Application of Entropy and Fractal Dimension Analyses to the Pattern Recognition of Contaminated Fish Responses in Aquaculture

The objective of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the collective fish response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm in order to detect moving fish and simultaneously eliminate background, noise and artifacts. The Entropy and the Fractal Dimension (FD) of the trajectory followed by the centroids of the groups of fish were calculated using Shannon and permutation Entropy and the Katz, Higuchi and Katz-Castiglioni's FD algorithms respectively. The methodology was tested on three case groups of European sea bass (Dicentrarchus labrax), two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish submerged in methylmercury contaminated water). The results indicate that Shannon entropy and Katz-Castiglioni were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses. In conclusion, we believe that this methodology has the potential to be embedded in online/real time architecture for contaminant monitoring programs in the aquaculture industry.

Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates

In a multi-target complex network, the links (L-ij) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K-i, K-m, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

Caracterização de imagens de microtomografia de raios X baseada em descritores de textura

A microtomografia computadorizada (computed microtomography - μCT) permite uma análise não destrutiva de amostras, além de possibilitar sua reutilização. A μCT permite também a reconstrução de objetos tridimensionais a partir de suas seções transversais que são obtidas interceptando a amostra através de planos paralelos. Equipamentos de μCT oferecem ao usuário diversas opções de configurações que alteram a qualidade das imagens obtidas afetando, dessa forma, o resultado esperado. Nesta tese foi realizada a caracterização e análise de imagens de μCT geradas pelo microtomógrafo SkyScan1174 Compact Micro-CT. A base desta caracterização é o processamento de imagens. Foram aplicadas técnicas de realce (brilho, saturação, equalização do histograma e filtro de mediana) nas imagens originais gerando novas imagens e em seguida a quantificação de ambos os conjuntos, utilizando descritores de textura (probabilidade máxima, momento de diferença, momento inverso de diferença, entropia e uniformidade). Os resultados mostram que, comparadas às originais, as imagens que passaram por técnicas de realce apresentaram melhoras quando gerados seus modelos tridimensionais.

La pêche au chalut en Côte d'Ivoire. Maximum de rendement économique

This paper analyses the relations between effort and catch per unit effort of trawlers which worked in Côte d'Ivoire from Jan 1966 to Dec 1970. A fishing effort permitting to exploit fishery in the best rentability conditions is proposed.

Optimizing the Curie temperature of pseudo-binary RxR2-x ' Fe-17 (R, R ' = rare earth) for magnetic refrigeration

Several pseudo-binary RxR2-x'Fe-17 alloys (with R = Y, Ce, Pr, Gd and Dy) were synthesized with rhombohedral Th2Zn17-type crystal structure determined from x-ray and neutron powder diffraction. The choice of compositions was done with the aim of tuning the Curie temperature (T-C) in the 270 +/- 20 K temperature range, in order to obtain the maximum magneto-caloric effect around room temperature. The investigated compounds exhibit broad isothermal magnetic entropy changes, Delta S-M(T), with moderate values of the refrigerant capacity, even though the values of Delta S-M(Peak) are relatively low compared with those of the R2Fe17 compounds with R = Pr or Nd. The reduction on the Delta S-M(Peak) is explained in terms of the diminution in the saturation magnetization value. Furthermore, the Delta S-M(T) curves exhibit a similar caret-like behavior, suggesting that the magneto-caloric effect is mainly governed by the Fe-sublattice. A single master curve for Delta S-M/Delta S-M(Peak)(T) under different values of the magnetic field change are obtained for each compound by rescaling of the temperature axis.

Estimating the maximum sustainable yield of bonito (Sarda chiliensis, Scombridae) of northern Chile from monthly catch data

Monthly catch data of bonito Sarda chiliensis from northern Chile, from 1976 to 1989, were used to obtain a series of estimates of the Z-G parameter (i.e., total mortality minus the growth coefficient in weight). This series was then used to estimate a maximum sustainable yield of 4,500 t/year through a modified version of the surplus production model of J. Csirke and J. Caddy. The status of the fishery is discussed.

Maximum likelihood estimation of mortality and growth with individual variability from multiple length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L∞. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.