Therefore, it is essential to have tools that enable a comprehensive characterization of the system to assess its performance in MFH. In this study, we have synthesized four ZnxFe3−xO4 MNP systems using three different methods: two by thermal decomposition at high temperatures, one by co-precipitation, and another by co-precipitation followed by ball milling. We analyze the effect of these various synthesis processes on the magnetic and crystallographic properties, aiming to correlate them with the response of each system in MFH. Neutron diffraction data are employed to determine the cation site occupation and to investigate the correlation with the synthesis method. MFH measurements were conducted in media of diverse viscosities, revealing different values of specific loss power, thus demonstrating a clear dependence on the synthesis process and Zn content. [ABSTRACT FROM AUTHOR]

We report a novel, metal‐free procedure for the direct aminophosphonation of imidazo[1,2‐a]pyridines in green solvents under open air conditions. This method is characterized by its mild and sustainable conditions, ease of operation, scalability, and excellent functional group compatibility. The synthesized compounds exhibit promising photophysical properties, including significant Stokes shifts and quantum yields, making them potential candidates for innovative fluorescent probes. [ABSTRACT FROM AUTHOR]

A method for the synthesis of flufenamic acid, a nonstereoidal anti-inflammatory drug (NSAID) of the anthranilate family (fenams), is described as an experiment for the upper-division undergraduate organic chemistry laboratory. The key step is the formation of the diarylamine moiety of flufenamic acid by a novel reaction consisting of the coupling of nitrosobenzenes with boronic acids under transition-metal-free conditions. On the one hand, students can compare the performance of two different methods for the preparation of nitrosobenzenes (oxidation of amines and "ipso"-S[subscript E]Ar reaction on potassium organotrifluoroborates). On the other hand, they compare the yields of two complementary examples for the coupling of nitrosobenzenes with boronic acids. The reactions are followed by thin layer chromatography, and the products are purified by percolation or by column chromatography. Students are also tasked with the confirmation of the structure of the products based on melting point, infrared, [superscript 1]H NMR, [superscript 13]C NMR, and [superscript 19]F NMR spectroscopy, and MS spectrometry.

A report from the International Union of Crystallography Commission on Magnetic Structures outlining the recommendations for communicating commensurate magnetic structures. [ABSTRACT FROM AUTHOR]