Objectives: Our aim was to identify the pathogen that caused stem canker on royal poinciana and evaluate the efficacy of antagonistic Actinomycetes in vitro, in vivo under greenhouse and naturally infested plants. Methodology: DNA isolation, PCR, Phylogenetic analysis, Disease assays and Pathogenicity tests. Results: The fungus DSM 109897, was recovered from tissues, this was confirmed by our laboratory studies. Phylogenetic analyses of the translation elongation factor 1-a (TEF1-?) of N. dimidiatum from the UAE with reference specimens of Botryosphaeriaceae family validated the identity of the pathogen. Three isolates, Streptomyces rochei UAE2, S. coelicoflavus UAE1 and S. antibioticus UAE1, significantly inhibited N. dimidiatum in vitro. "apple bioassay" is useful when performing biocontrol treatment studies. Under field conditions, S. antibioticus proved to be the most effective against N. dimidiatum. Conclusion: Our data suggest that the causal agent of canker on royal poinciana in the UAE is N. dimidiatum.
Objectives: Our aim in this study was to identify the pathogen and evaluate the efficacy of fungicides in vitro and in vivo under greenhouse and naturally infested plants. Methodology: DNA isolation, PCR, Phylogenetic analysis, Disease assays and Pathogenicity test. Results: The fungus DSM 109897, was recovered from tissues; this was confirmed by studies. Phylogenetic analyses of the translation elongation factor 1-a (TEF1-α) of N. dimidiatum from the UAE with reference specimens of Botryosphaeriaceae family validated the identity of the pathogen. The chemical fungicides Protifert®, Cidely® Top and Amistrar® Top significantly inhibited mycelial growth and reduced conidial numbers of N. dimidiatum. "apple bioassay" is useful when performing fungicide treatment studies. Under field conditions, Cidely® Top proved to be the most effective fungicide against N. dimidiatum. Conclusion: Our data suggest that the causal agent of canker on royal poinciana in the UAE is N. dimidiatum.
The main objective of this work was to isolate halophilic actinobacteria from rhizospheric soils of S. bigelovii and to analyse the plant growth promoting (PGP) capabilities by considering these actinobacteria as biological inoculants on seawater-irrigated S. bigelovii plants. Streptomyces chartreusis (Sc), S. tritolerans (St) and S. rochei(Sr) are the three isolates used to determine the effects on S. bigelovii in the greenhouse. The experiments conducted with the three isolates individualy and in combination to apply on S. bigelovii. Plants treated with Sc, St and Sr resulted in 46.1%, 60.0% and 69.1% increase in seed yield, respectively, when compared to control plants. The results also showed a significant (P<0.05) increases in the levels of photosynthetic pigments, endogenous auxins but a reduction in the levels of ACC in tissues of plants inoculated with Sc/St/Sr. Final results showed that the consortium of isolates was the most effective treatment on S. bigelovii growth.
Citrullus colocynthis, a native plant to the Arabian deserts, has several medicinal and economic benefits that enable it to be a potential cash crop. This importance of the species necessitates understanding the dormancy and environmental factors that control germination processes. In the UAE, we noticed big variations in fruit and seed size and morphology between individuals of the same population. Here, we assessed the impacts of seed collection time, the temperature of incubation on salinity tolerance during the seed germination stage of individuals (hereafter referred to as accession) growing in the botanical garden of the University of Sharjah. Results showed significant effects of all factors (accession, collection time, temperature, and salinity) and their interactions on germination percentage. Summer seeds germinated significantly greater and tolerated higher salinity than winter seeds. No germination occurred at lower temperatures, but seeds germinated more than 96% at moderate and higher temperatures.
This paper presents two candidate optimal controllers based on deep learning (DL) technique for physical safety purpose of autonomous cars. The two DL controller's frameworks are based on a Greedy layer-wise (GLW) and a Long Short-Term Memory (LSTM) neural network (NN) algorithms and are utilized to control an active suspension system (ASS). The DL controllers are trained with the dataset generated, at a selected worst-case road profile, from an optimal LQR controller. The applied training methodology allows to develop an effective DL- NN structure capable of providing control that tackles the various operating conditions during handling manoeuvres and isolate/protect the passengers, payload, and expensive sensors from road disturbances. Both trained networks were tested under parameters uncertainties of a real internal road profile. The results have proved that the developed DL based controllers, LSTM and GLW models, outperform the optimal LQR controller in term of minimizing the sprung mass acceleration.
This paper proposes a new two-link compliant manipulator design for safe human-robot interaction. The manipulator consists of two compliant joints, where each joint is basically a discrete variable stiffness actuator (DVSA). The DVSA offers four different stiffness levels (i.e., 6, 50, 100, and 180 [N-m/rad]) for the joint and can shift to any of the given stiffness values instantly (i.e., in 0.048 s), during operation, upon a change in the end-effector's load. First, the 3D model of this manipulator is developed. Then, a prototype of the two-link manipulator with compliant DVSA-joints is developed.
In this paper, a new multi-robot Adaptive Search Space Coverage Path Planning (multi-robot ASSCPP) approach is proposed to explore and cover 3D large structures using a decentralized multi-robot system. The multi-robot ASSCPP approach divides the coverage load on a team of robots to decrease the CPP execution time and simultaneously achieve high coverage. It utilizes the existence of the reference mesh model to divide it into segments based on surface area. Then it generates viewpoints adaptively exploiting the sensor's noise models to direct the search towards areas with low resolution and low coverage. The coverage paths are then generated using a heuristic function that evaluates the traveling distance and the quality of the model. In the multi-robot system, the generated coverage paths are executed on each robot starting at their allocated path starting position. Experiments were conducted in a realistic robotic simulator to test the validity of the proposed algorithm.
Robustly tracking a person of interest in the crowd with a robotic platform is one of the cornerstones of human-robot interaction. The robot platform which is limited by the computational power, rapid movements and occlusions of target requires an efficient and robust framework to perform tracking. This paper proposes a deep learning framework for tracking a person using a mobile robot with stereo camera. The proposed system detects a person based on its head, then utilizes the low cost, high speed regression network based tracker to track the person of interest in real time. The visual servoing of the mobile robot has been designed using PID controller which utilizes tracker output and depth estimation of the person in subsequent frames, hence providing smooth and adaptive movement of the robot based on target movement. The proposed system has been tested in real environment, thus proving its effectiveness.
In this paper, we propose a robotic gripper that utilizes a soft finger based on the Fin Ray Effect and a neuromorphic vision-based sensor to obtain tactile information from the finger. The sensor captures tactile information by observing brightness intensity changes of markers that are placed internally inside the finger. The tactile information is processed to detect incipient slip at a rate of 500?s.
The analysis, implementation and control of modular multi-copter structures, capable of coordinated flight, are investigated in this work. Graph theory is employed in order to generically define arbitrary multi-copter assemblies and extract dynamic properties. The proposed controller works by viewing each copter as an agent capable of providing a total thrust force and yaw torque, and can be implemented on most commercial flight control units, using standardized methods. Experimental studies are offered to show positive initial results, while future research goals are discussed, taking into account structural flexibilities and moving towards flexible aerial robots.
