The relationship between structure and function is an invaluable context with which to explore biological mechanisms of normal and dysfunctional hearing. The systematic and topographic representation of frequency originates at the cochlea, and is retained throughout much of the central auditory system. The cochlear nucleus (CN), which initiates all ascending auditory pathways, represents an essential link for understanding frequency organization. A model of the CN that maps frequency representation in 3D would facilitate investigations of possible frequency specializations and pathologic changes that disturb frequency organization. Toward this goal, we reconstructed in 3D the trajectories of labeled auditory nerve (AN) fibers following multiunit recordings and dye injections in the anteroventral CN of the CBA/J mouse. We observed that each injection produced a continuous sheet of labeled AN fibers. Individual cases were normalized to a template using 3D alignment procedures that revealed a systematic and tonotopic arrangement of AN fibers in each subdivision with a clear indication of isofrequency laminae. The combined dataset was used to mathematically derive a 3D quantitative map of frequency organization throughout the entire volume of the CN. This model, available online (http://3D.ryugolab.com/), can serve as a tool for quantitatively testing hypotheses concerning frequency and location in the CN.
This paper describes a thermal model that represents the heat generation behavior of a large format (10.5 Ah) Li-ion pouch cell. The thermal model is based on the calculation of the heat generation from experimental measurements of internal resistance and the entropic heat coefficient. Predictions from the thermal model are compared with experimental adiabatic calorimetry data. Higher discharge rates and larger temperature operation ranges than the ones reported in prior studies are considered. Results from the thermal model simulations have a prediction error of 21% in comparison with the experimental ones for discharge processes carried out at moderate rates. For discharge processes carried out at high discharge rates a maximum prediction error of 15% has been determined. The advantages and disadvantages of the model are further discussed, taking into account aspects such as accuracy, model development and implementation in different thermal management system designs.The rechargeable battery industry will experience significant growth in the near future given the increased need for battery systems for power electronics, renewable energy storage and power systems for transportation applications. 1 These new applications require large format lithium-ion (Li-ion) cells (2-100 Ah) that need to be integrated in large scale modules and packs and be managed by ad hoc control electronics, the so-called battery management systems (BMS). 2 New large format Li-ion batteries are rapidly becoming available from commercial cell manufacturers. 3,4 However, these cells still have many problems that need to be overcome -problems such as operating temperature behavior and cell temperature non-uniformities, 5 among others -which could result in accelerated degradation of the battery power performance and the reduction of the operating life, 6 critically affecting the safety issues of battery packs.Therefore, the kinds of applications that are powered by largescale Li-ion batteries make it necessary to design thermal management systems (TMS) that improve battery performance. A precise determination of heat generation in batteries could improve the TMS design process. Several investigations deal with the thermal modeling of single-cell batteries 7-11 and battery packs. 12-14 Some of these models predict heat generation rates based on experimental data 5,12,15-19 or electrochemical models. 8,10,13,14,[20][21][22] Pals and Newman 10,14 developed a thermal model for a Li-ion cell based on the electrochemical model presented by Doyle et al. 23 Song and Evans 13 took a similar approach and presented a 2D thermal model for a cell stack where the heat generation was estimated from a 1D electrochemical model. Such models are well-suited for designing batteries, but they are not suitable for the computational resources of the electronics used in BMSs. 24 Experimental studies show that the overpotential and entropic heat coefficients gathered from experiments can be used to predict the volumetric heat generation rate. These thermal simulat...
Liver radioembolization (RE) is a treatment option for patients with unresectable and chemorefractory primary and metastatic liver tumours. RE consists of intra-arterially administering via catheter radioactive microspheres that locally attack the tumours, sparing healthy tissue. Prior to RE, the standard practice is to conduct a treatment-mimicking pretreatment assessment via the infusion of Tc-labelled macroaggregated albumin microparticles. The usefulness of this pretreatment has been debated in the literature, and thus, the aim of the present study is to shed light on this issue by numerically simulating the liver RE pretreatment and actual treatment particle-haemodynamics in a patient-specific hepatic artery under two different literature-based cancer scenarios and two different placements of a realistic end-hole microcatheter in the proper hepatic artery. The parameters that are analysed are the following: microagent quantity and size (accounting for RE pretreatment and treatment), catheter-tip position (near the proper hepatic artery bifurcation and away from it), and cancer burden (10% and 30% liver involvement). The conclusion that can be reached from the simulations is that when it comes to mimicking RE in terms of delivering particles to tumour-bearing segments, the catheter-tip position is much more important (because of the importance of local haemodynamic pattern alteration) than the infused microagents (i.e. quantity and size). Cancer burden is another important feature because the increase in blood flow rate to tumour-bearing segments increases the power to drag particles. These numerical simulation-based conclusions are in agreement with clinically observed events reported in the literature. Copyright © 2016 John Wiley& Sons, Ltd.
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