962 resultados para one-dimensional model,
Resumo:
This paper presents a novel variable decomposition approach for pose recovery of the distal locking holes using single calibrated fluoroscopic image. The problem is formulated as a model-based optimal fitting process, where the control variables are decomposed into two sets: (a) the angle between the nail axis and its projection on the imaging plane, and (b) the translation and rotation of the geometrical model of the distal locking hole around the nail axis. By using an iterative algorithm to find the optimal values of the latter set of variables for any given value of the former variable, we reduce the multiple-dimensional model-based optimal fitting problem to a one-dimensional search along a finite interval. We report the results of our in vitro experiments, which demonstrate that the accuracy of our approach is adequate for successful distal locking of intramedullary nails.
Resumo:
Interest in the study of magnetic/non-magnetic multilayered structures took a giant leap since Grünberg and his group established that the interlayer exchange coupling (IEC) is a function of the non-magnetic spacer width. This interest was further fuelled by the discovery of the phenomenal Giant Magnetoresistance (GMR) effect. In fact, in 2007 Albert Fert and Peter Grünberg were awarded the Nobel Prize in Physics for their contribution to the discovery of GMR. GMR is the key property that is being used in the read-head of the present day computer hard drive as it requires a high sensitivity in the detection of magnetic field. The recent increase in demand for device miniaturization encouraged researchers to look for GMR in nanoscale multilayered structures. In this context, one dimensional(1-D) multilayerd nanowire structure has shown tremendous promise as a viable candidate for ultra sensitive read head sensors. In fact, the phenomenal giant magnetoresistance(GMR) effect, which is the novel feature of the currently used multilayered thin film, has already been observed in multilayered nanowire systems at ambient temperature. Geometrical confinement of the supper lattice along the 2-dimensions (2-D) to construct the 1-D multilayered nanowire prohibits the minimization of magnetic interaction- offering a rich variety of magnetic properties in nanowire that can be exploited for novel functionality. In addition, introduction of non-magnetic spacer between the magnetic layers presents additional advantage in controlling magnetic properties via tuning the interlayer magnetic interaction. Despite of a large volume of theoretical works devoted towards the understanding of GMR and IEC in super lattice structures, limited theoretical calculations are reported in 1-D multilayered systems. Thus to gauge their potential application in new generation magneto-electronic devices, in this thesis, I have discussed the usage of first principles density functional theory (DFT) in predicting the equilibrium structure, stability as well as electronic and magnetic properties of one dimensional multilayered nanowires. Particularly, I have focused on the electronic and magnetic properties of Fe/Pt multilayered nanowire structures and the role of non-magnetic Pt spacer in modulating the magnetic properties of the wire. It is found that the average magnetic moment per atom in the nanowire increases monotonically with an ~1/(N(Fe)) dependance, where N(Fe) is the number of iron layers in the nanowire. A simple model based upon the interfacial structure is given to explain the 1/(N(Fe)) trend in magnetic moment obtained from the first principle calculations. A new mechanism, based upon spin flip with in the layer and multistep electron transfer between the layers, is proposed to elucidate the enhancement of magnetic moment of Iron atom at the Platinum interface. The calculated IEC in the Fe/Pt multilayered nanowire is found to switch sign as the width of the non-magnetic spacer varies. The competition among short and long range direct exchange and the super exchange has been found to play a key role for the non-monotonous sign in IEC depending upon the width of the Platinum spacer layer. The calculated magnetoresistance from Julliere's model also exhibit similar switching behavior as that of IEC. The universality of the behavior of exchange coupling has also been looked into by introducing different non-magnetic spacers like Palladium, Copper, Silver, and Gold in between magnetic Iron layers. The nature of hybridization between Fe and other non-magnetic spacer is found to dictate the inter layer magnetic interaction. For example, in Fe/Pd nanowire the d-p hybridization in two spacer layer case favors anti-ferromagnetic (AFM) configuration over ferromagnetic (FM) configuration. However, the hybridization between half-filled Fe(d) and filled Cu(p) state in Fe/Cu nanowire favors FM coupling in the 2-spacer system.
