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This chapter demonstrates the pipeline from data collection until classifier models that achieve the best possible model in identifying the disparity between hunger states. The pre-processing segment describes the features of the data sets obtained by means of image processing. The method includes the simple moving average (SMA), downsizing factors, dynamic time warping (DTW) and clustering by the k-means method. This is to rationally assign the necessary significant information from the data collected and processed the images captured for demand feeder and fish motion as a synthesis for anticipating the state of fish starvation. The selection of features in this study takes place via the boxplot analysis and the principal component analysis (PCA) on dimensionality reduction. Finally, the validation of the hunger state will be addressed by comparing machine learning (ML) classifiers, namely the discriminant analysis (DA), support vector machine (SVM) and k-nearest neighbour (k-NN). The outcome in this chapter will validate the features from image processing as a tool for identifying the behavioural changes of the fish in school size.

This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish growth is essential, since they have implications for higher productivity in fish farms. Computer vision and machine learning techniques make it possible to quantify the subjective perception of hunger behaviour and so allow food to be provided as necessary. The book analyses the conceptual framework of motion tracking, feeding schedule and prediction classifiers in order to classify the hunger state, and proposes a system comprising an automated feeder system, image-processing module, as well as machine learning classifiers. Furthermore, the system substitutes conventional, complex modelling techniques with a robust, artificial intelligence approach. The findings presented are of interest to researchers, fish farmers, and aquaculture technologist wanting to gain insights into the productivity of fish and fish behaviour.

Tissue engineering of autologous lung tissue aims to become a therapeutic alternative to transplantation. Efforts published so far in creating scaffolds have used harsh decellularization techniques that damage the extracellular matrix (ECM), deplete its components and take up to 5 weeks to perform. The aim of this study was to create a lung natural acellular scaffold using a method that will reduce the time of production and better preserve scaffold architecture and ECM components. Decellularization of rat lungs via the intratracheal route removed most of the nuclear material when compared to the other entry points. An intermittent inflation approach that mimics lung respiration yielded an acellular scaffold in a shorter time with an improved preservation of pulmonary micro-architecture. Electron microscopy demonstrated the maintenance of an intact alveolar network, with no evidence of collapse or tearing. Pulsatile dye injection via the vasculature indicated an intact capillary network in the scaffold. Morphometry analysis demonstrated a significant increase in alveolar fractional volume, with alveolar size analysis confirming that alveolar dimensions were maintained. Biomechanical testing of the scaffolds indicated an increase in resistance and elastance when compared to fresh lungs. Staining and quantification for ECM components showed a presence of collagen, elastin, GAG and laminin. The intratracheal intermittent decellularization methodology could be translated to sheep lungs, demonstrating a preservation of ECM components, alveolar and vascular architecture. Decellularization treatment and methodology preserves lung architecture and ECM whilst reducing the production time to 3 h. Cell seeding and in vivo experiments are necessary to proceed towards clinical translation.

Mutations in the survival of motor neuron gene (SMN1) are responsible for spinal muscular atrophy (SMA), a fatal neuromuscular disorder. Mice carrying a homozygous deletion of Smn exon 7 directed to skeletal muscle (HSA-Cre, Smn^F7/F7 mice) present clinical features of human muscular dystrophies for which new therapeutic approaches are highly warranted. Herein we demonstrate that tail vein transplantation of mouse amniotic fluid stem (AFS) cells enhances the muscle strength and improves the survival rate of the affected animals. Secondly, after cardiotoxin injury of the Tibialis Anterior, only AFS-transplanted mice efficiently regenerate. Most importantly, secondary transplants of satellite cells (SC) derived from treated mice show that AFS cells integrate into the muscle stem cell compartment, and have long term muscle regeneration capacity indistinguishable from that of wild type-derived SC. This is the first study demonstrating the functional and stable integration of AFS cells into the skeletal muscle, highlighting their value as cell source for the treatment of muscular dystrophies.