Pregnant Sprague-Dawley rats received a single oral dose of 0, 20, 60, or 180 ng/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin on day 8 of gestation. Each litter contributed a single male-female pair trained to press a lever to obtain food pellets under two operant behavior procedures. Initially, each lever press was reinforced. The fixed-ratio (FR) requirement was then increased every four sessions f...

Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous work has shown that hierarchically organizational control is an effective way of coordinating DRL to improve its speed, quality, and likelihood of convergence. In this paper, we develop a distributed, negotiation-based...

Localization is a basic issue for underwater acoustic networks (UANs). Currently, most localization algorithms only perform well in one-hop networks or need more anchors which are not suitable for the underwater environment. In this paper, we proposed a double rate localization algorithm with one anchor for multi-hop underwater acoustic networks (DRL). The algorithm firstly presents a double ra...

background: high level radiation areas have been recognized on various parts of the earth. mahallat hot spring region is one of these areas. study of exposure in these areas can be helpful in investigating the effects of ionizing radiation. internal and external exposure to the staff was studied. materials and methods: used materials and instruments include: rss-112 ionizing chamber for environ...

Deep reinforcement learning (DRL) has shown incredible performance in learning various tasks to the human level. However, unlike human perception, current DRL models connect the entire low-level sensory input to the state-action values rather than exploiting the relationship between and among entities that constitute the sensory input. Because of this difference, DRL needs vast amount of experi...

The Drosophila Derailed (DRL) receptor tyrosine kinase (RTK) controls key guidance events in the developing nervous system and mesoderm. Like other members of the "related to tyrosine kinases" (RYK) subfamily of RTKs, DRL has several highly unusual amino acid substitutions within the catalytic domain, raising the possibility that members of this subfamily are catalytically inactive. To test the...

We propose a generic distributed learning framework for robust statistical learning on big contaminated data. The Distributed Robust Learning (DRL) framework can reduce the computational cost of traditional robust learning methods by several orders. We provide a sharp analysis on the robustness of DRL, showing that DRL not only preserves the robustness of base robust learning methods, but also ...

Abstract Background The concept of diagnostic reference level (DRL) is considered a regular method to optimize radiation protection in imaging system. objective implementing for dose produce high-quality images by applying minimum based on the As Low Reasonably Achievable (ALARA) principle. Therefore, this study aimed evaluate status radiology wards educational hospitals affiliated with Birjand...

The use of dynamically reconfigurable logic (DRL) in the design of embedded systems has added a new dimension to the hardware/software co-synthesis problem. The spatial computing advantage and silicon reuse offered by DRL comes at the cost of reconfiguration latency which has to be effectively managed in order to optimize the system performance and power consumption. The initial attempts at lev...

BACKGROUND Animal studies have shown that exposure to common, low-level environmental contaminants [e.g., polychlorinated biphenyls (PCBs), lead] causes excessive and inappropriate responding on intermittent reinforcement schedules. The Differential Reinforcement of Low Rates task (DRL) has been shown to be especially sensitive to low-level PCB exposure in monkeys. OBJECTIVES We investigated ...