951 resultados para Complex networks. Magnetic system. Metropolis
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OBJECTIVE: The voluntary control of micturition is believed to be integrated by complex interactions among the brainstem, subcortical areas and cortical areas. Several brain imaging studies using positron emission tomography (PET) have demonstrated that frontal brain areas, the limbic system, the pons and the premotor cortical areas were involved. However, the cortical and subcortical brain areas have not yet been precisely identified and their exact function is not yet completely understood. MATERIALS AND METHODS: This study used functional magnetic resonance imaging (fMRI) to compare brain activity during passive filling and emptying of the bladder. A cathetherism of the bladder was performed in seven healthy subjects (one man and six right-handed women). During scanning, the bladder was alternatively filled and emptied at a constant rate with bladder rincing solution. RESULTS: Comparison between passive filling of the bladder and emptying of the bladder showed an increased brain activity in the right inferior frontal gyrus, cerebellum, symmetrically in the operculum and mesial frontal. Subcortical areas were not evaluated. CONCLUSIONS: Our results suggest that several cortical brain areas are involved in the regulation of micturition.
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The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.
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Data on the evolution of geomagnetic paleointensity are crucial for understanding the geodynamo and Earth’s thermal history. Although basaltic flows are preferred for paleointensity experiments, quickly cooled mafic dykes have also been used. However, the paleointensity values obtained from the dykes are systematically lower than those from lava flows. This bias may originate from the difference in cooling histories and resultant magnetic mineralogies of extrusive and intrusive rocks. To explore this hypothesis, the magnetic mineralogy of two feeder dyke-lave flow systems, from Thunder Bay (Canada) and La Cienega (New-Mexico), has been studied using magnetic and microscopy methods. Within each system, the flow and dyke show different stages of deuteric oxidation of titanomagnetite, but the oxidation stages also differ between the two systems. It is concluded that the tested hypothesis is viable, but the relationships between the magnetic and mineralogical properties of flows and dykes are complex and need a further investigation.
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The goal of this work is to develop a magnetic-based passive and wireless pressure sensor for use in biomedical applications. Structurally, the pressure sensor, referred to as the magneto-harmonic pressure sensor, is composed of two magnetic elements: a magnetically-soft material acts as a sensing element, and a magnetically hard material acts as a biasing element. Both elements are embedded within a rigid sensor body and sealed with an elastomer pressure membrane. Upon excitation of an externally applied AC magnetic field, the sensing element is capable of producing higher-order magnetic signature that is able to be remotely detected with an external receiving coil. When exposed to environment with changing ambient pressure, the elastomer pressure membrane of pressure sensor is deflected depending on the surrounding pressure. The deflection of elastomer membrane changes the separation distance between the sensing and biasing elements. As a result, the higher-order harmonic signal emitted by the magnetically-soft sensing element is shifted, allowing detection of pressure change by determining the extent of the harmonic shifting. The passive and wireless nature of the sensor is enabled with an external excitation and receiving system consisting of an excitation coil and a receiving coil. These unique characteristics made the sensor suitable to be used for continuous and long-term pressure monitoring, particularly useful for biomedical applications which often require frequent surveillance. In this work, abdominal aortic aneurysm is selected as the disease model for evaluation the performance of pressure sensor and system. Animal model, with subcutaneous sensor implantation in mice, was conducted to demonstrate the efficacy and feasibility of pressure sensor in biological environment.
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Powder metallurgy is a branch of metallurgy which produces metallic compacts in their final forms by means of pressure and heat-treatment from the powders. The products of powder metallurgy are being used in our daily lives quite often. For example, the tungsten wires in the electric bulbs to the silver-tin fillings of our teeth.
