Proceedings of the Linux Audio Conference 2018

These proceedings contain all papers presented at the Linux Audio Conference 2018. The conference took place at c-base, Berlin, from June 7th - 10th, 2018 and was organized in cooperation with the Electronic Music Studio at TU Berlin

Multiple categorization and intergroup bias: examining the generalizability of three theories of intergroup relations

Research on intergroup bias usually focuses on a single dimension of social categorization. In real life, however, people are aware of others’ multiple group memberships and use this information to form attitudes about them. The present research tests the predictive power of identification, perceived conflict, and perceived symbolic threat in explaining the strength of intergroup bias on various dimensions of social categorization in multiple categorization settings. We conduct a factorial survey experiment, manipulating 9 dimensions of social categorization in diverse samples from 4 countries (n = 12,810 observations, 1,281 participants representing 103 social groups). The dimensions studied are age, gender, ethnicity, religion, place of residence, education, occupation, income, and 1 country-specific dimension. This approach allows exploring the generalizability of established determinants of bias across dimensions of categorization, contexts, and target groups. Identification and symbolic threat showed good generalizability across countries and categorization dimensions, but their effects varied as a function of participant and target groups’ status. Identification predicted stronger bias mainly when the participant belonged to a higher status and the target belonged to a lower status group. Symbolic threat predicted stronger bias mainly when the target was a minority group member. Conflict predicted bias only in few cases, and not only the strength but also the direction of the effects varied across countries, dimensions, and target and participant groups. These findings help to clarify the limits of generalizability of established determinants of intergroup bias and highlight the need for new explanations of social–cognitive processes among minority group members

Exon expression arrays as a tool to identify new cancer genes

Background: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes

Snow Loss Into Leads in Arctic Sea Ice: Minimal in Typical Wintertime Conditions, but High During a Warm and Windy Snowfall Event

The amount of snow on Arctic sea ice impacts the ice mass budget. Wind redistribution of snow into open water in leads is hypothesized to cause significant wintertime snow loss. However, there are no direct measurements of snow loss into Arctic leads. We measured the snow lost in four leads in the Central Arctic in winter 2020. We find, contrary to expectations, that under typical winter conditions, minimal snow was lost into leads. However, during a cyclone that delivered warm air temperatures, high winds, and snowfall, 35.0 ± 1.1 cm snow water equivalent (SWE) was lost into a lead (per unit lead area). This corresponded to a removal of 0.7–1.1 cm SWE from the entire surface—∼6%–10% of this site's annual snow precipitation. Warm air temperatures, which increase the length of time that wintertime leads remain unfrozen, may be an underappreciated factor in snow loss into leads

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

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers

Multiple categorization and intergroup bias: Examining the generalizability of three theories of intergroup relations.

Research on intergroup bias usually focuses on a single dimension of social categorization. In real life, however, people are aware of others’ multiple group memberships and use this information to form attitudes about them. The present research tests the predictive power of identification, perceived conflict, and perceived symbolic threat in explaining the strength of intergroup bias on various dimensions of social categorization in multiple categorization settings. We conduct a factorial survey experiment, manipulating 9 dimensions of social categorization in diverse samples from 4 countries (n = 12,810 observations, 1,281 participants representing 103 social groups). The dimensions studied are age, gender, ethnicity, religion, place of residence, education, occupation, income, and 1 country-specific dimension. This approach allows exploring the generalizability of established determinants of bias across dimensions of categorization, contexts, and target groups. Identification and symbolic threat showed good generalizability across countries and categorization dimensions, but their effects varied as a function of participant and target groups’ status. Identification predicted stronger bias mainly when the participant belonged to a higher status and the target belonged to a lower status group. Symbolic threat predicted stronger bias mainly when the target was a minority group member. Conflict predicted bias only in few cases, and not only the strength but also the direction of the effects varied across countries, dimensions, and target and participant groups. These findings help to clarify the limits of generalizability of established determinants of intergroup bias and highlight the need for new explanations of social–cognitive processes among minority group members. (PsycInfo Database Record (c) 2022 APA, all rights reserved

Les politiques économiques des années Brown 1997-2010

À partir de mai 1997, Gordon Brown, Chancelier de l’Échiquier et numéro 2 du New Labour, a été pendant dix ans responsable de la conduite de la politique économique correspondant à la période d’expansion la plus longue de l’histoire du Royaume-Uni. En conséquence, il a été, un temps, unanimement reconnu comme un modèle de prudence et de compétence en matière monétaire et fiscale, permettant au Royaume-Uni de devenir l’un des meilleurs élèves de l’OCDE. Au-delà de sa responsabilité individuelle dans les choix qui ont guidé l’action des gouvernements auxquels il a participé, se pose la question de la responsabilité collective du New Labour dans la crise économique actuelle et la crise de confiance politique qui s’en est suivie. Ce numéro dresse le bilan contrasté des années Brown, en analysant tant la politique économique du New Labour et ses effets sociaux que, plus largement, l’évolution de l’économie britannique entre 1997-2010

Genome sequence of Desulfovibrio sp. G11

The genome of Desulfovibrio sp. G11 has been sequenced, re-sequenced, and the transcriptome has been investigated

Genome sequence of Desulfovibrio sp. G11

The genome of Desulfovibrio sp. G11 has been sequenced, re-sequenced, and the transcriptome has been investigated