Neural bruise prediction models for fruit handling and machinery evaluation.

Some neural bruise prediction models have been implemented in the laboratory, for the most traded fruit species and varieties, allowing the prediction of the acceptability or rejectability for damages, with respect to the EC Standards. Different models have been built for both quasi-static (compression) and dynamic (impact) loads covering the whole commercial ripening period of fruits. A simulation process has been developed gathering the information on laboratory bruise models and load sensor calibrations for different electronic devices (IS-100 and DEA-1, for impact and compression loads respectively). Some evaluation methodology has been designed gathering the information on the mechanical properties of fruits and the loading records of electronic devices. The evaluation system allows to determine the current stage of fruit handling process and machinery.

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.

Inteligencia artificial para la predicción y control del acabado superficial en procesos de fresado a alta velocidad

El objetivo principal de esta tesis doctoral es profundizar en el análisis y diseño de un sistema inteligente para la predicción y control del acabado superficial en un proceso de fresado a alta velocidad, basado fundamentalmente en clasificadores Bayesianos, con el prop´osito de desarrollar una metodolog´ıa que facilite el diseño de este tipo de sistemas. El sistema, cuyo propósito es posibilitar la predicción y control de la rugosidad superficial, se compone de un modelo aprendido a partir de datos experimentales con redes Bayesianas, que ayudar´a a comprender los procesos dinámicos involucrados en el mecanizado y las interacciones entre las variables relevantes. Dado que las redes neuronales artificiales son modelos ampliamente utilizados en procesos de corte de materiales, también se incluye un modelo para fresado usándolas, donde se introdujo la geometría y la dureza del material como variables novedosas hasta ahora no estudiadas en este contexto. Por lo tanto, una importante contribución en esta tesis son estos dos modelos para la predicción de la rugosidad superficial, que se comparan con respecto a diferentes aspectos: la influencia de las nuevas variables, los indicadores de evaluación del desempeño, interpretabilidad. Uno de los principales problemas en la modelización con clasificadores Bayesianos es la comprensión de las enormes tablas de probabilidad a posteriori producidas. Introducimos un m´etodo de explicación que genera un conjunto de reglas obtenidas de árboles de decisión. Estos árboles son inducidos a partir de un conjunto de datos simulados generados de las probabilidades a posteriori de la variable clase, calculadas con la red Bayesiana aprendida a partir de un conjunto de datos de entrenamiento. Por último, contribuimos en el campo multiobjetivo en el caso de que algunos de los objetivos no se puedan cuantificar en números reales, sino como funciones en intervalo de valores. Esto ocurre a menudo en aplicaciones de aprendizaje automático, especialmente las basadas en clasificación supervisada. En concreto, se extienden las ideas de dominancia y frontera de Pareto a esta situación. Su aplicación a los estudios de predicción de la rugosidad superficial en el caso de maximizar al mismo tiempo la sensibilidad y la especificidad del clasificador inducido de la red Bayesiana, y no solo maximizar la tasa de clasificación correcta. Los intervalos de estos dos objetivos provienen de un m´etodo de estimación honesta de ambos objetivos, como e.g. validación cruzada en k rodajas o bootstrap.---ABSTRACT---The main objective of this PhD Thesis is to go more deeply into the analysis and design of an intelligent system for surface roughness prediction and control in the end-milling machining process, based fundamentally on Bayesian network classifiers, with the aim of developing a methodology that makes easier the design of this type of systems. The system, whose purpose is to make possible the surface roughness prediction and control, consists of a model learnt from experimental data with the aid of Bayesian networks, that will help to understand the dynamic processes involved in the machining and the interactions among the relevant variables. Since artificial neural networks are models widely used in material cutting proceses, we include also an end-milling model using them, where the geometry and hardness of the piecework are introduced as novel variables not studied so far within this context. Thus, an important contribution in this thesis is these two models for surface roughness prediction, that are then compared with respecto to different aspects: influence of the new variables, performance evaluation metrics, interpretability. One of the main problems with Bayesian classifier-based modelling is the understanding of the enormous posterior probabilitiy tables produced. We introduce an explanation method that generates a set of rules obtained from decision trees. Such trees are induced from a simulated data set generated from the posterior probabilities of the class variable, calculated with the Bayesian network learned from a training data set. Finally, we contribute in the multi-objective field in the case that some of the objectives cannot be quantified as real numbers but as interval-valued functions. This often occurs in machine learning applications, especially those based on supervised classification. Specifically, the dominance and Pareto front ideas are extended to this setting. Its application to the surface roughness prediction studies the case of maximizing simultaneously the sensitivity and specificity of the induced Bayesian network classifier, rather than only maximizing the correct classification rate. Intervals in these two objectives come from a honest estimation method of both objectives, like e.g. k-fold cross-validation or bootstrap.

