978 resultados para Simulated patients
Resumo:
Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.
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The evolution of entanglement in a 3-spin chain with nearest-neighbor Heisenberg-XY interactions for different initial states is investigated here. In an NMR experimental implementation, we generate multipartite entangled states starting from initial separable pseudo-pure states by simulating nearest-neighbor XY interactions in a 3-spin linear chain of nuclear spin qubits. For simulating XY interactions, we follow algebraic method of Zhang et al. Phys. Rev. A 72 (2005) 012331]. Bell state between end qubits has been generated by using only the unitary evolution of the XY Hamiltonian. For generating W-state and GHZ-state a single qubit rotation is applied on second and all the three qubits, respectively after the unitary evolution of the XY Hamiltonian.
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This paper shows how multidisciplinary research can help policy makers develop policies for sustainable agricultural water management interventions by supporting a dialogue between government departments that are in charge of different aspects of agricultural development. In the Jaldhaka Basin in West Bengal, India, a stakeholder dialogue helped identify potential water resource impacts and livelihood implications of an agricultural water management rural electrification scenario. Hydrologic modelling demonstrated that the expansion of irrigation is possible with only a localized effect on groundwater levels, but cascading effects such as declining soil fertility and negative impacts from agrochemicals will need to be addressed.
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Background: A better understanding of the quality of cellular immune responses directed against molecularly defined targets will guide the development of TB diagnostics and identification of molecularly defined, clinically relevant M.tb vaccine candidates. Methods: Recombinant proteins (n = 8) and peptide pools (n = 14) from M. tuberculosis (M.tb) targets were used to compare cellular immune responses defined by IFN-gamma and IL-17 production using a Whole Blood Assay (WBA) in a cohort of 148 individuals, i.e. patients with TB + (n = 38), TB- individuals with other pulmonary diseases (n = 81) and individuals exposed to TB without evidence of clinical TB (health care workers, n = 29). Results: M.tb antigens Rv2958c (glycosyltransferase), Rv2962c (mycolyltransferase), Rv1886c (Ag85B), Rv3804c (Ag85A), and the PPE family member Rv3347c were frequently recognized, defined by IFN-gamma production, in blood from healthy individuals exposed to M.tb (health care workers). A different recognition pattern was found for IL-17 production in blood from M.tb exposed individuals responding to TB10.4 (Rv0288), Ag85B (Rv1886c) and the PPE family members Rv0978c and Rv1917c. Conclusions: The pattern of immune target recognition is different in regard to IFN-gamma and IL-17 production to defined molecular M.tb targets in PBMCs from individuals frequently exposed to M.tb. The data represent the first mapping of cellular immune responses against M.tb targets in TB patients from Honduras.
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A composite of mesoporous carbon (MC) with poly(3,4-ethylenedioxythiophene) (PEDOT) is studied as catalyst support for platinum nanoparticles. The durability of commercial Pt/carbon and Pt/MC-PEDOT as cathode catalyst is investigated by invoking air-fuel boundary at the anode side so as to foster carbon corrosion at the cathode side of a polymer electrolyte fuel cell (PEFC). Pt/MC-PEDOT shows higher resistance to carbon corrosion in relation to Pt/C. Electrochemical techniques such as cyclic voltammetry (CV) and impedance measurements are used to evaluate the extent of degradation in the catalyst layer. It is surmised that the resistance of MC-PEDOT as catalyst support toward electrochemical oxidation makes Pt/MC-PEDOT a suitable and stable cathode catalyst for PEFCs.
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Damaged articulating joints can be repaired or replaced with synthetic biomaterials, which can release wear debris due to articulation, leading to the osteolysis. In a recent work, it has been shown that it is possible to achieve a better combination of flexural strength/fracture toughness as well as in vitro bioactivity and cytocompatibility properties in spark plasma sintered hydroxyapatite-titanium (HA-Ti) composites. Although hydroxyapatite and titanium are well documented for their good biocompatibility, nanosized hydroxyapatite (HA) and titanium (Ti) particles can cause severe toxicity to cells. In order to address this issue, fretting wear study of HA-Ti composites under dry and wet (1x SBF, supplemented with 5 g l(-1) bovine serum albumin (BSA)) condition was performed to assess the wear resistance as well as wear debris formation, in vitro. The experimental results reveal one order of magnitude lower wear rate for HA-10 wt% Ti (7.5 x 10(-5) mm(3) N-1 m(-1)) composite than monolithic HA (3.9 x 10(-4) mm(3) N-1 m(-1)) in simulated body fluid. The difference in the tribological properties has been analyzed in the light of phase assemblages and mechanical properties. Overall, the results suggest the potential use of HA-Ti composites over existing HA-based biocomposites in orthopedic as well as dental applications.
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Himalayan region is one of the most active seismic regions in the world and many researchers have highlighted the possibility of great seismic event in the near future due to seismic gap. Seismic hazard analysis and microzonation of highly populated places in the region are mandatory in a regional scale. Region specific Ground Motion Predictive Equation (GMPE) is an important input in the seismic hazard analysis for macro- and micro-zonation studies. Few GMPEs developed in India are based on the recorded data and are applicable for a particular range of magnitudes and distances. This paper focuses on the development of a new GMPE for the Himalayan region considering both the recorded and simulated earthquakes of moment magnitude 5.3-8.7. The Finite Fault simulation model has been used for the ground motion simulation considering region specific seismotectonic parameters from the past earthquakes and source models. Simulated acceleration time histories and response spectra are compared with available records. In the absence of a large number of recorded data, simulations have been performed at unavailable locations by adopting Apparent Stations concept. Earthquakes recorded up to 2007 have been used for the development of new GMPE and earthquakes records after 2007 are used to validate new GMPE. Proposed GMPE matched very well with recorded data and also with other highly ranked GMPEs developed elsewhere and applicable for the region. Comparison of response spectra also have shown good agreement with recorded earthquake data. Quantitative analysis of residuals for the proposed GMPE and region specific GMPEs to predict Nepal-India 2011 earthquake of Mw of 5.7 records values shows that the proposed GMPE predicts Peak ground acceleration and spectral acceleration for entire distance and period range with lower percent residual when compared to exiting region specific GMPEs. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
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Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.
