Challenges and Lessons Learned in the Development of a Participatory Learning and Action Intervention to Tackle Antibiotic Resistance: Experiences From Northern Vietnam.

Antibiotic use in the community for humans and animals is high in Vietnam, driven by easy access to over-the counter medicines and poor understanding of the role of antibiotics. This has contributed to antibiotic resistance levels that are amongst the highest in the world. To address this problem, we developed a participatory learning and action (PLA) intervention. Here we describe challenges and lessons learned while developing and testing this intervention in preparation for a large-scale One Health trial in northern Vietnam. We tested the PLA approach using community-led photography, and then reflected on how this approach worked in practice. We reviewed and discussed implementation documentation and developed and refined themes. Five main themes were identified related to challenges and lessons learned: understanding the local context, stakeholder relationship development, participant recruitment, building trust and motivation, and engagement with the topic of antibiotics and antimicrobial resistance (AMR). Partnerships with national and local authorities provided an important foundation for building relationships with communities, and enhanced visibility and credibility of activities. Partnership development required managing relationships, clarifying roles, and accommodating different management styles. When recruiting participants, we had to balance preferences for top-down and bottom-up approaches. Building trust and motivation took time and was challenged by limited study team presence in the community. Open discussions around expectations and appropriate incentives were re-visited throughout the process. Financial incentives provided initial motivation to participate, while less tangible benefits like collective knowledge, social connections, desire to help the community, and new skills, sustained longer-term motivation. Lack of awareness and perceived importance of the problem of AMR, affected initial motivation. Developing mutual understanding through use of common and simplified language helped when discussing the complexities of this topic. A sense of ownership emerged as the study progressed and participants understood more about AMR, how it related to their own concerns, and incorporated their own ideas into activities. PLA can be a powerful way of stimulating community action and bringing people together to tackle a common problem. Understanding the nuances of local power structures, and allowing time for stakeholder relationship development and consensus-building are important considerations when designing engagement projects.

Computational Generation of Virtual Concrete Mesostructures.

Concrete is a heterogeneous material with a disordered material morphology that strongly governs the behaviour of the material. In this contribution, we present a computational tool called the Concrete Mesostructure Generator (CMG) for the generation of ultra-realistic virtual concrete morphologies for mesoscale and multiscale computational modelling and the simulation of concrete. Given an aggregate size distribution, realistic generic concrete aggregates are generated by a sequential reduction of a cuboid to generate a polyhedron with multiple faces. Thereafter, concave depressions are introduced in the polyhedron using Gaussian surfaces. The generated aggregates are assembled into the mesostructure using a hierarchic random sequential adsorption algorithm. The virtual mesostructures are first calibrated using laboratory measurements of aggregate distributions. The model is validated by comparing the elastic properties obtained from laboratory testing of concrete specimens with the elastic properties obtained using computational homogenisation of virtual concrete mesostructures. Finally, a 3D-convolutional neural network is trained to directly generate elastic properties from voxel data.

Reduced Order Multiscale Simulation of Diffuse Damage in Concrete.

Damage in concrete structures initiates as the growth of diffuse microcracks that is followed by damage localisation and eventually leads to structural failure. Weak changes such as diffuse microcracking processes are failure precursors. Identification and characterisation of these failure precursors at an early stage of concrete degradation and application of suitable precautionary measures will considerably reduce the costs of repair and maintenance. To this end, a reduced order multiscale model for simulating microcracking-induced damage in concrete at the mesoscale level is proposed. The model simulates the propagation of microcracks in concrete using a two-scale computational methodology. First, a realistic concrete specimen that explicitly resolves the coarse aggregates in a mortar matrix was generated at the mesoscale. Microcrack growth in the mortar matrix is modelled using a synthesis of continuum micromechanics and fracture mechanics. Model order reduction of the two-scale model is achieved using a clustering technique. Model predictions are calibrated and validated using uniaxial compression tests performed in the laboratory.

Sensitivity of Ultrasonic Coda Wave Interferometry to Material Damage-Observations from a Virtual Concrete Lab.

Ultrasonic measurements are used in civil engineering for structural health monitoring of concrete infrastructures. The late portion of the ultrasonic wavefield, the coda, is sensitive to small changes in the elastic moduli of the material. Coda Wave Interferometry (CWI) correlates these small changes in the coda with the wavefield recorded in intact, or unperturbed, concrete specimen to reveal the amount of velocity change that occurred. CWI has the potential to detect localized damages and global velocity reductions alike. In this study, the sensitivity of CWI to different types of concrete mesostructures and their damage levels is investigated numerically. Realistic numerical concrete models of concrete specimen are generated, and damage evolution is simulated using the discrete element method. In the virtual concrete lab, the simulated ultrasonic wavefield is propagated from one transducer using a realistic source signal and recorded at a second transducer. Different damage scenarios reveal a different slope in the decorrelation of waveforms with the observed reduction in velocities in the material. Finally, the impact and possible generalizations of the findings are discussed, and recommendations are given for a potential application of CWI in concrete at structural scale.

Cementitious Composites with High Compaction Potential: Modeling and Calibration.

There is an increasing need for the development of novel technologies for tunnel construction in difficult geological conditions to protect segmental linings from unexpected large deformations. In the context of mechanized tunneling, one method to increase the damage tolerance of tunnel linings in such conditions is the integration of a compressible two-component grout for the annular gap between the segmental linings and the deformable ground. In this regard, expanded polystyrene (EPS) lightweight concrete/mortar has received increasing interest as a potential "candidate material" for the aforementioned application. In particular, the behavior of the EPS lightweight composites can be customized by modifying their pore structure to accommodate deformations due to specific geological conditions such as squeezing rocks. To this end, novel compressible cementitious EPS-based composite materials with high compaction potential have been developed. Specimens prepared from these composites have been subjected to compressive loads with and without lateral confinement. Based on these experimental data a computational model based on the Discrete Element Method (DEM) has been calibrated and validated. The proposed calibration procedure allows for modeling and prognosis of a wide variety of composite materials with a high compaction potential. The calibration procedure is characterized by the identification of physically quantifiable parameters and the use of phenomenological submodels. Model prognoses show excellent agreement with new experimental measurements that were not incorporated in the calibration procedure.

Anesthetic Management of a Cardiac Transplant Patient After Extensive Facial Trauma Caused by a Pit Bull Attack.

A 72-year-old male cardiac transplant patient presented after sustaining facial and extremity trauma caused by a pit bull dog attack. The case was further complicated by the duration of the surgery, bleeding, infection risk, intraoperative hypothermia, immunosuppression, and the risk of sepsis. His anesthetic management required careful coordination with his transplant team. We also sought the expertise of the in-house pharmacist to obtain the appropriate administration strategies for the patient's immunosuppressant agents. As the number of transplant patients increases, oral and maxillofacial surgeons must remain cognizant of the challenges and strategies associated with treating those undergoing graft-preserving immunosuppression. We have presented a more complex case of a cardiac transplant patient requiring extensive facial soft tissue reconstruction. The experience achieved in the management of a complex cardiac patient will no doubt provide guidance in the management of elective surgical procedures in other patients with simpler transplant histories.