Good exemplars of natural scene categories elicit clearer patterns than bad exemplars but not greater BOLD activity

Within the range of images that we might categorize as a “beach”, for example, some will be more representative of that category than others. We used ‘good’ and ‘bad’ exemplars of six natural scene categories to confirm that human categorization is sensitive to this manipulation and explore whether brain regions previously implicated in natural scene categorization show a similar sensitivity to how well an image exemplifies a category. Participants were more accurate and faster at categorizing good exemplars of natural scenes. A classifier trained to discriminate patterns of fMRI activity associated with the viewing of our scene categories showed higher decoding accuracy for good than bad exemplars of a category in the PPA, RSC and V1. A univariate analysis, however, revealed that there was either no difference in overall BOLD signal evoked by good and bad scenes (in RSC and V1) or the signal was actually higher for bad scenes (in PPA), suggesting that good exemplars produce a qualitatively, rather than quantitatively, better pattern of activity for categorizing natural scenes. Overall, our results provide further evidence that V1, RSC and the PPA contain information relevant for natural scene categorization. Finally, image statistic analysis shows that good images in our categories produce a more discernible average image and are more similar to each other. These results are consistent with both low-level models of scene category and models in which the category is built around a prototype

Climatic Variability Leads to Later Seasonal Flowering of Floridian Plants

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses

Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year

Advances in phenology (the annual timing of species’ life-cycles) in response to climate change are generally viewed as bioindicators of climate change, but have not been considered as predictors of range expansions. Here, we show that phenology advances combine with the number of reproductive cycles per year (voltinism) to shape abundance and distribution trends in 130 species of British Lepidoptera, in response to ~0.5 °C spring-temperature warming between 1995 and 2014. Early adult emergence in warm years resulted in increased within- and between-year population growth for species with multiple reproductive cycles per year (n = 39 multivoltine species). By contrast, early emergence had neutral or negative consequences for species with a single annual reproductive cycle (n = 91 univoltine species), depending on habitat specialisation. We conclude that phenology advances facilitate polewards range expansions in species exhibiting plasticity for both phenology and voltinism, but may inhibit expansion by less flexible species

Chemical characterization of extra layers at the interfaces in MOCVD InGaP/GaAs junctions by electron beam methods

Electron beam methods, such as cathodoluminescence (CL) that is based on an electron-probe microanalyser, and (200) dark field and high angle annular dark field (HAADF) in a scanning transmission electron microscope, are used to study the deterioration of interfaces in InGaP/GaAs system with the GaAs QW on top of InGaP. A CL emission peak different from that of the QW was detected. By using HAADF, it is found that the GaAs QW does not exist any longer, being replaced by extra interlayer(s) that are different from GaAs and InGaP because of atomic rearrangements at the interface. The nature and composition of the interlayer(s) are determined by HAADF. Such changes of the nominal GaAs QW can account for the emission observed by CL

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

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

"I am becoming more and more like my eldest brother!": the relationship between older siblings, adolescent gambling severity, and the attenuating role of parents in a large-scale nationally representative survey study

The present study examined the association between having older siblings who gamble and adolescent at-risk/problem gambling and how parents (i.e., parental knowledge of their whereabouts) and peers might moderate such effects. Data were drawn from the ESPAD®Italia2012 survey (European School Survey Project on Alcohol and Other Drugs) comprising a nationally representative Italian sample of adolescents. The analysis was carried out on a subsample of 10,063 Italian students aged 15–19 years (average age = 17.10; 55 % girls) who had at least one older sibling and who had gambled at some point in their lives. Respondents’ problem gambling severity, older gambler sibling, gambler peers, parental knowledge, and socio-demographic characteristics were individually assessed. Multinomial logistic regression analyses including two- and three-way interactions were conducted. The odds of being an at-risk/problem gambler were higher among high school students with older siblings that gambled and those with peers who gambled. Higher parental knowledge (of who the adolescent was with and where they were in their leisure time) was associated with lower rates of at-risk/problem gambling. There was also an interaction between gamblers with older siblings and parental knowledge. The combination of having siblings who gambled and a greater level of parental knowledge was associated with lower levels of problem gambling. The present study confirmed the occurrence of social risk processes (older siblings and peers who gambled) and demonstrated that gambling among older siblings and peers represents an important contextual factor for increased at-risk/problem gambling. However, parental knowledge appears to be sufficient to counterbalance the influence of older siblings

Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation

PubMed ID: 2313976

Molecular genetics of nicotine dependence and abstinence: whole genome association using 520,000 SNPs

BACKGROUND: Classical genetic studies indicate that nicotine dependence is a substantially heritable complex disorder. Genetic vulnerabilities to nicotine dependence largely overlap with genetic vulnerabilities to dependence on other addictive substances. Successful abstinence from nicotine displays substantial heritable components as well. Some of the heritability for the ability to quit smoking appears to overlap with the genetics of nicotine dependence and some does not. We now report genome wide association studies of nicotine dependent individuals who were successful in abstaining from cigarette smoking, nicotine dependent individuals who were not successful in abstaining and ethnically-matched control subjects free from substantial lifetime use of any addictive substance. RESULTS: These data, and their comparison with data that we have previously obtained from comparisons of four other substance dependent vs control samples support two main ideas: 1) Single nucleotide polymorphisms (SNPs) whose allele frequencies distinguish nicotine-dependent from control individuals identify a set of genes that overlaps significantly with the set of genes that contain markers whose allelic frequencies distinguish the four other substance dependent vs control groups (p < 0.018). 2) SNPs whose allelic frequencies distinguish successful vs unsuccessful abstainers cluster in small genomic regions in ways that are highly unlikely to be due to chance (Monte Carlo p < 0.00001). CONCLUSION: These clustered SNPs nominate candidate genes for successful abstinence from smoking that are implicated in interesting functions: cell adhesion, enzymes, transcriptional regulators, neurotransmitters and receptors and regulation of DNA, RNA and proteins. As these observations are replicated, they will provide an increasingly-strong basis for understanding mechanisms of successful abstinence, for identifying individuals more or less likely to succeed in smoking cessation efforts and for tailoring therapies so that genotypes can help match smokers with the treatments that are most likely to benefit them