Remote River Energy System: An open source low maintenance turbine design for remote areas

Axial flow hydro-kinetic turbines convert the kinetic energy of a flowing fluid into electrical energy, and can be designed for deployment in a wide range of locations. As relatively recent technology, these designs are often high in cost, complex, and require specialist maintenance and materials. This is not viable for many communities in developing countries, which may subsequently remain reliant on fossil fuels. A remote river energy system has been designed to be built and maintained using minimal equipment, with components that can be readily obtained. A formal design process has been used with design review and feedback stages; design tools included Simulink modelling, FEA, CFD, nodal analysis and flume testing. Only a handful of components such as the turbine blades require specialist machining and maintenance. The results demonstrate how an effective water turbine with a 3kW output can be theoretically produced and maintained without an over-reliance on specialised components and tools, thereby producing a more economically viable water turbine for use in developing countries. Open source distribution of the design drawings will facilitate application of the design and improvements by other stakeholders. The design study presented here is a platform for prototype technology trials to further develop the concept.

Novel loss functions for ensemble-based medical image classification

Medical images commonly exhibit multiple abnormalities. Predicting them requires multi-class classifiers whose training and desired reliable performance can be affected by a combination of factors, such as, dataset size, data source, distribution, and the loss function used to train deep neural networks. Currently, the cross-entropy loss remains the de-facto loss function for training deep learning classifiers. This loss function, however, asserts equal learning from all classes, leading to a bias toward the majority class. Although the choice of the loss function impacts model performance, to the best of our knowledge, we observed that no literature exists that performs a comprehensive analysis and selection of an appropriate loss function toward the classification task under study. In this work, we benchmark various state-of-the-art loss functions, critically analyze model performance, and propose improved loss functions for a multi-class classification task. We select a pediatric chest X-ray (CXR) dataset that includes images with no abnormality (normal), and those exhibiting manifestations consistent with bacterial and viral pneumonia. We construct prediction-level and model-level ensembles to improve classification performance. Our results show that compared to the individual models and the state-of-the-art literature, the weighted averaging of the predictions for top-3 and top-5 model-level ensembles delivered significantly superior classification performance (p < 0.05) in terms of MCC (0.9068, 95% confidence interval (0.8839, 0.9297)) metric. Finally, we performed localization studies to interpret model behavior and confirm that the individual models and ensembles learned task-specific features and highlighted disease-specific regions of interest. The code is available at https://github.com/sivaramakrishnan-rajaraman/multiloss_ensemble_models.

THE INFLUENCE OF FORWARD SPEED AND NONLINEARITIES ON THE DYNAMIC BEHAVIOUR OF A CONTAINER SHIP IN REGULAR WAVES

The aim of this paper is to compare the heave and pitch motions for the S175 containership, travelling in head regular waves, obtained from frequency domain linear and time domain partly nonlinear potential flow analyses. The frequency domain methods comprise the pulsating and the translating, pulsating Green’s function methods, with the relevant source distribution over the mean wetted surface of the hull. The time domain method uses the radiation and diffraction potentials related to the mean wetted surface, implemented using Impulse Response Functions (IRF), whilst the incident wave and restoring actions are evaluated on the instantaneous wetted surface. The calculations are carried out for a range of Froude numbers, and in the case of the partly nonlinear method for different wave steepness values. Comparisons are made with available experimental measurements. The discussion focuses on the necessity for a nonlinear approach for predicting the radiation potential and the possible numerical methods for its formulation.

Optimization of the Microwave-Assisted Carbothermical Reduction Process for Metals from Electric Arc Furnace Dust with Biochar

The main purpose of this work was to extract valuable metals from EAF dust with the addition of biochar, using microwaves to control and optimize the carbothermical reduction process. To achieve better microwave penetration and the most homogeneous electromagnetic heat source distribution possible in a sample, the content of EAF dust and biochar in centimeter-size spherical particles prepared by the pelletization process was considered to be radially heterogeneous. The content of EAF dust was determined experimentally and the effective permittivity, permeability, and thermal conductivity of the EAF dust as well as biochar–EAF powder mixture were determined using effective medium approximation. The microwave heating of a multilayered pellet of biochar-containing EAF dust was simulated and investigated. The influence of the distribution of the components within the pellet on the effectiveness of the microwave heating was investigated, as was the influence of the biochar conductivity. The interaction of the pellet with both plane waves in free space and with H10 mode waves in a single-mode waveguide was considered. The most optimal distribution of EAF dust and biochar within the pellet for the reduction process was determined.

887. Implementation of Long-acting Injectable Cabotegravir/Rilpivirine for HIV-1 Treatment at a Ryan White-funded Clinic in the U.S. South

Background In January 2021, the first ever long-acting injectable (LAI) antiretroviral therapy (ART), cabotegravir/rilpivirine (CAB/RPV), was approved for maintenance HIV-1 treatment in select patients with virologic suppression. LAI-ART has the potential to improve ART adherence, reduce HIV stigma, and promote equity in care outcomes, however, implementation in real-world settings has yet to be evaluated. Methods We launched a pilot LAI-ART program at the largest Ryan White-funded HIV clinic in the Southeast. From 4/14/21 to 5/14/21, providers referred patients interested and willing to switch to LAI-CAB/RPV who met screening criteria. Our interdisciplinary LAI team (Clinician-Pharmacy-Nursing) verified clinical eligibility (HIV-1 &lt; 200 c/ml ≥6 months and no history of virologic failure, resistance to either drug, or chronic HBV infection) and pursued medication access for 28-day oral lead-in and monthly injectable CAB/RPV. We describe demographic and clinical variables of referred PWH and early outcomes in accessing LAI-ART. Results Among 42 referrals, median age was 40.5 (Q1-Q3, 32-52) years, 83% were men, and 76% Black. Payor source distribution was 26% Private, 19% Medicare, 10% Medicaid, and 45% ADAP. At the time of referral, median CD4 count was 583 (Q1-Q3, 422-742) cells/mm3 and median sustained HIV-1 RNA &lt; 200 c/ml was 1427 (Q1-Q3, 961-2534) days. A total of 35 patients (74%) met clinical eligibility for LAI-CAB/RPV, including 4 patients who required a transition off proton pump inhibitor therapy to accommodate oral RPV. Ineligible PWH were excluded due to evidence of RPV resistance (n=5), possible RPV hypersensitivity (n=1), and HIV non-suppression (n=1). The table summarizes the process of pursuing LAI-ART access for the initial 10 enrollees by insurance status. Conclusion Our experience implementing LAI-ART at a Ryan White-funded HIV clinic in the Southern U.S. has been challenged by substantial human resource capital to attain drug, delayed therapy initiation due to insurance denials, and patient ineligibility primarily due to concern for potential RPV resistance. These barriers may perpetuate disparities in ART access and virologic suppression among PWH and need to be urgently addressed so that LAI-ART can be offered equitably. Disclosures Lauren F. Collins, MD, MSc, Nothing to disclose Bradley L. Smith, Pharm.D., AAHIVP, Gilead Sciences, Inc (Advisor or Review Panel member) Wendy Armstrong, MD, Nothing to disclose Jonathan Colasanti, MD, Integritas CME (Consultant, develop and deliver CME content around Rapid Entry/Rapid ART)