Search

The present study shows the development of computational algorithms to represent aircraft instruments such as the attitude indicator or the turn-and-slip indicator; moreover, the algorithms represent a magnetic compass and other instruments that function according to other physical theories. These instruments work by using the gyroscope and magnetic principles and help the pilot in navigation. These are considered to be the basic instruments required to provide location-related and positional information about the actual aircraft attitude. The algorithms developed in this study are capable of working in concordance with other instruments and the physical conditions established. The programming language used was C++ and the algorithms were compiled in independent files and subroutines for computational efficiency, eliminating unnecessary code. The display options were successfully tested. Additionally, an analysis that evaluated the error and approached flight simulation as a function of step time (Δt) is also described.

The management of large medical files poses a critical challenge in the health sector, with conventional systems facing deficiencies in security, scalability, and efficiency. Blockchain ensures the immutability and traceability of medical records, while the cloud allows scalable and efficient storage. Together, they can transform the data management of electronic health record applications. The method used was the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to choose and select the relevant studies that contribute to this research, with special emphasis set on maintaining the integrity and security of the blockchain while tackling the potential and efficiency of cloud infrastructures. The study’s focus is to provide a comprehensive and insightful examination of the modern landscape concerning the integration of blockchain and cloud advances, highlighting the current challenges and building a solid foundation for future development. Furthermore, it is very important to increase the integration of blockchain security with the dynamic potential of cloud computing while guaranteeing information integrity and security remain uncompromised. In conclusion, this paper serves as an important resource for analysts, specialists, and partners looking to delve into and develop the integration of blockchain and cloud innovations.

This manuscript describes the computational process to calculate an airplane path and display it in a 2D and 3D coordinate system on a computer screen. The airplane movement is calculated as a function of its dynamic’s conditions according to physical and logical theory. Here, the flight is divided into maneuvers and the aircraft conditions are defined as boundary conditions. Then the aircraft position is calculated using nested loops, which execute the calculation procedure at every step time (Δt). The calculation of the aircraft displacement is obtained as a function of the aircraft speed and heading angles. The simulator was created using the C++ programming language, and each part of the algorithm was compiled independently to reduce the source code, allow easy modification, and improve the programming efficiency. Aerial navigation involves very complex phenomena to be considered for an appropriate representation; moreover, in this manuscript, the influence of the mathematical approach to properly represent the aircraft flight is described in detail. The flight simulator was successfully tested by simulating some basic theoretical flights with different maneuvers, which include stationary position, running along the way, take off, and some movements in the airspace. The maximum aircraft speed tested was 120 km/h, the maximum maneuver time was 12 min, and the space for simulation was assumed to be without obstacles. Here, the geometrical description of path and speed is analyzed according to the symmetric and asymmetric results. Finally, an analysis was conducted to evaluate the approach of the numerical methods used; after that, it was possible to confirm that precision increased as the step time was reduced. According to this analysis, no more than 500 steps are required for a good approach in the calculation of the aircraft displacement.

The use of the orthogonal array L4 allows a determination of the effect between the welding parameters peak current (Ip), background current (Ib) and frequency (f) on the porosities in a dissimilar welded lap joint of CP800 and XPF1000 steel weldment by the gas metal arc welding process with the transfer pulsed mode. According to the results, modifications in the welding parameters affect the heat input during welding. A heat input higher than 0.30 KJ/mm generates up to 0.32% porosity in the weld metal, while a heat input lower than 0.25 KJ/mm generates up to 28% porosity in the weld metal. The variation in heat input generated by the process allowed the observation of the final microstructure of the welded joints and the effect of mechanical properties such as hardness because the results show values of hardness from 300 Hv to 400 Hv in the heat affected zone (HAZ).

Mezcal is an alcoholic beverage obtained by distilling musts and juices fermented by spontaneous or cultivated microorganisms, which are extracted from ripe stems of cooked Agaves and harvested in Mexico. Both raw material and production practices differ markedly between producing regions, locations, and even factories, resulting in a very distinctive set of products. The state of Oaxaca is the top producer worldwide of mezcal, and 35,000 families are involved in the production of this aromatic alcoholic beverage. Fermentation is the most important stage of mezcal production and is performed by different yeast and bacteria. In this study, the yeast strains were isolated from fermentation containers of four mezcal factories (palenques) in Oaxaca. Taxonomic determination was verified by ITS, and an analysis of the biotechnological process through personal interviews and principal component analysis was performed. Eighteen different isolates of eight different genera (Candida, Clavispora, Meyerozyma, Metarhizium, Pichia, Saccharomyces, Torulaspora, and Yarrowia) were identified. According to the biotechnological process analysis and principal component analysis, the artisanal palenques (palenques 1, 3, and 4) are more like each other than and differ radically from palenque 2, which is where the artisanal process has changed towards technical production.

