Situating emotional experience

Psychological construction approaches to emotion suggest that emotional experience is situated and dynamic. Fear, for example, is typically studied in a physical danger context (e.g., threatening snake), but in the real world, it often occurs in social contexts, especially those involving social evaluation (e.g., public speaking). Understanding situated emotional experience is critical because adaptive responding is guided by situational context (e.g., inferring the intention of another in a social evaluation situation vs. monitoring the environment in a physical danger situation). In an fMRI study, we assessed situated emotional experience using a newly developed paradigm in which participants vividly imagine different scenarios from a first-person perspective, in this case scenarios involving either social evaluation or physical danger. We hypothesized that distributed neural patterns would underlie immersion in social evaluation and physical danger situations, with shared activity patterns across both situations in multiple sensory modalities and in circuitry involved in integrating salient sensory information, and with unique activity patterns for each situation type in coordinated large-scale networks that reflect situated responding. More specifically, we predicted that networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations. In contrast, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. The results supported these hypotheses. In line with emerging psychological construction approaches, the findings suggest that coordinated brain networks offer a systematic way to interpret the distributed patterns that underlie the diverse situational contexts characterizing emotional life

Assessing Vividness of Mental Imagery: The Plymouth Sensory Imagery Questionnaire

Publisher allows archiving of submitted msMental imagery may occur in any sensory modality, although visual imagery has been most studied. A sensitive measure of the vividness of imagery across a range of modalities is needed: the shorter version of Bett’s QMI (Sheehan, 1967) uses outdated items and has an unreliable factor structure. We report the development and initial validation of the Plymouth Sensory Imagery Questionnaire (Psi-Q) comprising items for each of the following modalities: Vision, Sound, Smell, Taste, Touch, Bodily Sensation and Emotional Feeling. An Exploratory Factor Analysis on a 35-item form indicated that these modalities formed separate factors, rather than a single imagery factor, and this was replicated by confirmatory factor analysis. The Psi-Q was validated against the Spontaneous Use of Imagery Scale (Reisberg, Pearson & Kosslyn, 2003) and Marks’ (1995) Vividness of Visual Imagery Questionnaire-2. A short 21-item form comprising the best three items from the seven factors correlated with the total score and subscales of the full form, and with the VVIQ-2. Inspection of the data shows that while visual and sound imagery is most often rated as vivid, individuals who rate one modality as strong and the other as weak are not uncommon. Findings are interpreted within a working memory framework and point to the need for further research to identify the specific cognitive processes underlying the vividness of imagery across sensory modalities

Active microwave remote sensing of earth/land, chapter 2

Geoscience applications of active microwave remote sensing systems are examined. Major application areas for the system include: (1) exploration of petroleum, mineral, and ground water resources, (2) mapping surface and structural features, (3) terrain analysis, both morphometric and genetic, (4) application in civil works, and (5) application in the areas of earthquake prediction and crustal movements. Although the success of radar surveys has not been widely publicized, they have been used as a prime reconnaissance data base for mineral exploration and land-use evaluation in areas where photography cannot be obtained

Historical forest biomass dynamics modelled with Landsat spectral trajectories

Acknowledgements National Forest Inventory data are available online, provided by Ministerio de Agricultura, Alimentación y Medio Ambiente (España). Landsat images are available online, provided by the USGS.Peer reviewedPostprin

Application of ERTS-1 data to integrated state planning in the state of Maryland

There are no author-identified significant results in this report

Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the machine learning process, yielding regional model features whose construction is driven by model prediction performance rather than prior assumptions. Our results demonstrate that Genetic Programming is particularly well suited to this type of feature construction because it can automatically synthesize appropriate aggregations, as well as better incorporate them into predictive models compared to other regression methods we tested. In our experiments we consider a specific problem instance and real-world dataset relevant to predicting snow properties in high-mountain Asia

Third Earth Resources Technology Satellite Symposium. Volume 3: Discipline summary reports

Presentations at the conference covered the following disciplines: (1) agriculture, forestry, and range resources; (2) land use and mapping; (3) mineral resources, geological structure, and landform surveys; (4) water resources; (5) marine resources; (6) environment surveys; and (7) interpretation techniques