Mathematical modelling of neural processes within the oculomotor system

It is presented a mathematical model of the oculomotor plant, based on experimental data in cats. The system that generates, from the neuronal processes at the motoneuron, the control signals to the eye muscles that moves the eye. In contrast with previous models, that base the eye movement related motoneuron behavior on a first order linear differential equation, non-linear effects are described: A dependency on the eye angular position of the model parameters.

Functional neuroanatomical double dissociation of mnemonic and executive control processes contributing to working memory performance

We used event-related functional MRI to investigate the neural bases of two categories of mental processes believed to contribute to performance of an alphabetization working memory task: memory storage and memory manipulation. Our delayed-response tasks required memory for the identity and position-in-the-display of items in two- or five-letter memory sets (to identify load-sensitive regions) or memory for the identity and relative position-in-the-alphabet of items in five-letter memory sets (to identify manipulation-sensitive regions). Results revealed voxels in the left perisylvian cortex of five of five subjects showing load sensitivity (as contrasted with alphabetization-sensitive voxels in this region in only one subject) and voxels of dorsolateral prefrontal cortex in all subjects showing alphabetization sensitivity (as contrasted with load-sensitive voxels in this region in two subjects). This double dissociation was reliable at the group level. These data are consistent with the hypothesis that the nonmnemonic executive control processes that can contribute to working memory function are primarily prefrontal cortex-mediated whereas mnemonic processes necessary for working memory storage are primarily posteriorly mediated. More broadly, they support the view that working memory is a faculty that arises from the coordinated interaction of computationally and neuroanatomically dissociable processes.

Multipotent neural precursors can differentiate toward replacement of neurons undergoing targeted apoptotic degeneration in adult mouse neocortex

Neurons undergoing targeted photolytic cell death degenerate by apoptosis. Clonal, multipotent neural precursor cells were transplanted into regions of adult mouse neocortex undergoing selective degeneration of layer II/III pyramidal neurons via targeted photolysis. These precursors integrated into the regions of selective neuronal death; 15 ± 7% differentiated into neurons with many characteristics of the degenerated pyramidal neurons. They extended axons and dendrites and established afferent synaptic contacts. In intact and kainic acid-lesioned control adult neocortex, transplanted precursors differentiated exclusively into glia. These results suggest that the microenvironmental alterations produced by this synchronous apoptotic neuronal degeneration in adult neocortex induced multipotent neural precursors to undergo neuronal differentiation which ordinarily occurs only during embryonic corticogenesis. Studying the effects of this defined microenvironmental perturbation on the differentiation of clonal neural precursors may facilitate identification of factors involved in commitment and differentiation during normal development. Because photolytic degeneration simulates some mechanisms underlying apoptotic neurodegenerative diseases, these results also suggest the possibility of neural precursor transplantation as a potential cell replacement or molecular support therapy for some diseases of neocortex, even in the adult.

Nerve growth factor control of neuronal expression of angiogenetic and vasoactive factors

In postnatal tissues, angiogenesis occurs in nontumoral conditions on appropriate stimuli. In the nervous tissue, hypoxia, neural graft, increased neural function, and synaptic activity are associated with neoangiogenesis. We have investigated the occurrence of neoangiogenesis in the superior cervical ganglia (scg) of newborn rats treated for 8–21 days with 6-hydroxy-dopamine (6-OHDA), nerve growth factor (NGF), or 6-OHDA + NGF. The two latter treatments induced a significant increase in scg size. However, the increase after combined treatment far exceeded that of NGF alone. Similarly, histological and histochemical analysis revealed neuronal hypertrophy and endothelial cell hyperplasia associated with stromal hypertrophy (as described by laminin immunostaining) and increased vascular bed (as revealed by platelet/endothelial cell adhesion molecule-1 immunostaining) in 6-OHDA + NGF-treated pups. NGF, either alone or associated with 6-OHDA, also induced a significant up-regulation of NADPH diaphorase, neuronal nitric oxide synthase, and vascular endothelial growth factor expression in scg neurons. The present investigation suggests that the increase of scg size induced by NGF and 6-OHDA + NGF is associated with neoangiogenesis, and that the induction of vasoactive and angiogenic factors in neurons represents a further and previously undisclosed effect of NGF.

