X-ray vision at action space distances: depth perception in context

Accurate and usable x-ray vision has long been a goal in augmented reality (AR) research and development. X-ray vision, or the ability to comprehend location and object information when such is viewed through an opaque barrier, would be imminently useful in a variety of contexts, including industrial, disaster reconnaissance, and tactical applications. In order for x-ray vision to be a useful tool for many of these applications, it would need to extend operators’ perceptual awareness of the task or environment. The effectiveness with which x-ray vision can do this is of significant research interest and is a determinant of its usefulness in an application context. In substance, then, it is crucial to evaluate the effectiveness of x-ray vision—how does information presented through x-ray vision compare to real-world information? This approach requires narrowing as x-ray vision suffers from inherent limitations, analogous to viewing an object through a window. In both cases, information is presented beyond the local context, exists past an apparently solid object, and is limited by certain conditions. Further, in both cases, the naturally suggestive use cases occur over action space distances. These distances range from 1.5 to 30 meters and represent the area in which observers might contemplate immediate visually directed actions. These actions, simple tasks with a visual antecedent, represent action potentials for x-ray vision; in effect, x-ray vision extends an operators’ awareness and ability to visualize these actions into a new context. Thus, this work seeks to answer the question “Can a real window be replaced with an AR window?” This evaluation focuses on perceived object location, investigated through a series of experiments using visually directed actions as experimental measures. This approach leverages established methodology to investigate this topic by experimentally analyzing each of several distinct variables on a continuum between real-world depth perception and fully realized x-ray vision. It was found that a real window could not be replaced with an AR window without some loss of depth perception acuity and accuracy. However, no significant difference was found between a target viewed through an opaque wall and a target viewed through a real window

Barriers and Strategies by White Faculty Who Incorporate Anti-Racist Pedagogy

This study focused on the experiences of White faculty who incorporate an anti-racist framework into their college classrooms. The participants shared about the challenges of incorporating anti-racist pedagogy into their classrooms due to both perceived personal and institutional barriers. These participants perceived personal barriers stemming from an internalized struggle of understanding their own White identity while also struggling to be viewed as anti-racist educators by colleagues of color. These faculty participants also shared about perceived professional barriers which included the pressure to obtain tenure, perceived loss of control in the classroom by the students, and anti-racist work being disregarded by individuals in positions of institutional power. Through the use of narrative inquiry, five researchersexploredthe personal and professional barriers faced by White faculty engaging in anti-racist educational practices in the college classroom. The study included17 faculty participants teaching at predominately White private and public colleges and universities throughout the United States who teach in various academic disciplines. Findings revealed the ongoingbarriers in teaching anti-racism ideals and the discussion provides strategies and an emerging modelforincorporating intentional anti-racist pedagogy into the classroom

Design, Assembly, Calibration, and Measurement of an Augmented Reality Haploscope

A haploscope is an optical system which produces a carefully controlled virtual image. Since the development of Wheatstone's original stereoscope in 1838, haploscopes have been used to measure perceptual properties of human stereoscopic vision. This paper presents an augmented reality (AR) haploscope, which allows the viewing of virtual objects superimposed against the real world. Our lab has used generations of this device to make a careful series of perceptual measurements of AR phenomena, which have been described in publications over the previous 8 years. This paper systematically describes the design, assembly, calibration, and measurement of our AR haploscope. These methods have been developed and improved in our lab over the past 10 years. Despite the fact that 180 years have elapsed since the original report of Wheatstone's stereoscope, we have not previously found a paper that describes these kinds of details.Comment: Accepted and presented at the IEEE VR 2018 Workshop on Perceptual and Cognitive Issues in AR (PERCAR); pre-print versio

Analysis of the Type IIn Supernova 1998S: Effects of Circumstellar Interaction on Observed Spectra

We present spectral analysis of early observations of the Type IIn supernova 1998S using the general non-local thermodynamic equilibrium atmosphere code \tt PHOENIX}. We model both the underlying supernova spectrum and the overlying circumstellar interaction region and produce spectra in good agreement with observations. The early spectra are well fit by lines produced primarily in the circumstellar region itself, and later spectra are due primarily to the supernova ejecta. Intermediate spectra are affected by both regions. A mass-loss rate of order $\dot M \sim 0.0001-0.001$\msol yr$^{-1}$ is inferred for a wind speed of 100-1000 \kmps. We discuss how future self-consistent models will better clarify the underlying progenitor structure.Comment: to appear in ApJ, 2001, 54

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

The response of tropical rainforests to drought : lessons from recent research and future prospects

Key message: we review the recent findings on the influence of drought on tree mortality, growth or ecosystem functioning in tropical rainforests. Drought plays a major role in shaping tropical rainforests and the response mechanisms are highly diverse and complex. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical rainforests on the three continents. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance. - Context: tropical rainforest ecosystems are characterized by high annual rainfall. Nevertheless, rainfall regularly fluctuates during the year and seasonal soil droughts do occur. Over the past decades, a number of extreme droughts have hit tropical rainforests, not only in Amazonia but also in Asia and Africa. The influence of drought events on tree mortality and growth or on ecosystem functioning (carbon and water fluxes) in tropical rainforest ecosystems has been studied intensively, but the response mechanisms are complex.- Aims: herein, we review the recent findings related to the response of tropical forest ecosystems to seasonal and extreme droughts and the current knowledge about the future of these ecosystems. - Results: this review emphasizes the progress made over recent years and the importance of the studies conducted under extreme drought conditions or in through-fall exclusion experiments in understanding the response of these ecosystems. It also points to the great diversity and complexity of the response of tropical rainforest ecosystems to drought. - Conclusion: the numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical forest regions. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance

The Inference Engine

Data generated by complex, computational models can provide highly accurate predictions of hydrological and hydrodynamic data in multiple dimensions. Unfortunately, however, for large data sets, running these models is often timeconsuming and computationally expensive. Thus, finding a way to reduce the running time of these models, while still producing comparable results, is of notable interest. The Inference Engine is a proposed system for doing just this. It takes previously generated model data and uses them to predict additional data. Its performance, both accuracy and running time, has been compared to the performance of the actual models, in increasingly difficult data prediction tasks, and it is able, with sufficient accuracy, to quickly predict unknown model data