Plant functional types and elevated CO2: A method of scanning for causes of community alteration

In this paper, a general method for an a posteriori plant functional type (PFT) analysis of global change effects on community composition is developed. We apply the method to a case study, specifically the Giessen-FACE experiment. This experiment involves a Central European meadow that has been exposed to moderate CO2-enrichment since May 1998.The method for an a posteriori PFT-analysis: The method consists of four working steps and uses a combination of standard gradient analysis and Random Forests (RF). (1) The trait composition of the species is studied using Principal Components Analysis. Species trait information is gathered from databases. Natural PFT, i.e. groups of species with similar trait-sets, are identified specifically for the community under study. (2) A ranking of the species according to standardized/absolute CO2 abundance response is obtained from Redundancy Analysis. Initially, species with a response above or below the median are grouped into three response groups (RG) each having similar behaviour, i.e. positive/negative or no-response. (3) The outlyingness measure of RF is used to shift RG boundaries until satisfactory RG homogeneity is achieved. RF is utilized to find the best traits for the RG classification. The behaviour of species representative of the RG is derived from RF class centers. (4) From knowledge gained in steps 1-3, hypotheses about the causes underlying the community alteration are built. Strengths/weaknesses of the method are discussed.Application of the method to the case study: The community consists of three natural PFT. Five species are summer-green forbs of varying competitiveness. Four species are evergreen ruderal forbs characterized as (semi-) basal rosette plants. The third natural PFT contains evergreen, more or less competitive species, mostly grasses, but also a few forbs.Negative standardized CO2-response was practically restricted to two natural PFT, i.e. the summer-greens, irrespective of their competitiveness, and the evergreen ruderals. Standard positive response covered part of the evergreen competitive natural PFT. Among them was Glechoma hederacea, one of the forbs with the greatest similarity to grasses. Two hypotheses were formulated to explain the response pattern: (1) Summer-greens lost in competition with evergreens, because the annual time-integral they can use for enhanced growth was more limited with year-round CO2-enrichment. (2) As rosette plants, ruderal evergreens lagged behind evergreen competitors because periods with full sunlight, which enabled them to gain additional carbon, were shorter for them.Absolute responses were additionally dependent on dominance patterns. The most striking difference to standard responses was the restriction of positive response to (sub-)dominant grasses

Challenges of Cryptocurrencies Forensics – A Case Study of Investigating, Evidencing and Prosecuting Organised Cybercriminals

This article presents policing challenges of investigating, evidencing and prosecuting organized cybercriminals for the crimes committed using cryptocurrencies such as Bitcoin. A set of best practices is discussed to tackle these challenges in real world investigations. This work is a result of collaboration with a number of stakeholders the policing and judicial ecosystem with the objective of investigating and prosecuting the new generation of organised cybercriminals. Concrete scenarios of using Bitcoins in a range of cybercrimes were developed as part of this project and the devices were analysed to extract evidence to assist prosecution of organised cybercriminals. We have also presented our return of experience for various stages of digital forensics analysis of devices used in Bitcoin transactions

A cross-disorder dosage sensitivity map of the human genome.

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics