Evaluation of electromechanical impedance based structural health monitoring for detection of loosening in total knee arthroplasty

Total Knee Arthroplasty (TKA) continues to be a common and important orthopedic procedure for many in the United States. Despite recent medical advancements and increasing knowledge in the orthopedic community, it has been determined that 20% of TKA patients are still dissatisfied with their knee replacements. Causes of this failure include septic loosening and wear on the bearing component of the implant. Another cause of failure that has received specific attention from the mechanical community is aseptic loosening, which has been attributed to unbalanced ligaments or misalignment of the implant components. Previous efforts have been made to detect loosening by using passive force sensors such as piezoelectric transducers or strain gauges to detect misalignment. An alternative to this is to perform active sensing or structural health monitoring to evaluate possible loosening before it becomes a critical concern to the patient. One method of structural health monitoring, called the electromechanical impedance (EMI) method, is particularly attractive as it can use a single, compact piezoelectric transducer to determine the state of the host structure. This work is intended to evaluate the ability of the EMI method in sensing loosening between the cement and bone of a TKA tibial tray. This work will utilize real tibial trays implanted into synthetic bone (Sawbone) to evaluate the feasibility of detecting loosening using the EMI method. The intention of this work is to serve as a foundation for further in-vivo and intraoperative studies

Theory of Insulator Metal Transition and Colossal Magnetoresistance in Doped Manganites

The persistent proximity of insulating and metallic phases, a puzzling characterestic of manganites, is argued to arise from the self organization of the twofold degenerate e_g orbitals of Mn into localized Jahn-Teller(JT) polaronic levels and broad band states due to the large electron - JT phonon coupling present in them. We describe a new two band model with strong correlations and a dynamical mean-field theory calculation of equilibrium and transport properties. These explain the insulator metal transition and colossal magnetoresistance quantitatively, as well as other consequences of two state coexistence

Machine learning-driven approach for large scale decision making with the analytic hierarchy process

The Analytic Hierarchy Process (AHP) multicriteria method can be cognitively demanding for large-scale decision problems due to the requirement for the decision maker to make pairwise evaluations of all alternatives. To address this issue, this paper presents an interactive method that uses online learning to provide scalability for AHP. The proposed method involves a machine learning algorithm that learns the decision maker’s preferences through evaluations of small subsets of solutions, and guides the search for the optimal solution. The methodology was tested on four optimization problems with different surfaces to validate the results. We conducted a one factor at a time experimentation of each hyperparameter implemented, such as the number of alternatives to query the decision maker, the learner method, and the strategies for solution selection and recommendation. The results demonstrate that the model is able to learn the utility function that characterizes the decision maker in approximately 15 iterations with only a few comparisons, resulting in significant time and cognitive effort savings. The initial subset of solutions can be chosen randomly or from a cluster. The subsequent ones are recommended during the iterative process, with the best selection strategy depending on the problem type. Recommendation based solely on the smallest Euclidean or Cosine distances reveals better results on linear problems. The proposed methodology can also easily incorporate new parameters and multicriteria methods based on pairwise comparisons.This research was funded by National Funds through the FCT—Portuguese Foundation for Science and Technology, References UIDB/05256/2020 and UIDP/05256/2020

New bioassays reveal susceptibility of stone-fruit rootstocks to capnodis tenebrionis larvae

Larvae of Capnodis tenebrionis (L.) (Coleoptera Buprestidae) feed and develop in roots of stone-fruit trees, thereby decreasing their efficiency, which can lead to plant death. The control of these larvae is critical, due to their localization in the root, and the management of this pest is focused on adults, mainly by using non-specific synthetic insecticides. Less susceptible Prunus rootstocks might be applied as a preventative management of larval infestation by this pest. The current research investigated the susceptibility to C. tenebrionis larvae of the most commonly used rootstocks by combining two bio-assays during two-year trials: development of larvae assayed on semi-artificial substrates containing rootstock bark flour; infestation by neonate larvae on rootstock twigs. The rearing assay on semi-artificial substrates made it possible to distinguish (1) a rootstock cluster (Montclar and GF677) in which larvae developed faster and heavier and produced larger adults, (2) a cluster (Adesoto, CAB6P, Colt and MaxMa60) in which larval growth was less efficient as well as adult size, and (3) a cluster (Garnem and Myrabolan 29C) with intermediate responses in larval development and adult size. The twig infestation assay by neonates showed the most infested (Colt) and least infested (Barrier, MaxMa60 and Marianna 26) rootstocks. When the results of both assays are combined, GF677 and Myrabolan 29C appear more susceptible, while Adesoto and MaxMa60 less susceptible to C. tenebrionis larvae, although Barrier and Marianna 26 require further investigation. The experimental model applied in the current trials can enable processing of a large number of tests on different rootstocks, thereby allowing the accumulation of a large quantity of data on the potential susceptibility of rootstocks. The possibility of rearing larvae on a substrate can allow comparison of additional compounds that could interact with larval growth

