Efficacy of catheter-based drug delivery in a hybrid in vitro model of cardiac microvascular obstruction with porcine microthrombi.

Microvascular obstruction (MVO) often occurs in ST-elevation myocardial infarction (STEMI) patients after percutaneous coronary intervention (PCI). Diagnosis and treatment of MVO lack appropriate and established procedures. This study focused on two major points by using an in vitro multiscale flow model, which comprised an aortic root model with physiological blood flow and a microfluidic model of the microcirculation with vessel diameters down to 50 μm. First, the influence of porcine microthrombi (MT), injected into the fluidic microchip, on perfusion was investigated. We found that only of all injected MT were fully occlusive. Second, it could also be shown that the maximal concentration of a dye (representing therapeutic agent) during intracoronary infusion could be increased on average by , when proximally occluding the coronary artery by a balloon during drug infusion. The obtained results and insights enhance the understanding of perfusion in MVO-affected microcirculation and could lead to improved treatment methods for MVO patients

A fault mode identification methodology based on self-organizing map

One of the main goals of predictive maintenance is to be able to trigger the right maintenance actions at the right moment in time building upon the monitoring of the health status of the concerned systems and their components. As such, it allows identifying incipient faults and forecasting the moment of failure at the earliest stage. Many different data-driven methods are used in such approaches (Naderi and Khorasani in 2017 IEEE 30th Canadian conference on electrical and computer engineering (CCECE), Windsor, ON, IEEE, pp 1–6, 2017. https://doi.org/10.1109/ccece.2017.7946715; Sarkar et al. in J Eng Gas Turbines Power 1338(8):081602, 2011. https://doi.org/10.1115/1.4002877; Svärd et al. in Mech Syst Signal Process 45(1):170–192, 2014. https://doi.org/10.1016/j.ymssp.2013.11.002; Pourbabaee et al. Mech Syst Signal Process 76–77:136–156, 2016. https://doi.org/10.1016/j.ymssp.2016.02.023). This work uses the self-organizing maps (SOMs) or Kohonen map, thanks to its ability to emphasize underlying behavior such as fault modes. An automatic fault mode detection is presented based on a SOM network and the kernel density estimation with as less as possible prior knowledge. The different SOM development steps are presented and the suitable solutions proposed to structure the approach are accompanied by mathematical methods. The generated maps are then used with kernel density analysis to isolate fault modes on them. Finally, a methodology is presented to identify the different fault modes. The work is illustrated with an aircraft jet engines case study

An unsupervised approach for health index building and for similarity-based remaining useful life estimation

Predictive maintenance techniques attempt to trigger a maintenance intervention at the right moment by estimating the life expectation. Predictive maintenance is increasingly implemented by automated approaches able to perform diagnostics and prognostics. The main part of recent research in these approaches is focused in machine learning structures whose reasoning is implicit and cannot be easily explained. This poses a problem for their implementation in highly constrained area such as aeronautics. To overcome this constraint, explicit reasoning approaches such as the Similarity-Based Model (SBM) can be implemented. The SBM has been widely used for fault diagnostics and the remaining useful life (RUL) estimation, but the development of SBM includes tasks that often rely on high skilled experts. For instance, data reduction techniques required for SBM are often performed by experts judgment whose outcomes are not always consistent. The produced features from these techniques are used to build the Health Index that can be used to create the degradation trends that serve as a reference for the SBM. To overcome these difficulties, an automatic and unsupervised approach based on the Kernel Principal Component Analysis is proposed to enhance the Health Index creation. It preserves as much of the sensor information as possible improving the similarity-based RUL estimation. Additionally, when estimating the RUL of a system, the most similar degradation trends stored in the SBM library are used to compute individual RULs, the final RUL is obtained by a fusion rule technique that combines all these individual RULs into a consolidated value. For the fusion rule techniques, a self-adaptive method that does not rely on human expertize is proposed. This fusion rule can benefit of the accumulated knowledge over the SBM operation. This unsupervised approach to develop a SBM is validated with promising results against an equivalent and supervised algorithm that came out best in the 2008 prognostic health management challenge

Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics

The use of a modern technological system requires a good engineering approach, optimized operations, and proper maintenance in order to keep the system in an optimal state. Predictive maintenance focuses on the organization of maintenance actions according to the actual health state of the system, aiming at giving a precise indication of when a maintenance intervention will be necessary. Predictive maintenance is normally implemented by means of specialized computational systems that incorporate one of several models to fulfil diagnostics and prognostics tasks. As complexity of technological systems increases over time, single-model approaches hardly fulfil all functions and objectives for predictive maintenance systems. It is increasingly common to find research studies that combine different models in multi-model approaches to overcome complexity of predictive maintenance tasks, considering the advantages and disadvantages of each single model and trying to combine the best of them. These multi-model approaches have not been extensively addressed by previous review studies on predictive maintenance. Besides, many of the possible combinations for multi-model approaches remain unexplored in predictive maintenance applications; this offers a vast field of opportunities when architecting new predictive maintenance systems. This systematic survey aims at presenting the current trends in diagnostics and prognostics giving special attention to multi-model approaches and summarizing the current challenges and research opportunities

Adaptation of the African Couples HIV Testing and Counseling Model for Men who have Sex with Men in the United States: an Application of the ADAPT-ITT Framework

To respond to the need for new HIV prevention services for men who have sex with men (MSM) in the United States, and to respond to new data on the key role of main partnerships in US MSM epidemics, we sought to develop a new service for joint HIV testing of male couples. We used the ADAPT-ITT framework to guide our work. From May 2009 to July 2013, a multiphase process was undertaken to identify an appropriate service as the basis for adaptation, collect data to inform the adaptation, adapt the testing service, develop training materials, test the adapted service, and scale up and evaluate the initial version of the service. We chose to base our adaptation on an African couples HIV testing service that was developed in the 1980s and has been widely disseminated in low- and middle-income countries. Our adaptation was informed by qualitative data collections from MSM and HIV counselors, multiple online surveys of MSM, information gathering from key stakeholders, and theater testing of the adapted service with MSM and HIV counselors. Results of initial testing indicate that the adapted service is highly acceptable to MSM and to HIV counselors, that there are no evident harms (e.g., intimate partner violence, relationship dissolution) associated with the service, and that the service identifies a substantial number of HIV serodiscordant male couples. The story of the development and scale-up of the adapted service illustrates how multiple public and foundation funding sources can collaborate to bring a prevention adaptation from concept to public health application, touching on research, program evaluation, implementation science, and public health program delivery. The result of this process is an adapted couples HIV testing approach, with training materials and handoff from academic partners to public health for assessment of effectiveness and consideration of the potential benefits of implementation; further work is needed to optimally adapt the African couples testing service for use with male–female couples in the United States