885 resultados para Respiration artificial


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Artificial viscosity in SPH-based computations of impact dynamics is a numerical artifice that helps stabilize spurious oscillations near the shock fronts and requires certain user-defined parameters. Improper choice of these parameters may lead to spurious entropy generation within the discretized system and make it over-dissipative. This is of particular concern in impact mechanics problems wherein the transient structural response may depend sensitively on the transfer of momentum and kinetic energy due to impact. In order to address this difficulty, an acceleration correction algorithm was proposed in Shaw and Reid (''Heuristic acceleration correction algorithm for use in SPH computations in impact mechanics'', Comput. Methods Appl. Mech. Engrg., 198, 3962-3974) and further rationalized in Shaw et al. (An Optimally Corrected Form of Acceleration Correction Algorithm within SPH-based Simulations of Solid Mechanics, submitted to Comput. Methods Appl. Mech. Engrg). It was shown that the acceleration correction algorithm removes spurious high frequency oscillations in the computed response whilst retaining the stabilizing characteristics of the artificial viscosity in the presence of shocks and layers with sharp gradients. In this paper, we aim at gathering further insights into the acceleration correction algorithm by further exploring its application to problems related to impact dynamics. The numerical evidence in this work thus establishes that, together with the acceleration correction algorithm, SPH can be used as an accurate and efficient tool in dynamic, inelastic structural mechanics. (C) 2011 Elsevier Ltd. All rights reserved.

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Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

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Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

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In this paper, a method for the tuning the membership functions of a Mamdani type Fuzzy Logic Controller (FLC) using the Clonal Selection Algorithm(CSA) a model of the Artificial Immune System(AIS) paradigm is examined. FLC's are designed for two problems, firstly the linear cart centering problem and secondly the highly nonlinear inverted pendulum problem. The FLC tuned by AIS is compared with FLC tuned by GA. In order to check the robustness of the designed PLC's white noise was added to the system, further, the masses of the cart and the length and mass of the pendulum are changed. The PLC's were also tested in the presence of faulty rules. Finally, Kruskal Wallis test was performed to compare the performance of the GA and AIS. An insight into the algorithms are also given by studying the effect of the important parameters of GA and AIS.

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This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

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Design and development of a piezoelectric polyvinylidene fluoride (PVDF) thin film based nasal sensor to monitor human respiration pattern (RP) from each nostril simultaneously is presented in this paper. Thin film based PVDF nasal sensor is designed in a cantilever beam configuration. Two cantilevers are mounted on a spectacle frame in such a way that the air flow from each nostril impinges on this sensor causing bending of the cantilever beams. Voltage signal produced due to air flow induced dynamic piezoelectric effect produce a respective RP. A group of 23 healthy awake human subjects are studied. The RP in terms of respiratory rate (RR) and Respiratory air-flow changes/alterations obtained from the developed PVDF nasal sensor are compared with RP obtained from respiratory inductance plethysmograph (RIP) device. The mean RR of the developed nasal sensor (19.65 +/- A 4.1) and the RIP (19.57 +/- A 4.1) are found to be almost same (difference not significant, p > 0.05) with the correlation coefficient 0.96, p < 0.0001. It was observed that any change/alterations in the pattern of RIP is followed by same amount of change/alterations in the pattern of PVDF nasal sensor with k = 0.815 indicating strong agreement between the PVDF nasal sensor and RIP respiratory air-flow pattern. The developed sensor is simple in design, non-invasive, patient friendly and hence shows promising routine clinical usage. The preliminary result shows that this new method can have various applications in respiratory monitoring and diagnosis.

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Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

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It is no exaggeration to state that the energy crisis is the most serious challenge that we face today. Among the strategies to gain access to reliable, renewable energy, the use of solar energy has clearly emerged as the most viable option. A promising direction in this context is artificial photosynthesis. In this article, we briefly describe the essential features of artificial photosynthesis in comparison with natural photosynthesis and point out the modest success that we have had in splitting water to produce oxygen and hydrogen, specially the latter.