This work focuses on an analysis of hydrodynamics to improve the efficiency in a batch reactor for lead recycling. The study is based on computational fluid dynamics (CFD) methods, which are used to solve Navier–Stokes and Fick’s equations (continuity and momentum equations for understanding hydrodynamics and concentration for understanding distribution). The reactor analyzed is a tank with a dual geometry with a cylindrical body and a hemisphere for the bottom. This reactor is symmetrical vertically, and a shaft with four blades is used as an impeller for providing motion to the resident fluid. The initial resident fluid is static, and a tracer is defined in a volume inside to measure mixing efficiency, as is conducted in laboratory and industrial practices. Then, an evaluation of the mixing is performed by studying the tracer concentration curves at different evolution times. In order to understand the fluid flow hydrodynamics behavior with the purpose of identifying zones with rich and poor tracer concentrations, the tracer’s concentration was measured at monitoring points placed all around in a defined control plane of the tank. Moreover, this study is repeated independently to evaluate different injection points to determine the best one. Finally, it is proved that the selection of an appropriate injection point can reduce working times for mixing, which is an economically attractive motivation to provide proposals for improving industrial practices.

Background: Physical and mathematical theories have made it possible to generate methods for the characterization and diagnosis of physiological variables such as cardiac dynamics. Therefore, it would be useful to implement them to evaluate the dynamic changes in human physiology during the development of COVID-19, which causes disease, severe respiratory and death. Objective: to establish a method for detecting possible alterations associated with COVID-19 through simulations of adult cardiac dynamics and body temperature using dynamic systems theory, probability, entropy and set theory. Methodology: simulations of cardiac dynamics were generated in subjects with 10 temperature ranges between 32 °C and 42 °C via numerical attractors after their evaluation using entropy proportions. Results: differences were observed in the proportions of entropy that differentiate normal cardiac dynamics and acute myocardial infarction towards progression to fever. Conclusion: the physical mathematical analysis of cardiac behavior in relation to body temperature in people with COVID-19 allowed the establishment of a possible surveillance method for detecting minor alterations.

In 2021, 273 Rocky Mountain spotted fever cases were reported nationwide in Mexico. In Chihuahua City, fourteen samples were obtained from children suspected of rickettsial infection. The analysis of samples (January to December 2021) showed prevalence rates of 28.5%, 43%, and 28.5% for Rickettsia rickettsii, Ehrlichia canis, and both pathogens in coinfection, respectively. The analysis of clinical haematological and biochemistry analytes showed alterations; 100% of the children had elevated liver enzymes and coagulation times, 64% showed leukocytosis due to neutrophilia, 55% had thrombocytopenia, lymphopenia, and hypoalbuminemia, and 45% showed normocytic normochromic anaemia. Statistically significant differences were observed in the expression of the chemokines IL-8, RANTES, CXCL9/MIG, and CXCL10/IP-10 across the coinfected and control groups, and the difference in IP-10 expression was significant for patients infected by R. rickettsii compared to the control group. Additionally, significant differences were observed for expression levels of IL-1β, IL-6, IL-17, IFNγ, and TNFα among the R. rickettsii-positive group compared to the control group. On the other hand, the coinfected group exhibited modified levels of IL-6, IL-8, and IL-10 compared with the control group. Finally, significant differences were observed for CD8+ T lymphocyte subpopulations between individuals positive for R. rickettsii and those positive for E. canis.

Diffuse reflectance spectroscopy (DRS) is emerging as a rapid and cost-effective alternative to routine laboratory analysis for many soil properties. However, it has primarily been applied in project-specific contexts. Here, we provide an assessment of DRS spectroscopy at the scale of the continental United States by utilizing the large (n > 50,000) USDA National Soil Survey Center mid-infrared spectral library and associated soil characterization database. We tested and optimized several advanced statistical approaches for providing routine predictions of numerous soil properties relevant to studying carbon cycling. On independent validation sets, the machine learning algorithms Cubist and memory-based learner (MBL) both outperformed random forest (RF) and partial least squares regressions (PLSR) and produced excellent overall models with a mean R2 of 0.92 (mean ratio of performance to deviation = 6.5) across all 10 soil properties. We found that the use of root-mean-square error (RMSE) was misleading for understanding the actual uncertainty about any particular prediction; therefore, we developed routines to assess the prediction uncertainty for all models except Cubist. The MBL models produced much more precise predictions compared with global PLSR and RF. Finally, we present several techniques that can be used to flag predictions of new samples that may not be reliable because their spectra fall outside of the calibration set.