Plasticity in the neural coding of auditory space in the mammalian brain

Sound localization relies on the neural processing of monaural and binaural spatial cues that arise from the way sounds interact with the head and external ears. Neurophysiological studies of animals raised with abnormal sensory inputs show that the map of auditory space in the superior colliculus is shaped during development by both auditory and visual experience. An example of this plasticity is provided by monaural occlusion during infancy, which leads to compensatory changes in auditory spatial tuning that tend to preserve the alignment between the neural representations of visual and auditory space. Adaptive changes also take place in sound localization behavior, as demonstrated by the fact that ferrets raised and tested with one ear plugged learn to localize as accurately as control animals. In both cases, these adjustments may involve greater use of monaural spectral cues provided by the other ear. Although plasticity in the auditory space map seems to be restricted to development, adult ferrets show some recovery of sound localization behavior after long-term monaural occlusion. The capacity for behavioral adaptation is, however, task dependent, because auditory spatial acuity and binaural unmasking (a measure of the spatial contribution to the “cocktail party effect”) are permanently impaired by chronically plugging one ear, both in infancy but especially in adulthood. Experience-induced plasticity allows the neural circuitry underlying sound localization to be customized to individual characteristics, such as the size and shape of the head and ears, and to compensate for natural conductive hearing losses, including those associated with middle ear disease in infancy.

Combinatorial control of muscle development by basic helix-loop-helix and MADS-box transcription factors.

Members of the MyoD family of muscle-specific basic helix-loop-helix (bHLH) proteins function within a genetic pathway to control skeletal muscle development. Mutational analyses of these factors suggested that their DNA binding domains mediated interaction with a coregulator required for activation of muscle-specific transcription. Members of the myocyte enhancer binding factor 2 (MEF2) family of MADS-box proteins are expressed at high levels in muscle and neural cells and at lower levels in several other cell types. MEF2 factors are unable to activate muscle gene expression alone, but they potentiate the transcriptional activity of myogenic bHLH proteins. This potentiation appears to be mediated by direct interactions between the DNA binding domains of these different types of transcription factors. Biochemical and genetic evidence suggests that MEF2 factors are the coregulators for myogenic bHLH proteins. The presence of MEF2 and cell-specific bHLH proteins in other cell types raises the possibility that these proteins may also cooperate to regulate other programs of cell-specific gene expression. We present a model to account for such cooperative interactions.

Neural correlates of mental transformations of the body-in-space.

Regional cerebral blood flow was measured with positron emission tomography in human subjects during the performance of a task requiring mental rotation of their hand and a perceptually equivalent control task that did not require such a process. Comparison of the distribution of cerebral activity between these conditions demonstrated significant blood flow increases in the superior parietal cortex, the intraparietal sulcus, and the adjacent rostralmost part of the inferior parietal lobule. These findings demonstrated that, in the human brain, there is a specific system of parietal areas that are involved in mental transformations of the body-in-space.

Neural cell adhesion molecule (N-CAM) inhibits astrocyte proliferation after injury to different regions of the adult rat brain.

