Trophallaxis in Dehydrated Leaf Cutting Colonies of Atta sexdens rubropilosa (Hymenoptera: Formicidae)

Trophallaxis, the transfer of liquid among individuals by oral regurgitation or anal deposition, occurs in many insect groups including ants. The first indication that trophallaxis could occur in leaf cutting ants (Atta sexdens rubropilosa) was made by Autuori in 1942. He reported water collection by this ant species, and highlighted what in those days was an undescribed behavior for this species. In 2005, Da-Silva and Ribeiro presented preliminary results suggesting the existence of trophallaxis in A. sexdens rubropilosa. Here we report on a formal test of the hypothesis of trophallaxis in that species. Our approach was to test ant pairs in which only one individual (Group I) had access to blue-dyed water and the other individual (Group II), a nest-mate, came from a colony dehydrated by offering dry crushed corn for fungal growth. Positive results for trophallaxis were obtained in ants from four colonies and accounted for 33%-46% of all tests in which ants from Group I drank dyed water. These results indicate that trophallaxis occurs in this species.

Granulocyte Colony-stimulating Factor Reduces Mortality by Suppressing Ventricular Arrhythmias in Acute Phase of Myocardial Infarction in Rats

Our aim was to evaluate the effects of granulocyte colony-stimulating factor (G-CSF) on early cardiac arrhythmias after myocardial infarction (MI) and the impact on survival. Male Wistar rats received repeated doses of 50 mu g/kg G-CSF (MI-GCSF group) or vehicle (MI group) at 7, 3, and 1 days before surgery. MI was induced by permanent occlusion of left corollary artery. The electrocardiogram was obtained before occlusion and then for 30 minutes after surgery. Events and duration of ventricular arrhythmias were analyzed. The levels of connexin43 (Cx43) were measured by Western blot immediately before MI production. Survival was significantly increased in MI-GCSF pretreated group (74% versus 52.0% MI. P < 0.05). G-CSF pretreatment also significantly reduced the ventricular premature beats when compared with the untreated-MI group (201 +/- 47 versus 679 +/- 117, P < 0.05). The number and the duration of ventricular tachycardia were smaller in the MI-G-CSF group, as well as the number of ventricular fibrillation episodes (10% versus 69% in NIL P < 0.05). Cx43 levels were significantly increased by G-CSF treatment (1.27 +/- 0.13 versus 0.86 +/- 0.11; P < 0.05). The MI size 24 hours after occlusion was reduced by G-CSF pretreatment (36 +/- 3% versus 44 +/- 2% of left ventricle in MI group; P < 0.05). The increase of Cx43 expression in the heart may explain the reduced incidence in ventricular arrhythmias in the early phases after coronary artery occlusion in rats, thus increasing survival after MI.

The Antiapoptotic Effect of Granulocyte Colony-stimulating Factor Reduces Infarct Size and Prevents Heart Failure Development in Rats

Background/Aim. Granulocyte colony-stimulating factor (G-CSF) reduces myocardial injury and improves cardiac function after myocardial infarction (MI). We investigated the early alterations provided by G-CSF and the chronic repercussions in infarcted rats. Methods. Male Wistar rats (200-250g) received vehicle (MI) or G-CSF (MI-GCSF) (50 mu g/kg, sc) at 7, 3 and 1 days before MI surgery. Afterwards MI was produced and infarct size was measured 1 and 15 days after surgery. Expression of anti-and proapoptotic proteins was evaluated immediately before surgery. 24 hours after surgery, apoptotic nuclei were evaluated. Two weeks after MI, left ventricular (LV) function was evaluated, followed by in situ LV diastolic pressure-volume evaluation. Results. Infarct size was decreased by 1 day pretreatment before occlusion (36 +/- 2.8 vs. 44 +/- 2.1% in MI; P<0.05) and remained reduced at 15 days after infarction (28 +/- 2.2 vs. 36 +/- 1.4% in MI; P<0.05). G-CSF pretreatment increased Bcl-2 and Bcl-xL protein expression, but did not alter Bax in LV. Apoptotic nuclei were reduced by treatment (Sham: 0.46 +/- 0.42, MI: 15.5 +/- 2.43, MI-GCSF: 5.34 +/- 3.34%; P<0.05). Fifteen days after MI, cardiac function remained preserved in G-CSF pretreated rats. The LV dilation was reduced in MI-G-CSF group as compared to MI rats, being closely associated with infarct size. Conclusion. The early beneficial effects of G-CSF were essentials to preserve cardiac function at a chronic stage of myocardial infarction. Copyright (C) 2011 S. Karger AG, Basel

Three-dimensional Reconstruction of Ovaries of Leaf-cutting Ant (Atta sexdens rubropilosa) Queens (Hymenoptera: Formicidae)