In this paper we undertake the theoretical analysis of a two-stage semiconductor thermoelectric module (TEM) which contains an arbitrary and different number of thermocouples, n1 and n2, in each stage (pyramid-styled TEM). The analysis is based on a dimensionless entropy balance set of equations. We study the effects of n1 and n2, the flowing electric currents through each stage, the applied temperatures and the thermoelectric properties of the semiconductor materials on the exergetic efficiency. Our main result implies that the electric currents flowing in each stage must necessarily be different with a ratio about 4.3 if the best thermal performance and the highest temperature difference possible between the cold and hot side of the device are pursued. This fact had not been pointed out before for pyramid-styled two stage TEM. The ratio n1/n2 should be about 8.

There is a consensus about the necessity to achieve a quick soil spatial information with few human resources. Remote/proximal sensing and pedotransference are methods that can be integrated into this approach. On the other hand, there is still a lack of strategies indicating on how to put this in practice, especially in the tropics. Thus, the objective of this work was to suggest a strategy for the spatial prediction of soil classes by using soil spectroscopy from ground laboratory spectra to space images platform, as associated with terrain attributes and spectral libraries. The study area is located in São Paulo State, Brazil, which was covered by a regular grid (one per ha), with 473 boreholes collected at top and undersurface. All soil samples were analyzed in laboratory (granulometry and chemical), and scanned with a VIS-NIR-SWIR (400–2500 nm) spectroradiometer. We developed two traditional pedological maps with different detail levels for comparison: TFS-1 regarding orders and subgroups; and TFS-2 with additional information such as color, iron and fertility. Afterwards, we performed a digital soil map, generated by models, which used the following information: (i) predicted soil attributes from undersurface layer (diagnostic horizon), obtained by using a local spectral library; (ii) spectral reflectance of a bare soil surface obtained by Landsat image; and (iii) derivative of terrain attributes. Thus, the digital map was generated by a combination of three variables: remote sensing (Landsat data), proximal sensing (laboratory spectroscopy) and relief. Landsat image with bare soil was used as a first observation of surface. This strategy assisted on the location of topossequences to achieve soil variation in the area. Afterwards, spectral undersurface information from these locations was used to modelize soil attributes quantification (156 samples). The model was used to quantify samples in the entire area by spectra (other 317 samples). Since the surface was bare soil, it was sampled by image spectroscopy. Indeed, topsoil spectral laboratory information presented great similarity with satellite spectra. We observed angle variation on spectra from clayey to sandy soils as differentiated by intensity. Soil lines between bands 3/4 and 5/7 were helpful on the link between laboratory and satellite data. The spectral models of soil attributes (i.e., clay, sand, and iron) presented a high predictive performance (R2 0.71 to 0.90) with low error. The spatial prediction of these attributes also presented a high performance (validations with R2 > 0.78). The models increased spatial resolution of soil weathering information using a known spectral library. Elevation (altitude) improved mapping due to correlation with soil attributes (i.e., clay, iron and chemistry). We observed a close relationship between soil weathering index map and laboratory spectra + image spectra + relief parameters. The color composite of the 5R, 4G and 3B had great performance on the detection of soils along topossequences, since colors went from dark blue to light purple, and were related with soil texture and mineralogy of the region. The comparison between the traditional and digital soil maps showed a global accuracy of 69% for the TFS-1 map and 62% in the TFS-2, with kappa indices of 0.52 and 0.45, respectively. We randomly validated both digital and traditional maps with individual plots at field. We achieve a 75% and 80% agreement for digital and traditional maps, respectively, which allows us to conclude that traditional map is not necessarily the truth and digital is very close. The key of the strategy was to use bare soil image as a first step on the indication of soil variation in the area, indicating in-situ location for sample collection in all depths. The current strategy is innovative since we linked sensors from ground to space in addition with relief parameters and spectral libraries. The strategy indicates a more accurate map with less soil samples and lower cost.