After a penetrating lesion in the central nervous system, astrocytes enlarge, divide, and participate in creating an environment that adversely affects neuronal regeneration. We have recently shown that the neural cell adhesion molecule (N-CAM) partially inhibits the division of early postnatal rat astrocytes in vitro. In the present study, we demonstrate that addition of N-CAM, the third immunoglobulin-like domain of N-CAM, or a synthetic decapeptide corresponding to a putative homophilic binding site in N-CAM partially inhibits astrocyte proliferation after a stab lesion in the adult rat brain. Animals were lesioned in the cerebral cortex, hippocampus, or striatum with a Hamilton syringe and needle at defined stereotaxic positions. On one side, the lesions were concomitantly infused with N-CAM or with one of the N-CAM-related molecules. As a control, a peptide of the same composition as the N-CAM decapeptide but of random sequence was infused on the contralateral side of the brain. We consistently found that the population of dividing astrocytes was significantly smaller on the side in which N-CAM or one of the N-CAM-related molecules was infused than on the opposite side. The inhibition was greatest in the cortical lesion sites (approximately 50%) and was less pronounced in the hippocampus (approximately 25%) and striatum (approximately 20%). Two weeks after the lesion, the cerebral cortical sites infused with N-CAM continued to exhibit a significantly smaller population of dividing astrocytes than the sites on the opposite side. When N-CAM and basic fibroblast growth factor, which is known to stimulate astrocyte division in vitro, were coinfused into cortical lesion sites, astrocyte proliferation was still inhibited. These results suggest the hypothesis that, by reducing glial proliferation, N-CAM or its peptides may help create an environment that is more suitable for neuronal regeneration.

Neural basis of lexical-semantic processing and integration of symbolic gestures with words

Three studies investigated the relation between symbolic gestures and words, aiming at discover the neural basis and behavioural features of the lexical semantic processing and integration of the two communicative signals. The first study aimed at determining whether elaboration of communicative signals (symbolic gestures and words) is always accompanied by integration with each other and, if present, this integration can be considered in support of the existence of a same control mechanism. Experiment 1 aimed at determining whether and how gesture is integrated with word. Participants were administered with a semantic priming paradigm with a lexical decision task and pronounced a target word, which was preceded by a meaningful or meaningless prime gesture. When meaningful, the gesture could be either congruent or incongruent with word meaning. Duration of prime presentation (100, 250, 400 ms) randomly varied. Voice spectra, lip kinematics, and time to response were recorded and analyzed. Formant 1 of voice spectra, and mean velocity in lip kinematics increased when the prime was meaningful and congruent with the word, as compared to meaningless gesture. In other words, parameters of voice and movement were magnified by congruence, but this occurred only when prime duration was 250 ms. Time to response to meaningful gesture was shorter in the condition of congruence compared to incongruence. Experiment 2 aimed at determining whether the mechanism of integration of a prime word with a target word is similar to that of a prime gesture with a target word. Formant 1 of the target word increased when word prime was meaningful and congruent, as compared to meaningless congruent prime. Increase was, however, present for whatever prime word duration. In the second study, experiment 3 aimed at determining whether symbolic prime gesture comprehension makes use of motor simulation. Transcranial Magnetic Stimulation was delivered to left primary motor cortex 100, 250, 500 ms after prime gesture presentation. Motor Evoked Potential of First Dorsal Interosseus increased when stimulation occurred 100 ms post-stimulus. Thus, gesture was understood within 100ms and integrated with the target word within 250 ms. Experiment 4 excluded any hand motor simulation in order to comprehend prime word. The effect of the prior presentation of a symbolic gesture on congruent target word processing was investigated in study 3. In experiment 5, symbolic gestures were presented as primes, followed by semantically congruent target word or pseudowords. In this case, lexical-semantic decision was accompanied by a motor simulation at 100ms after the onset of the verbal stimuli. Summing up, the same type of integration with a word was present for both prime gesture and word. It was probably subsequent to understanding of the signal, which used motor simulation for gesture and direct access to semantics for words. However, gesture and words could be understood at the same motor level through simulation if words were preceded by an adequate gestural context. Results are discussed in the prospective of a continuum between transitive actions and emblems, in parallelism with language; the grounded/symbolic content of the different signals evidences relation between sensorimotor and linguistic systems, which could interact at different levels.

