A prelude to the fractional calculus applied to tumor dynamic

In order to refine the solution given by the classical logistic equation and extend its range of applications in the study of tumor dynamics, we propose and solve a generalization of this equation, using the so-called Fractional Calculus, i.e., we replace the ordinary derivative of order 1, in one version of the usual equation, by a non-integer derivative of order 0 < α < 1, and recover the classical solution as a particular case. Finally, we analyze the applicability of this model to describe the growth of cancer tumors.

Nonlinear state estimation and control applied to a manipulator robotic including drive motor

A robotic control design considering all the inherent nonlinearities of the robot engine configuration is developed. The interactions between the robot and joint motor drive mechanism are considered. The proposed control combines two strategies, one feedforward control in order to maintain the system in the desired coordinate, and feedback control system to take the system into a desired coordinate. The feedback control is obtained using State Dependent Riccati Equation (SDRE). For link positioning two cases are considered. Case 1: For control positioning, it is only used motor voltage; Case 2: For control positioning, it is used both motor voltage and torque between the links. Simulation results, including parametric uncertainties in control shows the feasibility of the proposed control for the considered system.

Statistical detection of spurious variations in daily raingauge data caused by changes in observation practices, as applied to records from various parts of the world

In the instrumental records of daily precipitation, we often encounter one or more periods in which values below some threshold were not registered. Such periods, besides lacking small values, also have a large number of dry days. Their cumulative distribution function is shifted to the right in relation to that for other portions of the record having more reliable observations. Such problems are examined in this work, based mostly on the two-sample Kolmogorov–Smirnov (KS) test, where the portion of the series with more number of dry days is compared with the portion with less number of dry days. Another relatively common problem in daily rainfall data is the prevalence of integers either throughout the period of record or in some part of it, likely resulting from truncation during data compilation prior to archiving or by coarse rounding of daily readings by observers. This problem is identified by simple calculation of the proportion of integers in the series, taking the expected proportion as 10%. The above two procedures were applied to the daily rainfall data sets from the European Climate Assessment (ECA), Southeast Asian Climate Assessment (SACA), and Brazilian Water Resources Agency (BRA). Taking the statistic D of the KS test >0.15 and the corresponding p-value <0.001 as the condition to classify a given series as suspicious, the proportions of the ECA, SACA, and BRA series falling into this category are, respectively, 34.5%, 54.3%, and 62.5%. With relation to coarse rounding problem, the proportions of series exceeding twice the 10% reference level are 3%, 60%, and 43% for the ECA, SACA, and BRA data sets, respectively. A simple way to visualize the two problems addressed here is by plotting the time series of daily rainfall for a limited range, for instance, 0–10 mm day−1.

Ensino de ecoico, tato e mando: uma revisão bibliográfica dos artigos do Journal of Applied Behavior Analysis (JABA)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Artificial neural networks applied to bandsawing process control

In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.

Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics

Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq)

Genetic erosion risk by environmental and antropic factor applied on strategies for Lychnophora ericoides conservation

This study evaluated the genetic erosion risk factors and the strategic points for the conservation of Lychnophora ericoides population in “Paraíso Perdido” farm, Serra da Canastra (20° 37’ 54” S; 46° 19’ 37” W; 833 m height) in São João Batista do Glória City, Minas Gerais State, Brazil. The number of young and adult plants, the soil and the phenology were evaluated in two sample areas of 125 m2. Information about the species utilization was obtained with local informants. Data on the region were obtained through literature review, in loco evaluation, GPS and geo-referenced map. In addition, local use of the plant for mixtures of drug was evaluated. According to the results obtained, the soil of the population is lithic with a weathered portion of frank-sandy texture, very acidic and dystrophic. The population density is 0.16 individuals/m2, 0.078 young/adult plant. The predominant phenophase was fruiting (100% plants) followed by flowering (21.62% plants). The local community uses the leaves of the plant in the form of hydroalcoholic extracts, as anti-inflammatory. Based on the evaluated parameters, the population is at 73% risk of genetic erosion. The detected key points were the development of activities including the participation of the local community for habitat protection as well as germplasm collection, seedlings production and reintroduction, together with environmental education, supervision, and reduction in the propensity for fire.

Review of Applied Spatial Data Analysis with R by R. S. Bivand, E. J. Pebesma, and V. Gomez-Rubio

Most authors struggle to pick a title that adequately conveys all of the material covered in a book. When I first saw Applied Spatial Data Analysis with R, I expected a review of spatial statistical models and their applications in packages (libraries) from the CRAN site of R. The authors’ title is not misleading, but I was very pleasantly surprised by how deep the word “applied” is here. The first half of the book essentially covers how R handles spatial data. To some statisticians this may be boring. Do you want, or need, to know the difference between S3 and S4 classes, how spatial objects in R are organized, and how various methods work on the spatial objects? A few years ago I would have said “no,” especially to the “want” part. Just let me slap my EXCEL spreadsheet into R and run some spatial functions on it. Unfortunately, the world is not so simple, and ultimately we want to minimize effort to get all of our spatial analyses accomplished. The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot.

