Understanding the truth about subjectivity

Results of two experiments show children’s understanding of diversity in personal preference is incomplete. Despite acknowledging diversity, in Experiment 1(N=108), 6- and 8-year-old children were less likely than adults to see preference as a legitimate basis for personal tastes and more likely to say a single truth could be found about a matter of taste. In Experiment 2 (N=96), 7- and 9-year-olds were less likely than 11- and 13-yearolds to say a dispute about a matter of preference might not be resolved. These data suggest that acceptance of the possibility of diversity does not indicate an adult-like understanding of subjectivity. An understanding of the relative emphasis placed on objective and subjective factors in different contexts continues to develop into adolescence

Economic impact of large public programs: The NASA experience

The economic impact of NASA programs on weather forecasting and the computer and semiconductor industries is discussed. Contributions to the advancement of the science of astronomy are also considered

Towards Semantic Integration of Heterogeneous Sensor Data with Indigenous Knowledge for Drought Forecasting

In the Internet of Things (IoT) domain, various heterogeneous ubiquitous devices would be able to connect and communicate with each other seamlessly, irrespective of the domain. Semantic representation of data through detailed standardized annotation has shown to improve the integration of the interconnected heterogeneous devices. However, the semantic representation of these heterogeneous data sources for environmental monitoring systems is not yet well supported. To achieve the maximum benefits of IoT for drought forecasting, a dedicated semantic middleware solution is required. This research proposes a middleware that semantically represents and integrates heterogeneous data sources with indigenous knowledge based on a unified ontology for an accurate IoT-based drought early warning system (DEWS).Comment: 5 pages, 3 figures, In Proceedings of the Doctoral Symposium of the 16th International Middleware Conference (Middleware Doct Symposium 2015), Ivan Beschastnikh and Wouter Joosen (Eds.). ACM, New York, NY, US

The effect of flooding on the exchange of the volatile C₂-compounds ethanol, acetaldehyde and acetic acid between leaves of Amazonian floodplain tree species and the atmosphere

The effect of root inundation on the leaf emissions of ethanol, acetaldehyde and acetic acid in relation to assimilation and transpiration was investigated with 2–3 years old tree seedlings of four Amazonian floodplain species by applying dynamic cuvette systems under greenhouse conditions. Emissions were monitored over a period of several days of inundation using a combination of Proton Transfer Reaction Mass Spectrometry (PTR-MS) and conventional techniques (HPLC, ion chromatography). Under non-flooded conditions, none of the species exhibited measurable emissions of any of the compounds, but rather low deposition of acetaldehyde and acetic acid was observed instead. Tree species specific variations in deposition velocities were largely due to variations in stomatal conductance. Flooding of the roots resulted in leaf emissions of ethanol and acetaldehyde by all species, while emissions of acetic acid were only observed from the species exhibiting the highest ethanol and acetaldehyde emission rates. All three compounds showed a similar diurnal emission profile, each displaying an emission burst in the morning, followed by a decline in the evening. This concurrent behavior supports the conclusion, that all three compounds emitted by the leaves are derived from ethanol produced in the roots by alcoholic fermentation, transported to the leaves with the transpiration stream and finally partly converted to acetaldehyde and acetic acid by enzymatic processes. Co-emissions and peaking in the early morning suggest that root ethanol, after transportation with the transpiration stream to the leaves and enzymatic oxidation to acetaldehyde and acetate, is the metabolic precursor for all compounds emitted, though we can not totally exclude other production pathways. Emission rates substantially varied among tree species, with maxima differing by up to two orders of magnitude (25–1700 nmol m−2 min−1 for ethanol and 5–500 nmol m−2 min−1 for acetaldehyde). Acetic acid emissions reached 12 nmol m−2 min−1. The observed differences in emission rates between the tree species are discussed with respect to their root adaptive strategies to tolerate long term flooding, providing an indirect line of evidence that the root ethanol production is a major factor determining the foliar emissions. Species which develop morphological root structures allowing for enhanced root aeration produced less ethanol and showed much lower emissions compared to species which lack gas transporting systems, and respond to flooding with substantially enhanced fermentation rates and a non-trivial loss of carbon to the atmosphere. The pronounced differences in the relative emissions of ethanol to acetaldehyde and acetic acid between the tree species indicate that not only the ethanol production in the roots but also the metabolic conversion in the leaf is an important factor determining the release of these compounds to the atmosphere