Phagocytosis of Photoreceptor Outer Segments by Transplanted Human Neural Stem Cells as a Neuroprotective Mechanism in Retinal Degeneration

Purpose. Transplantation of human central nervous system stem cells (HuCNS-SC) into the subretinal space of Royal College of Surgeons (RCS) rats preserves photoreceptors and visual function. To explore possible mechanism(s) of action underlying this neuroprotective effect, we performed a detailed morphologic and ultrastructure analysis of HuCNS-SC transplanted retinas. Methods. The HuCNS-SC were transplanted into the subretinal space of RCS rats. Histologic examination of the transplanted retinas was performed by light and electron microscopy. Areas of the retina adjacent to HuCNS-SC graft (treated regions) were analyzed and compared to control sections obtained from the same retina, but distant from the transplant site (untreated regions). Results. The HuCNS-SC were detected as a layer of STEM 121 immunopositive cells in the subretinal space. In treated regions, preserved photoreceptor nuclei, as well as inner and outer segments were identified readily. In contrast, classic signs of degeneration were observed in the untreated regions. Interestingly, detailed ultrastructure analysis revealed a striking preservation of the photoreceptor–bipolar–horizontal cell synaptic contacts in the outer plexiform layer (OPL) of treated areas, in stark contrast with untreated areas. Finally, the presence of phagosomes and vesicles exhibiting the lamellar structure of outer segments also was detected within the cytosol of HuCNS-SC, indicating that these cells have phagocytic capacity in vivo. Conclusions. This study reveals the novel finding that preservation of specialized synaptic contacts between photoreceptors and second order neurons, as well as phagocytosis of photoreceptor outer segments, are potential mechanism(s) of HuCNS-SC transplantation, mediating functional rescue in retinal degeneration.

An Electronic Reconfigurable Neural Architecture for Intrusion Detection

The explosive growth of the traffic in computer systems has made it clear that traditional control techniques are not adequate to provide the system users fast access to network resources and prevent unfair uses. In this paper, we present a reconfigurable digital hardware implementation of a specific neural model for intrusion detection. It uses a specific vector of characterization of the network packages (intrusion vector) which is starting from information obtained during the access intent. This vector will be treated by the system. Our approach is adaptative and to detecting these intrusions by using a complex artificial intelligence method known as multilayer perceptron. The implementation have been developed and tested into a reconfigurable hardware (FPGA) for embedded systems. Finally, the Intrusion detection system was tested in a real-world simulation to gauge its effectiveness and real-time response.

Countermanding in rats as a practical model for investigation of adaptive control of behaviour, lifespan changes in behavioural control and neurotransmitter function

The countermanding paradigm was designed to investigate the ability to cancel a prepotent response when a stop signal is presented and allows estimation of the stop signal response time (SSRT), an otherwise unobservable behaviour. Humans exhibit adaptive control of behaviour in the countermanding task, proactively lengthening response time (RT) in expectation of stopping and reactively lengthening RT following stop trials or errors. Human performance changes throughout the lifespan, with longer RT, SSRT and greater emphasis on post-error slowing reported for older compared to younger adults. Inhibition in the task has generally been improved by drugs that increase extracellular norepinephrine. The current thesis examined a novel choice response countermanding task in rats to explore whether rodent countermanding performance is a suitable model for the study of adaptive control of behaviour, lifespan changes in behavioural control and the role of neurotransmitters in these behaviours. Rats reactively adjusted RT in the countermanding task, shortening RT after consecutive correct go trials and lengthening RT following non-cancelled, but not cancelled stop trials, in sessions with a 10 s, but not a 1 s post-error timeout interval. Rats proactively lengthened RT in countermanding task sessions compared to go trial-only sessions. Together, these findings suggest that rats strategically lengthened RT in the countermanding task to improve accuracy and avoid longer, unrewarded timeout intervals. Next, rats exhibited longer RT and relatively conserved post-error slowing, but no significant change in SSRT when tested at 12, compared to 7 months of age, suggesting that rats exhibit changes in countermanding task performance with aging similar to those observed in humans. Finally, acute administration of yohimbine (1.25, 2.5 mg/kg) and d-amphetamine (0.25, 0.5 mg/kg), which putatively increase extracellular norepinephrine and dopamine respectively, resulted in RT shortening, baseline-dependent effects on SSRT, and attenuated adaptive RT adjustments in rats in the case of d-amphetamine. These findings suggest that dopamine and norepinephrine encouraged motivated, reward-seeking behaviour and supported inhibitory control in an inverted-U-like fashion. Taken together, these observations validate the rat countermanding task for further study of the neural correlates and neurotransmitters mediating adaptive control of behaviour and lifespan changes in behavioural control.