An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload, which can result in impaired cognitive functioning and can be detrimental to job performance. For example, some professions (e.g., fire fighters, emergency medical personnel, doctors and nurses working in an emergency room, pilots) require long periods of low workload (boredom), followed by sudden, high-tempo operations during which they may be required to respond to an emergency and perform at peak cognitive levels. Conversely, other professions (e.g., air traffic controllers, market investors in financial industries, analysts) require long periods of high workload and multitasking during which the addition of just one more task results in cognitive overload resulting in mistakes. An unobtrusive system to measure, assess, and predict cognitive workload could warn individuals, their teammates, or their supervisors when steps should be taken to augment cognitive readiness. In this talk I will describe an approach to this problem that we have found to be successful across work domains including: (1) a suite of unobtrusive, field-ready neurophysiological, physiological, and behavioral sensors that are chosen to best suit the target environment; (2) custom algorithms and statistical techniques to process and time-align raw data originating from the sensor suite; (3) probabilistic and statistical models designed to interpret the data into the human state of interest (e.g., cognitive workload, attention, fatigue); (4) and machine-learning techniques to predict upcoming performance based on the current pattern of events, and (5) display of each piece of information depending on the needs of the target user who may or may not want to drill down into the functioning of the system to determine how conclusions about human state and performance are determined. I will then focus in on our experimental results from our custom functional near-infrared spectroscopy sensor, designed to operate in real-world environments to be worn comfortably (e.g., positioned into a baseball cap or a surgeons cap) to measure changes in brain blood oxygenation without adding burden to the individual being assessed

Staff understanding of recovery-orientated mental health practice: a systematic review and narrative synthesis

Background: Mental health policy is for staff to transform their practice towards a recovery orientation. Staff understanding of recovery-orientated practice will influence the implementation of this policy. The aim of this study was to conduct a systematic review and narrative synthesis of empirical studies identifying clinician and manager conceptualisations of recovery-orientated practice. Methods: A systematic review of empirical primary research was conducted. Data sources were online databases (n = 8), journal table of contents (n = 5), internet, expert consultation (n = 13), reference lists of included studies and references to included studies. Narrative synthesis was used to integrate the findings. Results: A total of 10,125 studies were screened, 245 full papers were retrieved, and 22 were included (participants, n = 1163). The following three conceptualisations of recovery-orientated practice were identified: clinical recovery, personal recovery and service-defined recovery. Service-defined recovery is a new conceptualisation which translates recovery into practice according to the goals and financial needs of the organisation. Conclusions: Organisational priorities influence staff understanding of recovery support. This influence is leading to the emergence of an additional meaning of recovery. The impact of service-led approaches to operationalising recovery-orientated practice has not been evaluated. Trial Registration: The protocol for the review was pre-registered (PROSPERO 2013: CRD42013005942)

Ubiquitin E3 Ligase Ring1b/Rnf2 of Polycomb Repressive Complex 1 Contributes to Stable Maintenance of Mouse Embryonic Stem Cells

Polycomb repressive complex 1 (PRC1) core member Ring1b/Rnf2, with ubiquitin E3 ligase activity towards histone H2A at lysine 119, is essential for early embryogenesis. To obtain more insight into the role of Ring1b in early development, we studied its function in mouse embryonic stem (ES) cells.We investigated the effects of Ring1b ablation on transcriptional regulation using Ring1b conditional knockout ES cells and large-scale gene expression analysis. The absence of Ring1b results in aberrant expression of key developmental genes and deregulation of specific differentiation-related pathways, including TGFbeta signaling, cell cycle regulation and cellular communication. Moreover, ES cell markers, including Zfp42/Rex-1 and Sox2, are downregulated. Importantly, retained expression of ES cell regulators Oct4, Nanog and alkaline phosphatase indicates that Ring1b-deficient ES cells retain important ES cell specific characteristics. Comparative analysis of our expression profiling data with previously published global binding studies shows that the genes that are bound by Ring1b in ES cells have bivalent histone marks, i.e. both active H3K4me3 and repressive H3K27me3, or the active H3K4me3 histone mark alone and are associated with CpG-'rich' promoters. However, deletion of Ring1b results in deregulation, mainly derepression, of only a subset of these genes, suggesting that additional silencing mechanisms are involved in repression of the other Ring1b bound genes in ES cells.Ring1b is essential to stably maintain an undifferentiated state of mouse ES cells by repressing genes with important roles during differentiation and development. These genes are characterized by high CpG content promoters and bivalent histone marks or the active H3K4me3 histone mark alone

Surface Ocean Dispersion Observations From the Ship-Tethered Aerostat Remote Sensing System

Oil slicks and sheens reside at the air-sea interface, a region of the ocean that is notoriously difficult to measure. Little is known about the velocity field at the sea surface in general, making predictions of oil dispersal difficult. The Ship-Tethered Aerostat Remote Sensing System (STARSS) was developed to measure Lagrangian velocities at the air-sea interface by tracking the transport and dispersion of bamboo dinner plates in the field of view of a high-resolution aerial imaging system. The camera had a field of view of approximately 300 × 200 m and images were obtained every 15 s over periods of up to 3 h. A series of experiments were conducted in the northern Gulf of Mexico in January-February 2016. STARSS was equipped with a GPS and inertial navigation system (INS) that was used to directly georectify the aerial images. A relative rectification technique was developed that translates and rotates the plates to minimize their total movement from one frame to the next. Rectified plate positions were used to quantify scale-dependent dispersion by computing relative dispersion, relative diffusivity, and velocity structure functions. STARSS was part of a nested observational framework, which included deployments of large numbers of GPS-tracked surface drifters from two ships, in situ ocean measurements, X-band radar observations of surface currents, and synoptic maps of sea surface temperature from a manned aircraft. Here we describe the STARSS system and image analysis techniques, and present results from an experiment that was conducted on a density front that was approximately 130 km offshore. These observations are the first of their kind and the methodology presented here can be adopted into existing and planned oceanographic campaigns to improve our understanding of small-scale and high-frequency variability at the air-sea interface and to provide much-needed benchmarks for numerical simulations