Konnyaku jelly: A quick preparation and cost effective ultrasound-guided IV phantom model

Clinicians commonly place ultrasound-guided intravenous catheters in peripheral veins for the diagnostic and therapeutic treatments of patients. This procedural skill requires practice and static phantom models are a commonly used education tool. Several commercial models that simulate blood vessels within tissue are available; however, they can be expensive. There are many examples of “Do-It-Yourself” models proposed; however, many of these require time to create the model. Mixing water and gelatin to make a gelatinous material, and the time necessary to set and store the phantom may deter people from pursuing these options. We propose Konnyaku jelly, or “yam cake,” found in many Asian grocery stores, as the substrate to create a phantom model. When imaging with ultrasound, this model is similar to commercially available models, however the cost is less than $3.00 and preparation is about 5 min. We believe that Konnyaku jelly should be a more generally accepted homemade static model for phantom preparation.

Hybrid Numerical-Experimental Model Update Based on Correlation Approach for Turbine Components

Bladed-disks in turbo-machines experience high cycle fatigue failures due to high vibration amplitudes. Therefore, it is important to accurately predict their dynamic characteristics including the mechanical joints at blade-disk interfaces. Before the experimental identification of these joints, it is of paramount importance to accurately measure the interface degrees-of-freedom (DoF). However, they are largely inaccessible for the measurements. For this reason, expansion techniques can be used in order to update the single components. But the expansion can be affected adversely if the measurements are not properly correlated with the updated model. Therefore, a frequency domain expansion method called System Equivalent Model Mixing (SEMM) is used to expand a limited set of measurements to a larger set of numerical DoF. Different measured models - termed the overlay models - are taken from an impact testing campaign of a blade and a disk and coupled to the numerical model according to the SEMM. The expanded models - termed the hybrid models - are then correlated with the validation channels in a round-robin way by means of Frequency Response Assurance Criteria (FRAC). The global correlations depict whether or not a measurement and the respective expansion is properly correlated. By this approach, the least correlated channels can be done away with from the measurements to have a better updated hybrid model. The method is tested on both the structures (the blade and the disk) and it is successfully shown that removing the uncorrelated channels does improve the quality of the hybrid models.

Mixed finite element method of a seawater intrusion problem in confined aquifers

We consider a model mixing sharp and diffuse interface approach for the seawater intrusion phenomenon in confined aquifers. The aim of this work is to introduce and analyze a new mixed formulation, obtained by writing the problem into a matrix form, and introducing a new variable σ = R(u)∇u representing the flux tensor of the primal variable u = (h, Φf)T. Here, h represents the depth of the salt/freshwater interface, Φf, the hydraulic head of freshwater, and R(u) a symmetric and positive definite diffusion matrix. We show that the continuous problem is well-posed. For the time discretization of this new mixed formulation, we use a semi-implicit scheme, and we show that the problem is well posed.

Fas-threshold signalling in MSCs causes tumour progression and metastasis

Mesenchymal stem cells (MSCs) are part of the tumour microenvironment and have been implicated in tumour progression. We found the number of MSCs significantly increased in tumour-burdened mice driven by Fas-threshold signalling. Consequently, MSCs lacking Fas lost their ability to induce metastasis development in a pancreatic cancer model. Mixing of MSCs with pancreatic cancer cells led to sustained production of the pro-metastatic cytokines CCL2 and IL6 by the stem cells. The levels of these cytokines depended on the number of MSCs, linking Fas-mediated MSC-proliferation to their capacity to promote tumour progression. Furthermore, we discovered that CCL2 and IL6 were induced by pancreatic cancer cell-derived IL1. Analysis of patient transcriptomic data revealed that high FasL expression correlates with high levels of MSC markers as well as increased IL6 and CCL2 in pancreatic tumours. Moreover, both FasL and CCL2 are linked to elevated levels of markers specific for monocytes known to possess further pro-metastatic activities. These results confirm our experimental findings of a FasL-MSC-IL1-CCL2/IL6 axis in pancreatic cancer and highlight the role MSCs play in tumour progression.