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Effects of fluctuations in habitat temperature (18-30 degrees) on mitochondrial respiratory behavior and oxidative metabolic responses in the euryhaline ectotherm Scylla serrate are not fully understood. In the present study, effects of different temperatures ranging from 12 to 40 degrees C on glutamate and succinate mediated mitochondrial respiration, respiratory control ratio (RCR), ATP generation rate, ratio for the utilization of phosphate molecules per atomic oxygen consumption (P/O), levels of lipid peroxidation and H2O2 in isolated gill mitochondria of S. serrata are reported. The pattern of variation in the studied parameters was similar for the two substrates at different temperatures. The values recorded for RCR ( >= 3) and P/O ratio (1.4-2.7) at the temperature range of 15-25 degrees C were within the normal range reported for other animals (3-10 for RCR and 1.5-3 for P/O). Values for P/O ratio, ATP generation rate and RCR were highest at 18 degrees C when compared to the other assay temperatures. However, at low and high extreme temperatures, i.e. at 12 and 40 degrees C, states III and IV respiration rates were not clearly distinguishable from each other indicating that mitochondria were completely uncoupled. Positive correlations were noticed between temperature and the levels of both lipid peroxidation and H2O2. It is inferred that fluctuations on either side of ambient habitat temperature may adversely influence mitochondria respiration and oxidative metabolism in S. serrata. The results provide baseline data to understand the impacts of acute changes in temperature on ectotherms inhabiting estuarine or marine environments. (C) 2014 Elsevier Ltd. All rights reserved.

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Robotic surgical tools used in minimally invasive surgeries (MIS) require miniaturized and reliable actuators for precise positioning and control of the end-effector. Miniature pneumatic artificial muscles (MPAMs) are a good choice due to their inert nature, high force to weight ratio, and fast actuation. In this paper, we present the development of miniaturized braided pneumatic muscles with an outer diameter of similar to 1.2 mm, a high contraction ratio of about 18%, and capable of providing a pull force in excess of 4 N at a supply pressure of 0.8 MPa. We present the details of the developed experimental setup, experimental data on contraction and force as a function of applied pressure, and characterization of the MPAM. We also present a simple kinematics and experimental data based model of the braided pneumatic muscle and show that the model predicts contraction in length to within 20% of the measured value. Finally, a robust controller for the MPAMs is developed and validated with experiments and it is shown that the MPAMs have a time constant of similar to 10 ms thereby making them suitable for actuating endoscopic and robotic surgical tools.

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Conventional solids are prepared from building blocks that are conceptually no larger than a hundred atoms. While van der Waals and dipole-dipole interactions also influence the formation of these materials, stronger interactions, referred to as chemical bonds, play a more decisive role in determining the structures of most solids. Chemical bonds that hold such materials together are said to be ionic, covalent, metallic, dative, or otherwise a combination of these. Solids that utilize semiconductor nanocrystal quantum dots as building units have been demonstrated to exist; however, the interparticle forces in such materials are decidedly not chemical. Here we demonstrate the formation of charge transfer states in a binary quantum dot mixture. Charge is observed to reside in quantum confined states of one of the participating quantum dots. These interactions lead to materials that may be regarded as the nanoscale analog of an ionic solid. The process by which these materials form has interesting parallels to chemical reactions in conventional chemistry.

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Mycobacterium tuberculosis (Mtb) adaptation to hypoxia is considered crucial to its prolonged latent persistence in humans. Mtb lesions are known to contain physiologically heterogeneous microenvironments that bring about differential responses from bacteria. Here we exploit metabolic variability within biofilm cells to identify alternate respiratory polyketide quinones (PkQs) from both Mycobacterium smegmatis (Msmeg) and Mtb. PkQs are specifically expressed in biofilms and other oxygen-deficient niches to maintain cellular bioenergetics. Under such conditions, these metabolites function as mobile electron carriers in the respiratory electron transport chain. In the absence of PkQs, mycobacteria escape from the hypoxic core of biofilms and prefer oxygenrich conditions. Unlike the ubiquitous isoprenoid pathway for the biosynthesis of respiratory quinones, PkQs are produced by type III polyketide synthases using fatty acyl-CoA precursors. The biosynthetic pathway is conserved in several other bacterial genomes, and our study reveals a redox-balancing chemicocellular process in microbial physiology.