Resumo:
The seasonal appearance of a deep chlorophyll maximum (DCM) in Lake Superior is a striking phenomenon that is widely observed; however its mechanisms of formation and maintenance are not well understood. As this phenomenon may be the reflection of an ecological driver, or a driver itself, a lack of understanding its driving forces limits the ability to accurately predict and manage changes in this ecosystem. Key mechanisms generally associated with DCM dynamics (i.e. ecological, physiological and physical phenomena) are examined individually and in concert to establish their role. First the prevailing paradigm, “the DCM is a great place to live”, is analyzed through an integration of the results of laboratory experiments and field measurements. The analysis indicates that growth at this depth is severely restricted and thus not able to explain the full magnitude of this phenomenon. Additional contributing mechanisms like photoadaptation, settling and grazing are reviewed with a one-dimensional mathematical model of chlorophyll and particulate organic carbon. Settling has the strongest impact on the formation and maintenance of the DCM, transporting biomass to the metalimnion and resulting in the accumulation of algae, i.e. a peak in the particulate organic carbon profile. Subsequently, shade adaptation becomes manifest as a chlorophyll maximum deeper in the water column where light conditions particularly favor the process. Shade adaptation mediates the magnitude, shape and vertical position of the chlorophyll peak. Growth at DCM depth shows only a marginal contribution, while grazing has an adverse effect on the extent of the DCM. The observed separation of the carbon biomass and chlorophyll maximum should caution scientists to equate the DCM with a large nutrient pool that is available to higher trophic levels. The ecological significance of the DCM should not be separated from the underlying carbon dynamics. When evaluated in its entirety, the DCM becomes the projected image of a structure that remains elusive to measure but represents the foundation of all higher trophic levels. These results also offer guidance in examine ecosystem perturbations such as climate change. For example, warming would be expected to prolong the period of thermal stratification, extending the late summer period of suboptimal (phosphorus-limited) growth and attendant transport of phytoplankton to the metalimnion. This reduction in epilimnetic algal production would decrease the supply of algae to the metalimnion, possibly reducing the supply of prey to the grazer community. This work demonstrates the value of modeling to challenge and advance our understanding of ecosystem dynamics, steps vital to reliable testing of management alternatives.
Resumo:
Ethanol-gasoline fuel blends are increasingly being used in spark ignition (SI) engines due to continued growth in renewable fuels as part of a growing renewable portfolio standard (RPS). This leads to the need for a simple and accurate ethanol-gasoline blends combustion model that is applicable to one-dimensional engine simulation. A parametric combustion model has been developed, integrated into an engine simulation tool, and validated using SI engine experimental data. The parametric combustion model was built inside a user compound in GT-Power. In this model, selected burn durations were computed using correlations as functions of physically based non-dimensional groups that have been developed using the experimental engine database over a wide range of ethanol-gasoline blends, engine geometries, and operating conditions. A coefficient of variance (COV) of gross indicated mean effective pressure (IMEP) correlation was also added to the parametric combustion model. This correlation enables the cycle combustion variation modeling as a function of engine geometry and operating conditions. The computed burn durations were then used to fit single and double Wiebe functions. The single-Wiebe parametric combustion compound used the least squares method to compute the single-Wiebe parameters, while the double-Wiebe parametric combustion compound used an analytical solution to compute the double-Wiebe parameters. These compounds were then integrated into the engine model in GT-Power through the multi-Wiebe combustion template in which the values of Wiebe parameters (single-Wiebe or double-Wiebe) were sensed via RLT-dependence. The parametric combustion models were validated by overlaying the simulated pressure trace from GT-Power on to experimentally measured pressure traces. A thermodynamic engine model was also developed to study the effect of fuel blends, engine geometries and operating conditions on both the burn durations and COV of gross IMEP simulation results.