Hybrid Numerical-Experimental Model Update Based on Correlation Approach for Turbine Components

Bladed-disks in turbo-machines experience high cycle fatigue failures due to high vibration amplitudes. Therefore, it is important to accurately predict their dynamic characteristics including the mechanical joints at blade-disk (root joint) or blade-blade (shroud) interfaces. These joints help in dampening the vibration amplitudes. Before the experimental identification of these joints, it is of paramount importance to accurately measure the interface degrees-of-freedom (DoF). However, they are largely inaccessible for the measurements. For this reason, expansion techniques are used in order to update the single components before their coupling. But the expansion can be affected adversely if the measurements are not properly correlated with the updated model or if they have significant errors. Therefore, a frequency domain expansion method called System Equivalent Model Mixing (SEMM) is used to expand a limited set of measurements to a larger set of numerical DoF. Different measured models — termed the overlay models — are taken from an impact testing campaign of a blade and a disk and coupled to the numerical model according to the SEMM. The expanded models — termed the hybrid models — are then correlated with the validation channels in a round-robin way by means of Frequency Response Assurance Criteria (FRAC). The global correlations depict whether or not a measurement and the respective expansion is properly correlated. By this approach, the least correlated channels can be done away with from the measurements to have a better updated hybrid model. The method is tested on both the structures (the blade and the disk) and it is successfully shown that removing the uncorrelated channels does improve the quality of the hybrid models.

Experimental Joint Identification Using System Equivalent Model Mixing in a Bladed Disk

A joint between two components can be seen as a means to transmit dynamic information from one side to the other. To identify the joint, a reverse process called decoupling can be applied. This is not as straightforward as the coupling, especially when the substructures have three-dimensional characteristics, or sensor mounting effects are significant, or the interface degrees-of-freedom (DoF) are inaccessible for response measurement and excitation. Acquiring frequency response functions (FRFs) at the interface DoF, therefore, becomes challenging. Consequently, one has to consider hybrid or expansion methods that can expand the observed dynamics on accessible DoF to inaccessible DoF. In this work, we attempt to identify the joint dynamics using the system equivalent model mixing (SEMM) decoupling method with a virtual point description of the interface. Measurements are made only at the internal DoF of the uncoupled substructures and also of the coupled structure assuming that the joint dynamics are observable in the assembled state. Expanding them to the interface DoF and performing coupling and decoupling operations iteratively, the joint is identified. The substructures under consideration are a disk and blade—an academic test geometry that has a total of 18 blades but only one blade-to-disk joint is considered in this investigation. The joint is a typical dove-tail assembly. The method is shown to identify the joint without any direct interface DoF measurement.

Demystifying a class of multiply robust estimators

Summary For estimating the population mean of a response variable subject to ignorable missingness, a new class of methods, called multiply robust procedures, has been proposed. The advantage of multiply robust procedures over the traditional doubly robust methods is that they permit the use of multiple candidate models for both the propensity score and the outcome regression, and they are consistent if any one of the multiple models is correctly specified, a property termed multiple robustness. This paper shows that, somewhat surprisingly, multiply robust estimators are special cases of doubly robust estimators, where the final propensity score and outcome regression models are certain combinations of the candidate models. To further improve model specifications in the doubly robust estimators, we adapt a model mixing procedure as an alternative method for combining multiple candidate models. We show that multiple robustness and asymptotic normality can also be achieved by our mixing-based doubly robust estimator. Moreover, our estimator and its theoretical properties are not confined to parametric models. Numerical examples demonstrate that the proposed estimator is comparable to and can even outperform existing multiply robust estimators.

The Emergent Behaviour of Thermal Networks and Its Impact on the Thermal Conductivity of Heterogeneous Materials and Systems

The properties of thermal networks are examined to understand the effective thermal conductivity of heterogeneous two-phase composite materials and systems. At conditions of high contrast in thermal conductivity of the individual phases (k1 and k2), where k1 << k2 or k1 >> k2, the effective thermal conductivity of individual networks of the same composition was seen to be highly sensitive to the distribution of the phases and the presence of percolation paths across the network. However, when the contrast in thermal conductivities of the two phases was modest (k1/k2 ~ 10−2 to 102), the thermal networks were observed to exhibit an emergent response with a low variability in the effective thermal conductivity of mixtures of the same composition. A logarithmic mixing rule is presented to predict the network response in the low variability region. Excellent agreement between the model, mixing rule and experimental data is observed for a range two-phase porous and granular media. The modelling approach provides new insights into the design of multi-phase composites for thermal management applications and the interpretation or prediction of their heat transfer properties.