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El presente trabajo se realizó en la Empresa Genética Roberto Alvarado (Chiltepe), ubicada en la península de Chiltepe, en el departamento de Managua, con el objetivo de establecer la mejor forma de suministrar dietas liquidas, establecer la asociación entre los niveles de calostro con los comportamientos productivos de terneras bajo crianza artificial. Se emplearon 18 terneras de raza Holstein F., con un promedio de 40 Kg+- 8 kg de peso vivo, las que fueron distribuidas aleatoriamente en tres grupos asignándoles los siguientes tratamientos: T15 litros de leche entera/día (testigo) ; T2: 5 Litros de mezcla de calostro y leche/día (20:80) y T3: 5 Litros de mezcla de calostro y leche/día (40:60). Adicionalmente todos los tratamientos recibieron "adibitum", alimento solido a base de forraje Taiwán picado, heno de pasto estrella, agua y concentrado iniciador. El manejo de las terneras se realizó de manera similar a la utilizada en los centros de crianza de las empresas. Se efectuaron pasajes semanales individuales y se registró el consumo de concentrado. Se realizó análisis bromatológico de las dietas liquidas según metodología A.O.A.C. (1984), así como un análisis económico de las mismas. Al realizar ANDEVA para la variable GMD28, GMD49 y GMD70, se encontró para la primera que no existen diferencias (P<0.05) y para la dos últimas si existen diferencias significativas (P<0.05). El ANDECOVA (mínimo cuadrado realizado para la variable P28, utilizando la covariable PI mostró que no existen diferencias entre las dietas, y diferencias significativas (P<0.05) para la covariable. Para la variable Cons28, utilizando como variable el PI, se encontró diferencias significativas entre las dietas y no significativas para la variable concomitante. Al analizar la variable P49 usando como variable concomitante el P28, mostró diferencias estadísticamente significativas (P<0.05) tanto para las dietas como para la covariable. Para la variable P70, utilizando como covariable P49, se encontró que existen diferencias significativas para las dietas suministradas así como para la variable concomitante. Posteriormente al realizar prueba de separación de medidas con rangos múltiples utilizando test de Duncan, para las variables GMD14, GMD28, GMD49 y GMD70 se encontró el siguiente orden de mérito para las dietas: Calostro: Leche (40:60) a; Calostro: Leche (20:80)a, y Calostro: Leche (0:100) b. El análisis económico mostro que las dietas T3 y T2 tiene costos notablemente inferiores en relación al costo del T1. Estos análisis conllevan a establecer un orden decreciente del efecto de las dietas liquidas sobre la GMD y el PF según el siguiente esquema: T3 (40:60)>T2 (20:80)>T1 (0.100). Encontrando que la dieta más efectiva es la del T3.

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Este experimento se realizó en la Granja Experimental Porcina (G.E.P), Cofradía, Masaya, con 82 cerdas del cuarto parto, 30 servidas a través de inseminación artificial (I.A) y 52 cerdas por monta natural (M.N); iniciando en mayo de 1,995 hasta mayo de 1,996 con el objetivo de evaluar los parámetros reproductivos y económicos en ambos sistemas de monta. Los dos grupos de cerdas reproductoras estaban compuestos por las razas LANDRACE, YORKSHIRE y DUROC. Las variables evaluadas fueron: Tasa de concepción (T.C) y tasa de parición (T.P), números de crías por partos (N.C.P), peso vivo promedio del lechón en la camada al nacer (P.V.L.C), relación beneficio-costo (B-C). Los resultados finales comprobados al 5% de significancia estadísticas fueron: T.P en I.A con 56.66% menor que en M.N con 76.92%, en N.C.P para I.A con 7.06, menor que en M.N de 8.725, P.V.L.C en I.A de 1.85 kg, similar a 1.74 kg, en MN. Para la relación B-C en I.A fue de 0.53 córdobas y para M.N de 0.56 córdobas.