Abstract
Sky-coverage in laser-Assisted AO observations largely depends on the system's capability to guide on the faintest natural guide-stars possible. Here we give an up-To-date status of our natural guide-star processing tailored to the European-ELT's visible and near-infrared (0.47 to 2.45 µm) integral field spectrograph-Harmoni. We tour the processing of both the isoplanatic and anisoplanatic tilt modes using the spatio-Angular approach whereby the wavefront is estimated directly in the pupil plane avoiding a cumbersome explicit layered estimation on the 35-layer profiles we're currently using. Taking the case of Harmoni, we cover the choice of wave-front sensors, the number and field location of guide-stars, the optimised algorithms to beat down angular anisoplanatism and the performance obtained with different temporal controllers under split high-order/low-order tomography or joint tomography. We consider both atmospheric and far greater telescope wind buffeting disturbances. In addition we provide the sky-coverage estimates thus obtained.

Abstract
Digital technologies have become our privileged method of interacting with information. With their ubiquity, and focus on personalisation, optimisation and functionality, chance and accidental interactions in the Digital Medium are being replaced with filtered, predictable and known ones, limiting the scope of possible user experiences. In order to promote the design of richer experiences that go beyond the functionally-driven paradigm, we propose that digital systems be designed in order to favour serendipity. Through a literature-based analysis of serendipity, we explore the distinct meanings of value that are possible with serendipitous systems, offering examples of the current state of the art, observing the methods used to do so, and proposing a possible typology, while highlighting unexplored fields, experiences and interactions.

Abstract

Abstract
Develop ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge. Because of two main reasons: harsh condition of the terrain and unstable localization accuracy got from Global Positioning Systems (GPS). This paper presents a hybrid SLAM (VineSLAM) considering low cost landmarks to increase the robot localization accuracy, robustness and redundancy on these steep slope vineyards. Also, we present a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environment. Test results got in a simulated and in a real test case supports the proposed approach and robot.

Abstract
CANARY is the Multi-Object Adaptive Optics (MOAO) pathfinder for the future MOAO-Assisted Integral-Field Units (IFU) proposed for Extremely Large Telescopes (ELT). The MOAO concept relies on tomographically reconstructing the turbulence using multiple measurements along different lines of sight. Tomography requires the knowledge of the statistical turbulence parameters, commonly recovered from the system telemetry using a dedicated profiling technique. For demonstration purposes with the MOAO pathfinder CANARY, this identification is performed thanks to the Learn & Apply (L&A) algorithm, that consists in model-fitting the covariance matrix of WFS measurements dependant on relevant parameters: Cn2(h) profile, outer scale profile and system mis-registration. We explore an upgrade of this algorithm, the Learn 3 Steps (L3S) approach, that allows one to dissociate the identification of the altitude layers from the ground in order to mitigate the lack of convergence of the required empirical covariance matrices therefore reducing the required length of data time-series for reaching a given accuracy. For nominal observation conditions, the L3S can reach the same level of tomographic error in using five times less data frames than the L&A approach. The L3S technique has been applied over a large amount of CANARY data to characterize the turbulence above the William Herschel Telescope (WHT). These data have been acquired the 13th, 15th, 16th, 17th and 18th September 2013 and we find 0.67"/8.9m/3.07m.s-1 of total seeing/outer scale/wind-speed, with 0.552"/9.2m/2.89m.s-1 below 1.5 km and 0.263"/10.3m/5.22m.s-1 between 1.5 and 20 km. We have also determined the high altitude layers above 20 km, missed by the tomographic reconstruction on CANARY, have a median seeing of 0.187" and have occurred 16% of observation time.

Abstract
Meiosis is a differentiated program of the cell cycle that is characterized by high levels of recombination followed by two nuclear divisions. In fission yeast, the genetic program during meiosis is regulated at multiple levels, including transcription, mRNA stabilization, and splicing. Mei4 is a forkhead transcription factor that controls the expression of mid-meiotic genes. Here, we describe that Fkh2, another forkhead transcription factor that is essential for mitotic cell-cycle progression, also plays a pivotal role in the control of meiosis. Fkh2 binding preexists in most Mei4-dependent genes, inhibiting their expression. During meiosis, Fkh2 is phosphorylated in a CDK/Cig2-dependent manner, decreasing its affinity for DNA, which creates a window of opportunity for Mei4 binding to its target genes. We propose that Fkh2 serves as a placeholder until the later appearance of Mei4 with a higher affinity for DNA that induces the expression of a subset of meiotic genes.