Resumo:
Since the advent of automobiles, alcohol has been considered a possible engine fuel1,2. With the recent increased concern about the high price of crude oil due to fluctuating supply and demand and environmental issues, interest in alcohol based fuels has increased2,3. However, using pure alcohols or blends with conventional fuels in high percentages requires changes to the engine and fuel system design2. This leads to the need for a simple and accurate conventional fuels-alcohol blends combustion models that can be used in developing parametric burn rate and knock combustion models for designing more efficient Spark Ignited (SI) engines. To contribute to this understanding, numerical simulations were performed to obtain detailed characteristics of Gasoline-Ethanol blends with respect to Laminar Flame Speed (LFS), autoignition and Flame-Wall interactions. The one-dimensional premixed flame code CHEMKIN® was applied to simulate the burning velocity and autoignition characteristics using the freely propagating model and closed homogeneous reactor model respectively. Computational Fluid Dynamics (CFD) was used to obtain detailed flow, temperature, and species fields for Flame-wall interactions. A semi-detailed validated chemical kinetic model for a gasoline surrogate fuel developed by Andrae and Head4 was used for the study of LFS and Autoignition. For the quenching study, a skeletal chemical kinetic mechanism of gasoline surrogate, having 50 species and 174 reactions was used. The surrogate fuel was defined as a mixture of pure n-heptane, isooctane, and toluene. For LFS study, the ethanol volume fraction was varied from 0 to 85%, initial pressure from 4 to 8 bar, initial temperature from 300 to 900K, and dilution from 0 to 32%. Whereas for Autoignition study, the ethanol volume fraction was varied between 0 to 85%, initial pressure was varied between 20 to 60 bar, initial temperature was varied between 800 to 1200K, and the dilution was varied between 0 to 32% at equivalence ratios of 0.5, 1.0 and 1.5 to represent the in-cylinder conditions of a SI engine. For quenching study three Ethanol blends, namely E0, E25 and E85 are described in detail at an initial pressure of 8 atm and 17 atm. Initial wall temperature was taken to be 400 K. Quenching thicknesses and heat fluxes to the wall were computed. The laminar flame speed was found to increase with ethanol concentration and temperature but decrease with pressure and dilution. The autoignition time was found to increase with ethanol concentration at lower temperatures but was found to decrease marginally at higher temperatures. The autoignition time was also found to decrease with pressure and equivalence ratio but increase with dilution. The average quenching thickness was found to decrease with an increase in Ethanol concentration in the blend. Heat flux to the wall increased with increase in ethanol percentage in the blend and at higher initial pressures. Whereas the wall heat flux decreased with an increase in dilution. Unburned Hydrocarbon (UHC) and CO % was also found to decrease with ethanol concentration in the blend.
Resumo:
The CopA copper ATPase of Enterococcus hirae belongs to the family of heavy metal pumping CPx-type ATPases and shares 43% sequence similarity with the human Menkes and Wilson copper ATPases. Due to a lack of suitable protein crystals, only partial three-dimensional structures have so far been obtained for this family of ion pumps. We present a structural model of CopA derived by combining topological information obtained by intramolecular cross-linking with molecular modeling. Purified CopA was cross-linked with different bivalent reagents, followed by tryptic digestion and identification of cross-linked peptides by mass spectrometry. The structural proximity of tryptic fragments provided information about the structural arrangement of the hydrophilic protein domains, which was integrated into a three-dimensional model of CopA. Comparative modeling of CopA was guided by the sequence similarity to the calcium ATPase of the sarcoplasmic reticulum, Serca1, for which detailed structures are available. In addition, known partial structures of CPx-ATPase homologous to CopA were used as modeling templates. A docking approach was used to predict the orientation of the heavy metal binding domain of CopA relative to the core structure, which was verified by distance constraints derived from cross-links. The overall structural model of CopA resembles the Serca1 structure, but reveals distinctive features of CPx-type ATPases. A prominent feature is the positioning of the heavy metal binding domain. It features an orientation of the Cu binding ligands which is appropriate for the interaction with Cu-loaded metallochaperones in solution. Moreover, a novel model of the architecture of the intramembranous Cu binding sites could be derived.
