971 resultados para Motor system
Resumo:
Cerebellar ataxias represent a spectrum of disorders which are, however, linked by common symptoms of motor incoordination and are typically associated with deficient in Purkinje cell firing activity and, often, degeneration. Cerebellar ataxias currently lack a curative agent. The endocannabinoid (eCB) system includes eCB compounds and their associated metabolic enzymes, together with cannabinoid receptors, predominantly the cannabinoid CB1 receptor (CB1R) in the cerebellum; activation of this system in the cerebellar cortex is associated with deficits in motor coordination characteristic of ataxia, effects which can be prevented by CB1R antagonists. Of further interest are various findings that CB1R deficits may also induce a progressive ataxic phenotype. Together these studies suggest that motor coordination is reliant on maintaining the correct balance in eCB system signalling. Recent work also demonstrates deficient cannabinoid signalling in the mouse ‘ducky2J’ model of ataxia. In light of these points, the potential mechanisms whereby cannabinoids may modulate the eCB system to ameliorate dysfunction associated with cerebellar ataxias are considered.
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Damage following ischemia and reperfusion (I/R) is common in the intestine and can be caused during abdominal surgery, in several disease states and following intestinal transplantation. Most studies have concentrated on damage to the mucosa, although published evidence also points to effects on neurons. Moreover, alterations of neuronally controlled functions of the intestine persist after I/R. The present study was designed to investigate the time course of damage to neurons and the selectivity of the effect of I/R damage for specific types of enteric neurons. A branch of the superior mesenteric artery supplying the distal ileum of anesthetised guinea pigs was occluded for 1 h and the animals were allowed to recover for 2 h to 4 weeks before tissue was taken for the immunohistochemical localization of markers of specific neuron types in tissues from sham and I/R animals. The dendrites of neurons with nitric oxide synthase (NOS) immunoreactivity, which are inhibitory motor neurons and interneurons, were distorted and swollen by 24 h after I/R and remained enlarged up to 28 days. The total neuron profile areas (cell body plus dendrites) increased by 25%, but the sizes of cell bodies did not change significantly. Neurons of type II morphology (intrinsic primary afferent neurons), revealed by NeuN immunoreactivity, were transiently reduced in cell size, at 24 h and 7 days. These neurons also showed signs of minor cell surface blebbing. Calretinin neurons, many of which are excitatory motor neurons, were unaffected. Thus, this study revealed a selective damage to NOS neurons that was observed at 24 h and persisted up to 4 weeks, without a significant change in the relative numbers of NOS neurons.
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Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.
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The purpose of this work is to develop a web based decision support system, based onfuzzy logic, to assess the motor state of Parkinson patients on their performance in onscreenmotor tests in a test battery on a hand computer. A set of well defined rules, basedon an expert’s knowledge, were made to diagnose the current state of the patient. At theend of a period, an overall score is calculated which represents the overall state of thepatient during the period. Acceptability of the rules is based on the absolute differencebetween patient’s own assessment of his condition and the diagnosed state. Anyinconsistency can be tracked by highlighted as an alert in the system. Graphicalpresentation of data aims at enhanced analysis of patient’s state and performancemonitoring by the clinic staff. In general, the system is beneficial for the clinic staff,patients, project managers and researchers.
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Energy efficiency and renewable energy use are two main priorities leading to industrial sustainability nowadays according to European Steel Technology Platform (ESTP). Modernization efforts can be done by industries to improve energy consumptions of the production lines. These days, steel making industrial applications are energy and emission intensive. It was estimated that over the past years, energy consumption and corresponding CO2 generation has increased steadily reaching approximately 338.15 parts per million in august 2010 [1]. These kinds of facts and statistics have introduced a lot of room for improvement in energy efficiency for industrial applications through modernization and use of renewable energy sources such as solar Photovoltaic Systems (PV).The purpose of this thesis work is to make a preliminary design and simulation of the solar photovoltaic system which would attempt to cover the energy demand of the initial part of the pickling line hydraulic system at the SSAB steel plant. For this purpose, the energy consumptions of this hydraulic system would be studied and evaluated and a general analysis of the hydraulic and control components performance would be done which would yield a proper set of guidelines contributing towards future energy savings. The results of the energy efficiency analysis showed that the initial part of the pickling line hydraulic system worked with a low efficiency of 3.3%. Results of general analysis showed that hydraulic accumulators of 650 liter size should be used by the initial part pickling line system in combination with a one pump delivery of 100 l/min. Based on this, one PV system can deliver energy to an AC motor-pump set covering 17.6% of total energy and another PV system can supply a DC hydraulic pump substituting 26.7% of the demand. The first system used 290 m2 area of the roof and was sized as 40 kWp, the second used 109 m2 and was sized as 15.2 kWp. It was concluded that the reason for the low efficiency was the oversized design of the system. Incremental modernization efforts could help to improve the hydraulic system energy efficiency and make the design of the solar photovoltaic system realistically possible. Two types of PV systems where analyzed in the thesis work. A method was found calculating the load simulation sequence based on the energy efficiency studies to help in the PV system simulations. Hydraulic accumulators integrated into the pickling line worked as energy storage when being charged by the PV system as well.
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This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulation results of PID controller provide very good results and the controller is further tuned in order to decrease its overshoot error which is common in PID controllers. Further it is purposed that in industrial environment these controllers are better than others controllers as PID controllers are easy to tuned and cheap. Pole placement controller is the best example of control engineering. An addition of integrator reduced the noise disturbances in pole placement controller and this makes it a good choice for industrial applications. The fuzzy controller is introduce with a DC chopper to make the DC motor speed control smooth and almost no steady state error is observed. Another advantage is achieved in fuzzy controller that the simulations of three different controllers are compared and concluded from the results that Fuzzy controller outperforms to PID controller in terms of steady state error and smooth step response. While Pole placement controller have no comparison in terms of controls because designer can change the step response according to nature of control systems, so this controller provide wide range of control over a system. Poles location change the step response in a sense that if poles are near to origin then step response of motor is fast. Finally a GUI of these three controllers are developed which allow the user to select any controller and change its parameters according to the situation.
