Supervisory Algorithm for Autonomous Hemodynamic Management Systems

Future military conflicts will require new solutions to manage combat casualties. The use of automated medical systems can potentially address this need by streamlining and augmenting the delivery of medical care in both emergency and combat trauma environments. However, in many situations, these systems may need to operate in conjunction with other autonomous and semi-autonomous devices. Management of complex patients may require multiple automated systems operating simultaneously and potentially competing with each other. Supervisory controllers capable of harmonizing multiple closed-loop systems are thus essential before multiple automated medical systems can be deployed in managing complex medical situations. The objective for this study was to develop a Supervisory Algorithm for Casualty Management (SACM) that manages decisions and interplay between two automated systems designed for management of hemorrhage control and resuscitation: an automatic extremity tourniquet system and an adaptive resuscitation controller. SACM monitors the required physiological inputs for both systems and synchronizes each respective system as needed. We present a series of trauma experiments carried out in a physiologically relevant benchtop circulatory system in which SACM must recognize extremity or internal hemorrhage, activate the corresponding algorithm to apply a tourniquet, and then resuscitate back to the target pressure setpoint. SACM continues monitoring after the initial stabilization so that additional medical changes can be quickly identified and addressed, essential to extending automation algorithms past initial trauma resuscitation into extended monitoring. Overall, SACM is an important step in transitioning automated medical systems into emergency and combat trauma situations. Future work will address further interplay between these systems and integrate additional medical systems.

A Deep Learning Framework for Automatic Meal Detection and Estimation in Artificial Pancreas Systems

Current artificial pancreas (AP) systems are hybrid closed-loop systems that require manual meal announcements to manage postprandial glucose control effectively. This poses a cognitive burden and challenge to users with T1D since this relies on frequent user engagement to maintain tight glucose control. In order to move towards fully automated closed-loop glucose control, we propose an algorithm based on a deep learning framework that performs multitask quantile regression, for both meal detection and carbohydrate estimation. Our proposed method is evaluated in silico on 10 adult subjects from the UVa/Padova simulator with a Bio-inspired Artificial Pancreas (BiAP) control algorithm over a 2 month period. Three different configurations of the AP are evaluated -BiAP without meal announcement (BiAP-NMA), BiAP with meal announcement (BiAP-MA), and BiAP with meal detection (BiAP-MD). We present results showing an improvement of BiAP-MD over BiAP-NMA, demonstrating 144.5 ± 6.8 mg/dL mean blood glucose level (−4.4 mg/dL, p< 0.01) and 77.8 ± 6.3% mean time between 70 and 180 mg/dL (+3.9%, p< 0.001). This improvement in control is realised without a significant increase in mean in hypoglycaemia (+0.1%, p= 0.4). In terms of detection of meals and snacks, the proposed method on average achieves 93% precision and 76% recall with a detection delay time of 38 ± 15 min (92% precision, 92% recall, and 37 min detection time for meals only). Furthermore, BiAP-MD handles hypoglycaemia better than BiAP-MA based on CVGA assessment with fewer control errors (10% vs. 20%). This study suggests that multitask quantile regression can improve the capability of AP systems for postprandial glucose control without increasing hypoglycaemia.

Evaluation of Physicothermal Properties of Silicone Oil Dispersed with Multiwalled Carbon Nanotubes and Data Prediction Using ANN

The researchers wanted to see whether MWCNTs changed the physicothermal properties of solar thermal working fluids. Assessing thermal properties is vital for solar thermal efficiency. Lubricant contains silicone oil resurfaced. It contains 0.25, 0.5, 0.75, and 1.0% multiwalled carbon nanotubes. Before dispersion in thermic fluids, nanomaterials must be properly surface modified. Between 100°C and 300°C, a fluid’s thermal conductivity and specific heat physical characteristics like viscosity and density may be inferred from data collected between 50°C and 150°C. Thermal conductivity increases by 15% to 20% when carbon nanotubes are dispersed. The pressure drop is minimal at 0.5 percent weight fraction, demonstrating the suitability of nanofluids in closed loop systems. The characteristics are forecasted using feed-forward backpropagation method and GRNN, and the best of them is selected for prediction. In this research, hidden layer neurons and factors are examined.

Barriers to Implementing the Circular Economy in the Construction Industry: A Critical Review

To facilitate the adoption of the circular economy (CE) in the architecture, engineering and construction (AEC) sector, some authors have demonstrated the potential of recent designs that take into account the sustainable management of an asset’s end-of-life (EOL), providing an alternative to the dominant designs that end with demolition. However, there is no review of the literature that encompasses a large range of sustainable designs in the current CE context. This paper provides a critical review of journal papers that deal with the barriers to implementing sustainable designs and approaches to the EOL management of assets that have the potential to fulfil the principles of the CE. Eighteen approaches related to prefabrication, design for change, design for deconstruction, reverse logistics, waste management and closed-loop systems were found. Through an analysis of the barriers that are common among these 18 approaches, we classified them into six different categories (organisational, economical, technical, social, political and environmental). Two Sankey diagrams illustrate the interrelation between the barriers, their categories and the 18 approaches. The diagrams clearly show that most of the barriers are common to multiple approaches and that most of the barriers relate to organisational concerns. The study gives a detailed map of the barriers that would help stakeholders from the AEC sector develop strategies to overcome the current obstacles in the shift to a CE.

SIMULATION AND CONTROL OF CLOSED-LOOP SYSTEMS WITH INTERNAL RESERVES

Рассматривается задача воспроизведения в искусственных объектах способности естественных систем к самовосстановлению вследствие существования в них замкнутого круговорота вещества и энергии. Показано, что создание замкнутого жизненного цикла в системе предполагает реализацию в ней процессов восстановления ресурсов и их накопления в виде внутренних резервов, расходуемых системой в неблагоприятных условиях существования. Получена функциональная схема системы с замкнутым циклом и предложена математическая модель её функционирования в виде дискретного однородного марковского процесса без последействия. Обнаружено, что введение в систему внутреннего резервирования требует рассмотрения двух альтернативных вариантов модели системы: варианта для случая, в котором объём резервов ограничен возможностями каналов восстановления в системе, и варианта, в котором указанное ограничение отсутствует. Составлены графы состояний системы для указанных режимов функционирования и получены выражения для финальных вероятностей этих состояний. На основе полученных финальных вероятностей составлены аналитические расчётные соотношения для характеристик эффективности системы с замкнутым циклом. В качестве основной характеристики эффективности такого рода систем предлагается использовать вероятность полного функционирования системы, т.е. вероятность её работы с использованием всего объёма активных ресурсов. Представлен числовой пример, подтверждающий работоспособность предложенной модели, и проведён сопоставительный анализ вариантов управления эффективностью замкнутой системы путём изменения объёма резервов, количества процессов восстановления и интенсивности этих процессов. Выявлено доминирующее значение внутренних резервов при обеспечении заданных показателей эффективности системы с замкнутым циклом Here we consider the problem of reproduction of the ability of natural systems to self-repair in artificial objects due to the existence of a closed loop of matter and energy in them. We show that the creation of a closed life cycle in the system presupposes the implementation of the process of restoring resources and their accumulation in the form of internal reserves consumed by the system in unfavorable conditions of existence. We obtained a functional diagram of a closed-loop system and proposed a mathematical model of its functioning in the form of a discrete homogeneous Markov process without aftereffect. We found that the introduction of internal redundancy into the system requires consideration of two alternative options for the system model: the option for the case in which the volume of reserves is limited by the capabilities of the recovery channels in the system, and the option in which the specified limitation is absent. We compiled the graphs of the states of the system for the specified modes of operation and obtained expressions for the final probabilities of these states. On the basis of the obtained final probabilities, we got analytical design ratios for the characteristics of the efficiency of a system with a closed loop. As the main characteristic of the efficiency of such systems, we propose to use the probability of the complete functioning of the system, i.e. the probability of its work using the entire volume of active resources. We present a numerical example that confirms the performance of the proposed model, and carried out a comparative analysis of options for managing the efficiency of a closed-loop system by changing the volume of reserves, the number of recovery processes and the intensity of these processes. We revealed the dominant value of internal reserves while ensuring the specified performance indicators of a closed-loop system

Closed-Loop Systems for Geothermal Energy Exploitation from Hydrocarbon Wells: An Italian Case Study

Geothermal energy resources associated with disused hydrocarbon wells in Italian oilfields represent a considerable source of renewable energy. Using the information available on Italian hydrocarbon wells and on-field temperatures, two simplified closed-loop-type systems models were implemented in the Python environment and applied to a selected hydrocarbon well (Trecate4) located inside the Italian Villafortuna–Trecate field (Northwestern Italy). Considering the maximum extracted working fluid temperatures, Coaxial WBHE turned out to be a better performing technology than the U-tube version. The obtained outflow temperatures of the working fluid at the wellhead for Coaxial and U-tube WBHEs of 98.6 °C and 84 °C, respectively, are both potentially exploitable for ensuring a multi-variant and comprehensive use of the resource through its application in sectors such as the food industry, horticultural and flower fields.