Resumo:
Plant diversity has been shown to influence the water cycle of forest ecosystems by differences in water consumption and the associated effects on groundwater recharge. However, the effects of biodiversity on soil water fluxes remain poorly understood for native tree species plantations in the tropics. Therefore, we estimated soil water fluxes and assessed the effects of tree species and diversity on these fluxes in an experimental native tree species plantation in Sardinilla (Panama). The study was conducted during the wet season 2008 on plots of monocultures and mixtures of three or six tree species. Rainfall and soil water content were measured and evapotranspiration was estimated with the Penman-Monteith equation. Soil water fluxes were estimated using a simple soil water budget model considering water input, output, and soil water and groundwater storage changes and in addition, were simulated using the physically based one-dimensional water flow model Hydrus-1D. In general, the Hydrus simulation did not reflect the observed pressure heads, in that modeled pressure heads were higher compared to measured ones. On the other hand, the results of the water balance equation (WBE) reproduced observed water use patterns well. In monocultures, the downward fluxes through the 200 cm-depth plane were highest below Hura crepitans (6.13 mm day−1) and lowest below Luehea seemannii (5.18 mm day−1). The average seepage rate in monocultures (±SE) was 5.66 ± 0.18 mm day−1, and therefore, significantly higher than below six-species mixtures (5.49 ± 0.04 mm day−1) according to overyielding analyses. The three-species mixtures had an average seepage rate of 5.63 ± 0.12 mm day−1 and their values did not differ significantly from the average values of the corresponding species in monocultures. Seepage rates were driven by the transpiration of the varying biomass among the plots (r = 0.61, p = 0.017). Thus, a mixture of trees with different growth rates resulted in moderate seepage rates compared to monocultures of either fast growing or slow growing tree species. Our results demonstrate that tree-species specific biomass production and tree diversity are important controls of seepage rates in the Sardinilla plantation during the wet season.
Resumo:
The apicomplexan parasite, Theileria annulata, is the causative agent of tropical theileriosis, a devastating lymphoproliferative disease of cattle. The schizont stage transforms bovine leukocytes and provides an intriguing model to study host/pathogen interactions. The genome of T. annulata has been sequenced and transcriptomic data are rapidly accumulating. In contrast, little is known about the proteome of the schizont, the pathogenic, transforming life cycle stage of the parasite. Using one-dimensional (1-D) gel LC-MS/MS, a proteomic analysis of purified T. annulata schizonts was carried out. In whole parasite lysates, 645 proteins were identified. Proteins with transmembrane domains (TMDs) were under-represented and no proteins with more than four TMDs could be detected. To tackle this problem, Triton X-114 treatment was applied, which facilitates the extraction of membrane proteins, followed by 1-D gel LC-MS/MS. This resulted in the identification of an additional 153 proteins. Half of those had one or more TMD and 30 proteins with more than four TMDs were identified. This demonstrates that Triton X-114 treatment can provide a valuable additional tool for the identification of new membrane proteins in proteomic studies. With two exceptions, all proteins involved in glycolysis and the citric acid cycle were identified. For at least 29% of identified proteins, the corresponding transcripts were not present in the existing expressed sequence tag databases. The proteomics data were integrated into the publicly accessible database resource at EuPathDB (www.eupathdb.org) so that mass spectrometry-based protein expression evidence for T. annulata can be queried alongside transcriptional and other genomics data available for these parasites.
Resumo:
During the last decades, the narcissistic personality inventory (npi) was the most widely used questionnaire to measure narcissism as a personality trait. But the npi assesses grandiose narcissism only, while recent discussions emphasize the existence of vulnerable narcissism. The pathological narcissism inventory (pni, pincus et al., 2009) is a new questionnaire assessing these different aspects of narcissism. However, with 54 items on seven subscales, the pni is quite long to serve as a screening tool for narcissistic traits. We therefore developed a short form to facilitate its application in research and practice. Even though the pni covers different symptoms of narcissism, they are all expressions of the same underlying construct. We therefore used the rasch model to guide the item selection. Method and results: a sample of 1837 participants (67.5% female, mean age 26.8 years) was used to choose the items for the short form. Two criteria were adopted: all aspects, represented by the seven subscales in the original, should be retained, and items should be rasch homogenous. In a step-by-step procedure we excluded items successively until reaching a homogenous pool of 22 items. All remaining items had satisfactory fit indices and fitstatistics for the model were good. characteristics of the resulting short form were tested using a new independent validation sample (n=104, mean age = 32.8, 45% female). Correlations of the short pni with different validation measures were comparable to the correlations obtained with the original form, indicating that the two forms were equivalent. Conclusion: the resulting one-dimensional measure can be used as a screening questionnaire for pathological narcissism. The rasch homogeneity facilitates the comparison of narcissism scores among a variety of samples.
