998 resultados para cortical modeling
Resumo:
One of existing strategies to engineer active antibody is to link VH and VL domains via a linker peptide. How the composition, length, and conformation of the linker affect antibody activity, however, remains poorly understood. In this study, a dual approach that coordinates molecule modeling, biological measurements, and affinity evaluation was developed to quantify the binding activity of a novel stable miniaturized anti-CD20 antibody or singlechain fragment variable (scFv) with a linker peptide. Upon computer-guided homology modeling, distance geometry analysis, and molecular superimposition and optimization, three new linker peptides PT1, PT2, and PT3 with respective 7, 10, and 15 residues were proposed and three engineered antibodies were then constructed by linking the cloned VH and VL domains and fusing to a derivative of human IgG1. The binding stability and activity of scFv-Fc chimera to CD20 antigen was quantified using a micropipette adhesion frequency assay and a Scatchard analysis. Our data indicated that the binding affinity was similar for the chimera with PT2 or PT3 and ~24-fold higher than that for the chimera with PT1, supporting theoretical predictions in molecular modeling. These results further the understanding in the impact of linker peptide on antibody structure and activity.
Resumo:
Unlike most previous studies on the transverse vortex-induced vibration(VIV) of a cylinder mainly under the wallfree condition (Williamson & Govardhan,2004),this paper experimentally investigates the vortex-induced vibration of a cylinder with two degrees of freedom near a rigid wall exposed to steady flow.The amplitude and frequency responses of the cylinder are discussed.The lee wake flow patterns of the cylinder undergoing VIV were visualized by employing the hydrogen bubble technique.The effects of the gap-to-diameter ratio (e0/D) and the mass ratio on the vibration amplitude and frequency are analyzed.Comparisons of VIV response of the cylinder are made between one degree (only transverse) and two degrees of freedom (streamwise and transverse) and those between the present study and previous ones.The experimental observation indicates that there are two types of streamwise vibration,i.e.the first streamwise vibration (FSV) with small amplitude and the second streamwise vibration (SSV) which coexists with transverse vibration.The vortex shedding pattem for the FSV is approximately symmetric and that for the SSV is alternate.The first streamwise vibration tends to disappear with the decrease of e0/D.For the case of large gap-to-diameter ratios (e.g.e0/D = 0.54~1.58),the maximum amplitudes of the second streamwise vibration and transverse one increase with the increasing gapto-diameter ratio.But for the case of small gap-to-diameter ratios (e.g.e0/D = 0.16,0.23),the vibration amplitude of the cylinder increases slowly at the initial stage (i.e.at small reduced velocity V,),and across the maximum amplitude it decreases quickly at the last stage (i.e.at large Vr).Within the range ofthe examined small mass ratio (m<4),both streamwise and transverse vibration amplitude of the cylinder decrease with the increase of mass ratio for the fixed value of V,.The vibration range (in terms of Vr ) tends to widen with the decrease of the mass ratio.In the second streamwise vibration region,the vibration frequency of the cylinder with a small mass ratio (e.g.mx = 1.44) undergoes a jump at a certain Vr,.The maximum amplitudes of the transverse vibration for two-degree-of-freedom case is larger than that for one-degree-of-freedom case,but the transverse vibration frequency of the cylinder with two degrees of freedom is lower than that with one degree of freedom (transverse).
Resumo:
Internal waves are an important factor in the design of drill operations and production in deep water, because the waves have very large amplitude and may induce large horizontal velocity. How the internal waves occur and propagate over benthal terrain is of great concern for ocean engineers. In the present paper, we have formulated a mathematical model of internal wave propagation in a two-layer deep water, which involves the effects of friction, dissipation and shoaling, and is capable of manifesting the variation of the amplitude and the velocity pattern. After calibration by field data measured at the Continental Slope in the Northern South China Sea, we have applied the model to the South China Sea, investigating the westward propagation of internal waves from the Luzon Strait, where internal waves originate due to the interaction of benthal ridge and tides. We find that the internal wave induced velocity profile is obviously characterized by the opposite flow below and above the pycnocline, which results in a strong shear, threatening safety of ocean structures, such as mooring system of oil platform, risers, etc. When internal waves propagate westwards, the amplitude attenuates due to the effects of friction and dissipation. The preliminary results show that the amplitude is likely to become half of its initial value at Luzon Strait when the internal waves propagate about 400 kilometers westwards.
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The prediction and estimate of water and soil loss is fundamental important for understanding the effect of the spatial heterogeneity of underlying surfaces and preventing ecological environment deterioration. In this paper, a dynamic model of runoff and sediment yield in small watersheds is established. The proposed model includes three components: runoff generation caused by rainfall, soil erosion on hillslopes by overland flow, and runoff concentration and sediment transport on watersheds. Applying the proposed model, the runoff and sediment yield processes in a typical catchment on the loess plateau was estimated, which exhibited a good agreement between predicted results and observation.
