Toolgraph Design of Optimal and Feasible Control Strategies for Time-Varying Dynamical Systems

The paper presents a new method for designing optimal and feasible control strategies for time-variant dynamical processes. The key point of the presented idea lies in utilizing a flow graph structure for representing pertinent properties of the autonomous dynamics of a given dynamical process in a time-and-state space, which is composed of certain elementary segments. The structure is referred to as a time-and-state space toolgraph. In the procedure, each segment of the temporary state space is assigned a node of the time-and-state space toolgraph. The flow values are proportional to the cost of driving the operational point of the dynamical process between the centers of adjacent segments. Any of the discrete optimization algorithms can be applied to search for a cheapest path connecting the initial and terminal points of the sought optimal piecewise-linear trajectory of the operational points in the considered time-and-state space. Additional assumptions or restrictions concerning arbitrary forbidden zones for the operational points can be easily taken into account. In such cases the nodes representing the segments partially or entirely belonging to the finite forbidden zones are deposed from the toolgraph structure

In Vivo Retinal Pigment Epithelium Imaging using Transscleral Optical Imaging in Healthy Eyes.

To image healthy retinal pigment epithelial (RPE) cells in vivo using Transscleral OPtical Imaging (TOPI) and to analyze statistics of RPE cell features as a function of age, axial length (AL), and eccentricity. Single-center, exploratory, prospective, and descriptive clinical study. Forty-nine eyes (AL: 24.03 ± 0.93 mm; range: 21.9-26.7 mm) from 29 participants aged 21 to 70 years (37.1 ± 13.3 years; 19 men, 10 women). Retinal images, including fundus photography and spectral-domain OCT, AL, and refractive error measurements were collected at baseline. For each eye, 6 high-resolution RPE images were acquired using TOPI at different locations, one of them being imaged 5 times to evaluate the repeatability of the method. Follow-up ophthalmic examination was repeated 1 to 3 weeks after TOPI to assess safety. Retinal pigment epithelial images were analyzed with a custom automated software to extract cell parameters. Statistical analysis of the selected high-contrast images included calculation of coefficient of variation (CoV) for each feature at each repetition and Spearman and Mann-Whitney tests to investigate the relationship between cell features and eye and subject characteristics. Retinal pigment epithelial cell features: density, area, center-to-center spacing, number of neighbors, circularity, elongation, solidity, and border distance CoV. Macular RPE cell features were extracted from TOPI images at an eccentricity of 1.6° to 16.3° from the fovea. For each feature, the mean CoV was < 4%. Spearman test showed correlation within RPE cell features. In the perifovea, the region in which images were selected for all participants, longer AL significantly correlated with decreased RPE cell density (R Spearman, Rs = -0.746; P < 0.0001) and increased cell area (Rs = 0.668; P < 0.0001), without morphologic changes. Aging was also significantly correlated with decreased RPE density (Rs = -0.391; P = 0.036) and increased cell area (Rs = 0.454; P = 0.013). Lower circular, less symmetric, more elongated, and larger cells were observed in those > 50 years. The TOPI technology imaged RPE cells in vivo with a repeatability of < 4% for the CoV and was used to analyze the influence of physiologic factors on RPE cell morphometry in the perifovea of healthy volunteers. Proprietary or commercial disclosure may be found after the references

Protocols for the field testing

The COMMON SENSE project has been designed and planned in order to meet the general and specific scientific and technical objectives mentioned in its Description of Work (page 77). In an overall strategy of the work plan, work packages (11) can be grouped into 3 key phases: (1) RD basis for cost-effective sensor development, (2) Sensor development, sensor web platform and integration, and (3) Field testing. In the first two phases WP1 and WP2 partners have provided a general understanding and integrated basis for a cost effective sensors development. Within the following WPs 4 to 8 the new sensors are created and integrated into different identified platforms. During the third phase 3, characterized by WP9, partners will deploy precompetitive prototypes at chosen platforms (e.g. research vessels, oil platforms, buoys and submerged moorings, ocean racing yachts, drifting buoys). Starting from August 2015 (month 22; task 9.2), these platforms will allow the partnership to test the adaptability and performance of the in-situ sensors and verify if the transmission of data is properly made, correcting deviations. In task 9.1 all stakeholders identified in WP2, and other relevant agents, have been contacted in order to close a coordinated agenda for the field testing phase for each of the platforms. Field testing procedures (WP2) and deployment specificities, defined during sensor development in WPs 4 to 8, are closely studied by all stakeholders involved in field testing activities in order for everyone to know their role, how to proceed and to provide themselves with the necessary material and equipment (e.g. transport of instruments). All this information will provide the basis for designing and coordinating field testing activities. Type and characteristics of the system (vessel or mooring, surface or deep, open sea or coastal area, duration, etc.), used for the field testing activities, are planned comprising the indicators included in the above-mentioned descriptors, taking into account that they must of interest for eutrophication, concentration of contaminants, marine litter and underwater noise. In order to obtain the necessary information, two tables were realized starting from the information acquired for D2.2 delivered in June 2014. One table was created for sensor developers and one for those partners that will test the sensors at sea. The six developers in COMMON SENSE have provided information on the seven sensors: CEFAS and IOPAN for underwater noise; IDRONAUT and LEITAT for microplastics; CSIC for an innovative piro and piezo resistive polymeric temperature and pressure and for heavy metal; DCU for the eutrophication sensor. This information is anyway incomplete because in most cases the novel sensors are still far to be ready and will be developed over the course of COMMON SENSE. So the sensors cannot be clearly designed yet and, consequently, technical characteristics cannot still be perfectly defined. This produces some lag in the acquired information and, consequently, in the planning of their testing on specific platforms that will be solved in the near future. In the table for Testers, partners have provided information on fifteen available platforms. Specific answers have been given on number and type of sensors on each platforms, their availability and technical characteristics, compatibility issues and, very important when new sensors are tested, comparative measurements to be implemented to verify them. Finally IOPAN has described two more platforms, a motorboat not listed in the DoW, but already introduced in D2.2, and their oceanographic buoy in the Gdansk Bay that was previously unavailable. The same availability now is present for the OBSEA Underwater observatory from CSIC, while their Aqualog undulating mooring is still not ready for use. In the following months, new information on sensors and platforms will be provided and the planning of testing activities will improve. Further updates of this report will be therefore necessary in order to individuate the most suitable platforms to test each kind of sensor. Objectives and rationale The objective of deliverable 9.1 is the definition of field testing procedures (WP2), the study of deployment specificities during sensor development work packages (from WP4 to WP8) and the preparation of protocols. This with the participation of all stakeholders involved in field testing activities in order for everyone to know their role, how to proceed and to provide themselves with the necessary material and equipment

Seasonality of bivalve larvae within a high Arctic fjord

Paid Open Acces