Zero Temperature Insulator-Metal Transition in Doped Manganites

We study the transition at T=0 from a ferromagnetic insulating to a ferromagnetic metallic phase in manganites as a function of hole doping using an effective low-energy model Hamiltonian proposed by us recently. The model incorporates the quantum nature of the dynamic Jahn-Teller(JT) phonons strongly coupled to orbitally degenerate electrons as well as strong Coulomb correlation effects and leads naturally to the coexistence of localized (JT polaronic) and band-like electronic states. We study the insulator-metal transition as a function of doping as well as of the correlation strength U and JT gain in energy E_{JT}, and find, for realistic values of parameters, a ground state phase diagram in agreement with experiments. We also discuss how several other features of manganites as well as differences in behaviour among manganites can be understood in terms of our model.Comment: To be published in Europhysics Letter

Buffer breakdown in GaN-on-Si HEMTs: A comprehensive study based on a sequential growth experiment

Abstract The aim of this work is to investigate the breakdown mechanisms of the layers constituting the vertical buffer of GaN-on-Si HEMTs; in addition, for the first time we demonstrate that the breakdown field of the AlN nucleation layer grown on a silicon substrate is equal to 3.2 MV/cm and evaluate its temperature dependence. To this aim, three samples, obtained by stopping the epitaxial growth of a GaN on Silicon stack at different steps, are studied and compared: Si/AlN, Si/AlN/AlGaN, full vertical stack up to the Carbon doped buffer layer. The current-voltage (IV) characterizations performed at both room temperature and high temperature show that: (i) the defectiveness of the AlN nucleation layer is the root cause of the leakage through an AlN/Silicon junction, and causes the vertical I-V characteristics to have a high device-to-device variability; (ii) the first AlGaN layer grown over the AlN, beside improving the breakdown voltage of the whole structure, causes the leakage current to be more stable and uniform across the sample area; (iii) a thick strain-relief stack and a carbon-doped GaN buffer enhance the breakdown voltage up to more than 750 V at 170 °C, and guarantee a remarkably low device-to-device variability. Furthermore, a set of constant voltage stress on the Si/AlN sample demonstrate that the aluminum nitride layer shows a time dependent breakdown, with Weibull-distributed failures and a shape factor greater than 1, in line with the percolation model

Microwave Remote Sensing of Falling Snow

This study analyzes passive and active microwave measurements during the 2003 Wakasa Bay field experiment for understanding of the electromagnetic characteristics of frozen hydrometeors at millimeter-wave frequencies. Based on these understandings, parameterizations of the electromagnetic scattering properties of snow at millimeter-wave frequencies are developed and applied to the hydrometeor profiles obtained by airborne radar measurements. Calculated brightness temperatures and radar reflectivity are compared with the millimeter-wave measurements

Flow Around a Slender Circular Cylinder: A Case Study on Distributed Hopf Bifurcation

This paper presents a short overview of the flow around a slender circular cylinder, the purpose being to place it within the frame of the distributed Hopf bifurcation problems described by the Ginzburg-Landau equation (GLE). In particular, the chaotic behavior superposed to a well tuned harmonic oscillation observed in the range Re > 270, with Re being the Reynolds number, is related to the defect-chaos regime of the GLE. Apparently new results, related to a Kolmogorov like length scale and the rms of the response amplitude, are derived in this defect-chaos regime and further related to the experimental rms of the lift coefficient measured in the range Re > 270

A multi-channel trigger and acquisition board for TDC-based readout: Application to the cosmic rays detector of the PolarQuEEEst 2018 project

In the summer of 2018, the PolarQuEEEst experiment accomplished a measurement of cosmic rays flux in the Arctic. The detector, installed on a sailboat, was based on scintillation tiles read by a total of 16 SiPM. A multi-channel board (called TRB) has been designed to process the discriminated SiPM signals providing both self-trigger capability and time-to-digital conversion; it was based on a Cyclone-V Intel FPGA. Time-to-digital conversion has been implemented both into FPGA and with the HPTDC chip (as a backup). In this document the board will be described, enlightening the main features and the achieved performance. Lastly, the PolarQuEEEst measurement campaigns will be briefly described, showing how the TRB board has proved to be effective for experiments which require low power consumption, integration with position and environmental sensors and great portability as well. Final thoughts on future improvements will be also discussed