Abscisic acid (ABA) induces production of reactive oxygen species (ROS) and nitric oxide (NO), elevation of the cytosolic free calcium ion concentration ([Ca(2+)](cyt)) and cytosolic pH (pH(cyt)), and activation of S-type anion channels in guard cells, causing stomatal closure. To investigate whether Arabidopsis Two pore channel 1 (AtTPC1) that encodes the slow vacuolar (SV) channel is involved in stomatal closure, we examined stomatal movements and mobilization of second messengers in the attpc1-2 loss-of-function mutant in response to ABA, methyl jasmonate (MeJA) and Ca(2+). Both ABA and MeJA elicited production of ROS and NO, [Ca(2+)](cyt) oscillations, cytosolic alkalization and activation of S-type anion channel currents to lead to stomatal closure in the attpc1-2 mutant as well as the wild type. Unlike the wild type, in the attpc1-2 mutant exogenous Ca(2+) neither induced stomatal closure nor activated plasma membrane S-type anion channel currents despite [Ca(2+)](cyt) elevation. These results indicate that AtTPC1 functions in response to external Ca(2+) but not to ABA and MeJA in Arabidopsis guard cells and suggest that AtTPC1 could be involved in priming of plasma membrane S-type anion channels by external Ca(2+) in Arabidopsis guard cells.

Thioglucoside glucohydrolase (myrosinase), TGG1, is a strikingly abundant protein in Arabidopsis guard cells. We investigated responses of tgg1-3, tgg2-1 and tgg1-3 tgg2-1 mutants to abscisic acid (ABA) and methyl jasmonate (MeJA) to clarify whether two myrosinases, TGG1 and TGG2, function during stomatal closure. ABA, MeJA and H(2)O(2) induced stomatal closure in wild type, tgg1-3 and tgg2-1, but failed to induce stomatal closure in tgg1-3 tgg2-1. All mutants and wild type showed Ca(2+)-induced stomatal closure and ABA-induced reactive oxygen species (ROS)production. A model is discussed in which two myrosinases redundantly function downstream of ROS production and upstream of cytosolic Ca(2+) elevation in ABA and MeJA signaling in guard cells.

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Abscisic acid (ABA)- and methyl jasmonate (MeJA)-induced stomatal closure are accompanied by cytosolic alkalization in guard cells. However, it remains to be clarified how the alkalization functions in not only ABA signaling but also MeJA. We investigated cytosolic alkalization in guard cells during ABA-, MeJA- and Ca(2+)-induced stomatal closure of wild type, abi1-1, abi2-1, ost1-2 and coi1 using a pH-sensitive fluorescent dye, BCECF-AM. ABA induced cytosolic alkalization in guard cells of wild-type and coi1 but not in ost1-2 guard cells whereas MeJA elicited cytosolic alkalization in wild-type and ost1-2 guard cells but not in coi1. Neither ABA nor MeJA induced cytosolic alkalization in abi1-1 and abi2-1 guard cells. Exogenous Ca(2+) induced stomatal closure accompanied by cytosolic alkalization in guard cells of wild-type, abi1-1, abi2-1, ost1-2 and coi1 plants. An agent to acidify cytosol, butyrate, suppressed Ca(2+)-induced cytosolic alkalization and ABA-, MeJA- and Ca(2+)-induced cytosolic Ca(2+) oscillation in wild-type guard cells to prevent stomatal closure. These results indicate that cytosolic alkalization and cytosolic Ca(2+) oscillation coordinately function in ABA and MeJA signaling in Arabidopsis guard cells.

This paper explores the design and development of a class of robust diver-following algorithms for autonomous underwater robots. By considering the operational challenges for underwater visual tracking in diverse real-world settings, we formulate a set of desired features of a generic diver following algorithm. We attempt to accommodate these features and maximize general tracking performance by exploiting the state-of-the-art deep object detection models. We fine-tune the building blocks of these models with a goal of balancing the trade-off between robustness and efficiency in an on-board setting under real-time constraints. Subsequently, we design an architecturally simple Convolutional Neural Network (CNN)-based diver-detection model that is much faster than the state-of-the-art deep models yet provides comparable detection performances. In addition, we validate the performance and effectiveness of the proposed diver-following modules through a number of field experiments in closed-water and open-water environments.

Software-Defined Networking (SDN) and Blockchain are leading technologies used worldwide to establish safe network communication as well as build secure network infrastructures. They provide a robust and reliable platform to address threats and face challenges such as security, privacy, flexibility, scalability, and confidentiality. Driven by these assumptions, this paper presents an optimized energyefficient and secure Blockchain-based software-defined IoT framework for smart networks. Indeed, SDN and Blockchain technologies have proven to be able to suitably manage resource utilization and to develop secure network communication across the IoT ecosystem. However, there is a lack of research works that present a comprehensive definition of such a framework that can meet the requirements of the IoT ecosystem (i.e. efficient energy utilization and reduced end-to-end delay). Therefore, in this research, we present a layered hierarchical architecture for the deployment of a distributed yet efficient Blockchain-enabled SDN-IoT framework that ensures efficient cluster-head selection and secure network communication via the identification and isolation of rouge switches. Besides, the Blockchain-enabled flow-rules record keeps track of the rules enforced in the switches and maintains the consistency within the controller cluster. Finally, we assess the performance of the proposed framework in a simulation environment and show that it can achieve optimized energy-utilization, end-to-end delay, and throughput compared to considered baselines, thus being able to achieve efficiency and security in the smart network.

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