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Simulated boundary potential data for Electrical Impedance Tomography (EIT) are generated by a MATLAB based EIT data generator and the resistivity reconstruction is evaluated with Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS). Circular domains containing subdomains as inhomogeneity are defined in MATLAB-based EIT data generator and the boundary data are calculated by a constant current simulation with opposite current injection (OCI) method. The resistivity images reconstructed for different boundary data sets and images are analyzed with image parameters to evaluate the reconstruction.
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Object. Insulin-like growth factor binding proteins (IGEBPs) have been implicated in the pathogenesis of glioma. In a previous study the authors demonstrated that IGFBP-3 is a novel glioblastoma biomarker associated with poor survival. Since signal transducer and activator of transcription 1 (STAT-1) has been shown to be regulated by IGFBP-3 during chondrogenesis and is a prosurvival and radioresistant molecule in different tumors, the aim in the present study was to explore the functional significance of IGFBP-3 in malignant glioma cells, to determine if STAT-1 is indeed regulated by IGFBP-3, and to study the potential of STAT-1 as a biomarker in glioblastoma. Methods. The functional significance of IGFBP-3 was investigated using the short hairpin (sh)RNA gene knockdown approach on U251MG cells. STAT-1 regulation by IGFBP-3 was tested on U251MG and U87MG cells by shRNA gene knockdown and exogenous treatment with recombinant IGFBP-3 protein. Subsequently, the expression of STAT-1 was analyzed with real-time reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC) in glioblastoma and control brain tissues. Survival analyses were done on a uniformly treated prospective cohort of adults with newly diagnosed glioblastoma (136 patients) using Kaplan-Meier and Cox regression models. Results. IGFBP-3 knockdown significantly impaired proliferation, motility, migration, and invasive capacity of U251MG cells in vitro (p < 0.005). Exogenous overexpression of IGFBP-3 in U251MG and U87MG cells demonstrated STAT-1 regulation. The mean transcript levels (by real-time RT-PCR) and the mean labeling index of STAT-1 (by IHC) were significantly higher in glioblastoma than in control brain tissues (p = 0.0239 and p < 0.001, respectively). Multivariate survival analysis revealed that STAT-1 protein expression (HR 1.015, p = 0.033, 95% CI 1.001-1.029) along with patient age (HR 1.025, p = 0.005, 95% CI 1.008-1.042) were significant predictors of shorter survival in patients with glioblastoma. Conclusions. IGFBP-3 influences tumor cell proliferation, migration, and invasion and regulates STAT-1 expression in malignant glioma cells. STAT-1 is overexpressed in human glioblastoma tissues and emerges as a novel prognostic biomarker.
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Solar radiation management (SRM) geoengineering has been proposed as a potential option to counteract climate change. We perform a set of idealized geoengineering simulations using Community Atmosphere Model version 3.1 developed at the National Center for Atmospheric Research to investigate the global hydrological implications of varying the latitudinal distribution of solar insolation reduction in SRM methods. To reduce the solar insolation we have prescribed sulfate aerosols in the stratosphere. The radiative forcing in the geoengineering simulations is the net forcing from a doubling of CO2 and the prescribed stratospheric aerosols. We find that for a fixed total mass of sulfate aerosols (12.6 Mt of SO4), relative to a uniform distribution which nearly offsets changes in global mean temperature from a doubling of CO2, global mean radiative forcing is larger when aerosol concentration is maximum at the poles leading to a warmer global mean climate and consequently an intensified hydrological cycle. Opposite changes are simulated when aerosol concentration is maximized in the tropics. We obtain a range of 1 K in global mean temperature and 3% in precipitation changes by varying the distribution pattern in our simulations: this range is about 50% of the climate change from a doubling of CO2. Hence, our study demonstrates that a range of global mean climate states, determined by the global mean radiative forcing, are possible for a fixed total amount of aerosols but with differing latitudinal distribution. However, it is important to note that this is an idealized study and thus not all important realistic climate processes are modeled.
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Patterned substrate growth has been a subject of much interest. In this work, characteristics of some statistical properties of a film grown on triangular and vicinal substrates using the Family model are studied. Substrate size and tilt angle are varied. It is found that the interface width and the correlation function increase as the roughness of the pattern is increased. The new scaling exponents are calculated and anomalous scaling is obtained. The transient persistence probability does not show a power law relation when the initial surface is sufficiently rough. The initial rough surface also causes multifractal behavior in the model.
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Solar geoengineering has been proposed as a potential means to counteract anthropogenic climate change, yet it is unknown how such climate intervention might affect the Earth's climate on the millennial time scale. Here we use the HadCM3L model to conduct a 1000year sunshade geoengineering simulation in which solar irradiance is uniformly reduced by 4% to approximately offset global mean warming from an abrupt quadrupling of atmospheric CO2. During the 1000year period, modeled global climate, including temperature, hydrological cycle, and ocean circulation of the high-CO2 simulation departs substantially from that of the control preindustrial simulation, whereas the climate of the geoengineering simulation remains much closer to that of the preindustrial state with little drift. The results of our study do not support the hypothesis that nonlinearities in the climate system would cause substantial drift in the climate system if solar geoengineering was to be deployed on the timescale of a millennium.