Task offloading optimization in Mobile Edge Computing based on Deep Reinforcement Learning

The Cloud Computing (CC) paradigm has risen in recent years as a solution to a need for computation and battery constrained User Equipment (UE) to run increasingly intensive computation tasks. Nevertheless, given the centralized nature of the CC paradigm, this option introduces significant network congestion problems and unpredictable communication delays unsuitable for real-time applications. In order to cope with these problems, the Mobile Edge Computing (MEC) concept has been introduced, which proposes to bring computation resources closer to the edge of the mobile networks in a distributed way. However, given that these edge computation resources are limited, this paradigm comes with its set of challenges that need to be solved in order to make it viable. This work proposes to innovate by presenting a network management agent capable of making offloading decisions from a heterogeneous network of UEs to a heterogeneous network of MEC servers. This agent is the orchestrator of a group of 5G Small Cells (SCeNBs), enhanced with computation and storage capabilities. In order to solve this high complexity problem, an Advantage Actor-Critic (A2C) agent is implemented and tested against several baselines. The proposed solution is shown to be at the baselines by making intelligent decisions taking into account computation, battery, delay and communication constraints ignored by the baselines. The solution is also shown to be scalable, data-efficient, robust, stable and adjustable to address not only the overall system performance but also to take into account the worst-case scenario.</p

Additional file 1: of Improving the delivery and efficiency of fungus-impregnated cloths for control of adult Aedes aegypti using a synthetic attractive lure

PET Traps with black cloths, adhesive films and attractive lures. Figure S1 PET traps. a PET trap with black cloth only. b PET trap with adhesive film and attractive lure. c PET trap with black cloth covered in adhesive film and attractive lure attached to the base of the cloth. (PDF 424 kb

<i>In vitro</i> test systems supporting the development of improved pest control methods: a case study with chemical mixtures and bivalve biofoulers

<p>Using the bivalve macrofouler <i>Corbicula fluminea</i>, the suitability of <i>in vitro</i> testing as a stepping stone towards the improvement of control methods based on chemical mixtures was addressed in this study. <i>In vitro</i> cholinesterase (ChE) activity inhibition following single exposure of <i>C. fluminea</i> tissue to four model chemicals (the organophosphates dimethoate and dichlorvos, copper and sodium dodecyl phosphate [SDS]) was first assessed. Consequently, mixtures of dimethoate with copper and dichlorvos with SDS were tested and modelled; mixtures with ChE revealed synergistic interactions for both chemical pairs. These synergic combinations were subsequently validated <i>in vivo</i> and the increased control potential of these selected combinations was verified, with gains of up to 50% in <i>C. fluminea</i> mortality relative to corresponding single chemical treatments. Such consistency supports the suitability of using time- and cost-effective surrogate testing platforms to assist the development of biofouling control strategies incorporating mixtures.</p

Additional file 1: of Neem oil increases the efficiency of the entomopathogenic fungus Metarhizium anisopliae for the control of Aedes aegypti (Diptera: Culicidae) larvae

Table S1. Percentage conidial germination at 16h post-inoculation on culture media. Figure S1. Radial growth rates of Metarhizium anisopliae when formulated in different concentrations of neem oil over a 7 day period. (DOC 63 kb

Appendix C. A table presenting the volatile compounds collected from headspace of leaf litter of Ageratina adenophora of different regional origins.

A table presenting the volatile compounds collected from headspace of leaf litter of Ageratina adenophora of different regional origins

Appendix A. Figures summarizing seedling length and germination data of Bidens biternata and Bambusa arundinacea grown in the presence or absence of Ageratina adenophora leaf litter.

Figures summarizing seedling length and germination data of Bidens biternata and Bambusa arundinacea grown in the presence or absence of Ageratina adenophora leaf litter

Appendix D. Tables for two-way ANOVAs for the effects of region (Mexico, China, or India) and population on the concentration of six selected terpenes from Ageratina adenophora.

Tables for two-way ANOVAs for the effects of region (Mexico, China, or India) and population on the concentration of six selected terpenes from Ageratina adenophora

Appendix B. A figure presenting volatiles collected from headspace of 200-mg air-dried leaf material of three different origins.

A figure presenting volatiles collected from headspace of 200-mg air-dried leaf material of three different origins

Clinical classification of seropositive dogs in three regions in the extreme west of Paraná state, Southern Brazil.

<p>OR: Odds Ratio.–Non observed date. * seropositive dogs in ELISA and DPP tests /total of dogs with clinical signals.</p

Additional file 2: TableS1. of Lapachol, a compound targeting pyrimidine metabolism, ameliorates experimental autoimmune arthritis

LAP and LAP sodium salt pharmacokinetic parameters determined by noncompartmental and compartmental approaches after i.v. administration of 2 mg/kg in Wistar rats. (PDF 93 kb