In this study, the ovary morphology of newly emerged ant queens of Atta sexdens rubropilosa was studied in whole mount preparations by confocal microscopy. The ovaries are composed of approximately 40 ovarioles, showing non-synchronic oocyte maturation. The terminal filament with clusters of undifferentiated cells was found at the distal end of the ovarioles. Next to this region is the germarium, composed of several elongated cystocytes interconnected by cytoplasmic bridges. The nurse cells (23-28 cells) result from asymmetric mitosis. Cytoskeleton analysis showed F-actin concentrated at the muscle cells of the external tunica and in fusomes inside the ovarioles. Microtubules were concentrated around the nuclei of the nurse and follicular cells. In contrast, the oocytes and the external tunica showed faint staining for tubulin.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Infeasibility handling in genetic algorithm using nested domains for production planning

In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

A Mass-Conserving Algorithm for Dynamical Lubrication Problems With Cavitation

A numerical algorithm for fully dynamical lubrication problems based on the Elrod-Adams formulation of the Reynolds equation with mass-conserving boundary conditions is described. A simple but effective relaxation scheme is used to update the solution maintaining the complementarity conditions on the variables that represent the pressure and fluid fraction. The equations of motion are discretized in time using Newmark`s scheme, and the dynamical variables are updated within the same relaxation process just mentioned. The good behavior of the proposed algorithm is illustrated in two examples: an oscillatory squeeze flow (for which the exact solution is available) and a dynamically loaded journal bearing. This article is accompanied by the ready-to-compile source code with the implementation of the proposed algorithm. [DOI: 10.1115/1.3142903]

Improvements on the Porter`s Stemming Algorithm for Portuguese

The amount of textual information digitally stored is growing every day. However, our capability of processing and analyzing that information is not growing at the same pace. To overcome this limitation, it is important to develop semiautomatic processes to extract relevant knowledge from textual information, such as the text mining process. One of the main and most expensive stages of the text mining process is the text pre-processing stage, where the unstructured text should be transformed to structured format such as an attribute-value table. The stemming process, i.e. linguistics normalization, is usually used to find the attributes of this table. However, the stemming process is strongly dependent on the language in which the original textual information is given. Furthermore, for most languages, the stemming algorithms proposed in the literature are computationally expensive. In this work, several improvements of the well know Porter stemming algorithm for the Portuguese language, which explore the characteristics of this language, are proposed. Experimental results show that the proposed algorithm executes in far less time without affecting the quality of the generated stems.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Grid job scheduling using Route with Genetic Algorithm support

In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.

An unstructured CVFEM and moving interface algorithm for non-Newtonian Hele-Shaw flows in injection molding

Purpose - The purpose of this paper is to develop a novel unstructured simulation approach for injection molding processes described by the Hele-Shaw model. Design/methodology/approach - The scheme involves dual dynamic meshes with active and inactive cells determined from an initial background pointset. The quasi-static pressure solution in each timestep for this evolving unstructured mesh system is approximated using a control volume finite element method formulation coupled to a corresponding modified volume of fluid method. The flow is considered to be isothermal and non-Newtonian. Findings - Supporting numerical tests and performance studies for polystyrene described by Carreau, Cross, Ellis and Power-law fluid models are conducted. Results for the present method are shown to be comparable to those from other methods for both Newtonian fluid and polystyrene fluid injected in different mold geometries. Research limitations/implications - With respect to the methodology, the background pointset infers a mesh that is dynamically reconstructed here, and there are a number of efficiency issues and improvements that would be relevant to industrial applications. For instance, one can use the pointset to construct special bases and invoke a so-called ""meshless"" scheme using the basis. This would require some interesting strategies to deal with the dynamic point enrichment of the moving front that could benefit from the present front treatment strategy. There are also issues related to mass conservation and fill-time errors that might be addressed by introducing suitable projections. The general question of ""rate of convergence"" of these schemes requires analysis. Numerical results here suggest first-order accuracy and are consistent with the approximations made, but theoretical results are not available yet for these methods. Originality/value - This novel unstructured simulation approach involves dual meshes with active and inactive cells determined from an initial background pointset: local active dual patches are constructed ""on-the-fly"" for each ""active point"" to form a dynamic virtual mesh of active elements that evolves with the moving interface.

FAST, PARALLEL AND SECURE CRYPTOGRAPHY ALGORITHM USING LORENZ`S ATTRACTOR

A novel cryptography method based on the Lorenz`s attractor chaotic system is presented. The proposed algorithm is secure and fast, making it practical for general use. We introduce the chaotic operation mode, which provides an interaction among the password, message and a chaotic system. It ensures that the algorithm yields a secure codification, even if the nature of the chaotic system is known. The algorithm has been implemented in two versions: one sequential and slow and the other, parallel and fast. Our algorithm assures the integrity of the ciphertext (we know if it has been altered, which is not assured by traditional algorithms) and consequently its authenticity. Numerical experiments are presented, discussed and show the behavior of the method in terms of security and performance. The fast version of the algorithm has a performance comparable to AES, a popular cryptography program used commercially nowadays, but it is more secure, which makes it immediately suitable for general purpose cryptography applications. An internet page has been set up, which enables the readers to test the algorithm and also to try to break into the cipher.

A WAVELET-BASED SPEAKER VERIFICATION ALGORITHM

This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.