Nonlinear Inequalities and Entropy-Concurrence Plane

Nonlinear inequalities based on the quadratic Renyi entropy for mixed two-qubit states are characterized on the Entropy-Concurrence plane. This class of inequalities is stronger than Clauser-Horne-Shimony-Holt (CHSH) inequalities and, in particular, are violated "in toto" by the set of Type I Maximally-Entangled-Mixture States (MEMS I)

Basic principles of stable isotope analysis in humanitarian forensic science.

While the identity of a victim of a localized disaster – such as a train or bus crash – may be established quickly through personal effects, fingerprints, dental records, and a comparison of decedent DNA to family reference specimen DNA, a different scenario presents itself in mass disasters, such as the Asian Tsunami of 2004. In the aftermath of the tsunami, visual appearance was initially used to assign “foreign” or “indigenous” classifications to the remains of thousands of victims. However, this visual identification approach was undermined by the speed with which bodies deteriorated under the hot and humid conditions. Time was spent populating ante-mortem DNA databases for different nationalities, which led to problems when creating a post-mortem DNA database because recovery of viable DNA was compromised due to rapid decomposition. As a consequence, only 1.3% of victims were identified by DNA; in contrast, 61% were identified based on dental examination, although this process took several months and a significant number of deceased from the 2004 Asian Tsunami still remain to be identified

ZMYND11‐related syndromic intellectual disability: 16 patients delineating and expanding the phenotypic spectrum

Pathogenic variants in ZMYND11, which acts as a transcriptional repressor, have been associated with intellectual disability, behavioural abnormalities and seizures. Only 11 affected individuals have been reported to‐date, and the phenotype associated with pathogenic variants in this gene have not been fully defined. Here, we present 16 additional patients with predicted pathogenic heterozygous variants in ZMYND11, including four individuals from the same family, to further delineate and expand the genotypic and phenotypic spectrum of ZMYND11‐related syndromic intellectual disability. The associated phenotype includes developmental delay, particularly affecting speech, mild‐moderate intellectual disability, significant behavioural abnormalities, seizures, and hypotonia. There are subtle shared dysmorphic features, including prominent eyelashes and eyebrows, depressed nasal bridge with bulbous nasal tip, anteverted nares, thin vermilion of the upper lip and wide mouth. Novel features include brachydactyly and tooth enamel hypoplasia. Most identified variants are likely to result in premature truncation and/or nonsense mediated decay. Two ZMYND11 variants located in the final exon ‐ p.(Gln586*) (likely escaping nonsense‐mediated decay) and p.(Cys574Arg) ‐ are predicted to disrupt the MYND‐type zinc finger motif and likely interfere with binding to its interaction partners. Hence, the homogeneous phenotype likely results from a common mechanism of loss‐of‐function

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives