Point-of-care cell therapy manufacturing; it’s not for everyone

The use of cellular therapies to treat cancer, inherited immune deficiencies, hemoglobinopathies and viral infections is growing rapidly. The increased interest in cellular therapies has led to the development of reagents and closed-system automated instruments for the production of these therapies. For cellular therapy clinical trials involving multiple sites some people are advocating a decentralized model of manufacturing where patients are treated with cells produced using automated instruments at each participating center using a single, centrally held Investigational New Drug Application (IND). Many academic centers are purchasing these automated instruments for point-of-care manufacturing and participation in decentralized multiple center clinical trials. However, multiple site manufacturing requires harmonization of product testing and manufacturing in order to interpret the clinical trial results. Decentralized manufacturing is quite challenging since all centers should use the same manufacturing protocol, the same or comparable in-process and lot release assays and the quality programs from each center must work closely together. Consequently, manufacturing cellular therapies using a decentralized model is in many ways more difficult than manufacturing cells in a single centralized facility. Before an academic center decides to establish a point-of-care cell processing laboratory, they should consider all costs associated with such a program. For many academic cell processing centers, point-of-care manufacturing may not be a good investment.

Dynamo in tesla turbine, based on recyclable materials, for decentralized energy generation and recharge batteries: system evaluations

Nowadays the search for new forms of energy generation is one of the great challenges of humanity. Decentralized energy production as well as material recycling, in order to obtain low-cost environmental gains, are extremely important points, as they are issues that must be evaluated in parallel with sustainable development, being extremely discussed and disseminated for their relevance and importance, since the main focus certainly corresponds the environmental preservation of the planet. In view of this theme, in the present work, a prototype was built using Tesla turbine and a dynamo couplet, aiming at the decentralized energy generation model, for the recharge of lead-acid batteries concomitantly with the challenge of reaching an innovative and unprecedented device with economic and environmental gains. The developed system was made and structured from the manufacture of various accessories obtained from recyclable materials attached to its structure, through the improvement of the physical model during its manufacture until the performance of experimental tests investigating its functionality. The results show that the projected system responded significantly to what was proposed, where the dynamo generated current for the system, providing 12 V in the physical model, recharging the battery. In view of the results obtained, it is believed that the prototype has great potential, in a characteristic line and direction, where with the improvement of the structure and diversification of components it is possible to become a new proposal, that is, an innovative device that meets expectations at an affordable price, being a decentralized model of energy generation and environmentally friendly.

Integrating Blockchain Technology with Internet of things to Efficiency

The research study focused on integrating blockchain technology with the internet of things. The study is necessitated by the need to come up with practical and feasible means to improve the accuracy, accountability and trust among various parties involved in blockchain transactions. The research recognizes the fact that there has been an increasing using of the cryptocurrency in the global market. This has lead to the emergence of blockchain, which is one of the disruptive technologies in the information and technology sector. The research study indicates that there is a need to improve on the architecture of blockchain and the IoT system. It shows that there is a need to develop a new model to improve its efficiency and accuracy. This research paper recommends the use of decentralized model to enhance the efficiency of the integration of the blockchain technology and IoT.

126. Outpatient Antimicrobial Stewardship Utilizing a Decentralized Model

Background The majority of human antimicrobial utilization occurs in the outpatient setting. Despite being mainly viral in etiology, upper respiratory tract infections (URIs) were the most common indication for outpatient antimicrobial prescriptions at our institution. Methods Through our electronic health record (EHR), we were able to determine our rate of antibiotic prescriptions for inappropriate URI diagnosis at our primary care practice sites. We selected staff volunteers from each our primary care practice sites to serve as stewardship champions. They were given training in stewardship best practices, and an URI stewardship toolkit which included viral URI prescription pad, EHR order panel, and patient education signage. They were tasked with providing education and feedback to their practice sites. We meet with them on a monthly basis to disseminate prescribing data and education. They also provided feedback from practice sites to the stewardship committee. Results Our decentralized model was put in place in November 2020. In the 6 months prior to the intervention, the average prescribing rate was 29.1%. In the 6 months after the intervention, the average prescribing rate decreased by 15% to 24.8%. During the intervention phase, there was an increase in number of non-COVID URIs diagnosed at our primary care sites. Temporal Trend in Inappropriate Antibiotics Prescribing Rates for Viral URIs Pre- and Post- Intervention Inappropriate antibiotic prescribing rate for viral upper respiratory tract infections from May 2020 until May 2021. Intervention started in December 2021 (arrow). Pre-intervention average was 29.1%. Post-intervention age was 24.8% which is a 15% decline in prescribing rate. Viral Upper Respiratory Infections Visits The total number of visits for presumed viral upper respiratory infections to primary care sites from May 2020 until May 2021. The majority of COVID-19 precautions in the area expired at the end of March 2021. Conclusion We have been able to lower our inappropriate prescriptions for URIs utilizing a decentralized model of stewardship champions. This result was especially notable as the intervention phase corresponded with the end of COVID-19 precautions and an increase in non-COVID URIs diagnosed. The advantage of this approach includes an advocate embedded at each practice site who is familiar with the opportunities and challenges of the site, and a two-way flow of information from practice sites to the stewardship committee. This model provided additional benefit during the COVID-19 pandemic as the ability of centralized staff to travel to off campus clinic sites was curtailed. Disclosures All Authors: No reported disclosures