Opportunities for Growing Short-Rotation Woody Crops in Agroforestry Practices

Technologies are readily available for growing hybrid poplars and willows in block plantings as short-rotation woody crops (SRWC) for fuel and fiber. SRWC species and technologies can also be incorporated into agricultural systems as agroforestry practices. Examples are windbreaks, living snowfences, “timberbelts”, riparian buffer strips, and wastewater treatment plantings. Fast growth, convenient propagation (see AF Note - 11), and compatibility with conventional farming methods make SRWC suitable for use in agroforestry practices to provide multiple benefits such as solid wood and wood fiber products, water quality improvement, crop and soil protection, wildlife habitat, and buffers for agricultural/community interfaces

Disgust implicated in obsessive-compulsive disorder

Psychiatric classificatory systems consider obsessions and compulsions as forms of anxiety disorder. However, the neurology of diseases associated with obsessive-compulsive symptoms suggests the involvement of fronto-striatal regions likely to be involved in the mediation of the emotion of disgust, suggesting that dysfunctions of disgust should be considered alongside anxiety in the pathogenesis of obsessive-compulsive behaviours. We therefore tested recognition of facial expressions of basic emotions (including disgust) by groups of participants with obsessive-compulsive disorder (OCD) and with Gilles de la Tourette's syndrome (GTS) with and without co-present obsessive-compulsive behaviours (GTS with OCB; GTS without OCB). A group of people suffering from panic disorder and generalized anxiety were also included in the study. Both groups with obsessive-compulsive symptoms (OCD; GTS with OCB) showed impaired recognition of facial expressions of disgust. Such problems were not evident in participants with panic disorder and generalized anxiety, or for participants with GTS without obsessions or compulsions, indicating that the deficit is closely related to the presence of obsessive-compulsive symptoms. Participants with OCD were able to assign words to emotion categories without difficulty, showing that their problem with disgust is linked to a failure to recognize this emotion in others and not a comprehension or response criterion effect. Impaired recognition of disgust is consistent with the neurology of OCD and with the idea that abnormal experience of disgust may be involved in the genesis of obsessions and compulsions

Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media

The growing popularity of social media (e.g, Twitter) allows users to easily share information with each other and influence others by expressing their own sentiments on various subjects. In this work, we propose an unsupervised \emph{tri-clustering} framework, which analyzes both user-level and tweet-level sentiments through co-clustering of a tripartite graph. A compelling feature of the proposed framework is that the quality of sentiment clustering of tweets, users, and features can be mutually improved by joint clustering. We further investigate the evolution of user-level sentiments and latent feature vectors in an online framework and devise an efficient online algorithm to sequentially update the clustering of tweets, users and features with newly arrived data. The online framework not only provides better quality of both dynamic user-level and tweet-level sentiment analysis, but also improves the computational and storage efficiency. We verified the effectiveness and efficiency of the proposed approaches on the November 2012 California ballot Twitter data.Comment: A short version is in Proceeding of the 2014 ACM SIGMOD International Conference on Management of dat

Electroweak Sudakov Logarithms and Real Gauge-Boson Radiation in the TeV Region

Electroweak radiative corrections give rise to large negative, double-logarithmically enhanced corrections in the TeV region. These are partly compensated by real radiation and, moreover, affected by selecting isospin-noninvariant external states. We investigate the impact of real gauge boson radiation more quantitatively by considering different restricted final state configurations. We consider successively a massive abelian gauge theory, a spontaneously broken SU(2) theory and the electroweak Standard Model. We find that details of the choice of the phase space cuts, in particular whether a fraction of collinear and soft radiation is included, have a strong impact on the relative amount of real and virtual corrections.Comment: 20 pages, 4 figure