Kidney injury and cell therapy: Preclinical study

The aim of this study is to show histological and immunofluorescence analysis of renal parenchyma of agoutis affected by gentamicin‐induced renal disease after the infusion of bone marrow mononuclear cells (BMMC) stained with Hoechst®. Nine agouti's males were divided into three groups: Test group (TG): renal disease by gentamicin induced (n = 3), cell therapy group (CTG): renal disease by gentamicin induced and BMMC infusion (n = 3), and control group (CG): nonrenal disease and BMMC infusion (n = 3). TG and CTG were submitted to the protocol of renal disease induction using weekly application of gentamicin sulfate for 4 months. CG and CTG received a 1 × 108 BMMC stained with Hoechst and were euthanized for kidney examination 21 days after BMMC injection and samples were collected for histology and immunofluorescence analysis. Histological analysis demonstrated typical interstitial lesions in kidney similarly to human disease, as tubular necrosis, glomerular destruction, atrophy tubular, fibrotic areas, and collagen deposition. We conclude that histological analysis suggest a positive application of agouti's as a model for a gentamicin inducing of kidney disease, beyond the immunofluorescence analysis suggest a significant migration of BMMC to sites of renal injury in CTG. Microsc. Res. Tech., 2012. © 2011 Wiley Periodicals, Inc.     

Biodegradation of 4-methylaniline in a sequencing batch reactor

The biodegradation of the aromatic amine 4-methylaniline (4MA) using an aerobic sequencing batch reactor was evaluated. The specific degradation rate showed an exponential increase during the acclimation of the microorganisms reaching a maximal value of 34 mg 4MA/VSS/h. After the acclimation, the process showed a stable operation. A high similarity index was observed, indicating a low variation in the population diversity. During this period, the physicochemical parameters demonstrated a stable operation of the reactor.     

Replacing dichromate with hydrogen peroxide in the chemical oxygen demand (COD) test

The widely used standard method for chemical oxygen demand (COD) involves hazardous chromium species, and its two-hour heating protocol entails a substantial amount of energy expenditure. In the present work we report a proof of concept for a major modification of this method in the range 10-800 mgCOD/L, whereby H2O2 is proposed as a replacement oxidizer. This modification not only reduces the use of unsafe chromium species but also allows for the use of milder conditions that decrease the total energy outlay. The results are comparable with those obtained either with the standard method or with a commercial Hach? kit.     

Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules

This paper presents a proposal for the extraction of association rules called G3PARM (Grammar-Guided Genetic Programming for Association Rule Mining) that makes the knowledge extracted more expressive and flexible. This algorithm allows a context-free grammar to be adapted and applied to each specific problem or domain and eliminates the problems raised by discretization. This proposal keeps the best individuals (those that exceed a certain threshold of support and confidence) obtained with the passing of generations in an auxiliary population of fixed size n. G3PARM obtains solutions within specified time limits and does not require the large amounts of memory that the exhaustive search algorithms in the field of association rules do. Our approach is compared to exhaustive search (Apriori and FP-Growth) and genetic (QuantMiner and ARMGA) algorithms for mining association rules and performs an analysis of the mined rules. Finally, a series of experiments serve to contrast the scalability of our algorithm. The proposal obtains a small set of rules with high support and confidence, over 90 and 99% respectively. Moreover, the resulting set of rules closely satisfies all the dataset instances. These results illustrate that our proposal is highly promising for the discovery of association rules in different types of datasets.     

A Well-balanced Finite Volume-Augmented Lagrangian Method for an Integrated Herschel-Bulkley Model

We are interested in the derivation of an integrated Herschel-Bulkley model for shallow flows, as well as in the design of a numerical algorithm to solve the resulting equations. The goal is to simulate the evolution of thin sheet of viscoplastic materials on inclined planes and, in particular, to be able to compute the evolution from dynamic to stationary states. The model involves a variational inequality and it is valid from null to moderate slopes. The proposed numerical scheme is well balanced and involves a coupling between a duality technique (to treat plasticity), a fixed point method (to handle the power law) and a finite volume discretization. Several numerical tests are done, including a comparison with an analytical solution, to confirm the well balanced property and the ability to cope with the various rheological regimes associated with the Herschel-Bulkley constitutive law.     

A multi-objective evolutionary algorithm for an effective tuning of?fuzzy logic controllers in?heating, ventilating and air conditioning systems

This paper focuses on the use of multi-objective evolutionary algorithms to develop smartly tuned fuzzy logic controllers dedicated to the control of heating, ventilating and air conditioning systems, energy performance, stability and indoor comfort requirements. This problem presents some specific restrictions that make it very particular and complex because of the large time requirements needed to consider multiple criteria (which enlarge the solution search space) and the long computation time models required in each evaluation.     

Self-calibrated,Multi-spectral Photometric Stereo for 3D Face Capture

This paper addresses the problem of obtaining 3d detailed reconstructions of human faces in real-time and with inexpensive hardware. We present an algorithm based on a monocular multi-spectral photometric-stereo setup. This system is known to capture high-detailed deforming 3d surfaces at high frame rates and without having to use any expensive hardware or synchronized light stage. However, the main challenge of such a setup is the calibration stage, which depends on the lights setup and how they interact with the specific material being captured, in this case, human faces. For this purpose we develop a self-calibration technique where the person being captured is asked to perform a rigid motion in front of the camera, maintaining a neutral expression. Rigidity constrains are then used to compute the head’s motion with a structure-from-motion algorithm. Once the motion is obtained, a multi-view stereo algorithm reconstructs a coarse 3d model of the face. This coarse model is then used to estimate the lighting parameters with a stratified approach: In the first step we use a RANSAC search to identify purely diffuse points on the face and to simultaneously estimate this diffuse reflectance model. In the second step we apply non-linear optimization to fit a non-Lambertian reflectance model to the outliers of the previous step. The calibration procedure is validated with synthetic and real data.     

Distance maps from unthresholded magnitudes

A straightforward algorithm that computes distance maps from unthresholded magnitudes is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of spatial and temporal coherence of distance map values, showing better results in both measurements than those obtained with Sobel or Deriche gradients and classic chessboard distance transforms.