Multi-Objective Decentralized Model Predictive Control for Inverter Air Conditioner Control of Indoor Temperature and Frequency Stabilization in Microgrid

Microgrid (MG) is a novel concept for a future distribution power system that enables renewable energy sources (RES). The intermittent RES, such as wind turbines and photovoltaic generators, can be connected to the MG via a power electronics inverter. However, the inverter interfaced RESs reduce the total inertia and damping properties of the traditional MG. Consequently, the system exhibits steeper frequency nadir and the rate of change of frequency (RoCoF), which may degrade the dynamic performance and cause the severe frequency fluctuation of the system. Smart loads such as inverter air conditioners (IACs) tend to be used for ancillary services in power systems. The power consumption of IACs can be regulated to suppress frequency fluctuation. Nevertheless, these IACs, regulating power, can cause the deviation of indoor temperature from the temperature setting. The variation in indoor temperature should be controlled to fulfill residential comfort. This paper proposes a multi-objective decentralized model predictive control (DMPC) for controlling the power consumption of IACs to reduce MG frequency fluctuation and control the variation in indoor temperature. Simulation results on the studied microgrid with the high penetration of wind and photovoltaic generator demonstrate that the proposed DMPC is able to regulate frequency deviation and control indoor temperature deviation as a user preference. In addition, the DMPC has a superior performance effect to the proportional-integral (PI) controller in terms of reducing frequency deviation, satisfying indoor temperature preferences, and being robust to the varying numbers of IACs.

Distributed Address Table (DAT): A Decentralized Model for End-to-End Communication in IoT

To achieve a fully connected network in Internet of Things (IoT) there are number of challenges that have to be overcome. Among those, a big challenge is how to keep all of the devices accessible everywhere and every time. In the IoT network, the assumption is that each IoT device can be reached by any client at any given time. In practice, this is not always possible and without a proper mechanism the nodes behind a NAT are unable to communicate with each other directly, and their addresses have to be shared through a trusted third party. This challenge becomes harder by taking into consideration that most NAT traversal approaches have been developed prior to rising of the IoT, without taking into account the constrained nature of the participating devices and mostly depend on a centralized entity. In this paper we proposed the Distributed Address Table (DAT), a decentralized, secure and lightweight address distribution model that allows any two nodes to get the addresses of the other end without relying on a trusted third party. Structured Peer-to-Peer (P2P) overlay by utilizing Distributed Hash Table (DHT) technique is generated as its underlying communication scheme to ensure that all participating devices are accessible at any given time. This is achieved through simple, yet secure and efficient decentralized model. The DAT adopts the edge/fog computing paradigms to ensure a decentralized address distribution. The results showed that the proposed model is efficient. In addition, the security properties of the proposed model have been defined and proved.

Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts

This paper investigates the model-based methods in multi-agent reinforcement learning (MARL). We specify the dynamics sample complexity and the opponent sample complexity in MARL, and conduct a theoretic analysis of return discrepancy upper bound. To reduce the upper bound with the intention of low sample complexity during the whole learning process, we propose a novel decentralized model-based MARL method, named Adaptive Opponent-wise Rollout Policy Optimization (AORPO). In AORPO, each agent builds its multi-agent environment model, consisting of a dynamics model and multiple opponent models, and trains its policy with the adaptive opponent-wise rollout. We further prove the theoretic convergence of AORPO under reasonable assumptions. Empirical experiments on competitive and cooperative tasks demonstrate that AORPO can achieve improved sample efficiency with comparable asymptotic performance over the compared MARL methods.