Thermal Imagery Applied to Reducing Bird Hazards to Aircraft at Airports

Airports worldwide are at a disadvantage when it comes to being able to spot birds and warn aircrews about the location of flocks either on the ground or close to the airfield. Birds simply cannot be easily seen during the day and are nearly invisible targets for planes at night or during low visibility. Thermal imaging (infrared) devices can be used to allow ground and tower personnel to pinpoint bird locations day or night, thus giving the airport operators the ability to launch countermeasures or simply warn the aircrews. This technology is available now, though it has been predominately isolated to medical and military system modifications. The cost of these devices has dropped significantly in recent years as technology, capability, and availability have continued to increase. Davison Army Airfield (DAAF), which is located about 20 miles south of Ronald Reagan National Airport in Washington, DC, is the transient home to many bird species including an abundance of ducks, seagulls, pigeons, and migrating Canadian geese. Over the past few years, DAAF implemented a variety of measures in an attempt to control the bird hazards on the airfield. Unfortunately, when it came to controlling these birds on or near our runways and aircraft movement areas we were more reactive than proactive. We would do airfield checks several times an hour to detect and deter any birds in these areas. The deterrents used included vehicle/human presence, pyrotechnics, and the periodic use of a trained border collie. At the time, we felt like we were doing all we could to reduce the threat to aircraft and human life. It was not until a near fatal accident in October 1998, when we truly realized how dangerous our operating environment really was to aircraft at or near the airfield. It was at this time, we had a C-12 (twin-engine passenger plane) land on our primary runway at night. The tower cleared the aircraft to land, and upon touchdown to the runway the aircraft collided with a flock of geese. Neither the tower nor the crew of the aircraft saw the geese because they were obscured in the darkness. The end result was 12 dead geese and $374,000 damage to the C-12. Fortunately, there were no human fatalities, but it was painfully clear we needed to improve our method of clearing the runway at night and during low visibility conditions. It was through this realization that we ventured to the U.S. Army Communications and Electronics Command for ideas on ways to deal with our threat. It was through a sub-organization within this command, Night Vision Labs, that we realized the possibilities of modifying thermal imagery and infrared technology to detecting wildlife on airports.

When "Reason" Is In the Eye of the Beholder: A Reexamination of the "Reasonable Man" Standard as Applied to Organizational Management

“Specifically, issues of race, gender, disability, status, etc. provide a new context in which to judge the reasonableness of an individual’s actions.”

Influence of Particle Size, Applied Compression, and Substratum Material on Particle-Surface Adhesion Force Using the Centrifuge Technique

The centrifuge technique was used to investigate the influence of particle size, applied compression, and substrate material (stainless steel, glass, Teflon, and poly(vinyl chloride)) on particle-surface adhesion force. For this purpose, phosphatic rock (rho(p) = 3090 kg/m(3)) and manioc starch particles (rho(p) = 1480 kg/m(3)) were used as test particles. A microcentrifuge that reached a maximum rotation speed of 14 000 rpm and which contained specially designed centrifuge tubes was used in the adhesion force measurements. The curves showed that the adhesion force profile followed a normal log distribution. The adhesion force increased linearly with particle size and with the increase of each increment of compression force. The manioc starch particles presented greater adhesion forces than the phosphatic rock particles for all particle sizes studied. The glass substrate showed a higher adherence than the other materials, probably due to its smoother topographic surface roughness in relation to the other substrata.

Risk Assessment of the Introduction of H5N1 Highly Pathogenic Avian Influenza as a Tool to be Applied in Prevention Strategy Plan

Risks of the introduction of highly pathogenic avian influenza (HPAI) H5N1 through migratory birds to the main wintering site for wild birds in southern Brazil and its consequences were assessed. Likelihoods were estimated by a qualitative scale ranging from negligible to high. Northern migrants that breed in Alaska and regularly migrate to South America (primary Charadriiformes) can have contact with birds from affected areas in Asia. The likelihood of the introduction of HPAI H5N1 through migratory birds was found to be very low as it is a probability conditioned to successful transmission in breeding areas and the probabilities of an infected bird migrating and shedding the virus as far as southern Brazil. The probability of wild species becoming exposed to H5N1-infected birds is high as they nest with northern migrants from Alaska, whereas for backyard poultry it is moderate to high depending on proximity to wetlands and the presence of species that could increase the likelihood of contact with wild birds such as domestic duck. The magnitude of the biological and economic consequences of successful transmission to poultry or wild birds would be low to severe depending on the probability of the occurrence of outbreak scenarios described. As a result, the risk estimate is greater than negligible, and HPAI H5N1 prevention strategy in the region should always be carefully considered by the veterinary services in Brazil.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

Class-specific metrics for multidimensional data projection applied to CBIR

Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.