Resumo:
PURPOSE Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.
Resumo:
Modern mixed alluvial-bedrock channels in mountainous areas provide natural laboratories for understanding the time scales at which coarse-grained material has been entrained and transported from their sources to the adjacent sedimentary sink, where these deposits are preserved as conglomerates. This article assesses the shear stress conditions needed for the entrainment of the coarse-bed particles in the Glogn River that drains the 400 km2 Val Lumnezia basin, eastern Swiss Alps. In addition, quantitative data are presented on sediment transport patterns in this stream. The longitudinal stream profile of this river is characterized by three ca 500 m long knickzones where channel gradients range from 0·02 to 0·2 m m−1, and where the valley bottom confined into a <10 m wide gorge. Downstream of these knickzones, the stream is flat with gradients <0·01 m m−1 and widths ≥30 m. Measurements of the grain-size distribution along the trunk stream yield a mean D84 value of ca 270 mm, whereas the mean D50 is ca 100 mm. The consequences of the channel morphology and the grain-size distribution for the time scales of sediment transport were explored by using a one-dimensional step-backwater hydraulic model (Hydrologic Engineering Centre – River Analysis System). The results reveal that, along the entire trunk stream, a two to 10 year return period flood event is capable of mobilizing both the D50 and D84 fractions where the Shields stress exceeds the critical Shields stress for the initiation of particle motion. These return periods, however, varied substantially depending on the channel geometry and the pebble/boulder size distribution of the supplied material. Accordingly, the stream exhibits a highly dynamic boulder cover behaviour. It is likely that these time scales might also have been at work when coarse-grained conglomerates were constructed in the geological past.
Resumo:
Safe disposal of toxic wastes in geologic formations requires minimal water and gas movement in the vicinity of storage areas, Ventilation of repository tunnels or caverns built in solid rock can desaturate the near field up to a distance of meters from the rock surface, even when the surrounding geological formation is saturated and under hydrostatic pressures. A tunnel segment at the Grimsel test site located in the Aare granite of the Bernese Alps (central Switzerland) has been subjected to a resaturation and, subsequently, to a controlled desaturation, Using thermocouple psychrometers (TP) and time domain reflectometry (TDR), the water potentials psi and water contents theta were measured within the unsaturated granodiorite matrix near the tunnel wall at depths between 0 and 160 cm. During the resaturation the water potentials in the first 30 cm from the rock surface changed within weeks from values of less than -1.5 MPa to near saturation. They returned to the negative initial values during desaturation, The dynamics of this saturation-desaturation regime could be monitored very sensitively using the thermocouple psychrometers, The TDR measurements indicated that water contents changed dose to the surface, but at deeper installation depths the observed changes were within the experimental noise. The field-measured data of the desaturation cycle were used to test the predictive capabilities of the hydraulic parameter functions that were derived from the water retention characteristics psi(theta) determined in the laboratory. A depth-invariant saturated hydraulic conductivity k(s) = 3.0 x 10(-11) m s(-1) was estimated from the psi(t) data at all measurement depths, using the one-dimensional, unsaturated water flow and transport model HYDRUS Vogel er al., 1996, For individual measurement depths, the estimated k(s) varied between 9.8 x 10(-12) and 6.1 x 10(-11) The fitted k(s) values fell within the range of previously estimated k(s) for this location and led to a satisfactory description of the data, even though the model did not include transport of water vapor.
Resumo:
People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.
Resumo:
A three-dimensional model has been proposed that uses Monte Carlo and fast Fourier transform convolution techniques to calculate the dose distribution from a fast neutron beam. This method transports scattered neutrons and photons in the forward, lateral, and backward directions and protons, electrons, and positrons in the forward and lateral directions by convolving energy spread kernels with initial interaction available energy distributions. The primary neutron and photon spectrums have been derived from narrow beam attenuation measurements. The positions and strengths of the effective primary neutron, scattered neutron, and photon sources have been derived from dual ion chamber measurements. The size of the effective primary neutron source has been measured using a copper activation technique. Heterogeneous tissue calculations require a weighted sum of two convolutions for each component since the kernels must be invariant for FFT convolution. Comparisons between calculations and measurements were performed for several water and heterogeneous phantom geometries. ^
Resumo:
Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.