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Wireless sensor network is an emerging research topic due to its vast and ever-growing applications. Wireless sensor networks are made up of small nodes whose main goal is to monitor, compute and transmit data. The nodes are basically made up of low powered microcontrollers, wireless transceiver chips, sensors to monitor their environment and a power source. The applications of wireless sensor networks range from basic household applications, such as health monitoring, appliance control and security to military application, such as intruder detection. The wide spread application of wireless sensor networks has brought to light many research issues such as battery efficiency, unreliable routing protocols due to node failures, localization issues and security vulnerabilities. This report will describe the hardware development of a fault tolerant routing protocol for railroad pedestrian warning system. The protocol implemented is a peer to peer multi-hop TDMA based protocol for nodes arranged in a linear zigzag chain arrangement. The basic working of the protocol was derived from Wireless Architecture for Hard Real-Time Embedded Networks (WAHREN).
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Decentralised controls offer advantages for the implementation as well as the operation of controls of steady conveyors. Such concepts are mainly based on RFID. Due to the reduced expense for appliances and software, however, the plant behaviour cannot be determined as accurately as in centrally controlled systems. This article describes a simulation-based method by which the performances of these two control concepts can easily be evaluated in order to determine the suitability of the decentralised concept.
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OBJECTIVES This study sought to evaluate the relationship between fibrosis imaged by delayed-enhancement (DE) magnetic resonance imaging (MRI) and atrial electrograms (Egms) in persistent atrial fibrillation (AF). BACKGROUND Atrial fractionated Egms are strongly related to slow anisotropic conduction. Their relationship to atrial fibrosis has not yet been investigated. METHODS Atrial high-resolution MRI of 18 patients with persistent AF (11 long-lasting persistent AF) was registered with mapping geometry (NavX electro-anatomical system (version 8.0, St. Jude Medical, St. Paul, Minnesota)). DE areas were categorized as dense or patchy, depending on their DE content. Left atrial Egms during AF were acquired using a high-density, 20-pole catheter (514 ± 77 sites/map). Fractionation, organization/regularity, local mean cycle length (CL), and voltage were analyzed with regard to DE. RESULTS Patients with long-lasting persistent versus persistent AF had larger left atrial (LA) surface area (134 ± 38 cm(2) vs. 98 ± 9 cm(2), p = 0.02), a higher amount of atrial DE (70 ± 16 cm(2) vs. 49 ± 10 cm(2), p = 0.01), more complex fractionated atrial Egm (CFAE) extent (54 ± 16 cm(2) vs. 28 ± 15 cm(2), p = 0.02), and a shorter baseline AF CL (147 ± 10 ms vs. 182 ± 14 ms, p = 0.01). Continuous CFAE (CFEmean [NavX algorithm that quantifies Egm fractionation] <80 ms) occupied 38 ± 19% of total LA surface area. Dense DE was detected at the left posterior left atrium. In contrast, the right posterior left atrium contained predominantly patchy DE. Most CFAE (48 ± 14%) occurred at non-DE LA sites, followed by 41 ± 12% CFAE at patchy DE and 11 ± 6% at dense DE regions (p = 0.005 and p = 0.008, respectively); 19 ± 6% CFAE sites occurred at border zones of dense DE. Egms were less fractionated, with longer CL and lower voltage at dense DE versus non-DE regions: CFEmean: 97 ms versus 76 ms, p < 0.0001; local CL: 153 ms versus 143 ms, p < 0.0001; mean voltage: 0.63 mV versus 0.86 mV, p < 0.0001. CONCLUSIONS Atrial fibrosis as defined by DE MRI is associated with slower and more organized electrical activity but with lower voltage than healthy atrial areas. Ninety percent of continuous CFAE sites occur at non-DE and patchy DE LA sites. These findings are important when choosing the ablation strategy in persistent AF.
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This work addresses the evolution of an artificial neural network (ANN) to assist in the problem of indoor robotic localization. We investigate the design and building of an autonomous localization system based on information gathered from wireless networks (WN). The article focuses on the evolved ANN, which provides the position of a robot in a space, as in a Cartesian coordinate system, corroborating with the evolutionary robotic research area and showing its practical viability. The proposed system was tested in several experiments, evaluating not only the impact of different evolutionary computation parameters but also the role of the transfer functions on the evolution of the ANN. Results show that slight variations in the parameters lead to significant differences on the evolution process and, therefore, in the accuracy of the robot position.
