Complex and shifting interactions of phytochromes regulate fruit development in tomato

Tomato fruit ripening is a complex metabolic process regulated by a genetical hierarchy. A subset of this process is also modulated by light-signaling, as mutants encoding negative regulators of phytochrome signal transduction, show higher accumulation of carotenoids. In tomato phytochromes are encoded by a multi-gene family, namely PhyA, PhyB1, PhyB2, PhyE and PhyF, however, their contribution to fruit development and ripening has not been examined. Using single phytochrome mutants- phyA, phyB1 and phyB2 and multiple mutants- phyAB1, phyB1B2 and phyAB1B2, we compared the on-vine transitory phases of ripening till fruit abscission. The phyAB1B2 mutant showed accelerated transitions during ripening with shortest time to fruit abscission. Comparison of transition intervals in mutants indicated a phase-specific influence of different phytochrome species either singly or in combination on the ripening process. Examination of off-vine ripened fruits indicated that ripening specific carotenoid accumulation was not obligatorily dependent on light and even dark incubated fruits accumulated carotenoids. The accumulation of transcripts and carotenoids in off-vine and on-vine ripened mutant fruits indicated a complex and shifting phase-dependent modulation by phytochromes(s). Our results indicate that in addition to regulating carotenoid levels in tomato fruits, phytochrome(s) also regulate the time required for phase transitions during ripening

Bio-inspired relevant interaction modelling in cognitive crowd management

Cognitive algorithms, integrated in intelligent systems, represent an important innovation in designing interactive smart environments. More in details, Cognitive Systems have important applications in anomaly detection and management in advanced video surveillance. These algorithms mainly address the problem of modelling interactions and behaviours among the main entities in a scene. A bio-inspired structure is here proposed, which is able to encode and synthesize signals, not only for the description of single entities behaviours, but also for modelling cause–effect relationships between user actions and changes in environment configurations. Such models are stored within a memory (Autobiographical Memory) during a learning phase. Here the system operates an effective knowledge transfer from a human operator towards an automatic systems called Cognitive Surveillance Node (CSN), which is part of a complex cognitive JDL-based and bio-inspired architecture. After such a knowledge-transfer phase, learned representations can be used, at different levels, either to support human decisions, by detecting anomalous interaction models and thus compensating for human shortcomings, or, in an automatic decision scenario, to identify anomalous patterns and choose the best strategy to preserve stability of the entire system. Results are presented in a video surveillance scenario , where the CSN can observe two interacting entities consisting in a simulated crowd and a human operator. These can interact within a visual 3D simulator, where crowd behaviour is modelled by means of Social Forces. The way anomalies are detected and consequently handled is demonstrated, on synthetic and also on real video sequences, in both the user-support and automatic modes

Optimal modelling of buildings through simultaneous automatic simplifications of point clouds obtained with a laser scanner

[EN] In recent years, the laser scanner has become the most used tool for modelling buildings in pure documentation and structural studies. Laser scanning provides large numbers of points in a minimum amount of time with great precision. The point clouds generated and the subsequent mosaics (data fusion of different clouds) contain millions of points with a heterogeneous density that define the 3D geometry of the buildings. Often, the number of points results in excessive information without offering a better definition. As a result, it is necessary to analyse which points can be eliminated and which ones cannot, based on precision criteria, to obtain a precise geometry with the smallest possible number of points for each part of the building. The algorithm developed in this work reduces the point clouds (in mosaics made up of clouds with over 10 million points) with precision criteria by as much as 99% while still accurately resolving the geometry of the object. The developed process is automatic such that different models with different resolutions can be obtained simultaneously. As a result, we obtain single clouds with homogenous distributions and densities throughout the model of the building (based on multiple overlapping clouds), with a computational cost of only a few seconds per cloud. The final result is a complete model of the entire building with the optimal resolution for each element of the structure. (C) 2016 Elsevier Ltd. All rights reserved.S2432519

Binarity and multiperiodicity in high-amplitude delta Scuti stars

We have carried out a photometric and spectroscopic survey of bright high-amplitude delta Scuti (HADS) stars. The aim was to detect binarity and multiperiodicity (or both) in order to explore the possibility of combining binary star astrophysics with stellar oscillations. Here we present the first results for ten, predominantly southern, HADS variables. We detected the orbital motion of RS Gru with a semi-amplitude of ~6.5 km/s and 11.5 days period. The companion is inferred to be a low-mass dwarf star in a close orbit around RS Gru. We found multiperiodicity in RY Lep both from photometric and radial velocity data and detected orbital motion in the radial velocities with hints of a possible period of 500--700 days. The data also revealed that the amplitude of the secondary frequency is variable on the time-scale of a few years, whereas the dominant mode is stable. Radial velocities of AD CMi revealed cycle-to-cycle variations which might be due to non-radial pulsations. We confirmed the multiperiodic nature of BQ Ind, while we obtained the first radial velocity curves of ZZ Mic and BE Lyn. The radial velocity curve and the O-C diagram of CY Aqr are consistent with the long-period binary hypothesis. We took new time series photometry on XX Cyg, DY Her and DY Peg, with which we updated their O-C diagrams.Comment: 15 pages, 16 pages, accepted for publication in MNRA

A Concentric Neighborhood Solution to Disparity in Liver Access That Contains Current UNOS Districts

Background. Policymakers are deliberating reforms to reduce geographic disparity in liver allocation. Public comments and the United Network for Organ Sharing Liver and Intestinal Committee have expressed interest in refining the neighborhoods approach. Share 35 and Share 15 policies affect geographic disparity. Methods. We construct concentric neighborhoods superimposing the current 11 regions. Using concepts from concentric circles, we construct neighborhoods for each donor service area (DSA) that consider all DSAs within 400, 500, or 600 miles as neighbors. We consider limiting each neighborhood to 10 DSAs and use no metrics for liver supplies and demands. We change Model for End-Stage Liver Disease (MELD) thresholds for the Share 15 policy to 18 or 20 and apply 3-and 5-point MELD proximity boosts to enhance local priority, control travel distances, and reduce disparity. We conduct simulations comparing current allocation with the neighborhoods and sharing policies. Results. Concentric neighborhoods structures provide an array of solutions where simulation results indicate that they reduce geographic disparity, annual mortalities, and the airplane travel distances by varying degrees. Tuning of the parameters and policy combinations can lead to beneficial improvements with acceptable transplant volume loss and reductions in geographic disparity and travel distance. Particularly, the 10-DSA, 500-mile neighborhood solution with Share 35, Share 15, and 0-point MELD boost achieves such while limiting transplant volume losses to below10%. Conclusions. The current 11 districts can be adapted systematically by adding neighboring DSAs to improve geographic disparity, mortality, and airplane travel distance. Modifications to Share 35 and Share 15 policies result in further improvements. The solutions may be refined further for implementation