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A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.
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Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic. The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.
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In the artificial lift method by Electrical Submersible Pump (ESP), the energy is transmitted for the well´s deep through a flat electric handle, where it is converted into mechanical energy through an engine of sub-surface, which is connected to a centrifugal pump. This transmits energy to the fluid under the pressure form, bringing it to the surface In this method the subsurface equipment is basically divided into: pump, seal and motor. The main function of the seal is the protect the motor, avoiding the motor´s oil be contaminated by oil production and the consequent burning of it. Over time, the seal will be wearing and initiates a contamination of motor oil, causing it to lose its insulating characteristics. This work presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type Electrical Submersible Pump (ESP). The objective of this sensor is to generate alarm signal just the moment when the contamination in the isolated oil is present, enabling the implementation of a predictive maintenance. The prototype was designed to work in harsh conditions to reach a depth of 2000m and temperatures up to 150°C. It was used a simulator software to defined the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62HP motor showed a good reliability and fast response of the prototype.
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Contextualization: Several studies have examined the mobility of this group of children, however little is known about the impact of motor function in activities of daily living, considering the seriousness of their neuromotor damage. Objective: Identify the functional differences of children with Cerebral Palsy with different levels of motor dysfunction and correlate these differences with the areas of mobility, self-care and social function in functional ability and caregiver´s assistance of these children. Methods: An l analytical cross-section search was developed, which were part 70 children / families aged from 4 to 7.5 years, in the Rehabilitation Center for Children. As tools were used the Pediatric Evaluation Disability Inventory (PEDI) and the Gross Motor Function Classification System (GMFCS). Data analysis was performed by ANOVA and Pearson's correlation tests. Results: The results show the functional variability of children CP in different severity levels of motor disfunction This variation was observed in the areas of mobility, self-care and social function. The results also showed a strong correlation between the domains mobility and self-care, mobility and social function. Conclusions: The variability shown by the children with CP, suggests the use of PEDI and GMFCS as this association appears to increase the understanding of how the gross motor functions are related to activities of daily living, describing the best commitments and their degree of impact on functional activities. This correlation demonstrates how mobility is crucial to evaluate the performance and guide the therapeutic practice, to develop the children´s potencial, and guide the caregiver in stimulation
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This work describes the study and the implementation of the speed control for a three-phase induction motor of 1,1 kW and 4 poles using the neural rotor flux estimation. The vector speed control operates together with the winding currents controller of the stator phasis. The neural flux estimation applied to the vector speed controls has the objective of compensating the parameter dependences of the conventional estimators in relation to the parameter machine s variations due to the temperature increases or due to the rotor magnetic saturation. The implemented control system allows a direct comparison between the respective responses of the speed controls to the machine oriented by the neural rotor flux estimator in relation to the conventional flux estimator. All the system control is executed by a program developed in the ANSI C language. The main DSP recources used by the system are, respectively, the Analog/Digital channels converters, the PWM outputs and the parallel and RS-232 serial interfaces, which are responsible, respectively, by the DSP programming and the data capture through the supervisory system
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This dissertation dea1s with the active magnetic suspension controI system of an induction bearingIess motor configured with split windings. It analyses a dynamic modeI for the radial magnetic forces actuating on the rotor. From that, it proposes a new approach for the composition of the currents imposed to the machine's stator. It shows the tests accomplished with a prototype, proving the usefulness of the new actuating structure for the radial positioning controI. Finnaly, it points out the importance of adapting this structure to well-known rotational controI techniques, continuing this kind of equipment research, which is carried out at Federal University of Rio Grande do Norte since 2000
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The present work is based on the applied bilinear predictive control applied to an induction motor. As in particular case of the technique based on predictive control in nonlinem systems, these have desperted great interest, a time that present the advantage of being simpler than the non linear in general and most representative one than the linear one. One of the methods, adopted here, uses the linear model "quasi linear for step of time" based in Generalized Predictive Control. The modeling of the induction motor is made by the Vectorial control with orientation given for the indirect rotor. The system is formed by an induction motor of 3 cv with rotor in squirregate, set in motion for a group of benches of tests developed for this work, presented resulted for a variation of +5% in the value of set-point and for a variation of +10% and -10% in the value of the applied nominal load to the motor. The results prove a good efficiency of the predictive bilinear controllers, then compared with the linear cases
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The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant
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Neste trabalho, ajustou-se um modelo matemático para quantificar o efeito do rendimento do motor elétrico sobre os custos de um sistema de bombeamento para irrigação na estrutura tarifária de energia elétrica convencional e horo-sazonal verde, bem como calcular o tempo de recuperação do capital investido no equipamento de maior rendimento. em seguida, o mesmo foi aplicado a um sistema de irrigação tipo pivô central em duas opções de rendimento do motor elétrico: 92,6% (linha padrão) e 94,3% (linha alto rendimento), sendo que o custo de aquisição do primeiro correspondeu a 70% do segundo. A potência do motor elétrico era de 100 cv. Os resultados mostraram que o modelo permitiu avaliar se um motor de alto rendimento era viável economicamente em relação ao motor-padrão em cada estrutura tarifária. Nas duas estruturas tarifárias, o motor de alto rendimento não foi viável. Na tarifa horo-sazonal verde, somente seria viável se seu rendimento fosse 4,46% superior ao do motor-padrão. Na tarifa convencional, somente seria viável se o ganho de rendimento superasse 2,71%.