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The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.
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Three new coordination polymers [M(Pht)(1-MeIm)2]n (where M=Cu (1), Zn (2), Co (3); Pht2−=dianion of o-phthalic acid; 1-MeIm=1-methylimidazole) and two compounds [M(1-MeIm)6](HPht)2 · 2H2O (M=Co (4), Ni (5)) have been synthesized and characterized by X-ray crystallography. The structures of 1–3 (2 is isostructural to 3) consist of [M(1-MeIm)2] building units connected by 1,6-bridging phthalate ions to form infinite chains. In complex 1, each copper(II) center adopts a square coordination mode of N2O2 type by two O atoms from different phthalate ions and two N atoms of 1-MeIm, whereas in 3 two independent metal atoms are tetrahedrally (N2O2) coordinated to a pair of Pht ligands and a pair of 1-MeIm molecules. There are only van der Waals interactions between the chains in 1, while the three-dimensional network in 3 is assembled by C–H⋯O contacts. In contrast to polymers 1–3 the structures of 4 and 5 (complexes are also isostructural) are made up of the [M(1-MeIm)6]2+ cation, two hydrogen phthalate anions (HPht−) and two H2O solvate molecules. The coordination around each metal(II) atom is octahedral with six nitrogen atoms of 1-MeIm. Extended hydrogen bonding networks embracing the solvate water molecules and a phthalate residue as well as the weak C–H⋯O interactions stabilize the three-dimensional structures. Magnetic studies clearly show that the magnetic ions do not interact with each other. Furthermore, in compound 4 we have another example of a highly anisotropic Co2+ ion with a rhombic g-tensor and large zero-field-splitting. The complexes were also characterized by IR and 1H NMR spectroscopy, thermogravimetric analysis, and all data are discussed in the terms of known structures.
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The numerical simulations of the magnetic properties of extended three-dimensional networks containing M(II) ions with an S = 5/2 ground-state spin have been carried out within the framework of the isotropic Heisenberg model. Analytical expressions fitting the numerical simulations for the primitive cubic, diamond, together with (10−3) cubic networks have all been derived. With these empirical formulas in hands, we can now extract the interaction between the magnetic ions from the experimental data for these networks. In the case of the primitive cubic network, these expressions are directly compared with those from the high-temperature expansions of the partition function. A fit of the experimental data for three complexes, namely [(N(CH3)4][Mn(N3)] 1, [Mn(CN4)]n 2, and [FeII(bipy)3][MnII2(ox)3] 3, has been carried out. The best fits were those obtained using the following parameters, J = −3.5 cm-1, g = 2.01 (1); J = −8.3 cm-1, g = 1.95 (2); and J = −2.0 cm-1, g = 1.95 (3).
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PURPOSE Assessment of the cerebral blood flow (CBF) is crucial in the evaluation of patients with steno-occlusive diseases of the arteries supplying the brain for prediction of stroke risk. Quantitative phase contrast magnetic resonance angiography (PC-MRA) can be utilised for noninvasive quantification of CBF. The aim of this study was to validate in-vivo PC-MRA data by comparing them with colour-coded duplex (CCD) sonography in patients with cerebrovascular disease. METHODS AND MATERIALS We examined 24 consecutive patients (mean age 63 years) with stenosis of arteries supplying the brain using PC-MRA and CCD. Velocities were measured in a total of 209 stenotic and healthy arterial segments (110 extra- and 99 intracranial). RESULTS Moderate to good correlation of velocity measurements between both techniques was observed in all six extracranial and five out of seven intracranial segments (p <0.05). Velocities measured with CCD sonography were generally higher than those obtained by PC-MRA. Reversal of flow direction was detected consistently with both methods. CONCLUSION PC-MRA represents a robust, standardised magnetic resonance imaging technique for blood flow measurements within a reasonable acquisition time, potentially evolving as valuable work-up tool for more precise patient stratification for revascularisation therapy. PC-MRA overcomes relevant weaknesses of CCD in being not operator-dependent and not relying on a bone window to assess the intracranial arteries.