DePAint: A Decentralized Safe Multi-Agent Reinforcement Learning Algorithm considering Peak and Average Constraints

The field of safe multi-agent reinforcement learning, despite its potential applications in various domains such as drone delivery and vehicle automation, remains relatively unexplored. Training agents to learn optimal policies that maximize rewards while considering specific constraints can be challenging, particularly in scenarios where having a central controller to coordinate the agents during the training process is not feasible. In this paper, we address the problem of multi-agent policy optimization in a decentralized setting, where agents communicate with their neighbors to maximize the sum of their cumulative rewards while also satisfying each agent's safety constraints. We consider both peak and average constraints. In this scenario, there is no central controller coordinating the agents and both the rewards and constraints are only known to each agent locally/privately. We formulate the problem as a decentralized constrained multi-agent Markov Decision Problem and propose a momentum-based decentralized policy gradient method, DePAint, to solve it. To the best of our knowledge, this is the first privacy-preserving fully decentralized multi-agent reinforcement learning algorithm that considers both peak and average constraints. We also provide theoretical analysis and empirical evaluation of our algorithm in various scenarios and compare its performance to centralized algorithms that consider similar constraints

New insight in neuropharmacological activities of Dioscorea alata

The purpose of our present study was to evaluate the neuropharmacological activities of the methanolic extract of Dioscorea alata tuber using mice model. Neuropharmacological activities of this extract were determined using standard behavioral mice models like- elevated plus maze and hole board test for anxiolytic activity; open field, hole cross, tail suspension and force swimming test for exploratory activities of mice. Our result showed that D. alata extract possesses significant dose dependent indicative of neophilia in elevated plus maze and hole board test. The time spent in open arm was 28±0.95 seconds (for 250 mg/kg extract feeding group) and 82±2.02 seconds (for 500 mg/kg extract feeding group); whereas the control groups spent time was 19.0±2.17 seconds. In addition, the crude also showed a significant dose dependent suppression of exploratory activity by decreasing serotonin level of swiss albino mice in open field, hole cross, tail suspension and force swimming test respectively at both doses (

Neuropharmacological activity of the crude ethanolic extract of Syzygium aromaticum flowering bud

Backgroud: Present study was designed to assess the possibility of in-vivo neuropharmacological effects of the ethanolic extract of Syzygium aromaticum flowering buds by using behavioral models of mice.Methods: Anxiolytic effects of the extract were assessed using open field test (OFT), hole cross test (HCT), elevated plus maze (EPM), and hole board test (HBT) respectively; while antidepressant properties were determined using forced swimming test (FST), and tail suspension test (TST). Finally thiopental sodium (TS)-induced sleeping time test helped us to evaluate the sedative-hypnotic potential of the extract.Results: In OFT and HCT, the movement of the mice decreased significantly (*p<0.005) for the extract treated groups when compare to control. This decrease indicates the suppression of locomotor activities of mice (from 1st-5th observation periods). Moreover, the increase of the spending time in EPM open arm, and head dipping in HBT endorsed the anxiolytic-like behavior of the extract. In FST and TST, S. aromaticum extract significantly (*p<0.05, **p<0.001) reduced the immobility time of the mice. Approx. 29% and 34% reduction of the immobility time were found in FST for 250 mg/kg, and 500 mg/kg b.w. doses respectively, which clearly indicates the presence of the antidepressant compounds in extract. Finally, TS-induced sleeping time test confirmed the potency of the sedative response of the extract (sleeping duration were 45.4±2.6 minutes for control, whereas 87.0±1.79 minutes for 500 mg/kg b.w. extract treated group). The observed neurological response may be due to binding of any phytoconstituent with gamma-amino-butyric acid (GABAA) or benzodiazepine (BZD) receptors.Conclusion: Our study results suggest that the ethanolic extract of S. aromaticum possess remarkable sedative, antidepressant and anxiolytic activities with a demand of further investigation for the drug development program

Lifetime Maximization of Sensor Networks Through Optimal Data Collection Scheduling of Mobile Sink

The problem of maximizing lifetime of a sensor network is still challenging mainly due to the stringent delay-deadline of real-time applications and heterogeneity of sensor devices. The problem is further complicated when the network contains many obstacles. In maximizing network lifetime, existing literature works either merely address issues of application delay-deadline and presence of obstacles, or analyze primitive data collection approaches for such an environment. In this paper, we formulate optimal data collection schedule of a mobile sink in an obstructed sensor network as a mixed-integer linear programming (MILP) problem. The proposed data collection scheduling finds an optimal set of rendezvous nodes over a preformed Starfish routing backbone, and corresponding sojourn duration so as to maximize the network lifetime while maintaining delay-deadline constraint in an obstructed network. The proposed Starfish-scheduling ensures a loop-free traveling path for a mobile sink across the network. The results of performance evaluation, performed in network simulator-2, depict the suitability of Starfish scheduling as it outperforms state-of-the-art-works in terms of extending network lifetime and data delivery throughput as well as reducing average end-to-end delay

Manual on financial mechanism for the health facilities: Introducing pay-for-performance approach to increase utilization of maternal, newborn, and child health services in Bangladesh

The Population Council initiated an operations research study to test two Pay-for-Performance (P4P) strategies to improve maternal, newborn, and child health (MNCH) services in Bangladesh in 2010. The P4P study is being implemented as part of the two ongoing MNCH and maternal and newborn health (MNH) projects of the United Nations Children’s Fund (UNICEF) implemented by the Directorate General of Health Services, Government of Bangladesh. The study has been testing two strategies. The first introduces incentives tied with performance for motivating service providers to improve the quantity as well as quality of services, and enable poor pregnant women, and mothers of newborns and under-five children to access services by reducing out-of-pocket costs for medicines, transportation, and incidental costs through subsidized coupons. The second constitutes a P4P scheme for providers only. This manual, developed by the Council, describes the purposes, processes, and appropriate documents that will enable facilities and P4P and/or Coupon Committees to opportunely receive and utilize funds under the P4P and coupon mechanism to improve MNCH services

抗菌ペプチド・マガイニン２が誘起する脂質膜中のポア形成に対する膜電位の役割

博士（理学）doctoral創造科学技術大学院静岡大学甲第1135号non

Link Expiration Time-Aware Routing Protocol for UWSNs

We propose a link expiration time-aware routing protocol for UWSNs. In this protocol, a sending node forwards a data packet after being sure that the packet reaches the forwarding node, and acknowledgment is returned to the sending node after receiving the data packet. Node mobility is handled in the protocol through the calculation of the link expiration time and sending the packet based on the link expiration time. Although the protocol employs two types of control packet, it provides less energy consumption and at the same time is providing better reliability of packets reaching to the destination because of using acknowledgement packet. The forwarding decision of node is taken by applying Bayes’ uncertainty theorem. We use depth, residual energy, and distance from the forwarding node to the sending node as evidence in Bayes’ theorem. In this protocol, we use the concept of expert systems ranking potentially true hypothesis. Extensive simulation has been executed to endorse better performance of the proposed protocol