The independence and interdependence of coacting observers in regard to performance efficiency, workload, and stress in a vigilance task

Objective We investigated performance, workload, and stress in groups of paired observers who performed a vigilance task in a coactive (independent) manner. Background Previous studies have demonstrated that groups of coactive observers detect more signals in a vigilance task than observers working alone. Therefore, the use of such groups might be effective in enhancing signal detection in operational situations. However, concern over appearing less competent than one's cohort might induce elevated levels of workload and stress in coactive group members and thereby undermine group performance benefits. Accordingly, we performed the initial experiment comparing workload and stress in observers who performed a vigilance task coactively with those of observers who performed the vigilance task alone. Method Observers monitored a video display for collision flight paths in a simulated unmanned aerial vehicle control task. Self-reports of workload and stress were secured via the NASA-Task Load Index and the Dundee Stress State Questionnaire, respectively. Results Groups of coactive observers detected significantly more signals than did single observers. Coacting observers did not differ significantly from those operating by themselves in terms of workload but did in regard to stress; posttask distress was significantly lower for coacting than for single observers. Conclusion Performing a visual vigilance task in a coactive manner with another observer does not elevate workload above that of observers working alone and serves to attenuate the stress associated with vigilance task performance. Application The use of coacting observers could be an effective vehicle for enhancing performance efficiency in operational vigilance

China’s market economy, shadow banking and the frequency of growth slowdown

The activity of the Shadow Banks in China has been the subject of considerable interest in recent years. Total shadow banking lending has reached over 60% of GDP and has grown faster than regular bank lending. It has been argued that unregulated shadow banking has fuelled a credit boom that poses a risk to the stability of the financial system. This paper estimates a model of the Chinese economy using a DSGE framework that accommodates a banking sector that isolates the effects of lending to the private sector including shadow bank lending. A refinement of the model allows for bank lending including lending by the shadow banks to affect the credit premium on private investment. The main finding is that while financial shocks are significant, it is real shocks that dominate. The model is used to simulate the frequency of growth slowdowns in China and concludes that these are more likely to be driven by real sector shocks rather than financial sector, including shadow bank shocks. This paper differs from other applications in its use of indirect inference to test the fitted model against a threeequation VAR of inflation, output gap and interest rate

Initial sequencing and analysis of the human genome

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62798/1/409860a0.pd

Genetic assessment of additional endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study

The Consortium on the Genetics of Schizophrenia Family Study (COGS-1) has previously reported our efforts to characterize the genetic architecture of 12 primary endophenotypes for schizophrenia. We now report the characterization of 13 additional measures derived from the same endophenotype test paradigms in the COGS-1 families. Nine of the measures were found to discriminate between schizophrenia patients and controls, were significantly heritable (31 to 62%), and were sufficiently independent of previously assessed endophenotypes, demonstrating utility as additional endophenotypes. Genotyping via a custom array of 1536 SNPs from 94 candidate genes identified associations for CTNNA2, ERBB4, GRID1, GRID2, GRIK3, GRIK4, GRIN2B, NOS1AP, NRG1, and RELN across multiple endophenotypes. An experiment-wide p value of 0.003 suggested that the associations across all SNPs and endophenotypes collectively exceeded chance. Linkage analyses performed using a genome-wide SNP array further identified significant or suggestive linkage for six of the candidate endophenotypes, with several genes of interest located beneath the linkage peaks (e.g., CSMD1, DISC1, DLGAP2, GRIK2, GRIN3A, and SLC6A3). While the partial convergence of the association and linkage likely reflects differences in density of gene coverage provided by the distinct genotyping platforms, it is also likely an indication of the differential contribution of rare and common variants for some genes and methodological differences in detection ability. Still, many of the genes implicated by COGS through endophenotypes have been identified by independent studies of common, rare, and de novo variation in schizophrenia, all converging on a functional genetic network related to glutamatergic neurotransmission that warrants further investigation

A Coalition Study of Warfighter Acceptance of Wearable Physiological Sensors

Combat operations are often high tempo, resulting in undesirable levels of operator workload and stress. Adaptive automation has been suggested as a solution to these issues. However, this augmentation approach is predicated on operator consent to monitoring. Acceptance of such systems may be influenced by concerns regarding the use of monitor data and mistrust of automation technology. The purpose of the current investigation was to examine operator acceptance of physiological monitoring and future augmentation strategies after limited exposure to one device. During a simulated exercise, eleven command and control operators were equipped with a physiological monitor prior to each mission. Following the exercise, operators were surveyed regarding their acceptance of monitoring and several potential augmentation strategies. The results of the survey suggested that the operators were generally open to both monitoring and augmentation, but that they may also be insensitive to the limitations of current augmentation technology

Human Span-Of-Control in Cyber Operations: An Experimental Evaluation of Fan-Out

Modern cyber operations require operators to maintain supervisory control of remote computer agents. A current operational concern is the number of agents an operator can control at once. This issue resonates with similar “span-of-control” research conducted in UAV operations (e.g., Cummings & Mitchel, 2008). One way to identify operator span is via “fan-out,” a numeric calculation that provides a span-of-control estimate based on system and environmental variables. However, fan-out is a mechanical representation that only accounts for task-characteristics and environmental variables, thus providing an upper bound of human performance that does account for cognition, workload, or work interruptions. The present study compares fan-out estimates against actual human performance in a supervisory control cyber task. Results are discussed and future research trajectories proposed

Fractal Time Series Analysis of Human Heartbeat Intervals for Physical and Mental Workload

As the environments and tasks that teams (in both military and civilian settings) are faced with increase in complexity, standard statistical methods may not fully capture team dynamics and processes. Nonlinear analyses provide alternative, mathematically derived descriptions quantifying the level of complexity and variability inherent in a data set, and may provide a more accurate understanding of dynamic systems. The goal of the present study was to investigate changes in heart interbeat interval associated with task workload using one type of nonlinear analysis, power spectral density analysis. In this study, physical and mental workload were manipulated in separate tasks to explore the contributions of each to interbeat interval variability. Results indicated that spectral analysis can identify large changes in overall workload, but may be insensitive to small or medium changes. However, these conclusions are based on preliminary results; follow-up research is necessary to determine the veracity of these conclusions