Survival Augmented Patient Preference Incorporated Reinforcement Learning to Evaluate Tailoring Variables for Personalized Healthcare

In this paper, we consider personalized treatment decision strategies in the management of chronic diseases, such as chronic kidney disease, which typically consists of sequential and adaptive treatment decision making. We investigate a two-stage treatment setting with a survival outcome that could be right censored. This can be formulated through a dynamic treatment regime (DTR) framework, where the goal is to tailor treatment to each individual based on their own medical history in order to maximize a desirable health outcome. We develop a new method, Survival Augmented Patient Preference incorporated reinforcement Q-Learning (SAPP-Q-Learning) to decide between quality of life and survival restricted at maximal follow-up. Our method incorporates the latent patient preference into a weighted utility function that balances between quality of life and survival time, in a Q-learning model framework. We further propose a corresponding m-out-of-n Bootstrap procedure to accurately make statistical inferences and construct confidence intervals on the effects of tailoring variables, whose values can guide personalized treatment strategies.

Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT

In order to support a massive number of resource-constrained Internet-of-Things (IoT) devices and machine-type devices, it is crucial to design a future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating suitable network coverage expansion methodologies. To this end, this paper proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both time-switching (TS) and power-splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated to jointly optimize the throughput, harvested energy, and transmit power of a SWIPT-enabled system with the proposed hybrid scheme. In this regard, we provide two distinct ways to obtain suitable solutions based on the Lagrange dual technique and Dinkelbach method assisted convex programming, respectively, where both the approaches yield an appreciable solution within polynomial computational time. The experimental results are obtained by directly solving the primal problem using a non-linear optimizer. Our numerical results in terms of weighted utility function show the superior performance of the proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.

Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT

In order to support a massive number of resource-constrained Internet-of-Things (IoT) devices and machine-type devices, it is crucial to design future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating suitable network coverage expansion methodologies. To this end, this invited paper proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both the time-switching (TS) and power-splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated to jointly optimize the throughput, harvested energy, and transmit power of a SWIPT-enabled system with the proposed hybrid scheme. In this regard, we provide two distinct ways to obtain suitable solutions based on the Lagrange dual technique and Dinkelbach method assisted convex programming, respectively, where both the approaches yield an appreciable solution within polynomial computational-time. The experimental results are obtained by directly solving the primal problem using a non-linear optimizer. Our numerical results in terms of weighted utility function show the superior performance of proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.

DEXiAqua, a Model to Assess the Sustainability of Aquaculture Systems: Methodological Development and Application to a French Salmon Farm

Aquaculture is increasingly considered a major contributor to the growing demand for worldwide seafood production. Sustainability is becoming a key issue for aquaculture systems, with the objective to produce seafood with lower environmental impacts and that is economically viable and socially fair. In the context of the SIMTAP project, a multi-attribute model called DEXiAqua was developed. DEXiAqua uses the DEX method to assess the sustainability of aquaculture systems via indicators from technical domains and reference methods (i.e., life cycle assessment, life cycle costing, social life cycle assessment, and emergy accounting) selected and organized by the partners in the SIMTAP project. The DEX method consists of building an attribute tree that is organized to characterize a complex problem. Qualitative or quantitative indicators are measured at the end of each branch of the tree. The value of each indicator is translated into a qualitative scale for the associated attribute via threshold values. Weighted utility functions are used to build attributes from sub-attributes until the attribute of overall sustainability is reached. DEXiAqua was applied to a case study of salmon farming in France, which illustrated its ability to assess overall sustainability and help identify ways to improve the production system by identifying environmental, social, and economic hotspots. More case studies are required to apply DEXiAqua to a variety of systems with technical and contextual differences, which could result in changing attribute weights to adapt it better to different contexts.

Hybrid Active-and-Passive Relaying model for SWIPT-enabled 6G-IoT Greencom Networks

<div>In order to support a massive number of resource-constrained Internet of Things (IoT) devices and machine-type devices, it is crucial to design future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating the network extension methodologies. To this end, this letter proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both the Time-Switching (TS) and Power-Splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated for the joint optimization of throughput, harvested energy, and transmit power of a SWIPT-enabled system</div><div>with the proposed hybrid scheme, and is solved using a nonlinear optimizer. Our numerical results in terms of weighted utility function show the superior performance of proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.</div>

Hybrid Active-and-Passive Relaying model for SWIPT-enabled 6G-IoT Greencom Networks

<div>In order to support a massive number of resource-constrained Internet of Things (IoT) devices and machine-type devices, it is crucial to design future beyond 5G/6G wireless networks in an energy-efficient manner while incorporating the network extension methodologies. To this end, this letter proposes a novel two-hop hybrid active-and-passive relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both the Time-Switching (TS) and Power-Splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated for the joint optimization of throughput, harvested energy, and transmit power of a SWIPT-enabled system</div><div>with the proposed hybrid scheme, and is solved using a nonlinear optimizer. Our numerical results in terms of weighted utility function show the superior performance of proposed hybrid scheme over passive repeater-only and active relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems with the fixed-TP.</div>

Hybrid Backscatter and Relaying Scheme for 6G Greencom IoT Networks with SWIPT

<div>In order to support the massive number of resource-constrained Internet of Things (IoT) devices and machine-type devices, it is crucial to design future beyond 5G/6G wireless networks in an energy-efficient manner. To this end, this letter proposes a novel two-hop hybrid backscatter-and-relaying scheme to facilitate simultaneous wireless information and power transfer (SWIPT) considering both the Time-Switching (TS) and Power-Splitting (PS) receiver architectures, while dynamically modelling the involved dual-hop time-period (TP) metric. An optimization problem is formulated for the joint optimization of throughput, harvested energy, and transmit power of a SWIPT-enabled system with the proposed hybrid scheme, and is solved using a nonlinear optimizer. Our numerical results in terms of weighted utility function show the superior performance of proposed hybrid scheme over backscatter-only and relay-only schemes, while also depicting their individual performance benefits over the corresponding benchmark SWIPT systems designed with the fixed-TP.</div>