Resumo:
Development pressure throughout the coastal areas of the United States continues to build, particularly in the southeast (Allen and Lu 2003, Crossett et al. 2004). It is well known that development alters watershed hydrology: as land becomes covered with surfaces impervious to rain, water is redirected from groundwater recharge and evapotranspiration to stormwater runoff, and as the area of impervious cover increases, so does the volume and rate of runoff (Schueler 1994, Corbett et al. 1997). Pollutants accumulate on impervious surfaces, and the increased runoff with urbanization is a leading cause of nonpoint source pollution (USEPA 2002). Sediment, chemicals, bacteria, viruses, and other pollutants are carried into receiving water bodies, resulting in degraded water quality (Holland et al. 2004, Sanger et al. 2008). (PDF contains 5 pages)
Resumo:
The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.
It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.
The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.
Resumo:
The temporal structure of neuronal spike trains in the visual cortex can provide detailed information about the stimulus and about the neuronal implementation of visual processing. Spike trains recorded from the macaque motion area MT in previous studies (Newsome et al., 1989a; Britten et al., 1992; Zohary et al., 1994) are analyzed here in the context of the dynamic random dot stimulus which was used to evoke them. If the stimulus is incoherent, the spike trains can be highly modulated and precisely locked in time to the stimulus. In contrast, the coherent motion stimulus creates little or no temporal modulation and allows us to study patterns in the spike train that may be intrinsic to the cortical circuitry in area MT. Long gaps in the spike train evoked by the preferred direction motion stimulus are found, and they appear to be symmetrical to bursts in the response to the anti-preferred direction of motion. A novel cross-correlation technique is used to establish that the gaps are correlated between pairs of neurons. Temporal modulation is also found in psychophysical experiments using a modified stimulus. A model is made that can account for the temporal modulation in terms of the computational theory of biological image motion processing. A frequency domain analysis of the stimulus reveals that it contains a repeated power spectrum that may account for psychophysical and electrophysiological observations.
Some neurons tend to fire bursts of action potentials while others avoid burst firing. Using numerical and analytical models of spike trains as Poisson processes with the addition of refractory periods and bursting, we are able to account for peaks in the power spectrum near 40 Hz without assuming the existence of an underlying oscillatory signal. A preliminary examination of the local field potential reveals that stimulus-locked oscillation appears briefly at the beginning of the trial.
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This panel will discuss the research being conducted, and the models being used in three current coastal EPA studies being conducted on ecosystem services in Tampa Bay, the Chesapeake Bay and the Coastal Carolinas. These studies are intended to provide a broader and more comprehensive approach to policy and decision-making affecting coastal ecosystems as well as provide an account of valued services that have heretofore been largely unrecognized. Interim research products, including updated and integrated spatial data, models and model frameworks, and interactive decision support systems will be demonstrated to engage potential users and to elicit feedback. It is anticipated that the near-term impact of the projects will be to increase the awareness by coastal communities and coastal managers of the implications of their actions and to foster partnerships for ecosystem services research and applications. (PDF contains 4 pages)
Resumo:
Shellfish bed closures along the North Carolina coast have increased over the years seemingly concurrent with increases in population (Mallin 2000). More and faster flowing storm water has come to mean more bacteria, and fecal indicator bacterial (FIB) standards for shellfish harvesting are often exceeded when no source of contamination is readily apparent (Kator and Rhodes, 1994). Could management reduce bacterial loads if the source of the bacteria where known? Several potentially useful methods for differentiating human versus animal pollution sources have emerged including Ribotyping and Multiple Antibiotic Resistance (MAR) (US EPA, 2005). Total Maximum Daily Load (TMDL) studies on bacterial sources have been conducted for streams in NC mountain and Piedmont areas (U.S. EPA, 1991 and 2005) and are likely to be mandated for coastal waters. TMDL analysis estimates allowable pollutant loads and allocates them to known sources so management actions may be taken to restore water to its intended uses (U.S. EPA, 1991 and 2005). This project sought first to quantify and compare fecal contamination levels for three different types of land use on the coast, and second, to apply MAR and ribotyping techniques and assess their effectiveness for indentifying bacterial sources. Third, results from these studies would be applied to one watershed to develop a case study coastal TMDL. All three watershed study areas are within Carteret County, North Carolina. Jumping Run Creek and Pettiford Creek are within the White Oak River Basin management unit whereas the South River falls within the Neuse River Basin. Jumping Run Creek watershed encompasses approximately 320 ha. Its watershed was a dense, coastal pocosin on sandy, relic dune ridges, but current land uses are primarily medium density residential. Pettiford Creek is in the Croatan National Forest, is 1133 ha. and is basically undeveloped. The third study area is on Open Grounds Farm in the South River watershed. Half of the 630 ha. watershed is under cultivation with most under active water control (flashboard risers). The remaining portion is forested silviculture.(PDF contains 4 pages)