Rockfall detection from LIDAR point clouds: A clustering approach using R

The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Effects of the social environment on the survival and fungal resistance of ant brood

The phenotype of social animals can be influenced by genetic, maternal and environmental effects, which include social interactions during development. In social insects, the social environment and genetic origin of brood can each influence a whole suite of traits, from individual size to caste differentiation. Here, we investigate to which degree the social environment during development affects the survival and fungal resistance of ant brood of known maternal origin. We manipulated one component of the social environment, the worker/brood ratio, of brood originating from single queens of Formica selysi. We monitored the survival of brood and measured the head size and ability to resist the entomopathogenic fungus Beauveria bassiana of the resulting callow workers. The worker/brood ratio and origin of eggs affected the survival and maturation time of the brood and the size of the resulting callow workers. The survival of the callow workers varied greatly according to their origin, both in controls and when challenged with B. bassiana. However, there was no interaction between the fungal challenge and either the worker/brood ratio or origin of eggs, suggesting that these factors did not affect parasite resistance in the conditions tested. Overall, the social conditions during brood rearing and the origin of eggs had a strong impact on brood traits that are important for fitness. We detected a surprisingly large amount of variation among queens in the survival of their brood reared in standard queenless conditions, which calls for further studies on genetic, maternal and social effects influencing brood development in the social insects.

Statistical discrimination and employers' recruitment : Practices for low-skilled workers

This paper deals with the recruitment strategies of employers in the low-skilled segment of the labour market. We focus on low-skilled workers because they are overrepresented among jobless people and constitute the bulk of the clientele included in various activation and labour market programmes. A better understanding of the constraints and opportunities of interventions in this labour market segment may help improve their quality and effectiveness. On the basis of qualitative interviews with 41 employers in six European countries, we find that the traditional signals known to be used as statistical discrimination devices (old age, immigrant status and unemployment) play a somewhat reduced role, since these profiles are overrepresented among applicants for low skill positions. However, we find that other signals, mostly considered to be indicators of motivation, have a bigger impact in the selection process. These tend to concern the channel through which the contact with a prospective candidate is made. Unsolicited applications and recommendations from already employed workers emit a positive signal, whereas the fact of being referred by the public employment office is associated with the likelihood of lower motivation.

France's Charter for the Environment : of Presidents, Principles and Environmental Protection

France amended its constitution in 2005 to include a Charter for the Environment. The Charter lays out France's commitment to supporting the right to a 'balanced environment'. This article first traces the Charter's origins to a legacy-building presidential initiative. Jacques Chirac decided to invest in a neglected policy domain in which his own majority had shown little interest. He was obliged to intervene repeatedly in order to bring this project to a successful conclusion. In doing so, he staked out environmental affairs as an area of potential presidential supremacy. Next, the content of the Charter is examined. In this document, French traditions of universalism come together with an international movement for anticipatory environmental protection. This is reflected in the constitutionalisation of the precautionary principle, which emerged as the most controversial part of the Charter. The debates this provoked tended to caricature a risk-management principle whose meaning has been carefully refined to forestall objections. Finally, the Charter's potential efficacy is analysed. The post-Charter record of legislative and judicial activity concerning the environment is meagre, but not wholly inauspicious.

Sensing the light environment in plants: photoreceptors and early signaling steps.

Plants must constantly adapt to a changing light environment in order to optimize energy conversion through the process of photosynthesis and to limit photodamage. In addition, plants use light cues for timing of key developmental transitions such as initiation of reproduction (transition to flowering). Plants are equipped with a battery of photoreceptors enabling them to sense a very broad light spectrum spanning from UV-B to far-red wavelength (280-750nm). In this review we briefly describe the different families of plant photosensory receptors and the mechanisms by which they transduce environmental information to influence numerous aspects of plant growth and development throughout their life cycle.

Studying social interactions through immersive virtual environment technology: Virtues, pitfalls, and future challenges

Thegoalofthepresentreviewistoexplainhowimmersivevirtualenvironmenttechnology(IVET)canbeusedforthestudyofsocialinteractionsandhowtheuseofvirtualhumansinimmersivevirtualenvironmentscanadvanceresearchandapplicationinmanydifferentfields.Researchersstudyingindividualdifferencesinsocialinteractionsaretypicallyinterestedinkeepingthebehaviorandtheappearanceoftheinteractionpartnerconstantacrossparticipants.WithIVETresearchershavefullcontrolovertheinteractionpartners,canstandardizethemwhilestillkeepingthesimulationrealistic.Virtualsimulationsarevalid:growingevidenceshowsthatindeedstudiesconductedwithIVETcanreplicatesomewell-knownfindingsofsocialpsychology.Moreover,IVETallowsresearcherstosubtlymanipulatecharacteristicsoftheenvironment(e.g.,visualcuestoprimeparticipants)orofthesocialpartner(e.g.,his/herrace)toinvestigatetheirinfluencesonparticipants'behaviorandcognition.Furthermore,manipulationsthatwouldbedifficultorimpossibleinreallife(e.g.,changingparticipants'height)canbeeasilyobtainedwithIVET.Besidetheadvantagesfortheoreticalresearch,weexplorethemostrecenttrainingandclinicalapplicationsofIVET,itsintegrationwithothertechnologies(e.g.,socialsensing)andfuturechallengesforresearchers(e.g.,makingthecommunicationbetweenvirtualhumansandparticipantssmoother).

Improved statistical analysis of low abundance phenomena in bimodal bacterial populations.

Accurate detection of subpopulation size determinations in bimodal populations remains problematic yet it represents a powerful way by which cellular heterogeneity under different environmental conditions can be compared. So far, most studies have relied on qualitative descriptions of population distribution patterns, on population-independent descriptors, or on arbitrary placement of thresholds distinguishing biological ON from OFF states. We found that all these methods fall short of accurately describing small population sizes in bimodal populations. Here we propose a simple, statistics-based method for the analysis of small subpopulation sizes for use in the free software environment R and test this method on real as well as simulated data. Four so-called population splitting methods were designed with different algorithms that can estimate subpopulation sizes from bimodal populations. All four methods proved more precise than previously used methods when analyzing subpopulation sizes of transfer competent cells arising in populations of the bacterium Pseudomonas knackmussii B13. The methods' resolving powers were further explored by bootstrapping and simulations. Two of the methods were not severely limited by the proportions of subpopulations they could estimate correctly, but the two others only allowed accurate subpopulation quantification when this amounted to less than 25% of the total population. In contrast, only one method was still sufficiently accurate with subpopulations smaller than 1% of the total population. This study proposes a number of rational approximations to quantifying small subpopulations and offers an easy-to-use protocol for their implementation in the open source statistical software environment R.