Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Children with autism spectrum disorders (ASD) and their unaffected siblings (US) are frequent targets of social bullying, which leads to severe physical, emotional, and social consequences. Understanding the risk factors is essential for developing preventative measures. We suggest that one such risk factor may be a difficulty to discriminate different biological body movements (BBM), a task that requires fast and flexible processing and interpretation of complex visual cues, especially during social interactions. Deficits in cognition of BBM have been reported in ASD. Since US display an autism endophenotype we expect that they will also display deficits in social interpretation of BBM. Methods. Participants: 8 US, 8 matched TD children, age 7-14; Tasks/Measurements: Social Blue Man Task: Narrative interpretation with a Latent Dirichlet Allocation [LDA] analysis; Social Experience Questionnaires with children and parents. Results. The US displayed as compared to TD: (i) low self-awareness of social bullying in contrast to high parental reports; (ii) reduced speed in identifying social cues; (iii) lower quality and repetitious wording in social interaction narratives (LDA). Conclusions. US demonstrate social endophenotype of autism reflected in delayed identification, interpretation and verbalization of social cues; these may constitute a high risk factor for becoming a victim of social bullying.

The Rim-to-Rim Wearables At The Canyon for Health (R2R WATCH) study examines metrics recordable on commercial off the shelf (COTS) devices that are most relevant and reliable for the earliest possible indication of a health or performance decline. This is accomplished through collaboration between Sandia National Laboratories (SNL) and The University of New Mexico (UNM) where the two organizations team up to collect physiological, cognitive, and biological markers from volunteer hikers who attempt the Rim-to-Rim (R2R) hike at the Grand Canyon. Three forms of data are collected as hikers travel from rim to rim: physiological data through wearable devices, cognitive data through a cognitive task taken every 3 hours, and blood samples obtained before and after completing the hike. Data is collected from both civilian and warfighter hikers. Once the data is obtained, it is analyzed to understand the effectiveness of each COTS device and the validity of the data collected. We also aim to identify which physiological and cognitive phenomena collected by wearable devices are the most relatable to overall health and task performance in extreme environments, and of these ascertain which markers provide the earliest yet reliable indication of health decline. Finally, we analyze the data for significant differences between civilians’ and warfighters’ markers and the relationship to performance. This is a study funded by the Defense Threat Reduction Agency (DTRA, Project CB10359) and the University of New Mexico (The main portion of the R2R WATCH study is funded by DTRA. UNM is currently funding all activities related to bloodwork. DTRA, Project CB10359; SAND2017-1872 C). This paper describes the experimental design and methodology for the first year of the R2R WATCH project.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Research, the manufacture of knowledge, is currently practiced largely as an “art,” not a “science.” Just as science (understanding) and technology (tools) have revolutionized the manufacture of other goods and services, it is natural, perhaps inevitable, that they will ultimately also be applied to the manufacture of knowledge. In this article, we present an emerging perspective on opportunities for such application, at three different levels of the research enterprise. At the cognitive science level of the individual researcher, opportunities include: overcoming idea fixation and sloppy thinking, and balancing divergent and convergent thinking. At the social network level of the research team, opportunities include: overcoming strong links and groupthink, and optimally distributing divergent and convergent thinking between individuals and teams. At the research ecosystem level of the research institution and the larger national and international community of researchers, opportunities include: overcoming performance fixation, overcoming narrow measures of research impact, and overcoming (or harnessing) existential/social stress.

Analysts across national security domains are required to sift through large amounts of data to find and compile relevant information in a form that enables decision makers to take action in high-consequence scenarios. However, even the most experienced analysts are unable to be 100 % consistent and accurate based on the entire dataset, unbiased towards familiar documentation, and are unable to synthesize and process large amounts of information in a small amount of time. Sandia National Laboratories has attempted to solve this problem by developing an intelligent web crawler called Huntsman. Huntsman acts as a personal research assistant by browsing the internet or offline datasets in a way similar to the human search process, only much faster (millions of documents per day), by submitting queries to search engines and assessing the usefulness of page results through analysis of full-page content with a suite of text analytics. This paper will discuss Huntsman’s capability to both mirror and enhance human analysts using intelligent web crawling with analysts-in-the-loop. The goal is to demonstrate how weaknesses in human cognitive processing can be compensated for by fusing human processes with text analytics and web crawling systems, which ultimately reduces analysts’ cognitive burden and increases mission effectiveness.